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| static_assert(K_QUANTS_PER_ITERATION == 1 || K_QUANTS_PER_ITERATION == 2, "K_QUANTS_PER_ITERATION must be 1 or 2"); | |
| struct ggml_backend_vk_context; | |
| struct vk_queue { | |
| uint32_t queue_family_index; | |
| vk::Queue queue; | |
| vk::CommandPool pool; | |
| uint32_t cmd_buffer_idx; | |
| std::vector<vk::CommandBuffer> cmd_buffers; | |
| vk::PipelineStageFlags stage_flags; | |
| }; | |
| struct vk_pipeline_struct { | |
| std::string name; | |
| vk::ShaderModule shader_module; | |
| vk::DescriptorSetLayout dsl; | |
| std::vector<vk::DescriptorPool> descriptor_pools; | |
| std::vector<vk::DescriptorSet> descriptor_sets; | |
| uint32_t descriptor_set_idx; | |
| vk::PipelineLayout layout; | |
| vk::Pipeline pipeline; | |
| uint32_t push_constant_size; | |
| uint32_t parameter_count; | |
| std::array<uint32_t, 3> wg_denoms; | |
| uint32_t align; | |
| }; | |
| typedef std::shared_ptr<vk_pipeline_struct> vk_pipeline; | |
| typedef std::weak_ptr<vk_pipeline_struct> vk_pipeline_ref; | |
| static void ggml_vk_destroy_pipeline(vk::Device& device, vk_pipeline& pipeline); | |
| struct vk_matmul_pipeline_struct { | |
| vk_pipeline l, m, s; | |
| vk_pipeline a_l, a_m, a_s; | |
| }; | |
| typedef std::shared_ptr<vk_matmul_pipeline_struct> vk_matmul_pipeline; | |
| struct vk_device { | |
| vk::PhysicalDevice physical_device; | |
| vk::PhysicalDeviceProperties properties; | |
| std::string name; | |
| uint64_t max_memory_allocation_size; | |
| bool fp16; | |
| vk::Device device; | |
| uint32_t vendor_id; | |
| vk_queue compute_queue; | |
| vk_queue transfer_queue; | |
| bool single_queue; | |
| uint32_t descriptor_set_mode; | |
| uint32_t subgroup_size; | |
| bool uma; | |
| bool initialized; | |
| size_t idx; | |
| vk_matmul_pipeline pipeline_matmul_f32; | |
| vk_matmul_pipeline pipeline_matmul_f16; | |
| vk_matmul_pipeline pipeline_matmul_f16_f32; | |
| vk_pipeline pipeline_matmul_split_k_reduce; | |
| vk_matmul_pipeline pipeline_dequant_mul_mat_mat[VK_NUM_TYPES]; | |
| vk_matmul_pipeline pipeline_matmul_id_f32; | |
| vk_matmul_pipeline pipeline_matmul_id_f16; | |
| vk_matmul_pipeline pipeline_matmul_id_f16_f32; | |
| vk_matmul_pipeline pipeline_dequant_mul_mat_mat_id[VK_NUM_TYPES]; | |
| vk_pipeline pipeline_dequant[VK_NUM_TYPES]; | |
| vk_pipeline pipeline_dequant_mul_mat_vec_f32_f32[VK_NUM_TYPES]; | |
| vk_pipeline pipeline_dequant_mul_mat_vec_f16_f32[VK_NUM_TYPES]; | |
| vk_pipeline pipeline_dequant_mul_mat_vec_id_f32[VK_NUM_TYPES]; | |
| vk_pipeline pipeline_mul_mat_vec_p021_f16_f32; | |
| vk_pipeline pipeline_mul_mat_vec_nc_f16_f32; | |
| vk_pipeline pipeline_get_rows[VK_NUM_TYPES]; | |
| vk_pipeline pipeline_get_rows_f32[VK_NUM_TYPES]; | |
| vk_pipeline pipeline_mul_f32; | |
| vk_pipeline pipeline_add_f32; | |
| vk_pipeline pipeline_scale_f32; | |
| vk_pipeline pipeline_sqr_f32; | |
| vk_pipeline pipeline_clamp_f32; | |
| vk_pipeline pipeline_cpy_f32_f32, pipeline_cpy_f32_f16, pipeline_cpy_f16_f16; | |
| vk_pipeline pipeline_norm_f32; | |
| vk_pipeline pipeline_rms_norm_f32; | |
| vk_pipeline pipeline_gelu_f32; | |
| vk_pipeline pipeline_silu_f32; | |
| vk_pipeline pipeline_relu_f32; | |
| vk_pipeline pipeline_diag_mask_inf_f32; | |
| vk_pipeline pipeline_soft_max_f32, pipeline_soft_max_f32_f16; | |
| vk_pipeline pipeline_rope_f32, pipeline_rope_f16; | |
| vk_pipeline pipeline_rope_neox_f32, pipeline_rope_neox_f16; | |
| vk_pipeline pipeline_argsort_f32; | |
| std::vector<vk_pipeline_ref> pipelines; | |
| ~vk_device() { | |
| std::cerr << "destroy device " << name << std::endl; | |
| device.destroyCommandPool(compute_queue.pool); | |
| if (!single_queue) { | |
| device.destroyCommandPool(transfer_queue.pool); | |
| } | |
| for (auto& pipeline : pipelines) { | |
| if (pipeline.expired()) { | |
| continue; | |
| } | |
| vk_pipeline pl = pipeline.lock(); | |
| ggml_vk_destroy_pipeline(device, pl); | |
| } | |
| pipelines.clear(); | |
| device.destroy(); | |
| } | |
| }; | |
| struct vk_buffer_struct { | |
| vk::Buffer buffer; | |
| vk::DeviceMemory device_memory; | |
| vk::MemoryPropertyFlags memory_property_flags; | |
| void * ptr; | |
| size_t size = 0; | |
| ggml_backend_vk_context * ctx; | |
| std::shared_ptr<vk_device> device; | |
| ~vk_buffer_struct() { | |
| if (size == 0) { | |
| return; | |
| } | |
| std::cerr << "~vk_buffer_struct(" << buffer << ", " << size << ")" << std::endl; | |
| device->device.freeMemory(device_memory); | |
| device->device.destroyBuffer(buffer); | |
| } | |
| }; | |
| typedef std::shared_ptr<vk_buffer_struct> vk_buffer; | |
| typedef std::weak_ptr<vk_buffer_struct> vk_buffer_ref; | |
| struct vk_subbuffer { | |
| vk_buffer buffer; | |
| uint64_t offset; | |
| uint64_t size; | |
| }; | |
| struct vk_semaphore { | |
| vk::Semaphore s; | |
| uint64_t value; | |
| }; | |
| struct vk_submission { | |
| vk::CommandBuffer buffer; | |
| std::vector<vk_semaphore> wait_semaphores; | |
| std::vector<vk_semaphore> signal_semaphores; | |
| }; | |
| typedef std::vector<vk_submission> vk_sequence; | |
| struct vk_mat_mat_push_constants { | |
| uint32_t M; uint32_t N; uint32_t K; | |
| uint32_t stride_a; uint32_t stride_b; uint32_t stride_d; uint32_t k_split; | |
| uint32_t ne02; uint32_t ne12; uint32_t broadcast2; uint32_t broadcast3; | |
| uint32_t batch_stride_a; uint32_t batch_stride_b; uint32_t batch_stride_d; | |
| uint32_t expert_stride_b; uint32_t expert_stride_d; | |
| uint32_t idx; uint32_t nbi1; uint32_t n_as; | |
| }; | |
| struct vk_mat_vec_push_constants { | |
| uint32_t ncols; uint32_t stride_a; uint32_t stride_b; uint32_t stride_d; | |
| uint32_t ne02; uint32_t ne12; uint32_t broadcast2; uint32_t broadcast3; | |
| uint32_t batch_stride_a; uint32_t batch_stride_b; uint32_t batch_stride_d; | |
| }; | |
| struct vk_op_push_constants { | |
| uint32_t KX; | |
| uint32_t KY; | |
| float param1; | |
| float param2; | |
| }; | |
| struct vk_op_unary_push_constants { | |
| uint32_t ne; | |
| uint32_t ne00; uint32_t ne01; uint32_t ne02; uint32_t ne03; uint32_t nb00; uint32_t nb01; uint32_t nb02; uint32_t nb03; | |
| uint32_t ne10; uint32_t ne11; uint32_t ne12; uint32_t ne13; uint32_t nb10; uint32_t nb11; uint32_t nb12; uint32_t nb13; | |
| uint32_t d_offset; | |
| float param1; float param2; | |
| }; | |
| struct vk_op_binary_push_constants { | |
| uint32_t ne; | |
| uint32_t ne00; uint32_t ne01; uint32_t ne02; uint32_t ne03; uint32_t nb00; uint32_t nb01; uint32_t nb02; uint32_t nb03; | |
| uint32_t ne10; uint32_t ne11; uint32_t ne12; uint32_t ne13; uint32_t nb10; uint32_t nb11; uint32_t nb12; uint32_t nb13; | |
| uint32_t ne20; uint32_t ne21; uint32_t ne22; uint32_t ne23; uint32_t nb20; uint32_t nb21; uint32_t nb22; uint32_t nb23; | |
| uint32_t d_offset; | |
| float param1; float param2; | |
| }; | |
| struct vk_op_diag_mask_push_constants { | |
| uint32_t ncols; | |
| uint32_t rows_per_channel; | |
| int32_t n_past; | |
| }; | |
| struct vk_op_rope_push_constants { | |
| uint32_t ncols; | |
| float freq_scale; | |
| uint32_t p_delta_rows; | |
| float freq_base; | |
| float ext_factor; | |
| float attn_factor; | |
| float corr_dims[4]; | |
| }; | |
| struct vk_op_rope_neox_push_constants { | |
| uint32_t ncols; | |
| uint32_t ndims; | |
| float freq_scale; | |
| uint32_t p_delta_rows; | |
| float freq_base; | |
| float ext_factor; | |
| float attn_factor; | |
| float corr_dims[4]; | |
| float theta_scale; | |
| float inv_ndims; | |
| }; | |
| struct vk_op_soft_max_push_constants { | |
| uint32_t KX; | |
| uint32_t KY; | |
| uint32_t KZ; | |
| float scale; | |
| float max_bias; | |
| float m0; | |
| float m1; | |
| uint32_t n_head_log2; | |
| }; | |
| struct vk_op_argsort_push_constants { | |
| uint32_t ncols; | |
| bool ascending; | |
| }; | |
| // Allow pre-recording command buffers | |
| struct vk_staging_memcpy { | |
| vk_staging_memcpy(void * _dst, const void * _src, size_t _n) : dst(_dst), src(_src), n(_n) {} | |
| void * dst; | |
| const void * src; | |
| size_t n; | |
| }; | |
| struct vk_context { | |
| size_t idx; | |
| vk_submission * s; | |
| std::vector<vk_sequence> seqs; | |
| ggml_tensor * exit_tensor; | |
| std::vector<vk_staging_memcpy> in_memcpys; | |
| std::vector<vk_staging_memcpy> out_memcpys; | |
| vk_queue * q; | |
| }; | |
| struct ggml_tensor_extra_gpu { | |
| bool ready; | |
| size_t ctx_idx; | |
| vk_buffer_ref buffer_gpu; | |
| uint64_t offset; | |
| void reset() { | |
| ready = false; | |
| ctx_idx = 0; | |
| buffer_gpu.reset(); | |
| offset = 0; | |
| } | |
| }; | |
| struct ggml_vk_garbage_collector { | |
| std::vector<vk_semaphore> tl_semaphores; | |
| std::vector<vk_semaphore> semaphores; | |
| std::vector<vk::Event> events; | |
| std::vector<vk_buffer> temp_buffers; | |
| std::vector<vk_context> contexts; | |
| }; | |
| struct ggml_backend_vk_context { | |
| std::string name; | |
| std::shared_ptr<vk_device> device; | |
| size_t semaphore_idx, event_idx; | |
| ggml_vk_garbage_collector gc; | |
| std::vector<std::tuple<void*, size_t, vk_buffer>> pinned_memory; | |
| size_t prealloc_size_x, prealloc_size_y, prealloc_size_split_k; | |
| vk_buffer prealloc_x, prealloc_y, prealloc_split_k; | |
| vk::Fence fence; | |
| vk_buffer staging; | |
| size_t staging_size; | |
| size_t staging_offset; | |
| vk_buffer sync_staging; | |
| vk_buffer buffer_pool[MAX_VK_BUFFERS]; | |
| vk_context * compute_ctx; | |
| vk_context * transfer_ctx; | |
| bool disable; | |
| bool initialized; | |
| size_t idx; | |
| }; | |
| struct vk_instance { | |
| vk::Instance instance; | |
| std::vector<size_t> device_indices; | |
| ggml_backend_t backends[GGML_VK_MAX_DEVICES]; | |
| ggml_backend_vk_context contexts[GGML_VK_MAX_DEVICES]; | |
| ggml_backend_buffer_type buffer_types[GGML_VK_MAX_DEVICES]; | |
| bool initialized[GGML_VK_MAX_DEVICES]; | |
| }; | |
| static std::shared_ptr<vk_device> ggml_vk_get_device(size_t idx) { | |
| std::cerr << "ggml_vk_get_device(" << idx << ")" << std::endl; | |
| static std::weak_ptr<vk_device> devices[GGML_VK_MAX_DEVICES]; | |
| if (devices[idx].expired()) { | |
| std::cerr << "Initializing new vk_device" << std::endl; | |
| std::shared_ptr<vk_device> device = std::make_shared<vk_device>(); | |
| device->initialized = false; | |
| devices[idx] = device; | |
| return device; | |
| } | |
| return devices[idx].lock(); | |
| } | |
| static size_t vk_skip_checks; | |
| static size_t vk_output_tensor; | |
| static void ggml_vk_print_tensor(ggml_backend * ctx, const ggml_tensor * tensor, const char * name); | |
| static void ggml_vk_check_results_0(ggml_backend_vk_context * ctx, ggml_compute_params * params, ggml_tensor * tensor); | |
| static void ggml_vk_check_results_1(ggml_backend_vk_context * ctx, ggml_compute_params * params, ggml_tensor * tensor); | |
| typedef void (*ggml_vk_func_t)(ggml_backend_vk_context * ctx, vk_context * subctx, const ggml_tensor * src0, const ggml_tensor * src1, ggml_tensor * dst); | |
| static bool vk_instance_initialized = false; | |
| static vk_instance vk_instance; | |
| GGML_CALL static void ggml_backend_vk_free(ggml_backend_t backend); | |
| static void ggml_vk_create_pipeline(ggml_backend_vk_context * ctx, vk_pipeline& pipeline, const std::string& name, size_t spv_size, const void* spv_data, const std::string& entrypoint, uint32_t parameter_count, uint32_t push_constant_size, std::array<uint32_t, 3> wg_denoms, std::vector<uint32_t>&& specialization_constants, uint32_t align) { | |
| std::cerr << "ggml_vk_create_pipeline(" << name << ", " << entrypoint << ", " << parameter_count << ", " << push_constant_size << ", (" << wg_denoms[0] << "," << wg_denoms[1] << "," << wg_denoms[2] << "), specialization_constants, " << align << ")" << std::endl; | |
| GGML_ASSERT(parameter_count > 0); | |
| GGML_ASSERT(wg_denoms[0] > 0 && wg_denoms[1] > 0 && wg_denoms[2] > 0); // NOLINT | |
| pipeline = std::make_shared<vk_pipeline_struct>(); | |
| pipeline->name = name; | |
| pipeline->parameter_count = parameter_count; | |
| pipeline->push_constant_size = push_constant_size; | |
| pipeline->wg_denoms = wg_denoms; | |
| pipeline->align = align; | |
| vk::ShaderModuleCreateInfo shader_module_create_info({}, spv_size, reinterpret_cast<const uint32_t *>(spv_data)); | |
| pipeline->shader_module = ctx->device->device.createShaderModule(shader_module_create_info); | |
| std::vector<vk::DescriptorSetLayoutBinding> dsl_binding; | |
| std::vector<vk::DescriptorBindingFlags> dsl_binding_flags; | |
| for (uint32_t i = 0; i < parameter_count; i++) { | |
| dsl_binding.push_back({i, vk::DescriptorType::eStorageBuffer, 1, vk::ShaderStageFlagBits::eCompute}); | |
| dsl_binding_flags.push_back({}); | |
| } | |
| vk::DescriptorSetLayoutBindingFlagsCreateInfo dslbfci = { dsl_binding_flags }; | |
| vk::PushConstantRange pcr( | |
| vk::ShaderStageFlagBits::eCompute, | |
| 0, | |
| pipeline->push_constant_size | |
| ); | |
| vk::DescriptorSetLayoutCreateInfo descriptor_set_layout_create_info( | |
| {}, | |
| dsl_binding); | |
| descriptor_set_layout_create_info.setPNext(&dslbfci); | |
| pipeline->dsl = ctx->device->device.createDescriptorSetLayout(descriptor_set_layout_create_info); | |
| // Check if device supports multiple descriptors per pool | |
| if (ctx->device->descriptor_set_mode == VK_DEVICE_DESCRIPTOR_POOL_MODE_UNKNOWN) { | |
| const uint32_t alloc_count = 2; | |
| // Try allocating multiple sets from one pool | |
| // This fails on AMD for some reason, so add a fall back to allocating one pool per set | |
| vk::DescriptorPoolSize descriptor_pool_size(vk::DescriptorType::eStorageBuffer, pipeline->parameter_count); | |
| vk::DescriptorPoolCreateInfo descriptor_pool_create_info({}, alloc_count, descriptor_pool_size); | |
| vk::DescriptorPool pool = ctx->device->device.createDescriptorPool(descriptor_pool_create_info); | |
| std::vector<vk::DescriptorSetLayout> layouts(alloc_count); | |
| for (uint32_t i = 0; i < alloc_count; i++) { | |
| layouts[i] = pipeline->dsl; | |
| } | |
| try { | |
| vk::DescriptorSetAllocateInfo descriptor_set_alloc_info(pool, alloc_count, layouts.data()); | |
| std::vector<vk::DescriptorSet> sets = ctx->device->device.allocateDescriptorSets(descriptor_set_alloc_info); | |
| } catch(vk::OutOfPoolMemoryError const&) { | |
| ctx->device->descriptor_set_mode = VK_DEVICE_DESCRIPTOR_POOL_MODE_SINGLE; | |
| } | |
| ctx->device->device.destroyDescriptorPool(pool); | |
| } | |
| if (ctx->device->descriptor_set_mode == VK_DEVICE_DESCRIPTOR_POOL_MODE_MULTI) { | |
| vk::DescriptorPoolSize descriptor_pool_size(vk::DescriptorType::eStorageBuffer, pipeline->parameter_count); | |
| vk::DescriptorPoolCreateInfo descriptor_pool_create_info({}, 128, descriptor_pool_size); | |
| pipeline->descriptor_pools.push_back(ctx->device->device.createDescriptorPool(descriptor_pool_create_info)); | |
| } | |
| pipeline->descriptor_set_idx = 0; | |
| vk::PipelineLayoutCreateInfo pipeline_layout_create_info(vk::PipelineLayoutCreateFlags(), pipeline->dsl, pcr); | |
| pipeline->layout = ctx->device->device.createPipelineLayout(pipeline_layout_create_info); | |
| std::vector<vk::SpecializationMapEntry> specialization_entries(specialization_constants.size()); | |
| for (size_t i = 0; i < specialization_constants.size(); i++) { | |
| specialization_entries[i].constantID = i; | |
| specialization_entries[i].offset = i * sizeof(uint32_t); | |
| specialization_entries[i].size = sizeof(uint32_t); | |
| } | |
| vk::SpecializationInfo specialization_info( | |
| specialization_entries.size(), | |
| specialization_entries.data(), | |
| specialization_constants.size() * sizeof(uint32_t), | |
| specialization_constants.data() | |
| ); | |
| vk::PipelineShaderStageCreateInfo pipeline_shader_create_info( | |
| vk::PipelineShaderStageCreateFlags(), | |
| vk::ShaderStageFlagBits::eCompute, | |
| pipeline->shader_module, | |
| entrypoint.c_str(), | |
| &specialization_info); | |
| vk::ComputePipelineCreateInfo compute_pipeline_create_info( | |
| vk::PipelineCreateFlags(), | |
| pipeline_shader_create_info, | |
| pipeline->layout); | |
| pipeline->pipeline = ctx->device->device.createComputePipeline(VK_NULL_HANDLE, compute_pipeline_create_info).value; | |
| ctx->device->pipelines.push_back(pipeline); | |
| } | |
| static void ggml_vk_destroy_pipeline(vk::Device& device, vk_pipeline& pipeline) { | |
| std::cerr << "ggml_pipeline_destroy_pipeline(" << pipeline->name << ")" << std::endl; | |
| for (auto& pool : pipeline->descriptor_pools) { | |
| device.destroyDescriptorPool(pool); | |
| } | |
| pipeline->descriptor_pools.clear(); | |
| pipeline->descriptor_sets.clear(); | |
| pipeline->descriptor_set_idx = 0; | |
| device.destroyDescriptorSetLayout(pipeline->dsl); | |
| device.destroyPipelineLayout(pipeline->layout); | |
| device.destroyShaderModule(pipeline->shader_module); | |
| device.destroyPipeline(pipeline->pipeline); | |
| } | |
| static void ggml_pipeline_allocate_descriptor_sets(ggml_backend_vk_context * ctx, vk_pipeline& pipeline, uint32_t n) { | |
| std::cerr << "ggml_pipeline_allocate_descriptor_sets(" << pipeline->name << ", " << n << ")" << std::endl; | |
| if (pipeline->descriptor_sets.size() >= pipeline->descriptor_set_idx + n) { | |
| // Enough descriptors are available | |
| return; | |
| } | |
| if (ctx->device->descriptor_set_mode == VK_DEVICE_DESCRIPTOR_POOL_MODE_MULTI) { | |
| const uint32_t alloc_count = pipeline->descriptor_set_idx + n - pipeline->descriptor_sets.size(); | |
| std::vector<vk::DescriptorSetLayout> layouts(alloc_count); | |
| for (uint32_t i = 0; i < alloc_count; i++) { | |
| layouts[i] = pipeline->dsl; | |
| } | |
| vk::DescriptorSetAllocateInfo descriptor_set_alloc_info(pipeline->descriptor_pools[0], alloc_count, layouts.data()); | |
| std::vector<vk::DescriptorSet> sets = ctx->device->device.allocateDescriptorSets(descriptor_set_alloc_info); | |
| pipeline->descriptor_sets.insert(pipeline->descriptor_sets.end(), sets.begin(), sets.end()); | |
| } else { | |
| for (uint32_t i = pipeline->descriptor_sets.size(); i < pipeline->descriptor_set_idx + n; i++) { | |
| vk::DescriptorPoolSize descriptor_pool_size(vk::DescriptorType::eStorageBuffer, pipeline->parameter_count); | |
| vk::DescriptorPoolCreateInfo descriptor_pool_create_info({}, 1, descriptor_pool_size); | |
| pipeline->descriptor_pools.push_back(ctx->device->device.createDescriptorPool(descriptor_pool_create_info)); | |
| vk::DescriptorSetAllocateInfo descriptor_set_alloc_info(pipeline->descriptor_pools[i], 1, &pipeline->dsl); | |
| std::vector<vk::DescriptorSet> sets = ctx->device->device.allocateDescriptorSets(descriptor_set_alloc_info); | |
| pipeline->descriptor_sets.push_back(sets[0]); | |
| } | |
| } | |
| } | |
| static void ggml_pipeline_cleanup(vk_pipeline& pipeline) { | |
| std::cerr << "ggml_pipeline_cleanup(" << pipeline->name << ")" << std::endl; | |
| pipeline->descriptor_set_idx = 0; | |
| } | |
| static vk::CommandBuffer ggml_vk_create_cmd_buffer(ggml_backend_vk_context * ctx, vk_queue& q) { | |
| std::cerr << "ggml_vk_create_cmd_buffer()" << std::endl; | |
| if (q.cmd_buffers.size() > q.cmd_buffer_idx) { | |
| // Reuse command buffer | |
| return q.cmd_buffers[q.cmd_buffer_idx++]; | |
| } | |
| vk::CommandBufferAllocateInfo command_buffer_alloc_info( | |
| q.pool, | |
| vk::CommandBufferLevel::ePrimary, | |
| 1); | |
| const std::vector<vk::CommandBuffer> cmd_buffers = ctx->device->device.allocateCommandBuffers(command_buffer_alloc_info); | |
| auto buf = cmd_buffers.front(); | |
| q.cmd_buffers.push_back(buf); | |
| q.cmd_buffer_idx++; | |
| return buf; | |
| } | |
| static vk_submission ggml_vk_create_submission(ggml_backend_vk_context * ctx, vk_queue& q, std::vector<vk_semaphore> wait_semaphores, std::vector<vk_semaphore> signal_semaphores) { | |
| std::cerr << "ggml_vk_create_submission()" << std::endl; | |
| vk_submission s; | |
| s.buffer = ggml_vk_create_cmd_buffer(ctx, q); | |
| s.wait_semaphores = std::move(wait_semaphores); | |
| s.signal_semaphores = std::move(signal_semaphores); | |
| return s; | |
| } | |
| static void ggml_vk_submit(vk_context * ctx, vk::Fence fence) { | |
| std::cerr << "ggml_vk_submit(" << ctx->seqs.size() << ", " << fence << ")" << std::endl; | |
| if (ctx->seqs.empty()) { | |
| return; | |
| } | |
| std::vector<std::vector<uint64_t>> tl_wait_vals; | |
| std::vector<std::vector<uint64_t>> tl_signal_vals; | |
| std::vector<std::vector<vk::Semaphore>> tl_wait_semaphores; | |
| std::vector<std::vector<vk::Semaphore>> tl_signal_semaphores; | |
| std::vector<vk::TimelineSemaphoreSubmitInfo> tl_submit_infos; | |
| std::vector<vk::SubmitInfo> submit_infos; | |
| int idx = -1; | |
| std::vector<std::vector<vk::PipelineStageFlags>> stage_flags; | |
| size_t reserve = 0; | |
| for (const auto& sequence : ctx->seqs) { | |
| reserve += sequence.size(); | |
| } | |
| // Pre-reserve vectors to prevent reallocation, which invalidates pointers | |
| tl_wait_semaphores.reserve(reserve); | |
| tl_wait_vals.reserve(reserve); | |
| tl_signal_semaphores.reserve(reserve); | |
| tl_signal_vals.reserve(reserve); | |
| tl_submit_infos.reserve(reserve); | |
| submit_infos.reserve(reserve); | |
| stage_flags.reserve(reserve); | |
| for (const auto& sequence : ctx->seqs) { | |
| for (const auto& submission : sequence) { | |
| stage_flags.push_back({}); | |
| idx++; | |
| tl_wait_vals.push_back({}); | |
| tl_wait_semaphores.push_back({}); | |
| tl_signal_vals.push_back({}); | |
| tl_signal_semaphores.push_back({}); | |
| for (size_t i = 0; i < submission.wait_semaphores.size(); i++) { | |
| stage_flags[idx].push_back(ctx->q->stage_flags); | |
| tl_wait_vals[idx].push_back(submission.wait_semaphores[i].value); | |
| tl_wait_semaphores[idx].push_back(submission.wait_semaphores[i].s); | |
| } | |
| for (size_t i = 0; i < submission.signal_semaphores.size(); i++) { | |
| tl_signal_vals[idx].push_back(submission.signal_semaphores[i].value); | |
| tl_signal_semaphores[idx].push_back(submission.signal_semaphores[i].s); | |
| } | |
| tl_submit_infos.push_back({ | |
| (uint32_t) submission.wait_semaphores.size(), | |
| tl_wait_vals[idx].data(), | |
| (uint32_t) submission.signal_semaphores.size(), | |
| tl_signal_vals[idx].data(), | |
| }); | |
| tl_submit_infos[idx].sType = vk::StructureType::eTimelineSemaphoreSubmitInfo; | |
| tl_submit_infos[idx].pNext = nullptr; | |
| vk::SubmitInfo si{ | |
| (uint32_t) submission.wait_semaphores.size(), | |
| tl_wait_semaphores[idx].data(), | |
| stage_flags[idx].data(), | |
| 1, | |
| &submission.buffer, | |
| (uint32_t) submission.signal_semaphores.size(), | |
| tl_signal_semaphores[idx].data(), | |
| }; | |
| si.setPNext(&tl_submit_infos[idx]); | |
| submit_infos.push_back(si); | |
| } | |
| } | |
| ctx->q->queue.submit(submit_infos, fence); | |
| ctx->seqs.clear(); | |
| } | |
| static uint32_t ggml_vk_find_queue_family_index(std::vector<vk::QueueFamilyProperties>& queue_family_props, const vk::QueueFlags& required, const vk::QueueFlags& avoid, int32_t compute_index, uint32_t min_num_queues) { | |
| std::cerr << "ggml_vk_find_queue_family_index()" << std::endl; | |
| const uint32_t qfsize = queue_family_props.size(); | |
| // Try with avoid preferences first | |
| for (uint32_t i = 0; i < qfsize; i++) { | |
| if (queue_family_props[i].queueCount >= min_num_queues && (compute_index < 0 || i != (uint32_t) compute_index) && queue_family_props[i].queueFlags & required && !(queue_family_props[i].queueFlags & avoid)) { | |
| return i; | |
| } | |
| } | |
| // Fall back to only required | |
| for (size_t i = 0; i < qfsize; i++) { | |
| if (queue_family_props[i].queueCount >= min_num_queues && (compute_index < 0 || i != (uint32_t) compute_index) && queue_family_props[i].queueFlags & required) { | |
| return i; | |
| } | |
| } | |
| // Fall back to reusing compute queue | |
| for (size_t i = 0; i < qfsize; i++) { | |
| if (queue_family_props[i].queueCount >= min_num_queues && queue_family_props[i].queueFlags & required) { | |
| return i; | |
| } | |
| } | |
| // Fall back to ignoring min_num_queries | |
| for (size_t i = 0; i < qfsize; i++) { | |
| if (queue_family_props[i].queueFlags & required) { | |
| return i; | |
| } | |
| } | |
| // All commands that are allowed on a queue that supports transfer operations are also allowed on a queue that supports either graphics or compute operations. | |
| // Thus, if the capabilities of a queue family include VK_QUEUE_GRAPHICS_BIT or VK_QUEUE_COMPUTE_BIT, then reporting the VK_QUEUE_TRANSFER_BIT capability separately for that queue family is optional. | |
| if (compute_index >= 0) { | |
| return compute_index; | |
| } | |
| std::cerr << "ggml_vulkan: No suitable queue family index found." << std::endl; | |
| for(auto &q_family : queue_family_props) { | |
| std::cerr << "Queue number: " + std::to_string(q_family.queueCount) << " flags: " + to_string(q_family.queueFlags) << std::endl; | |
| } | |
| abort(); | |
| } | |
| static void ggml_vk_create_queue(ggml_backend_vk_context * ctx, vk_queue& q, uint32_t queue_family_index, uint32_t queue_index, vk::PipelineStageFlags&& stage_flags) { | |
| std::cerr << "ggml_vk_create_queue()" << std::endl; | |
| q.queue_family_index = queue_family_index; | |
| vk::CommandPoolCreateInfo command_pool_create_info_compute(vk::CommandPoolCreateFlags(VK_COMMAND_POOL_CREATE_TRANSIENT_BIT), queue_family_index); | |
| q.pool = ctx->device->device.createCommandPool(command_pool_create_info_compute); | |
| q.cmd_buffer_idx = 0; | |
| q.queue = ctx->device->device.getQueue(queue_family_index, queue_index); | |
| q.stage_flags = stage_flags; | |
| } | |
| static vk_context * ggml_vk_create_context(ggml_backend_vk_context * ctx, vk_queue& q) { | |
| std::cerr << "ggml_vk_create_context()" << std::endl; | |
| ctx->gc.contexts.emplace_back(); | |
| vk_context * result = &ctx->gc.contexts[ctx->gc.contexts.size() - 1]; | |
| memset((void *) result, 0, sizeof(vk_context)); | |
| result->idx = ctx->gc.contexts.size() - 1; | |
| result->q = &q; | |
| return result; | |
| } | |
| static vk_semaphore * ggml_vk_create_binary_semaphore(ggml_backend_vk_context * ctx) { | |
| std::cerr << "ggml_vk_create_timeline_semaphore()" << std::endl; | |
| vk::SemaphoreTypeCreateInfo tci{ vk::SemaphoreType::eBinary, 0 }; | |
| vk::SemaphoreCreateInfo ci{}; | |
| ci.setPNext(&tci); | |
| vk::Semaphore semaphore = ctx->device->device.createSemaphore(ci); | |
| ctx->gc.semaphores.push_back({ semaphore, 0 }); | |
| return &ctx->gc.semaphores[ctx->gc.semaphores.size() - 1]; | |
| } | |
| static vk_semaphore * ggml_vk_create_timeline_semaphore(ggml_backend_vk_context * ctx) { | |
| std::cerr << "ggml_vk_create_timeline_semaphore()" << std::endl; | |
| if (ctx->semaphore_idx >= ctx->gc.tl_semaphores.size()) { | |
| vk::SemaphoreTypeCreateInfo tci{ vk::SemaphoreType::eTimeline, 0 }; | |
| vk::SemaphoreCreateInfo ci{}; | |
| ci.setPNext(&tci); | |
| vk::Semaphore semaphore = ctx->device->device.createSemaphore(ci); | |
| ctx->gc.tl_semaphores.push_back({ semaphore, 0 }); | |
| } | |
| return &ctx->gc.tl_semaphores[ctx->semaphore_idx++]; | |
| } | |
| static vk::Event ggml_vk_create_event(ggml_backend_vk_context * ctx) { | |
| if (ctx->event_idx >= ctx->gc.events.size()) { | |
| ctx->gc.events.push_back(ctx->device->device.createEvent({})); | |
| } | |
| return ctx->gc.events[ctx->event_idx++]; | |
| } | |
| static void ggml_vk_queue_cleanup(ggml_backend_vk_context * ctx, vk_queue& q) { | |
| std::cerr << "ggml_vk_queue_cleanup()" << std::endl; | |
| // Requires command buffers to be done | |
| ctx->device->device.resetCommandPool(q.pool); | |
| q.cmd_buffer_idx = 0; | |
| } | |
| static uint32_t find_properties(const vk::PhysicalDeviceMemoryProperties* mem_props, vk::MemoryRequirements* mem_req, vk::MemoryPropertyFlags flags) { | |
| for (uint32_t i = 0; i < mem_props->memoryTypeCount; ++i) { | |
| vk::MemoryType memory_type = mem_props->memoryTypes[i]; | |
| if ((mem_req->memoryTypeBits & ((uint64_t)1 << i)) && | |
| (flags & memory_type.propertyFlags) == flags && | |
| mem_props->memoryHeaps[memory_type.heapIndex].size >= mem_req->size) { | |
| return static_cast<int32_t>(i); | |
| } | |
| } | |
| return UINT32_MAX; | |
| } | |
| static vk_buffer ggml_vk_create_buffer(ggml_backend_vk_context * ctx, size_t size, vk::MemoryPropertyFlags req_flags, vk::MemoryPropertyFlags fallback_flags = vk::MemoryPropertyFlags(0)) { | |
| std::cerr << "ggml_vk_create_buffer(device " << ctx->idx << ", " << size << ", " << to_string(req_flags) << ", " << to_string(fallback_flags) << ")" << std::endl; | |
| vk_buffer buf = std::make_shared<vk_buffer_struct>(); | |
| if (size == 0) { | |
| buf->size = 0; | |
| return buf; | |
| } | |
| buf->size = size; | |
| vk::BufferCreateInfo buffer_create_info{ | |
| vk::BufferCreateFlags(), | |
| size, | |
| vk::BufferUsageFlagBits::eStorageBuffer | vk::BufferUsageFlagBits::eTransferSrc | vk::BufferUsageFlagBits::eTransferDst, | |
| vk::SharingMode::eExclusive, | |
| 0, | |
| nullptr, | |
| }; | |
| buf->buffer = ctx->device->device.createBuffer(buffer_create_info); | |
| vk::MemoryRequirements mem_req = ctx->device->device.getBufferMemoryRequirements(buf->buffer); | |
| vk::PhysicalDeviceMemoryProperties mem_props = ctx->device->physical_device.getMemoryProperties(); | |
| uint32_t memory_type_index = UINT32_MAX; | |
| memory_type_index = find_properties(&mem_props, &mem_req, req_flags); | |
| buf->memory_property_flags = req_flags; | |
| if (memory_type_index == UINT32_MAX && fallback_flags) { | |
| memory_type_index = find_properties(&mem_props, &mem_req, fallback_flags); | |
| buf->memory_property_flags = fallback_flags; | |
| } | |
| if (memory_type_index == UINT32_MAX) { | |
| ctx->device->device.destroyBuffer(buf->buffer); | |
| buf->size = 0; | |
| throw vk::OutOfDeviceMemoryError("No suitable memory type found"); | |
| } | |
| try { | |
| buf->device_memory = ctx->device->device.allocateMemory({ mem_req.size, memory_type_index }); | |
| } catch (const vk::SystemError& e) { | |
| // Out of Host/Device memory, clean up buffer | |
| ctx->device->device.destroyBuffer(buf->buffer); | |
| buf->size = 0; | |
| throw e; | |
| } | |
| buf->ptr = nullptr; | |
| if (buf->memory_property_flags & vk::MemoryPropertyFlagBits::eHostVisible) { | |
| buf->ptr = ctx->device->device.mapMemory(buf->device_memory, 0, VK_WHOLE_SIZE); | |
| } | |
| ctx->device->device.bindBufferMemory(buf->buffer, buf->device_memory, 0); | |
| buf->ctx = ctx; | |
| buf->device = ctx->device; | |
| std::cerr << "Created buffer " << buf->buffer << std::endl; | |
| return buf; | |
| } | |
| static vk_buffer ggml_vk_create_buffer_check(ggml_backend_vk_context * ctx, size_t size, vk::MemoryPropertyFlags req_flags, vk::MemoryPropertyFlags fallback_flags = vk::MemoryPropertyFlags(0)) { | |
| try { | |
| return ggml_vk_create_buffer(ctx, size, req_flags, fallback_flags); | |
| } catch (const vk::SystemError& e) { | |
| std::cerr << "ggml_vulkan: Memory allocation of size " << size << " failed." << std::endl; | |
| std::cerr << "ggml_vulkan: " << e.what() << std::endl; | |
| throw e; | |
| } | |
| } | |
| static vk_buffer ggml_vk_create_buffer_device(ggml_backend_vk_context * ctx, size_t size) { | |
| vk_buffer buf; | |
| try { | |
| if (ctx->device->uma) { | |
| // Fall back to host memory type | |
| buf = ggml_vk_create_buffer(ctx, size, vk::MemoryPropertyFlagBits::eDeviceLocal, vk::MemoryPropertyFlagBits::eHostVisible | vk::MemoryPropertyFlagBits::eHostCoherent); | |
| } else { | |
| buf = ggml_vk_create_buffer(ctx, size, vk::MemoryPropertyFlagBits::eDeviceLocal); | |
| } | |
| } catch (const vk::SystemError& e) { | |
| std::cerr << "ggml_vulkan: Device memory allocation of size " << size << " failed." << std::endl; | |
| std::cerr << "ggml_vulkan: " << e.what() << std::endl; | |
| throw e; | |
| } | |
| return buf; | |
| } | |
| static void ggml_vk_destroy_buffer(vk_buffer& buf) { | |
| buf.reset(); | |
| } | |
| static vk_subbuffer ggml_vk_subbuffer(vk_buffer& buf) { | |
| return { buf, 0, VK_WHOLE_SIZE }; | |
| } | |
| static void ggml_vk_sync_buffers(vk_context * ctx) { | |
| std::cerr << "ggml_vk_sync_buffers()" << std::endl; | |
| const std::vector<vk::MemoryBarrier> mem_barriers{ { { vk::AccessFlagBits::eMemoryRead | vk::AccessFlagBits::eMemoryWrite }, { vk::AccessFlagBits::eMemoryRead | vk::AccessFlagBits::eMemoryWrite } } }; | |
| ctx->s->buffer.pipelineBarrier( | |
| ctx->q->stage_flags, | |
| ctx->q->stage_flags, | |
| {}, | |
| mem_barriers, | |
| {}, | |
| {} | |
| ); | |
| } | |
| static void ggml_vk_wait_events(vk_context * ctx, std::vector<vk::Event>&& events) { | |
| std::cerr << "ggml_vk_wait_events()" << std::endl; | |
| if (events.empty()) { | |
| return; | |
| } | |
| ctx->s->buffer.waitEvents( | |
| events, | |
| ctx->q->stage_flags, | |
| ctx->q->stage_flags, | |
| {}, | |
| {}, | |
| {} | |
| ); | |
| } | |
| static bool ggml_vk_build_shader(ggml_type type) { | |
| switch(type) { | |
| case GGML_TYPE_F16: | |
| case GGML_TYPE_Q4_0: | |
| case GGML_TYPE_Q4_1: | |
| case GGML_TYPE_Q5_0: | |
| case GGML_TYPE_Q5_1: | |
| case GGML_TYPE_Q8_0: | |
| case GGML_TYPE_Q2_K: | |
| case GGML_TYPE_Q3_K: | |
| case GGML_TYPE_Q4_K: | |
| case GGML_TYPE_Q5_K: | |
| case GGML_TYPE_Q6_K: | |
| return true; | |
| default: | |
| return false; | |
| } | |
| } | |
| static void ggml_vk_load_shaders(ggml_backend_vk_context * ctx) { | |
| std::cerr << "ggml_vk_load_shaders(" << ctx->name << ")" << std::endl; | |
| const std::shared_ptr<vk_device> device = ctx->device; | |
| // mulmat | |
| std::initializer_list<uint32_t> warptile_l = { 128, 128, 128, 16, device->subgroup_size * 2, 64, 2, 4, 4, device->subgroup_size }; | |
| std::initializer_list<uint32_t> warptile_m = { 128, 64, 64, 16, device->subgroup_size, 32, 2, 4, 2, device->subgroup_size }; | |
| std::initializer_list<uint32_t> warptile_s = { device->subgroup_size, 32, 32, 16, 32, 32, 2, 2, 2, device->subgroup_size }; | |
| std::initializer_list<uint32_t> warptile_mmq_l = { 128, 128, 128, 32, device->subgroup_size * 2, 64, 2, 4, 4, device->subgroup_size }; | |
| std::initializer_list<uint32_t> warptile_mmq_m = { 128, 64, 64, 32, device->subgroup_size, 32, 2, 4, 2, device->subgroup_size }; | |
| std::initializer_list<uint32_t> warptile_mmq_s = { device->subgroup_size, 32, 32, 32, 32, 32, 2, 2, 2, device->subgroup_size }; | |
| std::array<uint32_t, 3> l_wg_denoms = {128, 128, 1 }; | |
| std::array<uint32_t, 3> m_wg_denoms = { 64, 64, 1 }; | |
| std::array<uint32_t, 3> s_wg_denoms = { 32, 32, 1 }; | |
| uint32_t l_align = 128; | |
| uint32_t m_align = 64; | |
| uint32_t s_align = 32; | |
| ctx->device->pipeline_matmul_f32 = std::make_shared<vk_matmul_pipeline_struct>(); | |
| ctx->device->pipeline_matmul_f16_f32 = std::make_shared<vk_matmul_pipeline_struct>(); | |
| ctx->device->pipeline_matmul_f16 = std::make_shared<vk_matmul_pipeline_struct>(); | |
| ctx->device->pipeline_dequant_mul_mat_mat[GGML_TYPE_Q4_0] = std::make_shared<vk_matmul_pipeline_struct>(); | |
| ctx->device->pipeline_dequant_mul_mat_mat[GGML_TYPE_Q4_1] = std::make_shared<vk_matmul_pipeline_struct>(); | |
| ctx->device->pipeline_dequant_mul_mat_mat[GGML_TYPE_Q5_0] = std::make_shared<vk_matmul_pipeline_struct>(); | |
| ctx->device->pipeline_dequant_mul_mat_mat[GGML_TYPE_Q5_1] = std::make_shared<vk_matmul_pipeline_struct>(); | |
| ctx->device->pipeline_dequant_mul_mat_mat[GGML_TYPE_Q8_0] = std::make_shared<vk_matmul_pipeline_struct>(); | |
| ctx->device->pipeline_dequant_mul_mat_mat[GGML_TYPE_Q2_K] = std::make_shared<vk_matmul_pipeline_struct>(); | |
| ctx->device->pipeline_dequant_mul_mat_mat[GGML_TYPE_Q3_K] = std::make_shared<vk_matmul_pipeline_struct>(); | |
| ctx->device->pipeline_dequant_mul_mat_mat[GGML_TYPE_Q4_K] = std::make_shared<vk_matmul_pipeline_struct>(); | |
| ctx->device->pipeline_dequant_mul_mat_mat[GGML_TYPE_Q5_K] = std::make_shared<vk_matmul_pipeline_struct>(); | |
| ctx->device->pipeline_dequant_mul_mat_mat[GGML_TYPE_Q6_K] = std::make_shared<vk_matmul_pipeline_struct>(); | |
| /*ctx->device->pipeline_matmul_id_f32 = std::make_shared<vk_matmul_pipeline_struct>(); | |
| ctx->device->pipeline_matmul_id_f16_f32 = std::make_shared<vk_matmul_pipeline_struct>(); | |
| ctx->device->pipeline_matmul_id_f16 = std::make_shared<vk_matmul_pipeline_struct>(); | |
| ctx->device->pipeline_dequant_mul_mat_mat_id[GGML_TYPE_Q4_0] = std::make_shared<vk_matmul_pipeline_struct>(); | |
| ctx->device->pipeline_dequant_mul_mat_mat_id[GGML_TYPE_Q4_1] = std::make_shared<vk_matmul_pipeline_struct>(); | |
| ctx->device->pipeline_dequant_mul_mat_mat_id[GGML_TYPE_Q5_0] = std::make_shared<vk_matmul_pipeline_struct>(); | |
| ctx->device->pipeline_dequant_mul_mat_mat_id[GGML_TYPE_Q5_1] = std::make_shared<vk_matmul_pipeline_struct>(); | |
| ctx->device->pipeline_dequant_mul_mat_mat_id[GGML_TYPE_Q8_0] = std::make_shared<vk_matmul_pipeline_struct>(); | |
| ctx->device->pipeline_dequant_mul_mat_mat_id[GGML_TYPE_Q2_K] = std::make_shared<vk_matmul_pipeline_struct>(); | |
| ctx->device->pipeline_dequant_mul_mat_mat_id[GGML_TYPE_Q3_K] = std::make_shared<vk_matmul_pipeline_struct>(); | |
| ctx->device->pipeline_dequant_mul_mat_mat_id[GGML_TYPE_Q4_K] = std::make_shared<vk_matmul_pipeline_struct>(); | |
| ctx->device->pipeline_dequant_mul_mat_mat_id[GGML_TYPE_Q5_K] = std::make_shared<vk_matmul_pipeline_struct>(); | |
| ctx->device->pipeline_dequant_mul_mat_mat_id[GGML_TYPE_Q6_K] = std::make_shared<vk_matmul_pipeline_struct>();*/ | |
| if (device->fp16) { | |
| ggml_vk_create_pipeline(ctx, ctx->device->pipeline_matmul_f32->l, "matmul_f32_l", matmul_f32_len, matmul_f32_data, "main", 3, sizeof(vk_mat_mat_push_constants), l_wg_denoms, warptile_l, 1); | |
| ggml_vk_create_pipeline(ctx, ctx->device->pipeline_matmul_f32->m, "matmul_f32_m", matmul_f32_len, matmul_f32_data, "main", 3, sizeof(vk_mat_mat_push_constants), m_wg_denoms, warptile_m, 1); | |
| ggml_vk_create_pipeline(ctx, ctx->device->pipeline_matmul_f32->s, "matmul_f32_s", matmul_f32_len, matmul_f32_data, "main", 3, sizeof(vk_mat_mat_push_constants), s_wg_denoms, warptile_s, 1); | |
| ggml_vk_create_pipeline(ctx, ctx->device->pipeline_matmul_f32->a_l, "matmul_f32_aligned_l", matmul_f32_aligned_len, matmul_f32_aligned_data, "main", 3, sizeof(vk_mat_mat_push_constants), l_wg_denoms, warptile_l, l_align); | |
| ggml_vk_create_pipeline(ctx, ctx->device->pipeline_matmul_f32->a_m, "matmul_f32_aligned_m", matmul_f32_aligned_len, matmul_f32_aligned_data, "main", 3, sizeof(vk_mat_mat_push_constants), m_wg_denoms, warptile_m, m_align); | |
| ggml_vk_create_pipeline(ctx, ctx->device->pipeline_matmul_f32->a_s, "matmul_f32_aligned_s", matmul_f32_aligned_len, matmul_f32_aligned_data, "main", 3, sizeof(vk_mat_mat_push_constants), s_wg_denoms, warptile_s, s_align); | |
| ggml_vk_create_pipeline(ctx, ctx->device->pipeline_matmul_f16->l, "matmul_f16_l", matmul_f16_len, matmul_f16_data, "main", 3, sizeof(vk_mat_mat_push_constants), l_wg_denoms, warptile_l, 1); | |
| ggml_vk_create_pipeline(ctx, ctx->device->pipeline_matmul_f16->m, "matmul_f16_m", matmul_f16_len, matmul_f16_data, "main", 3, sizeof(vk_mat_mat_push_constants), m_wg_denoms, warptile_m, 1); | |
| ggml_vk_create_pipeline(ctx, ctx->device->pipeline_matmul_f16->s, "matmul_f16_s", matmul_f16_len, matmul_f16_data, "main", 3, sizeof(vk_mat_mat_push_constants), s_wg_denoms, warptile_s, 1); | |
| ggml_vk_create_pipeline(ctx, ctx->device->pipeline_matmul_f16->a_l, "matmul_f16_aligned_l", matmul_f16_aligned_len, matmul_f16_aligned_data, "main", 3, sizeof(vk_mat_mat_push_constants), l_wg_denoms, warptile_l, l_align); | |
| ggml_vk_create_pipeline(ctx, ctx->device->pipeline_matmul_f16->a_m, "matmul_f16_aligned_m", matmul_f16_aligned_len, matmul_f16_aligned_data, "main", 3, sizeof(vk_mat_mat_push_constants), m_wg_denoms, warptile_m, m_align); | |
| ggml_vk_create_pipeline(ctx, ctx->device->pipeline_matmul_f16->a_s, "matmul_f16_aligned_s", matmul_f16_aligned_len, matmul_f16_aligned_data, "main", 3, sizeof(vk_mat_mat_push_constants), s_wg_denoms, warptile_s, s_align); | |
| ggml_vk_create_pipeline(ctx, ctx->device->pipeline_matmul_f16_f32->l, "matmul_f16_f32_l", matmul_f16_f32_len, matmul_f16_f32_data, "main", 3, sizeof(vk_mat_mat_push_constants), l_wg_denoms, warptile_l, 1); | |
| ggml_vk_create_pipeline(ctx, ctx->device->pipeline_matmul_f16_f32->m, "matmul_f16_f32_m", matmul_f16_f32_len, matmul_f16_f32_data, "main", 3, sizeof(vk_mat_mat_push_constants), m_wg_denoms, warptile_m, 1); | |
| ggml_vk_create_pipeline(ctx, ctx->device->pipeline_matmul_f16_f32->s, "matmul_f16_f32_s", matmul_f16_f32_len, matmul_f16_f32_data, "main", 3, sizeof(vk_mat_mat_push_constants), s_wg_denoms, warptile_s, 1); | |
| ggml_vk_create_pipeline(ctx, ctx->device->pipeline_matmul_f16_f32->a_l, "matmul_f16_f32_aligned_l", matmul_f16_f32_aligned_len, matmul_f16_f32_aligned_data, "main", 3, sizeof(vk_mat_mat_push_constants), l_wg_denoms, warptile_l, l_align); | |
| ggml_vk_create_pipeline(ctx, ctx->device->pipeline_matmul_f16_f32->a_m, "matmul_f16_f32_aligned_m", matmul_f16_f32_aligned_len, matmul_f16_f32_aligned_data, "main", 3, sizeof(vk_mat_mat_push_constants), m_wg_denoms, warptile_m, m_align); | |
| ggml_vk_create_pipeline(ctx, ctx->device->pipeline_matmul_f16_f32->a_s, "matmul_f16_f32_aligned_s", matmul_f16_f32_aligned_len, matmul_f16_f32_aligned_data, "main", 3, sizeof(vk_mat_mat_push_constants), s_wg_denoms, warptile_s, s_align); | |
| ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_mat[GGML_TYPE_Q4_0]->l, "matmul_q4_0_f32_l", matmul_q4_0_f32_len, matmul_q4_0_f32_data, "main", 3, sizeof(vk_mat_mat_push_constants), l_wg_denoms, warptile_mmq_l, l_align); | |
| ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_mat[GGML_TYPE_Q4_0]->m, "matmul_q4_0_f32_m", matmul_q4_0_f32_len, matmul_q4_0_f32_data, "main", 3, sizeof(vk_mat_mat_push_constants), m_wg_denoms, warptile_mmq_m, m_align); | |
| ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_mat[GGML_TYPE_Q4_0]->s, "matmul_q4_0_f32_s", matmul_q4_0_f32_len, matmul_q4_0_f32_data, "main", 3, sizeof(vk_mat_mat_push_constants), s_wg_denoms, warptile_mmq_s, s_align); | |
| ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_mat[GGML_TYPE_Q4_0]->a_l, "matmul_q4_0_f32_aligned_l", matmul_q4_0_f32_aligned_len, matmul_q4_0_f32_aligned_data, "main", 3, sizeof(vk_mat_mat_push_constants), l_wg_denoms, warptile_mmq_l, l_align); | |
| ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_mat[GGML_TYPE_Q4_0]->a_m, "matmul_q4_0_f32_aligned_m", matmul_q4_0_f32_aligned_len, matmul_q4_0_f32_aligned_data, "main", 3, sizeof(vk_mat_mat_push_constants), m_wg_denoms, warptile_mmq_m, m_align); | |
| ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_mat[GGML_TYPE_Q4_0]->a_s, "matmul_q4_0_f32_aligned_s", matmul_q4_0_f32_aligned_len, matmul_q4_0_f32_aligned_data, "main", 3, sizeof(vk_mat_mat_push_constants), s_wg_denoms, warptile_mmq_s, s_align); | |
| ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_mat[GGML_TYPE_Q4_1]->l, "matmul_q4_0_f32_l", matmul_q4_1_f32_len, matmul_q4_1_f32_data, "main", 3, sizeof(vk_mat_mat_push_constants), l_wg_denoms, warptile_mmq_l, l_align); | |
| ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_mat[GGML_TYPE_Q4_1]->m, "matmul_q4_0_f32_m", matmul_q4_1_f32_len, matmul_q4_1_f32_data, "main", 3, sizeof(vk_mat_mat_push_constants), m_wg_denoms, warptile_mmq_m, m_align); | |
| ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_mat[GGML_TYPE_Q4_1]->s, "matmul_q4_0_f32_s", matmul_q4_1_f32_len, matmul_q4_1_f32_data, "main", 3, sizeof(vk_mat_mat_push_constants), s_wg_denoms, warptile_mmq_s, s_align); | |
| ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_mat[GGML_TYPE_Q4_1]->a_l, "matmul_q4_0_f32_aligned_l", matmul_q4_1_f32_aligned_len, matmul_q4_1_f32_aligned_data, "main", 3, sizeof(vk_mat_mat_push_constants), l_wg_denoms, warptile_mmq_l, l_align); | |
| ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_mat[GGML_TYPE_Q4_1]->a_m, "matmul_q4_0_f32_aligned_m", matmul_q4_1_f32_aligned_len, matmul_q4_1_f32_aligned_data, "main", 3, sizeof(vk_mat_mat_push_constants), m_wg_denoms, warptile_mmq_m, m_align); | |
| ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_mat[GGML_TYPE_Q4_1]->a_s, "matmul_q4_0_f32_aligned_s", matmul_q4_1_f32_aligned_len, matmul_q4_1_f32_aligned_data, "main", 3, sizeof(vk_mat_mat_push_constants), s_wg_denoms, warptile_mmq_s, s_align); | |
| ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_mat[GGML_TYPE_Q5_0]->l, "matmul_q5_0_f32_l", matmul_q5_0_f32_len, matmul_q5_0_f32_data, "main", 3, sizeof(vk_mat_mat_push_constants), l_wg_denoms, warptile_mmq_l, l_align); | |
| ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_mat[GGML_TYPE_Q5_0]->m, "matmul_q5_0_f32_m", matmul_q5_0_f32_len, matmul_q5_0_f32_data, "main", 3, sizeof(vk_mat_mat_push_constants), m_wg_denoms, warptile_mmq_m, m_align); | |
| ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_mat[GGML_TYPE_Q5_0]->s, "matmul_q5_0_f32_s", matmul_q5_0_f32_len, matmul_q5_0_f32_data, "main", 3, sizeof(vk_mat_mat_push_constants), s_wg_denoms, warptile_mmq_s, s_align); | |
| ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_mat[GGML_TYPE_Q5_0]->a_l, "matmul_q5_0_f32_aligned_l", matmul_q5_0_f32_aligned_len, matmul_q5_0_f32_aligned_data, "main", 3, sizeof(vk_mat_mat_push_constants), l_wg_denoms, warptile_mmq_l, l_align); | |
| ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_mat[GGML_TYPE_Q5_0]->a_m, "matmul_q5_0_f32_aligned_m", matmul_q5_0_f32_aligned_len, matmul_q5_0_f32_aligned_data, "main", 3, sizeof(vk_mat_mat_push_constants), m_wg_denoms, warptile_mmq_m, m_align); | |
| ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_mat[GGML_TYPE_Q5_0]->a_s, "matmul_q5_0_f32_aligned_s", matmul_q5_0_f32_aligned_len, matmul_q5_0_f32_aligned_data, "main", 3, sizeof(vk_mat_mat_push_constants), s_wg_denoms, warptile_mmq_s, s_align); | |
| ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_mat[GGML_TYPE_Q5_1]->l, "matmul_q5_1_f32_l", matmul_q5_1_f32_len, matmul_q5_1_f32_data, "main", 3, sizeof(vk_mat_mat_push_constants), l_wg_denoms, warptile_mmq_l, l_align); | |
| ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_mat[GGML_TYPE_Q5_1]->m, "matmul_q5_1_f32_m", matmul_q5_1_f32_len, matmul_q5_1_f32_data, "main", 3, sizeof(vk_mat_mat_push_constants), m_wg_denoms, warptile_mmq_m, m_align); | |
| ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_mat[GGML_TYPE_Q5_1]->s, "matmul_q5_1_f32_s", matmul_q5_1_f32_len, matmul_q5_1_f32_data, "main", 3, sizeof(vk_mat_mat_push_constants), s_wg_denoms, warptile_mmq_s, s_align); | |
| ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_mat[GGML_TYPE_Q5_1]->a_l, "matmul_q5_1_f32_aligned_l", matmul_q5_1_f32_aligned_len, matmul_q5_1_f32_aligned_data, "main", 3, sizeof(vk_mat_mat_push_constants), l_wg_denoms, warptile_mmq_l, l_align); | |
| ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_mat[GGML_TYPE_Q5_1]->a_m, "matmul_q5_1_f32_aligned_m", matmul_q5_1_f32_aligned_len, matmul_q5_1_f32_aligned_data, "main", 3, sizeof(vk_mat_mat_push_constants), m_wg_denoms, warptile_mmq_m, m_align); | |
| ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_mat[GGML_TYPE_Q5_1]->a_s, "matmul_q5_1_f32_aligned_s", matmul_q5_1_f32_aligned_len, matmul_q5_1_f32_aligned_data, "main", 3, sizeof(vk_mat_mat_push_constants), s_wg_denoms, warptile_mmq_s, s_align); | |
| ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_mat[GGML_TYPE_Q8_0]->l, "matmul_q8_0_f32_l", matmul_q8_0_f32_len, matmul_q8_0_f32_data, "main", 3, sizeof(vk_mat_mat_push_constants), l_wg_denoms, warptile_mmq_l, l_align); | |
| ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_mat[GGML_TYPE_Q8_0]->m, "matmul_q8_0_f32_m", matmul_q8_0_f32_len, matmul_q8_0_f32_data, "main", 3, sizeof(vk_mat_mat_push_constants), m_wg_denoms, warptile_mmq_m, m_align); | |
| ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_mat[GGML_TYPE_Q8_0]->s, "matmul_q8_0_f32_s", matmul_q8_0_f32_len, matmul_q8_0_f32_data, "main", 3, sizeof(vk_mat_mat_push_constants), s_wg_denoms, warptile_mmq_s, s_align); | |
| ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_mat[GGML_TYPE_Q8_0]->a_l, "matmul_q8_0_f32_aligned_l", matmul_q8_0_f32_aligned_len, matmul_q8_0_f32_aligned_data, "main", 3, sizeof(vk_mat_mat_push_constants), l_wg_denoms, warptile_mmq_l, l_align); | |
| ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_mat[GGML_TYPE_Q8_0]->a_m, "matmul_q8_0_f32_aligned_m", matmul_q8_0_f32_aligned_len, matmul_q8_0_f32_aligned_data, "main", 3, sizeof(vk_mat_mat_push_constants), m_wg_denoms, warptile_mmq_m, m_align); | |
| ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_mat[GGML_TYPE_Q8_0]->a_s, "matmul_q8_0_f32_aligned_s", matmul_q8_0_f32_aligned_len, matmul_q8_0_f32_aligned_data, "main", 3, sizeof(vk_mat_mat_push_constants), s_wg_denoms, warptile_mmq_s, s_align); | |
| ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_mat[GGML_TYPE_Q2_K]->l, "matmul_q2_k_f32_l", matmul_q2_k_f32_len, matmul_q2_k_f32_data, "main", 3, sizeof(vk_mat_mat_push_constants), l_wg_denoms, warptile_mmq_l, l_align); | |
| ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_mat[GGML_TYPE_Q2_K]->m, "matmul_q2_k_f32_m", matmul_q2_k_f32_len, matmul_q2_k_f32_data, "main", 3, sizeof(vk_mat_mat_push_constants), m_wg_denoms, warptile_mmq_m, m_align); | |
| ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_mat[GGML_TYPE_Q2_K]->s, "matmul_q2_k_f32_s", matmul_q2_k_f32_len, matmul_q2_k_f32_data, "main", 3, sizeof(vk_mat_mat_push_constants), s_wg_denoms, warptile_mmq_s, s_align); | |
| ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_mat[GGML_TYPE_Q2_K]->a_l, "matmul_q2_k_f32_aligned_l", matmul_q2_k_f32_aligned_len, matmul_q2_k_f32_aligned_data, "main", 3, sizeof(vk_mat_mat_push_constants), l_wg_denoms, warptile_mmq_l, l_align); | |
| ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_mat[GGML_TYPE_Q2_K]->a_m, "matmul_q2_k_f32_aligned_m", matmul_q2_k_f32_aligned_len, matmul_q2_k_f32_aligned_data, "main", 3, sizeof(vk_mat_mat_push_constants), m_wg_denoms, warptile_mmq_m, m_align); | |
| ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_mat[GGML_TYPE_Q2_K]->a_s, "matmul_q2_k_f32_aligned_s", matmul_q2_k_f32_aligned_len, matmul_q2_k_f32_aligned_data, "main", 3, sizeof(vk_mat_mat_push_constants), s_wg_denoms, warptile_mmq_s, s_align); | |
| ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_mat[GGML_TYPE_Q3_K]->l, "matmul_q3_k_f32_l", matmul_q3_k_f32_len, matmul_q3_k_f32_data, "main", 3, sizeof(vk_mat_mat_push_constants), l_wg_denoms, warptile_mmq_l, l_align); | |
| ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_mat[GGML_TYPE_Q3_K]->m, "matmul_q3_k_f32_m", matmul_q3_k_f32_len, matmul_q3_k_f32_data, "main", 3, sizeof(vk_mat_mat_push_constants), m_wg_denoms, warptile_mmq_m, m_align); | |
| ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_mat[GGML_TYPE_Q3_K]->s, "matmul_q3_k_f32_s", matmul_q3_k_f32_len, matmul_q3_k_f32_data, "main", 3, sizeof(vk_mat_mat_push_constants), s_wg_denoms, warptile_mmq_s, s_align); | |
| ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_mat[GGML_TYPE_Q3_K]->a_l, "matmul_q3_k_f32_aligned_l", matmul_q3_k_f32_aligned_len, matmul_q3_k_f32_aligned_data, "main", 3, sizeof(vk_mat_mat_push_constants), l_wg_denoms, warptile_mmq_l, l_align); | |
| ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_mat[GGML_TYPE_Q3_K]->a_m, "matmul_q3_k_f32_aligned_m", matmul_q3_k_f32_aligned_len, matmul_q3_k_f32_aligned_data, "main", 3, sizeof(vk_mat_mat_push_constants), m_wg_denoms, warptile_mmq_m, m_align); | |
| ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_mat[GGML_TYPE_Q3_K]->a_s, "matmul_q3_k_f32_aligned_s", matmul_q3_k_f32_aligned_len, matmul_q3_k_f32_aligned_data, "main", 3, sizeof(vk_mat_mat_push_constants), s_wg_denoms, warptile_mmq_s, s_align); | |
| ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_mat[GGML_TYPE_Q4_K]->l, "matmul_q4_k_f32_l", matmul_q4_k_f32_len, matmul_q4_k_f32_data, "main", 3, sizeof(vk_mat_mat_push_constants), l_wg_denoms, warptile_mmq_l, l_align); | |
| ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_mat[GGML_TYPE_Q4_K]->m, "matmul_q4_k_f32_m", matmul_q4_k_f32_len, matmul_q4_k_f32_data, "main", 3, sizeof(vk_mat_mat_push_constants), m_wg_denoms, warptile_mmq_m, m_align); | |
| ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_mat[GGML_TYPE_Q4_K]->s, "matmul_q4_k_f32_s", matmul_q4_k_f32_len, matmul_q4_k_f32_data, "main", 3, sizeof(vk_mat_mat_push_constants), s_wg_denoms, warptile_mmq_s, s_align); | |
| ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_mat[GGML_TYPE_Q4_K]->a_l, "matmul_q4_k_f32_aligned_l", matmul_q4_k_f32_aligned_len, matmul_q4_k_f32_aligned_data, "main", 3, sizeof(vk_mat_mat_push_constants), l_wg_denoms, warptile_mmq_l, l_align); | |
| ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_mat[GGML_TYPE_Q4_K]->a_m, "matmul_q4_k_f32_aligned_m", matmul_q4_k_f32_aligned_len, matmul_q4_k_f32_aligned_data, "main", 3, sizeof(vk_mat_mat_push_constants), m_wg_denoms, warptile_mmq_m, m_align); | |
| ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_mat[GGML_TYPE_Q4_K]->a_s, "matmul_q4_k_f32_aligned_s", matmul_q4_k_f32_aligned_len, matmul_q4_k_f32_aligned_data, "main", 3, sizeof(vk_mat_mat_push_constants), s_wg_denoms, warptile_mmq_s, s_align); | |
| ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_mat[GGML_TYPE_Q5_K]->l, "matmul_q5_k_f32_l", matmul_q5_k_f32_len, matmul_q5_k_f32_data, "main", 3, sizeof(vk_mat_mat_push_constants), l_wg_denoms, warptile_mmq_l, l_align); | |
| ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_mat[GGML_TYPE_Q5_K]->m, "matmul_q5_k_f32_m", matmul_q5_k_f32_len, matmul_q5_k_f32_data, "main", 3, sizeof(vk_mat_mat_push_constants), m_wg_denoms, warptile_mmq_m, m_align); | |
| ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_mat[GGML_TYPE_Q5_K]->s, "matmul_q5_k_f32_s", matmul_q5_k_f32_len, matmul_q5_k_f32_data, "main", 3, sizeof(vk_mat_mat_push_constants), s_wg_denoms, warptile_mmq_s, s_align); | |
| ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_mat[GGML_TYPE_Q5_K]->a_l, "matmul_q5_k_f32_aligned_l", matmul_q5_k_f32_aligned_len, matmul_q5_k_f32_aligned_data, "main", 3, sizeof(vk_mat_mat_push_constants), l_wg_denoms, warptile_mmq_l, l_align); | |
| ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_mat[GGML_TYPE_Q5_K]->a_m, "matmul_q5_k_f32_aligned_m", matmul_q5_k_f32_aligned_len, matmul_q5_k_f32_aligned_data, "main", 3, sizeof(vk_mat_mat_push_constants), m_wg_denoms, warptile_mmq_m, m_align); | |
| ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_mat[GGML_TYPE_Q5_K]->a_s, "matmul_q5_k_f32_aligned_s", matmul_q5_k_f32_aligned_len, matmul_q5_k_f32_aligned_data, "main", 3, sizeof(vk_mat_mat_push_constants), s_wg_denoms, warptile_mmq_s, s_align); | |
| ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_mat[GGML_TYPE_Q6_K]->l, "matmul_q6_k_f32_l", matmul_q6_k_f32_len, matmul_q6_k_f32_data, "main", 3, sizeof(vk_mat_mat_push_constants), l_wg_denoms, warptile_mmq_l, l_align); | |
| ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_mat[GGML_TYPE_Q6_K]->m, "matmul_q6_k_f32_m", matmul_q6_k_f32_len, matmul_q6_k_f32_data, "main", 3, sizeof(vk_mat_mat_push_constants), m_wg_denoms, warptile_mmq_m, m_align); | |
| ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_mat[GGML_TYPE_Q6_K]->s, "matmul_q6_k_f32_s", matmul_q6_k_f32_len, matmul_q6_k_f32_data, "main", 3, sizeof(vk_mat_mat_push_constants), s_wg_denoms, warptile_mmq_s, s_align); | |
| ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_mat[GGML_TYPE_Q6_K]->a_l, "matmul_q6_k_f32_aligned_l", matmul_q6_k_f32_aligned_len, matmul_q6_k_f32_aligned_data, "main", 3, sizeof(vk_mat_mat_push_constants), l_wg_denoms, warptile_mmq_l, l_align); | |
| ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_mat[GGML_TYPE_Q6_K]->a_m, "matmul_q6_k_f32_aligned_m", matmul_q6_k_f32_aligned_len, matmul_q6_k_f32_aligned_data, "main", 3, sizeof(vk_mat_mat_push_constants), m_wg_denoms, warptile_mmq_m, m_align); | |
| ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_mat[GGML_TYPE_Q6_K]->a_s, "matmul_q6_k_f32_aligned_s", matmul_q6_k_f32_aligned_len, matmul_q6_k_f32_aligned_data, "main", 3, sizeof(vk_mat_mat_push_constants), s_wg_denoms, warptile_mmq_s, s_align); | |
| /*ggml_vk_create_pipeline(ctx, ctx->device->pipeline_matmul_id_f32->l, "matmul_id_f32_l", matmul_id_f32_len, matmul_id_f32_data, "main", 4, sizeof(vk_mat_mat_push_constants), l_wg_denoms, warptile_l, 1); | |
| ggml_vk_create_pipeline(ctx, ctx->device->pipeline_matmul_id_f32->m, "matmul_id_f32_m", matmul_id_f32_len, matmul_id_f32_data, "main", 4, sizeof(vk_mat_mat_push_constants), m_wg_denoms, warptile_m, 1); | |
| ggml_vk_create_pipeline(ctx, ctx->device->pipeline_matmul_id_f32->s, "matmul_id_f32_s", matmul_id_f32_len, matmul_id_f32_data, "main", 4, sizeof(vk_mat_mat_push_constants), s_wg_denoms, warptile_s, 1); | |
| ggml_vk_create_pipeline(ctx, ctx->device->pipeline_matmul_id_f32->a_l, "matmul_id_f32_aligned_l", matmul_id_f32_aligned_len, matmul_id_f32_aligned_data, "main", 4, sizeof(vk_mat_mat_push_constants), l_wg_denoms, warptile_l, l_align); | |
| ggml_vk_create_pipeline(ctx, ctx->device->pipeline_matmul_id_f32->a_m, "matmul_id_f32_aligned_m", matmul_id_f32_aligned_len, matmul_id_f32_aligned_data, "main", 4, sizeof(vk_mat_mat_push_constants), m_wg_denoms, warptile_m, m_align); | |
| ggml_vk_create_pipeline(ctx, ctx->device->pipeline_matmul_id_f32->a_s, "matmul_id_f32_aligned_s", matmul_id_f32_aligned_len, matmul_id_f32_aligned_data, "main", 4, sizeof(vk_mat_mat_push_constants), s_wg_denoms, warptile_s, s_align); | |
| ggml_vk_create_pipeline(ctx, ctx->device->pipeline_matmul_id_f16->l, "matmul_id_f16_l", matmul_id_f16_len, matmul_id_f16_data, "main", 4, sizeof(vk_mat_mat_push_constants), l_wg_denoms, warptile_l, 1); | |
| ggml_vk_create_pipeline(ctx, ctx->device->pipeline_matmul_id_f16->m, "matmul_id_f16_m", matmul_id_f16_len, matmul_id_f16_data, "main", 4, sizeof(vk_mat_mat_push_constants), m_wg_denoms, warptile_m, 1); | |
| ggml_vk_create_pipeline(ctx, ctx->device->pipeline_matmul_id_f16->s, "matmul_id_f16_s", matmul_id_f16_len, matmul_id_f16_data, "main", 4, sizeof(vk_mat_mat_push_constants), s_wg_denoms, warptile_s, 1); | |
| ggml_vk_create_pipeline(ctx, ctx->device->pipeline_matmul_id_f16->a_l, "matmul_id_f16_aligned_l", matmul_id_f16_aligned_len, matmul_id_f16_aligned_data, "main", 4, sizeof(vk_mat_mat_push_constants), l_wg_denoms, warptile_l, l_align); | |
| ggml_vk_create_pipeline(ctx, ctx->device->pipeline_matmul_id_f16->a_m, "matmul_id_f16_aligned_m", matmul_id_f16_aligned_len, matmul_id_f16_aligned_data, "main", 4, sizeof(vk_mat_mat_push_constants), m_wg_denoms, warptile_m, m_align); | |
| ggml_vk_create_pipeline(ctx, ctx->device->pipeline_matmul_id_f16->a_s, "matmul_id_f16_aligned_s", matmul_id_f16_aligned_len, matmul_id_f16_aligned_data, "main", 4, sizeof(vk_mat_mat_push_constants), s_wg_denoms, warptile_s, s_align); | |
| ggml_vk_create_pipeline(ctx, ctx->device->pipeline_matmul_id_f16_f32->l, "matmul_id_f16_f32_l", matmul_id_f16_f32_len, matmul_id_f16_f32_data, "main", 4, sizeof(vk_mat_mat_push_constants), l_wg_denoms, warptile_l, 1); | |
| ggml_vk_create_pipeline(ctx, ctx->device->pipeline_matmul_id_f16_f32->m, "matmul_id_f16_f32_m", matmul_id_f16_f32_len, matmul_id_f16_f32_data, "main", 4, sizeof(vk_mat_mat_push_constants), m_wg_denoms, warptile_m, 1); | |
| ggml_vk_create_pipeline(ctx, ctx->device->pipeline_matmul_id_f16_f32->s, "matmul_id_f16_f32_s", matmul_id_f16_f32_len, matmul_id_f16_f32_data, "main", 4, sizeof(vk_mat_mat_push_constants), s_wg_denoms, warptile_s, 1); | |
| ggml_vk_create_pipeline(ctx, ctx->device->pipeline_matmul_id_f16_f32->a_l, "matmul_id_f16_f32_aligned_l", matmul_id_f16_f32_aligned_len, matmul_id_f16_f32_aligned_data, "main", 4, sizeof(vk_mat_mat_push_constants), l_wg_denoms, warptile_l, l_align); | |
| ggml_vk_create_pipeline(ctx, ctx->device->pipeline_matmul_id_f16_f32->a_m, "matmul_id_f16_f32_aligned_m", matmul_id_f16_f32_aligned_len, matmul_id_f16_f32_aligned_data, "main", 4, sizeof(vk_mat_mat_push_constants), m_wg_denoms, warptile_m, m_align); | |
| ggml_vk_create_pipeline(ctx, ctx->device->pipeline_matmul_id_f16_f32->a_s, "matmul_id_f16_f32_aligned_s", matmul_id_f16_f32_aligned_len, matmul_id_f16_f32_aligned_data, "main", 4, sizeof(vk_mat_mat_push_constants), s_wg_denoms, warptile_s, s_align); | |
| ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_mat_id[GGML_TYPE_Q4_0]->l, "matmul_id_q4_0_f32_l", matmul_id_q4_0_f32_len, matmul_id_q4_0_f32_data, "main", 4, sizeof(vk_mat_mat_push_constants), l_wg_denoms, warptile_mmq_l, l_align); | |
| ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_mat_id[GGML_TYPE_Q4_0]->m, "matmul_id_q4_0_f32_m", matmul_id_q4_0_f32_len, matmul_id_q4_0_f32_data, "main", 4, sizeof(vk_mat_mat_push_constants), m_wg_denoms, warptile_mmq_m, m_align); | |
| ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_mat_id[GGML_TYPE_Q4_0]->s, "matmul_id_q4_0_f32_s", matmul_id_q4_0_f32_len, matmul_id_q4_0_f32_data, "main", 4, sizeof(vk_mat_mat_push_constants), s_wg_denoms, warptile_mmq_s, s_align); | |
| ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_mat_id[GGML_TYPE_Q4_0]->a_l, "matmul_id_q4_0_f32_aligned_l", matmul_id_q4_0_f32_aligned_len, matmul_id_q4_0_f32_aligned_data, "main", 4, sizeof(vk_mat_mat_push_constants), l_wg_denoms, warptile_mmq_l, l_align); | |
| ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_mat_id[GGML_TYPE_Q4_0]->a_m, "matmul_id_q4_0_f32_aligned_m", matmul_id_q4_0_f32_aligned_len, matmul_id_q4_0_f32_aligned_data, "main", 4, sizeof(vk_mat_mat_push_constants), m_wg_denoms, warptile_mmq_m, m_align); | |
| ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_mat_id[GGML_TYPE_Q4_0]->a_s, "matmul_id_q4_0_f32_aligned_s", matmul_id_q4_0_f32_aligned_len, matmul_id_q4_0_f32_aligned_data, "main", 4, sizeof(vk_mat_mat_push_constants), s_wg_denoms, warptile_mmq_s, s_align); | |
| ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_mat_id[GGML_TYPE_Q4_1]->l, "matmul_id_q4_0_f32_l", matmul_id_q4_1_f32_len, matmul_id_q4_1_f32_data, "main", 4, sizeof(vk_mat_mat_push_constants), l_wg_denoms, warptile_mmq_l, l_align); | |
| ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_mat_id[GGML_TYPE_Q4_1]->m, "matmul_id_q4_0_f32_m", matmul_id_q4_1_f32_len, matmul_id_q4_1_f32_data, "main", 4, sizeof(vk_mat_mat_push_constants), m_wg_denoms, warptile_mmq_m, m_align); | |
| ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_mat_id[GGML_TYPE_Q4_1]->s, "matmul_id_q4_0_f32_s", matmul_id_q4_1_f32_len, matmul_id_q4_1_f32_data, "main", 4, sizeof(vk_mat_mat_push_constants), s_wg_denoms, warptile_mmq_s, s_align); | |
| ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_mat_id[GGML_TYPE_Q4_1]->a_l, "matmul_id_q4_0_f32_aligned_l", matmul_id_q4_1_f32_aligned_len, matmul_id_q4_1_f32_aligned_data, "main", 4, sizeof(vk_mat_mat_push_constants), l_wg_denoms, warptile_mmq_l, l_align); | |
| ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_mat_id[GGML_TYPE_Q4_1]->a_m, "matmul_id_q4_0_f32_aligned_m", matmul_id_q4_1_f32_aligned_len, matmul_id_q4_1_f32_aligned_data, "main", 4, sizeof(vk_mat_mat_push_constants), m_wg_denoms, warptile_mmq_m, m_align); | |
| ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_mat_id[GGML_TYPE_Q4_1]->a_s, "matmul_id_q4_0_f32_aligned_s", matmul_id_q4_1_f32_aligned_len, matmul_id_q4_1_f32_aligned_data, "main", 4, sizeof(vk_mat_mat_push_constants), s_wg_denoms, warptile_mmq_s, s_align); | |
| ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_mat_id[GGML_TYPE_Q5_0]->l, "matmul_id_q5_0_f32_l", matmul_id_q5_0_f32_len, matmul_id_q5_0_f32_data, "main", 4, sizeof(vk_mat_mat_push_constants), l_wg_denoms, warptile_mmq_l, l_align); | |
| ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_mat_id[GGML_TYPE_Q5_0]->m, "matmul_id_q5_0_f32_m", matmul_id_q5_0_f32_len, matmul_id_q5_0_f32_data, "main", 4, sizeof(vk_mat_mat_push_constants), m_wg_denoms, warptile_mmq_m, m_align); | |
| ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_mat_id[GGML_TYPE_Q5_0]->s, "matmul_id_q5_0_f32_s", matmul_id_q5_0_f32_len, matmul_id_q5_0_f32_data, "main", 4, sizeof(vk_mat_mat_push_constants), s_wg_denoms, warptile_mmq_s, s_align); | |
| ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_mat_id[GGML_TYPE_Q5_0]->a_l, "matmul_id_q5_0_f32_aligned_l", matmul_id_q5_0_f32_aligned_len, matmul_id_q5_0_f32_aligned_data, "main", 4, sizeof(vk_mat_mat_push_constants), l_wg_denoms, warptile_mmq_l, l_align); | |
| ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_mat_id[GGML_TYPE_Q5_0]->a_m, "matmul_id_q5_0_f32_aligned_m", matmul_id_q5_0_f32_aligned_len, matmul_id_q5_0_f32_aligned_data, "main", 4, sizeof(vk_mat_mat_push_constants), m_wg_denoms, warptile_mmq_m, m_align); | |
| ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_mat_id[GGML_TYPE_Q5_0]->a_s, "matmul_id_q5_0_f32_aligned_s", matmul_id_q5_0_f32_aligned_len, matmul_id_q5_0_f32_aligned_data, "main", 4, sizeof(vk_mat_mat_push_constants), s_wg_denoms, warptile_mmq_s, s_align); | |
| ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_mat_id[GGML_TYPE_Q5_1]->l, "matmul_id_q5_1_f32_l", matmul_id_q5_1_f32_len, matmul_id_q5_1_f32_data, "main", 4, sizeof(vk_mat_mat_push_constants), l_wg_denoms, warptile_mmq_l, l_align); | |
| ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_mat_id[GGML_TYPE_Q5_1]->m, "matmul_id_q5_1_f32_m", matmul_id_q5_1_f32_len, matmul_id_q5_1_f32_data, "main", 4, sizeof(vk_mat_mat_push_constants), m_wg_denoms, warptile_mmq_m, m_align); | |
| ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_mat_id[GGML_TYPE_Q5_1]->s, "matmul_id_q5_1_f32_s", matmul_id_q5_1_f32_len, matmul_id_q5_1_f32_data, "main", 4, sizeof(vk_mat_mat_push_constants), s_wg_denoms, warptile_mmq_s, s_align); | |
| ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_mat_id[GGML_TYPE_Q5_1]->a_l, "matmul_id_q5_1_f32_aligned_l", matmul_id_q5_1_f32_aligned_len, matmul_id_q5_1_f32_aligned_data, "main", 4, sizeof(vk_mat_mat_push_constants), l_wg_denoms, warptile_mmq_l, l_align); | |
| ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_mat_id[GGML_TYPE_Q5_1]->a_m, "matmul_id_q5_1_f32_aligned_m", matmul_id_q5_1_f32_aligned_len, matmul_id_q5_1_f32_aligned_data, "main", 4, sizeof(vk_mat_mat_push_constants), m_wg_denoms, warptile_mmq_m, m_align); | |
| ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_mat_id[GGML_TYPE_Q5_1]->a_s, "matmul_id_q5_1_f32_aligned_s", matmul_id_q5_1_f32_aligned_len, matmul_id_q5_1_f32_aligned_data, "main", 4, sizeof(vk_mat_mat_push_constants), s_wg_denoms, warptile_mmq_s, s_align); | |
| ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_mat_id[GGML_TYPE_Q8_0]->l, "matmul_id_q8_0_f32_l", matmul_id_q8_0_f32_len, matmul_id_q8_0_f32_data, "main", 4, sizeof(vk_mat_mat_push_constants), l_wg_denoms, warptile_mmq_l, l_align); | |
| ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_mat_id[GGML_TYPE_Q8_0]->m, "matmul_id_q8_0_f32_m", matmul_id_q8_0_f32_len, matmul_id_q8_0_f32_data, "main", 4, sizeof(vk_mat_mat_push_constants), m_wg_denoms, warptile_mmq_m, m_align); | |
| ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_mat_id[GGML_TYPE_Q8_0]->s, "matmul_id_q8_0_f32_s", matmul_id_q8_0_f32_len, matmul_id_q8_0_f32_data, "main", 4, sizeof(vk_mat_mat_push_constants), s_wg_denoms, warptile_mmq_s, s_align); | |
| ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_mat_id[GGML_TYPE_Q8_0]->a_l, "matmul_id_q8_0_f32_aligned_l", matmul_id_q8_0_f32_aligned_len, matmul_id_q8_0_f32_aligned_data, "main", 4, sizeof(vk_mat_mat_push_constants), l_wg_denoms, warptile_mmq_l, l_align); | |
| ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_mat_id[GGML_TYPE_Q8_0]->a_m, "matmul_id_q8_0_f32_aligned_m", matmul_id_q8_0_f32_aligned_len, matmul_id_q8_0_f32_aligned_data, "main", 4, sizeof(vk_mat_mat_push_constants), m_wg_denoms, warptile_mmq_m, m_align); | |
| ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_mat_id[GGML_TYPE_Q8_0]->a_s, "matmul_id_q8_0_f32_aligned_s", matmul_id_q8_0_f32_aligned_len, matmul_id_q8_0_f32_aligned_data, "main", 4, sizeof(vk_mat_mat_push_constants), s_wg_denoms, warptile_mmq_s, s_align); | |
| ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_mat_id[GGML_TYPE_Q2_K]->l, "matmul_id_q2_k_f32_l", matmul_id_q2_k_f32_len, matmul_id_q2_k_f32_data, "main", 4, sizeof(vk_mat_mat_push_constants), l_wg_denoms, warptile_mmq_l, l_align); | |
| ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_mat_id[GGML_TYPE_Q2_K]->m, "matmul_id_q2_k_f32_m", matmul_id_q2_k_f32_len, matmul_id_q2_k_f32_data, "main", 4, sizeof(vk_mat_mat_push_constants), m_wg_denoms, warptile_mmq_m, m_align); | |
| ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_mat_id[GGML_TYPE_Q2_K]->s, "matmul_id_q2_k_f32_s", matmul_id_q2_k_f32_len, matmul_id_q2_k_f32_data, "main", 4, sizeof(vk_mat_mat_push_constants), s_wg_denoms, warptile_mmq_s, s_align); | |
| ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_mat_id[GGML_TYPE_Q2_K]->a_l, "matmul_id_q2_k_f32_aligned_l", matmul_id_q2_k_f32_aligned_len, matmul_id_q2_k_f32_aligned_data, "main", 4, sizeof(vk_mat_mat_push_constants), l_wg_denoms, warptile_mmq_l, l_align); | |
| ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_mat_id[GGML_TYPE_Q2_K]->a_m, "matmul_id_q2_k_f32_aligned_m", matmul_id_q2_k_f32_aligned_len, matmul_id_q2_k_f32_aligned_data, "main", 4, sizeof(vk_mat_mat_push_constants), m_wg_denoms, warptile_mmq_m, m_align); | |
| ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_mat_id[GGML_TYPE_Q2_K]->a_s, "matmul_id_q2_k_f32_aligned_s", matmul_id_q2_k_f32_aligned_len, matmul_id_q2_k_f32_aligned_data, "main", 4, sizeof(vk_mat_mat_push_constants), s_wg_denoms, warptile_mmq_s, s_align); | |
| ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_mat_id[GGML_TYPE_Q3_K]->l, "matmul_id_q3_k_f32_l", matmul_id_q3_k_f32_len, matmul_id_q3_k_f32_data, "main", 4, sizeof(vk_mat_mat_push_constants), l_wg_denoms, warptile_mmq_l, l_align); | |
| ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_mat_id[GGML_TYPE_Q3_K]->m, "matmul_id_q3_k_f32_m", matmul_id_q3_k_f32_len, matmul_id_q3_k_f32_data, "main", 4, sizeof(vk_mat_mat_push_constants), m_wg_denoms, warptile_mmq_m, m_align); | |
| ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_mat_id[GGML_TYPE_Q3_K]->s, "matmul_id_q3_k_f32_s", matmul_id_q3_k_f32_len, matmul_id_q3_k_f32_data, "main", 4, sizeof(vk_mat_mat_push_constants), s_wg_denoms, warptile_mmq_s, s_align); | |
| ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_mat_id[GGML_TYPE_Q3_K]->a_l, "matmul_id_q3_k_f32_aligned_l", matmul_id_q3_k_f32_aligned_len, matmul_id_q3_k_f32_aligned_data, "main", 4, sizeof(vk_mat_mat_push_constants), l_wg_denoms, warptile_mmq_l, l_align); | |
| ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_mat_id[GGML_TYPE_Q3_K]->a_m, "matmul_id_q3_k_f32_aligned_m", matmul_id_q3_k_f32_aligned_len, matmul_id_q3_k_f32_aligned_data, "main", 4, sizeof(vk_mat_mat_push_constants), m_wg_denoms, warptile_mmq_m, m_align); | |
| ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_mat_id[GGML_TYPE_Q3_K]->a_s, "matmul_id_q3_k_f32_aligned_s", matmul_id_q3_k_f32_aligned_len, matmul_id_q3_k_f32_aligned_data, "main", 4, sizeof(vk_mat_mat_push_constants), s_wg_denoms, warptile_mmq_s, s_align); | |
| ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_mat_id[GGML_TYPE_Q4_K]->l, "matmul_id_q4_k_f32_l", matmul_id_q4_k_f32_len, matmul_id_q4_k_f32_data, "main", 4, sizeof(vk_mat_mat_push_constants), l_wg_denoms, warptile_mmq_l, l_align); | |
| ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_mat_id[GGML_TYPE_Q4_K]->m, "matmul_id_q4_k_f32_m", matmul_id_q4_k_f32_len, matmul_id_q4_k_f32_data, "main", 4, sizeof(vk_mat_mat_push_constants), m_wg_denoms, warptile_mmq_m, m_align); | |
| ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_mat_id[GGML_TYPE_Q4_K]->s, "matmul_id_q4_k_f32_s", matmul_id_q4_k_f32_len, matmul_id_q4_k_f32_data, "main", 4, sizeof(vk_mat_mat_push_constants), s_wg_denoms, warptile_mmq_s, s_align); | |
| ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_mat_id[GGML_TYPE_Q4_K]->a_l, "matmul_id_q4_k_f32_aligned_l", matmul_id_q4_k_f32_aligned_len, matmul_id_q4_k_f32_aligned_data, "main", 4, sizeof(vk_mat_mat_push_constants), l_wg_denoms, warptile_mmq_l, l_align); | |
| ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_mat_id[GGML_TYPE_Q4_K]->a_m, "matmul_id_q4_k_f32_aligned_m", matmul_id_q4_k_f32_aligned_len, matmul_id_q4_k_f32_aligned_data, "main", 4, sizeof(vk_mat_mat_push_constants), m_wg_denoms, warptile_mmq_m, m_align); | |
| ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_mat_id[GGML_TYPE_Q4_K]->a_s, "matmul_id_q4_k_f32_aligned_s", matmul_id_q4_k_f32_aligned_len, matmul_id_q4_k_f32_aligned_data, "main", 4, sizeof(vk_mat_mat_push_constants), s_wg_denoms, warptile_mmq_s, s_align); | |
| ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_mat_id[GGML_TYPE_Q5_K]->l, "matmul_id_q5_k_f32_l", matmul_id_q5_k_f32_len, matmul_id_q5_k_f32_data, "main", 4, sizeof(vk_mat_mat_push_constants), l_wg_denoms, warptile_mmq_l, l_align); | |
| ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_mat_id[GGML_TYPE_Q5_K]->m, "matmul_id_q5_k_f32_m", matmul_id_q5_k_f32_len, matmul_id_q5_k_f32_data, "main", 4, sizeof(vk_mat_mat_push_constants), m_wg_denoms, warptile_mmq_m, m_align); | |
| ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_mat_id[GGML_TYPE_Q5_K]->s, "matmul_id_q5_k_f32_s", matmul_id_q5_k_f32_len, matmul_id_q5_k_f32_data, "main", 4, sizeof(vk_mat_mat_push_constants), s_wg_denoms, warptile_mmq_s, s_align); | |
| ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_mat_id[GGML_TYPE_Q5_K]->a_l, "matmul_id_q5_k_f32_aligned_l", matmul_id_q5_k_f32_aligned_len, matmul_id_q5_k_f32_aligned_data, "main", 4, sizeof(vk_mat_mat_push_constants), l_wg_denoms, warptile_mmq_l, l_align); | |
| ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_mat_id[GGML_TYPE_Q5_K]->a_m, "matmul_id_q5_k_f32_aligned_m", matmul_id_q5_k_f32_aligned_len, matmul_id_q5_k_f32_aligned_data, "main", 4, sizeof(vk_mat_mat_push_constants), m_wg_denoms, warptile_mmq_m, m_align); | |
| ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_mat_id[GGML_TYPE_Q5_K]->a_s, "matmul_id_q5_k_f32_aligned_s", matmul_id_q5_k_f32_aligned_len, matmul_id_q5_k_f32_aligned_data, "main", 4, sizeof(vk_mat_mat_push_constants), s_wg_denoms, warptile_mmq_s, s_align); | |
| ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_mat_id[GGML_TYPE_Q6_K]->l, "matmul_id_q6_k_f32_l", matmul_id_q6_k_f32_len, matmul_id_q6_k_f32_data, "main", 4, sizeof(vk_mat_mat_push_constants), l_wg_denoms, warptile_mmq_l, l_align); | |
| ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_mat_id[GGML_TYPE_Q6_K]->m, "matmul_id_q6_k_f32_m", matmul_id_q6_k_f32_len, matmul_id_q6_k_f32_data, "main", 4, sizeof(vk_mat_mat_push_constants), m_wg_denoms, warptile_mmq_m, m_align); | |
| ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_mat_id[GGML_TYPE_Q6_K]->s, "matmul_id_q6_k_f32_s", matmul_id_q6_k_f32_len, matmul_id_q6_k_f32_data, "main", 4, sizeof(vk_mat_mat_push_constants), s_wg_denoms, warptile_mmq_s, s_align); | |
| ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_mat_id[GGML_TYPE_Q6_K]->a_l, "matmul_id_q6_k_f32_aligned_l", matmul_id_q6_k_f32_aligned_len, matmul_id_q6_k_f32_aligned_data, "main", 4, sizeof(vk_mat_mat_push_constants), l_wg_denoms, warptile_mmq_l, l_align); | |
| ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_mat_id[GGML_TYPE_Q6_K]->a_m, "matmul_id_q6_k_f32_aligned_m", matmul_id_q6_k_f32_aligned_len, matmul_id_q6_k_f32_aligned_data, "main", 4, sizeof(vk_mat_mat_push_constants), m_wg_denoms, warptile_mmq_m, m_align); | |
| ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_mat_id[GGML_TYPE_Q6_K]->a_s, "matmul_id_q6_k_f32_aligned_s", matmul_id_q6_k_f32_aligned_len, matmul_id_q6_k_f32_aligned_data, "main", 4, sizeof(vk_mat_mat_push_constants), s_wg_denoms, warptile_mmq_s, s_align);*/ | |
| } else { | |
| ggml_vk_create_pipeline(ctx, ctx->device->pipeline_matmul_f32->l, "matmul_f32_l", matmul_f32_fp32_len, matmul_f32_fp32_data, "main", 3, sizeof(vk_mat_mat_push_constants), l_wg_denoms, warptile_l, 1); | |
| ggml_vk_create_pipeline(ctx, ctx->device->pipeline_matmul_f32->m, "matmul_f32_m", matmul_f32_fp32_len, matmul_f32_fp32_data, "main", 3, sizeof(vk_mat_mat_push_constants), m_wg_denoms, warptile_m, 1); | |
| ggml_vk_create_pipeline(ctx, ctx->device->pipeline_matmul_f32->s, "matmul_f32_s", matmul_f32_fp32_len, matmul_f32_fp32_data, "main", 3, sizeof(vk_mat_mat_push_constants), s_wg_denoms, warptile_s, 1); | |
| ggml_vk_create_pipeline(ctx, ctx->device->pipeline_matmul_f32->a_l, "matmul_f32_aligned_l", matmul_f32_aligned_fp32_len, matmul_f32_aligned_fp32_data, "main", 3, sizeof(vk_mat_mat_push_constants), l_wg_denoms, warptile_l, l_align); | |
| ggml_vk_create_pipeline(ctx, ctx->device->pipeline_matmul_f32->a_m, "matmul_f32_aligned_m", matmul_f32_aligned_fp32_len, matmul_f32_aligned_fp32_data, "main", 3, sizeof(vk_mat_mat_push_constants), m_wg_denoms, warptile_m, m_align); | |
| ggml_vk_create_pipeline(ctx, ctx->device->pipeline_matmul_f32->a_s, "matmul_f32_aligned_s", matmul_f32_aligned_fp32_len, matmul_f32_aligned_fp32_data, "main", 3, sizeof(vk_mat_mat_push_constants), s_wg_denoms, warptile_s, s_align); | |
| ggml_vk_create_pipeline(ctx, ctx->device->pipeline_matmul_f16->l, "matmul_f16_l", matmul_f16_fp32_len, matmul_f16_fp32_data, "main", 3, sizeof(vk_mat_mat_push_constants), l_wg_denoms, warptile_l, 1); | |
| ggml_vk_create_pipeline(ctx, ctx->device->pipeline_matmul_f16->m, "matmul_f16_m", matmul_f16_fp32_len, matmul_f16_fp32_data, "main", 3, sizeof(vk_mat_mat_push_constants), m_wg_denoms, warptile_m, 1); | |
| ggml_vk_create_pipeline(ctx, ctx->device->pipeline_matmul_f16->s, "matmul_f16_s", matmul_f16_fp32_len, matmul_f16_fp32_data, "main", 3, sizeof(vk_mat_mat_push_constants), s_wg_denoms, warptile_s, 1); | |
| ggml_vk_create_pipeline(ctx, ctx->device->pipeline_matmul_f16->a_l, "matmul_f16_aligned_l", matmul_f16_aligned_fp32_len, matmul_f16_aligned_fp32_data, "main", 3, sizeof(vk_mat_mat_push_constants), l_wg_denoms, warptile_l, l_align); | |
| ggml_vk_create_pipeline(ctx, ctx->device->pipeline_matmul_f16->a_m, "matmul_f16_aligned_m", matmul_f16_aligned_fp32_len, matmul_f16_aligned_fp32_data, "main", 3, sizeof(vk_mat_mat_push_constants), m_wg_denoms, warptile_m, m_align); | |
| ggml_vk_create_pipeline(ctx, ctx->device->pipeline_matmul_f16->a_s, "matmul_f16_aligned_s", matmul_f16_aligned_fp32_len, matmul_f16_aligned_fp32_data, "main", 3, sizeof(vk_mat_mat_push_constants), s_wg_denoms, warptile_s, s_align); | |
| ggml_vk_create_pipeline(ctx, ctx->device->pipeline_matmul_f16_f32->l, "matmul_f16_f32_l", matmul_f16_f32_fp32_len, matmul_f16_f32_fp32_data, "main", 3, sizeof(vk_mat_mat_push_constants), l_wg_denoms, warptile_l, 1); | |
| ggml_vk_create_pipeline(ctx, ctx->device->pipeline_matmul_f16_f32->m, "matmul_f16_f32_m", matmul_f16_f32_fp32_len, matmul_f16_f32_fp32_data, "main", 3, sizeof(vk_mat_mat_push_constants), m_wg_denoms, warptile_m, 1); | |
| ggml_vk_create_pipeline(ctx, ctx->device->pipeline_matmul_f16_f32->s, "matmul_f16_f32_s", matmul_f16_f32_fp32_len, matmul_f16_f32_fp32_data, "main", 3, sizeof(vk_mat_mat_push_constants), s_wg_denoms, warptile_s, 1); | |
| ggml_vk_create_pipeline(ctx, ctx->device->pipeline_matmul_f16_f32->a_l, "matmul_f16_f32_aligned_l", matmul_f16_f32_aligned_fp32_len, matmul_f16_f32_aligned_fp32_data, "main", 3, sizeof(vk_mat_mat_push_constants), l_wg_denoms, warptile_l, l_align); | |
| ggml_vk_create_pipeline(ctx, ctx->device->pipeline_matmul_f16_f32->a_m, "matmul_f16_f32_aligned_m", matmul_f16_f32_aligned_fp32_len, matmul_f16_f32_aligned_fp32_data, "main", 3, sizeof(vk_mat_mat_push_constants), m_wg_denoms, warptile_m, m_align); | |
| ggml_vk_create_pipeline(ctx, ctx->device->pipeline_matmul_f16_f32->a_s, "matmul_f16_f32_aligned_s", matmul_f16_f32_aligned_fp32_len, matmul_f16_f32_aligned_fp32_data, "main", 3, sizeof(vk_mat_mat_push_constants), s_wg_denoms, warptile_s, s_align); | |
| ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_mat[GGML_TYPE_Q4_0]->l, "matmul_q4_0_f32_l", matmul_q4_0_f32_fp32_len, matmul_q4_0_f32_fp32_data, "main", 3, sizeof(vk_mat_mat_push_constants), l_wg_denoms, warptile_mmq_l, l_align); | |
| ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_mat[GGML_TYPE_Q4_0]->m, "matmul_q4_0_f32_m", matmul_q4_0_f32_fp32_len, matmul_q4_0_f32_fp32_data, "main", 3, sizeof(vk_mat_mat_push_constants), m_wg_denoms, warptile_mmq_m, m_align); | |
| ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_mat[GGML_TYPE_Q4_0]->s, "matmul_q4_0_f32_s", matmul_q4_0_f32_fp32_len, matmul_q4_0_f32_fp32_data, "main", 3, sizeof(vk_mat_mat_push_constants), s_wg_denoms, warptile_mmq_s, s_align); | |
| ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_mat[GGML_TYPE_Q4_0]->a_l, "matmul_q4_0_f32_aligned_l", matmul_q4_0_f32_aligned_fp32_len, matmul_q4_0_f32_aligned_fp32_data, "main", 3, sizeof(vk_mat_mat_push_constants), l_wg_denoms, warptile_mmq_l, l_align); | |
| ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_mat[GGML_TYPE_Q4_0]->a_m, "matmul_q4_0_f32_aligned_m", matmul_q4_0_f32_aligned_fp32_len, matmul_q4_0_f32_aligned_fp32_data, "main", 3, sizeof(vk_mat_mat_push_constants), m_wg_denoms, warptile_mmq_m, m_align); | |
| ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_mat[GGML_TYPE_Q4_0]->a_s, "matmul_q4_0_f32_aligned_s", matmul_q4_0_f32_aligned_fp32_len, matmul_q4_0_f32_aligned_fp32_data, "main", 3, sizeof(vk_mat_mat_push_constants), s_wg_denoms, warptile_mmq_s, s_align); | |
| ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_mat[GGML_TYPE_Q4_1]->l, "matmul_q4_1_f32_l", matmul_q4_1_f32_fp32_len, matmul_q4_1_f32_fp32_data, "main", 3, sizeof(vk_mat_mat_push_constants), l_wg_denoms, warptile_mmq_l, l_align); | |
| ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_mat[GGML_TYPE_Q4_1]->m, "matmul_q4_1_f32_m", matmul_q4_1_f32_fp32_len, matmul_q4_1_f32_fp32_data, "main", 3, sizeof(vk_mat_mat_push_constants), m_wg_denoms, warptile_mmq_m, m_align); | |
| ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_mat[GGML_TYPE_Q4_1]->s, "matmul_q4_1_f32_s", matmul_q4_1_f32_fp32_len, matmul_q4_1_f32_fp32_data, "main", 3, sizeof(vk_mat_mat_push_constants), s_wg_denoms, warptile_mmq_s, s_align); | |
| ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_mat[GGML_TYPE_Q4_1]->a_l, "matmul_q4_1_f32_aligned_l", matmul_q4_1_f32_aligned_fp32_len, matmul_q4_1_f32_aligned_fp32_data, "main", 3, sizeof(vk_mat_mat_push_constants), l_wg_denoms, warptile_mmq_l, l_align); | |
| ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_mat[GGML_TYPE_Q4_1]->a_m, "matmul_q4_1_f32_aligned_m", matmul_q4_1_f32_aligned_fp32_len, matmul_q4_1_f32_aligned_fp32_data, "main", 3, sizeof(vk_mat_mat_push_constants), m_wg_denoms, warptile_mmq_m, m_align); | |
| ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_mat[GGML_TYPE_Q4_1]->a_s, "matmul_q4_1_f32_aligned_s", matmul_q4_1_f32_aligned_fp32_len, matmul_q4_1_f32_aligned_fp32_data, "main", 3, sizeof(vk_mat_mat_push_constants), s_wg_denoms, warptile_mmq_s, s_align); | |
| ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_mat[GGML_TYPE_Q5_0]->l, "matmul_q5_0_f32_l", matmul_q5_0_f32_fp32_len, matmul_q5_0_f32_fp32_data, "main", 3, sizeof(vk_mat_mat_push_constants), l_wg_denoms, warptile_mmq_l, l_align); | |
| ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_mat[GGML_TYPE_Q5_0]->m, "matmul_q5_0_f32_m", matmul_q5_0_f32_fp32_len, matmul_q5_0_f32_fp32_data, "main", 3, sizeof(vk_mat_mat_push_constants), m_wg_denoms, warptile_mmq_m, m_align); | |
| ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_mat[GGML_TYPE_Q5_0]->s, "matmul_q5_0_f32_s", matmul_q5_0_f32_fp32_len, matmul_q5_0_f32_fp32_data, "main", 3, sizeof(vk_mat_mat_push_constants), s_wg_denoms, warptile_mmq_s, s_align); | |
| ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_mat[GGML_TYPE_Q5_0]->a_l, "matmul_q5_0_f32_aligned_l", matmul_q5_0_f32_aligned_fp32_len, matmul_q5_0_f32_aligned_fp32_data, "main", 3, sizeof(vk_mat_mat_push_constants), l_wg_denoms, warptile_mmq_l, l_align); | |
| ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_mat[GGML_TYPE_Q5_0]->a_m, "matmul_q5_0_f32_aligned_m", matmul_q5_0_f32_aligned_fp32_len, matmul_q5_0_f32_aligned_fp32_data, "main", 3, sizeof(vk_mat_mat_push_constants), m_wg_denoms, warptile_mmq_m, m_align); | |
| ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_mat[GGML_TYPE_Q5_0]->a_s, "matmul_q5_0_f32_aligned_s", matmul_q5_0_f32_aligned_fp32_len, matmul_q5_0_f32_aligned_fp32_data, "main", 3, sizeof(vk_mat_mat_push_constants), s_wg_denoms, warptile_mmq_s, s_align); | |
| ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_mat[GGML_TYPE_Q5_1]->l, "matmul_q5_1_f32_l", matmul_q5_1_f32_fp32_len, matmul_q5_1_f32_fp32_data, "main", 3, sizeof(vk_mat_mat_push_constants), l_wg_denoms, warptile_mmq_l, l_align); | |
| ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_mat[GGML_TYPE_Q5_1]->m, "matmul_q5_1_f32_m", matmul_q5_1_f32_fp32_len, matmul_q5_1_f32_fp32_data, "main", 3, sizeof(vk_mat_mat_push_constants), m_wg_denoms, warptile_mmq_m, m_align); | |
| ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_mat[GGML_TYPE_Q5_1]->s, "matmul_q5_1_f32_s", matmul_q5_1_f32_fp32_len, matmul_q5_1_f32_fp32_data, "main", 3, sizeof(vk_mat_mat_push_constants), s_wg_denoms, warptile_mmq_s, s_align); | |
| ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_mat[GGML_TYPE_Q5_1]->a_l, "matmul_q5_1_f32_aligned_l", matmul_q5_1_f32_aligned_fp32_len, matmul_q5_1_f32_aligned_fp32_data, "main", 3, sizeof(vk_mat_mat_push_constants), l_wg_denoms, warptile_mmq_l, l_align); | |
| ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_mat[GGML_TYPE_Q5_1]->a_m, "matmul_q5_1_f32_aligned_m", matmul_q5_1_f32_aligned_fp32_len, matmul_q5_1_f32_aligned_fp32_data, "main", 3, sizeof(vk_mat_mat_push_constants), m_wg_denoms, warptile_mmq_m, m_align); | |
| ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_mat[GGML_TYPE_Q5_1]->a_s, "matmul_q5_1_f32_aligned_s", matmul_q5_1_f32_aligned_fp32_len, matmul_q5_1_f32_aligned_fp32_data, "main", 3, sizeof(vk_mat_mat_push_constants), s_wg_denoms, warptile_mmq_s, s_align); | |
| ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_mat[GGML_TYPE_Q8_0]->l, "matmul_q8_0_f32_l", matmul_q8_0_f32_fp32_len, matmul_q8_0_f32_fp32_data, "main", 3, sizeof(vk_mat_mat_push_constants), l_wg_denoms, warptile_mmq_l, l_align); | |
| ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_mat[GGML_TYPE_Q8_0]->m, "matmul_q8_0_f32_m", matmul_q8_0_f32_fp32_len, matmul_q8_0_f32_fp32_data, "main", 3, sizeof(vk_mat_mat_push_constants), m_wg_denoms, warptile_mmq_m, m_align); | |
| ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_mat[GGML_TYPE_Q8_0]->s, "matmul_q8_0_f32_s", matmul_q8_0_f32_fp32_len, matmul_q8_0_f32_fp32_data, "main", 3, sizeof(vk_mat_mat_push_constants), s_wg_denoms, warptile_mmq_s, s_align); | |
| ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_mat[GGML_TYPE_Q8_0]->a_l, "matmul_q8_0_f32_aligned_l", matmul_q8_0_f32_aligned_fp32_len, matmul_q8_0_f32_aligned_fp32_data, "main", 3, sizeof(vk_mat_mat_push_constants), l_wg_denoms, warptile_mmq_l, l_align); | |
| ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_mat[GGML_TYPE_Q8_0]->a_m, "matmul_q8_0_f32_aligned_m", matmul_q8_0_f32_aligned_fp32_len, matmul_q8_0_f32_aligned_fp32_data, "main", 3, sizeof(vk_mat_mat_push_constants), m_wg_denoms, warptile_mmq_m, m_align); | |
| ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_mat[GGML_TYPE_Q8_0]->a_s, "matmul_q8_0_f32_aligned_s", matmul_q8_0_f32_aligned_fp32_len, matmul_q8_0_f32_aligned_fp32_data, "main", 3, sizeof(vk_mat_mat_push_constants), s_wg_denoms, warptile_mmq_s, s_align); | |
| ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_mat[GGML_TYPE_Q2_K]->l, "matmul_q2_k_f32_l", matmul_q2_k_f32_fp32_len, matmul_q2_k_f32_fp32_data, "main", 3, sizeof(vk_mat_mat_push_constants), l_wg_denoms, warptile_mmq_l, l_align); | |
| ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_mat[GGML_TYPE_Q2_K]->m, "matmul_q2_k_f32_m", matmul_q2_k_f32_fp32_len, matmul_q2_k_f32_fp32_data, "main", 3, sizeof(vk_mat_mat_push_constants), m_wg_denoms, warptile_mmq_m, m_align); | |
| ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_mat[GGML_TYPE_Q2_K]->s, "matmul_q2_k_f32_s", matmul_q2_k_f32_fp32_len, matmul_q2_k_f32_fp32_data, "main", 3, sizeof(vk_mat_mat_push_constants), s_wg_denoms, warptile_mmq_s, s_align); | |
| ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_mat[GGML_TYPE_Q2_K]->a_l, "matmul_q2_k_f32_aligned_l", matmul_q2_k_f32_aligned_fp32_len, matmul_q2_k_f32_aligned_fp32_data, "main", 3, sizeof(vk_mat_mat_push_constants), l_wg_denoms, warptile_mmq_l, l_align); | |
| ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_mat[GGML_TYPE_Q2_K]->a_m, "matmul_q2_k_f32_aligned_m", matmul_q2_k_f32_aligned_fp32_len, matmul_q2_k_f32_aligned_fp32_data, "main", 3, sizeof(vk_mat_mat_push_constants), m_wg_denoms, warptile_mmq_m, m_align); | |
| ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_mat[GGML_TYPE_Q2_K]->a_s, "matmul_q2_k_f32_aligned_s", matmul_q2_k_f32_aligned_fp32_len, matmul_q2_k_f32_aligned_fp32_data, "main", 3, sizeof(vk_mat_mat_push_constants), s_wg_denoms, warptile_mmq_s, s_align); | |
| ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_mat[GGML_TYPE_Q3_K]->l, "matmul_q3_k_f32_l", matmul_q3_k_f32_fp32_len, matmul_q3_k_f32_fp32_data, "main", 3, sizeof(vk_mat_mat_push_constants), l_wg_denoms, warptile_mmq_l, l_align); | |
| ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_mat[GGML_TYPE_Q3_K]->m, "matmul_q3_k_f32_m", matmul_q3_k_f32_fp32_len, matmul_q3_k_f32_fp32_data, "main", 3, sizeof(vk_mat_mat_push_constants), m_wg_denoms, warptile_mmq_m, m_align); | |
| ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_mat[GGML_TYPE_Q3_K]->s, "matmul_q3_k_f32_s", matmul_q3_k_f32_fp32_len, matmul_q3_k_f32_fp32_data, "main", 3, sizeof(vk_mat_mat_push_constants), s_wg_denoms, warptile_mmq_s, s_align); | |
| ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_mat[GGML_TYPE_Q3_K]->a_l, "matmul_q3_k_f32_aligned_l", matmul_q3_k_f32_aligned_fp32_len, matmul_q3_k_f32_aligned_fp32_data, "main", 3, sizeof(vk_mat_mat_push_constants), l_wg_denoms, warptile_mmq_l, l_align); | |
| ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_mat[GGML_TYPE_Q3_K]->a_m, "matmul_q3_k_f32_aligned_m", matmul_q3_k_f32_aligned_fp32_len, matmul_q3_k_f32_aligned_fp32_data, "main", 3, sizeof(vk_mat_mat_push_constants), m_wg_denoms, warptile_mmq_m, m_align); | |
| ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_mat[GGML_TYPE_Q3_K]->a_s, "matmul_q3_k_f32_aligned_s", matmul_q3_k_f32_aligned_fp32_len, matmul_q3_k_f32_aligned_fp32_data, "main", 3, sizeof(vk_mat_mat_push_constants), s_wg_denoms, warptile_mmq_s, s_align); | |
| ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_mat[GGML_TYPE_Q4_K]->l, "matmul_q4_k_f32_l", matmul_q4_k_f32_fp32_len, matmul_q4_k_f32_fp32_data, "main", 3, sizeof(vk_mat_mat_push_constants), l_wg_denoms, warptile_mmq_l, l_align); | |
| ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_mat[GGML_TYPE_Q4_K]->m, "matmul_q4_k_f32_m", matmul_q4_k_f32_fp32_len, matmul_q4_k_f32_fp32_data, "main", 3, sizeof(vk_mat_mat_push_constants), m_wg_denoms, warptile_mmq_m, m_align); | |
| ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_mat[GGML_TYPE_Q4_K]->s, "matmul_q4_k_f32_s", matmul_q4_k_f32_fp32_len, matmul_q4_k_f32_fp32_data, "main", 3, sizeof(vk_mat_mat_push_constants), s_wg_denoms, warptile_mmq_s, s_align); | |
| ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_mat[GGML_TYPE_Q4_K]->a_l, "matmul_q4_k_f32_aligned_l", matmul_q4_k_f32_aligned_fp32_len, matmul_q4_k_f32_aligned_fp32_data, "main", 3, sizeof(vk_mat_mat_push_constants), l_wg_denoms, warptile_mmq_l, l_align); | |
| ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_mat[GGML_TYPE_Q4_K]->a_m, "matmul_q4_k_f32_aligned_m", matmul_q4_k_f32_aligned_fp32_len, matmul_q4_k_f32_aligned_fp32_data, "main", 3, sizeof(vk_mat_mat_push_constants), m_wg_denoms, warptile_mmq_m, m_align); | |
| ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_mat[GGML_TYPE_Q4_K]->a_s, "matmul_q4_k_f32_aligned_s", matmul_q4_k_f32_aligned_fp32_len, matmul_q4_k_f32_aligned_fp32_data, "main", 3, sizeof(vk_mat_mat_push_constants), s_wg_denoms, warptile_mmq_s, s_align); | |
| ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_mat[GGML_TYPE_Q5_K]->l, "matmul_q5_k_f32_l", matmul_q5_k_f32_fp32_len, matmul_q5_k_f32_fp32_data, "main", 3, sizeof(vk_mat_mat_push_constants), l_wg_denoms, warptile_mmq_l, l_align); | |
| ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_mat[GGML_TYPE_Q5_K]->m, "matmul_q5_k_f32_m", matmul_q5_k_f32_fp32_len, matmul_q5_k_f32_fp32_data, "main", 3, sizeof(vk_mat_mat_push_constants), m_wg_denoms, warptile_mmq_m, m_align); | |
| ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_mat[GGML_TYPE_Q5_K]->s, "matmul_q5_k_f32_s", matmul_q5_k_f32_fp32_len, matmul_q5_k_f32_fp32_data, "main", 3, sizeof(vk_mat_mat_push_constants), s_wg_denoms, warptile_mmq_s, s_align); | |
| ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_mat[GGML_TYPE_Q5_K]->a_l, "matmul_q5_k_f32_aligned_l", matmul_q5_k_f32_aligned_fp32_len, matmul_q5_k_f32_aligned_fp32_data, "main", 3, sizeof(vk_mat_mat_push_constants), l_wg_denoms, warptile_mmq_l, l_align); | |
| ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_mat[GGML_TYPE_Q5_K]->a_m, "matmul_q5_k_f32_aligned_m", matmul_q5_k_f32_aligned_fp32_len, matmul_q5_k_f32_aligned_fp32_data, "main", 3, sizeof(vk_mat_mat_push_constants), m_wg_denoms, warptile_mmq_m, m_align); | |
| ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_mat[GGML_TYPE_Q5_K]->a_s, "matmul_q5_k_f32_aligned_s", matmul_q5_k_f32_aligned_fp32_len, matmul_q5_k_f32_aligned_fp32_data, "main", 3, sizeof(vk_mat_mat_push_constants), s_wg_denoms, warptile_mmq_s, s_align); | |
| ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_mat[GGML_TYPE_Q6_K]->l, "matmul_q6_k_f32_l", matmul_q6_k_f32_fp32_len, matmul_q6_k_f32_fp32_data, "main", 3, sizeof(vk_mat_mat_push_constants), l_wg_denoms, warptile_mmq_l, l_align); | |
| ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_mat[GGML_TYPE_Q6_K]->m, "matmul_q6_k_f32_m", matmul_q6_k_f32_fp32_len, matmul_q6_k_f32_fp32_data, "main", 3, sizeof(vk_mat_mat_push_constants), m_wg_denoms, warptile_mmq_m, m_align); | |
| ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_mat[GGML_TYPE_Q6_K]->s, "matmul_q6_k_f32_s", matmul_q6_k_f32_fp32_len, matmul_q6_k_f32_fp32_data, "main", 3, sizeof(vk_mat_mat_push_constants), s_wg_denoms, warptile_mmq_s, s_align); | |
| ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_mat[GGML_TYPE_Q6_K]->a_l, "matmul_q6_k_f32_aligned_l", matmul_q6_k_f32_aligned_fp32_len, matmul_q6_k_f32_aligned_fp32_data, "main", 3, sizeof(vk_mat_mat_push_constants), l_wg_denoms, warptile_mmq_l, l_align); | |
| ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_mat[GGML_TYPE_Q6_K]->a_m, "matmul_q6_k_f32_aligned_m", matmul_q6_k_f32_aligned_fp32_len, matmul_q6_k_f32_aligned_fp32_data, "main", 3, sizeof(vk_mat_mat_push_constants), m_wg_denoms, warptile_mmq_m, m_align); | |
| ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_mat[GGML_TYPE_Q6_K]->a_s, "matmul_q6_k_f32_aligned_s", matmul_q6_k_f32_aligned_fp32_len, matmul_q6_k_f32_aligned_fp32_data, "main", 3, sizeof(vk_mat_mat_push_constants), s_wg_denoms, warptile_mmq_s, s_align); | |
| /*ggml_vk_create_pipeline(ctx, ctx->device->pipeline_matmul_id_f32->l, "matmul_id_f32_l", matmul_id_f32_fp32_len, matmul_id_f32_fp32_data, "main", 4, sizeof(vk_mat_mat_push_constants), l_wg_denoms, warptile_l, 1); | |
| ggml_vk_create_pipeline(ctx, ctx->device->pipeline_matmul_id_f32->m, "matmul_id_f32_m", matmul_id_f32_fp32_len, matmul_id_f32_fp32_data, "main", 4, sizeof(vk_mat_mat_push_constants), m_wg_denoms, warptile_m, 1); | |
| ggml_vk_create_pipeline(ctx, ctx->device->pipeline_matmul_id_f32->s, "matmul_id_f32_s", matmul_id_f32_fp32_len, matmul_id_f32_fp32_data, "main", 4, sizeof(vk_mat_mat_push_constants), s_wg_denoms, warptile_s, 1); | |
| ggml_vk_create_pipeline(ctx, ctx->device->pipeline_matmul_id_f32->a_l, "matmul_id_f32_aligned_l", matmul_id_f32_aligned_fp32_len, matmul_id_f32_aligned_fp32_data, "main", 4, sizeof(vk_mat_mat_push_constants), l_wg_denoms, warptile_l, l_align); | |
| ggml_vk_create_pipeline(ctx, ctx->device->pipeline_matmul_id_f32->a_m, "matmul_id_f32_aligned_m", matmul_id_f32_aligned_fp32_len, matmul_id_f32_aligned_fp32_data, "main", 4, sizeof(vk_mat_mat_push_constants), m_wg_denoms, warptile_m, m_align); | |
| ggml_vk_create_pipeline(ctx, ctx->device->pipeline_matmul_id_f32->a_s, "matmul_id_f32_aligned_s", matmul_id_f32_aligned_fp32_len, matmul_id_f32_aligned_fp32_data, "main", 4, sizeof(vk_mat_mat_push_constants), s_wg_denoms, warptile_s, s_align); | |
| ggml_vk_create_pipeline(ctx, ctx->device->pipeline_matmul_id_f16->l, "matmul_id_f16_l", matmul_id_f16_fp32_len, matmul_id_f16_fp32_data, "main", 4, sizeof(vk_mat_mat_push_constants), l_wg_denoms, warptile_l, 1); | |
| ggml_vk_create_pipeline(ctx, ctx->device->pipeline_matmul_id_f16->m, "matmul_id_f16_m", matmul_id_f16_fp32_len, matmul_id_f16_fp32_data, "main", 4, sizeof(vk_mat_mat_push_constants), m_wg_denoms, warptile_m, 1); | |
| ggml_vk_create_pipeline(ctx, ctx->device->pipeline_matmul_id_f16->s, "matmul_id_f16_s", matmul_id_f16_fp32_len, matmul_id_f16_fp32_data, "main", 4, sizeof(vk_mat_mat_push_constants), s_wg_denoms, warptile_s, 1); | |
| ggml_vk_create_pipeline(ctx, ctx->device->pipeline_matmul_id_f16->a_l, "matmul_id_f16_aligned_l", matmul_id_f16_aligned_fp32_len, matmul_id_f16_aligned_fp32_data, "main", 4, sizeof(vk_mat_mat_push_constants), l_wg_denoms, warptile_l, l_align); | |
| ggml_vk_create_pipeline(ctx, ctx->device->pipeline_matmul_id_f16->a_m, "matmul_id_f16_aligned_m", matmul_id_f16_aligned_fp32_len, matmul_id_f16_aligned_fp32_data, "main", 4, sizeof(vk_mat_mat_push_constants), m_wg_denoms, warptile_m, m_align); | |
| ggml_vk_create_pipeline(ctx, ctx->device->pipeline_matmul_id_f16->a_s, "matmul_id_f16_aligned_s", matmul_id_f16_aligned_fp32_len, matmul_id_f16_aligned_fp32_data, "main", 4, sizeof(vk_mat_mat_push_constants), s_wg_denoms, warptile_s, s_align); | |
| ggml_vk_create_pipeline(ctx, ctx->device->pipeline_matmul_id_f16_f32->l, "matmul_id_f16_f32_l", matmul_id_f16_f32_fp32_len, matmul_id_f16_f32_fp32_data, "main", 4, sizeof(vk_mat_mat_push_constants), l_wg_denoms, warptile_l, 1); | |
| ggml_vk_create_pipeline(ctx, ctx->device->pipeline_matmul_id_f16_f32->m, "matmul_id_f16_f32_m", matmul_id_f16_f32_fp32_len, matmul_id_f16_f32_fp32_data, "main", 4, sizeof(vk_mat_mat_push_constants), m_wg_denoms, warptile_m, 1); | |
| ggml_vk_create_pipeline(ctx, ctx->device->pipeline_matmul_id_f16_f32->s, "matmul_id_f16_f32_s", matmul_id_f16_f32_fp32_len, matmul_id_f16_f32_fp32_data, "main", 4, sizeof(vk_mat_mat_push_constants), s_wg_denoms, warptile_s, 1); | |
| ggml_vk_create_pipeline(ctx, ctx->device->pipeline_matmul_id_f16_f32->a_l, "matmul_id_f16_f32_aligned_l", matmul_id_f16_f32_aligned_fp32_len, matmul_id_f16_f32_aligned_fp32_data, "main", 4, sizeof(vk_mat_mat_push_constants), l_wg_denoms, warptile_l, l_align); | |
| ggml_vk_create_pipeline(ctx, ctx->device->pipeline_matmul_id_f16_f32->a_m, "matmul_id_f16_f32_aligned_m", matmul_id_f16_f32_aligned_fp32_len, matmul_id_f16_f32_aligned_fp32_data, "main", 4, sizeof(vk_mat_mat_push_constants), m_wg_denoms, warptile_m, m_align); | |
| ggml_vk_create_pipeline(ctx, ctx->device->pipeline_matmul_id_f16_f32->a_s, "matmul_id_f16_f32_aligned_s", matmul_id_f16_f32_aligned_fp32_len, matmul_id_f16_f32_aligned_fp32_data, "main", 4, sizeof(vk_mat_mat_push_constants), s_wg_denoms, warptile_s, s_align); | |
| ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_mat_id[GGML_TYPE_Q4_0]->l, "matmul_id_q4_0_f32_l", matmul_id_q4_0_f32_fp32_len, matmul_id_q4_0_f32_fp32_data, "main", 4, sizeof(vk_mat_mat_push_constants), l_wg_denoms, warptile_mmq_l, l_align); | |
| ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_mat_id[GGML_TYPE_Q4_0]->m, "matmul_id_q4_0_f32_m", matmul_id_q4_0_f32_fp32_len, matmul_id_q4_0_f32_fp32_data, "main", 4, sizeof(vk_mat_mat_push_constants), m_wg_denoms, warptile_mmq_m, m_align); | |
| ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_mat_id[GGML_TYPE_Q4_0]->s, "matmul_id_q4_0_f32_s", matmul_id_q4_0_f32_fp32_len, matmul_id_q4_0_f32_fp32_data, "main", 4, sizeof(vk_mat_mat_push_constants), s_wg_denoms, warptile_mmq_s, s_align); | |
| ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_mat_id[GGML_TYPE_Q4_0]->a_l, "matmul_id_q4_0_f32_aligned_l", matmul_id_q4_0_f32_aligned_fp32_len, matmul_id_q4_0_f32_aligned_fp32_data, "main", 4, sizeof(vk_mat_mat_push_constants), l_wg_denoms, warptile_mmq_l, l_align); | |
| ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_mat_id[GGML_TYPE_Q4_0]->a_m, "matmul_id_q4_0_f32_aligned_m", matmul_id_q4_0_f32_aligned_fp32_len, matmul_id_q4_0_f32_aligned_fp32_data, "main", 4, sizeof(vk_mat_mat_push_constants), m_wg_denoms, warptile_mmq_m, m_align); | |
| ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_mat_id[GGML_TYPE_Q4_0]->a_s, "matmul_id_q4_0_f32_aligned_s", matmul_id_q4_0_f32_aligned_fp32_len, matmul_id_q4_0_f32_aligned_fp32_data, "main", 4, sizeof(vk_mat_mat_push_constants), s_wg_denoms, warptile_mmq_s, s_align); | |
| ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_mat_id[GGML_TYPE_Q4_1]->l, "matmul_id_q4_0_f32_l", matmul_id_q4_1_f32_fp32_len, matmul_id_q4_1_f32_fp32_data, "main", 4, sizeof(vk_mat_mat_push_constants), l_wg_denoms, warptile_mmq_l, l_align); | |
| ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_mat_id[GGML_TYPE_Q4_1]->m, "matmul_id_q4_0_f32_m", matmul_id_q4_1_f32_fp32_len, matmul_id_q4_1_f32_fp32_data, "main", 4, sizeof(vk_mat_mat_push_constants), m_wg_denoms, warptile_mmq_m, m_align); | |
| ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_mat_id[GGML_TYPE_Q4_1]->s, "matmul_id_q4_0_f32_s", matmul_id_q4_1_f32_fp32_len, matmul_id_q4_1_f32_fp32_data, "main", 4, sizeof(vk_mat_mat_push_constants), s_wg_denoms, warptile_mmq_s, s_align); | |
| ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_mat_id[GGML_TYPE_Q4_1]->a_l, "matmul_id_q4_0_f32_aligned_l", matmul_id_q4_1_f32_aligned_fp32_len, matmul_id_q4_1_f32_aligned_fp32_data, "main", 4, sizeof(vk_mat_mat_push_constants), l_wg_denoms, warptile_mmq_l, l_align); | |
| ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_mat_id[GGML_TYPE_Q4_1]->a_m, "matmul_id_q4_0_f32_aligned_m", matmul_id_q4_1_f32_aligned_fp32_len, matmul_id_q4_1_f32_aligned_fp32_data, "main", 4, sizeof(vk_mat_mat_push_constants), m_wg_denoms, warptile_mmq_m, m_align); | |
| ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_mat_id[GGML_TYPE_Q4_1]->a_s, "matmul_id_q4_0_f32_aligned_s", matmul_id_q4_1_f32_aligned_fp32_len, matmul_id_q4_1_f32_aligned_fp32_data, "main", 4, sizeof(vk_mat_mat_push_constants), s_wg_denoms, warptile_mmq_s, s_align); | |
| ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_mat_id[GGML_TYPE_Q5_0]->l, "matmul_id_q5_0_f32_l", matmul_id_q5_0_f32_fp32_len, matmul_id_q5_0_f32_fp32_data, "main", 4, sizeof(vk_mat_mat_push_constants), l_wg_denoms, warptile_mmq_l, l_align); | |
| ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_mat_id[GGML_TYPE_Q5_0]->m, "matmul_id_q5_0_f32_m", matmul_id_q5_0_f32_fp32_len, matmul_id_q5_0_f32_fp32_data, "main", 4, sizeof(vk_mat_mat_push_constants), m_wg_denoms, warptile_mmq_m, m_align); | |
| ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_mat_id[GGML_TYPE_Q5_0]->s, "matmul_id_q5_0_f32_s", matmul_id_q5_0_f32_fp32_len, matmul_id_q5_0_f32_fp32_data, "main", 4, sizeof(vk_mat_mat_push_constants), s_wg_denoms, warptile_mmq_s, s_align); | |
| ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_mat_id[GGML_TYPE_Q5_0]->a_l, "matmul_id_q5_0_f32_aligned_l", matmul_id_q5_0_f32_aligned_fp32_len, matmul_id_q5_0_f32_aligned_fp32_data, "main", 4, sizeof(vk_mat_mat_push_constants), l_wg_denoms, warptile_mmq_l, l_align); | |
| ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_mat_id[GGML_TYPE_Q5_0]->a_m, "matmul_id_q5_0_f32_aligned_m", matmul_id_q5_0_f32_aligned_fp32_len, matmul_id_q5_0_f32_aligned_fp32_data, "main", 4, sizeof(vk_mat_mat_push_constants), m_wg_denoms, warptile_mmq_m, m_align); | |
| ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_mat_id[GGML_TYPE_Q5_0]->a_s, "matmul_id_q5_0_f32_aligned_s", matmul_id_q5_0_f32_aligned_fp32_len, matmul_id_q5_0_f32_aligned_fp32_data, "main", 4, sizeof(vk_mat_mat_push_constants), s_wg_denoms, warptile_mmq_s, s_align); | |
| ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_mat_id[GGML_TYPE_Q5_1]->l, "matmul_id_q5_1_f32_l", matmul_id_q5_1_f32_fp32_len, matmul_id_q5_1_f32_fp32_data, "main", 4, sizeof(vk_mat_mat_push_constants), l_wg_denoms, warptile_mmq_l, l_align); | |
| ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_mat_id[GGML_TYPE_Q5_1]->m, "matmul_id_q5_1_f32_m", matmul_id_q5_1_f32_fp32_len, matmul_id_q5_1_f32_fp32_data, "main", 4, sizeof(vk_mat_mat_push_constants), m_wg_denoms, warptile_mmq_m, m_align); | |
| ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_mat_id[GGML_TYPE_Q5_1]->s, "matmul_id_q5_1_f32_s", matmul_id_q5_1_f32_fp32_len, matmul_id_q5_1_f32_fp32_data, "main", 4, sizeof(vk_mat_mat_push_constants), s_wg_denoms, warptile_mmq_s, s_align); | |
| ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_mat_id[GGML_TYPE_Q5_1]->a_l, "matmul_id_q5_1_f32_aligned_l", matmul_id_q5_1_f32_aligned_fp32_len, matmul_id_q5_1_f32_aligned_fp32_data, "main", 4, sizeof(vk_mat_mat_push_constants), l_wg_denoms, warptile_mmq_l, l_align); | |
| ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_mat_id[GGML_TYPE_Q5_1]->a_m, "matmul_id_q5_1_f32_aligned_m", matmul_id_q5_1_f32_aligned_fp32_len, matmul_id_q5_1_f32_aligned_fp32_data, "main", 4, sizeof(vk_mat_mat_push_constants), m_wg_denoms, warptile_mmq_m, m_align); | |
| ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_mat_id[GGML_TYPE_Q5_1]->a_s, "matmul_id_q5_1_f32_aligned_s", matmul_id_q5_1_f32_aligned_fp32_len, matmul_id_q5_1_f32_aligned_fp32_data, "main", 4, sizeof(vk_mat_mat_push_constants), s_wg_denoms, warptile_mmq_s, s_align); | |
| ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_mat_id[GGML_TYPE_Q8_0]->l, "matmul_id_q8_0_f32_l", matmul_id_q8_0_f32_fp32_len, matmul_id_q8_0_f32_fp32_data, "main", 4, sizeof(vk_mat_mat_push_constants), l_wg_denoms, warptile_mmq_l, l_align); | |
| ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_mat_id[GGML_TYPE_Q8_0]->m, "matmul_id_q8_0_f32_m", matmul_id_q8_0_f32_fp32_len, matmul_id_q8_0_f32_fp32_data, "main", 4, sizeof(vk_mat_mat_push_constants), m_wg_denoms, warptile_mmq_m, m_align); | |
| ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_mat_id[GGML_TYPE_Q8_0]->s, "matmul_id_q8_0_f32_s", matmul_id_q8_0_f32_fp32_len, matmul_id_q8_0_f32_fp32_data, "main", 4, sizeof(vk_mat_mat_push_constants), s_wg_denoms, warptile_mmq_s, s_align); | |
| ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_mat_id[GGML_TYPE_Q8_0]->a_l, "matmul_id_q8_0_f32_aligned_l", matmul_id_q8_0_f32_aligned_fp32_len, matmul_id_q8_0_f32_aligned_fp32_data, "main", 4, sizeof(vk_mat_mat_push_constants), l_wg_denoms, warptile_mmq_l, l_align); | |
| ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_mat_id[GGML_TYPE_Q8_0]->a_m, "matmul_id_q8_0_f32_aligned_m", matmul_id_q8_0_f32_aligned_fp32_len, matmul_id_q8_0_f32_aligned_fp32_data, "main", 4, sizeof(vk_mat_mat_push_constants), m_wg_denoms, warptile_mmq_m, m_align); | |
| ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_mat_id[GGML_TYPE_Q8_0]->a_s, "matmul_id_q8_0_f32_aligned_s", matmul_id_q8_0_f32_aligned_fp32_len, matmul_id_q8_0_f32_aligned_fp32_data, "main", 4, sizeof(vk_mat_mat_push_constants), s_wg_denoms, warptile_mmq_s, s_align); | |
| ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_mat_id[GGML_TYPE_Q2_K]->l, "matmul_id_q2_k_f32_l", matmul_id_q2_k_f32_fp32_len, matmul_id_q2_k_f32_fp32_data, "main", 4, sizeof(vk_mat_mat_push_constants), l_wg_denoms, warptile_mmq_l, l_align); | |
| ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_mat_id[GGML_TYPE_Q2_K]->m, "matmul_id_q2_k_f32_m", matmul_id_q2_k_f32_fp32_len, matmul_id_q2_k_f32_fp32_data, "main", 4, sizeof(vk_mat_mat_push_constants), m_wg_denoms, warptile_mmq_m, m_align); | |
| ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_mat_id[GGML_TYPE_Q2_K]->s, "matmul_id_q2_k_f32_s", matmul_id_q2_k_f32_fp32_len, matmul_id_q2_k_f32_fp32_data, "main", 4, sizeof(vk_mat_mat_push_constants), s_wg_denoms, warptile_mmq_s, s_align); | |
| ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_mat_id[GGML_TYPE_Q2_K]->a_l, "matmul_id_q2_k_f32_aligned_l", matmul_id_q2_k_f32_aligned_fp32_len, matmul_id_q2_k_f32_aligned_fp32_data, "main", 4, sizeof(vk_mat_mat_push_constants), l_wg_denoms, warptile_mmq_l, l_align); | |
| ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_mat_id[GGML_TYPE_Q2_K]->a_m, "matmul_id_q2_k_f32_aligned_m", matmul_id_q2_k_f32_aligned_fp32_len, matmul_id_q2_k_f32_aligned_fp32_data, "main", 4, sizeof(vk_mat_mat_push_constants), m_wg_denoms, warptile_mmq_m, m_align); | |
| ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_mat_id[GGML_TYPE_Q2_K]->a_s, "matmul_id_q2_k_f32_aligned_s", matmul_id_q2_k_f32_aligned_fp32_len, matmul_id_q2_k_f32_aligned_fp32_data, "main", 4, sizeof(vk_mat_mat_push_constants), s_wg_denoms, warptile_mmq_s, s_align); | |
| ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_mat_id[GGML_TYPE_Q3_K]->l, "matmul_id_q3_k_f32_l", matmul_id_q3_k_f32_fp32_len, matmul_id_q3_k_f32_fp32_data, "main", 4, sizeof(vk_mat_mat_push_constants), l_wg_denoms, warptile_mmq_l, l_align); | |
| ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_mat_id[GGML_TYPE_Q3_K]->m, "matmul_id_q3_k_f32_m", matmul_id_q3_k_f32_fp32_len, matmul_id_q3_k_f32_fp32_data, "main", 4, sizeof(vk_mat_mat_push_constants), m_wg_denoms, warptile_mmq_m, m_align); | |
| ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_mat_id[GGML_TYPE_Q3_K]->s, "matmul_id_q3_k_f32_s", matmul_id_q3_k_f32_fp32_len, matmul_id_q3_k_f32_fp32_data, "main", 4, sizeof(vk_mat_mat_push_constants), s_wg_denoms, warptile_mmq_s, s_align); | |
| ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_mat_id[GGML_TYPE_Q3_K]->a_l, "matmul_id_q3_k_f32_aligned_l", matmul_id_q3_k_f32_aligned_fp32_len, matmul_id_q3_k_f32_aligned_fp32_data, "main", 4, sizeof(vk_mat_mat_push_constants), l_wg_denoms, warptile_mmq_l, l_align); | |
| ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_mat_id[GGML_TYPE_Q3_K]->a_m, "matmul_id_q3_k_f32_aligned_m", matmul_id_q3_k_f32_aligned_fp32_len, matmul_id_q3_k_f32_aligned_fp32_data, "main", 4, sizeof(vk_mat_mat_push_constants), m_wg_denoms, warptile_mmq_m, m_align); | |
| ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_mat_id[GGML_TYPE_Q3_K]->a_s, "matmul_id_q3_k_f32_aligned_s", matmul_id_q3_k_f32_aligned_fp32_len, matmul_id_q3_k_f32_aligned_fp32_data, "main", 4, sizeof(vk_mat_mat_push_constants), s_wg_denoms, warptile_mmq_s, s_align); | |
| ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_mat_id[GGML_TYPE_Q4_K]->l, "matmul_id_q4_k_f32_l", matmul_id_q4_k_f32_fp32_len, matmul_id_q4_k_f32_fp32_data, "main", 4, sizeof(vk_mat_mat_push_constants), l_wg_denoms, warptile_mmq_l, l_align); | |
| ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_mat_id[GGML_TYPE_Q4_K]->m, "matmul_id_q4_k_f32_m", matmul_id_q4_k_f32_fp32_len, matmul_id_q4_k_f32_fp32_data, "main", 4, sizeof(vk_mat_mat_push_constants), m_wg_denoms, warptile_mmq_m, m_align); | |
| ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_mat_id[GGML_TYPE_Q4_K]->s, "matmul_id_q4_k_f32_s", matmul_id_q4_k_f32_fp32_len, matmul_id_q4_k_f32_fp32_data, "main", 4, sizeof(vk_mat_mat_push_constants), s_wg_denoms, warptile_mmq_s, s_align); | |
| ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_mat_id[GGML_TYPE_Q4_K]->a_l, "matmul_id_q4_k_f32_aligned_l", matmul_id_q4_k_f32_aligned_fp32_len, matmul_id_q4_k_f32_aligned_fp32_data, "main", 4, sizeof(vk_mat_mat_push_constants), l_wg_denoms, warptile_mmq_l, l_align); | |
| ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_mat_id[GGML_TYPE_Q4_K]->a_m, "matmul_id_q4_k_f32_aligned_m", matmul_id_q4_k_f32_aligned_fp32_len, matmul_id_q4_k_f32_aligned_fp32_data, "main", 4, sizeof(vk_mat_mat_push_constants), m_wg_denoms, warptile_mmq_m, m_align); | |
| ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_mat_id[GGML_TYPE_Q4_K]->a_s, "matmul_id_q4_k_f32_aligned_s", matmul_id_q4_k_f32_aligned_fp32_len, matmul_id_q4_k_f32_aligned_fp32_data, "main", 4, sizeof(vk_mat_mat_push_constants), s_wg_denoms, warptile_mmq_s, s_align); | |
| ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_mat_id[GGML_TYPE_Q5_K]->l, "matmul_id_q5_k_f32_l", matmul_id_q5_k_f32_fp32_len, matmul_id_q5_k_f32_fp32_data, "main", 4, sizeof(vk_mat_mat_push_constants), l_wg_denoms, warptile_mmq_l, l_align); | |
| ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_mat_id[GGML_TYPE_Q5_K]->m, "matmul_id_q5_k_f32_m", matmul_id_q5_k_f32_fp32_len, matmul_id_q5_k_f32_fp32_data, "main", 4, sizeof(vk_mat_mat_push_constants), m_wg_denoms, warptile_mmq_m, m_align); | |
| ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_mat_id[GGML_TYPE_Q5_K]->s, "matmul_id_q5_k_f32_s", matmul_id_q5_k_f32_fp32_len, matmul_id_q5_k_f32_fp32_data, "main", 4, sizeof(vk_mat_mat_push_constants), s_wg_denoms, warptile_mmq_s, s_align); | |
| ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_mat_id[GGML_TYPE_Q5_K]->a_l, "matmul_id_q5_k_f32_aligned_l", matmul_id_q5_k_f32_aligned_fp32_len, matmul_id_q5_k_f32_aligned_fp32_data, "main", 4, sizeof(vk_mat_mat_push_constants), l_wg_denoms, warptile_mmq_l, l_align); | |
| ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_mat_id[GGML_TYPE_Q5_K]->a_m, "matmul_id_q5_k_f32_aligned_m", matmul_id_q5_k_f32_aligned_fp32_len, matmul_id_q5_k_f32_aligned_fp32_data, "main", 4, sizeof(vk_mat_mat_push_constants), m_wg_denoms, warptile_mmq_m, m_align); | |
| ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_mat_id[GGML_TYPE_Q5_K]->a_s, "matmul_id_q5_k_f32_aligned_s", matmul_id_q5_k_f32_aligned_fp32_len, matmul_id_q5_k_f32_aligned_fp32_data, "main", 4, sizeof(vk_mat_mat_push_constants), s_wg_denoms, warptile_mmq_s, s_align); | |
| ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_mat_id[GGML_TYPE_Q6_K]->l, "matmul_id_q6_k_f32_l", matmul_id_q6_k_f32_fp32_len, matmul_id_q6_k_f32_fp32_data, "main", 4, sizeof(vk_mat_mat_push_constants), l_wg_denoms, warptile_mmq_l, l_align); | |
| ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_mat_id[GGML_TYPE_Q6_K]->m, "matmul_id_q6_k_f32_m", matmul_id_q6_k_f32_fp32_len, matmul_id_q6_k_f32_fp32_data, "main", 4, sizeof(vk_mat_mat_push_constants), m_wg_denoms, warptile_mmq_m, m_align); | |
| ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_mat_id[GGML_TYPE_Q6_K]->s, "matmul_id_q6_k_f32_s", matmul_id_q6_k_f32_fp32_len, matmul_id_q6_k_f32_fp32_data, "main", 4, sizeof(vk_mat_mat_push_constants), s_wg_denoms, warptile_mmq_s, s_align); | |
| ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_mat_id[GGML_TYPE_Q6_K]->a_l, "matmul_id_q6_k_f32_aligned_l", matmul_id_q6_k_f32_aligned_fp32_len, matmul_id_q6_k_f32_aligned_fp32_data, "main", 4, sizeof(vk_mat_mat_push_constants), l_wg_denoms, warptile_mmq_l, l_align); | |
| ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_mat_id[GGML_TYPE_Q6_K]->a_m, "matmul_id_q6_k_f32_aligned_m", matmul_id_q6_k_f32_aligned_fp32_len, matmul_id_q6_k_f32_aligned_fp32_data, "main", 4, sizeof(vk_mat_mat_push_constants), m_wg_denoms, warptile_mmq_m, m_align); | |
| ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_mat_id[GGML_TYPE_Q6_K]->a_s, "matmul_id_q6_k_f32_aligned_s", matmul_id_q6_k_f32_aligned_fp32_len, matmul_id_q6_k_f32_aligned_fp32_data, "main", 4, sizeof(vk_mat_mat_push_constants), s_wg_denoms, warptile_mmq_s, s_align);*/ | |
| } | |
| // mul mat vec | |
| ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_vec_f32_f32[GGML_TYPE_F16 ], "mul_mat_vec_f16_f32_f32", mul_mat_vec_f16_f32_f32_len, mul_mat_vec_f16_f32_f32_data, "main", 3, sizeof(vk_mat_vec_push_constants), {1, 1, 1}, { device->subgroup_size }, 1); | |
| ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_vec_f32_f32[GGML_TYPE_Q4_0], "mul_mat_vec_q4_0_f32_f32", mul_mat_vec_q4_0_f32_f32_len, mul_mat_vec_q4_0_f32_f32_data, "main", 3, sizeof(vk_mat_vec_push_constants), {1, 1, 1}, { device->subgroup_size }, 1); | |
| ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_vec_f32_f32[GGML_TYPE_Q4_1], "mul_mat_vec_q4_1_f32_f32", mul_mat_vec_q4_1_f32_f32_len, mul_mat_vec_q4_1_f32_f32_data, "main", 3, sizeof(vk_mat_vec_push_constants), {1, 1, 1}, { device->subgroup_size }, 1); | |
| ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_vec_f32_f32[GGML_TYPE_Q5_0], "mul_mat_vec_q5_0_f32_f32", mul_mat_vec_q5_0_f32_f32_len, mul_mat_vec_q5_0_f32_f32_data, "main", 3, sizeof(vk_mat_vec_push_constants), {1, 1, 1}, { device->subgroup_size }, 1); | |
| ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_vec_f32_f32[GGML_TYPE_Q5_1], "mul_mat_vec_q5_1_f32_f32", mul_mat_vec_q5_1_f32_f32_len, mul_mat_vec_q5_1_f32_f32_data, "main", 3, sizeof(vk_mat_vec_push_constants), {1, 1, 1}, { device->subgroup_size }, 1); | |
| ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_vec_f32_f32[GGML_TYPE_Q8_0], "mul_mat_vec_q8_0_f32_f32", mul_mat_vec_q8_0_f32_f32_len, mul_mat_vec_q8_0_f32_f32_data, "main", 3, sizeof(vk_mat_vec_push_constants), {1, 1, 1}, { device->subgroup_size }, 1); | |
| ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_vec_f32_f32[GGML_TYPE_Q2_K], "mul_mat_vec_q2_K_f32_f32", mul_mat_vec_q2_K_f32_f32_len, mul_mat_vec_q2_K_f32_f32_data, "main", 3, sizeof(vk_mat_vec_push_constants), {1, 1, 1}, { device->subgroup_size }, 1); | |
| ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_vec_f32_f32[GGML_TYPE_Q3_K], "mul_mat_vec_q3_K_f32_f32", mul_mat_vec_q3_K_f32_f32_len, mul_mat_vec_q3_K_f32_f32_data, "main", 3, sizeof(vk_mat_vec_push_constants), {1, 1, 1}, { device->subgroup_size }, 1); | |
| ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_vec_f32_f32[GGML_TYPE_Q4_K], "mul_mat_vec_q4_K_f32_f32", mul_mat_vec_q4_K_f32_f32_len, mul_mat_vec_q4_K_f32_f32_data, "main", 3, sizeof(vk_mat_vec_push_constants), {1, 1, 1}, { device->subgroup_size }, 1); | |
| ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_vec_f32_f32[GGML_TYPE_Q5_K], "mul_mat_vec_q5_K_f32_f32", mul_mat_vec_q5_K_f32_f32_len, mul_mat_vec_q5_K_f32_f32_data, "main", 3, sizeof(vk_mat_vec_push_constants), {1, 1, 1}, { device->subgroup_size }, 1); | |
| ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_vec_f32_f32[GGML_TYPE_Q6_K], "mul_mat_vec_q6_K_f32_f32", mul_mat_vec_q6_K_f32_f32_len, mul_mat_vec_q6_K_f32_f32_data, "main", 3, sizeof(vk_mat_vec_push_constants), {1, 1, 1}, { device->subgroup_size }, 1); | |
| ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_vec_f16_f32[GGML_TYPE_F16 ], "mul_mat_vec_f16_f16_f32", mul_mat_vec_f16_f16_f32_len, mul_mat_vec_f16_f16_f32_data, "main", 3, sizeof(vk_mat_vec_push_constants), {1, 1, 1}, { device->subgroup_size }, 1); | |
| ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_vec_f16_f32[GGML_TYPE_Q4_0], "mul_mat_vec_q4_0_f16_f32", mul_mat_vec_q4_0_f16_f32_len, mul_mat_vec_q4_0_f16_f32_data, "main", 3, sizeof(vk_mat_vec_push_constants), {1, 1, 1}, { device->subgroup_size }, 1); | |
| ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_vec_f16_f32[GGML_TYPE_Q4_1], "mul_mat_vec_q4_1_f16_f32", mul_mat_vec_q4_1_f16_f32_len, mul_mat_vec_q4_1_f16_f32_data, "main", 3, sizeof(vk_mat_vec_push_constants), {1, 1, 1}, { device->subgroup_size }, 1); | |
| ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_vec_f16_f32[GGML_TYPE_Q5_0], "mul_mat_vec_q5_0_f16_f32", mul_mat_vec_q5_0_f16_f32_len, mul_mat_vec_q5_0_f16_f32_data, "main", 3, sizeof(vk_mat_vec_push_constants), {1, 1, 1}, { device->subgroup_size }, 1); | |
| ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_vec_f16_f32[GGML_TYPE_Q5_1], "mul_mat_vec_q5_1_f16_f32", mul_mat_vec_q5_1_f16_f32_len, mul_mat_vec_q5_1_f16_f32_data, "main", 3, sizeof(vk_mat_vec_push_constants), {1, 1, 1}, { device->subgroup_size }, 1); | |
| ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_vec_f16_f32[GGML_TYPE_Q8_0], "mul_mat_vec_q8_0_f16_f32", mul_mat_vec_q8_0_f16_f32_len, mul_mat_vec_q8_0_f16_f32_data, "main", 3, sizeof(vk_mat_vec_push_constants), {1, 1, 1}, { device->subgroup_size }, 1); | |
| ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_vec_f16_f32[GGML_TYPE_Q2_K], "mul_mat_vec_q2_K_f16_f32", mul_mat_vec_q2_K_f16_f32_len, mul_mat_vec_q2_K_f16_f32_data, "main", 3, sizeof(vk_mat_vec_push_constants), {1, 1, 1}, { device->subgroup_size }, 1); | |
| ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_vec_f16_f32[GGML_TYPE_Q3_K], "mul_mat_vec_q3_K_f16_f32", mul_mat_vec_q3_K_f16_f32_len, mul_mat_vec_q3_K_f16_f32_data, "main", 3, sizeof(vk_mat_vec_push_constants), {1, 1, 1}, { device->subgroup_size }, 1); | |
| ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_vec_f16_f32[GGML_TYPE_Q4_K], "mul_mat_vec_q4_K_f16_f32", mul_mat_vec_q4_K_f16_f32_len, mul_mat_vec_q4_K_f16_f32_data, "main", 3, sizeof(vk_mat_vec_push_constants), {1, 1, 1}, { device->subgroup_size }, 1); | |
| ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_vec_f16_f32[GGML_TYPE_Q5_K], "mul_mat_vec_q5_K_f16_f32", mul_mat_vec_q5_K_f16_f32_len, mul_mat_vec_q5_K_f16_f32_data, "main", 3, sizeof(vk_mat_vec_push_constants), {1, 1, 1}, { device->subgroup_size }, 1); | |
| ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_vec_f16_f32[GGML_TYPE_Q6_K], "mul_mat_vec_q6_K_f16_f32", mul_mat_vec_q6_K_f16_f32_len, mul_mat_vec_q6_K_f16_f32_data, "main", 3, sizeof(vk_mat_vec_push_constants), {1, 1, 1}, { device->subgroup_size }, 1); | |
| /*ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_vec_id_f32[GGML_TYPE_F16 ], "mul_mat_vec_id_f16_f32", mul_mat_vec_id_f16_f32_len, mul_mat_vec_id_f16_f32_data, "main", 4, sizeof(vk_mat_vec_push_constants), {1, 1, 1}, { device->subgroup_size }, 1); | |
| ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_vec_id_f32[GGML_TYPE_Q4_0], "mul_mat_vec_id_q4_0_f32", mul_mat_vec_id_q4_0_f32_len, mul_mat_vec_id_q4_0_f32_data, "main", 4, sizeof(vk_mat_vec_push_constants), {1, 1, 1}, { device->subgroup_size }, 1); | |
| ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_vec_id_f32[GGML_TYPE_Q4_1], "mul_mat_vec_id_q4_1_f32", mul_mat_vec_id_q4_1_f32_len, mul_mat_vec_id_q4_1_f32_data, "main", 4, sizeof(vk_mat_vec_push_constants), {1, 1, 1}, { device->subgroup_size }, 1); | |
| ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_vec_id_f32[GGML_TYPE_Q5_0], "mul_mat_vec_id_q5_0_f32", mul_mat_vec_id_q5_0_f32_len, mul_mat_vec_id_q5_0_f32_data, "main", 4, sizeof(vk_mat_vec_push_constants), {1, 1, 1}, { device->subgroup_size }, 1); | |
| ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_vec_id_f32[GGML_TYPE_Q5_1], "mul_mat_vec_id_q5_1_f32", mul_mat_vec_id_q5_1_f32_len, mul_mat_vec_id_q5_1_f32_data, "main", 4, sizeof(vk_mat_vec_push_constants), {1, 1, 1}, { device->subgroup_size }, 1); | |
| ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_vec_id_f32[GGML_TYPE_Q8_0], "mul_mat_vec_id_q8_0_f32", mul_mat_vec_id_q8_0_f32_len, mul_mat_vec_id_q8_0_f32_data, "main", 4, sizeof(vk_mat_vec_push_constants), {1, 1, 1}, { device->subgroup_size }, 1); | |
| ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_vec_id_f32[GGML_TYPE_Q2_K], "mul_mat_vec_id_q2_K_f32", mul_mat_vec_id_q2_K_f32_len, mul_mat_vec_id_q2_K_f32_data, "main", 4, sizeof(vk_mat_vec_push_constants), {1, 1, 1}, { device->subgroup_size }, 1); | |
| ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_vec_id_f32[GGML_TYPE_Q3_K], "mul_mat_vec_id_q3_K_f32", mul_mat_vec_id_q3_K_f32_len, mul_mat_vec_id_q3_K_f32_data, "main", 4, sizeof(vk_mat_vec_push_constants), {1, 1, 1}, { device->subgroup_size }, 1); | |
| ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_vec_id_f32[GGML_TYPE_Q4_K], "mul_mat_vec_id_q4_K_f32", mul_mat_vec_id_q4_K_f32_len, mul_mat_vec_id_q4_K_f32_data, "main", 4, sizeof(vk_mat_vec_push_constants), {1, 1, 1}, { device->subgroup_size }, 1); | |
| ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_vec_id_f32[GGML_TYPE_Q5_K], "mul_mat_vec_id_q5_K_f32", mul_mat_vec_id_q5_K_f32_len, mul_mat_vec_id_q5_K_f32_data, "main", 4, sizeof(vk_mat_vec_push_constants), {1, 1, 1}, { device->subgroup_size }, 1); | |
| ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_vec_id_f32[GGML_TYPE_Q6_K], "mul_mat_vec_id_q6_K_f32", mul_mat_vec_id_q6_K_f32_len, mul_mat_vec_id_q6_K_f32_data, "main", 4, sizeof(vk_mat_vec_push_constants), {1, 1, 1}, { device->subgroup_size }, 1);*/ | |
| // dequant shaders | |
| ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant[GGML_TYPE_F32 ], "f32_to_f16", dequant_f32_len, dequant_f32_data, "main", 2, 5 * sizeof(uint32_t), {256 * 16, 1, 1}, {}, 1); | |
| ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant[GGML_TYPE_Q4_0], "dequant_q4_0", dequant_q4_0_len, dequant_q4_0_data, "main", 2, 5 * sizeof(uint32_t), {256 * 16, 1, 1}, {}, 1); | |
| ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant[GGML_TYPE_Q4_1], "dequant_q4_1", dequant_q4_1_len, dequant_q4_1_data, "main", 2, 5 * sizeof(uint32_t), {256 * 16, 1, 1}, {}, 1); | |
| ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant[GGML_TYPE_Q5_0], "dequant_q5_0", dequant_q5_0_len, dequant_q5_0_data, "main", 2, 5 * sizeof(uint32_t), {256 * 16, 1, 1}, {}, 1); | |
| ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant[GGML_TYPE_Q5_1], "dequant_q5_1", dequant_q5_1_len, dequant_q5_1_data, "main", 2, 5 * sizeof(uint32_t), {256 * 16, 1, 1}, {}, 1); | |
| ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant[GGML_TYPE_Q8_0], "dequant_q8_0", dequant_q8_0_len, dequant_q8_0_data, "main", 2, 5 * sizeof(uint32_t), {256 * 16, 1, 1}, {}, 1); | |
| ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant[GGML_TYPE_Q2_K], "dequant_q2_K", dequant_q2_K_len, dequant_q2_K_data, "main", 2, 5 * sizeof(uint32_t), {256 * 64, 1, 1}, {}, 1); | |
| ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant[GGML_TYPE_Q3_K], "dequant_q3_K", dequant_q3_K_len, dequant_q3_K_data, "main", 2, 5 * sizeof(uint32_t), {256 * 64, 1, 1}, {}, 1); | |
| ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant[GGML_TYPE_Q4_K], "dequant_q4_K", dequant_q4_K_len, dequant_q4_K_data, "main", 2, 5 * sizeof(uint32_t), {256 * 32, 1, 1}, {}, 1); | |
| ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant[GGML_TYPE_Q5_K], "dequant_q5_K", dequant_q5_K_len, dequant_q5_K_data, "main", 2, 5 * sizeof(uint32_t), {256 * 64, 1, 1}, {}, 1); | |
| ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant[GGML_TYPE_Q6_K], "dequant_q6_K", dequant_q6_K_len, dequant_q6_K_data, "main", 2, 5 * sizeof(uint32_t), {256 * 64, 1, 1}, {}, 1); | |
| // get_rows | |
| ggml_vk_create_pipeline(ctx, ctx->device->pipeline_get_rows[GGML_TYPE_F32 ], "get_rows_f32", get_rows_f32_len, get_rows_f32_data, "main", 3, sizeof(vk_op_binary_push_constants), { 512, 1, 1}, {}, 1); | |
| ggml_vk_create_pipeline(ctx, ctx->device->pipeline_get_rows[GGML_TYPE_F16 ], "get_rows_f16", get_rows_f16_len, get_rows_f16_data, "main", 3, sizeof(vk_op_binary_push_constants), { 512, 1, 1}, {}, 1); | |
| ggml_vk_create_pipeline(ctx, ctx->device->pipeline_get_rows[GGML_TYPE_Q4_0], "get_rows_q4_0", get_rows_q4_0_len, get_rows_q4_0_data, "main", 3, sizeof(vk_op_binary_push_constants), {1024, 1, 1}, {}, 1); | |
| ggml_vk_create_pipeline(ctx, ctx->device->pipeline_get_rows[GGML_TYPE_Q4_1], "get_rows_q4_1", get_rows_q4_1_len, get_rows_q4_1_data, "main", 3, sizeof(vk_op_binary_push_constants), {1024, 1, 1}, {}, 1); | |
| ggml_vk_create_pipeline(ctx, ctx->device->pipeline_get_rows[GGML_TYPE_Q5_0], "get_rows_q5_0", get_rows_q5_0_len, get_rows_q5_0_data, "main", 3, sizeof(vk_op_binary_push_constants), {1024, 1, 1}, {}, 1); | |
| ggml_vk_create_pipeline(ctx, ctx->device->pipeline_get_rows[GGML_TYPE_Q5_1], "get_rows_q5_1", get_rows_q5_1_len, get_rows_q5_1_data, "main", 3, sizeof(vk_op_binary_push_constants), {1024, 1, 1}, {}, 1); | |
| ggml_vk_create_pipeline(ctx, ctx->device->pipeline_get_rows[GGML_TYPE_Q8_0], "get_rows_q8_0", get_rows_q8_0_len, get_rows_q8_0_data, "main", 3, sizeof(vk_op_binary_push_constants), {1024, 1, 1}, {}, 1); | |
| ggml_vk_create_pipeline(ctx, ctx->device->pipeline_get_rows_f32[GGML_TYPE_F32 ], "get_rows_f32_f32", get_rows_f32_f32_len, get_rows_f32_f32_data, "main", 3, sizeof(vk_op_binary_push_constants), { 512, 1, 1}, {}, 1); | |
| ggml_vk_create_pipeline(ctx, ctx->device->pipeline_get_rows_f32[GGML_TYPE_F16 ], "get_rows_f16_f32", get_rows_f16_f32_len, get_rows_f16_f32_data, "main", 3, sizeof(vk_op_binary_push_constants), { 512, 1, 1}, {}, 1); | |
| ggml_vk_create_pipeline(ctx, ctx->device->pipeline_get_rows_f32[GGML_TYPE_Q4_0], "get_rows_q4_0_f32", get_rows_q4_0_f32_len, get_rows_q4_0_f32_data, "main", 3, sizeof(vk_op_binary_push_constants), {1024, 1, 1}, {}, 1); | |
| ggml_vk_create_pipeline(ctx, ctx->device->pipeline_get_rows_f32[GGML_TYPE_Q4_1], "get_rows_q4_1_f32", get_rows_q4_1_f32_len, get_rows_q4_1_f32_data, "main", 3, sizeof(vk_op_binary_push_constants), {1024, 1, 1}, {}, 1); | |
| ggml_vk_create_pipeline(ctx, ctx->device->pipeline_get_rows_f32[GGML_TYPE_Q5_0], "get_rows_q5_0_f32", get_rows_q5_0_f32_len, get_rows_q5_0_f32_data, "main", 3, sizeof(vk_op_binary_push_constants), {1024, 1, 1}, {}, 1); | |
| ggml_vk_create_pipeline(ctx, ctx->device->pipeline_get_rows_f32[GGML_TYPE_Q5_1], "get_rows_q5_1_f32", get_rows_q5_1_f32_len, get_rows_q5_1_f32_data, "main", 3, sizeof(vk_op_binary_push_constants), {1024, 1, 1}, {}, 1); | |
| ggml_vk_create_pipeline(ctx, ctx->device->pipeline_get_rows_f32[GGML_TYPE_Q8_0], "get_rows_q8_0_f32", get_rows_q8_0_f32_len, get_rows_q8_0_f32_data, "main", 3, sizeof(vk_op_binary_push_constants), {1024, 1, 1}, {}, 1); | |
| ggml_vk_create_pipeline(ctx, ctx->device->pipeline_matmul_split_k_reduce, "split_k_reduce", split_k_reduce_len, split_k_reduce_data, "main", 2, 2 * sizeof(uint32_t), {256, 1, 1}, {}, 1); | |
| ggml_vk_create_pipeline(ctx, ctx->device->pipeline_mul_mat_vec_p021_f16_f32, "mul_mat_vec_p021_f16_f32", mul_mat_vec_p021_f16_f32_len, mul_mat_vec_p021_f16_f32_data, "main", 3, 6 * sizeof(uint32_t), {1, 1, 1}, {}, 1); | |
| ggml_vk_create_pipeline(ctx, ctx->device->pipeline_mul_mat_vec_nc_f16_f32, "mul_mat_vec_nc_f16_f32", mul_mat_vec_nc_f16_f32_len, mul_mat_vec_nc_f16_f32_data, "main", 3, 7 * sizeof(uint32_t), {1, 1, 1}, {}, 1); | |
| ggml_vk_create_pipeline(ctx, ctx->device->pipeline_norm_f32, "norm_f32", norm_f32_len, norm_f32_data, "main", 2, sizeof(vk_op_push_constants), {1, 1, 1}, {}, 1); | |
| ggml_vk_create_pipeline(ctx, ctx->device->pipeline_rms_norm_f32, "rms_norm_f32", rms_norm_f32_len, rms_norm_f32_data, "main", 2, sizeof(vk_op_push_constants), {1, 1, 1}, {}, 1); | |
| ggml_vk_create_pipeline(ctx, ctx->device->pipeline_cpy_f32_f32, "cpy_f32_f32", cpy_f32_f32_len, cpy_f32_f32_data, "main", 2, sizeof(vk_op_unary_push_constants), {512, 1, 1}, {}, 1); | |
| ggml_vk_create_pipeline(ctx, ctx->device->pipeline_cpy_f32_f16, "cpy_f32_f16", cpy_f32_f16_len, cpy_f32_f16_data, "main", 2, sizeof(vk_op_unary_push_constants), {512, 1, 1}, {}, 1); | |
| ggml_vk_create_pipeline(ctx, ctx->device->pipeline_cpy_f16_f16, "cpy_f16_f16", cpy_f16_f16_len, cpy_f16_f16_data, "main", 2, sizeof(vk_op_unary_push_constants), {512, 1, 1}, {}, 1); | |
| ggml_vk_create_pipeline(ctx, ctx->device->pipeline_add_f32, "add_f32", add_f32_len, add_f32_data, "main", 3, sizeof(vk_op_binary_push_constants), {512, 1, 1}, {}, 1); | |
| ggml_vk_create_pipeline(ctx, ctx->device->pipeline_mul_f32, "mul_f32", mul_f32_len, mul_f32_data, "main", 3, sizeof(vk_op_binary_push_constants), {512, 1, 1}, {}, 1); | |
| ggml_vk_create_pipeline(ctx, ctx->device->pipeline_scale_f32, "scale_f32", scale_f32_len, scale_f32_data, "main", 2, sizeof(vk_op_unary_push_constants), {512, 1, 1}, {}, 1); | |
| ggml_vk_create_pipeline(ctx, ctx->device->pipeline_sqr_f32, "sqr_f32", sqr_f32_len, sqr_f32_data, "main", 2, sizeof(vk_op_unary_push_constants), {512, 1, 1}, {}, 1); | |
| ggml_vk_create_pipeline(ctx, ctx->device->pipeline_clamp_f32, "clamp_f32", clamp_f32_len, clamp_f32_data, "main", 2, sizeof(vk_op_unary_push_constants), {512, 1, 1}, {}, 1); | |
| ggml_vk_create_pipeline(ctx, ctx->device->pipeline_gelu_f32, "gelu_f32", gelu_f32_len, gelu_f32_data, "main", 2, sizeof(vk_op_push_constants), {512, 1, 1}, {}, 1); | |
| ggml_vk_create_pipeline(ctx, ctx->device->pipeline_silu_f32, "silu_f32", silu_f32_len, silu_f32_data, "main", 2, sizeof(vk_op_push_constants), {512, 1, 1}, {}, 1); | |
| ggml_vk_create_pipeline(ctx, ctx->device->pipeline_relu_f32, "relu_f32", relu_f32_len, relu_f32_data, "main", 2, sizeof(vk_op_push_constants), {512, 1, 1}, {}, 1); | |
| ggml_vk_create_pipeline(ctx, ctx->device->pipeline_diag_mask_inf_f32, "diag_mask_inf_f32", diag_mask_inf_f32_len, diag_mask_inf_f32_data, "main", 2, sizeof(vk_op_diag_mask_push_constants), {512, 1, 1}, {}, 1); | |
| ggml_vk_create_pipeline(ctx, ctx->device->pipeline_soft_max_f32, "soft_max_f32", soft_max_f32_len, soft_max_f32_data, "main", 4, sizeof(vk_op_soft_max_push_constants), {1, 1, 1}, {}, 1); | |
| ggml_vk_create_pipeline(ctx, ctx->device->pipeline_soft_max_f32_f16, "soft_max_f32_f16", soft_max_f32_f16_len, soft_max_f32_f16_data, "main", 4, sizeof(vk_op_soft_max_push_constants), {1, 1, 1}, {}, 1); | |
| ggml_vk_create_pipeline(ctx, ctx->device->pipeline_rope_f32, "rope_f32", rope_f32_len, rope_f32_data, "main", 3, sizeof(vk_op_rope_push_constants), {1, 512, 1}, {}, 1); | |
| ggml_vk_create_pipeline(ctx, ctx->device->pipeline_rope_f16, "rope_f16", rope_f16_len, rope_f16_data, "main", 3, sizeof(vk_op_rope_push_constants), {1, 512, 1}, {}, 1); | |
| ggml_vk_create_pipeline(ctx, ctx->device->pipeline_rope_neox_f32, "rope_neox_f32", rope_neox_f32_len, rope_neox_f32_data, "main", 3, sizeof(vk_op_rope_neox_push_constants), {1, 512, 1}, {}, 1); | |
| ggml_vk_create_pipeline(ctx, ctx->device->pipeline_rope_neox_f16, "rope_neox_f16", rope_neox_f16_len, rope_neox_f16_data, "main", 3, sizeof(vk_op_rope_neox_push_constants), {1, 512, 1}, {}, 1); | |
| ggml_vk_create_pipeline(ctx, ctx->device->pipeline_argsort_f32, "argsort_f32", argsort_f32_len, argsort_f32_data, "main", 2, sizeof(vk_op_argsort_push_constants), {1024, 1, 1}, {}, 1); | |
| } | |
| static void ggml_vk_print_gpu_info(size_t idx) { | |
| GGML_ASSERT(idx < vk_instance.device_indices.size()); | |
| size_t dev_num = vk_instance.device_indices[idx]; | |
| std::cerr << "ggml_vk_print_gpu_info(" << dev_num << ")" << std::endl; | |
| GGML_ASSERT(vk_instance.initialized); | |
| std::vector<vk::PhysicalDevice> devices = vk_instance.instance.enumeratePhysicalDevices(); | |
| if (dev_num >= devices.size()) { | |
| std::cerr << "ggml_vulkan: Device with index " << dev_num << " does not exist." << std::endl; | |
| throw std::runtime_error("Device not found"); | |
| } | |
| vk::PhysicalDevice physical_device = devices[dev_num]; | |
| std::vector<vk::ExtensionProperties> ext_props = physical_device.enumerateDeviceExtensionProperties(); | |
| vk::PhysicalDeviceProperties2 props2; | |
| vk::PhysicalDeviceMaintenance3Properties props3; | |
| vk::PhysicalDeviceSubgroupProperties subgroup_props; | |
| props2.pNext = &props3; | |
| props3.pNext = &subgroup_props; | |
| physical_device.getProperties2(&props2); | |
| const size_t subgroup_size = subgroup_props.subgroupSize; | |
| const bool uma = props2.properties.deviceType == vk::PhysicalDeviceType::eIntegratedGpu; | |
| bool fp16_storage = false; | |
| bool fp16_compute = false; | |
| for (auto properties : ext_props) { | |
| if (strcmp("VK_KHR_16bit_storage", properties.extensionName) == 0) { | |
| fp16_storage = true; | |
| } else if (strcmp("VK_KHR_shader_float16_int8", properties.extensionName) == 0) { | |
| fp16_compute = true; | |
| } | |
| } | |
| const char* GGML_VK_DISABLE_F16 = getenv("GGML_VK_DISABLE_F16"); | |
| bool force_disable_f16 = GGML_VK_DISABLE_F16 != nullptr; | |
| bool fp16 = !force_disable_f16 && fp16_storage && fp16_compute; | |
| vk::PhysicalDeviceFeatures device_features = physical_device.getFeatures(); | |
| VkPhysicalDeviceFeatures2 device_features2; | |
| device_features2.sType = VK_STRUCTURE_TYPE_PHYSICAL_DEVICE_FEATURES_2; | |
| device_features2.pNext = nullptr; | |
| device_features2.features = (VkPhysicalDeviceFeatures)device_features; | |
| VkPhysicalDeviceVulkan11Features vk11_features; | |
| vk11_features.pNext = nullptr; | |
| vk11_features.sType = VK_STRUCTURE_TYPE_PHYSICAL_DEVICE_VULKAN_1_1_FEATURES; | |
| device_features2.pNext = &vk11_features; | |
| VkPhysicalDeviceVulkan12Features vk12_features; | |
| vk12_features.pNext = nullptr; | |
| vk12_features.sType = VK_STRUCTURE_TYPE_PHYSICAL_DEVICE_VULKAN_1_2_FEATURES; | |
| vk11_features.pNext = &vk12_features; | |
| vkGetPhysicalDeviceFeatures2(physical_device, &device_features2); | |
| fp16 = fp16 && vk12_features.shaderFloat16; | |
| std::string device_name = props2.properties.deviceName.data(); | |
| std::cerr << GGML_VK_NAME << idx << ": " << device_name << " | uma: " << uma << " | fp16: " << fp16 << " | warp size: " << subgroup_size << std::endl; | |
| if (props2.properties.deviceType == vk::PhysicalDeviceType::eCpu) { | |
| std::cerr << "ggml_vulkan: Warning: Device type is CPU. This is probably not the device you want." << std::endl; | |
| } | |
| } | |
| static bool ggml_vk_instance_validation_ext_available(const std::vector<vk::ExtensionProperties>& instance_extensions); | |
| static bool ggml_vk_instance_portability_enumeration_ext_available(const std::vector<vk::ExtensionProperties>& instance_extensions); | |
| void ggml_vk_instance_init() { | |
| if (vk_instance_initialized) { | |
| return; | |
| } | |
| std::cerr << "ggml_vk_instance_init()" << std::endl; | |
| vk::ApplicationInfo app_info{ "ggml-vulkan", 1, nullptr, 0, VK_API_VERSION }; | |
| const std::vector<vk::ExtensionProperties> instance_extensions = vk::enumerateInstanceExtensionProperties(); | |
| const bool validation_ext = ggml_vk_instance_validation_ext_available(instance_extensions); | |
| const bool portability_enumeration_ext = ggml_vk_instance_portability_enumeration_ext_available(instance_extensions); | |
| std::vector<const char*> layers; | |
| if (validation_ext) { | |
| layers.push_back("VK_LAYER_KHRONOS_validation"); | |
| } | |
| std::vector<const char*> extensions; | |
| if (validation_ext) { | |
| extensions.push_back("VK_EXT_validation_features"); | |
| } | |
| if (portability_enumeration_ext) { | |
| extensions.push_back("VK_KHR_portability_enumeration"); | |
| } | |
| vk::InstanceCreateInfo instance_create_info(vk::InstanceCreateFlags{}, &app_info, layers, extensions); | |
| if (portability_enumeration_ext) { | |
| instance_create_info.flags |= vk::InstanceCreateFlagBits::eEnumeratePortabilityKHR; | |
| } | |
| std::vector<vk::ValidationFeatureEnableEXT> features_enable; | |
| vk::ValidationFeaturesEXT validation_features; | |
| if (validation_ext) { | |
| features_enable = { vk::ValidationFeatureEnableEXT::eBestPractices }; | |
| validation_features = { | |
| features_enable, | |
| {}, | |
| }; | |
| validation_features.setPNext(nullptr); | |
| instance_create_info.setPNext(&validation_features); | |
| std::cerr << "ggml_vulkan: Validation layers enabled" << std::endl; | |
| } | |
| vk_instance.instance = vk::createInstance(instance_create_info); | |
| memset(vk_instance.initialized, 0, sizeof(bool) * GGML_VK_MAX_DEVICES); | |
| size_t num_available_devices = vk_instance.instance.enumeratePhysicalDevices().size(); | |
| // Emulate behavior of CUDA_VISIBLE_DEVICES for Vulkan | |
| char * devices_env = getenv("GGML_VK_VISIBLE_DEVICES"); | |
| if (devices_env != nullptr) { | |
| std::string devices(devices_env); | |
| std::replace(devices.begin(), devices.end(), ',', ' '); | |
| std::stringstream ss(devices); | |
| size_t tmp; | |
| while (ss >> tmp) { | |
| if(tmp >= num_available_devices) { | |
| std::cerr << "ggml_vulkan: Invalid device index " << tmp << " in GGML_VK_VISIBLE_DEVICES." << std::endl; | |
| throw std::runtime_error("Invalid Vulkan device index"); | |
| } | |
| vk_instance.device_indices.push_back(tmp); | |
| } | |
| } else { | |
| std::vector<vk::PhysicalDevice> devices = vk_instance.instance.enumeratePhysicalDevices(); | |
| // Make sure at least one device exists | |
| if (devices.empty()) { | |
| std::cerr << "ggml_vulkan: Error: No devices found." << std::endl; | |
| GGML_ASSERT(false); | |
| } | |
| // Default to using all dedicated GPUs | |
| for (size_t i = 0; i < devices.size(); i++) { | |
| vk::PhysicalDeviceProperties props = devices[i].getProperties(); | |
| if (props.deviceType == vk::PhysicalDeviceType::eDiscreteGpu) { | |
| vk_instance.device_indices.push_back(i); | |
| } | |
| } | |
| // If no dedicated GPUs found, fall back to GPU 0 | |
| if (vk_instance.device_indices.empty()) { | |
| vk_instance.device_indices.push_back(0); | |
| } | |
| } | |
| std::cerr << "ggml_vulkan: Found " << vk_instance.device_indices.size() << " Vulkan devices:" << std::endl; | |
| for (size_t i = 0; i < vk_instance.device_indices.size(); i++) { | |
| ggml_vk_print_gpu_info(i); | |
| } | |
| vk_instance_initialized = true; | |
| } | |
| static void ggml_vk_init(ggml_backend_vk_context * ctx, size_t idx) { | |
| GGML_ASSERT(idx < vk_instance.device_indices.size()); | |
| size_t dev_num = vk_instance.device_indices[idx]; | |
| std::cerr << "ggml_vk_init(" << ctx->name << ", " << dev_num << ")" << std::endl; | |
| ggml_vk_instance_init(); | |
| std::vector<vk::PhysicalDevice> devices = vk_instance.instance.enumeratePhysicalDevices(); | |
| if (dev_num >= devices.size()) { | |
| std::cerr << "ggml_vulkan: Device with index " << dev_num << " does not exist." << std::endl; | |
| throw std::runtime_error("Device not found"); | |
| } | |
| ctx->device = ggml_vk_get_device(idx); | |
| if (!ctx->device->initialized) { | |
| ctx->device->physical_device = devices[dev_num]; | |
| const std::vector<vk::ExtensionProperties> ext_props = ctx->device->physical_device.enumerateDeviceExtensionProperties(); | |
| bool maintenance4_support = false; | |
| // Check if maintenance4 is supported | |
| for (const auto& properties : ext_props) { | |
| if (strcmp("VK_KHR_maintenance4", properties.extensionName) == 0) { | |
| maintenance4_support = true; | |
| } | |
| } | |
| vk::PhysicalDeviceProperties2 props2; | |
| vk::PhysicalDeviceMaintenance3Properties props3; | |
| vk::PhysicalDeviceMaintenance4Properties props4; | |
| vk::PhysicalDeviceSubgroupProperties subgroup_props; | |
| props2.pNext = &props3; | |
| props3.pNext = &subgroup_props; | |
| if (maintenance4_support) { | |
| subgroup_props.pNext = &props4; | |
| } | |
| ctx->device->physical_device.getProperties2(&props2); | |
| ctx->device->properties = props2.properties; | |
| const char* GGML_VK_FORCE_MAX_ALLOCATION_SIZE = getenv("GGML_VK_FORCE_MAX_ALLOCATION_SIZE"); | |
| if (GGML_VK_FORCE_MAX_ALLOCATION_SIZE != nullptr) { | |
| ctx->device->max_memory_allocation_size = std::stoi(GGML_VK_FORCE_MAX_ALLOCATION_SIZE); | |
| } else if (maintenance4_support) { | |
| ctx->device->max_memory_allocation_size = std::min(props3.maxMemoryAllocationSize, props4.maxBufferSize); | |
| } else { | |
| ctx->device->max_memory_allocation_size = props3.maxMemoryAllocationSize; | |
| } | |
| ctx->device->vendor_id = ctx->device->properties.vendorID; | |
| ctx->device->subgroup_size = subgroup_props.subgroupSize; | |
| ctx->device->uma = ctx->device->properties.deviceType == vk::PhysicalDeviceType::eIntegratedGpu; | |
| bool fp16_storage = false; | |
| bool fp16_compute = false; | |
| for (const auto& properties : ext_props) { | |
| if (strcmp("VK_KHR_16bit_storage", properties.extensionName) == 0) { | |
| fp16_storage = true; | |
| } else if (strcmp("VK_KHR_shader_float16_int8", properties.extensionName) == 0) { | |
| fp16_compute = true; | |
| } | |
| } | |
| const char* GGML_VK_DISABLE_F16 = getenv("GGML_VK_DISABLE_F16"); | |
| const bool force_disable_f16 = GGML_VK_DISABLE_F16 != nullptr; | |
| ctx->device->fp16 = !force_disable_f16 && fp16_storage && fp16_compute; | |
| std::vector<vk::QueueFamilyProperties> queue_family_props = ctx->device->physical_device.getQueueFamilyProperties(); | |
| // Try to find a non-graphics compute queue and transfer-focused queues | |
| const uint32_t compute_queue_family_index = ggml_vk_find_queue_family_index(queue_family_props, vk::QueueFlagBits::eCompute, vk::QueueFlagBits::eGraphics, -1, 1); | |
| const uint32_t transfer_queue_family_index = ggml_vk_find_queue_family_index(queue_family_props, vk::QueueFlagBits::eTransfer, vk::QueueFlagBits::eCompute | vk::QueueFlagBits::eGraphics, compute_queue_family_index, 1); | |
| const float priorities[] = { 1.0f, 1.0f }; | |
| ctx->device->single_queue = compute_queue_family_index == transfer_queue_family_index && queue_family_props[compute_queue_family_index].queueCount == 1; | |
| std::vector<vk::DeviceQueueCreateInfo> device_queue_create_infos; | |
| if (compute_queue_family_index != transfer_queue_family_index) { | |
| device_queue_create_infos.push_back({vk::DeviceQueueCreateFlags(), compute_queue_family_index, 1, priorities}); | |
| device_queue_create_infos.push_back({vk::DeviceQueueCreateFlags(), transfer_queue_family_index, 1, priorities + 1}); | |
| } else if(!ctx->device->single_queue) { | |
| device_queue_create_infos.push_back({vk::DeviceQueueCreateFlags(), compute_queue_family_index, 2, priorities}); | |
| } else { | |
| device_queue_create_infos.push_back({vk::DeviceQueueCreateFlags(), compute_queue_family_index, 1, priorities}); | |
| } | |
| vk::DeviceCreateInfo device_create_info; | |
| std::vector<const char *> device_extensions; | |
| vk::PhysicalDeviceFeatures device_features = ctx->device->physical_device.getFeatures(); | |
| VkPhysicalDeviceFeatures2 device_features2; | |
| device_features2.sType = VK_STRUCTURE_TYPE_PHYSICAL_DEVICE_FEATURES_2; | |
| device_features2.pNext = nullptr; | |
| device_features2.features = (VkPhysicalDeviceFeatures)device_features; | |
| VkPhysicalDeviceVulkan11Features vk11_features; | |
| vk11_features.pNext = nullptr; | |
| vk11_features.sType = VK_STRUCTURE_TYPE_PHYSICAL_DEVICE_VULKAN_1_1_FEATURES; | |
| device_features2.pNext = &vk11_features; | |
| VkPhysicalDeviceVulkan12Features vk12_features; | |
| vk12_features.pNext = nullptr; | |
| vk12_features.sType = VK_STRUCTURE_TYPE_PHYSICAL_DEVICE_VULKAN_1_2_FEATURES; | |
| vk11_features.pNext = &vk12_features; | |
| vkGetPhysicalDeviceFeatures2(ctx->device->physical_device, &device_features2); | |
| ctx->device->fp16 = ctx->device->fp16 && vk12_features.shaderFloat16; | |
| if (!vk11_features.storageBuffer16BitAccess) { | |
| std::cerr << "ggml_vulkan: device " << GGML_VK_NAME << idx << " does not support 16-bit storage." << std::endl; | |
| throw std::runtime_error("Unsupported device"); | |
| } | |
| device_extensions.push_back("VK_KHR_16bit_storage"); | |
| device_extensions.push_back("VK_KHR_shader_non_semantic_info"); | |
| if (ctx->device->fp16) { | |
| device_extensions.push_back("VK_KHR_shader_float16_int8"); | |
| } | |
| ctx->device->name = ctx->device->properties.deviceName.data(); | |
| device_create_info = { | |
| vk::DeviceCreateFlags(), | |
| device_queue_create_infos, | |
| {}, | |
| device_extensions | |
| }; | |
| device_create_info.setPNext(&device_features2); | |
| ctx->device->device = ctx->device->physical_device.createDevice(device_create_info); | |
| ctx->device->descriptor_set_mode = VK_DEVICE_DESCRIPTOR_POOL_MODE_UNKNOWN; | |
| // Queues | |
| ggml_vk_create_queue(ctx, ctx->device->compute_queue, compute_queue_family_index, 0, { vk::PipelineStageFlagBits::eComputeShader | vk::PipelineStageFlagBits::eTransfer }); | |
| // Shaders | |
| ggml_vk_load_shaders(ctx); | |
| if (!ctx->device->single_queue) { | |
| const uint32_t transfer_queue_index = compute_queue_family_index == transfer_queue_family_index ? 1 : 0; | |
| ggml_vk_create_queue(ctx, ctx->device->transfer_queue, transfer_queue_family_index, transfer_queue_index, { vk::PipelineStageFlagBits::eTransfer }); | |
| } else { | |
| // TODO: Use pointer or reference to avoid copy | |
| ctx->device->transfer_queue = ctx->device->compute_queue; | |
| } | |
| ctx->device->idx = dev_num; | |
| ctx->device->initialized = true; | |
| } else if (ctx->device->idx != dev_num) { | |
| std::cerr << "ggml_vulkan: Device " << ctx->device->name << " already initialized with index " << ctx->device->idx << ", but trying to reinitialize with index " << dev_num << std::endl; | |
| throw std::runtime_error("Device already initialized"); | |
| } | |
| ctx->fence = ctx->device->device.createFence({}); | |
| ctx->compute_ctx = nullptr; | |
| ctx->transfer_ctx = nullptr; | |
| ctx->disable = false; | |
| ctx->initialized = true; | |
| ctx->idx = idx; | |
| const char* skip_checks = getenv("GGML_VULKAN_SKIP_CHECKS"); | |
| vk_skip_checks = (skip_checks == NULL ? 0 : atoi(skip_checks)); | |
| const char* output_tensor = getenv("GGML_VULKAN_OUTPUT_TENSOR"); | |
| vk_output_tensor = (output_tensor == NULL ? 0 : atoi(output_tensor)); | |
| } | |
| static vk_pipeline ggml_vk_get_to_fp16(ggml_backend_vk_context * ctx, ggml_type type) { | |
| std::cerr << "ggml_vk_get_to_fp16()" << std::endl; | |
| switch (type) { | |
| case GGML_TYPE_F32: | |
| case GGML_TYPE_Q4_0: | |
| case GGML_TYPE_Q4_1: | |
| case GGML_TYPE_Q5_0: | |
| case GGML_TYPE_Q5_1: | |
| case GGML_TYPE_Q8_0: | |
| case GGML_TYPE_Q2_K: | |
| case GGML_TYPE_Q3_K: | |
| case GGML_TYPE_Q4_K: | |
| case GGML_TYPE_Q5_K: | |
| case GGML_TYPE_Q6_K: | |
| break; | |
| default: | |
| return nullptr; | |
| } | |
| return ctx->device->pipeline_dequant[type]; | |
| } | |
| static vk_matmul_pipeline ggml_vk_get_mul_mat_mat_pipeline(ggml_backend_vk_context * ctx, ggml_type src0_type, ggml_type src1_type) { | |
| std::cerr << "ggml_vk_get_mul_mat_mat_pipeline()" << std::endl; | |
| if (src0_type == GGML_TYPE_F32 && src1_type == GGML_TYPE_F32) { | |
| return ctx->device->pipeline_matmul_f32; | |
| } | |
| if (src0_type == GGML_TYPE_F16 && src1_type == GGML_TYPE_F32) { | |
| return ctx->device->pipeline_matmul_f16_f32; | |
| } | |
| if (src0_type == GGML_TYPE_F16 && src1_type == GGML_TYPE_F16) { | |
| return ctx->device->pipeline_matmul_f16; | |
| } | |
| GGML_ASSERT(src1_type == GGML_TYPE_F32); | |
| switch (src0_type) { | |
| case GGML_TYPE_Q4_0: | |
| case GGML_TYPE_Q4_1: | |
| case GGML_TYPE_Q5_0: | |
| case GGML_TYPE_Q5_1: | |
| case GGML_TYPE_Q8_0: | |
| case GGML_TYPE_Q2_K: | |
| case GGML_TYPE_Q3_K: | |
| case GGML_TYPE_Q4_K: | |
| case GGML_TYPE_Q5_K: | |
| case GGML_TYPE_Q6_K: | |
| break; | |
| default: | |
| return nullptr; | |
| } | |
| return ctx->device->pipeline_dequant_mul_mat_mat[src0_type]; | |
| } | |
| static vk_matmul_pipeline ggml_vk_get_mul_mat_mat_id_pipeline(ggml_backend_vk_context * ctx, ggml_type src0_type, ggml_type src1_type) { | |
| std::cerr << "ggml_vk_get_mul_mat_mat_id_pipeline()" << std::endl; | |
| if (src0_type == GGML_TYPE_F32 && src1_type == GGML_TYPE_F32) { | |
| return ctx->device->pipeline_matmul_id_f32; | |
| } | |
| if (src0_type == GGML_TYPE_F16 && src1_type == GGML_TYPE_F32) { | |
| return ctx->device->pipeline_matmul_id_f16_f32; | |
| } | |
| if (src0_type == GGML_TYPE_F16 && src1_type == GGML_TYPE_F16) { | |
| return ctx->device->pipeline_matmul_id_f16; | |
| } | |
| GGML_ASSERT(src1_type == GGML_TYPE_F32); | |
| switch (src0_type) { | |
| case GGML_TYPE_Q4_0: | |
| case GGML_TYPE_Q4_1: | |
| case GGML_TYPE_Q5_0: | |
| case GGML_TYPE_Q5_1: | |
| case GGML_TYPE_Q8_0: | |
| case GGML_TYPE_Q2_K: | |
| case GGML_TYPE_Q3_K: | |
| case GGML_TYPE_Q4_K: | |
| case GGML_TYPE_Q5_K: | |
| case GGML_TYPE_Q6_K: | |
| break; | |
| default: | |
| return nullptr; | |
| } | |
| return ctx->device->pipeline_dequant_mul_mat_mat_id[src0_type]; | |
| } | |
| static vk_pipeline ggml_vk_get_dequantize_mul_mat_vec(ggml_backend_vk_context * ctx, ggml_type a_type, ggml_type b_type) { | |
| std::cerr << "ggml_vk_get_dequantize_mul_mat_vec()" << std::endl; | |
| GGML_ASSERT(b_type == GGML_TYPE_F32 || b_type == GGML_TYPE_F16); | |
| switch (a_type) { | |
| case GGML_TYPE_F16: | |
| case GGML_TYPE_Q4_0: | |
| case GGML_TYPE_Q4_1: | |
| case GGML_TYPE_Q5_0: | |
| case GGML_TYPE_Q5_1: | |
| case GGML_TYPE_Q8_0: | |
| case GGML_TYPE_Q2_K: | |
| case GGML_TYPE_Q3_K: | |
| case GGML_TYPE_Q4_K: | |
| case GGML_TYPE_Q5_K: | |
| case GGML_TYPE_Q6_K: | |
| break; | |
| default: | |
| return nullptr; | |
| } | |
| return b_type == GGML_TYPE_F32 ? ctx->device->pipeline_dequant_mul_mat_vec_f32_f32[a_type] : ctx->device->pipeline_dequant_mul_mat_vec_f16_f32[a_type]; | |
| } | |
| static vk_buffer ggml_vk_pool_malloc(ggml_backend_vk_context * ctx, size_t size) { | |
| std::cerr << "ggml_vk_pool_malloc(" << size << ")" << std::endl; | |
| int best_i = -1; | |
| size_t best_size = std::numeric_limits<size_t>::max(); //smallest unused buffer that fits our needs | |
| int worst_i = -1; | |
| size_t worst_size = 0; //largest unused buffer seen so far | |
| for (int i = 0; i < MAX_VK_BUFFERS; ++i) { | |
| vk_buffer &b = ctx->buffer_pool[i]; | |
| if (b != nullptr && b->size >= size && b->size < best_size) { | |
| best_i = i; | |
| best_size = b->size; | |
| } | |
| if (b != nullptr && b->size > worst_size) { | |
| worst_i = i; | |
| worst_size = b->size; | |
| } | |
| } | |
| if(best_i != -1) { | |
| //found the smallest buffer that fits our needs | |
| vk_buffer b = ctx->buffer_pool[best_i]; | |
| ctx->buffer_pool[best_i].reset(); | |
| return b; | |
| } | |
| if(worst_i != -1) { | |
| //no buffer that fits our needs, resize largest one to save memory | |
| vk_buffer& b = ctx->buffer_pool[worst_i]; | |
| ggml_vk_destroy_buffer(b); | |
| } | |
| return ggml_vk_create_buffer_check(ctx, size, vk::MemoryPropertyFlagBits::eDeviceLocal); | |
| } | |
| static void ggml_vk_pool_free(ggml_backend_vk_context * ctx, vk_buffer& buffer) { | |
| std::cerr << "ggml_vk_pool_free(" << buffer->size << ")" << std::endl; | |
| for (int i = 0; i < MAX_VK_BUFFERS; ++i) { | |
| vk_buffer& b = ctx->buffer_pool[i]; | |
| if (b == nullptr) { | |
| b = buffer; | |
| return; | |
| } | |
| } | |
| std::cerr << "ggml_vulkan: WARNING: vk buffer pool full, increase MAX_VK_BUFFERS" << std::endl; | |
| ggml_vk_destroy_buffer(buffer); | |
| } | |
| // Returns an available temporary buffer that may only be used temporarily, it will be reused | |
| static vk_buffer ggml_vk_create_buffer_temp(ggml_backend_vk_context * ctx, size_t size) { | |
| // Try to find existing temp buffer with enough capacity | |
| for (auto& buffer : ctx->gc.temp_buffers) { | |
| if (buffer->size >= size) { | |
| return buffer; | |
| } | |
| } | |
| // Otherwise create new buffer | |
| vk_buffer buf = ggml_vk_pool_malloc(ctx, size); | |
| ctx->gc.temp_buffers.push_back(buf); | |
| return buf; | |
| } | |
| static void * ggml_vk_host_malloc(ggml_backend_vk_context * ctx, size_t size) { | |
| std::cerr << "ggml_vk_host_malloc(" << size << ")" << std::endl; | |
| vk_buffer buf = ggml_vk_create_buffer(ctx, size, | |
| vk::MemoryPropertyFlagBits::eHostVisible | vk::MemoryPropertyFlagBits::eHostCoherent | vk::MemoryPropertyFlagBits::eHostCached, | |
| vk::MemoryPropertyFlagBits::eHostVisible | vk::MemoryPropertyFlagBits::eHostCoherent); | |
| if(!(buf->memory_property_flags & vk::MemoryPropertyFlagBits::eHostVisible)) { | |
| fprintf(stderr, "WARNING: failed to allocate %.2f MB of pinned memory\n", | |
| size/1024.0/1024.0); | |
| ctx->device->device.freeMemory(buf->device_memory); | |
| ctx->device->device.destroyBuffer(buf->buffer); | |
| return nullptr; | |
| } | |
| ctx->pinned_memory.push_back(std::make_tuple(buf->ptr, size, buf)); | |
| return buf->ptr; | |
| } | |
| static void ggml_vk_host_free(ggml_backend_vk_context * ctx, void* ptr) { | |
| if (ptr == nullptr) { | |
| return; | |
| } | |
| std::cerr << "ggml_vk_host_free(" << ptr << ")" << std::endl; | |
| vk_buffer buf; | |
| size_t index; | |
| for (size_t i = 0; i < ctx->pinned_memory.size(); i++) { | |
| const uint8_t* addr = (const uint8_t*) std::get<0>(ctx->pinned_memory[i]); | |
| const uint8_t* endr = addr + std::get<1>(ctx->pinned_memory[i]); | |
| if (ptr >= addr && ptr < endr) { | |
| buf = std::get<2>(ctx->pinned_memory[i]); | |
| index = i; | |
| break; | |
| } | |
| } | |
| if (buf == nullptr) { | |
| fprintf(stderr, "WARNING: failed to free pinned memory: memory not in map\n"); | |
| return; | |
| } | |
| ggml_vk_destroy_buffer(buf); | |
| ctx->pinned_memory.erase(ctx->pinned_memory.begin() + index); | |
| } | |
| static void ggml_vk_host_get(ggml_backend_vk_context * ctx, const void * ptr, vk_buffer& buf, size_t& buf_offset) { | |
| buf = nullptr; | |
| buf_offset = 0; | |
| for (size_t i = 0; i < ctx->pinned_memory.size(); i++) { | |
| const uint8_t* addr = (const uint8_t*) std::get<0>(ctx->pinned_memory[i]); | |
| const uint8_t* endr = addr + std::get<1>(ctx->pinned_memory[i]); | |
| if (ptr >= addr && ptr < endr) { | |
| buf = std::get<2>(ctx->pinned_memory[i]); | |
| buf_offset = ((const uint8_t *)ptr) - addr; | |
| break; | |
| } | |
| } | |
| } | |
| static vk_submission ggml_vk_begin_submission(ggml_backend_vk_context * ctx, vk_queue& q, bool one_time = true) { | |
| vk_submission s; | |
| s.buffer = ggml_vk_create_cmd_buffer(ctx, q); | |
| if (one_time) { | |
| s.buffer.begin({ vk::CommandBufferUsageFlagBits::eOneTimeSubmit }); | |
| } else { | |
| s.buffer.begin({ vk::CommandBufferUsageFlags{} }); | |
| } | |
| return s; | |
| } | |
| static void ggml_vk_dispatch_pipeline(ggml_backend_vk_context * ctx, vk_context * subctx, vk_pipeline& pipeline, std::vector<vk_subbuffer>&& buffers, size_t push_constant_size, const void* push_constants, std::array<uint32_t, 3> elements) { | |
| const uint32_t wg0 = CEIL_DIV(elements[0], pipeline->wg_denoms[0]); | |
| const uint32_t wg1 = CEIL_DIV(elements[1], pipeline->wg_denoms[1]); | |
| const uint32_t wg2 = CEIL_DIV(elements[2], pipeline->wg_denoms[2]); | |
| std::cerr << "ggml_vk_dispatch_pipeline(" << pipeline->name << ", (" << wg0 << "," << wg1 << "," << wg2 << "))" << std::endl; | |
| std::vector<vk::DescriptorBufferInfo> descriptor_buffer_infos; | |
| std::vector<vk::WriteDescriptorSet> write_descriptor_sets; | |
| GGML_ASSERT(pipeline->descriptor_set_idx < pipeline->descriptor_sets.size()); | |
| GGML_ASSERT(buffers.size() == pipeline->parameter_count); | |
| vk::DescriptorSet& descriptor_set = pipeline->descriptor_sets[pipeline->descriptor_set_idx++]; | |
| for (uint32_t i = 0; i < pipeline->parameter_count; i++) { | |
| descriptor_buffer_infos.push_back({buffers[i].buffer->buffer, buffers[i].offset, buffers[i].size}); | |
| } | |
| for (uint32_t i = 0; i < pipeline->parameter_count; i++) { | |
| write_descriptor_sets.push_back({descriptor_set, i, 0, 1, vk::DescriptorType::eStorageBuffer, nullptr, &descriptor_buffer_infos[i]}); | |
| } | |
| ctx->device->device.updateDescriptorSets(write_descriptor_sets, {}); | |
| subctx->s->buffer.pushConstants(pipeline->layout, vk::ShaderStageFlagBits::eCompute, 0, push_constant_size, push_constants); | |
| subctx->s->buffer.bindPipeline(vk::PipelineBindPoint::eCompute, pipeline->pipeline); | |
| subctx->s->buffer.bindDescriptorSets(vk::PipelineBindPoint::eCompute, | |
| pipeline->layout, | |
| 0, | |
| { descriptor_set }, | |
| {}); | |
| subctx->s->buffer.dispatch(wg0, wg1, wg2); | |
| } | |
| static void ggml_vk_end_submission(vk_submission& s, std::vector<vk_semaphore> wait_semaphores, std::vector<vk_semaphore> signal_semaphores) { | |
| s.buffer.end(); | |
| s.wait_semaphores = std::move(wait_semaphores); | |
| s.signal_semaphores = std::move(signal_semaphores); | |
| } | |
| static void ggml_vk_ctx_end(vk_context * ctx) { | |
| std::cerr << "ggml_vk_ctx_end(" << ctx << ", " << ctx->seqs.size() << ")" << std::endl; | |
| if (ctx->s == nullptr) { | |
| return; | |
| } | |
| ctx->s->buffer.end(); | |
| ctx->s = nullptr; | |
| } | |
| static void ggml_vk_ctx_begin(ggml_backend_vk_context * ctx, vk_context * subctx) { | |
| std::cerr << "ggml_vk_ctx_begin(" << ctx << ")" << std::endl; | |
| if (subctx->s != nullptr) { | |
| ggml_vk_ctx_end(subctx); | |
| } | |
| subctx->seqs.push_back({ ggml_vk_begin_submission(ctx, *subctx->q) }); | |
| subctx->s = subctx->seqs[subctx->seqs.size() - 1].data(); | |
| } | |
| static size_t ggml_vk_align_size(size_t width, size_t align) { | |
| std::cerr << "ggml_vk_align_size(" << width << ", " << align << ")" << std::endl; | |
| return CEIL_DIV(width, align) * align; | |
| } | |
| static void deferred_memcpy(void * dst, const void * src, size_t size, std::vector<vk_staging_memcpy>* memcpys = nullptr) { | |
| if (memcpys == nullptr) { | |
| memcpy(dst, src, size); | |
| } else { | |
| memcpys->emplace_back(dst, src, size); | |
| } | |
| } | |
| static void ggml_vk_ensure_sync_staging_buffer(ggml_backend_vk_context * ctx, size_t size) { | |
| if (ctx->sync_staging == nullptr || ctx->sync_staging->size < size) { | |
| ggml_vk_destroy_buffer(ctx->sync_staging); | |
| ctx->sync_staging = ggml_vk_create_buffer_check(ctx, size, | |
| vk::MemoryPropertyFlagBits::eHostVisible | vk::MemoryPropertyFlagBits::eHostCoherent | vk::MemoryPropertyFlagBits::eHostCached, | |
| vk::MemoryPropertyFlagBits::eHostVisible | vk::MemoryPropertyFlagBits::eHostCoherent); | |
| } | |
| } | |
| static void ggml_vk_buffer_write_nc_async(ggml_backend_vk_context * ctx, vk_context * subctx, vk_buffer& dst, size_t offset, const ggml_tensor * tensor, bool sync_staging = false) { | |
| std::cerr << "ggml_vk_buffer_write_nc_async(" << tensor << ")" << std::endl; | |
| GGML_ASSERT(!ggml_is_contiguous(tensor)); | |
| // Buffer is already mapped | |
| if(dst->memory_property_flags & vk::MemoryPropertyFlagBits::eHostVisible) { | |
| std::cerr << "ggml_vulkan: buffer_write_nc_async dst buffer is host_visible. Use synchronous write." << std::endl; | |
| GGML_ASSERT(false); | |
| } | |
| // Check if src is pinned memory | |
| vk_buffer buf; | |
| size_t buf_offset; | |
| ggml_vk_host_get(ctx, tensor->data, buf, buf_offset); | |
| const uint64_t ne0 = tensor->ne[0]; | |
| const uint64_t ne1 = tensor->ne[1]; | |
| const uint64_t ne2 = tensor->ne[2]; | |
| const uint64_t ne3 = tensor->ne[3]; | |
| const uint64_t nb0 = tensor->nb[0]; | |
| const uint64_t nb1 = tensor->nb[1]; | |
| const uint64_t nb2 = tensor->nb[2]; | |
| const uint64_t nb3 = tensor->nb[3]; | |
| const ggml_type type = tensor->type; | |
| const uint64_t ts = ggml_type_size(type); | |
| const uint64_t bs = ggml_blck_size(type); | |
| const uint64_t dstnb0 = ts; | |
| const uint64_t dstnb1 = dstnb0*(ne0/bs); | |
| const uint64_t dstnb2 = dstnb1*ne1; | |
| const uint64_t dstnb3 = dstnb2*ne2; | |
| const uint64_t ne = ggml_nelements(tensor); | |
| if (buf != nullptr) { | |
| // Memory is pinned, use as staging buffer | |
| std::vector<vk::BufferCopy> slices; | |
| for (uint64_t i3 = 0; i3 < ne3; i3++) { | |
| for (uint64_t i2 = 0; i2 < ne2; i2++) { | |
| // Find longest contiguous slice | |
| if (ne1*nb1 == dstnb2) { | |
| slices.push_back({ buf_offset + i3*nb3 + i2*nb2, offset + i3*dstnb3 + i2*dstnb2, dstnb2 }); | |
| } else { | |
| for (uint64_t i1 = 0; i1 < ne1; i1++) { | |
| if (ne0*nb0/bs == dstnb1) { | |
| slices.push_back({ buf_offset + i3*nb3 + i2*nb2 + i1*nb1, offset + i3*dstnb3 + i2*dstnb2 + i1*dstnb1, dstnb1 }); | |
| } else { | |
| const uint64_t s_off = buf_offset + i3*nb3 + i2*nb2 + i1*nb1; | |
| const uint64_t d_off = offset + i3*dstnb3 + i2*dstnb2 + i1*dstnb1; | |
| for (uint64_t i0 = 0; i0 < ne0; i0++) { | |
| slices.push_back({ s_off + i1*nb0, d_off + i0*dstnb0, dstnb0 }); | |
| } | |
| } | |
| } | |
| } | |
| } | |
| } | |
| ggml_vk_sync_buffers(subctx); | |
| subctx->s->buffer.copyBuffer(buf->buffer, dst->buffer, slices); | |
| return; | |
| } | |
| // Staging buffer required | |
| vk_buffer staging = ctx->staging; | |
| size_t staging_offset = ctx->staging_offset; | |
| const size_t copy_size = ts*ne/bs; | |
| if (ctx->staging->size < ctx->staging_offset + copy_size) { | |
| if (sync_staging) { | |
| // Create temporary larger buffer | |
| ggml_vk_ensure_sync_staging_buffer(ctx, copy_size); | |
| staging = ctx->sync_staging; | |
| staging_offset = 0; | |
| } else { | |
| GGML_ASSERT(false); | |
| } | |
| } | |
| VkBufferCopy buf_copy{ staging_offset, offset, copy_size }; | |
| ggml_vk_sync_buffers(subctx); | |
| vkCmdCopyBuffer(subctx->s->buffer, staging->buffer, dst->buffer, 1, &buf_copy); | |
| for (uint64_t i3 = 0; i3 < ne3; i3++) { | |
| for (uint64_t i2 = 0; i2 < ne2; i2++) { | |
| // Find longest contiguous slice | |
| if (ne1*nb1 == dstnb2) { | |
| deferred_memcpy((uint8_t *)staging->ptr + staging_offset + i3*dstnb3 + i2*dstnb2, (const uint8_t *) tensor->data + buf_offset + i3*nb3 + i2*nb2, dstnb2, &subctx->in_memcpys); | |
| } else { | |
| for (uint64_t i1 = 0; i1 < ne1; i1++) { | |
| if (ne0*nb0/bs == dstnb1) { | |
| deferred_memcpy((uint8_t *)staging->ptr + staging_offset + i3*dstnb3 + i2*dstnb2 + i1*dstnb1, (const uint8_t *) tensor->data + buf_offset + i3*nb3 + i2*nb2 + i1*nb1, dstnb1, &subctx->in_memcpys); | |
| } else { | |
| const uint64_t s_off = buf_offset + i3*nb3 + i2*nb2 + i1*nb1; | |
| const uint64_t d_off = staging_offset + i3*dstnb3 + i2*dstnb2 + i1*dstnb1; | |
| for (uint64_t i0 = 0; i0 < ne0; i0++) { | |
| deferred_memcpy((uint8_t *)staging->ptr + d_off + i0*dstnb0, (const uint8_t *) tensor->data + s_off + i0*nb0, dstnb0, &subctx->in_memcpys); | |
| } | |
| } | |
| } | |
| } | |
| } | |
| } | |
| } | |
| static void ggml_vk_buffer_write_2d_async(ggml_backend_vk_context * ctx, vk_context * subctx, vk_buffer& dst, size_t offset, const void * src, size_t spitch, size_t width, size_t height, bool sync_staging = false) { | |
| std::cerr << "ggml_vk_buffer_write_2d_async(" << width << ", " << height << ")" << std::endl; | |
| // Make sure ctx owns the buffer | |
| GGML_ASSERT(dst->ctx == ctx); | |
| // Buffer is already mapped | |
| if(dst->memory_property_flags & vk::MemoryPropertyFlagBits::eHostVisible) { | |
| std::cerr << "ggml_vulkan: buffer_write_async dst buffer is host_visible. Use synchronous write." << std::endl; | |
| GGML_ASSERT(false); | |
| } | |
| // Check if src is pinned memory | |
| vk_buffer buf = nullptr; | |
| size_t buf_offset; | |
| ggml_vk_host_get(ctx, src, buf, buf_offset); | |
| if (buf != nullptr) { | |
| // Memory is pinned, use as staging buffer | |
| std::vector<vk::BufferCopy> slices(1); | |
| if (width == spitch) { | |
| // Only do single write if stride is equal | |
| slices[0].srcOffset = buf_offset; | |
| slices[0].dstOffset = offset; | |
| slices[0].size = width * height; | |
| } else { | |
| slices.resize(height); | |
| for (size_t i = 0; i < height; i++) { | |
| slices[i].srcOffset = buf_offset + i * spitch; | |
| slices[i].dstOffset = offset + i * width; | |
| slices[i].size = width; | |
| } | |
| } | |
| ggml_vk_sync_buffers(subctx); | |
| subctx->s->buffer.copyBuffer(buf->buffer, dst->buffer, slices); | |
| return; | |
| } | |
| std::cerr << "STAGING" << std::endl; | |
| // Staging buffer required | |
| vk_buffer staging = ctx->staging; | |
| size_t staging_offset = ctx->staging_offset; | |
| const size_t copy_size = width*height; | |
| if (ctx->staging == nullptr || ctx->staging->size < ctx->staging_offset + copy_size) { | |
| if (sync_staging) { | |
| ggml_vk_ensure_sync_staging_buffer(ctx, copy_size); | |
| staging = ctx->sync_staging; | |
| staging_offset = 0; | |
| } else { | |
| GGML_ASSERT(false); | |
| } | |
| } | |
| VkBufferCopy buf_copy = { | |
| staging_offset, | |
| offset, | |
| copy_size}; | |
| ggml_vk_sync_buffers(subctx); | |
| vkCmdCopyBuffer(subctx->s->buffer, staging->buffer, dst->buffer, 1, &buf_copy); | |
| if (width == spitch) { | |
| deferred_memcpy((uint8_t *)staging->ptr + staging_offset, src, width * height, &subctx->in_memcpys); | |
| } else { | |
| for (size_t i = 0; i < height; i++) { | |
| deferred_memcpy((uint8_t *)staging->ptr + staging_offset + i * width, (const uint8_t *) src + i * spitch, width, &subctx->in_memcpys); | |
| } | |
| } | |
| } | |
| static void ggml_vk_buffer_write_async(ggml_backend_vk_context * ctx, vk_context * subctx, vk_buffer& dst, size_t offset, const void * src, size_t size, bool sync_staging = false) { | |
| std::cerr << "ggml_vk_buffer_write_async(" << size << ")" << std::endl; | |
| return ggml_vk_buffer_write_2d_async(ctx, subctx, dst, offset, src, size, size, 1, sync_staging); | |
| } | |
| static void ggml_vk_buffer_write_2d(ggml_backend_vk_context * ctx, vk_buffer& dst, size_t offset, const void * src, size_t spitch, size_t width, size_t height) { | |
| std::cerr << "ggml_vk_buffer_write_2d(" << width << ", " << height << ")" << std::endl; | |
| // Buffer is already mapped | |
| if(dst->memory_property_flags & vk::MemoryPropertyFlagBits::eHostVisible) { | |
| GGML_ASSERT(dst->memory_property_flags & vk::MemoryPropertyFlagBits::eHostCoherent); | |
| for (size_t i = 0; i < height; i++) { | |
| memcpy((uint8_t *)dst->ptr + offset + i * width, (const uint8_t *) src + i * spitch, width); | |
| } | |
| } else { | |
| vk_context * subctx = ggml_vk_create_context(ctx, ctx->device->transfer_queue); | |
| ggml_vk_ctx_begin(ctx, subctx); | |
| ggml_vk_buffer_write_2d_async(ctx, subctx, dst, offset, src, spitch, width, height, true); | |
| ggml_vk_ctx_end(subctx); | |
| for (auto& cpy : subctx->in_memcpys) { | |
| memcpy(cpy.dst, cpy.src, cpy.n); | |
| } | |
| ggml_vk_submit(subctx, ctx->fence); | |
| VK_CHECK(ctx->device->device.waitForFences({ ctx->fence }, true, UINT64_MAX), "vk_buffer_write_2d waitForFences"); | |
| ctx->device->device.resetFences({ ctx->fence }); | |
| } | |
| } | |
| static void ggml_vk_buffer_write(ggml_backend_vk_context * ctx, vk_buffer& dst, size_t offset, const void * src, size_t size) { | |
| std::cerr << "ggml_vk_buffer_write(" << size << ")" << std::endl; | |
| ggml_vk_buffer_write_2d(ctx, dst, offset, src, 0, size, 1); | |
| } | |
| static void ggml_vk_buffer_read_2d_async(ggml_backend_vk_context * ctx, vk_context * subctx, vk_buffer& src, size_t offset, void * dst, size_t spitch, size_t dpitch, size_t width, size_t height, bool sync_staging = false) { | |
| std::cerr << "ggml_vk_buffer_read_2d_async(offset=" << offset << ", width=" << width << ", height=" << height << ")" << std::endl; | |
| GGML_ASSERT(width > 0); | |
| GGML_ASSERT(height > 0); | |
| GGML_ASSERT(src != nullptr); | |
| // Make sure ctx owns the buffer | |
| GGML_ASSERT(src->ctx == ctx); | |
| // Check if dst is pinned memory | |
| vk_buffer buf = nullptr; | |
| size_t buf_offset; | |
| ggml_vk_host_get(ctx, dst, buf, buf_offset); | |
| std::vector<vk::BufferCopy> slices(1); | |
| if (width == spitch && width == dpitch) { | |
| // Only do single write if stride is equal | |
| slices[0].srcOffset = offset; | |
| slices[0].dstOffset = buf_offset; | |
| slices[0].size = width * height; | |
| } else { | |
| slices.resize(height); | |
| for (size_t i = 0; i < height; i++) { | |
| slices[i].srcOffset = offset + i * spitch; | |
| slices[i].dstOffset = buf_offset + i * dpitch; | |
| slices[i].size = width; | |
| } | |
| } | |
| if (buf != nullptr) { | |
| // Memory is pinned, use as staging buffer | |
| ggml_vk_sync_buffers(subctx); | |
| subctx->s->buffer.copyBuffer(src->buffer, buf->buffer, slices); | |
| return; | |
| } | |
| std::cerr << "STAGING" << std::endl; | |
| // Fall back to staging buffer | |
| vk_buffer staging = ctx->staging; | |
| const size_t copy_size = dpitch * height; | |
| if (ctx->staging == nullptr || ctx->staging->size < ctx->staging_offset + copy_size) { | |
| if (sync_staging) { | |
| // Create temporary larger buffer | |
| ggml_vk_ensure_sync_staging_buffer(ctx, copy_size); | |
| staging = ctx->sync_staging; | |
| } else { | |
| GGML_ASSERT(false); | |
| } | |
| } | |
| ggml_vk_sync_buffers(subctx); | |
| subctx->s->buffer.copyBuffer(src->buffer, staging->buffer, slices); | |
| deferred_memcpy(dst, staging->ptr, copy_size, &subctx->out_memcpys); | |
| } | |
| static void ggml_vk_buffer_read_async(ggml_backend_vk_context * ctx, vk_context * subctx, vk_buffer& src, size_t offset, void * dst, size_t size, bool sync_staging = false) { | |
| return ggml_vk_buffer_read_2d_async(ctx, subctx, src, offset, dst, size, size, size, 1, sync_staging); | |
| } | |
| static void ggml_vk_buffer_read(ggml_backend_vk_context * ctx, vk_buffer& src, size_t offset, void * dst, size_t size) { | |
| std::cerr << "ggml_vk_buffer_read(" << offset << ", " << size << ")" << std::endl; | |
| if(src->memory_property_flags & vk::MemoryPropertyFlagBits::eHostVisible) { | |
| GGML_ASSERT(src->memory_property_flags & vk::MemoryPropertyFlagBits::eHostCoherent); | |
| memcpy(dst, (uint8_t *) src->ptr + offset, size); | |
| } else { | |
| vk_context * subctx = ggml_vk_create_context(ctx, ctx->device->transfer_queue); | |
| ggml_vk_ctx_begin(ctx, subctx); | |
| ggml_vk_buffer_read_async(ctx, subctx, src, offset, dst, size, true); | |
| ggml_vk_ctx_end(subctx); | |
| ggml_vk_submit(subctx, ctx->fence); | |
| VK_CHECK(ctx->device->device.waitForFences({ ctx->fence }, true, UINT64_MAX), "vk_buffer_read waitForFences"); | |
| ctx->device->device.resetFences({ ctx->fence }); | |
| for (auto& cpy : subctx->out_memcpys) { | |
| memcpy(cpy.dst, cpy.src, cpy.n); | |
| } | |
| } | |
| } | |
| static void ggml_vk_buffer_copy_async(vk_context * ctx, vk_buffer& dst, size_t dst_offset, vk_buffer& src, size_t src_offset, size_t size) { | |
| std::cerr << "ggml_vk_buffer_copy_async(" << size << ")" << std::endl; | |
| // Make sure both buffers are on same ctx | |
| GGML_ASSERT(src->ctx == dst->ctx); | |
| VkBufferCopy bc{ src_offset, dst_offset, size }; | |
| vkCmdCopyBuffer(ctx->s->buffer, src->buffer, dst->buffer, 1, &bc); | |
| } | |
| static void ggml_vk_buffer_copy(vk_buffer& dst, size_t dst_offset, vk_buffer& src, size_t src_offset, size_t size) { | |
| if (src->ctx == dst->ctx) { | |
| std::cerr << "ggml_vk_buffer_copy(SINGLE_DEVICE, " << size << ")" << std::endl; | |
| // Copy within the device | |
| ggml_backend_vk_context * ctx = src->ctx; | |
| vk_context * subctx = ggml_vk_create_context(ctx, ctx->device->transfer_queue); | |
| ggml_vk_ctx_begin(ctx, subctx); | |
| ggml_vk_buffer_copy_async(subctx, dst, dst_offset, src, src_offset, size); | |
| ggml_vk_ctx_end(subctx); | |
| ggml_vk_submit(subctx, ctx->fence); | |
| VK_CHECK(ctx->device->device.waitForFences({ ctx->fence }, true, UINT64_MAX), "vk_buffer_copy waitForFences"); | |
| ctx->device->device.resetFences({ ctx->fence }); | |
| } else { | |
| std::cerr << "ggml_vk_buffer_copy(MULTI_DEVICE, " << size << ")" << std::endl; | |
| // Copy device to device | |
| ggml_backend_vk_context * src_ctx = src->ctx; | |
| ggml_backend_vk_context * dst_ctx = dst->ctx; | |
| ggml_vk_ensure_sync_staging_buffer(src_ctx, size); | |
| ggml_vk_ensure_sync_staging_buffer(dst_ctx, size); | |
| // Copy to src staging buffer | |
| ggml_vk_buffer_copy(src_ctx->sync_staging, 0, src, src_offset, size); | |
| // memcpy to dst staging buffer | |
| memcpy(dst_ctx->sync_staging->ptr, src_ctx->sync_staging->ptr, size); | |
| // Copy to dst buffer | |
| ggml_vk_buffer_copy(dst, dst_offset, dst_ctx->sync_staging, 0, size); | |
| } | |
| } | |
| static void ggml_vk_buffer_memset(ggml_backend_vk_context * ctx, vk_buffer& dst, size_t offset, uint32_t c, size_t size) { | |
| std::cerr << "ggml_vk_buffer_memset(" << offset << ", " << c << ", " << size << ")" << std::endl; | |
| // Make sure ctx owns the buffer | |
| GGML_ASSERT(dst->ctx == ctx); | |
| vk_context * subctx = ggml_vk_create_context(ctx, ctx->device->transfer_queue); | |
| ggml_vk_ctx_begin(ctx, subctx); | |
| subctx->s->buffer.fillBuffer(dst->buffer, offset, size, c); | |
| ggml_vk_ctx_end(subctx); | |
| ggml_vk_submit(subctx, ctx->fence); | |
| VK_CHECK(ctx->device->device.waitForFences({ ctx->fence }, true, UINT64_MAX), "vk_memset waitForFences"); | |
| ctx->device->device.resetFences({ ctx->fence }); | |
| } | |
| static void ggml_vk_h2d_tensor_2d(ggml_backend_vk_context * ctx, vk_context * subctx, vk_buffer& dst, size_t offset, const ggml_tensor * src, uint64_t i3, uint64_t i2, uint64_t i1) { | |
| std::cerr << "ggml_vk_h2d_tensor_2d(dst=" << dst << ", offset=" << offset << ", src=" << src << ", i3=" << i3 << ", i2=" << i2 << ", i1=" << i1 << ")" << std::endl; | |
| const uint64_t ne0 = src->ne[0]; | |
| const uint64_t ne1 = src->ne[1]; | |
| const uint64_t nb0 = src->nb[0]; | |
| const uint64_t nb1 = src->nb[1]; | |
| const uint64_t nb2 = src->nb[2]; | |
| const uint64_t nb3 = src->nb[3]; | |
| const enum ggml_type type = src->type; | |
| const size_t ts = ggml_type_size(type); | |
| const size_t bs = ggml_blck_size(type); | |
| const size_t row_length = ts*ne0/bs; | |
| const void * x = (const void *) ((const char *) src->data + i2*nb2 + i3*nb3); | |
| if (nb0 == ts && nb1 == row_length) { | |
| return ggml_vk_buffer_write_async(ctx, subctx, dst, offset, x, i1*nb1); | |
| } | |
| if (nb0 == ts && (i1 == ne1 || !ggml_is_permuted(src))) { | |
| return ggml_vk_buffer_write_2d_async(ctx, subctx, dst, offset, x, nb1, row_length, i1); | |
| } | |
| GGML_ASSERT(i3 == 0); | |
| GGML_ASSERT(i2 == 0); | |
| GGML_ASSERT(i1 == (uint64_t) ggml_nrows(src)); | |
| return ggml_vk_buffer_write_nc_async(ctx, subctx, dst, offset, src); | |
| } | |
| static void ggml_vk_d2h_tensor_2d(ggml_backend_vk_context * ctx, vk_context * subctx, vk_buffer& src, size_t offset, const ggml_tensor * dst) { | |
| std::cerr << "ggml_vk_d2h_tensor_2d()" << std::endl; | |
| const uint64_t ne0 = dst->ne[0]; | |
| const uint64_t ne1 = dst->ne[1]; | |
| const uint64_t ne2 = dst->ne[2]; | |
| const uint64_t ne3 = dst->ne[3]; | |
| const uint64_t nb0 = dst->nb[0]; | |
| const uint64_t nb1 = dst->nb[1]; | |
| // const uint64_t nb2 = dst->nb[2]; | |
| // const uint64_t nb3 = dst->nb[3]; | |
| const enum ggml_type type = dst->type; | |
| const size_t ts = ggml_type_size(type); | |
| const size_t bs = ggml_blck_size(type); | |
| const size_t row_length = ts*ne0/bs; | |
| if (ggml_is_contiguous(dst)) { | |
| return ggml_vk_buffer_read_async(ctx, subctx, src, offset, dst->data, ne1*nb1*ne2*ne3); | |
| } | |
| if (nb0 == ts) { | |
| return ggml_vk_buffer_read_2d_async(ctx, subctx, src, offset, dst->data, nb1, nb1, row_length, ne1*ne2*ne3); | |
| } | |
| GGML_ASSERT(false); | |
| } | |
| static uint32_t ggml_vk_guess_split_k(int m, int n, int k) { | |
| std::cerr << "ggml_vk_guess_split_k(" << m << ", " << n << ", " << k << ")" << std::endl; | |
| // if (k > 128 && (m < 128 || n < 128) && m > 2 && n > 2) { | |
| // return 4; | |
| // } | |
| return 1; | |
| GGML_UNUSED(m); GGML_UNUSED(n); GGML_UNUSED(k); | |
| } | |
| static vk_pipeline ggml_vk_guess_matmul_pipeline_amd(ggml_backend_vk_context * ctx, vk_matmul_pipeline& mmp, int m, int n, bool aligned) { | |
| if (m <= 32 || n <= 32) { | |
| return aligned ? mmp->a_s : mmp->s; | |
| } | |
| return aligned ? mmp->a_m : mmp->m; | |
| GGML_UNUSED(ctx); | |
| } | |
| static vk_pipeline ggml_vk_guess_matmul_pipeline_apple(ggml_backend_vk_context * ctx, vk_matmul_pipeline& mmp, bool aligned) { | |
| return aligned ? mmp->a_m : mmp->m; | |
| GGML_UNUSED(ctx); | |
| } | |
| static vk_pipeline ggml_vk_guess_matmul_pipeline_intel(ggml_backend_vk_context * ctx, vk_matmul_pipeline& mmp, bool aligned) { | |
| return aligned ? mmp->a_s : mmp->s; | |
| GGML_UNUSED(ctx); | |
| } | |
| static vk_pipeline ggml_vk_guess_matmul_pipeline(ggml_backend_vk_context * ctx, vk_matmul_pipeline& mmp, int m, int n, bool aligned) { | |
| std::cerr << "ggml_vk_guess_matmul_pipeline(" << m << ", " << n << ", " << aligned << ")" << std::endl; | |
| switch (ctx->device->vendor_id) { | |
| case VK_VENDOR_ID_AMD: | |
| return ggml_vk_guess_matmul_pipeline_amd(ctx, mmp, m, n, aligned); | |
| case VK_VENDOR_ID_APPLE: | |
| return ggml_vk_guess_matmul_pipeline_apple(ctx, mmp, aligned); | |
| case VK_VENDOR_ID_INTEL: | |
| return ggml_vk_guess_matmul_pipeline_intel(ctx, mmp, aligned); | |
| default: | |
| break; | |
| } | |
| if (m <= 32 || n <= 32) { | |
| return aligned ? mmp->a_s : mmp->s; | |
| } | |
| if (m <= 64 || n <= 64) { | |
| return aligned ? mmp->a_m : mmp->m; | |
| } | |
| return aligned ? mmp->a_l : mmp->l; | |
| } | |
| static uint32_t ggml_vk_guess_matmul_pipeline_align(ggml_backend_vk_context * ctx, vk_matmul_pipeline& mmp, int m, int n) { | |
| std::cerr << "ggml_vk_guess_matmul_pipeline_align(" << m << ", " << n << ")" << std::endl; | |
| return ggml_vk_guess_matmul_pipeline(ctx, mmp, m, n, true)->align; | |
| } | |
| static void ggml_vk_matmul( | |
| ggml_backend_vk_context * ctx, vk_context * subctx, vk_pipeline& pipeline, | |
| vk_subbuffer&& a, vk_subbuffer&& b, vk_subbuffer&& d, vk_subbuffer&& split_k_buffer, | |
| uint32_t m, uint32_t n, uint32_t k, uint32_t stride_a, uint32_t stride_b, uint32_t stride_d, | |
| uint32_t split_k, uint32_t batch, uint32_t ne02, uint32_t ne12, uint32_t broadcast2, uint32_t broadcast3, | |
| uint32_t batch_stride_a, uint32_t batch_stride_b, uint32_t batch_stride_d, | |
| uint32_t expert_stride_b, uint32_t expert_stride_d, uint32_t idx, uint32_t nbi1, uint32_t n_as) { | |
| std::cerr << "ggml_vk_matmul(a: (" << a.buffer->buffer << ", " << a.offset << ", " << a.size << "), b: (" << b.buffer->buffer << ", " << b.offset << ", " << b.size << "), c: (" << d.buffer->buffer << ", " << d.offset << ", " << d.size << "), split_k: (" << split_k_buffer.buffer->buffer << ", " << split_k_buffer.offset << ", " << split_k_buffer.size << "), m: " << m << ", n: " << n << ", k: " << k << ", stride_a: " << stride_a << ", stride_b: " << stride_b << ", stride_d: " << stride_d << ", split_k: " << split_k << ", batch: " << batch << ", ne02: " << ne02 << ", ne12: " << ne12 << ", broadcast2: " << broadcast2 << ", broadcast3: " << broadcast3 << ", batch_stride_a: " << batch_stride_a << ", batch_stride_b: " << batch_stride_b << ", batch_stride_d: " << batch_stride_d << ")" << std::endl; | |
| ggml_vk_sync_buffers(subctx); | |
| if (split_k == 1) { | |
| const vk_mat_mat_push_constants pc = { m, n, k, stride_a, stride_b, stride_d, k, ne02, ne12, broadcast2, broadcast3, batch_stride_a, batch_stride_b, batch_stride_d, expert_stride_b, expert_stride_d, idx, nbi1, n_as }; | |
| ggml_vk_dispatch_pipeline(ctx, subctx, pipeline, { a, b, d }, sizeof(vk_mat_mat_push_constants), &pc, { m, n, batch }); | |
| return; | |
| } | |
| GGML_ASSERT(batch_stride_d == m * n); | |
| const vk_mat_mat_push_constants pc1 = { m, n, k, stride_a, stride_b, stride_d, CEIL_DIV(k, split_k), ne02, ne12, broadcast2, broadcast3, batch_stride_a, batch_stride_b, batch_stride_d, expert_stride_b, expert_stride_d, idx, nbi1, n_as }; | |
| // Make sure enough workgroups get assigned for split k to work | |
| ggml_vk_dispatch_pipeline(ctx, subctx, pipeline, { a, b, split_k_buffer }, sizeof(vk_mat_mat_push_constants), &pc1, { (CEIL_DIV(m, pipeline->wg_denoms[0]) * pipeline->wg_denoms[0]) * split_k, n, batch }); | |
| ggml_vk_sync_buffers(subctx); | |
| const std::array<uint32_t, 2> pc2 = { (uint32_t)(m * n * batch), split_k }; | |
| ggml_vk_dispatch_pipeline(ctx, subctx, ctx->device->pipeline_matmul_split_k_reduce, { split_k_buffer, d }, pc2.size() * sizeof(uint32_t), pc2.data(), { m * n * batch, 1, 1 }); | |
| } | |
| static void ggml_vk_matmul_id( | |
| ggml_backend_vk_context * ctx, vk_context * subctx, vk_pipeline& pipeline, | |
| vk_subbuffer&& ids, vk_subbuffer&& b, vk_subbuffer&& d, vk_subbuffer&& a, vk_subbuffer&& split_k_buffer, | |
| uint32_t m, uint32_t n, uint32_t k, uint32_t stride_a, uint32_t stride_b, uint32_t stride_d, | |
| uint32_t split_k, uint32_t batch, uint32_t ne02, uint32_t ne12, uint32_t broadcast2, uint32_t broadcast3, | |
| uint32_t batch_stride_a, uint32_t batch_stride_b, uint32_t batch_stride_d, | |
| uint32_t expert_stride_b, uint32_t expert_stride_d, uint32_t idx, uint32_t nbi1, uint32_t n_as) { | |
| std::cerr << "ggml_vk_matmul(a: (" << a.buffer->buffer << ", " << a.offset << ", " << a.size << "), b: (" << b.buffer->buffer << ", " << b.offset << ", " << b.size << "), c: (" << d.buffer->buffer << ", " << d.offset << ", " << d.size << "), split_k: (" << split_k_buffer.buffer->buffer << ", " << split_k_buffer.offset << ", " << split_k_buffer.size << "), m: " << m << ", n: " << n << ", k: " << k << ", stride_a: " << stride_a << ", stride_b: " << stride_b << ", stride_d: " << stride_d << ", split_k: " << split_k << ", batch: " << batch << ", ne02: " << ne02 << ", ne12: " << ne12 << ", broadcast2: " << broadcast2 << ", broadcast3: " << broadcast3 << ", batch_stride_a: " << batch_stride_a << ", batch_stride_b: " << batch_stride_b << ", batch_stride_d: " << batch_stride_d << ")" << std::endl; | |
| ggml_vk_sync_buffers(subctx); | |
| if (split_k == 1) { | |
| const vk_mat_mat_push_constants pc = { m, n, k, stride_a, stride_b, stride_d, k, ne02, ne12, broadcast2, broadcast3, batch_stride_a, batch_stride_b, batch_stride_d, expert_stride_b, expert_stride_d, idx, nbi1, n_as }; | |
| ggml_vk_dispatch_pipeline(ctx, subctx, pipeline, { ids, b, d, a }, sizeof(vk_mat_mat_push_constants), &pc, { m, n, batch }); | |
| return; | |
| } | |
| GGML_ASSERT(batch_stride_d == m * n); | |
| const vk_mat_mat_push_constants pc1 = { m, n, k, stride_a, stride_b, stride_d, CEIL_DIV(k, split_k), ne02, ne12, broadcast2, broadcast3, batch_stride_a, batch_stride_b, batch_stride_d, expert_stride_b, expert_stride_d, idx, nbi1, n_as }; | |
| // Make sure enough workgroups get assigned for split k to work | |
| ggml_vk_dispatch_pipeline(ctx, subctx, pipeline, { ids, b, split_k_buffer, a }, sizeof(vk_mat_mat_push_constants), &pc1, { (CEIL_DIV(m, pipeline->wg_denoms[0]) * pipeline->wg_denoms[0]) * split_k, n, batch }); | |
| ggml_vk_sync_buffers(subctx); | |
| const std::array<uint32_t, 2> pc2 = { (uint32_t)(m * n * batch), split_k }; | |
| ggml_vk_dispatch_pipeline(ctx, subctx, ctx->device->pipeline_matmul_split_k_reduce, { split_k_buffer, d }, pc2.size() * sizeof(uint32_t), pc2.data(), { m * n * batch, 1, 1 }); | |
| } | |
| static bool ggml_vk_dim01_contiguous(const ggml_tensor * tensor) { | |
| return | |
| tensor->nb[0] == ggml_type_size(tensor->type) && | |
| tensor->nb[1] == (tensor->nb[0]*tensor->ne[0])/ggml_blck_size(tensor->type) && | |
| tensor->nb[3] == tensor->nb[2]*tensor->ne[2]; | |
| } | |
| static vk_pipeline ggml_vk_get_cpy_pipeline(ggml_backend_vk_context * ctx, ggml_type from, ggml_type to) { | |
| if (from == GGML_TYPE_F32 && to == GGML_TYPE_F32) { | |
| return ctx->device->pipeline_cpy_f32_f32; | |
| } | |
| if (from == GGML_TYPE_F32 && to == GGML_TYPE_F16) { | |
| return ctx->device->pipeline_cpy_f32_f16; | |
| } | |
| if (from == GGML_TYPE_F16 && to == GGML_TYPE_F16) { | |
| return ctx->device->pipeline_cpy_f16_f16; | |
| } | |
| std::cerr << "Missing CPY op for types: " << ggml_type_name(from) << " " << ggml_type_name(to) << std::endl; | |
| GGML_ASSERT(false); | |
| } | |
| static void ggml_vk_cpy_to_contiguous(ggml_backend_vk_context * ctx, vk_context * subctx, vk_pipeline pipeline, const ggml_tensor * tensor, vk_subbuffer&& in, vk_subbuffer&& out) { | |
| std::cerr << "ggml_vk_cpy_to_contiguous((" << tensor << ", type=" << tensor->type << ", backend=" << tensor->backend << ", ne0=" << tensor->ne[0] << ", ne1=" << tensor->ne[1] << ", ne2=" << tensor->ne[2] << ", ne3=" << tensor->ne[3] << ", nb0=" << tensor->nb[0] << ", nb1=" << tensor->nb[1] << ", nb2=" << tensor->nb[2] << ", nb3=" << tensor->nb[3] << "), "; | |
| std::cerr << "buffer in size=" << in.buffer->size << ", buffer out size=" << out.buffer->size << ")" << std::endl; | |
| const int tensor_type_size = ggml_type_size(tensor->type); | |
| const uint32_t ne = ggml_nelements(tensor); | |
| const vk_op_unary_push_constants pc = { | |
| (uint32_t)ne, | |
| (uint32_t)tensor->ne[0], (uint32_t)tensor->ne[1], (uint32_t)tensor->ne[2], (uint32_t)tensor->ne[3], (uint32_t)tensor->nb[0] / tensor_type_size, (uint32_t)tensor->nb[1] / tensor_type_size, (uint32_t)tensor->nb[2] / tensor_type_size, (uint32_t)tensor->nb[3] / tensor_type_size, | |
| (uint32_t)tensor->ne[0], (uint32_t)tensor->ne[1], (uint32_t)tensor->ne[2], (uint32_t)tensor->ne[3], 1 , (uint32_t)tensor->ne[0] , (uint32_t)(tensor->ne[0] * tensor->ne[1]) , (uint32_t)(tensor->ne[0] * tensor->ne[1] * tensor->ne[2]), | |
| 0, | |
| 0.0f, 0.0f, | |
| }; | |
| ggml_vk_sync_buffers(subctx); | |
| ggml_vk_dispatch_pipeline(ctx, subctx, pipeline, { in, out }, sizeof(vk_op_unary_push_constants), &pc, { ne, 1, 1 }); | |
| } | |
| static void ggml_vk_mul_mat_q_f16(ggml_backend_vk_context * ctx, vk_context * subctx, const ggml_tensor * src0, const ggml_tensor * src1, ggml_tensor * dst) { | |
| std::cerr << "ggml_vk_mul_mat_q_f16((" << src0 << ", name=" << src0->name << ", type=" << src0->type << ", backend=" << src0->backend << ", ne0=" << src0->ne[0] << ", ne1=" << src0->ne[1] << ", ne2=" << src0->ne[2] << ", ne3=" << src0->ne[3] << ", nb0=" << src0->nb[0] << ", nb1=" << src0->nb[1] << ", nb2=" << src0->nb[2] << ", nb3=" << src0->nb[3]; | |
| std::cerr << "), (" << src1 << ", name=" << src1->name << ", type=" << src1->type << ", backend=" << src1->backend << ", ne0=" << src1->ne[0] << ", ne1=" << src1->ne[1] << ", ne2=" << src1->ne[2] << ", ne3=" << src1->ne[3] << ", nb0=" << src1->nb[0] << ", nb1=" << src1->nb[1] << ", nb2=" << src1->nb[2] << ", nb3=" << src1->nb[3]; | |
| std::cerr << "), (" << dst << ", name=" << dst->name << ", type=" << dst->type << ", backend=" << dst->backend << ", ne0=" << dst->ne[0] << ", ne1=" << dst->ne[1] << ", ne2=" << dst->ne[2] << ", ne3=" << dst->ne[3] << ", nb0=" << dst->nb[0] << ", nb1=" << dst->nb[1] << ", nb2=" << dst->nb[2] << ", nb3=" << dst->nb[3] << "),)" << std::endl; | |
| GGML_ASSERT(ggml_vk_dim01_contiguous(src0) || src0->type == GGML_TYPE_F32 || src0->type == GGML_TYPE_F16); // NOLINT | |
| GGML_ASSERT(ggml_vk_dim01_contiguous(src1) || src1->type == GGML_TYPE_F32 || src1->type == GGML_TYPE_F16); // NOLINT | |
| const uint64_t ne00 = src0->ne[0]; | |
| const uint64_t ne01 = src0->ne[1]; | |
| const uint64_t ne02 = src0->ne[2]; | |
| const uint64_t ne03 = src0->ne[3]; | |
| const uint64_t ne10 = src1->ne[0]; | |
| const uint64_t ne11 = src1->ne[1]; | |
| const uint64_t ne12 = src1->ne[2]; | |
| const uint64_t ne13 = src1->ne[3]; | |
| const uint64_t ne20 = dst->ne[0]; | |
| const uint64_t ne21 = dst->ne[1]; | |
| const uint64_t r2 = ne12 / ne02; | |
| const uint64_t r3 = ne13 / ne03; | |
| ggml_tensor_extra_gpu * extra = (ggml_tensor_extra_gpu *) dst->extra; | |
| ggml_tensor_extra_gpu * extra_src0 = (ggml_tensor_extra_gpu *) src0->extra; | |
| ggml_tensor_extra_gpu * extra_src1 = (ggml_tensor_extra_gpu *) src1->extra; | |
| vk_buffer d_Qx; | |
| size_t qx_buf_offset = 0; | |
| vk_buffer d_Qy; | |
| size_t qy_buf_offset = 0; | |
| bool src0_uma = false; | |
| bool src1_uma = false; | |
| if (ctx->device->uma) { | |
| ggml_vk_host_get(ctx, src0->data, d_Qx, qx_buf_offset); | |
| ggml_vk_host_get(ctx, src1->data, d_Qy, qy_buf_offset); | |
| src0_uma = d_Qx != nullptr; | |
| src1_uma = d_Qy != nullptr; | |
| } | |
| const bool x_non_contig = !ggml_vk_dim01_contiguous(src0); | |
| const bool y_non_contig = !ggml_vk_dim01_contiguous(src1); | |
| const bool y_f32_kernel = src1->type == GGML_TYPE_F32 && !y_non_contig; | |
| vk_matmul_pipeline mmp = ggml_vk_get_mul_mat_mat_pipeline(ctx, src0->type, y_non_contig ? GGML_TYPE_F16 : src1->type); | |
| const bool qx_needs_dequant = mmp == nullptr || x_non_contig; | |
| const bool qy_needs_dequant = (src1->type != GGML_TYPE_F16 && !y_f32_kernel) || y_non_contig; | |
| if (mmp == nullptr) { | |
| // Fall back to dequant + f16 mulmat | |
| mmp = ggml_vk_get_mul_mat_mat_pipeline(ctx, GGML_TYPE_F16, y_f32_kernel ? GGML_TYPE_F32 : GGML_TYPE_F16); | |
| } | |
| // Not implemented | |
| GGML_ASSERT(y_non_contig || !qy_needs_dequant); // NOLINT | |
| const int x_ne = ne01 * ne00; | |
| const int y_ne = ne11 * ne10; | |
| const int d_ne = ne11 * ne01; | |
| const uint32_t kpad = ggml_vk_align_size(ne10, ggml_vk_guess_matmul_pipeline_align(ctx, mmp, ne01, ne11)); | |
| const bool aligned = ne10 == kpad && ne01 > 8 && ne11 > 8; | |
| const uint32_t split_k = ggml_vk_guess_split_k(ne01, ne11, ne10); | |
| vk_pipeline pipeline = ggml_vk_guess_matmul_pipeline(ctx, mmp, ne01, ne11, aligned); | |
| const uint64_t qx_sz = ggml_type_size(src0->type) * x_ne / ggml_blck_size(src0->type); | |
| const uint64_t qy_sz = ggml_type_size(src1->type) * y_ne / ggml_blck_size(src1->type); | |
| const uint64_t x_sz = !qx_needs_dequant ? qx_sz : sizeof(ggml_fp16_t) * x_ne; | |
| const uint64_t y_sz = y_f32_kernel ? sizeof(float) * y_ne : sizeof(ggml_fp16_t) * y_ne; | |
| const uint64_t d_sz = sizeof(float) * d_ne; | |
| vk_buffer d_D = extra->buffer_gpu.lock(); | |
| const uint64_t d_buf_offset = extra->offset; | |
| GGML_ASSERT(d_D != nullptr); | |
| GGML_ASSERT(d_D->size >= d_buf_offset + d_sz * ne02 * ne03); | |
| vk_buffer d_X; | |
| uint64_t x_buf_offset = 0; | |
| vk_buffer d_Y; | |
| uint64_t y_buf_offset = 0; | |
| if (!src0_uma) { | |
| d_Qx = extra_src0->buffer_gpu.lock(); | |
| qx_buf_offset = extra_src0->offset; | |
| GGML_ASSERT(d_Qx != nullptr); | |
| } | |
| if (!src1_uma) { | |
| d_Qy = extra_src1->buffer_gpu.lock(); | |
| qy_buf_offset = extra_src1->offset; | |
| GGML_ASSERT(d_Qy != nullptr); | |
| } | |
| if (qx_needs_dequant) { | |
| d_X = ctx->prealloc_x; | |
| GGML_ASSERT(d_X->size >= x_sz * ne02 * ne03); | |
| } else { | |
| d_X = d_Qx; | |
| x_buf_offset = qx_buf_offset; | |
| GGML_ASSERT(qx_sz == x_sz); | |
| } | |
| if (qy_needs_dequant) { | |
| d_Y = ctx->prealloc_y; | |
| GGML_ASSERT(d_Y->size >= y_sz * ne02 * ne03); | |
| } else { | |
| d_Y = d_Qy; | |
| y_buf_offset = qy_buf_offset; | |
| GGML_ASSERT(qy_sz == y_sz); | |
| } | |
| vk_pipeline to_fp16_vk_0 = nullptr; | |
| vk_pipeline to_fp16_vk_1 = nullptr; | |
| if (x_non_contig) { | |
| to_fp16_vk_0 = ggml_vk_get_cpy_pipeline(ctx, src0->type, GGML_TYPE_F16); | |
| } else { | |
| to_fp16_vk_0 = ggml_vk_get_to_fp16(ctx, src0->type); | |
| } | |
| if (y_non_contig) { | |
| to_fp16_vk_1 = ggml_vk_get_cpy_pipeline(ctx, src1->type, GGML_TYPE_F16); | |
| } else { | |
| to_fp16_vk_1 = ggml_vk_get_to_fp16(ctx, src1->type); | |
| } | |
| GGML_ASSERT(!qx_needs_dequant || to_fp16_vk_0 != nullptr); // NOLINT | |
| GGML_ASSERT(!qy_needs_dequant || to_fp16_vk_1 != nullptr); // NOLINT | |
| // Allocate descriptor sets | |
| ggml_pipeline_allocate_descriptor_sets(ctx, pipeline, 1); | |
| if (qx_needs_dequant) { | |
| ggml_pipeline_allocate_descriptor_sets(ctx, to_fp16_vk_0, 1); | |
| } | |
| if (qy_needs_dequant) { | |
| ggml_pipeline_allocate_descriptor_sets(ctx, to_fp16_vk_1, 1); | |
| } | |
| if (split_k > 1) { | |
| ggml_pipeline_allocate_descriptor_sets(ctx, ctx->device->pipeline_matmul_split_k_reduce, 1); | |
| } | |
| if (x_non_contig) { | |
| ggml_vk_cpy_to_contiguous(ctx, subctx, to_fp16_vk_0, src0, { d_Qx, qx_buf_offset, VK_WHOLE_SIZE }, { d_X, 0, VK_WHOLE_SIZE }); | |
| } else if (qx_needs_dequant) { | |
| const std::vector<uint32_t> pc = { (uint32_t)ne01, (uint32_t)ne10, (uint32_t)ne10, (uint32_t)ne10, (uint32_t)(ggml_nelements(src0)) }; | |
| ggml_vk_sync_buffers(subctx); | |
| ggml_vk_dispatch_pipeline(ctx, subctx, to_fp16_vk_0, { { d_Qx, qx_buf_offset, qx_sz * ne02 * ne03 }, { d_X, 0, x_sz * ne02 * ne03 } }, pc.size() * sizeof(uint32_t), pc.data(), { (uint32_t)(x_ne * ne02 * ne03), 1, 1}); | |
| } | |
| if (y_non_contig) { | |
| ggml_vk_cpy_to_contiguous(ctx, subctx, to_fp16_vk_1, src1, { d_Qy, qy_buf_offset, VK_WHOLE_SIZE }, { d_Y, 0, VK_WHOLE_SIZE }); | |
| } | |
| uint32_t stride_batch_x = ne00*ne01; | |
| uint32_t stride_batch_y = ne10*ne11; | |
| if (!ggml_vk_dim01_contiguous(src0) && !qx_needs_dequant) { | |
| stride_batch_x = src0->nb[0] / ggml_type_size(src0->type); | |
| } | |
| if (!ggml_vk_dim01_contiguous(src1) && !qy_needs_dequant) { | |
| stride_batch_y = src1->nb[0] / ggml_type_size(src1->type); | |
| } | |
| // compute | |
| ggml_vk_matmul( | |
| ctx, subctx, pipeline, | |
| { d_X, x_buf_offset, x_sz * ne02 * ne03 }, { d_Y, y_buf_offset, y_sz * ne12 * ne13 }, | |
| { d_D, d_buf_offset, d_sz * ne12 * ne13 }, { ctx->prealloc_split_k, 0, d_sz * ne12 * ne13 * split_k }, | |
| ne01, ne11, ne10, ne10, ne10, ne01, split_k, ne12*ne13, ne02, ne12, r2, r3, stride_batch_x, stride_batch_y, ne20*ne21, | |
| 0, 0, 0, 0, 1 | |
| ); // NOLINT | |
| if (dst->backend == GGML_BACKEND_TYPE_CPU) { | |
| // copy dst to host | |
| float * d = (float *) ((char *) dst->data); | |
| ggml_vk_buffer_read_async(ctx, subctx, d_D, 0, d, sizeof(float) * d_ne * ne12 * ne13); | |
| } | |
| } | |
| static void ggml_vk_mul_mat_vec_q_f16(ggml_backend_vk_context * ctx, vk_context * subctx, const ggml_tensor * src0, const ggml_tensor * src1, ggml_tensor * dst) { | |
| std::cerr << "ggml_vk_mul_mat_vec_q_f16((" << src0 << ", name=" << src0->name << ", type=" << src0->type << ", backend=" << src0->backend << ", ne0=" << src0->ne[0] << ", ne1=" << src0->ne[1] << ", ne2=" << src0->ne[2] << ", ne3=" << src0->ne[3] << ", nb0=" << src0->nb[0] << ", nb1=" << src0->nb[1] << ", nb2=" << src0->nb[2] << ", nb3=" << src0->nb[3]; | |
| std::cerr << "), (" << src1 << ", name=" << src1->name << ", type=" << src1->type << ", backend=" << src1->backend << ", ne0=" << src1->ne[0] << ", ne1=" << src1->ne[1] << ", ne2=" << src1->ne[2] << ", ne3=" << src1->ne[3] << ", nb0=" << src1->nb[0] << ", nb1=" << src1->nb[1] << ", nb2=" << src1->nb[2] << ", nb3=" << src1->nb[3]; | |
| std::cerr << "), (" << dst << ", name=" << dst->name << ", type=" << dst->type << ", backend=" << dst->backend << ", ne0=" << dst->ne[0] << ", ne1=" << dst->ne[1] << ", ne2=" << dst->ne[2] << ", ne3=" << dst->ne[3] << ", nb0=" << dst->nb[0] << ", nb1=" << dst->nb[1] << ", nb2=" << dst->nb[2] << ", nb3=" << dst->nb[3] << "),)" << std::endl; | |
| GGML_ASSERT(ggml_vk_dim01_contiguous(src0) || src0->type == GGML_TYPE_F32 || src0->type == GGML_TYPE_F16); // NOLINT | |
| GGML_ASSERT(ggml_vk_dim01_contiguous(src1) || src1->type == GGML_TYPE_F32 || src1->type == GGML_TYPE_F16); // NOLINT | |
| const uint64_t ne00 = src0->ne[0]; | |
| const uint64_t ne01 = src0->ne[1]; | |
| const uint64_t ne02 = src0->ne[2]; | |
| const uint64_t ne03 = src0->ne[3]; | |
| const uint64_t ne10 = src1->ne[0]; | |
| const uint64_t ne11 = src1->ne[1]; | |
| const uint64_t ne12 = src1->ne[2]; | |
| const uint64_t ne13 = src1->ne[3]; | |
| GGML_ASSERT(ne11 == 1); | |
| const uint64_t ne20 = dst->ne[0]; | |
| const uint64_t ne21 = dst->ne[1]; | |
| const uint64_t ne22 = dst->ne[2]; | |
| const uint64_t ne23 = dst->ne[3]; | |
| const uint64_t r2 = ne12 / ne02; | |
| const uint64_t r3 = ne13 / ne03; | |
| ggml_tensor_extra_gpu * extra = (ggml_tensor_extra_gpu *) dst->extra; | |
| ggml_tensor_extra_gpu * extra_src0 = (ggml_tensor_extra_gpu *) src0->extra; | |
| ggml_tensor_extra_gpu * extra_src1 = (ggml_tensor_extra_gpu *) src1->extra; | |
| vk_buffer d_Qx; | |
| size_t qx_buf_offset = 0; | |
| vk_buffer d_Qy; | |
| size_t qy_buf_offset = 0; | |
| bool src0_uma = false; | |
| bool src1_uma = false; | |
| if (ctx->device->uma) { | |
| ggml_vk_host_get(ctx, src0->data, d_Qx, qx_buf_offset); | |
| ggml_vk_host_get(ctx, src1->data, d_Qy, qy_buf_offset); | |
| src0_uma = d_Qx != nullptr; | |
| src1_uma = d_Qy != nullptr; | |
| } | |
| const bool x_non_contig = !ggml_vk_dim01_contiguous(src0); | |
| const bool y_non_contig = !ggml_vk_dim01_contiguous(src1); | |
| const bool f16_f32_kernel = src1->type == GGML_TYPE_F32; | |
| const bool qx_needs_dequant = x_non_contig; | |
| const bool qy_needs_dequant = (src1->type != GGML_TYPE_F16 && !f16_f32_kernel) || y_non_contig; | |
| // Not implemented | |
| GGML_ASSERT(y_non_contig || !qy_needs_dequant); // NOLINT | |
| const uint64_t x_ne = ne01 * ne00; | |
| const uint64_t y_ne = ne11 * ne10; | |
| const uint64_t d_ne = ne11 * ne01; | |
| const uint64_t qx_sz = ggml_vk_align_size(ggml_type_size(src0->type) * x_ne / ggml_blck_size(src0->type), ctx->device->properties.limits.minStorageBufferOffsetAlignment); | |
| const uint64_t qy_sz = ggml_type_size(src1->type) * y_ne / ggml_blck_size(src1->type); | |
| const uint64_t x_sz = x_non_contig ? ggml_vk_align_size(ggml_type_size(src0->type) * x_ne, ctx->device->properties.limits.minStorageBufferOffsetAlignment) : qx_sz; | |
| const uint64_t y_sz = f16_f32_kernel ? sizeof(float) * y_ne : sizeof(ggml_fp16_t) * y_ne; | |
| const uint64_t d_sz = sizeof(float) * d_ne; | |
| vk_buffer d_D = extra->buffer_gpu.lock(); | |
| const uint64_t d_buf_offset = extra->offset; | |
| GGML_ASSERT(d_D != nullptr); | |
| vk_buffer d_X; | |
| uint64_t x_buf_offset = 0; | |
| vk_buffer d_Y; | |
| uint64_t y_buf_offset = 0; | |
| if(!src0_uma) { | |
| d_Qx = extra_src0->buffer_gpu.lock(); | |
| qx_buf_offset = extra_src0->offset; | |
| GGML_ASSERT(d_Qx != nullptr); | |
| } | |
| if(!src1_uma) { | |
| d_Qy = extra_src1->buffer_gpu.lock(); | |
| qy_buf_offset = extra_src1->offset; | |
| GGML_ASSERT(d_Qy != nullptr); | |
| } | |
| if (qx_needs_dequant) { | |
| d_X = ctx->prealloc_x; | |
| } else { | |
| d_X = d_Qx; | |
| x_buf_offset = qx_buf_offset; | |
| GGML_ASSERT(qx_sz == x_sz); | |
| } | |
| if (qy_needs_dequant) { | |
| d_Y = ctx->prealloc_y; | |
| } else { | |
| d_Y = d_Qy; | |
| y_buf_offset = qy_buf_offset; | |
| GGML_ASSERT(qy_sz == y_sz); | |
| } | |
| vk_pipeline to_fp16_vk_0 = nullptr; | |
| vk_pipeline to_fp16_vk_1 = nullptr; | |
| if (x_non_contig) { | |
| to_fp16_vk_0 = ggml_vk_get_cpy_pipeline(ctx, src0->type, src0->type); | |
| } | |
| if (y_non_contig) { | |
| to_fp16_vk_1 = ggml_vk_get_cpy_pipeline(ctx, src1->type, src1->type); | |
| } else { | |
| to_fp16_vk_1 = ggml_vk_get_to_fp16(ctx, src1->type); | |
| } | |
| vk_pipeline dmmv = ggml_vk_get_dequantize_mul_mat_vec(ctx, src0->type, src1->type); | |
| GGML_ASSERT(!qx_needs_dequant || to_fp16_vk_0 != nullptr); // NOLINT | |
| GGML_ASSERT(!qy_needs_dequant || to_fp16_vk_1 != nullptr); // NOLINT | |
| GGML_ASSERT(dmmv != nullptr); | |
| // Allocate descriptor sets | |
| if (qx_needs_dequant) { | |
| ggml_pipeline_allocate_descriptor_sets(ctx, to_fp16_vk_0, 1); | |
| } | |
| if (qy_needs_dequant) { | |
| ggml_pipeline_allocate_descriptor_sets(ctx, to_fp16_vk_1, y_non_contig ? 1 : ne12 * ne13); | |
| } | |
| ggml_pipeline_allocate_descriptor_sets(ctx, dmmv, ne12 * ne13); | |
| if (x_non_contig) { | |
| GGML_ASSERT(x_sz == ggml_vk_align_size(ggml_type_size(src0->type) * x_ne, ctx->device->properties.limits.minStorageBufferOffsetAlignment)); | |
| ggml_vk_cpy_to_contiguous(ctx, subctx, to_fp16_vk_0, src0, { d_Qx, qx_buf_offset, VK_WHOLE_SIZE }, { d_X, 0, VK_WHOLE_SIZE }); | |
| } | |
| if (y_non_contig) { | |
| GGML_ASSERT(y_sz == ggml_type_size(src1->type) * y_ne); | |
| ggml_vk_cpy_to_contiguous(ctx, subctx, to_fp16_vk_1, src1, { d_Qy, qy_buf_offset, VK_WHOLE_SIZE }, { d_Y, 0, VK_WHOLE_SIZE }); | |
| } | |
| uint32_t stride_batch_x = ne00*ne01; | |
| uint32_t stride_batch_y = ne10*ne11; | |
| if (!ggml_vk_dim01_contiguous(src0) && !qx_needs_dequant) { | |
| stride_batch_x = src0->nb[0] / ggml_type_size(src0->type); | |
| } | |
| if (!ggml_vk_dim01_contiguous(src1) && !qy_needs_dequant) { | |
| stride_batch_y = src1->nb[0] / ggml_type_size(src1->type); | |
| } | |
| // compute | |
| const vk_mat_vec_push_constants pc = { | |
| (uint32_t)ne00, (uint32_t)ne10, (uint32_t)ne10, (uint32_t)ne01, | |
| (uint32_t)ne02, (uint32_t)ne12, (uint32_t)r2, (uint32_t)r3, | |
| stride_batch_x, stride_batch_y, (uint32_t)(ne20*ne21), | |
| }; | |
| ggml_vk_sync_buffers(subctx); | |
| ggml_vk_dispatch_pipeline(ctx, subctx, dmmv, { { d_X, x_buf_offset, x_sz * ne02 * ne03 }, { d_Y, y_buf_offset, y_sz * ne12 * ne13 }, { d_D, d_buf_offset, d_sz * ne22 * ne23} }, sizeof(vk_mat_vec_push_constants), &pc, { (uint32_t)ne01, (uint32_t)(ne12 * ne13), 1}); | |
| } | |
| static void ggml_vk_mul_mat_vec_p021_f16_f32(ggml_backend_vk_context * ctx, vk_context * subctx, const ggml_tensor * src0, const ggml_tensor * src1, ggml_tensor * dst) { | |
| std::cerr << "ggml_vk_mul_mat_p021_f16_f32((" << src0 << ", name=" << src0->name << ", type=" << src0->type << ", backend=" << src0->backend << ", ne0=" << src0->ne[0] << ", ne1=" << src0->ne[1] << ", ne2=" << src0->ne[2] << ", ne3=" << src0->ne[3] << ", nb0=" << src0->nb[0] << ", nb1=" << src0->nb[1] << ", nb2=" << src0->nb[2] << ", nb3=" << src0->nb[3]; | |
| std::cerr << "), (" << src1 << ", name=" << src1->name << ", type=" << src1->type << ", backend=" << src1->backend << ", ne0=" << src1->ne[0] << ", ne1=" << src1->ne[1] << ", ne2=" << src1->ne[2] << ", ne3=" << src1->ne[3] << ", nb0=" << src1->nb[0] << ", nb1=" << src1->nb[1] << ", nb2=" << src1->nb[2] << ", nb3=" << src1->nb[3]; | |
| std::cerr << "), (" << dst << ", name=" << dst->name << ", type=" << dst->type << ", backend=" << dst->backend << ", ne0=" << dst->ne[0] << ", ne1=" << dst->ne[1] << ", ne2=" << dst->ne[2] << ", ne3=" << dst->ne[3] << ", nb0=" << dst->nb[0] << ", nb1=" << dst->nb[1] << ", nb2=" << dst->nb[2] << ", nb3=" << dst->nb[3] << "),)" << std::endl; | |
| GGML_ASSERT(ggml_is_permuted(src0) && ggml_is_permuted(src1)); | |
| GGML_ASSERT(src0->backend == GGML_BACKEND_TYPE_GPU); | |
| GGML_ASSERT(src0->nb[0] <= src0->nb[1] && src0->nb[2] <= src0->nb[3]); // NOLINT | |
| GGML_ASSERT(src1->nb[0] <= src1->nb[1] && src1->nb[2] <= src1->nb[3]); // NOLINT | |
| GGML_ASSERT(src0->type == GGML_TYPE_F16); | |
| GGML_ASSERT(src1->type == GGML_TYPE_F32); | |
| const uint64_t ne00 = src0->ne[0]; | |
| const uint64_t ne01 = src0->ne[1]; | |
| const uint64_t ne02 = src0->ne[2]; | |
| // const uint64_t ne03 = src0->ne[3]; | |
| const uint64_t ne10 = src1->ne[0]; | |
| const uint64_t ne11 = src1->ne[1]; | |
| const uint64_t ne12 = src1->ne[2]; | |
| // const uint64_t ne13 = src1->ne[3]; | |
| GGML_ASSERT(ne11 == 1); | |
| ggml_tensor_extra_gpu * extra = (ggml_tensor_extra_gpu *) dst->extra; | |
| ggml_tensor_extra_gpu * extra_src0 = (ggml_tensor_extra_gpu *) src0->extra; | |
| ggml_tensor_extra_gpu * extra_src1 = (ggml_tensor_extra_gpu *) src1->extra; | |
| vk_buffer d_Qy; | |
| size_t qy_buf_offset = 0; | |
| bool src1_uma = false; | |
| if (ctx->device->uma) { | |
| ggml_vk_host_get(ctx, src1->data, d_Qy, qy_buf_offset); | |
| src1_uma = d_Qy != nullptr; | |
| } | |
| const uint64_t x_ne = ne00 * ne01 * ne02; | |
| const uint64_t y_ne = ne10 * ne11 * ne12; | |
| const uint64_t d_ne = ne01 * ne11 * ne12; | |
| const uint64_t qx_sz = ggml_vk_align_size(ggml_type_size(src0->type) * x_ne / ggml_blck_size(src0->type), ctx->device->properties.limits.minStorageBufferOffsetAlignment); | |
| const uint64_t qy_sz = ggml_type_size(src1->type) * y_ne / ggml_blck_size(src1->type); | |
| const uint64_t d_sz = sizeof(float) * d_ne; | |
| vk_buffer d_D = extra->buffer_gpu.lock(); | |
| const uint64_t d_buf_offset = extra->offset; | |
| GGML_ASSERT(d_D != nullptr); | |
| vk_buffer d_Qx = extra_src0->buffer_gpu.lock(); | |
| const uint64_t qx_buf_offset = extra_src0->offset; | |
| GGML_ASSERT(d_Qx != nullptr); | |
| if (!src1_uma) { | |
| d_Qy = extra_src1->buffer_gpu.lock(); | |
| qy_buf_offset = extra_src1->offset; | |
| GGML_ASSERT(d_Qx != nullptr); | |
| } | |
| // Allocate descriptor sets | |
| ggml_pipeline_allocate_descriptor_sets(ctx, ctx->device->pipeline_mul_mat_vec_p021_f16_f32, 1); | |
| const uint64_t qy_buffer_offset = (qy_buf_offset / ctx->device->properties.limits.minStorageBufferOffsetAlignment) * ctx->device->properties.limits.minStorageBufferOffsetAlignment; | |
| const uint64_t qy_shader_offset = qy_buf_offset - qy_buffer_offset; | |
| const uint64_t d_buffer_offset = (d_buf_offset / ctx->device->properties.limits.minStorageBufferOffsetAlignment) * ctx->device->properties.limits.minStorageBufferOffsetAlignment; | |
| const uint64_t d_shader_offset = d_buf_offset - d_buffer_offset; | |
| // compute | |
| const std::array<uint32_t, 6> pc = { (uint32_t)ne00, (uint32_t)ne01, (uint32_t)ne02, (uint32_t)ne12, (uint32_t)(qy_shader_offset / ggml_type_size(src1->type)), (uint32_t)(d_shader_offset / ggml_type_size(dst->type)) }; | |
| ggml_vk_sync_buffers(subctx); | |
| ggml_vk_dispatch_pipeline(ctx, subctx, ctx->device->pipeline_mul_mat_vec_p021_f16_f32, { { d_Qx, qx_buf_offset, qx_sz }, { d_Qy, qy_buffer_offset, qy_sz + qy_shader_offset }, { d_D, d_buffer_offset, d_sz + d_shader_offset } }, 6 * sizeof(uint32_t), &pc, { 1, (uint32_t)ne01, (uint32_t)ne12 }); | |
| if (dst->backend == GGML_BACKEND_TYPE_CPU) { | |
| // copy dst to host | |
| float * d = (float *) dst->data; | |
| ggml_vk_sync_buffers(subctx); | |
| ggml_vk_buffer_read_async(ctx, subctx, d_D, d_buf_offset, d, sizeof(float) * d_ne); | |
| } | |
| } | |
| static void ggml_vk_mul_mat_vec_nc_f16_f32(ggml_backend_vk_context * ctx, vk_context * subctx, const ggml_tensor * src0, const ggml_tensor * src1, ggml_tensor * dst) { | |
| std::cerr << "ggml_vk_mul_mat_nc_f16_f32((" << src0 << ", name=" << src0->name << ", type=" << src0->type << ", backend=" << src0->backend << ", ne0=" << src0->ne[0] << ", ne1=" << src0->ne[1] << ", ne2=" << src0->ne[2] << ", ne3=" << src0->ne[3] << ", nb0=" << src0->nb[0] << ", nb1=" << src0->nb[1] << ", nb2=" << src0->nb[2] << ", nb3=" << src0->nb[3]; | |
| std::cerr << "), (" << src1 << ", name=" << src1->name << ", type=" << src1->type << ", backend=" << src1->backend << ", ne0=" << src1->ne[0] << ", ne1=" << src1->ne[1] << ", ne2=" << src1->ne[2] << ", ne3=" << src1->ne[3] << ", nb0=" << src1->nb[0] << ", nb1=" << src1->nb[1] << ", nb2=" << src1->nb[2] << ", nb3=" << src1->nb[3]; | |
| std::cerr << "), (" << dst << ", name=" << dst->name << ", type=" << dst->type << ", backend=" << dst->backend << ", ne0=" << dst->ne[0] << ", ne1=" << dst->ne[1] << ", ne2=" << dst->ne[2] << ", ne3=" << dst->ne[3] << ", nb0=" << dst->nb[0] << ", nb1=" << dst->nb[1] << ", nb2=" << dst->nb[2] << ", nb3=" << dst->nb[3] << "),)" << std::endl; | |
| GGML_ASSERT(!ggml_is_transposed(src0)); | |
| GGML_ASSERT(!ggml_is_transposed(src1)); | |
| GGML_ASSERT(!ggml_is_permuted(src0)); | |
| GGML_ASSERT(src0->backend == GGML_BACKEND_TYPE_GPU); | |
| GGML_ASSERT(src0->type == GGML_TYPE_F16); | |
| GGML_ASSERT(src1->type == GGML_TYPE_F32); | |
| const uint64_t ne00 = src0->ne[0]; | |
| const uint64_t ne01 = src0->ne[1]; | |
| const uint64_t ne02 = src0->ne[2]; | |
| // const uint64_t ne03 = src0->ne[3]; | |
| const uint64_t nb01 = src0->nb[1]; | |
| const uint64_t nb02 = src0->nb[2]; | |
| // const uint64_t ne10 = src1->ne[0]; | |
| const uint64_t ne11 = src1->ne[1]; | |
| const uint64_t ne12 = src1->ne[2]; | |
| // const uint64_t ne13 = src1->ne[3]; | |
| GGML_ASSERT(ne11 == 1); | |
| ggml_tensor_extra_gpu * extra = (ggml_tensor_extra_gpu *) dst->extra; | |
| ggml_tensor_extra_gpu * extra_src0 = (ggml_tensor_extra_gpu *) src0->extra; | |
| ggml_tensor_extra_gpu * extra_src1 = (ggml_tensor_extra_gpu *) src1->extra; | |
| vk_buffer d_Qy = nullptr; | |
| size_t qy_buf_offset = 0; | |
| bool src1_uma = false; | |
| if (ctx->device->uma) { | |
| ggml_vk_host_get(ctx, src1->data, d_Qy, qy_buf_offset); | |
| src1_uma = d_Qy != nullptr; | |
| } | |
| const uint64_t d_ne = ne01 * ne11 * ne12; | |
| const uint32_t row_stride_x = nb01 / sizeof(ggml_fp16_t); | |
| const uint32_t channel_stride_x = nb02 / sizeof(ggml_fp16_t); | |
| const uint64_t qx_sz = ggml_nbytes(src0); | |
| const uint64_t qy_sz = ggml_nbytes(src1); | |
| const uint64_t d_sz = sizeof(float) * d_ne; | |
| vk_buffer d_D = extra->buffer_gpu.lock(); | |
| const uint64_t d_buf_offset = extra->offset; | |
| GGML_ASSERT(d_D != nullptr); | |
| vk_buffer d_Qx = extra_src0->buffer_gpu.lock(); | |
| const uint64_t qx_buf_offset = extra_src0->offset; | |
| GGML_ASSERT(d_Qx != nullptr); | |
| if (!src1_uma) { | |
| d_Qy = extra_src1->buffer_gpu.lock(); | |
| qy_buf_offset = extra_src1->offset; | |
| GGML_ASSERT(d_Qx != nullptr); | |
| } | |
| // Allocate descriptor sets | |
| ggml_pipeline_allocate_descriptor_sets(ctx, ctx->device->pipeline_mul_mat_vec_nc_f16_f32, 1); | |
| const uint64_t qy_buffer_offset = (qy_buf_offset / ctx->device->properties.limits.minStorageBufferOffsetAlignment) * ctx->device->properties.limits.minStorageBufferOffsetAlignment; | |
| const uint64_t qy_shader_offset = qy_buf_offset - qy_buffer_offset; | |
| const uint64_t d_buffer_offset = (d_buf_offset / ctx->device->properties.limits.minStorageBufferOffsetAlignment) * ctx->device->properties.limits.minStorageBufferOffsetAlignment; | |
| const uint64_t d_shader_offset = d_buf_offset - d_buffer_offset; | |
| // compute | |
| const std::array<uint32_t, 7> pc = { (uint32_t)ne00, (uint32_t)ne01, row_stride_x, channel_stride_x, (uint32_t)(ne12 / ne02), (uint32_t)(qy_shader_offset / ggml_type_size(src1->type)), (uint32_t)(d_shader_offset / ggml_type_size(dst->type)) }; | |
| ggml_vk_sync_buffers(subctx); | |
| ggml_vk_dispatch_pipeline(ctx, subctx, ctx->device->pipeline_mul_mat_vec_nc_f16_f32, { { d_Qx, qx_buf_offset, qx_sz }, { d_Qy, qy_buffer_offset, qy_sz + qy_shader_offset }, { d_D, d_buffer_offset, d_sz + d_shader_offset } }, 7 * sizeof(uint32_t), &pc, { 1, (uint32_t)ne01, (uint32_t)ne12 }); | |
| if (dst->backend == GGML_BACKEND_TYPE_CPU) { | |
| // copy dst to host | |
| float * d = (float *) dst->data; | |
| ggml_vk_sync_buffers(subctx); | |
| ggml_vk_buffer_read_async(ctx, subctx, d_D, d_buf_offset, d, sizeof(float) * d_ne); | |
| } | |
| } | |
| static bool ggml_vk_can_mul_mat(const ggml_tensor * src0, const ggml_tensor * src1, const ggml_tensor * dst) { | |
| const uint64_t ne10 = src1->ne[0]; | |
| const uint64_t ne0 = dst->ne[0]; | |
| const uint64_t ne1 = dst->ne[1]; | |
| // TODO: find the optimal values for these | |
| return (src0->type == GGML_TYPE_F32 || src0->type == GGML_TYPE_F16 || ggml_is_quantized(src0->type)) && | |
| (src1->type == GGML_TYPE_F32 || src1->type == GGML_TYPE_F16 || ggml_is_quantized(src1->type)) && | |
| dst->type == GGML_TYPE_F32 && | |
| ((ne0 >= 32 && ne1 >= 32 && ne10 >= 32) || src0->backend == GGML_BACKEND_TYPE_GPU); | |
| } | |
| static void ggml_vk_mul_mat(ggml_backend_vk_context * ctx, vk_context * subctx, const ggml_tensor * src0, const ggml_tensor * src1, ggml_tensor * dst) { | |
| std::cerr << "ggml_vk_mul_mat(" << src0 << ", " << src1 << ", " << dst << ")" << std::endl; | |
| if (src0->type == GGML_TYPE_F16 && ggml_is_permuted(src0) && ggml_is_permuted(src1) && src1->ne[1] == 1) { | |
| ggml_vk_mul_mat_vec_p021_f16_f32(ctx, subctx, src0, src1, dst); | |
| } else if (src0->type == GGML_TYPE_F16 && !ggml_is_contiguous(src0) && !ggml_is_transposed(src1) && src1->ne[1] == 1) { | |
| ggml_vk_mul_mat_vec_nc_f16_f32(ctx, subctx, src0, src1, dst); | |
| } else if (src1->ne[1] == 1 && (src0->type == GGML_TYPE_F16 || ggml_is_quantized(src0->type))) { | |
| ggml_vk_mul_mat_vec_q_f16(ctx, subctx, src0, src1, dst); | |
| } else { | |
| ggml_vk_mul_mat_q_f16(ctx, subctx, src0, src1, dst); | |
| } | |
| } | |
| /*static void ggml_vk_mul_mat_id_q_f16(ggml_backend_vk_context * ctx, vk_context * subctx, const ggml_tensor * src0, const ggml_tensor * src1, const ggml_tensor * ids, ggml_tensor * dst) { | |
| #ifdef GGML_VULKAN_DEBUG | |
| std::cerr << "ggml_vk_mul_mat_id_q_f16((" << src0 << ", name=" << src0->name << ", type=" << src0->type << ", backend=" << src0->backend << ", ne0=" << src0->ne[0] << ", ne1=" << src0->ne[1] << ", ne2=" << src0->ne[2] << ", ne3=" << src0->ne[3] << ", nb0=" << src0->nb[0] << ", nb1=" << src0->nb[1] << ", nb2=" << src0->nb[2] << ", nb3=" << src0->nb[3]; | |
| std::cerr << "), (" << src1 << ", name=" << src1->name << ", type=" << src1->type << ", backend=" << src1->backend << ", ne0=" << src1->ne[0] << ", ne1=" << src1->ne[1] << ", ne2=" << src1->ne[2] << ", ne3=" << src1->ne[3] << ", nb0=" << src1->nb[0] << ", nb1=" << src1->nb[1] << ", nb2=" << src1->nb[2] << ", nb3=" << src1->nb[3]; | |
| std::cerr << "), (" << ids << ", name=" << ids->name << ", type=" << ids->type << ", backend=" << ids->backend << ", ne0=" << ids->ne[0] << ", ne1=" << ids->ne[1] << ", ne2=" << ids->ne[2] << ", ne3=" << ids->ne[3] << ", nb0=" << ids->nb[0] << ", nb1=" << ids->nb[1] << ", nb2=" << ids->nb[2] << ", nb3=" << ids->nb[3]; | |
| std::cerr << "), (" << dst << ", name=" << dst->name << ", type=" << dst->type << ", backend=" << dst->backend << ", ne0=" << dst->ne[0] << ", ne1=" << dst->ne[1] << ", ne2=" << dst->ne[2] << ", ne3=" << dst->ne[3] << ", nb0=" << dst->nb[0] << ", nb1=" << dst->nb[1] << ", nb2=" << dst->nb[2] << ", nb3=" << dst->nb[3] << "),)" << std::endl; | |
| #endif | |
| GGML_ASSERT(src0->type == GGML_TYPE_I32); | |
| GGML_ASSERT(ggml_vk_dim01_contiguous(src1) || src1->type == GGML_TYPE_F32 || src1->type == GGML_TYPE_F16); // NOLINT | |
| const uint64_t ne00 = src0->ne[0]; | |
| const uint64_t ne01 = src0->ne[1]; | |
| const uint64_t ne02 = src0->ne[2]; | |
| const uint64_t ne03 = src0->ne[3]; | |
| const uint64_t ne10 = src1->ne[0]; | |
| const uint64_t ne11 = src1->ne[1]; | |
| const uint64_t ne12 = src1->ne[2]; | |
| const uint64_t ne13 = src1->ne[3]; | |
| const uint32_t nb11 = src1->nb[1]; | |
| const uint64_t ne20 = dst->ne[0]; | |
| const uint64_t ne21 = dst->ne[1]; | |
| const uint64_t r2 = ne12 / ne02; | |
| const uint64_t r3 = ne13 / ne03; | |
| const uint32_t nbi1 = src0->nb[1]; | |
| const uint32_t idx = ((uint32_t *) dst->op_params)[0]; | |
| const uint64_t n_as = ne02; | |
| GGML_ASSERT(n_as <= 8); | |
| ggml_tensor_extra_gpu * extra = (ggml_tensor_extra_gpu *) dst->extra; | |
| ggml_tensor_extra_gpu * extra_src0 = (ggml_tensor_extra_gpu *) src0->extra; | |
| ggml_tensor_extra_gpu * extra_src1 = (ggml_tensor_extra_gpu *) src1->extra; | |
| ggml_tensor_extra_gpu * extra_ids = (ggml_tensor_extra_gpu *) ids->extra; | |
| vk_buffer d_Qx; | |
| size_t qx_buf_offset = 0; | |
| vk_buffer d_Qy; | |
| size_t qy_buf_offset = 0; | |
| bool src0_uma = false; | |
| bool src1_uma = false; | |
| if (ctx->device->uma) { | |
| ggml_vk_host_get(ctx, src0->data, d_Qx, qx_buf_offset); | |
| ggml_vk_host_get(ctx, src1->data, d_Qy, qy_buf_offset); | |
| src0_uma = d_Qx != nullptr; | |
| src1_uma = d_Qy != nullptr; | |
| } | |
| const bool x_non_contig = !ggml_vk_dim01_contiguous(src0); | |
| const bool y_non_contig = !ggml_vk_dim01_contiguous(src1); | |
| const bool y_f32_kernel = src1->type == GGML_TYPE_F32 && !y_non_contig; | |
| vk_matmul_pipeline mmp = ggml_vk_get_mul_mat_mat_id_pipeline(ctx, src0->type, y_non_contig ? GGML_TYPE_F16 : src1->type); | |
| const bool qx_needs_dequant = mmp == nullptr || x_non_contig; | |
| const bool qy_needs_dequant = (src1->type != GGML_TYPE_F16 && !y_f32_kernel) || y_non_contig; | |
| if (mmp == nullptr) { | |
| GGML_ASSERT(false); | |
| } | |
| // Not implemented | |
| GGML_ASSERT(y_non_contig || !qy_needs_dequant); // NOLINT | |
| const int x_ne = ne01 * ne00; | |
| const int y_ne = ne11 * ne10; | |
| const int d_ne = ne11 * ne01; | |
| const uint32_t kpad = ggml_vk_align_size(ne10, ggml_vk_guess_matmul_pipeline_align(ctx, mmp, ne01, ne11)); | |
| const bool aligned = ne10 == kpad && ne01 > 8 && ne11 > 8; | |
| const uint32_t split_k = ggml_vk_guess_split_k(ne01, ne11, ne10); | |
| vk_pipeline pipeline = ggml_vk_guess_matmul_pipeline(ctx, mmp, ne01, ne11, aligned); | |
| const uint64_t qx_sz = ggml_type_size(src0->type) * x_ne / ggml_blck_size(src0->type); | |
| const uint64_t qy_sz = ggml_type_size(src1->type) * y_ne / ggml_blck_size(src1->type); | |
| const uint64_t x_sz = !qx_needs_dequant ? qx_sz : sizeof(ggml_fp16_t) * x_ne; | |
| const uint64_t y_sz = y_f32_kernel ? sizeof(float) * y_ne : sizeof(ggml_fp16_t) * y_ne; | |
| const uint64_t d_sz = sizeof(float) * d_ne; | |
| vk_buffer d_D = extra->buffer_gpu.lock(); | |
| const uint64_t d_buf_offset = extra->offset; | |
| GGML_ASSERT(d_D != nullptr); | |
| GGML_ASSERT(d_D->size >= d_buf_offset + d_sz * ne02 * ne03); | |
| vk_buffer d_X; | |
| uint64_t x_buf_offset = 0; | |
| vk_buffer d_Y; | |
| uint64_t y_buf_offset = 0; | |
| if (!src0_uma) { | |
| d_Qx = extra_src0->buffer_gpu.lock(); | |
| qx_buf_offset = extra_src0->offset; | |
| GGML_ASSERT(d_Qx != nullptr); | |
| } | |
| if (!src1_uma) { | |
| d_Qy = extra_src1->buffer_gpu.lock(); | |
| qy_buf_offset = extra_src1->offset; | |
| GGML_ASSERT(d_Qy != nullptr); | |
| } | |
| if (qx_needs_dequant) { | |
| d_X = ctx->prealloc_x; | |
| GGML_ASSERT(d_X->size >= x_sz * ne02 * ne03); | |
| } else { | |
| d_X = d_Qx; | |
| x_buf_offset = qx_buf_offset; | |
| GGML_ASSERT(qx_sz == x_sz); | |
| } | |
| if (qy_needs_dequant) { | |
| d_Y = ctx->prealloc_y; | |
| GGML_ASSERT(d_Y->size >= y_sz * ne02 * ne03); | |
| } else { | |
| d_Y = d_Qy; | |
| y_buf_offset = qy_buf_offset; | |
| GGML_ASSERT(qy_sz == y_sz); | |
| } | |
| vk_pipeline to_fp16_vk_0 = nullptr; | |
| vk_pipeline to_fp16_vk_1 = nullptr; | |
| if (x_non_contig) { | |
| to_fp16_vk_0 = ggml_vk_get_cpy_pipeline(ctx, src0->type, GGML_TYPE_F16); | |
| } else { | |
| to_fp16_vk_0 = ggml_vk_get_to_fp16(ctx, src0->type); | |
| } | |
| if (y_non_contig) { | |
| to_fp16_vk_1 = ggml_vk_get_cpy_pipeline(ctx, src1->type, GGML_TYPE_F16); | |
| } else { | |
| to_fp16_vk_1 = ggml_vk_get_to_fp16(ctx, src1->type); | |
| } | |
| GGML_ASSERT(!qx_needs_dequant || to_fp16_vk_0 != nullptr); // NOLINT | |
| GGML_ASSERT(!qy_needs_dequant || to_fp16_vk_1 != nullptr); // NOLINT | |
| // Allocate descriptor sets | |
| ggml_pipeline_allocate_descriptor_sets(ctx, pipeline, 1); | |
| if (qx_needs_dequant) { | |
| ggml_pipeline_allocate_descriptor_sets(ctx, to_fp16_vk_0, 1); | |
| } | |
| if (qy_needs_dequant) { | |
| ggml_pipeline_allocate_descriptor_sets(ctx, to_fp16_vk_1, 1); | |
| } | |
| if (split_k > 1) { | |
| ggml_pipeline_allocate_descriptor_sets(ctx, ctx->device->pipeline_matmul_split_k_reduce, 1); | |
| } | |
| if (x_non_contig) { | |
| ggml_vk_cpy_to_contiguous(ctx, subctx, to_fp16_vk_0, src0, { d_Qx, qx_buf_offset, VK_WHOLE_SIZE }, { d_X, 0, VK_WHOLE_SIZE }); | |
| } else if (qx_needs_dequant) { | |
| const std::vector<uint32_t> pc = { (uint32_t)ne01, (uint32_t)ne10, (uint32_t)ne10, (uint32_t)ne10, (uint32_t)(ggml_nelements(src0)) }; | |
| ggml_vk_sync_buffers(subctx); | |
| ggml_vk_dispatch_pipeline(ctx, subctx, to_fp16_vk_0, { { d_Qx, qx_buf_offset, qx_sz * ne02 * ne03 }, { d_X, 0, x_sz * ne02 * ne03 } }, pc.size() * sizeof(uint32_t), pc.data(), { (uint32_t)(x_ne * ne02 * ne03), 1, 1}); | |
| } | |
| if (y_non_contig) { | |
| ggml_vk_cpy_to_contiguous(ctx, subctx, to_fp16_vk_1, src1, { d_Qy, qy_buf_offset, VK_WHOLE_SIZE }, { d_Y, 0, VK_WHOLE_SIZE }); | |
| } | |
| uint32_t stride_batch_x = ne00*ne01; | |
| uint32_t stride_batch_y = ne10*ne11; | |
| if (!ggml_vk_dim01_contiguous(src0) && !qx_needs_dequant) { | |
| stride_batch_x = src0->nb[0] / ggml_type_size(src0->type); | |
| } | |
| if (!ggml_vk_dim01_contiguous(src1) && !qy_needs_dequant) { | |
| stride_batch_y = src1->nb[0] / ggml_type_size(src1->type); | |
| } | |
| // compute | |
| ggml_vk_matmul( | |
| ctx, subctx, pipeline, | |
| { d_X, x_buf_offset, x_sz * ne02 * ne03 }, { d_Y, y_buf_offset, y_sz * ne12 * ne13 }, | |
| { d_D, d_buf_offset, d_sz * ne12 * ne13 }, { ctx->prealloc_split_k, 0, d_sz * ne12 * ne13 * split_k }, | |
| ne01, ne11, ne10, ne10, ne10, ne01, split_k, ne12*ne13, ne02, ne12, r2, r3, stride_batch_x, stride_batch_y, ne20*ne21, | |
| nb11 / ggml_type_size(src1->type), ne20, idx, nbi1, n_as | |
| ); // NOLINT | |
| } | |
| static void ggml_vk_mul_mat_vec_id_q_f16(ggml_backend_vk_context * ctx, vk_context * subctx, const ggml_tensor * src0, const ggml_tensor * src1, ggml_tensor * dst) { | |
| #ifdef GGML_VULKAN_DEBUG | |
| std::cerr << "ggml_vk_mul_mat_vec_id_q_f16((" << src0 << ", name=" << src0->name << ", type=" << src0->type << ", backend=" << src0->backend << ", ne0=" << src0->ne[0] << ", ne1=" << src0->ne[1] << ", ne2=" << src0->ne[2] << ", ne3=" << src0->ne[3] << ", nb0=" << src0->nb[0] << ", nb1=" << src0->nb[1] << ", nb2=" << src0->nb[2] << ", nb3=" << src0->nb[3]; | |
| std::cerr << "), (" << src1 << ", name=" << src1->name << ", type=" << src1->type << ", backend=" << src1->backend << ", ne0=" << src1->ne[0] << ", ne1=" << src1->ne[1] << ", ne2=" << src1->ne[2] << ", ne3=" << src1->ne[3] << ", nb0=" << src1->nb[0] << ", nb1=" << src1->nb[1] << ", nb2=" << src1->nb[2] << ", nb3=" << src1->nb[3]; | |
| std::cerr << "), (" << dst << ", name=" << dst->name << ", type=" << dst->type << ", backend=" << dst->backend << ", ne0=" << dst->ne[0] << ", ne1=" << dst->ne[1] << ", ne2=" << dst->ne[2] << ", ne3=" << dst->ne[3] << ", nb0=" << dst->nb[0] << ", nb1=" << dst->nb[1] << ", nb2=" << dst->nb[2] << ", nb3=" << dst->nb[3] << "),)" << std::endl; | |
| #endif | |
| GGML_ASSERT(ggml_vk_dim01_contiguous(src0) || src0->type == GGML_TYPE_F32 || src0->type == GGML_TYPE_F16); // NOLINT | |
| GGML_ASSERT(ggml_vk_dim01_contiguous(src1) || src1->type == GGML_TYPE_F32 || src1->type == GGML_TYPE_F16); // NOLINT | |
| const uint64_t ne00 = src0->ne[0]; | |
| const uint64_t ne01 = src0->ne[1]; | |
| const uint64_t ne02 = src0->ne[2]; | |
| const uint64_t ne03 = src0->ne[3]; | |
| const uint64_t ne10 = src1->ne[0]; | |
| const uint64_t ne11 = src1->ne[1]; | |
| const uint64_t ne12 = src1->ne[2]; | |
| const uint64_t ne13 = src1->ne[3]; | |
| GGML_ASSERT(ne11 == 1); | |
| const uint64_t ne20 = dst->ne[0]; | |
| const uint64_t ne21 = dst->ne[1]; | |
| const uint64_t ne22 = dst->ne[2]; | |
| const uint64_t ne23 = dst->ne[3]; | |
| const uint64_t nb22 = dst->nb[2]; | |
| const uint64_t nb23 = dst->nb[3]; | |
| const uint64_t r2 = ne12 / ne02; | |
| const uint64_t r3 = ne13 / ne03; | |
| ggml_tensor_extra_gpu * extra = (ggml_tensor_extra_gpu *) dst->extra; | |
| ggml_tensor_extra_gpu * extra_src0 = (ggml_tensor_extra_gpu *) src0->extra; | |
| ggml_tensor_extra_gpu * extra_src1 = (ggml_tensor_extra_gpu *) src1->extra; | |
| vk_buffer d_Qx; | |
| size_t qx_buf_offset = 0; | |
| vk_buffer d_Qy; | |
| size_t qy_buf_offset = 0; | |
| bool src0_uma = false; | |
| bool src1_uma = false; | |
| if (ctx->device->uma) { | |
| ggml_vk_host_get(ctx, src0->data, d_Qx, qx_buf_offset); | |
| ggml_vk_host_get(ctx, src1->data, d_Qy, qy_buf_offset); | |
| src0_uma = d_Qx != nullptr; | |
| src1_uma = d_Qy != nullptr; | |
| } | |
| const bool x_non_contig = !ggml_vk_dim01_contiguous(src0); | |
| const bool y_non_contig = !ggml_vk_dim01_contiguous(src1); | |
| const bool f16_f32_kernel = src1->type == GGML_TYPE_F32; | |
| const bool qx_needs_dequant = x_non_contig; | |
| const bool qy_needs_dequant = (src1->type != GGML_TYPE_F16 && !f16_f32_kernel) || y_non_contig; | |
| // Not implemented | |
| GGML_ASSERT(y_non_contig || !qy_needs_dequant); // NOLINT | |
| const uint64_t x_ne = ne01 * ne00; | |
| const uint64_t y_ne = ne11 * ne10; | |
| const uint64_t d_ne = ne11 * ne01; | |
| const uint64_t qx_sz = ggml_vk_align_size(ggml_type_size(src0->type) * x_ne / ggml_blck_size(src0->type), ctx->device->properties.limits.minStorageBufferOffsetAlignment); | |
| const uint64_t qy_sz = ggml_type_size(src1->type) * y_ne / ggml_blck_size(src1->type); | |
| const uint64_t x_sz = x_non_contig ? ggml_vk_align_size(ggml_type_size(src0->type) * x_ne, ctx->device->properties.limits.minStorageBufferOffsetAlignment) : qx_sz; | |
| const uint64_t y_sz = f16_f32_kernel ? sizeof(float) * y_ne : sizeof(ggml_fp16_t) * y_ne; | |
| const uint64_t d_sz = sizeof(float) * d_ne; | |
| vk_buffer d_D = extra->buffer_gpu.lock(); | |
| const uint64_t d_buf_offset = extra->offset; | |
| GGML_ASSERT(d_D != nullptr); | |
| vk_buffer d_X; | |
| uint64_t x_buf_offset = 0; | |
| vk_buffer d_Y; | |
| uint64_t y_buf_offset = 0; | |
| if(!src0_uma) { | |
| d_Qx = extra_src0->buffer_gpu.lock(); | |
| qx_buf_offset = extra_src0->offset; | |
| GGML_ASSERT(d_Qx != nullptr); | |
| } | |
| if(!src1_uma) { | |
| d_Qy = extra_src1->buffer_gpu.lock(); | |
| qy_buf_offset = extra_src1->offset; | |
| GGML_ASSERT(d_Qy != nullptr); | |
| } | |
| if (qx_needs_dequant) { | |
| d_X = ctx->prealloc_x; | |
| } else { | |
| d_X = d_Qx; | |
| x_buf_offset = qx_buf_offset; | |
| GGML_ASSERT(qx_sz == x_sz); | |
| } | |
| if (qy_needs_dequant) { | |
| d_Y = ctx->prealloc_y; | |
| } else { | |
| d_Y = d_Qy; | |
| y_buf_offset = qy_buf_offset; | |
| GGML_ASSERT(qy_sz == y_sz); | |
| } | |
| vk_pipeline to_fp16_vk_0 = nullptr; | |
| vk_pipeline to_fp16_vk_1 = nullptr; | |
| if (x_non_contig) { | |
| to_fp16_vk_0 = ggml_vk_get_cpy_pipeline(ctx, src0->type, src0->type); | |
| } | |
| if (y_non_contig) { | |
| to_fp16_vk_1 = ggml_vk_get_cpy_pipeline(ctx, src1->type, src1->type); | |
| } else { | |
| to_fp16_vk_1 = ggml_vk_get_to_fp16(ctx, src1->type); | |
| } | |
| vk_pipeline dmmv = ggml_vk_get_dequantize_mul_mat_vec(ctx, src0->type, src1->type); | |
| GGML_ASSERT(!qx_needs_dequant || to_fp16_vk_0 != nullptr); // NOLINT | |
| GGML_ASSERT(!qy_needs_dequant || to_fp16_vk_1 != nullptr); // NOLINT | |
| GGML_ASSERT(dmmv != nullptr); | |
| // Allocate descriptor sets | |
| if (qx_needs_dequant) { | |
| ggml_pipeline_allocate_descriptor_sets(ctx, to_fp16_vk_0, 1); | |
| } | |
| if (qy_needs_dequant) { | |
| ggml_pipeline_allocate_descriptor_sets(ctx, to_fp16_vk_1, y_non_contig ? 1 : ne12 * ne13); | |
| } | |
| ggml_pipeline_allocate_descriptor_sets(ctx, dmmv, ne12 * ne13); | |
| if (x_non_contig) { | |
| GGML_ASSERT(x_sz == ggml_vk_align_size(ggml_type_size(src0->type) * x_ne, ctx->device->properties.limits.minStorageBufferOffsetAlignment)); | |
| ggml_vk_cpy_to_contiguous(ctx, subctx, to_fp16_vk_0, src0, { d_Qx, qx_buf_offset, VK_WHOLE_SIZE }, { d_X, 0, VK_WHOLE_SIZE }); | |
| } | |
| if (y_non_contig) { | |
| GGML_ASSERT(y_sz == ggml_type_size(src1->type) * y_ne); | |
| ggml_vk_cpy_to_contiguous(ctx, subctx, to_fp16_vk_1, src1, { d_Qy, qy_buf_offset, VK_WHOLE_SIZE }, { d_Y, 0, VK_WHOLE_SIZE }); | |
| } | |
| uint32_t stride_batch_x = ne00*ne01; | |
| uint32_t stride_batch_y = ne10*ne11; | |
| if (!ggml_vk_dim01_contiguous(src0) && !qx_needs_dequant) { | |
| stride_batch_x = src0->nb[0] / ggml_type_size(src0->type); | |
| } | |
| if (!ggml_vk_dim01_contiguous(src1) && !qy_needs_dequant) { | |
| stride_batch_y = src1->nb[0] / ggml_type_size(src1->type); | |
| } | |
| // compute | |
| const vk_mat_vec_push_constants pc = { | |
| (uint32_t)ne00, (uint32_t)ne10, (uint32_t)ne10, (uint32_t)ne01, | |
| (uint32_t)ne02, (uint32_t)ne12, (uint32_t)r2, (uint32_t)r3, | |
| stride_batch_x, stride_batch_y, (uint32_t)(ne20*ne21), | |
| // 0, 0, 0, 0, 1 | |
| }; | |
| ggml_vk_sync_buffers(subctx); | |
| ggml_vk_dispatch_pipeline(ctx, subctx, dmmv, { { d_X, x_buf_offset, x_sz * ne02 * ne03 }, { d_Y, y_buf_offset, y_sz * ne12 * ne13 }, { d_D, d_buf_offset, d_sz * ne22 * ne23} }, sizeof(vk_mat_vec_push_constants), &pc, { (uint32_t)ne01, (uint32_t)(ne12 * ne13), 1}); | |
| }*/ | |
| static void ggml_vk_op_repeat(ggml_backend_vk_context * ctx, vk_context * subctx, const ggml_tensor * src0, const ggml_tensor * src1, ggml_tensor * dst) { | |
| // guaranteed to be an integer due to the check in ggml_can_repeat | |
| const uint64_t ne0 = dst->ne[0]; | |
| const uint64_t ne1 = dst->ne[1]; | |
| const uint64_t ne2 = dst->ne[2]; | |
| const uint64_t ne3 = dst->ne[3]; | |
| const uint64_t ne00 = src0->ne[0]; | |
| const uint64_t ne01 = src0->ne[1]; | |
| const uint64_t ne02 = src0->ne[2]; | |
| const uint64_t ne03 = src0->ne[3]; | |
| const uint64_t nb0 = dst->nb[0]; | |
| const uint64_t nb1 = dst->nb[1]; | |
| const uint64_t nb2 = dst->nb[2]; | |
| const uint64_t nb3 = dst->nb[3]; | |
| const uint64_t nb00 = src0->nb[0]; | |
| const uint64_t nb01 = src0->nb[1]; | |
| const uint64_t nb02 = src0->nb[2]; | |
| const uint64_t nb03 = src0->nb[3]; | |
| const uint64_t nr0 = ne0/ne00; | |
| const uint64_t nr1 = ne1/ne01; | |
| const uint64_t nr2 = ne2/ne02; | |
| const uint64_t nr3 = ne3/ne03; | |
| // TODO: support for transposed / permuted tensors | |
| GGML_ASSERT(nb0 == sizeof(float)); | |
| GGML_ASSERT(nb00 == sizeof(float)); | |
| GGML_ASSERT(src0->backend == GGML_BACKEND_TYPE_GPU); | |
| GGML_ASSERT(dst->backend == GGML_BACKEND_TYPE_GPU); | |
| ggml_tensor_extra_gpu * extra = (ggml_tensor_extra_gpu *) dst->extra; | |
| ggml_tensor_extra_gpu * extra_src0 = (ggml_tensor_extra_gpu *) src0->extra; | |
| const vk_buffer src_buf = extra_src0->buffer_gpu.lock(); | |
| const uint64_t src_offset = extra_src0->offset; | |
| vk_buffer dst_buf = extra->buffer_gpu.lock(); | |
| const uint64_t dst_offset = extra->offset; | |
| std::vector<vk::BufferCopy> copies; | |
| for (uint64_t i3 = 0; i3 < nr3; i3++) { | |
| for (uint64_t k3 = 0; k3 < ne03; k3++) { | |
| for (uint64_t i2 = 0; i2 < nr2; i2++) { | |
| for (uint64_t k2 = 0; k2 < ne02; k2++) { | |
| for (uint64_t i1 = 0; i1 < nr1; i1++) { | |
| for (uint64_t k1 = 0; k1 < ne01; k1++) { | |
| for (uint64_t i0 = 0; i0 < nr0; i0++) { | |
| copies.push_back({ | |
| src_offset + (i3*ne03 + k3)*nb3 + (i2*ne02 + k2)*nb2 + (i1*ne01 + k1)*nb1 + (i0*ne00)*nb0, | |
| dst_offset + ( k3)*nb03 + ( k2)*nb02 + ( k1)*nb01, | |
| ne00*nb0, | |
| }); | |
| } | |
| } | |
| } | |
| } | |
| } | |
| } | |
| } | |
| ggml_vk_sync_buffers(subctx); | |
| subctx->s->buffer.copyBuffer(src_buf->buffer, dst_buf->buffer, copies); | |
| GGML_UNUSED(ctx); | |
| GGML_UNUSED(src1); | |
| } | |
| static vk_pipeline ggml_vk_op_get_pipeline(ggml_backend_vk_context * ctx, const ggml_tensor * src0, const ggml_tensor * src1, const ggml_tensor * src2, ggml_tensor * dst, ggml_op op) { | |
| switch (op) { | |
| case GGML_OP_ADD: | |
| if (src0->type == GGML_TYPE_F32 && src1->type == GGML_TYPE_F32 && dst->type == GGML_TYPE_F32) { | |
| return ctx->device->pipeline_add_f32; | |
| } | |
| return nullptr; | |
| case GGML_OP_GET_ROWS: | |
| GGML_ASSERT(src1->type == GGML_TYPE_I32); | |
| if (dst->type == GGML_TYPE_F16) { | |
| return ctx->device->pipeline_get_rows[src0->type]; | |
| } | |
| if (dst->type == GGML_TYPE_F32) { | |
| return ctx->device->pipeline_get_rows_f32[src0->type]; | |
| } | |
| return nullptr; | |
| case GGML_OP_MUL: | |
| if (src0->type == GGML_TYPE_F32 && src1->type == GGML_TYPE_F32 && dst->type == GGML_TYPE_F32) { | |
| return ctx->device->pipeline_mul_f32; | |
| } | |
| return nullptr; | |
| case GGML_OP_SCALE: | |
| if (src0->type == GGML_TYPE_F32 && dst->type == GGML_TYPE_F32) { | |
| return ctx->device->pipeline_scale_f32; | |
| } | |
| return nullptr; | |
| case GGML_OP_SQR: | |
| if (src0->type == GGML_TYPE_F32 && dst->type == GGML_TYPE_F32) { | |
| return ctx->device->pipeline_sqr_f32; | |
| } | |
| return nullptr; | |
| case GGML_OP_CLAMP: | |
| if (src0->type == GGML_TYPE_F32 && dst->type == GGML_TYPE_F32) { | |
| return ctx->device->pipeline_clamp_f32; | |
| } | |
| return nullptr; | |
| case GGML_OP_CPY: | |
| case GGML_OP_CONT: | |
| case GGML_OP_DUP: | |
| return ggml_vk_get_cpy_pipeline(ctx, src0->type, dst->type); | |
| case GGML_OP_NORM: | |
| if (src0->type == GGML_TYPE_F32 && dst->type == GGML_TYPE_F32) { | |
| return ctx->device->pipeline_norm_f32; | |
| } | |
| return nullptr; | |
| case GGML_OP_RMS_NORM: | |
| if (src0->type == GGML_TYPE_F32 && dst->type == GGML_TYPE_F32) { | |
| return ctx->device->pipeline_rms_norm_f32; | |
| } | |
| return nullptr; | |
| case GGML_OP_UNARY: | |
| switch (ggml_get_unary_op(dst)) { | |
| case GGML_UNARY_OP_SILU: | |
| if (src0->type == GGML_TYPE_F32 && dst->type == GGML_TYPE_F32) { | |
| return ctx->device->pipeline_silu_f32; | |
| } | |
| break; | |
| case GGML_UNARY_OP_GELU: | |
| if (src0->type == GGML_TYPE_F32 && dst->type == GGML_TYPE_F32) { | |
| return ctx->device->pipeline_gelu_f32; | |
| } | |
| break; | |
| case GGML_UNARY_OP_RELU: | |
| if (src0->type == GGML_TYPE_F32 && dst->type == GGML_TYPE_F32) { | |
| return ctx->device->pipeline_relu_f32; | |
| } | |
| break; | |
| default: | |
| break; | |
| } | |
| return nullptr; | |
| case GGML_OP_DIAG_MASK_INF: | |
| if (src0->type == GGML_TYPE_F32 && dst->type == GGML_TYPE_F32) { | |
| return ctx->device->pipeline_diag_mask_inf_f32; | |
| } | |
| return nullptr; | |
| case GGML_OP_SOFT_MAX: | |
| GGML_ASSERT(!src1 || src1->type == GGML_TYPE_F32 || src1->type == GGML_TYPE_F16); | |
| if (src0->type == GGML_TYPE_F32 && (src1 == nullptr || src1->type == GGML_TYPE_F32) && dst->type == GGML_TYPE_F32) { | |
| return ctx->device->pipeline_soft_max_f32; | |
| } | |
| if (src0->type == GGML_TYPE_F32 && src1->type == GGML_TYPE_F16 && src2->type == GGML_TYPE_F16 && dst->type == GGML_TYPE_F32) { | |
| return ctx->device->pipeline_soft_max_f32_f16; | |
| } | |
| return nullptr; | |
| case GGML_OP_ROPE: | |
| { | |
| const int mode = ((const int32_t *) dst->op_params)[2]; | |
| const bool is_neox = mode & 2; | |
| const bool is_glm = mode & 4; | |
| if (is_glm) { | |
| return nullptr; | |
| } | |
| if (is_neox) { | |
| if (src0->type == GGML_TYPE_F32 && dst->type == GGML_TYPE_F32) { | |
| return ctx->device->pipeline_rope_neox_f32; | |
| } | |
| if (src0->type == GGML_TYPE_F16 && dst->type == GGML_TYPE_F16) { | |
| return ctx->device->pipeline_rope_neox_f16; | |
| } | |
| } else { | |
| if (src0->type == GGML_TYPE_F32 && dst->type == GGML_TYPE_F32) { | |
| return ctx->device->pipeline_rope_f32; | |
| } | |
| if (src0->type == GGML_TYPE_F16 && dst->type == GGML_TYPE_F16) { | |
| return ctx->device->pipeline_rope_f16; | |
| } | |
| } | |
| return nullptr; | |
| } | |
| case GGML_OP_ARGSORT: | |
| if (src0->type == GGML_TYPE_F32 && dst->type == GGML_TYPE_I32) { | |
| return ctx->device->pipeline_argsort_f32; | |
| } | |
| return nullptr; | |
| default: | |
| return nullptr; | |
| } | |
| } | |
| static ggml_vk_func_t ggml_vk_op_get_func(ggml_op op) { | |
| switch(op) { | |
| case GGML_OP_REPEAT: | |
| return ggml_vk_op_repeat; | |
| default: | |
| return nullptr; | |
| } | |
| } | |
| static bool ggml_vk_op_supports_incontiguous(ggml_op op) { | |
| switch (op) { | |
| case GGML_OP_CPY: | |
| case GGML_OP_GET_ROWS: | |
| case GGML_OP_ADD: | |
| case GGML_OP_MUL: | |
| case GGML_OP_SCALE: | |
| case GGML_OP_SQR: | |
| case GGML_OP_CLAMP: | |
| return true; | |
| default: | |
| return false; | |
| } | |
| } | |
| template<typename PC> | |
| static void ggml_vk_op_f32(ggml_backend_vk_context * ctx, vk_context * subctx, const ggml_tensor * src0, const ggml_tensor * src1, const ggml_tensor * src2, ggml_tensor * dst, ggml_op op, const PC&& pc) { | |
| std::cerr << "ggml_vk_op_f32((" << src0 << ", name=" << src0->name << ", type=" << src0->type << ", backend=" << src0->backend << ", ne0=" << src0->ne[0] << ", ne1=" << src0->ne[1] << ", ne2=" << src0->ne[2] << ", ne3=" << src0->ne[3] << ", nb0=" << src0->nb[0] << ", nb1=" << src0->nb[1] << ", nb2=" << src0->nb[2] << ", nb3=" << src0->nb[3]; | |
| if (src1 != nullptr) { | |
| std::cerr << "), (" << src1 << ", name=" << src1->name << ", type=" << src1->type << ", backend=" << src1->backend << ", ne0=" << src1->ne[0] << ", ne1=" << src1->ne[1] << ", ne2=" << src1->ne[2] << ", ne3=" << src1->ne[3] << ", nb0=" << src1->nb[0] << ", nb1=" << src1->nb[1] << ", nb2=" << src1->nb[2] << ", nb3=" << src1->nb[3]; | |
| } | |
| if (src2 != nullptr) { | |
| std::cerr << "), (" << src2 << ", name=" << src2->name << ", type=" << src2->type << ", backend=" << src2->backend << ", ne0=" << src2->ne[0] << ", ne1=" << src2->ne[1] << ", ne2=" << src2->ne[2] << ", ne3=" << src2->ne[3] << ", nb0=" << src2->nb[0] << ", nb1=" << src2->nb[1] << ", nb2=" << src2->nb[2] << ", nb3=" << src2->nb[3]; | |
| } | |
| std::cerr << "), (" << dst << ", name=" << dst->name << ", type=" << dst->type << ", backend=" << dst->backend << ", ne0=" << dst->ne[0] << ", ne1=" << dst->ne[1] << ", ne2=" << dst->ne[2] << ", ne3=" << dst->ne[3] << ", nb0=" << dst->nb[0] << ", nb1=" << dst->nb[1] << ", nb2=" << dst->nb[2] << ", nb3=" << dst->nb[3] << "), " << ggml_op_name(op) << ")" << std::endl; | |
| GGML_ASSERT(op == GGML_OP_GET_ROWS || (!ggml_is_quantized(src0->type) && (src1 == nullptr || !ggml_is_quantized(src1->type)))); // NOLINT | |
| GGML_ASSERT(op == GGML_OP_CPY || ggml_vk_dim01_contiguous(src0)); // NOLINT | |
| GGML_ASSERT(dst->extra != nullptr); | |
| const uint64_t ne00 = src0->ne[0]; | |
| const uint64_t ne01 = src0->ne[1]; | |
| const uint64_t ne02 = src0->ne[2]; | |
| const uint64_t ne03 = src0->ne[3]; | |
| const uint64_t ne0 = ne00 * ne01; | |
| const bool use_src1 = src1 != nullptr; | |
| const uint64_t ne10 = use_src1 ? src1->ne[0] : 0; | |
| const uint64_t ne11 = use_src1 ? src1->ne[1] : 0; | |
| const uint64_t ne12 = use_src1 ? src1->ne[2] : 0; | |
| const uint64_t ne13 = use_src1 ? src1->ne[3] : 0; | |
| const uint64_t ne1 = ne10 * ne11; | |
| // const uint64_t nb10 = use_src1 ? src1->nb[0] : 0; | |
| const uint64_t nb2 = dst->nb[2]; | |
| const uint64_t nb3 = dst->nb[3]; | |
| const bool use_src2 = src2 != nullptr; | |
| const uint64_t ne2 = use_src2 ? src2->ne[0] * src2->ne[1] : 0; | |
| vk_pipeline pipeline = ggml_vk_op_get_pipeline(ctx, src0, src1, src2, dst, op); | |
| ggml_vk_func_t op_func; | |
| if (pipeline == nullptr) { | |
| op_func = ggml_vk_op_get_func(op); | |
| if (op_func == nullptr) { | |
| std::cerr << "ggml_vulkan: Error: Missing op: " << ggml_op_name(op) << " for " << ggml_type_name(src0->type); | |
| if (src1 != nullptr) { | |
| std::cerr << " and " << ggml_type_name(src1->type); | |
| } | |
| std::cerr << " to " << ggml_type_name(dst->type) << std::endl; | |
| GGML_ASSERT(false); | |
| } | |
| op_func(ctx, subctx, src0, src1, dst); | |
| return; | |
| } | |
| const bool op_supports_incontiguous = ggml_vk_op_supports_incontiguous(op); | |
| ggml_tensor_extra_gpu * extra = (ggml_tensor_extra_gpu *) dst->extra; | |
| ggml_tensor_extra_gpu * extra_src0 = (ggml_tensor_extra_gpu *) src0->extra; | |
| ggml_tensor_extra_gpu * extra_src1 = use_src1 ? (ggml_tensor_extra_gpu *) src1->extra : nullptr; | |
| ggml_tensor_extra_gpu * extra_src2 = use_src2 ? (ggml_tensor_extra_gpu *) src2->extra : nullptr; | |
| vk_buffer d_X = nullptr; | |
| size_t x_buf_offset = 0; | |
| vk_buffer d_Y = nullptr; | |
| size_t y_buf_offset = 0; | |
| vk_buffer d_Z = nullptr; | |
| size_t z_buf_offset = 0; | |
| bool src0_uma = false; | |
| bool src1_uma = false; | |
| bool src2_uma = false; | |
| if (ctx->device->uma) { | |
| ggml_vk_host_get(ctx, src0->data, d_X, x_buf_offset); | |
| src0_uma = d_X != nullptr; | |
| if (use_src1) { | |
| ggml_vk_host_get(ctx, src1->data, d_Y, y_buf_offset); | |
| src1_uma = d_Y != nullptr; | |
| } | |
| if (use_src2) { | |
| ggml_vk_host_get(ctx, src1->data, d_Z, z_buf_offset); | |
| src2_uma = d_Z != nullptr; | |
| } | |
| } | |
| uint64_t x_sz = ggml_vk_align_size(ggml_type_size(src0->type)/ggml_blck_size(src0->type) * ne0, ctx->device->properties.limits.minStorageBufferOffsetAlignment); | |
| uint64_t y_sz = use_src1 ? ggml_vk_align_size(ggml_type_size(src1->type) * ne1, ctx->device->properties.limits.minStorageBufferOffsetAlignment) : 0; | |
| uint64_t z_sz = use_src2 ? ggml_vk_align_size(ggml_type_size(src2->type) * ne2, ctx->device->properties.limits.minStorageBufferOffsetAlignment) : 0; | |
| uint64_t d_sz = ggml_type_size(dst->type) * ne0; | |
| vk_buffer d_D = extra->buffer_gpu.lock(); | |
| // Workaround for tiny tensor inputs on ROPE | |
| if (use_src1 && src1->backend == GGML_BACKEND_TYPE_GPU && y_sz > d_D->size) { | |
| y_sz = VK_WHOLE_SIZE; | |
| } | |
| GGML_ASSERT(d_D != nullptr); | |
| uint64_t d_buf_offset = (extra->offset / ctx->device->properties.limits.minStorageBufferOffsetAlignment) * ctx->device->properties.limits.minStorageBufferOffsetAlignment; | |
| GGML_ASSERT(d_buf_offset == extra->offset || op == GGML_OP_CPY); // NOLINT | |
| if(!src0_uma) { | |
| d_X = extra_src0->buffer_gpu.lock(); | |
| x_buf_offset = extra_src0->offset; | |
| GGML_ASSERT(d_X != nullptr); | |
| } | |
| if (use_src1 && !src1_uma) { | |
| d_Y = extra_src1->buffer_gpu.lock(); | |
| y_buf_offset = extra_src1->offset; | |
| GGML_ASSERT(d_Y != nullptr); | |
| } | |
| if (use_src2 && !src2_uma) { | |
| d_Z = extra_src2->buffer_gpu.lock(); | |
| z_buf_offset = extra_src2->offset; | |
| GGML_ASSERT(d_Z != nullptr); | |
| } | |
| if (op_supports_incontiguous) { | |
| x_sz = ggml_nbytes(src0); | |
| y_sz = use_src1 ? ggml_nbytes(src1) : 0; | |
| d_sz = ggml_nbytes(dst); | |
| if (x_buf_offset + x_sz >= d_X->size) { | |
| x_sz = VK_WHOLE_SIZE; | |
| } | |
| if (use_src1 && y_buf_offset + y_sz >= d_Y->size) { | |
| y_sz = VK_WHOLE_SIZE; | |
| } | |
| if (d_buf_offset + d_sz >= d_D->size) { | |
| d_sz = VK_WHOLE_SIZE; | |
| } | |
| } | |
| std::array<uint32_t, 3> elements; | |
| // Single call if dimension 2 is contiguous | |
| if (op_supports_incontiguous || (ggml_is_contiguous(src0) && (src1 == nullptr || ggml_is_contiguous(src1)))) { | |
| ggml_pipeline_allocate_descriptor_sets(ctx, pipeline, 1); | |
| switch (dst->op) { | |
| case GGML_OP_NORM: | |
| case GGML_OP_RMS_NORM: | |
| case GGML_OP_SOFT_MAX: | |
| elements = { (uint32_t)ggml_nrows(src0), 1, 1 }; | |
| break; | |
| case GGML_OP_DIAG_MASK_INF: | |
| case GGML_OP_ROPE: | |
| elements = { (uint32_t)ggml_nrows(src0), (uint32_t)ne00, 1 }; | |
| break; | |
| case GGML_OP_GET_ROWS: | |
| elements = { (uint32_t)ne00, (uint32_t)ne10, (uint32_t)(ne11 * ne12) }; | |
| break; | |
| default: | |
| elements = { (uint32_t)ggml_nelements(src0), 1, 1 }; | |
| break; | |
| } | |
| if (!op_supports_incontiguous) { | |
| if (x_sz != VK_WHOLE_SIZE) { | |
| x_sz *= ne02 * ne03; | |
| } | |
| if (use_src1 && y_sz != VK_WHOLE_SIZE) { | |
| y_sz *= ne12 * ne13; | |
| } | |
| if (d_sz != VK_WHOLE_SIZE) { | |
| d_sz *= ne02 * ne03; | |
| } | |
| } | |
| if (op == GGML_OP_SOFT_MAX) { | |
| // Empty src1 and src2 are possible on soft_max, but the shader needs buffers | |
| vk_subbuffer subbuf_y; | |
| if (use_src1) { | |
| subbuf_y = { d_Y, y_buf_offset, y_sz }; | |
| } else { | |
| subbuf_y = { d_X, 0, d_X->size }; | |
| } | |
| vk_subbuffer subbuf_z; | |
| if (use_src2) { | |
| subbuf_z = { d_Z, z_buf_offset, z_sz }; | |
| } else { | |
| subbuf_z = { d_X, 0, d_X->size }; | |
| } | |
| ggml_vk_sync_buffers(subctx); | |
| ggml_vk_dispatch_pipeline(ctx, subctx, pipeline, { { d_X, x_buf_offset, x_sz }, subbuf_y, subbuf_z, { d_D, d_buf_offset, d_sz } }, sizeof(PC), &pc, elements); | |
| } else if (use_src1) { | |
| ggml_vk_sync_buffers(subctx); | |
| ggml_vk_dispatch_pipeline(ctx, subctx, pipeline, { { d_X, x_buf_offset, x_sz }, { d_Y, y_buf_offset, y_sz }, { d_D, d_buf_offset, d_sz } }, sizeof(PC), &pc, elements); | |
| } else { | |
| ggml_vk_sync_buffers(subctx); | |
| ggml_vk_dispatch_pipeline(ctx, subctx, pipeline, { { d_X, x_buf_offset, x_sz }, { d_D, d_buf_offset, d_sz } }, sizeof(PC), &pc, elements); | |
| } | |
| if (dst->backend == GGML_BACKEND_TYPE_CPU && op == GGML_OP_CPY) { | |
| ggml_vk_d2h_tensor_2d(ctx, subctx, d_D, 0, dst); | |
| } else if(dst->backend == GGML_BACKEND_TYPE_CPU) { | |
| // copy dst to host | |
| float * d = (float *) dst->data; | |
| ggml_vk_buffer_read_async(ctx, subctx, d_D, 0, d, d_sz); | |
| } | |
| } else { | |
| GGML_ASSERT(op != GGML_OP_SOFT_MAX); | |
| ggml_pipeline_allocate_descriptor_sets(ctx, pipeline, ne02 * ne03); | |
| switch (dst->op) { | |
| case GGML_OP_NORM: | |
| case GGML_OP_RMS_NORM: | |
| case GGML_OP_SOFT_MAX: | |
| elements = { (uint32_t)ne01, 1, 1 }; | |
| break; | |
| case GGML_OP_DIAG_MASK_INF: | |
| case GGML_OP_ROPE: | |
| elements = { (uint32_t)ne01, (uint32_t)ne00, 1 }; | |
| break; | |
| case GGML_OP_GET_ROWS: | |
| elements = { (uint32_t)ne00, (uint32_t)ne10, (uint32_t)(ne11 * ne12) }; | |
| break; | |
| default: | |
| elements = { (uint32_t)ne0, 1, 1 }; | |
| break; | |
| } | |
| for (uint64_t i03 = 0; i03 < ne03; i03++) { | |
| for (uint64_t i02 = 0; i02 < ne02; i02++) { | |
| const uint32_t it_idx0 = (i03 * ne02 + i02); | |
| const uint32_t it_idx1 = use_src1 ? ((i03 % ne13) * ne12 + (i02 % ne12)) : 0; | |
| const uint32_t x_offset = x_sz * it_idx0; | |
| const uint32_t y_offset = y_sz * it_idx1; | |
| const uint32_t d_offset = d_sz * it_idx0; | |
| if (use_src1) { | |
| ggml_vk_sync_buffers(subctx); | |
| ggml_vk_dispatch_pipeline(ctx, subctx, pipeline, { { d_X, x_buf_offset + x_offset, x_sz }, { d_Y, y_buf_offset + y_offset, y_sz }, { d_D, d_buf_offset + d_offset, d_sz } }, sizeof(PC), &pc, elements); | |
| } else { | |
| ggml_vk_sync_buffers(subctx); | |
| ggml_vk_dispatch_pipeline(ctx, subctx, pipeline, { { d_X, x_buf_offset + x_offset, x_sz }, { d_D, d_buf_offset + d_offset, d_sz } }, sizeof(PC), &pc, elements); | |
| } | |
| if (dst->backend == GGML_BACKEND_TYPE_CPU) { | |
| // copy dst to host | |
| ggml_vk_buffer_read_async(ctx, subctx, d_D, d_buf_offset + d_offset, (char *) dst->data + i02*nb2 + i03*nb3, d_sz); | |
| } | |
| } | |
| } | |
| } | |
| } | |
| static void ggml_vk_repeat(ggml_backend_vk_context * ctx, vk_context * subctx, const ggml_tensor * src0, const ggml_tensor * src1, ggml_tensor * dst) { | |
| ggml_vk_op_f32<vk_op_push_constants>(ctx, subctx, src0, src1, nullptr, dst, GGML_OP_REPEAT, { (uint32_t)ggml_nelements(src0), (uint32_t)ggml_nelements(src1), 0.0f, 0.0f }); | |
| } | |
| static void ggml_vk_get_rows(ggml_backend_vk_context * ctx, vk_context * subctx, const ggml_tensor * src0, const ggml_tensor * src1, ggml_tensor * dst) { | |
| const uint32_t src0_type_size = ggml_type_size(src0->type); | |
| const uint32_t src1_type_size = ggml_type_size(src1->type); | |
| const uint32_t dst_type_size = ggml_type_size(dst->type); | |
| ggml_vk_op_f32<vk_op_binary_push_constants>(ctx, subctx, src0, src1, nullptr, dst, GGML_OP_GET_ROWS, { | |
| (uint32_t)ggml_nelements(src0), | |
| (uint32_t)src0->ne[0], (uint32_t)src0->ne[1], (uint32_t)src0->ne[2],(uint32_t)src0->ne[3], (uint32_t)src0->nb[0] / src0_type_size, (uint32_t)src0->nb[1] / src0_type_size, (uint32_t)src0->nb[2] / src0_type_size, (uint32_t)src0->nb[3] / src0_type_size, | |
| (uint32_t)src1->ne[0], (uint32_t)src1->ne[1], (uint32_t)src1->ne[2],(uint32_t)src1->ne[3], (uint32_t)src1->nb[0] / src1_type_size, (uint32_t)src1->nb[1] / src1_type_size, (uint32_t)src1->nb[2] / src1_type_size, (uint32_t)src1->nb[3] / src1_type_size, | |
| (uint32_t) dst->ne[0], (uint32_t) dst->ne[1], (uint32_t) dst->ne[2],(uint32_t) dst->ne[3], (uint32_t) dst->nb[0] / dst_type_size, (uint32_t) dst->nb[1] / dst_type_size, (uint32_t) dst->nb[2] / dst_type_size, (uint32_t) dst->nb[3] / dst_type_size, | |
| 0, | |
| 0.0f, 0.0f, | |
| }); | |
| } | |
| static void ggml_vk_add(ggml_backend_vk_context * ctx, vk_context * subctx, const ggml_tensor * src0, const ggml_tensor * src1, ggml_tensor * dst) { | |
| const uint32_t src0_type_size = ggml_type_size(src0->type); | |
| const uint32_t src1_type_size = ggml_type_size(src1->type); | |
| const uint32_t dst_type_size = ggml_type_size(dst->type); | |
| ggml_vk_op_f32<vk_op_binary_push_constants>(ctx, subctx, src0, src1, nullptr, dst, GGML_OP_ADD, { | |
| (uint32_t)ggml_nelements(src0), | |
| (uint32_t)src0->ne[0], (uint32_t)src0->ne[1], (uint32_t)src0->ne[2],(uint32_t)src0->ne[3], (uint32_t)src0->nb[0] / src0_type_size, (uint32_t)src0->nb[1] / src0_type_size, (uint32_t)src0->nb[2] / src0_type_size, (uint32_t)src0->nb[3] / src0_type_size, | |
| (uint32_t)src1->ne[0], (uint32_t)src1->ne[1], (uint32_t)src1->ne[2],(uint32_t)src1->ne[3], (uint32_t)src1->nb[0] / src1_type_size, (uint32_t)src1->nb[1] / src1_type_size, (uint32_t)src1->nb[2] / src1_type_size, (uint32_t)src1->nb[3] / src1_type_size, | |
| (uint32_t) dst->ne[0], (uint32_t) dst->ne[1], (uint32_t) dst->ne[2],(uint32_t) dst->ne[3], (uint32_t) dst->nb[0] / dst_type_size, (uint32_t) dst->nb[1] / dst_type_size, (uint32_t) dst->nb[2] / dst_type_size, (uint32_t) dst->nb[3] / dst_type_size, | |
| 0, | |
| 0.0f, 0.0f, | |
| }); | |
| } | |
| static void ggml_vk_mul(ggml_backend_vk_context * ctx, vk_context * subctx, const ggml_tensor * src0, const ggml_tensor * src1, ggml_tensor * dst) { | |
| const uint32_t src0_type_size = ggml_type_size(src0->type); | |
| const uint32_t src1_type_size = ggml_type_size(src1->type); | |
| const uint32_t dst_type_size = ggml_type_size(dst->type); | |
| ggml_vk_op_f32<vk_op_binary_push_constants>(ctx, subctx, src0, src1, nullptr, dst, GGML_OP_MUL, { | |
| (uint32_t)ggml_nelements(src0), | |
| (uint32_t)src0->ne[0], (uint32_t)src0->ne[1], (uint32_t)src0->ne[2],(uint32_t)src0->ne[3], (uint32_t)src0->nb[0] / src0_type_size, (uint32_t)src0->nb[1] / src0_type_size, (uint32_t)src0->nb[2] / src0_type_size, (uint32_t)src0->nb[3] / src0_type_size, | |
| (uint32_t)src1->ne[0], (uint32_t)src1->ne[1], (uint32_t)src1->ne[2],(uint32_t)src1->ne[3], (uint32_t)src1->nb[0] / src1_type_size, (uint32_t)src1->nb[1] / src1_type_size, (uint32_t)src1->nb[2] / src1_type_size, (uint32_t)src1->nb[3] / src1_type_size, | |
| (uint32_t) dst->ne[0], (uint32_t) dst->ne[1], (uint32_t) dst->ne[2],(uint32_t) dst->ne[3], (uint32_t) dst->nb[0] / dst_type_size, (uint32_t) dst->nb[1] / dst_type_size, (uint32_t) dst->nb[2] / dst_type_size, (uint32_t) dst->nb[3] / dst_type_size, | |
| 0, | |
| 0.0f, 0.0f, | |
| }); | |
| } | |
| static void ggml_vk_scale(ggml_backend_vk_context * ctx, vk_context * subctx, const ggml_tensor * src0, ggml_tensor * dst) { | |
| float * op_params = (float *)dst->op_params; | |
| const uint32_t src0_type_size = ggml_type_size(src0->type); | |
| const uint32_t dst_type_size = ggml_type_size(dst->type); | |
| ggml_vk_op_f32<vk_op_unary_push_constants>(ctx, subctx, src0, nullptr, nullptr, dst, GGML_OP_SCALE, { | |
| (uint32_t)ggml_nelements(src0), | |
| (uint32_t)src0->ne[0], (uint32_t)src0->ne[1], (uint32_t)src0->ne[2], (uint32_t)src0->ne[3], (uint32_t)src0->nb[0] / src0_type_size, (uint32_t)src0->nb[1] / src0_type_size, (uint32_t)src0->nb[2] / src0_type_size, (uint32_t)src0->nb[3] / src0_type_size, | |
| (uint32_t) dst->ne[0], (uint32_t) dst->ne[1], (uint32_t) dst->ne[2], (uint32_t) dst->ne[3], (uint32_t) dst->nb[0] / dst_type_size, (uint32_t) dst->nb[1] / dst_type_size, (uint32_t) dst->nb[2] / dst_type_size, (uint32_t) dst->nb[3] / dst_type_size, | |
| 0, | |
| op_params[0], 0.0f | |
| }); | |
| } | |
| static void ggml_vk_sqr(ggml_backend_vk_context * ctx, vk_context * subctx, const ggml_tensor * src0, ggml_tensor * dst) { | |
| const uint32_t src0_type_size = ggml_type_size(src0->type); | |
| const uint32_t dst_type_size = ggml_type_size(dst->type); | |
| ggml_vk_op_f32<vk_op_unary_push_constants>(ctx, subctx, src0, nullptr, nullptr, dst, GGML_OP_SQR, { | |
| (uint32_t)ggml_nelements(src0), | |
| (uint32_t)src0->ne[0], (uint32_t)src0->ne[1], (uint32_t)src0->ne[2], (uint32_t)src0->ne[3], (uint32_t)src0->nb[0] / src0_type_size, (uint32_t)src0->nb[1] / src0_type_size, (uint32_t)src0->nb[2] / src0_type_size, (uint32_t)src0->nb[3] / src0_type_size, | |
| (uint32_t) dst->ne[0], (uint32_t) dst->ne[1], (uint32_t) dst->ne[2], (uint32_t) dst->ne[3], (uint32_t) dst->nb[0] / dst_type_size, (uint32_t) dst->nb[1] / dst_type_size, (uint32_t) dst->nb[2] / dst_type_size, (uint32_t) dst->nb[3] / dst_type_size, | |
| 0, | |
| 0.0f, 0.0f, | |
| }); | |
| } | |
| static void ggml_vk_clamp(ggml_backend_vk_context * ctx, vk_context * subctx, const ggml_tensor * src0, ggml_tensor * dst) { | |
| float * op_params = (float *)dst->op_params; | |
| const uint32_t src0_type_size = ggml_type_size(src0->type); | |
| const uint32_t dst_type_size = ggml_type_size(dst->type); | |
| ggml_vk_op_f32<vk_op_unary_push_constants>(ctx, subctx, src0, nullptr, nullptr, dst, GGML_OP_CLAMP, { | |
| (uint32_t)ggml_nelements(src0), | |
| (uint32_t)src0->ne[0], (uint32_t)src0->ne[1], (uint32_t)src0->ne[2], (uint32_t)src0->ne[3], (uint32_t)src0->nb[0] / src0_type_size, (uint32_t)src0->nb[1] / src0_type_size, (uint32_t)src0->nb[2] / src0_type_size, (uint32_t)src0->nb[3] / src0_type_size, | |
| (uint32_t) dst->ne[0], (uint32_t) dst->ne[1], (uint32_t) dst->ne[2], (uint32_t) dst->ne[3], (uint32_t) dst->nb[0] / dst_type_size, (uint32_t) dst->nb[1] / dst_type_size, (uint32_t) dst->nb[2] / dst_type_size, (uint32_t) dst->nb[3] / dst_type_size, | |
| 0, | |
| op_params[0], op_params[1], | |
| }); | |
| } | |
| static void ggml_vk_cpy(ggml_backend_vk_context * ctx, vk_context * subctx, const ggml_tensor * src0, ggml_tensor * dst) { | |
| ggml_tensor_extra_gpu * extra = (ggml_tensor_extra_gpu *) dst->extra; | |
| const uint32_t src0_type_size = ggml_type_size(src0->type); | |
| const uint32_t dst_type_size = ggml_type_size(dst->type); | |
| const uint32_t d_offset = (extra->offset % ctx->device->properties.limits.minStorageBufferOffsetAlignment) / dst_type_size; | |
| ggml_vk_op_f32<vk_op_unary_push_constants>(ctx, subctx, src0, nullptr, nullptr, dst, GGML_OP_CPY, { | |
| (uint32_t)ggml_nelements(src0), | |
| (uint32_t)src0->ne[0], (uint32_t)src0->ne[1], (uint32_t)src0->ne[2], (uint32_t)src0->ne[3], (uint32_t)src0->nb[0] / src0_type_size, (uint32_t)src0->nb[1] / src0_type_size, (uint32_t)src0->nb[2] / src0_type_size, (uint32_t)src0->nb[3] / src0_type_size, | |
| (uint32_t) dst->ne[0], (uint32_t) dst->ne[1], (uint32_t) dst->ne[2], (uint32_t) dst->ne[3], (uint32_t) dst->nb[0] / dst_type_size, (uint32_t) dst->nb[1] / dst_type_size, (uint32_t) dst->nb[2] / dst_type_size, (uint32_t) dst->nb[3] / dst_type_size, | |
| d_offset, | |
| 0.0f, 0.0f, | |
| }); | |
| } | |
| static void ggml_vk_norm(ggml_backend_vk_context * ctx, vk_context * subctx, const ggml_tensor * src0, ggml_tensor * dst) { | |
| float * op_params = (float *)dst->op_params; | |
| ggml_vk_op_f32<vk_op_push_constants>(ctx, subctx, src0, nullptr, nullptr, dst, GGML_OP_NORM, { (uint32_t)src0->ne[0], (uint32_t)src0->ne[1], op_params[0], 0.0f }); | |
| } | |
| static void ggml_vk_rms_norm(ggml_backend_vk_context * ctx, vk_context * subctx, const ggml_tensor * src0, ggml_tensor * dst) { | |
| float * op_params = (float *)dst->op_params; | |
| ggml_vk_op_f32<vk_op_push_constants>(ctx, subctx, src0, nullptr, nullptr, dst, GGML_OP_RMS_NORM, { (uint32_t)src0->ne[0], (uint32_t)src0->ne[1], op_params[0], 0.0f }); | |
| } | |
| static void ggml_vk_unary(ggml_backend_vk_context * ctx, vk_context * subctx, const ggml_tensor * src0, ggml_tensor * dst) { | |
| ggml_vk_op_f32<vk_op_push_constants>(ctx, subctx, src0, nullptr, nullptr, dst, GGML_OP_UNARY, { (uint32_t)ggml_nelements(src0), 0, 0.0f, 0.0f }); | |
| } | |
| static void ggml_vk_diag_mask_inf(ggml_backend_vk_context * ctx, vk_context * subctx, const ggml_tensor * src0, ggml_tensor * dst) { | |
| int32_t * op_params = (int32_t *)dst->op_params; | |
| ggml_vk_op_f32<vk_op_diag_mask_push_constants>(ctx, subctx, src0, nullptr, nullptr, dst, GGML_OP_DIAG_MASK_INF, { (uint32_t)src0->ne[0], (uint32_t)src0->ne[1], op_params[0] }); | |
| } | |
| static void ggml_vk_soft_max(ggml_backend_vk_context * ctx, vk_context * subctx, const ggml_tensor * src0, const ggml_tensor * src1, const ggml_tensor * src2, ggml_tensor * dst) { | |
| float * op_params = (float *)dst->op_params; | |
| float scale = op_params[0]; | |
| float max_bias = op_params[1]; | |
| const uint32_t ncols = (uint32_t)src0->ne[0]; | |
| const uint32_t nrows_x = (uint32_t)ggml_nrows(src0); | |
| const uint32_t nrows_y = (uint32_t)src0->ne[1]; | |
| const uint32_t n_head_kv = nrows_x/nrows_y; | |
| const uint32_t n_head_log2 = 1u << (uint32_t) floorf(log2f((float) n_head_kv)); | |
| const float m0 = powf(2.0f, -(max_bias ) / n_head_log2); | |
| const float m1 = powf(2.0f, -(max_bias / 2.0f) / n_head_log2); | |
| ggml_vk_op_f32<vk_op_soft_max_push_constants>(ctx, subctx, src0, src1, src2, dst, GGML_OP_SOFT_MAX, { | |
| ncols, | |
| src1 != nullptr ? nrows_y : (uint32_t)0, | |
| src2 != nullptr ? (uint32_t)1 : (uint32_t)0, | |
| scale, max_bias, | |
| m0, m1, | |
| n_head_log2, | |
| }); | |
| } | |
| static void ggml_vk_rope(ggml_backend_vk_context * ctx, vk_context * subctx, const ggml_tensor * src0, const ggml_tensor * src1, ggml_tensor * dst) { | |
| const int n_dims = ((int32_t *) dst->op_params)[1]; | |
| const int mode = ((int32_t *) dst->op_params)[2]; | |
| // const int n_ctx = ((int32_t *) dst->op_params)[3]; | |
| const int n_orig_ctx = ((int32_t *) dst->op_params)[4]; | |
| const float freq_base = ((float *) dst->op_params)[5]; | |
| const float freq_scale = ((float *) dst->op_params)[6]; | |
| const float ext_factor = ((float *) dst->op_params)[7]; | |
| const float attn_factor = ((float *) dst->op_params)[8]; | |
| const float beta_fast = ((float *) dst->op_params)[9]; | |
| const float beta_slow = ((float *) dst->op_params)[10]; | |
| const bool is_neox = mode & 2; | |
| const bool is_glm = mode & 4; | |
| GGML_ASSERT(!is_glm); | |
| float corr_dims[2]; | |
| ggml_rope_yarn_corr_dims(n_dims, n_orig_ctx, freq_base, beta_fast, beta_slow, corr_dims); | |
| if (is_neox) { | |
| const float theta_scale = powf(freq_base, -2.0f/n_dims); | |
| const float inv_ndims = -1.0f / n_dims; | |
| ggml_vk_op_f32<vk_op_rope_neox_push_constants>(ctx, subctx, src0, src1, nullptr, dst, GGML_OP_ROPE, { (uint32_t)src0->ne[0], (uint32_t)n_dims, freq_scale, (uint32_t)src0->ne[1], freq_base, ext_factor, attn_factor, {corr_dims[0], corr_dims[1], 0.0f, 0.0f}, theta_scale, inv_ndims }); | |
| } else { | |
| ggml_vk_op_f32<vk_op_rope_push_constants>(ctx, subctx, src0, src1, nullptr, dst, GGML_OP_ROPE, { (uint32_t)src0->ne[0], freq_scale, (uint32_t)src0->ne[1], freq_base, ext_factor, attn_factor, {corr_dims[0], corr_dims[1], 0.0f, 0.0f} }); | |
| } | |
| } | |
| static void ggml_vk_argsort(ggml_backend_vk_context * ctx, vk_context * subctx, const ggml_tensor * src0, ggml_tensor * dst) { | |
| int32_t * op_params = (int32_t *)dst->op_params; | |
| ggml_vk_op_f32<vk_op_argsort_push_constants>(ctx, subctx, src0, nullptr, nullptr, dst, GGML_OP_ARGSORT, { (uint32_t)src0->ne[0], ((ggml_sort_order) op_params[0]) == GGML_SORT_ORDER_ASC }); | |
| } | |
| static void ggml_vk_print_matrix_area(const void * data, ggml_type type, int ne0, int ne1, int i0, int i1, int i2) { | |
| if (type != GGML_TYPE_F32 && type != GGML_TYPE_F16) { | |
| return; | |
| } | |
| i0 = std::max(i0, 5); | |
| i1 = std::max(i1, 5); | |
| i2 = std::max(i2, 0); | |
| fprintf(stderr, " "); | |
| for (int idx1 = i1 - 5; idx1 < i1 + 5; idx1++) { | |
| fprintf(stderr, "%7d ", idx1); | |
| } | |
| fprintf(stderr, "\n"); | |
| for (int idx0 = i0 - 5; idx0 < i0 + 5; idx0++) { | |
| fprintf(stderr, "%7d: ", idx0); | |
| for (int idx1 = i1 - 5; idx1 < i1 + 5; idx1++) { | |
| if (idx0 >= 0 && idx0 < ne0 && idx1 >= 0 && idx1 < ne1) { | |
| float val; | |
| if (type == GGML_TYPE_F32) { | |
| val = *((const float *) data + i2*ne1*ne0 + idx1*ne0 + idx0); | |
| } else if (type == GGML_TYPE_F16) { | |
| val = ggml_fp16_to_fp32(*((const ggml_fp16_t *) data + i2*ne1*ne0 + idx1*ne0 + idx0)); | |
| } else { | |
| GGML_ASSERT(false); | |
| } | |
| fprintf(stderr, "% 7.2f ", val); | |
| } else { | |
| fprintf(stderr, " "); | |
| } | |
| } | |
| fprintf(stderr, "\n"); | |
| } | |
| } | |
| template <typename X_TYPE, typename Y_TYPE> | |
| static void ggml_vk_test_matmul(ggml_backend_vk_context * ctx, size_t m, size_t n, size_t k, size_t batch, size_t num_it, int split_k, int shader_size) { | |
| std::cerr << "ggml_vk_test_matmul(" << m << ", " << n << ", " << k << ", " << batch << ", " << num_it << ", " << split_k << ", " << shader_size << ")" << std::endl; | |
| const size_t x_ne = m * k * batch; | |
| const size_t y_ne = k * n * batch; | |
| const size_t d_ne = m * n * batch; | |
| vk_pipeline p; | |
| std::string shname; | |
| if (shader_size == 0) { | |
| if (std::is_same<float, X_TYPE>() && std::is_same<float, Y_TYPE>()) { | |
| p = ctx->device->pipeline_matmul_f32->a_s; | |
| shname = "F32_ALIGNED_S"; | |
| } else if (std::is_same<ggml_fp16_t, X_TYPE>() && std::is_same<float, Y_TYPE>()) { | |
| p = ctx->device->pipeline_matmul_f16_f32->a_s; | |
| shname = "F16_F32_ALIGNED_S"; | |
| } else if (std::is_same<ggml_fp16_t, X_TYPE>() && std::is_same<ggml_fp16_t, Y_TYPE>()) { | |
| p = ctx->device->pipeline_matmul_f16->a_s; | |
| shname = "F16_ALIGNED_S"; | |
| } else { | |
| GGML_ASSERT(false); | |
| } | |
| } else if (shader_size == 1) { | |
| if (std::is_same<float, X_TYPE>() && std::is_same<float, Y_TYPE>()) { | |
| p = ctx->device->pipeline_matmul_f32->a_m; | |
| shname = "F32_ALIGNED_M"; | |
| } else if (std::is_same<ggml_fp16_t, X_TYPE>() && std::is_same<float, Y_TYPE>()) { | |
| p = ctx->device->pipeline_matmul_f16_f32->a_m; | |
| shname = "F16_F32_ALIGNED_M"; | |
| } else if (std::is_same<ggml_fp16_t, X_TYPE>() && std::is_same<ggml_fp16_t, Y_TYPE>()) { | |
| p = ctx->device->pipeline_matmul_f16->a_m; | |
| shname = "F16_ALIGNED_M"; | |
| } else { | |
| GGML_ASSERT(false); | |
| } | |
| } else if (shader_size == 2) { | |
| if (std::is_same<float, X_TYPE>() && std::is_same<float, Y_TYPE>()) { | |
| p = ctx->device->pipeline_matmul_f32->a_l; | |
| shname = "F32_ALIGNED_L"; | |
| } else if (std::is_same<ggml_fp16_t, X_TYPE>() && std::is_same<float, Y_TYPE>()) { | |
| p = ctx->device->pipeline_matmul_f16_f32->a_l; | |
| shname = "F16_F32_ALIGNED_L"; | |
| } else if (std::is_same<ggml_fp16_t, X_TYPE>() && std::is_same<ggml_fp16_t, Y_TYPE>()) { | |
| p = ctx->device->pipeline_matmul_f16->a_l; | |
| shname = "F16_ALIGNED_L"; | |
| } else { | |
| GGML_ASSERT(false); | |
| } | |
| } else { | |
| GGML_ASSERT(0); | |
| } | |
| const size_t kpad = ggml_vk_align_size(k, p->align); | |
| if (k != kpad) { | |
| if (shader_size == 0) { | |
| if (std::is_same<float, X_TYPE>() && std::is_same<float, Y_TYPE>()) { | |
| p = ctx->device->pipeline_matmul_f32->s; | |
| shname = "F32_S"; | |
| } else if (std::is_same<ggml_fp16_t, X_TYPE>() && std::is_same<float, Y_TYPE>()) { | |
| p = ctx->device->pipeline_matmul_f16_f32->s; | |
| shname = "F16_F32_S"; | |
| } else if (std::is_same<ggml_fp16_t, X_TYPE>() && std::is_same<ggml_fp16_t, Y_TYPE>()) { | |
| p = ctx->device->pipeline_matmul_f16->s; | |
| shname = "F16_S"; | |
| } | |
| } else if (shader_size == 1) { | |
| if (std::is_same<float, X_TYPE>() && std::is_same<float, Y_TYPE>()) { | |
| p = ctx->device->pipeline_matmul_f32->m; | |
| shname = "F32_M"; | |
| } else if (std::is_same<ggml_fp16_t, X_TYPE>() && std::is_same<float, Y_TYPE>()) { | |
| p = ctx->device->pipeline_matmul_f16_f32->m; | |
| shname = "F16_F32_M"; | |
| } else if (std::is_same<ggml_fp16_t, X_TYPE>() && std::is_same<ggml_fp16_t, Y_TYPE>()) { | |
| p = ctx->device->pipeline_matmul_f16->m; | |
| shname = "F16_M"; | |
| } | |
| } else if (shader_size == 2) { | |
| if (std::is_same<float, X_TYPE>() && std::is_same<float, Y_TYPE>()) { | |
| p = ctx->device->pipeline_matmul_f32->l; | |
| shname = "F32_L"; | |
| } else if (std::is_same<ggml_fp16_t, X_TYPE>() && std::is_same<float, Y_TYPE>()) { | |
| p = ctx->device->pipeline_matmul_f16_f32->l; | |
| shname = "F16_F32_L"; | |
| } else if (std::is_same<ggml_fp16_t, X_TYPE>() && std::is_same<ggml_fp16_t, Y_TYPE>()) { | |
| p = ctx->device->pipeline_matmul_f16->l; | |
| shname = "F16_L"; | |
| } | |
| } | |
| } | |
| ggml_pipeline_allocate_descriptor_sets(ctx, p, num_it); | |
| if (split_k > 1) { | |
| ggml_pipeline_allocate_descriptor_sets(ctx, ctx->device->pipeline_matmul_split_k_reduce, num_it); | |
| if (ctx->prealloc_split_k == nullptr || ctx->prealloc_split_k->size < sizeof(float) * d_ne * split_k) { | |
| // Resize buffer | |
| if (ctx->prealloc_split_k != nullptr) { | |
| ggml_vk_destroy_buffer(ctx->prealloc_split_k); | |
| } | |
| ctx->prealloc_split_k = ggml_vk_create_buffer_check(ctx, sizeof(float) * d_ne * split_k, vk::MemoryPropertyFlagBits::eDeviceLocal); | |
| } | |
| } | |
| vk_buffer d_X = ggml_vk_create_buffer_check(ctx, sizeof(X_TYPE) * x_ne, vk::MemoryPropertyFlagBits::eDeviceLocal); | |
| vk_buffer d_Y = ggml_vk_create_buffer_check(ctx, sizeof(Y_TYPE) * y_ne, vk::MemoryPropertyFlagBits::eDeviceLocal); | |
| vk_buffer d_D = ggml_vk_create_buffer_check(ctx, sizeof(float) * d_ne, vk::MemoryPropertyFlagBits::eDeviceLocal); | |
| X_TYPE* x = (X_TYPE *) malloc(sizeof(X_TYPE) * x_ne); | |
| Y_TYPE* y = (Y_TYPE *) malloc(sizeof(Y_TYPE) * y_ne); | |
| float* d = (float *) malloc(sizeof(float) * d_ne); | |
| for (size_t i = 0; i < x_ne; i++) { | |
| if (std::is_same<float, X_TYPE>()) { | |
| x[i] = (rand() / (float)RAND_MAX) * 2.0f - 1.0f; | |
| } else if (std::is_same<ggml_fp16_t, X_TYPE>()) { | |
| x[i] = ggml_fp32_to_fp16((rand() / (float)RAND_MAX) * 2.0f - 1.0f); | |
| } else { | |
| GGML_ASSERT(false); | |
| } | |
| } | |
| for (size_t i = 0; i < y_ne; i++) { | |
| if (std::is_same<float, Y_TYPE>()) { | |
| // y[i] = (rand() / (float)RAND_MAX) * 2.0f - 1.0f; | |
| y[i] = (i % k == i / k) ? 1.0f : 0.0f; | |
| } else if (std::is_same<ggml_fp16_t, Y_TYPE>()) { | |
| // y[i] = ggml_fp32_to_fp16((rand() / (float)RAND_MAX) * 2.0f - 1.0f); | |
| y[i] = ggml_fp32_to_fp16((i % k == i / k) ? 1.0f : 0.0f); | |
| } else { | |
| GGML_ASSERT(false); | |
| } | |
| } | |
| ggml_vk_buffer_write(ctx, d_X, 0, x, sizeof(X_TYPE) * k * m * batch); | |
| ggml_vk_buffer_write(ctx, d_Y, 0, y, sizeof(Y_TYPE) * k * n * batch); | |
| vk_context * subctx = ggml_vk_create_context(ctx, ctx->device->compute_queue); | |
| for (size_t i = 0; i < num_it; i++) { | |
| ggml_vk_ctx_begin(ctx, subctx); | |
| ggml_vk_matmul( | |
| ctx, subctx, p, ggml_vk_subbuffer(d_X), ggml_vk_subbuffer(d_Y), ggml_vk_subbuffer(d_D), ggml_vk_subbuffer(ctx->prealloc_split_k), | |
| m, n, k, k, k, m, split_k, batch, batch, batch, 1, 1, k*m, k*n, m*n, 0, 0, 0, 0, 1 | |
| ); | |
| ggml_vk_ctx_end(subctx); | |
| } | |
| auto begin = std::chrono::high_resolution_clock::now(); | |
| ggml_vk_submit(subctx, ctx->fence); | |
| VK_CHECK(ctx->device->device.waitForFences({ ctx->fence }, true, UINT64_MAX), "ggml_vk_test_matmul waitForFences"); | |
| ctx->device->device.resetFences({ ctx->fence }); | |
| auto end = std::chrono::high_resolution_clock::now(); | |
| double time = std::chrono::duration_cast<std::chrono::microseconds>(end-begin).count() / 1000.0; | |
| // copy dst to host | |
| ggml_vk_buffer_read(ctx, d_D, 0, d, sizeof(float) * d_ne); | |
| float * d_chk = (float *) malloc(sizeof(float) * d_ne); | |
| ggml_init_params iparams = { | |
| /*.mem_size =*/ 1024*1024*1024, | |
| /*.mem_buffer =*/ NULL, | |
| /*.no_alloc =*/ true, | |
| }; | |
| ggml_context * ggml_ctx = ggml_init(iparams); | |
| ggml_type src0_type; | |
| ggml_type src1_type; | |
| if (std::is_same<float, X_TYPE>()) { | |
| src0_type = GGML_TYPE_F32; | |
| } else if (std::is_same<ggml_fp16_t, X_TYPE>()) { | |
| src0_type = GGML_TYPE_F16; | |
| } else { | |
| GGML_ASSERT(false); | |
| } | |
| if (std::is_same<float, Y_TYPE>()) { | |
| src1_type = GGML_TYPE_F32; | |
| } else if (std::is_same<ggml_fp16_t, Y_TYPE>()) { | |
| src1_type = GGML_TYPE_F16; | |
| } else { | |
| GGML_ASSERT(false); | |
| } | |
| ggml_tensor * src0_ggml = ggml_new_tensor_3d(ggml_ctx, src0_type, k, m, batch); | |
| ggml_tensor * src1_ggml = ggml_new_tensor_3d(ggml_ctx, src1_type, k, n, batch); | |
| ggml_tensor * tensor_ggml = ggml_mul_mat(ggml_ctx, src0_ggml, src1_ggml); | |
| src0_ggml->data = x; | |
| src1_ggml->data = y; | |
| tensor_ggml->data = d_chk; | |
| ctx->disable = true; | |
| ggml_cgraph * cgraph = ggml_new_graph(ggml_ctx); | |
| ggml_build_forward_expand(cgraph, tensor_ggml); | |
| ggml_graph_compute_with_ctx(ggml_ctx, cgraph, 1); | |
| ctx->disable = false; | |
| ggml_free(ggml_ctx); | |
| double avg_err = 0.0; | |
| int first_err_n = -1; | |
| int first_err_m = -1; | |
| int first_err_b = -1; | |
| for (size_t i = 0; i < m*n*batch; i++) { | |
| double err = std::fabs(d[i] - d_chk[i]); | |
| avg_err += err; | |
| if (err > 0.05f && first_err_n == -1) { | |
| first_err_b = i / (m * n); | |
| first_err_n = (i % (m * n)) / m; | |
| first_err_m = (i % (m * n)) % m; | |
| } | |
| } | |
| avg_err /= m * n; | |
| std::cerr << "TEST " << shname << " m=" << m << " n=" << n << " k=" << k << " batch=" << batch << " split_k=" << split_k << " matmul " << time / num_it << "ms avg_err=" << avg_err << std::endl; | |
| if (avg_err > 0.1) { | |
| std::cerr << "m = " << first_err_m << " n = " << first_err_n << " b = " << first_err_b << std::endl; | |
| std::cerr << "Actual result: " << std::endl << std::endl; | |
| ggml_vk_print_matrix_area(d, GGML_TYPE_F32, m, n, first_err_m, first_err_n, first_err_b); | |
| std::cerr << std::endl; | |
| ggml_vk_print_matrix_area(d, GGML_TYPE_F32, m, n, first_err_m, first_err_n + 15, first_err_b); | |
| std::cerr << "Expected result: " << std::endl << std::endl; | |
| ggml_vk_print_matrix_area(d_chk, GGML_TYPE_F32, m, n, first_err_m, first_err_n, first_err_b); | |
| if (split_k > 1) { | |
| float * split_k_buf = (float *) malloc(sizeof(float) * d_ne * split_k); | |
| ggml_vk_buffer_read(ctx, ctx->prealloc_split_k, 0, split_k_buf, sizeof(float) * d_ne * split_k); | |
| std::cerr << "d_buf0: " << std::endl << std::endl; | |
| ggml_vk_print_matrix_area(split_k_buf, GGML_TYPE_F32, m, n, first_err_m, first_err_n, first_err_b); | |
| std::cerr << "d_buf1: " << std::endl << std::endl; | |
| ggml_vk_print_matrix_area(split_k_buf + d_ne, GGML_TYPE_F32, m, n, first_err_m, first_err_n, first_err_b); | |
| std::cerr << "d_buf2: " << std::endl << std::endl; | |
| ggml_vk_print_matrix_area(split_k_buf + 2 * d_ne, GGML_TYPE_F32, m, n, first_err_m, first_err_n, first_err_b); | |
| std::cerr << "d_buf3: " << std::endl << std::endl; | |
| ggml_vk_print_matrix_area(split_k_buf + 3 * d_ne, GGML_TYPE_F32, m, n, first_err_m, first_err_n, first_err_b); | |
| free(split_k_buf); | |
| } | |
| } | |
| free(d_chk); | |
| ggml_vk_queue_cleanup(ctx, ctx->device->transfer_queue); | |
| ggml_vk_queue_cleanup(ctx, ctx->device->compute_queue); | |
| ggml_vk_destroy_buffer(d_X); | |
| ggml_vk_destroy_buffer(d_Y); | |
| ggml_vk_destroy_buffer(d_D); | |
| ggml_pipeline_cleanup(p); | |
| ggml_pipeline_cleanup(ctx->device->pipeline_matmul_split_k_reduce); | |
| free(x); | |
| free(y); | |
| free(d); | |
| } | |
| static void ggml_vk_print_tensor_area(const ggml_tensor * tensor, int i0, int i1, int i2, int i3) { | |
| if (tensor->type != GGML_TYPE_F32 && tensor->type != GGML_TYPE_F16) { | |
| return; | |
| } | |
| i0 = std::max(i0, 5); | |
| i1 = std::max(i1, 5); | |
| i2 = std::max(i2, 0); | |
| i3 = std::max(i3, 0); | |
| fprintf(stderr, " "); | |
| for (int idx1 = i1 - 5; idx1 < i1 + 5; idx1++) { | |
| fprintf(stderr, "%7d ", idx1); | |
| } | |
| fprintf(stderr, "\n"); | |
| for (int idx0 = i0 - 5; idx0 < i0 + 5; idx0++) { | |
| fprintf(stderr, "%7d: ", idx0); | |
| for (int idx1 = i1 - 5; idx1 < i1 + 5; idx1++) { | |
| if (idx0 >= 0 && idx0 < tensor->ne[0] && idx1 >= 0 && idx1 < tensor->ne[1] && i2 >= 0 && i2 < tensor->ne[2] && i3 >= 0 && i3 < tensor->ne[3]) { | |
| float val; | |
| if (tensor->type == GGML_TYPE_F32) { | |
| val = *(float *) ((char *) tensor->data + i3*tensor->nb[3] + i2*tensor->nb[2] + idx1*tensor->nb[1] + idx0*tensor->nb[0]); | |
| } else if (tensor->type == GGML_TYPE_F16) { | |
| val = ggml_fp16_to_fp32(*(ggml_fp16_t *) ((char *) tensor->data + i3*tensor->nb[3] + i2*tensor->nb[2] + idx1*tensor->nb[1] + idx0*tensor->nb[0])); | |
| } else { | |
| GGML_ASSERT(false); | |
| } | |
| fprintf(stderr, "% 7.2f ", val); | |
| } else { | |
| fprintf(stderr, " "); | |
| } | |
| } | |
| fprintf(stderr, "\n"); | |
| } | |
| } | |
| static void ggml_vk_test_h2d_nc(ggml_backend_vk_context * ctx, size_t ne0, size_t ne1, size_t ne2, size_t ne3) { | |
| const size_t ne = ne0 * ne1 * ne2 * ne3; | |
| ggml_init_params iparams = { | |
| /*.mem_size =*/ 1024*1024*1024, | |
| /*.mem_buffer =*/ NULL, | |
| /*.no_alloc =*/ true, | |
| }; | |
| ggml_context * ggml_ctx = ggml_init(iparams); | |
| ggml_tensor * tensor = ggml_new_tensor_4d(ggml_ctx, GGML_TYPE_F32, ne0, ne2, ne1, ne3); // NOLINT | |
| ggml_tensor * result_tensor = ggml_new_tensor_4d(ggml_ctx, GGML_TYPE_F32, ne0, ne1, ne2, ne3); | |
| float * data = (float *) ggml_vk_host_malloc(ctx, ggml_nbytes(tensor)); | |
| tensor->data = data; | |
| float * result_data = (float *) malloc(ggml_nbytes(tensor)); | |
| result_tensor->data = result_data; | |
| // Permute | |
| { | |
| size_t tmp = tensor->nb[2]; | |
| tensor->nb[2] = tensor->nb[1]; | |
| tensor->nb[1] = tmp; | |
| tensor->ne[2] = ne2; | |
| tensor->ne[1] = ne1; | |
| } | |
| for (size_t i = 0; i < ne; i++) { | |
| data[i] = (rand() / (float)RAND_MAX) * 2.0f - 1.0f; | |
| } | |
| vk_context * subctx = ggml_vk_create_context(ctx, ctx->device->compute_queue); | |
| ggml_vk_ctx_begin(ctx, subctx); | |
| vk_buffer buffer = ggml_vk_create_buffer_check(ctx, ggml_nbytes(tensor), vk::MemoryPropertyFlagBits::eDeviceLocal); | |
| ggml_vk_h2d_tensor_2d(ctx, subctx, buffer, 0, tensor, 0, 0, ggml_nrows(tensor)); | |
| ggml_vk_ctx_end(subctx); | |
| ggml_vk_submit(subctx, ctx->fence); | |
| VK_CHECK(ctx->device->device.waitForFences({ ctx->fence }, true, UINT64_MAX), "ggml_vk_test_h2d_nc waitForFences"); | |
| ctx->device->device.resetFences({ ctx->fence }); | |
| ggml_vk_buffer_read(ctx, buffer, 0, result_data, ggml_nbytes(tensor)); | |
| double avg_err = 0.0; | |
| int first_err_i0 = -1; | |
| int first_err_i1 = -1; | |
| int first_err_i2 = -1; | |
| int first_err_i3 = -1; | |
| for (size_t i3 = 0; i3 < ne3; i3++) { | |
| for (size_t i2 = 0; i2 < ne2; i2++) { | |
| for (size_t i1 = 0; i1 < ne1; i1++) { | |
| for (size_t i0 = 0; i0 < ne0; i0++) { | |
| float correct = *(float *) ((char *) data + i3*tensor->nb[3] + i2*tensor->nb[2] + i1*tensor->nb[1] + i0*tensor->nb[0]); | |
| float result = *(float *) ((char *) result_data + i3*ne2*ne1*ne0*sizeof(float) + i2*ne1*ne0*sizeof(float) + i1*ne0*sizeof(float) + i0*sizeof(float)); | |
| double err = std::fabs(result - correct); | |
| avg_err += err; | |
| if (err > 0.05f && first_err_i0 == -1) { | |
| first_err_i0 = i0; | |
| first_err_i1 = i1; | |
| first_err_i2 = i2; | |
| first_err_i3 = i3; | |
| } | |
| } | |
| } | |
| } | |
| } | |
| avg_err /= ne; | |
| std::cerr << "TEST nc copy ne0=" << ne0 << " ne1=" << ne1 << " ne2=" << ne2 << " ne3=" << ne3 << " avg_err=" << avg_err << std::endl; | |
| if (avg_err > 0.1) { | |
| std::cerr << "i0 = " << first_err_i0 << " i1 = " << first_err_i1 << " i2 = " << first_err_i2 << " i3 = " << first_err_i3 << std::endl; | |
| std::cerr << "Actual result: " << std::endl << std::endl; | |
| ggml_vk_print_tensor_area(result_tensor, first_err_i0, first_err_i1, first_err_i2, first_err_i3); | |
| std::cerr << "Expected result: " << std::endl << std::endl; | |
| ggml_vk_print_tensor_area(tensor, first_err_i0, first_err_i1, first_err_i2, first_err_i3); | |
| } | |
| ggml_free(ggml_ctx); | |
| ggml_vk_destroy_buffer(buffer); | |
| ggml_vk_host_free(ctx, data); | |
| free(result_data); | |
| } | |
| static void ggml_vk_test_transfer(ggml_backend_vk_context * ctx, size_t ne, bool pinned) { | |
| std::cerr << "ggml_vk_test_transfer(" << ne << ")" << std::endl; | |
| // Check transfers are correct | |
| vk_buffer buffer = ggml_vk_create_buffer_check(ctx, sizeof(float) * ne, vk::MemoryPropertyFlagBits::eDeviceLocal); | |
| float * x; | |
| float * y; | |
| if (pinned) { | |
| x = (float *) ggml_vk_host_malloc(ctx, sizeof(float) * ne); | |
| y = (float *) ggml_vk_host_malloc(ctx, sizeof(float) * ne); | |
| } else { | |
| x = (float *) malloc(sizeof(float) * ne); | |
| y = (float *) malloc(sizeof(float) * ne); | |
| } | |
| for (size_t i = 0; i < ne; i++) { | |
| x[i] = rand() / (float)RAND_MAX; | |
| } | |
| vk_context * subctx = ggml_vk_create_context(ctx, ctx->device->compute_queue); | |
| ggml_vk_ctx_begin(ctx, subctx); | |
| auto begin = std::chrono::high_resolution_clock::now(); | |
| ggml_vk_buffer_write_async(ctx, subctx, buffer, 0, x, sizeof(float) * ne); | |
| for (auto& cpy : subctx->in_memcpys) { | |
| memcpy(cpy.dst, cpy.src, cpy.n); | |
| } | |
| subctx->in_memcpys.clear(); | |
| ggml_vk_ctx_end(subctx); | |
| ggml_vk_submit(subctx, ctx->fence); | |
| VK_CHECK(ctx->device->device.waitForFences({ ctx->fence }, true, UINT64_MAX), "ggml_vk_test_transfer waitForFences"); | |
| ctx->device->device.resetFences({ ctx->fence }); | |
| auto end = std::chrono::high_resolution_clock::now(); | |
| double ms_to_gpu = std::chrono::duration_cast<std::chrono::microseconds>(end-begin).count() / 1000.0; | |
| ggml_vk_ctx_begin(ctx, subctx); | |
| begin = std::chrono::high_resolution_clock::now(); | |
| ggml_vk_buffer_read_async(ctx, subctx, buffer, 0, y, sizeof(float) * ne); | |
| ggml_vk_ctx_end(subctx); | |
| ggml_vk_submit(subctx, ctx->fence); | |
| VK_CHECK(ctx->device->device.waitForFences({ ctx->fence }, true, UINT64_MAX), "ggml_vk_test_transfer waitForFences"); | |
| ctx->device->device.resetFences({ ctx->fence }); | |
| for (auto& cpy : subctx->out_memcpys) { | |
| memcpy(cpy.dst, cpy.src, cpy.n); | |
| } | |
| subctx->out_memcpys.clear(); | |
| end = std::chrono::high_resolution_clock::now(); | |
| double ms_from_gpu = std::chrono::duration_cast<std::chrono::microseconds>(end-begin).count() / 1000.0; | |
| double avg_err = 0.0; | |
| for (size_t i = 0; i < ne; i++) { | |
| avg_err += std::fabs(x[i] - y[i]); | |
| } | |
| double kb = ne * sizeof(float) / 1024.0; | |
| std::cerr << "TEST TRANSFER " << kb << " KB to_gpu " << ms_to_gpu << "ms (" << kb / ms_to_gpu * 1000.0 / 1024.0 << " MB/s) from_gpu " << ms_from_gpu << "ms (" << kb / ms_from_gpu * 1000.0 / 1024.0 << " MB/s) avg_err=" << avg_err / ne << std::endl; | |
| ggml_vk_destroy_buffer(buffer); | |
| if (pinned) { | |
| ggml_vk_host_free(ctx, x); | |
| ggml_vk_host_free(ctx, y); | |
| } else { | |
| free(x); | |
| free(y); | |
| } | |
| } | |
| static void ggml_vk_quantize_data(const float * from, void * to, size_t ne, ggml_type quant) { | |
| ggml_quantize_chunk(quant, from, to, 0, 1, ne, nullptr); | |
| } | |
| static void ggml_vk_test_dequant(ggml_backend_vk_context * ctx, size_t ne, ggml_type quant) { | |
| std::cerr << "ggml_vk_test_dequant(" << ne << ")" << std::endl; | |
| const size_t x_sz = sizeof(float) * ne; | |
| const size_t x_sz_f16 = sizeof(ggml_fp16_t) * ne; | |
| const size_t qx_sz = ne * ggml_type_size(quant)/ggml_blck_size(quant); | |
| float * x = (float *) malloc(x_sz); | |
| void * qx = malloc(qx_sz); | |
| vk_buffer qx_buf = ggml_vk_create_buffer_check(ctx, qx_sz, vk::MemoryPropertyFlagBits::eDeviceLocal); | |
| vk_buffer x_buf = ggml_vk_create_buffer_check(ctx, x_sz_f16, vk::MemoryPropertyFlagBits::eDeviceLocal); | |
| ggml_fp16_t * x_chk = (ggml_fp16_t *) malloc(x_sz_f16); | |
| for (size_t i = 0; i < ne; i++) { | |
| x[i] = rand() / (float)RAND_MAX; | |
| } | |
| vk_pipeline p = ctx->device->pipeline_dequant[quant]; | |
| ggml_vk_quantize_data(x, qx, ne, quant); | |
| ggml_pipeline_allocate_descriptor_sets(ctx, p, 1); | |
| ggml_vk_buffer_write(ctx, qx_buf, 0, qx, qx_sz); | |
| vk_context * subctx = ggml_vk_create_context(ctx, ctx->device->compute_queue); | |
| ggml_vk_ctx_begin(ctx, subctx); | |
| const std::vector<uint32_t> pc = { 1, (uint32_t)ne, (uint32_t)ne, (uint32_t)ne, (uint32_t)ne }; | |
| ggml_vk_dispatch_pipeline(ctx, subctx, p, { { qx_buf, 0, qx_sz }, { x_buf, 0, x_sz_f16 } }, pc.size() * sizeof(int), pc.data(), { (uint32_t)ne, 1, 1}); | |
| ggml_vk_ctx_end(subctx); | |
| auto begin = std::chrono::high_resolution_clock::now(); | |
| ggml_vk_submit(subctx, ctx->fence); | |
| VK_CHECK(ctx->device->device.waitForFences({ ctx->fence }, true, UINT64_MAX), "ggml_vk_test_dequant waitForFences"); | |
| ctx->device->device.resetFences({ ctx->fence }); | |
| auto end = std::chrono::high_resolution_clock::now(); | |
| double ms_dequant = std::chrono::duration_cast<std::chrono::microseconds>(end-begin).count() / 1000.0; | |
| ggml_vk_buffer_read(ctx, x_buf, 0, x_chk, x_sz_f16); | |
| int first_err = -1; | |
| double avg_err = 0.0; | |
| for (size_t i = 0; i < ne; i++) { | |
| double error = std::fabs(x[i] - ggml_fp16_to_fp32(x_chk[i])); | |
| avg_err += error; | |
| if (first_err < 0 && error > 0.05) { | |
| first_err = i; | |
| } | |
| } | |
| avg_err /= ne; | |
| std::cerr << "TEST DEQUANT " << ggml_type_name(quant) << " time=" << ms_dequant << "ms avg_err=" << avg_err << std::endl; | |
| if (avg_err > 0.1) { | |
| std::cerr << "first_error = " << first_err << std::endl; | |
| std::cerr << "Actual result: " << std::endl << std::endl; | |
| for (int i = std::max(0, first_err - 5); i < std::min((int)ne, first_err + 5); i++) { | |
| std::cerr << ggml_fp16_to_fp32(x_chk[i]) << ", "; | |
| } | |
| std::cerr << std::endl << "Expected result: " << std::endl << std::endl; | |
| for (int i = std::max(0, first_err - 5); i < std::min((int)ne, first_err + 5); i++) { | |
| std::cerr << x[i] << ", "; | |
| } | |
| std::cerr << std::endl; | |
| } | |
| ggml_vk_destroy_buffer(x_buf); | |
| ggml_vk_destroy_buffer(qx_buf); | |
| free(x); | |
| free(qx); | |
| free(x_chk); | |
| } | |
| static void ggml_vk_test_dequant_matmul(ggml_backend_vk_context * ctx, size_t m, size_t n, size_t k, size_t batch, size_t num_it, size_t split_k, size_t shader_size, ggml_type quant) { | |
| std::cerr << "ggml_vk_test_dequant_matmul(" << m << ", " << n << ", " << k << ", " << batch << ", " << num_it << ", " << split_k << ", " << ggml_type_name(quant) << ")" << std::endl; | |
| const size_t x_ne = m * k * batch; | |
| const size_t y_ne = k * n * batch; | |
| const size_t d_ne = m * n * batch; | |
| vk_pipeline p; | |
| std::string shname; | |
| if (shader_size == 0) { | |
| p = ctx->device->pipeline_dequant_mul_mat_mat[quant]->a_s; | |
| shname = std::string(ggml_type_name(quant)) + "_ALIGNED_S"; | |
| } else if (shader_size == 1) { | |
| p = ctx->device->pipeline_dequant_mul_mat_mat[quant]->a_m; | |
| shname = std::string(ggml_type_name(quant)) + "_ALIGNED_M"; | |
| } else if (shader_size == 2) { | |
| p = ctx->device->pipeline_dequant_mul_mat_mat[quant]->a_l; | |
| shname = std::string(ggml_type_name(quant)) + "_ALIGNED_L"; | |
| } else { | |
| GGML_ASSERT(0); | |
| } | |
| const size_t kpad = ggml_vk_align_size(k, p->align); | |
| if (k != kpad) { | |
| if (shader_size == 0) { | |
| p = ctx->device->pipeline_dequant_mul_mat_mat[quant]->s; | |
| shname = std::string(ggml_type_name(quant)) + "_S"; | |
| } else if (shader_size == 1) { | |
| p = ctx->device->pipeline_dequant_mul_mat_mat[quant]->m; | |
| shname = std::string(ggml_type_name(quant)) + "_M"; | |
| } else if (shader_size == 2) { | |
| p = ctx->device->pipeline_dequant_mul_mat_mat[quant]->l; | |
| shname = std::string(ggml_type_name(quant)) + "_L"; | |
| } else { | |
| GGML_ASSERT(0); | |
| } | |
| } | |
| const size_t x_sz = sizeof(float) * x_ne; | |
| const size_t y_sz = sizeof(float) * y_ne; | |
| const size_t qx_sz = x_ne * ggml_type_size(quant)/ggml_blck_size(quant); | |
| const size_t d_sz = sizeof(float) * d_ne; | |
| float * x = (float *) malloc(x_sz); | |
| float * y = (float *) malloc(y_sz); | |
| void * qx = malloc(qx_sz); | |
| vk_buffer qx_buf = ggml_vk_create_buffer_check(ctx, qx_sz, vk::MemoryPropertyFlagBits::eDeviceLocal); | |
| vk_buffer y_buf = ggml_vk_create_buffer_check(ctx, y_sz, vk::MemoryPropertyFlagBits::eDeviceLocal); | |
| vk_buffer d_buf = ggml_vk_create_buffer_check(ctx, d_sz, vk::MemoryPropertyFlagBits::eDeviceLocal); | |
| float * d = (float *) malloc(d_sz); | |
| float * d_chk = (float *) malloc(d_sz); | |
| for (size_t i = 0; i < x_ne; i++) { | |
| x[i] = (rand() / (float)RAND_MAX) * 2.0f - 1.0f; | |
| } | |
| ggml_vk_quantize_data(x, qx, x_ne, quant); | |
| for (size_t i = 0; i < y_ne; i++) { | |
| // y[i] = rand() / (float)RAND_MAX; | |
| y[i] = (i % k == i / k) ? 1.0f : 0.0f; | |
| } | |
| ggml_pipeline_allocate_descriptor_sets(ctx, p, num_it); | |
| if (split_k > 1) { | |
| ggml_pipeline_allocate_descriptor_sets(ctx, ctx->device->pipeline_matmul_split_k_reduce, num_it); | |
| if (ctx->prealloc_split_k == nullptr || ctx->prealloc_split_k->size < sizeof(float) * d_ne * split_k) { | |
| // Resize buffer | |
| if (ctx->prealloc_split_k != nullptr) { | |
| ggml_vk_destroy_buffer(ctx->prealloc_split_k); | |
| } | |
| ctx->prealloc_split_k = ggml_vk_create_buffer_check(ctx, sizeof(float) * d_ne * split_k, vk::MemoryPropertyFlagBits::eDeviceLocal); | |
| } | |
| } | |
| ggml_vk_buffer_write(ctx, qx_buf, 0, qx, qx_sz); | |
| ggml_vk_buffer_write(ctx, y_buf, 0, y, y_sz); | |
| vk_context * subctx = ggml_vk_create_context(ctx, ctx->device->compute_queue); | |
| for (size_t i = 0; i < num_it; i++) { | |
| ggml_vk_ctx_begin(ctx, subctx); | |
| ggml_vk_matmul( | |
| ctx, subctx, p, ggml_vk_subbuffer(qx_buf), ggml_vk_subbuffer(y_buf), ggml_vk_subbuffer(d_buf), ggml_vk_subbuffer(ctx->prealloc_split_k), | |
| m, n, k, k, k, m, split_k, batch, batch, batch, 1, 1, k*m, k*n, m*n, 0, 0, 0, 0, 1 | |
| ); | |
| ggml_vk_ctx_end(subctx); | |
| } | |
| auto begin = std::chrono::high_resolution_clock::now(); | |
| ggml_vk_submit(subctx, ctx->fence); | |
| VK_CHECK(ctx->device->device.waitForFences({ ctx->fence }, true, UINT64_MAX), "ggml_vk_test_dequant waitForFences"); | |
| ctx->device->device.resetFences({ ctx->fence }); | |
| auto end = std::chrono::high_resolution_clock::now(); | |
| double time_ms = std::chrono::duration_cast<std::chrono::microseconds>(end-begin).count() / 1000.0; | |
| ggml_vk_buffer_read(ctx, d_buf, 0, d, d_sz); | |
| ggml_init_params iparams = { | |
| /*.mem_size =*/ 1024*1024*1024, | |
| /*.mem_buffer =*/ NULL, | |
| /*.no_alloc =*/ true, | |
| }; | |
| ggml_context * ggml_ctx = ggml_init(iparams); | |
| ggml_tensor * src0_ggml = ggml_new_tensor_3d(ggml_ctx, quant, k, m, batch); | |
| ggml_tensor * src1_ggml = ggml_new_tensor_3d(ggml_ctx, GGML_TYPE_F32, k, n, batch); | |
| ggml_tensor * tensor_ggml = ggml_mul_mat(ggml_ctx, src0_ggml, src1_ggml); | |
| src0_ggml->data = qx; | |
| src1_ggml->data = y; | |
| tensor_ggml->data = d_chk; | |
| ctx->disable = true; | |
| ggml_cgraph * cgraph = ggml_new_graph(ggml_ctx); | |
| ggml_build_forward_expand(cgraph, tensor_ggml); | |
| ggml_graph_compute_with_ctx(ggml_ctx, cgraph, 1); | |
| ctx->disable = false; | |
| ggml_free(ggml_ctx); | |
| double avg_err = 0.0; | |
| int first_err_n = -1; | |
| int first_err_m = -1; | |
| int first_err_b = -1; | |
| for (size_t i = 0; i < m*n*batch; i++) { | |
| double err = std::fabs(d[i] - d_chk[i]); | |
| avg_err += err; | |
| if ((err > 0.05f || std::isnan(err)) && first_err_n == -1) { | |
| first_err_b = i / (m * n); | |
| first_err_n = (i % (m * n)) / m; | |
| first_err_m = (i % (m * n)) % m; | |
| } | |
| } | |
| avg_err /= m * n; | |
| std::cerr << "TEST MMQ " << shname << " m=" << m << " n=" << n << " k=" << k << " batch=" << batch << " split_k=" << split_k << " matmul " << time_ms / num_it << "ms avg_err=" << avg_err << std::endl; | |
| if (avg_err > 0.01 || std::isnan(avg_err)) { | |
| std::cerr << "m = " << first_err_m << " n = " << first_err_n << " b = " << first_err_b << std::endl; | |
| std::cerr << "Actual result: " << std::endl << std::endl; | |
| ggml_vk_print_matrix_area(d, GGML_TYPE_F32, m, n, first_err_m, first_err_n, first_err_b); | |
| std::cerr << std::endl; | |
| std::cerr << "Expected result: " << std::endl << std::endl; | |
| ggml_vk_print_matrix_area(d_chk, GGML_TYPE_F32, m, n, first_err_m, first_err_n, first_err_b); | |
| if (split_k > 1) { | |
| float * split_k_buf = (float *) malloc(sizeof(float) * d_ne * split_k); | |
| ggml_vk_buffer_read(ctx, ctx->prealloc_split_k, 0, split_k_buf, sizeof(float) * d_ne * split_k); | |
| std::cerr << "d_buf0: " << std::endl << std::endl; | |
| ggml_vk_print_matrix_area(split_k_buf, GGML_TYPE_F32, m, n, first_err_m, first_err_n, first_err_b); | |
| std::cerr << "d_buf1: " << std::endl << std::endl; | |
| ggml_vk_print_matrix_area(split_k_buf + d_ne, GGML_TYPE_F32, m, n, first_err_m, first_err_n, first_err_b); | |
| std::cerr << "d_buf2: " << std::endl << std::endl; | |
| ggml_vk_print_matrix_area(split_k_buf + 2 * d_ne, GGML_TYPE_F32, m, n, first_err_m, first_err_n, first_err_b); | |
| std::cerr << "d_buf3: " << std::endl << std::endl; | |
| ggml_vk_print_matrix_area(split_k_buf + 3 * d_ne, GGML_TYPE_F32, m, n, first_err_m, first_err_n, first_err_b); | |
| free(split_k_buf); | |
| } | |
| } | |
| ggml_vk_destroy_buffer(qx_buf); | |
| ggml_vk_destroy_buffer(y_buf); | |
| ggml_vk_destroy_buffer(d_buf); | |
| free(x); | |
| free(qx); | |
| free(y); | |
| free(d); | |
| free(d_chk); | |
| } | |
| static ggml_tensor_extra_gpu * ggml_vk_tensor_create_extra(ggml_tensor * tensor) { | |
| std::cerr << "ggml_vk_create_extra(" << tensor << " (" << tensor->name << ", " << ggml_op_name(tensor->op) << "))" << std::endl; | |
| ggml_tensor_extra_gpu * extra = new ggml_tensor_extra_gpu; | |
| extra->reset(); | |
| tensor->extra = extra; | |
| return extra; | |
| } | |
| static void ggml_vk_preallocate_buffers_graph(ggml_backend_vk_context * ctx, ggml_tensor * node){ | |
| std::cerr << "ggml_vk_preallocate_buffers_graph(" << node << ")" << std::endl; | |
| if (ctx->disable || node->backend != GGML_BACKEND_TYPE_GPU) { | |
| return; | |
| } | |
| ggml_tensor_extra_gpu * extra = (ggml_tensor_extra_gpu *) node->extra; | |
| ggml_tensor * src0 = node->src[0]; | |
| ggml_tensor * src1 = node->src[1]; | |
| const bool use_src0 = src0 != nullptr; | |
| const int64_t ne00 = use_src0 ? src0->ne[0] : 0; | |
| const int64_t ne01 = use_src0 ? src0->ne[1] : 0; | |
| const int64_t ne02 = use_src0 ? src0->ne[2] : 0; | |
| const int64_t ne03 = use_src0 ? src0->ne[3] : 0; | |
| const bool use_src1 = src1 != nullptr && node->op != GGML_OP_CPY && node->op != GGML_OP_CONT && node->op != GGML_OP_DUP; | |
| const int64_t ne10 = use_src1 ? src1->ne[0] : 0; | |
| const int64_t ne11 = use_src1 ? src1->ne[1] : 0; | |
| const int64_t ne12 = use_src1 ? src1->ne[2] : 0; | |
| const int64_t ne13 = use_src1 ? src1->ne[3] : 0; | |
| const int64_t ne20 = node->ne[0]; | |
| const int64_t ne21 = node->ne[1]; | |
| const int64_t ne22 = node->ne[2]; | |
| const int64_t ne23 = node->ne[3]; | |
| const ggml_type src0_type = (use_src0 && src0->type == GGML_TYPE_F32) ? src0->type : GGML_TYPE_F16; | |
| const ggml_type src1_type = (use_src1 && src1->type == GGML_TYPE_F32) ? src1->type : GGML_TYPE_F16; | |
| const bool x_non_contig = use_src0 && !ggml_vk_dim01_contiguous(src0); | |
| const bool y_non_contig = use_src1 && !ggml_vk_dim01_contiguous(src1); | |
| const bool y_f32_kernel = use_src1 && src1->type == GGML_TYPE_F32 && !y_non_contig; | |
| bool mmp = (use_src0 && use_src1 && src1_type == GGML_TYPE_F32) ? ggml_vk_get_mul_mat_mat_pipeline(ctx, src0_type, y_non_contig ? GGML_TYPE_F16 : src1->type) != nullptr : false; | |
| const bool qx_needs_dequant = use_src0 && (mmp || x_non_contig); | |
| const bool qy_needs_dequant = use_src1 && ((src1->type != GGML_TYPE_F16 && !y_f32_kernel) || y_non_contig); | |
| int split_k; | |
| if (node->op == GGML_OP_MUL_MAT || node->op == GGML_OP_MUL_MAT_ID) { | |
| split_k = ggml_vk_guess_split_k(ne01, ne11, ne10); | |
| } else { | |
| split_k = 1; | |
| } | |
| const uint32_t x_ne = ne00 * ne01; | |
| const uint32_t y_ne = ne10 * ne11; | |
| const uint32_t d_ne = ne20 * ne21; | |
| const uint64_t x_sz = (use_src0 && qx_needs_dequant) ? ggml_vk_align_size(sizeof(src0_type) * x_ne, ctx->device->properties.limits.minStorageBufferOffsetAlignment) * ne02 * ne03 : 0; | |
| const uint64_t y_sz = (use_src1 && qy_needs_dequant) ? ggml_vk_align_size(sizeof(src1_type) * y_ne, ctx->device->properties.limits.minStorageBufferOffsetAlignment) * ne12 * ne13 : 0; | |
| uint64_t d_sz = ggml_vk_align_size(ggml_type_size(node->type) * d_ne, ctx->device->properties.limits.minStorageBufferOffsetAlignment) * ne22 * ne23; | |
| const uint64_t split_k_size = split_k > 1 ? d_sz * 4 : 0; | |
| if (extra->buffer_gpu.expired()) { | |
| // Workaround for CPU backend BLAS matmul calls | |
| extra->buffer_gpu = ggml_vk_create_buffer_temp(ctx, d_sz); | |
| } | |
| switch (node->op) { | |
| case GGML_OP_REPEAT: | |
| case GGML_OP_GET_ROWS: | |
| case GGML_OP_RESHAPE: | |
| case GGML_OP_VIEW: | |
| case GGML_OP_PERMUTE: | |
| case GGML_OP_TRANSPOSE: | |
| case GGML_OP_ADD: | |
| case GGML_OP_SCALE: | |
| case GGML_OP_SQR: | |
| case GGML_OP_CLAMP: | |
| case GGML_OP_CPY: | |
| case GGML_OP_CONT: | |
| case GGML_OP_DUP: | |
| case GGML_OP_MUL: | |
| case GGML_OP_NORM: | |
| case GGML_OP_RMS_NORM: | |
| case GGML_OP_DIAG_MASK_INF: | |
| case GGML_OP_SOFT_MAX: | |
| case GGML_OP_ROPE: | |
| case GGML_OP_ARGSORT: | |
| break; | |
| case GGML_OP_UNARY: | |
| switch (ggml_get_unary_op(node)) { | |
| case GGML_UNARY_OP_SILU: | |
| case GGML_UNARY_OP_GELU: | |
| case GGML_UNARY_OP_RELU: | |
| break; | |
| default: | |
| return; | |
| } | |
| break; | |
| case GGML_OP_MUL_MAT: | |
| case GGML_OP_MUL_MAT_ID: | |
| if (ctx->prealloc_size_x < x_sz) { | |
| ctx->prealloc_size_x = x_sz; | |
| } | |
| if (ctx->prealloc_size_y < y_sz) { | |
| ctx->prealloc_size_y = y_sz; | |
| } | |
| if (ctx->prealloc_size_split_k < split_k_size) { | |
| ctx->prealloc_size_split_k = split_k_size; | |
| } | |
| if (ctx->staging_size < x_sz + y_sz) { | |
| ctx->staging_size = x_sz + y_sz; | |
| } | |
| break; | |
| default: | |
| return; | |
| } | |
| } | |
| static void ggml_vk_preallocate_buffers(ggml_backend_vk_context * ctx) { | |
| if (ctx->disable) { | |
| return; | |
| } | |
| std::cerr << "ggml_vk_preallocate_buffers(x_size: " << ctx->prealloc_size_x << " y_size: " << ctx->prealloc_size_y << " split_k_size: " << ctx->prealloc_size_split_k << ")" << std::endl; | |
| ctx->staging = ggml_vk_create_buffer_check(ctx, 100ul * 1024ul * 1024ul, | |
| vk::MemoryPropertyFlagBits::eHostVisible | vk::MemoryPropertyFlagBits::eHostCoherent | vk::MemoryPropertyFlagBits::eHostCached, | |
| vk::MemoryPropertyFlagBits::eHostVisible | vk::MemoryPropertyFlagBits::eHostCoherent); | |
| ggml_vk_test_transfer(ctx, 8192 * 1000, false); | |
| ggml_vk_test_transfer(ctx, 8192 * 1000, true); | |
| ggml_vk_test_dequant(ctx, 7680, GGML_TYPE_F32); | |
| ggml_vk_test_dequant(ctx, 7680, GGML_TYPE_Q4_0); | |
| ggml_vk_test_dequant(ctx, 7680, GGML_TYPE_Q4_1); | |
| ggml_vk_test_dequant(ctx, 7680, GGML_TYPE_Q5_0); | |
| ggml_vk_test_dequant(ctx, 7680, GGML_TYPE_Q5_1); | |
| ggml_vk_test_dequant(ctx, 7680, GGML_TYPE_Q8_0); | |
| ggml_vk_test_dequant(ctx, 7680, GGML_TYPE_Q2_K); | |
| ggml_vk_test_dequant(ctx, 7680, GGML_TYPE_Q3_K); | |
| ggml_vk_test_dequant(ctx, 7680, GGML_TYPE_Q4_K); | |
| ggml_vk_test_dequant(ctx, 7680, GGML_TYPE_Q5_K); | |
| ggml_vk_test_dequant(ctx, 7680, GGML_TYPE_Q6_K); | |
| ggml_vk_test_matmul<ggml_fp16_t, ggml_fp16_t>(ctx, 512, 512, 100, 32, 100, 1, 2); | |
| ggml_vk_test_matmul<float, float>(ctx, 128, 512, 512, 2, 100, 1, 0); | |
| ggml_vk_test_matmul<float, float>(ctx, 128, 512, 512, 2, 100, 1, 1); | |
| ggml_vk_test_matmul<float, float>(ctx, 128, 512, 512, 2, 100, 1, 2); | |
| ggml_vk_test_matmul<float, float>(ctx, 128, 512, 512, 2, 100, 4, 0); | |
| ggml_vk_test_matmul<float, float>(ctx, 128, 512, 512, 2, 100, 4, 1); | |
| ggml_vk_test_matmul<float, float>(ctx, 128, 512, 512, 2, 100, 4, 2); | |
| ggml_vk_test_dequant_matmul(ctx, 128, 512, 512, 2, 100, 1, 0, GGML_TYPE_Q4_0); | |
| ggml_vk_test_dequant_matmul(ctx, 128, 512, 512, 2, 100, 1, 1, GGML_TYPE_Q4_0); | |
| ggml_vk_test_dequant_matmul(ctx, 128, 512, 512, 2, 100, 1, 2, GGML_TYPE_Q4_0); | |
| ggml_vk_test_dequant_matmul(ctx, 128, 512, 512, 2, 100, 4, 0, GGML_TYPE_Q4_0); | |
| ggml_vk_test_dequant_matmul(ctx, 128, 512, 512, 2, 100, 4, 1, GGML_TYPE_Q4_0); | |
| ggml_vk_test_dequant_matmul(ctx, 128, 512, 512, 2, 100, 4, 2, GGML_TYPE_Q4_0); | |
| ggml_vk_test_dequant_matmul(ctx, 128, 512, 512, 2, 100, 1, 0, GGML_TYPE_Q4_1); | |
| ggml_vk_test_dequant_matmul(ctx, 128, 512, 512, 2, 100, 1, 1, GGML_TYPE_Q4_1); | |
| ggml_vk_test_dequant_matmul(ctx, 128, 512, 512, 2, 100, 1, 2, GGML_TYPE_Q4_1); | |
| ggml_vk_test_dequant_matmul(ctx, 128, 512, 512, 2, 100, 4, 0, GGML_TYPE_Q4_1); | |
| ggml_vk_test_dequant_matmul(ctx, 128, 512, 512, 2, 100, 4, 1, GGML_TYPE_Q4_1); | |
| ggml_vk_test_dequant_matmul(ctx, 128, 512, 512, 2, 100, 4, 2, GGML_TYPE_Q4_1); | |
| ggml_vk_test_dequant_matmul(ctx, 128, 512, 512, 2, 100, 1, 0, GGML_TYPE_Q5_0); | |
| ggml_vk_test_dequant_matmul(ctx, 128, 512, 512, 2, 100, 1, 1, GGML_TYPE_Q5_0); | |
| ggml_vk_test_dequant_matmul(ctx, 128, 512, 512, 2, 100, 1, 2, GGML_TYPE_Q5_0); | |
| ggml_vk_test_dequant_matmul(ctx, 128, 512, 512, 2, 100, 4, 0, GGML_TYPE_Q5_0); | |
| ggml_vk_test_dequant_matmul(ctx, 128, 512, 512, 2, 100, 4, 1, GGML_TYPE_Q5_0); | |
| ggml_vk_test_dequant_matmul(ctx, 128, 512, 512, 2, 100, 4, 2, GGML_TYPE_Q5_0); | |
| ggml_vk_test_dequant_matmul(ctx, 128, 512, 512, 2, 100, 1, 0, GGML_TYPE_Q5_1); | |
| ggml_vk_test_dequant_matmul(ctx, 128, 512, 512, 2, 100, 1, 1, GGML_TYPE_Q5_1); | |
| ggml_vk_test_dequant_matmul(ctx, 128, 512, 512, 2, 100, 1, 2, GGML_TYPE_Q5_1); | |
| ggml_vk_test_dequant_matmul(ctx, 128, 512, 512, 2, 100, 4, 0, GGML_TYPE_Q5_1); | |
| ggml_vk_test_dequant_matmul(ctx, 128, 512, 512, 2, 100, 4, 1, GGML_TYPE_Q5_1); | |
| ggml_vk_test_dequant_matmul(ctx, 128, 512, 512, 2, 100, 4, 2, GGML_TYPE_Q5_1); | |
| ggml_vk_test_dequant_matmul(ctx, 128, 512, 512, 2, 100, 1, 0, GGML_TYPE_Q8_0); | |
| ggml_vk_test_dequant_matmul(ctx, 128, 512, 512, 2, 100, 1, 1, GGML_TYPE_Q8_0); | |
| ggml_vk_test_dequant_matmul(ctx, 128, 512, 512, 2, 100, 1, 2, GGML_TYPE_Q8_0); | |
| ggml_vk_test_dequant_matmul(ctx, 128, 512, 512, 2, 100, 4, 0, GGML_TYPE_Q8_0); | |
| ggml_vk_test_dequant_matmul(ctx, 128, 512, 512, 2, 100, 4, 1, GGML_TYPE_Q8_0); | |
| ggml_vk_test_dequant_matmul(ctx, 128, 512, 512, 2, 100, 4, 2, GGML_TYPE_Q8_0); | |
| ggml_vk_test_dequant_matmul(ctx, 128, 512, 512, 2, 100, 1, 0, GGML_TYPE_Q2_K); | |
| ggml_vk_test_dequant_matmul(ctx, 128, 512, 512, 2, 100, 1, 1, GGML_TYPE_Q2_K); | |
| ggml_vk_test_dequant_matmul(ctx, 128, 512, 512, 2, 100, 1, 2, GGML_TYPE_Q2_K); | |
| ggml_vk_test_dequant_matmul(ctx, 128, 512, 512, 2, 100, 4, 0, GGML_TYPE_Q2_K); | |
| ggml_vk_test_dequant_matmul(ctx, 128, 512, 512, 2, 100, 4, 1, GGML_TYPE_Q2_K); | |
| ggml_vk_test_dequant_matmul(ctx, 128, 512, 512, 2, 100, 4, 2, GGML_TYPE_Q2_K); | |
| ggml_vk_test_dequant_matmul(ctx, 128, 512, 512, 2, 100, 1, 0, GGML_TYPE_Q3_K); | |
| ggml_vk_test_dequant_matmul(ctx, 128, 512, 512, 2, 100, 1, 1, GGML_TYPE_Q3_K); | |
| ggml_vk_test_dequant_matmul(ctx, 128, 512, 512, 2, 100, 1, 2, GGML_TYPE_Q3_K); | |
| ggml_vk_test_dequant_matmul(ctx, 128, 512, 512, 2, 100, 4, 0, GGML_TYPE_Q3_K); | |
| ggml_vk_test_dequant_matmul(ctx, 128, 512, 512, 2, 100, 4, 1, GGML_TYPE_Q3_K); | |
| ggml_vk_test_dequant_matmul(ctx, 128, 512, 512, 2, 100, 4, 2, GGML_TYPE_Q3_K); | |
| ggml_vk_test_dequant_matmul(ctx, 128, 512, 512, 2, 100, 1, 0, GGML_TYPE_Q4_K); | |
| ggml_vk_test_dequant_matmul(ctx, 128, 512, 512, 2, 100, 1, 1, GGML_TYPE_Q4_K); | |
| ggml_vk_test_dequant_matmul(ctx, 128, 512, 512, 2, 100, 1, 2, GGML_TYPE_Q4_K); | |
| ggml_vk_test_dequant_matmul(ctx, 128, 512, 512, 2, 100, 4, 0, GGML_TYPE_Q4_K); | |
| ggml_vk_test_dequant_matmul(ctx, 128, 512, 512, 2, 100, 4, 1, GGML_TYPE_Q4_K); | |
| ggml_vk_test_dequant_matmul(ctx, 128, 512, 512, 2, 100, 4, 2, GGML_TYPE_Q4_K); | |
| ggml_vk_test_dequant_matmul(ctx, 128, 512, 512, 2, 100, 1, 0, GGML_TYPE_Q5_K); | |
| ggml_vk_test_dequant_matmul(ctx, 128, 512, 512, 2, 100, 1, 1, GGML_TYPE_Q5_K); | |
| ggml_vk_test_dequant_matmul(ctx, 128, 512, 512, 2, 100, 1, 2, GGML_TYPE_Q5_K); | |
| ggml_vk_test_dequant_matmul(ctx, 128, 512, 512, 2, 100, 4, 0, GGML_TYPE_Q5_K); | |
| ggml_vk_test_dequant_matmul(ctx, 128, 512, 512, 2, 100, 4, 1, GGML_TYPE_Q5_K); | |
| ggml_vk_test_dequant_matmul(ctx, 128, 512, 512, 2, 100, 4, 2, GGML_TYPE_Q5_K); | |
| ggml_vk_test_dequant_matmul(ctx, 128, 512, 512, 2, 100, 1, 0, GGML_TYPE_Q6_K); | |
| ggml_vk_test_dequant_matmul(ctx, 128, 512, 512, 2, 100, 1, 1, GGML_TYPE_Q6_K); | |
| ggml_vk_test_dequant_matmul(ctx, 128, 512, 512, 2, 100, 1, 2, GGML_TYPE_Q6_K); | |
| ggml_vk_test_dequant_matmul(ctx, 128, 512, 512, 2, 100, 4, 0, GGML_TYPE_Q6_K); | |
| ggml_vk_test_dequant_matmul(ctx, 128, 512, 512, 2, 100, 4, 1, GGML_TYPE_Q6_K); | |
| ggml_vk_test_dequant_matmul(ctx, 128, 512, 512, 2, 100, 4, 2, GGML_TYPE_Q6_K); | |
| std::cerr << std::endl; | |
| const std::vector<size_t> vals { | |
| 8, 8, 8, | |
| 100, 46, 576, | |
| 623, 111, 128, | |
| 100, 46, 558, | |
| 512, 1, 256, | |
| 128, 110, 622, | |
| 511, 511, 127, | |
| 511, 511, 7, | |
| 511, 511, 17, | |
| 49, 49, 128, | |
| 128, 49, 49, | |
| 4096, 49, 4096, | |
| 11008, 49, 4096, | |
| 4096, 49, 11008, | |
| 32000, 49, 4096, | |
| 512, 512, 128, | |
| 128, 512, 512, | |
| 4096, 512, 4096, | |
| 11008, 512, 4096, | |
| 4096, 512, 11008, | |
| 32000, 512, 4096, | |
| }; | |
| const size_t num_it = 1; | |
| for (size_t i = 0; i < vals.size(); i += 3) { | |
| ggml_vk_test_matmul<ggml_fp16_t, float>(ctx, vals[i], vals[i + 1], vals[i + 2], 2, num_it, 1, 0); | |
| ggml_vk_test_matmul<ggml_fp16_t, float>(ctx, vals[i], vals[i + 1], vals[i + 2], 2, num_it, 1, 1); | |
| ggml_vk_test_matmul<ggml_fp16_t, float>(ctx, vals[i], vals[i + 1], vals[i + 2], 2, num_it, 1, 2); | |
| ggml_vk_test_matmul<ggml_fp16_t, float>(ctx, vals[i], vals[i + 1], vals[i + 2], 2, num_it, 4, 0); | |
| ggml_vk_test_matmul<ggml_fp16_t, float>(ctx, vals[i], vals[i + 1], vals[i + 2], 2, num_it, 4, 1); | |
| ggml_vk_test_matmul<ggml_fp16_t, float>(ctx, vals[i], vals[i + 1], vals[i + 2], 2, num_it, 4, 2); | |
| std::cerr << std::endl; | |
| } | |
| GGML_ASSERT(false); | |
| if (ctx->prealloc_x == nullptr || (ctx->prealloc_size_x > 0 && ctx->prealloc_x->size < ctx->prealloc_size_x)) { | |
| // Resize buffer | |
| if (ctx->prealloc_x != nullptr) { | |
| ggml_vk_destroy_buffer(ctx->prealloc_x); | |
| } | |
| ctx->prealloc_x = ggml_vk_create_buffer_device(ctx, ctx->prealloc_size_x); | |
| } | |
| if (ctx->prealloc_y == nullptr || (ctx->prealloc_size_y > 0 && ctx->prealloc_y->size < ctx->prealloc_size_y)) { | |
| // Resize buffer | |
| if (ctx->prealloc_y != nullptr) { | |
| ggml_vk_destroy_buffer(ctx->prealloc_y); | |
| } | |
| ctx->prealloc_y = ggml_vk_create_buffer_device(ctx, ctx->prealloc_size_y); | |
| } | |
| if (ctx->prealloc_split_k == nullptr || (ctx->prealloc_size_split_k > 0 && ctx->prealloc_split_k->size < ctx->prealloc_size_split_k)) { | |
| // Resize buffer | |
| if (ctx->prealloc_split_k != nullptr) { | |
| ggml_vk_destroy_buffer(ctx->prealloc_split_k); | |
| } | |
| ctx->prealloc_split_k = ggml_vk_create_buffer_device(ctx, ctx->prealloc_size_split_k); | |
| } | |
| if (ctx->staging == nullptr || (ctx->staging_size > 0 && ctx->staging->size < ctx->staging_size)) { | |
| // Resize buffer | |
| if (ctx->staging != nullptr) { | |
| ggml_vk_destroy_buffer(ctx->staging); | |
| } | |
| ctx->staging = ggml_vk_create_buffer_check(ctx, ctx->staging_size, | |
| vk::MemoryPropertyFlagBits::eHostVisible | vk::MemoryPropertyFlagBits::eHostCoherent | vk::MemoryPropertyFlagBits::eHostCached, | |
| vk::MemoryPropertyFlagBits::eHostVisible | vk::MemoryPropertyFlagBits::eHostCoherent); | |
| } | |
| } | |
| static void ggml_vk_build_graph(ggml_backend_vk_context * ctx, ggml_tensor * node, bool last_node){ | |
| if (ctx->disable || node->backend != GGML_BACKEND_TYPE_GPU || ggml_is_empty(node)) { | |
| return; | |
| } | |
| std::cerr << "ggml_vk_build_graph(" << node << ", " << ggml_op_name(node->op) << ")" << std::endl; | |
| ctx->semaphore_idx = 0; | |
| ctx->staging_offset = 0; | |
| const ggml_tensor * src0 = node->src[0]; | |
| const ggml_tensor * src1 = node->src[1]; | |
| const ggml_tensor * src2 = node->src[2]; | |
| ggml_tensor_extra_gpu * extra = (ggml_tensor_extra_gpu *) node->extra; | |
| switch (node->op) { | |
| case GGML_OP_UNARY: | |
| switch (ggml_get_unary_op(node)) { | |
| case GGML_UNARY_OP_SILU: | |
| case GGML_UNARY_OP_GELU: | |
| case GGML_UNARY_OP_RELU: | |
| break; | |
| default: | |
| return; | |
| } | |
| break; | |
| case GGML_OP_REPEAT: | |
| case GGML_OP_GET_ROWS: | |
| case GGML_OP_ADD: | |
| case GGML_OP_MUL: | |
| case GGML_OP_SCALE: | |
| case GGML_OP_SQR: | |
| case GGML_OP_CLAMP: | |
| case GGML_OP_CPY: | |
| case GGML_OP_CONT: | |
| case GGML_OP_DUP: | |
| case GGML_OP_RESHAPE: | |
| case GGML_OP_VIEW: | |
| case GGML_OP_PERMUTE: | |
| case GGML_OP_TRANSPOSE: | |
| case GGML_OP_NORM: | |
| case GGML_OP_RMS_NORM: | |
| case GGML_OP_DIAG_MASK_INF: | |
| case GGML_OP_SOFT_MAX: | |
| case GGML_OP_ROPE: | |
| case GGML_OP_MUL_MAT: | |
| case GGML_OP_MUL_MAT_ID: | |
| case GGML_OP_NONE: | |
| case GGML_OP_ARGSORT: | |
| break; | |
| default: | |
| std::cerr << "ggml_vulkan: Error: Missing op: " << ggml_op_name(node->op) << std::endl; | |
| GGML_ASSERT(false); | |
| return; | |
| } | |
| if (ctx->compute_ctx == nullptr) { | |
| ctx->compute_ctx = ggml_vk_create_context(ctx, ctx->device->compute_queue); | |
| ggml_vk_ctx_begin(ctx, ctx->compute_ctx); | |
| } | |
| switch (node->op) { | |
| case GGML_OP_REPEAT: | |
| ggml_vk_repeat(ctx, ctx->compute_ctx, src0, src1, node); | |
| break; | |
| case GGML_OP_GET_ROWS: | |
| ggml_vk_get_rows(ctx, ctx->compute_ctx, src0, src1, node); | |
| break; | |
| case GGML_OP_ADD: | |
| ggml_vk_add(ctx, ctx->compute_ctx, src0, src1, node); | |
| break; | |
| case GGML_OP_MUL: | |
| ggml_vk_mul(ctx, ctx->compute_ctx, src0, src1, node); | |
| break; | |
| case GGML_OP_SCALE: | |
| ggml_vk_scale(ctx, ctx->compute_ctx, src0, node); | |
| break; | |
| case GGML_OP_SQR: | |
| ggml_vk_sqr(ctx, ctx->compute_ctx, src0, node); | |
| break; | |
| case GGML_OP_CLAMP: | |
| ggml_vk_clamp(ctx, ctx->compute_ctx, src0, node); | |
| break; | |
| case GGML_OP_CPY: | |
| case GGML_OP_CONT: | |
| case GGML_OP_DUP: | |
| ggml_vk_cpy(ctx, ctx->compute_ctx, src0, node); | |
| break; | |
| case GGML_OP_RESHAPE: | |
| case GGML_OP_VIEW: | |
| case GGML_OP_PERMUTE: | |
| case GGML_OP_TRANSPOSE: | |
| case GGML_OP_NONE: | |
| break; | |
| case GGML_OP_NORM: | |
| ggml_vk_norm(ctx, ctx->compute_ctx, src0, node); | |
| break; | |
| case GGML_OP_RMS_NORM: | |
| ggml_vk_rms_norm(ctx, ctx->compute_ctx, src0, node); | |
| break; | |
| case GGML_OP_UNARY: | |
| switch (ggml_get_unary_op(node)) { | |
| case GGML_UNARY_OP_SILU: | |
| case GGML_UNARY_OP_GELU: | |
| case GGML_UNARY_OP_RELU: | |
| ggml_vk_unary(ctx, ctx->compute_ctx, src0, node); | |
| break; | |
| default: | |
| return; | |
| } | |
| break; | |
| case GGML_OP_DIAG_MASK_INF: | |
| ggml_vk_diag_mask_inf(ctx, ctx->compute_ctx, src0, node); | |
| break; | |
| case GGML_OP_SOFT_MAX: | |
| ggml_vk_soft_max(ctx, ctx->compute_ctx, src0, src1, src2, node); | |
| break; | |
| case GGML_OP_ROPE: | |
| ggml_vk_rope(ctx, ctx->compute_ctx, src0, src1, node); | |
| break; | |
| case GGML_OP_ARGSORT: | |
| ggml_vk_argsort(ctx, ctx->compute_ctx, src0, node); | |
| break; | |
| case GGML_OP_MUL_MAT: | |
| ggml_vk_mul_mat(ctx, ctx->compute_ctx, src0, src1, node); | |
| break; | |
| case GGML_OP_MUL_MAT_ID: | |
| //ggml_vk_mul_mat_id(ctx, ctx->compute_ctx, src0, src1, node); | |
| std::cerr << "ggml_vulkan: GGML_OP_MUL_MAT_ID not implemented yet." << std::endl; | |
| GGML_ASSERT(false); | |
| break; | |
| default: | |
| return; | |
| } | |
| extra->ready = true; | |
| extra->ctx_idx = ctx->compute_ctx->idx; | |
| // Force context reset on each node so that each tensor ends up in its own context | |
| // and can be run and compared to its CPU equivalent separately | |
| last_node = true; | |
| if (node->backend == GGML_BACKEND_TYPE_CPU || last_node) { | |
| ggml_vk_ctx_end(ctx->compute_ctx); | |
| ctx->compute_ctx->exit_tensor = node; | |
| ctx->compute_ctx = nullptr; | |
| } | |
| } | |
| static bool ggml_vk_compute_forward(ggml_backend_vk_context * ctx, ggml_compute_params * params, ggml_tensor * tensor){ | |
| if (ctx->disable) { | |
| return false; | |
| } | |
| ggml_tensor_extra_gpu * extra = nullptr; | |
| switch (tensor->op) { | |
| case GGML_OP_ADD: | |
| case GGML_OP_GET_ROWS: | |
| case GGML_OP_MUL: | |
| case GGML_OP_SCALE: | |
| case GGML_OP_SQR: | |
| case GGML_OP_CLAMP: | |
| case GGML_OP_CPY: | |
| case GGML_OP_CONT: | |
| case GGML_OP_DUP: | |
| case GGML_OP_NORM: | |
| case GGML_OP_RMS_NORM: | |
| case GGML_OP_DIAG_MASK_INF: | |
| case GGML_OP_SOFT_MAX: | |
| case GGML_OP_ROPE: | |
| case GGML_OP_RESHAPE: | |
| case GGML_OP_VIEW: | |
| case GGML_OP_PERMUTE: | |
| case GGML_OP_TRANSPOSE: | |
| case GGML_OP_NONE: | |
| case GGML_OP_ARGSORT: | |
| extra = (ggml_tensor_extra_gpu *) tensor->extra; | |
| break; | |
| case GGML_OP_UNARY: | |
| switch (ggml_get_unary_op(tensor)) { | |
| case GGML_UNARY_OP_SILU: | |
| case GGML_UNARY_OP_GELU: | |
| case GGML_UNARY_OP_RELU: | |
| extra = (ggml_tensor_extra_gpu *) tensor->extra; | |
| break; | |
| default: | |
| return false; | |
| } | |
| break; | |
| case GGML_OP_MUL_MAT: | |
| case GGML_OP_MUL_MAT_ID: | |
| extra = (ggml_tensor_extra_gpu *) tensor->extra; | |
| break; | |
| default: | |
| return false; | |
| } | |
| if (extra == nullptr) { | |
| return false; | |
| } | |
| if (params->ith != 0) { | |
| return true; | |
| } | |
| if (params->type == GGML_TASK_TYPE_INIT || params->type == GGML_TASK_TYPE_FINALIZE) { | |
| return true; | |
| } | |
| std::cerr << "ggml_vk_compute_forward(" << tensor << ", name=" << tensor->name << ", op=" << ggml_op_name(tensor->op) << ", type=" << tensor->type << ", backend=" << tensor->backend << ", ne0=" << tensor->ne[0] << ", ne1=" << tensor->ne[1] << ", ne2=" << tensor->ne[2] << ", ne3=" << tensor->ne[3] << ", nb0=" << tensor->nb[0] << ", nb1=" << tensor->nb[1] << ", nb2=" << tensor->nb[2] << ", nb3=" << tensor->nb[3] << ", view_src=" << tensor->view_src << ", view_offs=" << tensor->view_offs << ")" << std::endl; | |
| ggml_vk_check_results_0(ctx, params, tensor); | |
| GGML_ASSERT(extra->ready); | |
| vk_context& subctx = ctx->gc.contexts[extra->ctx_idx]; | |
| // Only run if ctx hasn't been submitted yet | |
| if (!subctx.seqs.empty()) { | |
| // Do staging buffer copies | |
| for (auto& cpy : subctx.in_memcpys) { | |
| memcpy(cpy.dst, cpy.src, cpy.n); | |
| } | |
| ggml_vk_submit(&subctx, ctx->fence); | |
| } | |
| if (tensor == subctx.exit_tensor) { | |
| VK_CHECK(ctx->device->device.waitForFences({ ctx->fence }, true, UINT64_MAX), "ggml_vk_compute_forward waitForFences"); | |
| ctx->device->device.resetFences({ ctx->fence }); | |
| // Do staging buffer copies | |
| for (auto& cpy : subctx.out_memcpys) { | |
| memcpy(cpy.dst, cpy.src, cpy.n); | |
| } | |
| subctx.in_memcpys.clear(); | |
| subctx.out_memcpys.clear(); | |
| } | |
| extra->ready = false; | |
| return true; | |
| } | |
| // Clean up after graph processing is done | |
| static void ggml_vk_graph_cleanup(ggml_backend_vk_context * ctx) { | |
| if (ctx->disable) { | |
| return; | |
| } | |
| std::cerr << "ggml_vk_graph_cleanup()" << std::endl; | |
| for (auto& buffer : ctx->gc.temp_buffers) { | |
| ggml_vk_pool_free(ctx, buffer); | |
| } | |
| ctx->gc.temp_buffers.clear(); | |
| for (auto& pipeline : ctx->device->pipelines) { | |
| if (pipeline.expired()) { | |
| continue; | |
| } | |
| vk_pipeline pl = pipeline.lock(); | |
| ggml_pipeline_cleanup(pl); | |
| } | |
| ggml_vk_queue_cleanup(ctx, ctx->device->compute_queue); | |
| ggml_vk_queue_cleanup(ctx, ctx->device->transfer_queue); | |
| for (size_t i = 0; i < ctx->gc.semaphores.size(); i++) { | |
| ctx->device->device.destroySemaphore({ ctx->gc.semaphores[i].s }); | |
| } | |
| ctx->gc.semaphores.clear(); | |
| for (size_t i = 0; i < ctx->gc.tl_semaphores.size(); i++) { | |
| ctx->device->device.destroySemaphore({ ctx->gc.tl_semaphores[i].s }); | |
| } | |
| ctx->gc.tl_semaphores.clear(); | |
| ctx->semaphore_idx = 0; | |
| ctx->event_idx = 0; | |
| for (auto& event : ctx->gc.events) { | |
| ctx->device->device.resetEvent(event); | |
| } | |
| ctx->staging_offset = 0; | |
| ctx->compute_ctx = nullptr; | |
| ctx->transfer_ctx = nullptr; | |
| ctx->gc.contexts.clear(); | |
| } | |
| // Clean up on backend free | |
| static void ggml_vk_cleanup(ggml_backend_vk_context * ctx) { | |
| std::cerr << "ggml_vk_cleanup(" << ctx->idx << ")" << std::endl; | |
| ggml_vk_graph_cleanup(ctx); | |
| ggml_vk_destroy_buffer(ctx->prealloc_x); | |
| ggml_vk_destroy_buffer(ctx->prealloc_y); | |
| ggml_vk_destroy_buffer(ctx->prealloc_split_k); | |
| ggml_vk_destroy_buffer(ctx->staging); | |
| ggml_vk_destroy_buffer(ctx->sync_staging); | |
| for (auto& buffer : ctx->buffer_pool) { | |
| ggml_vk_destroy_buffer(buffer); | |
| } | |
| ctx->prealloc_size_x = 0; | |
| ctx->prealloc_size_y = 0; | |
| ctx->prealloc_size_split_k = 0; | |
| ctx->staging_size = 0; | |
| for (auto& event : ctx->gc.events) { | |
| ctx->device->device.destroyEvent(event); | |
| } | |
| ctx->gc.events.clear(); | |
| ctx->device->device.destroyFence(ctx->fence); | |
| } | |
| GGML_CALL static int ggml_vk_get_device_count() { | |
| ggml_vk_instance_init(); | |
| return vk_instance.device_indices.size(); | |
| } | |
| GGML_CALL static void ggml_vk_get_device_description(int device, char * description, size_t description_size) { | |
| ggml_vk_instance_init(); | |
| std::vector<vk::PhysicalDevice> devices = vk_instance.instance.enumeratePhysicalDevices(); | |
| vk::PhysicalDeviceProperties props; | |
| devices[device].getProperties(&props); | |
| snprintf(description, description_size, "%s", props.deviceName.data()); | |
| } | |
| // backend interface | |
| // device backend | |
| static void * const vk_ptr_base = (void *)(uintptr_t) 0x1000; // NOLINT | |
| struct ggml_backend_vk_buffer_context { | |
| ggml_backend_vk_context * ctx; | |
| vk_buffer dev_buffer; | |
| ggml_tensor_extra_gpu * temp_tensor_extras = nullptr; | |
| size_t temp_tensor_extra_index = 0; | |
| std::string name; | |
| ggml_backend_vk_buffer_context(ggml_backend_vk_context * ctx, vk_buffer&& dev_buffer, std::string& name) : | |
| ctx(ctx), | |
| dev_buffer(dev_buffer), | |
| name(name) { | |
| } | |
| ~ggml_backend_vk_buffer_context() { | |
| ggml_vk_destroy_buffer(dev_buffer); | |
| delete[] temp_tensor_extras; | |
| } | |
| ggml_tensor_extra_gpu * ggml_vk_alloc_temp_tensor_extra() { | |
| if (temp_tensor_extras == nullptr) { | |
| temp_tensor_extras = new ggml_tensor_extra_gpu[GGML_VK_MAX_NODES]; | |
| } | |
| size_t alloc_index = temp_tensor_extra_index; | |
| temp_tensor_extra_index = (temp_tensor_extra_index + 1) % GGML_VK_MAX_NODES; | |
| ggml_tensor_extra_gpu * extra = &temp_tensor_extras[alloc_index]; | |
| extra->reset(); | |
| return extra; | |
| } | |
| }; | |
| GGML_CALL static const char * ggml_backend_vk_buffer_get_name(ggml_backend_buffer_t buffer) { | |
| ggml_backend_vk_buffer_context * ctx = (ggml_backend_vk_buffer_context *)buffer->context; | |
| return ctx->name.c_str(); | |
| } | |
| GGML_CALL static bool ggml_backend_buffer_is_vk(ggml_backend_buffer_t buffer) { | |
| return buffer->iface.get_name == ggml_backend_vk_buffer_get_name; | |
| } | |
| GGML_CALL static void ggml_backend_vk_buffer_free_buffer(ggml_backend_buffer_t buffer) { | |
| std::cerr << "ggml_backend_vk_buffer_free_buffer()" << std::endl; | |
| ggml_backend_vk_buffer_context * ctx = (ggml_backend_vk_buffer_context *)buffer->context; | |
| ggml_vk_destroy_buffer(ctx->dev_buffer); | |
| delete ctx; | |
| } | |
| GGML_CALL static void * ggml_backend_vk_buffer_get_base(ggml_backend_buffer_t buffer) { | |
| return vk_ptr_base; | |
| UNUSED(buffer); | |
| } | |
| GGML_CALL static void ggml_backend_vk_buffer_init_tensor(ggml_backend_buffer_t buffer, ggml_tensor * tensor) { | |
| std::cerr << "ggml_backend_vk_buffer_init_tensor(" << buffer << " (" << buffer->context << "), " << tensor << ")" << std::endl; | |
| ggml_backend_vk_buffer_context * ctx = (ggml_backend_vk_buffer_context *)buffer->context; | |
| ggml_tensor_extra_gpu * extra = ctx->ggml_vk_alloc_temp_tensor_extra(); | |
| if (tensor->view_src != nullptr && tensor->view_src->extra != nullptr) { | |
| GGML_ASSERT(tensor->view_src->buffer->buft == buffer->buft); | |
| ggml_tensor_extra_gpu * extra_view = (ggml_tensor_extra_gpu *) tensor->view_src->extra; | |
| extra->buffer_gpu = extra_view->buffer_gpu; | |
| extra->offset = extra_view->offset + tensor->view_offs; | |
| } else { | |
| extra->buffer_gpu = ctx->dev_buffer; | |
| extra->offset = (uint8_t *) tensor->data - (uint8_t *) vk_ptr_base; | |
| } | |
| tensor->backend = GGML_BACKEND_TYPE_GPU; | |
| tensor->extra = extra; | |
| } | |
| GGML_CALL static void ggml_backend_vk_buffer_set_tensor(ggml_backend_buffer_t buffer, ggml_tensor * tensor, const void * data, size_t offset, size_t size) { | |
| std::cerr << "ggml_backend_vk_buffer_set_tensor(" << buffer << ", " << tensor << ", " << data << ", " << offset << ", " << size << ")" << std::endl; | |
| GGML_ASSERT(tensor->backend == GGML_BACKEND_TYPE_GPU); | |
| ggml_backend_vk_buffer_context * ctx = (ggml_backend_vk_buffer_context *)buffer->context; | |
| ggml_tensor_extra_gpu * extra = (ggml_tensor_extra_gpu *) tensor->extra; | |
| vk_buffer buf = extra->buffer_gpu.lock(); | |
| ggml_vk_buffer_write(ctx->ctx, buf, extra->offset + offset, data, size); | |
| } | |
| GGML_CALL static void ggml_backend_vk_buffer_get_tensor(ggml_backend_buffer_t buffer, const ggml_tensor * tensor, void * data, size_t offset, size_t size) { | |
| std::cerr << "ggml_backend_vk_buffer_get_tensor(" << buffer << ", " << tensor << ", " << data << ", " << offset << ", " << size << ")" << std::endl; | |
| GGML_ASSERT(tensor->backend == GGML_BACKEND_TYPE_GPU); | |
| ggml_backend_vk_buffer_context * ctx = (ggml_backend_vk_buffer_context *)buffer->context; | |
| ggml_tensor_extra_gpu * extra = (ggml_tensor_extra_gpu *) tensor->extra; | |
| vk_buffer buf = extra->buffer_gpu.lock(); | |
| ggml_vk_buffer_read(ctx->ctx, buf, extra->offset + offset, data, size); | |
| } | |
| GGML_CALL static bool ggml_backend_vk_buffer_cpy_tensor(ggml_backend_buffer_t buffer, const ggml_tensor * src, ggml_tensor * dst) { | |
| if (ggml_backend_buffer_is_vk(src->buffer)) { | |
| ggml_tensor_extra_gpu * src_extra = (ggml_tensor_extra_gpu *) src->extra; | |
| ggml_tensor_extra_gpu * dst_extra = (ggml_tensor_extra_gpu *) dst->extra; | |
| vk_buffer src_buf = src_extra->buffer_gpu.lock(); | |
| vk_buffer dst_buf = dst_extra->buffer_gpu.lock(); | |
| ggml_vk_buffer_copy(dst_buf, dst_extra->offset, src_buf, src_extra->offset, ggml_nbytes(src)); | |
| return true; | |
| } | |
| return false; | |
| UNUSED(buffer); | |
| } | |
| GGML_CALL static void ggml_backend_vk_buffer_clear(ggml_backend_buffer_t buffer, uint8_t value) { | |
| ggml_backend_vk_buffer_context * ctx = (ggml_backend_vk_buffer_context *)buffer->context; | |
| ggml_vk_buffer_memset(ctx->ctx, ctx->dev_buffer, 0, value, buffer->size); | |
| } | |
| static ggml_backend_buffer_i ggml_backend_vk_buffer_interface = { | |
| /* .get_name = */ ggml_backend_vk_buffer_get_name, | |
| /* .free_buffer = */ ggml_backend_vk_buffer_free_buffer, | |
| /* .get_base = */ ggml_backend_vk_buffer_get_base, | |
| /* .init_tensor = */ ggml_backend_vk_buffer_init_tensor, | |
| /* .set_tensor = */ ggml_backend_vk_buffer_set_tensor, | |
| /* .get_tensor = */ ggml_backend_vk_buffer_get_tensor, | |
| /* .cpy_tensor = */ ggml_backend_vk_buffer_cpy_tensor, | |
| /* .clear = */ ggml_backend_vk_buffer_clear, | |
| /* .reset = */ NULL, | |
| }; | |
| // vk buffer type | |
| struct ggml_backend_vk_buffer_type_context { | |
| std::string name; | |
| ggml_backend_vk_context * ctx; | |
| }; | |
| GGML_CALL static const char * ggml_backend_vk_buffer_type_name(ggml_backend_buffer_type_t buft) { | |
| ggml_backend_vk_buffer_type_context * ctx = (ggml_backend_vk_buffer_type_context *)buft->context; | |
| return ctx->name.c_str(); | |
| } | |
| GGML_CALL static ggml_backend_buffer_t ggml_backend_vk_buffer_type_alloc_buffer(ggml_backend_buffer_type_t buft, size_t size) { | |
| std::cerr << "ggml_backend_vk_buffer_type_alloc_buffer(" << size << ")" << std::endl; | |
| ggml_backend_vk_buffer_type_context * ctx = (ggml_backend_vk_buffer_type_context *) buft->context; | |
| vk_buffer dev_buffer = ggml_vk_create_buffer_device(ctx->ctx, size); | |
| ggml_backend_vk_buffer_context * bufctx = new ggml_backend_vk_buffer_context(ctx->ctx, std::move(dev_buffer), ctx->name); | |
| return ggml_backend_buffer_init(buft, ggml_backend_vk_buffer_interface, bufctx, size); | |
| } | |
| GGML_CALL static size_t ggml_backend_vk_buffer_type_get_alignment(ggml_backend_buffer_type_t buft) { | |
| ggml_backend_vk_buffer_type_context * ctx = (ggml_backend_vk_buffer_type_context *) buft->context; | |
| return ctx->ctx->device->properties.limits.minStorageBufferOffsetAlignment; | |
| } | |
| GGML_CALL static size_t ggml_backend_vk_buffer_type_get_max_size(ggml_backend_buffer_type_t buft) { | |
| ggml_backend_vk_buffer_type_context * ctx = (ggml_backend_vk_buffer_type_context *) buft->context; | |
| return ctx->ctx->device->max_memory_allocation_size; | |
| } | |
| GGML_CALL static size_t ggml_backend_vk_buffer_type_get_alloc_size(ggml_backend_buffer_type_t buft, const ggml_tensor * tensor) { | |
| return ggml_nbytes(tensor); | |
| UNUSED(buft); | |
| } | |
| GGML_CALL static bool ggml_backend_vk_buffer_type_supports_backend(ggml_backend_buffer_type_t buft, ggml_backend_t backend) { | |
| if (!ggml_backend_is_vk(backend)) { | |
| return false; | |
| } | |
| ggml_backend_vk_buffer_type_context * buft_ctx = (ggml_backend_vk_buffer_type_context *)buft->context; | |
| ggml_backend_vk_context * ctx = (ggml_backend_vk_context *)backend->context; | |
| return buft_ctx->ctx->idx == ctx->idx; | |
| } | |
| static ggml_backend_buffer_type_i ggml_backend_vk_buffer_type_interface = { | |
| /* .get_name = */ ggml_backend_vk_buffer_type_name, | |
| /* .alloc_buffer = */ ggml_backend_vk_buffer_type_alloc_buffer, | |
| /* .get_alignment = */ ggml_backend_vk_buffer_type_get_alignment, | |
| /* .get_max_size = */ ggml_backend_vk_buffer_type_get_max_size, | |
| /* .get_alloc_size = */ ggml_backend_vk_buffer_type_get_alloc_size, | |
| /* .supports_backend = */ ggml_backend_vk_buffer_type_supports_backend, | |
| /* .is_host = */ NULL, | |
| }; | |
| GGML_CALL ggml_backend_buffer_type_t ggml_backend_vk_buffer_type(size_t dev_num) { | |
| std::cerr << "ggml_backend_vk_buffer_type(" << dev_num << ")" << std::endl; | |
| GGML_ASSERT(dev_num < vk_instance.device_indices.size()); | |
| ggml_backend_vk_init(dev_num); | |
| return &vk_instance.buffer_types[dev_num]; | |
| } | |
| // host buffer type | |
| GGML_CALL static const char * ggml_backend_vk_host_buffer_type_name(ggml_backend_buffer_type_t buft) { | |
| return GGML_VK_NAME "_Host"; | |
| UNUSED(buft); | |
| } | |
| GGML_CALL static const char * ggml_backend_vk_host_buffer_name(ggml_backend_buffer_t buffer) { | |
| return GGML_VK_NAME "_Host"; | |
| UNUSED(buffer); | |
| } | |
| GGML_CALL static void ggml_backend_vk_host_buffer_free_buffer(ggml_backend_buffer_t buffer) { | |
| std::cerr << "ggml_backend_vk_host_buffer_free_buffer()" << std::endl; | |
| ggml_vk_host_free(&vk_instance.contexts[0], buffer->context); | |
| } | |
| GGML_CALL static ggml_backend_buffer_t ggml_backend_vk_host_buffer_type_alloc_buffer(ggml_backend_buffer_type_t buft, size_t size) { | |
| std::cerr << "ggml_backend_vk_host_buffer_type_alloc_buffer(" << size << ")" << std::endl; | |
| void * ptr = nullptr; | |
| try { | |
| ptr = ggml_vk_host_malloc(&vk_instance.contexts[0], size); | |
| } catch (vk::SystemError& e) { | |
| std::cerr << "ggml_vulkan: Failed to allocate pinned memory." << std::endl; | |
| std::cerr << "ggml_vulkan: " << e.what() << std::endl; | |
| // fallback to cpu buffer | |
| return ggml_backend_buft_alloc_buffer(ggml_backend_cpu_buffer_type(), size); | |
| } | |
| ggml_backend_buffer_t buffer = ggml_backend_cpu_buffer_from_ptr(ptr, size); | |
| buffer->buft = buft; | |
| buffer->iface.get_name = ggml_backend_vk_host_buffer_name; | |
| buffer->iface.free_buffer = ggml_backend_vk_host_buffer_free_buffer; | |
| return buffer; | |
| } | |
| GGML_CALL static size_t ggml_backend_vk_host_buffer_type_get_alignment(ggml_backend_buffer_type_t buft) { | |
| return vk_instance.contexts[0].device->properties.limits.minMemoryMapAlignment; | |
| UNUSED(buft); | |
| } | |
| GGML_CALL ggml_backend_buffer_type_t ggml_backend_vk_host_buffer_type() { | |
| static struct ggml_backend_buffer_type ggml_backend_vk_buffer_type_host = { | |
| /* .iface = */ { | |
| /* .get_name = */ ggml_backend_vk_host_buffer_type_name, | |
| /* .alloc_buffer = */ ggml_backend_vk_host_buffer_type_alloc_buffer, | |
| /* .get_alignment = */ ggml_backend_vk_host_buffer_type_get_alignment, | |
| /* .get_max_size = */ NULL, // defaults to SIZE_MAX | |
| /* .get_alloc_size = */ ggml_backend_cpu_buffer_type()->iface.get_alloc_size, | |
| /* .supports_backend = */ ggml_backend_cpu_buffer_type()->iface.supports_backend, | |
| /* .is_host = */ ggml_backend_cpu_buffer_type()->iface.is_host, | |
| }, | |
| /* .context = */ nullptr, | |
| }; | |
| if (!vk_instance.contexts[0].initialized) { | |
| // Fall back to CPU | |
| return ggml_backend_cpu_buffer_type(); | |
| } | |
| return &ggml_backend_vk_buffer_type_host; | |
| } | |
| // backend | |
| GGML_CALL static const char * ggml_backend_vk_name(ggml_backend_t backend) { | |
| ggml_backend_vk_context * ctx = (ggml_backend_vk_context *)backend->context; | |
| return ctx->name.c_str(); | |
| } | |
| GGML_CALL static void ggml_backend_vk_free(ggml_backend_t backend) { | |
| ggml_backend_vk_context * ctx = (ggml_backend_vk_context *)backend->context; | |
| std::cerr << "ggml_backend_vk_free(" << ctx->name << ")" << std::endl; | |
| size_t idx = ctx->idx; | |
| ggml_vk_cleanup(ctx); | |
| ctx->device.reset(); | |
| ctx->initialized = false; | |
| vk_instance.initialized[idx] = false; | |
| vk_instance.backends[idx] = nullptr; | |
| memset(&vk_instance.buffer_types[idx], 0, sizeof(ggml_backend_buffer_type)); | |
| delete backend; | |
| } | |
| GGML_CALL static ggml_backend_buffer_type_t ggml_backend_vk_get_default_buffer_type(ggml_backend_t backend) { | |
| ggml_backend_vk_context * ctx = (ggml_backend_vk_context *)backend->context; | |
| GGML_ASSERT(ctx->initialized); | |
| return ggml_backend_vk_buffer_type(ctx->idx); | |
| } | |
| GGML_CALL static void ggml_backend_vk_set_tensor_async(ggml_backend_t backend, ggml_tensor * tensor, const void * data, size_t offset, size_t size) { | |
| std::cerr << "ggml_backend_vk_set_tensor_async(" << size << ")" << std::endl; | |
| ggml_backend_vk_context * ctx = (ggml_backend_vk_context *)backend->context; | |
| GGML_ASSERT((tensor->buffer->buft == ggml_backend_vk_buffer_type(ctx->idx) || tensor->buffer->buft == ggml_backend_vk_host_buffer_type()) && "unsupported buffer type"); | |
| GGML_ASSERT(tensor->backend == GGML_BACKEND_TYPE_GPU); | |
| ggml_tensor_extra_gpu * extra = (ggml_tensor_extra_gpu *) tensor->extra; | |
| if (ctx->transfer_ctx == nullptr) { | |
| // Initialize new transfer context | |
| ctx->transfer_ctx = ggml_vk_create_context(ctx, ctx->device->transfer_queue); | |
| ggml_vk_ctx_begin(ctx, ctx->transfer_ctx); | |
| } | |
| vk_buffer buf = extra->buffer_gpu.lock(); | |
| ggml_vk_buffer_write_async(ctx, ctx->transfer_ctx, buf, extra->offset + offset, data, size); | |
| } | |
| GGML_CALL static void ggml_backend_vk_get_tensor_async(ggml_backend_t backend, const ggml_tensor * tensor, void * data, size_t offset, size_t size) { | |
| std::cerr << "ggml_backend_vk_get_tensor_async(" << size << ")" << std::endl; | |
| ggml_backend_vk_context * ctx = (ggml_backend_vk_context *)backend->context; | |
| GGML_ASSERT((tensor->buffer->buft == ggml_backend_vk_buffer_type(ctx->idx) || tensor->buffer->buft == ggml_backend_vk_host_buffer_type()) && "unsupported buffer type"); | |
| GGML_ASSERT(tensor->backend == GGML_BACKEND_TYPE_GPU); | |
| ggml_tensor_extra_gpu * extra = (ggml_tensor_extra_gpu *) tensor->extra; | |
| if (ctx->transfer_ctx == nullptr) { | |
| // Initialize new transfer context | |
| ctx->transfer_ctx = ggml_vk_create_context(ctx, ctx->device->transfer_queue); | |
| ggml_vk_ctx_begin(ctx, ctx->transfer_ctx); | |
| } | |
| vk_buffer buf = extra->buffer_gpu.lock(); | |
| ggml_vk_buffer_read_async(ctx, ctx->transfer_ctx, buf, extra->offset + offset, data, size); | |
| } | |
| GGML_CALL static bool ggml_backend_vk_cpy_tensor_async(ggml_backend_t backend, const ggml_tensor * src, ggml_tensor * dst) { | |
| std::cerr << "ggml_backend_vk_cpy_tensor_async()" << std::endl; | |
| ggml_backend_vk_context * ctx = (ggml_backend_vk_context *)backend->context; | |
| if ((dst->buffer->buft == ggml_backend_vk_buffer_type(ctx->idx) || dst->buffer->buft == ggml_backend_vk_host_buffer_type()) && ggml_backend_buffer_is_vk(src->buffer)) { | |
| ggml_tensor_extra_gpu * src_extra = (ggml_tensor_extra_gpu *) src->extra; | |
| ggml_tensor_extra_gpu * dst_extra = (ggml_tensor_extra_gpu *) dst->extra; | |
| if (ctx->transfer_ctx == nullptr) { | |
| // Initialize new transfer context | |
| ctx->transfer_ctx = ggml_vk_create_context(ctx, ctx->device->transfer_queue); | |
| ggml_vk_ctx_begin(ctx, ctx->transfer_ctx); | |
| } | |
| vk_buffer src_buf = src_extra->buffer_gpu.lock(); | |
| vk_buffer dst_buf = dst_extra->buffer_gpu.lock(); | |
| ggml_vk_buffer_copy_async(ctx->transfer_ctx, dst_buf, dst_extra->offset, src_buf, src_extra->offset, ggml_nbytes(src)); | |
| return true; | |
| } | |
| return false; | |
| } | |
| GGML_CALL static void ggml_backend_vk_synchronize(ggml_backend_t backend) { | |
| std::cerr << "ggml_backend_vk_synchronize()" << std::endl; | |
| ggml_backend_vk_context * ctx = (ggml_backend_vk_context *)backend->context; | |
| if(ctx->transfer_ctx == nullptr) { | |
| return; | |
| } | |
| ggml_vk_ctx_end(ctx->transfer_ctx); | |
| for (auto& cpy : ctx->transfer_ctx->in_memcpys) { | |
| memcpy(cpy.dst, cpy.src, cpy.n); | |
| } | |
| ggml_vk_submit(ctx->transfer_ctx, ctx->fence); | |
| VK_CHECK(ctx->device->device.waitForFences({ ctx->fence }, true, UINT64_MAX), "ggml_backend_vk_synchronize waitForFences"); | |
| ctx->device->device.resetFences({ ctx->fence }); | |
| for (auto& cpy : ctx->transfer_ctx->out_memcpys) { | |
| memcpy(cpy.dst, cpy.src, cpy.n); | |
| } | |
| ctx->transfer_ctx = nullptr; | |
| } | |
| GGML_CALL static ggml_status ggml_backend_vk_graph_compute(ggml_backend_t backend, ggml_cgraph * cgraph) { | |
| std::cerr << "ggml_backend_vk_graph_compute(" << cgraph->n_nodes << " nodes)" << std::endl; | |
| ggml_backend_vk_context * ctx = (ggml_backend_vk_context *)backend->context; | |
| for (int i = 0; i < cgraph->n_nodes; i++) { | |
| ggml_vk_preallocate_buffers_graph(ctx, cgraph->nodes[i]); | |
| } | |
| ggml_vk_preallocate_buffers(ctx); | |
| int last_node = cgraph->n_nodes - 1; | |
| // If the last op in the cgraph isn't backend GPU, the command buffer doesn't get closed properly | |
| while (last_node > 0 && (cgraph->nodes[last_node]->backend != GGML_BACKEND_TYPE_GPU || ggml_is_empty(cgraph->nodes[last_node]))) { | |
| last_node -= 1; | |
| } | |
| for (int i = 0; i < cgraph->n_nodes; i++) { | |
| ggml_vk_build_graph(ctx,cgraph->nodes[i], i == last_node); | |
| } | |
| ggml_compute_params params = {}; | |
| params.type = GGML_TASK_TYPE_COMPUTE; | |
| params.ith = 0; | |
| for (int i = 0; i < cgraph->n_nodes; i++) { | |
| ggml_tensor * node = cgraph->nodes[i]; | |
| if (ggml_is_empty(node) || node->op == GGML_OP_RESHAPE || node->op == GGML_OP_TRANSPOSE || node->op == GGML_OP_VIEW || node->op == GGML_OP_PERMUTE || node->op == GGML_OP_NONE) { | |
| continue; | |
| } | |
| bool ok = ggml_vk_compute_forward(ctx, ¶ms, node); | |
| if (!ok) { | |
| fprintf(stderr, "%s: error: op not supported %s (%s)\n", __func__, node->name, ggml_op_name(node->op)); | |
| } | |
| else { | |
| ggml_vk_check_results_1(ctx, ¶ms, node); | |
| } | |
| GGML_ASSERT(ok); | |
| } | |
| ggml_vk_graph_cleanup(ctx); | |
| return GGML_STATUS_SUCCESS; | |
| UNUSED(backend); | |
| } | |
| GGML_CALL static bool ggml_backend_vk_supports_op(ggml_backend_t backend, const ggml_tensor * op) { | |
| // ggml_backend_vk_context * ctx = (ggml_backend_vk_context *) backend->context; | |
| switch (op->op) { | |
| case GGML_OP_UNARY: | |
| switch (ggml_get_unary_op(op)) { | |
| case GGML_UNARY_OP_GELU: | |
| case GGML_UNARY_OP_SILU: | |
| case GGML_UNARY_OP_RELU: | |
| return true; | |
| default: | |
| return false; | |
| } | |
| break; | |
| case GGML_OP_MUL_MAT: | |
| // case GGML_OP_MUL_MAT_ID: | |
| { | |
| switch (op->src[0]->type) { | |
| case GGML_TYPE_F32: | |
| case GGML_TYPE_F16: | |
| case GGML_TYPE_Q4_0: | |
| case GGML_TYPE_Q4_1: | |
| case GGML_TYPE_Q5_0: | |
| case GGML_TYPE_Q5_1: | |
| case GGML_TYPE_Q8_0: | |
| case GGML_TYPE_Q2_K: | |
| case GGML_TYPE_Q3_K: | |
| case GGML_TYPE_Q4_K: | |
| case GGML_TYPE_Q5_K: | |
| case GGML_TYPE_Q6_K: | |
| break; | |
| default: | |
| return false; | |
| } | |
| struct ggml_tensor * a; | |
| struct ggml_tensor * b; | |
| if (op->op == GGML_OP_MUL_MAT) { | |
| a = op->src[0]; | |
| b = op->src[1]; | |
| } else { | |
| a = op->src[2]; | |
| b = op->src[1]; | |
| } | |
| if (a->ne[3] != b->ne[3]) { | |
| return false; | |
| } | |
| return true; | |
| } break; | |
| case GGML_OP_GET_ROWS: | |
| { | |
| switch (op->src[0]->type) { | |
| case GGML_TYPE_F32: | |
| case GGML_TYPE_F16: | |
| case GGML_TYPE_Q4_0: | |
| case GGML_TYPE_Q4_1: | |
| case GGML_TYPE_Q5_0: | |
| case GGML_TYPE_Q5_1: | |
| case GGML_TYPE_Q8_0: | |
| return true; | |
| default: | |
| return false; | |
| } | |
| } break; | |
| case GGML_OP_CPY: | |
| case GGML_OP_DUP: | |
| { | |
| ggml_type src0_type = op->src[0]->type; | |
| ggml_type src1_type = op->src[1] != nullptr ? op->src[1]->type : src0_type; | |
| if (src0_type == GGML_TYPE_F32 && src1_type == GGML_TYPE_F32) { | |
| return true; | |
| } | |
| if (src0_type == GGML_TYPE_F32 && src1_type == GGML_TYPE_F16) { | |
| return true; | |
| } | |
| if (src0_type == GGML_TYPE_F16 && src1_type == GGML_TYPE_F16) { | |
| return true; | |
| } | |
| return false; | |
| } break; | |
| // case GGML_OP_REPEAT: | |
| // { | |
| // ggml_type src0_type = op->src[0]->type; | |
| // return src0_type != GGML_TYPE_I32 && src0_type != GGML_TYPE_I16; | |
| // } break; | |
| case GGML_OP_ROPE: | |
| { | |
| const int mode = ((const int32_t *) op->op_params)[2]; | |
| const bool is_glm = mode & 4; | |
| return !is_glm; | |
| } break; | |
| case GGML_OP_NONE: | |
| case GGML_OP_RESHAPE: | |
| case GGML_OP_VIEW: | |
| case GGML_OP_PERMUTE: | |
| case GGML_OP_TRANSPOSE: | |
| case GGML_OP_NORM: | |
| case GGML_OP_ADD: | |
| case GGML_OP_MUL: | |
| case GGML_OP_RMS_NORM: | |
| case GGML_OP_SCALE: | |
| case GGML_OP_SQR: | |
| case GGML_OP_CLAMP: | |
| case GGML_OP_CONT: | |
| case GGML_OP_DIAG_MASK_INF: | |
| case GGML_OP_SOFT_MAX: | |
| case GGML_OP_ARGSORT: | |
| return true; | |
| default: | |
| return false; | |
| } | |
| UNUSED(backend); | |
| } | |
| GGML_CALL static bool ggml_backend_vk_offload_op(ggml_backend_t backend, const ggml_tensor * op) { | |
| const ggml_tensor * dst = op; | |
| const int min_batch_size = 32; | |
| if (dst->ne[1] > min_batch_size && dst->op != GGML_OP_GET_ROWS) { | |
| return true; | |
| } | |
| return false; | |
| UNUSED(backend); | |
| } | |
| // TODO: enable async and synchronize | |
| static ggml_backend_i ggml_backend_vk_interface = { | |
| /* .get_name = */ ggml_backend_vk_name, | |
| /* .free = */ ggml_backend_vk_free, | |
| /* .get_default_buffer_type = */ ggml_backend_vk_get_default_buffer_type, | |
| /* .set_tensor_async = */ NULL, // ggml_backend_vk_set_tensor_async, | |
| /* .get_tensor_async = */ NULL, // ggml_backend_vk_get_tensor_async, | |
| /* .cpy_tensor_async = */ NULL, // ggml_backend_vk_cpy_tensor_async, | |
| /* .synchronize = */ NULL, // ggml_backend_vk_synchronize, | |
| /* .graph_plan_create = */ NULL, | |
| /* .graph_plan_free = */ NULL, | |
| /* .graph_plan_compute = */ NULL, | |
| /* .graph_compute = */ ggml_backend_vk_graph_compute, | |
| /* .supports_op = */ ggml_backend_vk_supports_op, | |
| /* .offload_op = */ ggml_backend_vk_offload_op, | |
| /* .event_new = */ NULL, | |
| /* .event_free = */ NULL, | |
| /* .event_record = */ NULL, | |
| /* .event_wait = */ NULL, | |
| /* .event_synchronize = */ NULL, | |
| }; | |
| static ggml_guid_t ggml_backend_vk_guid() { | |
| static ggml_guid guid = { 0xb8, 0xf7, 0x4f, 0x86, 0x40, 0x3c, 0xe1, 0x02, 0x91, 0xc8, 0xdd, 0xe9, 0x02, 0x3f, 0xc0, 0x2b }; | |
| return &guid; | |
| } | |
| GGML_CALL ggml_backend_t ggml_backend_vk_init(size_t dev_num) { | |
| if (vk_instance.initialized[dev_num]) { | |
| return vk_instance.backends[dev_num]; | |
| } | |
| std::cerr << "ggml_backend_vk_init(" << dev_num << ")" << std::endl; | |
| ggml_backend_vk_context * ctx = &vk_instance.contexts[dev_num]; | |
| ggml_vk_init(ctx, dev_num); | |
| ctx->name = GGML_VK_NAME + std::to_string(dev_num); | |
| vk_instance.buffer_types[dev_num] = { | |
| /* .iface = */ ggml_backend_vk_buffer_type_interface, | |
| /* .context = */ new ggml_backend_vk_buffer_type_context{ ctx->name, ctx }, | |
| }; | |
| vk_instance.initialized[dev_num] = true; | |
| ggml_backend_t vk_backend = new ggml_backend { | |
| /* .guid = */ ggml_backend_vk_guid(), | |
| /* .interface = */ ggml_backend_vk_interface, | |
| /* .context = */ &vk_instance.contexts[ctx->idx], | |
| }; | |
| vk_instance.backends[dev_num] = vk_backend; | |
| return vk_backend; | |
| } | |
| GGML_CALL bool ggml_backend_is_vk(ggml_backend_t backend) { | |
| return backend != NULL && ggml_guid_matches(backend->guid, ggml_backend_vk_guid()); | |
| } | |
| GGML_CALL int ggml_backend_vk_get_device_count() { | |
| return ggml_vk_get_device_count(); | |
| } | |
| GGML_CALL void ggml_backend_vk_get_device_description(int device, char * description, size_t description_size) { | |
| ggml_vk_get_device_description(device, description, description_size); | |
| } | |
| GGML_CALL void ggml_backend_vk_get_device_memory(int device, size_t * free, size_t * total) { | |
| GGML_ASSERT(device < (int) vk_instance.device_indices.size()); | |
| vk::PhysicalDevice vkdev = vk_instance.instance.enumeratePhysicalDevices()[vk_instance.device_indices[device]]; | |
| vk::PhysicalDeviceMemoryProperties memprops = vkdev.getMemoryProperties(); | |
| for (const vk::MemoryHeap& heap : memprops.memoryHeaps) { | |
| if (heap.flags & vk::MemoryHeapFlagBits::eDeviceLocal) { | |
| *total = heap.size; | |
| *free = heap.size; | |
| break; | |
| } | |
| } | |
| } | |
| // backend registry | |
| GGML_CALL static ggml_backend_t ggml_backend_reg_vk_init(const char * params, void * user_data) { | |
| ggml_backend_t vk_backend = ggml_backend_vk_init((int) (intptr_t) user_data); | |
| return vk_backend; | |
| UNUSED(params); | |
| } | |
| extern "C" GGML_CALL int ggml_backend_vk_reg_devices(); | |
| GGML_CALL int ggml_backend_vk_reg_devices() { | |
| ggml_vk_instance_init(); | |
| for (size_t i = 0; i < vk_instance.device_indices.size(); i++) { | |
| char name[128]; | |
| snprintf(name, sizeof(name), "%s%ld", GGML_VK_NAME, i); | |
| ggml_backend_register(name, ggml_backend_reg_vk_init, ggml_backend_vk_buffer_type(i), (void *) (intptr_t) i); // NOLINT | |
| } | |
| return vk_instance.device_indices.size(); | |
| } | |
| // Extension availability | |
| static bool ggml_vk_instance_validation_ext_available(const std::vector<vk::ExtensionProperties>& instance_extensions) { | |
| bool portability_enumeration_ext = false; | |
| // Check for portability enumeration extension for MoltenVK support | |
| for (const auto& properties : instance_extensions) { | |
| if (strcmp("VK_KHR_portability_enumeration", properties.extensionName) == 0) { | |
| return true; | |
| } | |
| } | |
| if (!portability_enumeration_ext) { | |
| std::cerr << "ggml_vulkan: WARNING: Instance extension VK_KHR_portability_enumeration not found." << std::endl; | |
| } | |
| return false; | |
| UNUSED(instance_extensions); | |
| } | |
| static bool ggml_vk_instance_portability_enumeration_ext_available(const std::vector<vk::ExtensionProperties>& instance_extensions) { | |
| bool portability_enumeration_ext = false; | |
| // Check for portability enumeration extension for MoltenVK support | |
| for (const auto& properties : instance_extensions) { | |
| if (strcmp("VK_KHR_portability_enumeration", properties.extensionName) == 0) { | |
| return true; | |
| } | |
| } | |
| if (!portability_enumeration_ext) { | |
| std::cerr << "ggml_vulkan: WARNING: Instance extension VK_KHR_portability_enumeration not found." << std::endl; | |
| } | |
| return false; | |
| UNUSED(instance_extensions); | |
| } | |
| // checks | |
| static void ggml_vk_print_graph_origin(const ggml_tensor * tensor, std::vector<const ggml_tensor *>& done, int level = 0) { | |
| if (std::find(done.begin(), done.end(), tensor) != done.end() || level > 10) { | |
| return; | |
| } | |
| for (int j = 0; j < level; j++) { | |
| std::cerr << " "; | |
| } | |
| std::cerr << ggml_op_name(tensor->op) << " gpu=" << (tensor->extra != nullptr) << " backend=" << tensor->backend << std::endl; | |
| done.push_back(tensor); | |
| for (int i = 0; i < GGML_MAX_SRC; i++) { | |
| if (tensor->src[i] != nullptr) { | |
| ggml_vk_print_graph_origin(tensor->src[i], done, level + 1); | |
| } | |
| } | |
| } | |
| static void ggml_vk_print_tensor_area(const ggml_tensor * tensor, const void * data, int i0, int i1, int i2, int i3) { | |
| if (tensor->type != GGML_TYPE_F32 && tensor->type != GGML_TYPE_F16) { | |
| return; | |
| } | |
| i0 = std::max(i0, 5); | |
| i1 = std::max(i1, 5); | |
| i2 = std::max(i2, 0); | |
| i3 = std::max(i3, 0); | |
| fprintf(stderr, " "); | |
| for (int idx1 = i1 - 5; idx1 < i1 + 5; idx1++) { | |
| fprintf(stderr, "%7d ", idx1); | |
| } | |
| fprintf(stderr, "\n"); | |
| for (int idx0 = i0 - 5; idx0 < i0 + 5; idx0++) { | |
| fprintf(stderr, "%7d: ", idx0); | |
| for (int idx1 = i1 - 5; idx1 < i1 + 5; idx1++) { | |
| if (idx0 >= 0 && idx0 < tensor->ne[0] && idx1 >= 0 && idx1 < tensor->ne[1] && i2 >= 0 && i2 < tensor->ne[2] && i3 >= 0 && i3 < tensor->ne[3]) { | |
| float val; | |
| if (tensor->type == GGML_TYPE_F32) { | |
| val = *(const float *) ((const char *) data + i3*tensor->nb[3] + i2*tensor->nb[2] + idx1*tensor->nb[1] + idx0*tensor->nb[0]); | |
| } else if (tensor->type == GGML_TYPE_F16) { | |
| val = ggml_fp16_to_fp32(*(const ggml_fp16_t *) ((const char *) data + i3*tensor->nb[3] + i2*tensor->nb[2] + idx1*tensor->nb[1] + idx0*tensor->nb[0])); | |
| } else { | |
| GGML_ASSERT(false); | |
| } | |
| fprintf(stderr, "% 7.2f ", val); | |
| } else { | |
| fprintf(stderr, " "); | |
| } | |
| } | |
| fprintf(stderr, "\n"); | |
| } | |
| } | |
| static void ggml_vk_print_tensor(ggml_backend_vk_context * ctx, const ggml_tensor * tensor, const char * name) { | |
| void * tensor_data = tensor->data; | |
| if (tensor->backend == GGML_BACKEND_TYPE_GPU) { | |
| const size_t tensor_size = ggml_nbytes(tensor); | |
| tensor_data = malloc(tensor_size); | |
| ggml_tensor_extra_gpu * extra = (ggml_tensor_extra_gpu *) tensor->extra; | |
| vk_buffer buffer_gpu = extra->buffer_gpu.lock(); | |
| ggml_vk_buffer_read(ctx, buffer_gpu, extra->offset, tensor_data, tensor_size); | |
| } | |
| std::cerr << "TENSOR CHECK " << name << " (" << tensor->name << "): " << ggml_op_name(tensor->op) << std::endl; | |
| std::cerr << "tensor=" << tensor << " tensor->backend: " << tensor->backend << " tensor->type: " << ggml_type_name(tensor->type) << " ne0=" << tensor->ne[0] << " nb0=" << tensor->nb[0] << " ne1=" << tensor->ne[1] << " nb1=" << tensor->nb[1] << " ne2=" << tensor->ne[2] << " nb2=" << tensor->nb[2] << " ne3=" << tensor->ne[3] << " nb3=" << tensor->nb[3] << std::endl; | |
| if (tensor->src[0] != nullptr) { | |
| std::cerr << "tensor->src[0]=" << tensor->src[0] << " name=" << tensor->src[0]->name << " op=" << ggml_op_name(tensor->src[0]->op) << " type=" << ggml_type_name(tensor->src[0]->type) << " backend=" << tensor->src[0]->backend << " ne0=" << tensor->src[0]->ne[0] << " nb0=" << tensor->src[0]->nb[0] << " ne1=" << tensor->src[0]->ne[1] << " nb1=" << tensor->src[0]->nb[1] << " ne2=" << tensor->src[0]->ne[2] << " nb2=" << tensor->src[0]->nb[2] << " ne3=" << tensor->src[0]->ne[3] << " nb3=" << tensor->src[0]->nb[3] << std::endl; | |
| } | |
| if (tensor->src[1] != nullptr) { | |
| std::cerr << "tensor->src[1]=" << tensor->src[1] << " name=" << tensor->src[1]->name << " op=" << ggml_op_name(tensor->src[1]->op) << " type=" << ggml_type_name(tensor->src[1]->type) << " backend=" << tensor->src[1]->backend << " ne0=" << tensor->src[1]->ne[0] << " nb0=" << tensor->src[1]->nb[0] << " ne1=" << tensor->src[1]->ne[1] << " nb1=" << tensor->src[1]->nb[1] << " ne2=" << tensor->src[1]->ne[2] << " nb2=" << tensor->src[1]->nb[2] << " ne3=" << tensor->src[1]->ne[3] << " nb3=" << tensor->src[1]->nb[3] << std::endl; | |
| } | |
| std::cerr << std::endl << "Result:" << std::endl; | |
| ggml_vk_print_tensor_area(tensor, tensor_data, 5, 5, 0, 0); | |
| std::cerr << std::endl; | |
| std::cerr << std::endl << "Result:" << std::endl; | |
| ggml_vk_print_tensor_area(tensor, tensor_data, 5, 5, 1, 0); | |
| std::cerr << std::endl; | |
| std::vector<const ggml_tensor *> done; | |
| ggml_vk_print_graph_origin(tensor, done); | |
| if (tensor->backend == GGML_BACKEND_TYPE_GPU) { | |
| free(tensor_data); | |
| } | |
| } | |
| static void ggml_vk_check_tensor(const std::string& name, const ggml_tensor * tensor) { | |
| return; | |
| GGML_ASSERT(tensor->backend == GGML_BACKEND_TYPE_CPU); | |
| if (tensor->type != GGML_TYPE_F32 && tensor->type != GGML_TYPE_F16) { | |
| return; | |
| } | |
| for (int i3 = 0; i3 < tensor->ne[3]; i3++) { | |
| for (int i2 = 0; i2 < tensor->ne[2]; i2++) { | |
| for (int i1 = 0; i1 < tensor->ne[1]; i1++) { | |
| for (int i0 = 0; i0 < tensor->ne[0]; i0++) { | |
| float val = 0.0f; | |
| if (tensor->type == GGML_TYPE_F32) { | |
| val = *(float *) ((char *) tensor->data + i3*tensor->nb[3] + i2*tensor->nb[2] + i1*tensor->nb[1] + i0*tensor->nb[0]); | |
| } else if (tensor->type == GGML_TYPE_F16) { | |
| val = ggml_fp16_to_fp32(*(ggml_fp16_t *) ((char *) tensor->data + i3*tensor->nb[3] + i2*tensor->nb[2] + i1*tensor->nb[1] + i0*tensor->nb[0])); | |
| } | |
| if (std::isnan(val)) { | |
| std::cerr << "ERROR: TENSOR CHECK " << name << ": Invalid value in " << ggml_op_name(tensor->op) << " i3=" << i3 << " i2=" << i2 << " i1=" << i1 << " i0=" << i0 << " val=" << val << std::endl; | |
| std::cerr << "tensor=" << tensor << " tensor->type=" << ggml_type_name(tensor->type) << " tensor->backend: " << tensor->backend << " ne0=" << tensor->ne[0] << " nb0=" << tensor->nb[0] << " ne1=" << tensor->ne[1] << " nb1=" << tensor->nb[1] << " ne2=" << tensor->ne[2] << " nb2=" << tensor->nb[2] << " ne3=" << tensor->ne[3] << " nb3=" << tensor->nb[3] << std::endl; | |
| std::cerr << std::endl; | |
| ggml_vk_print_tensor_area(tensor, tensor->data, i0, i1, i2, i3); | |
| std::cerr << std::endl; | |
| std::vector<const ggml_tensor *> done; | |
| ggml_vk_print_graph_origin(tensor, done); | |
| GGML_ASSERT(false); | |
| } | |
| } | |
| } | |
| } | |
| } | |
| } | |
| void * comp_result; | |
| size_t comp_size; | |
| size_t comp_nb[GGML_MAX_DIMS]; | |
| size_t check_counter = 0; | |
| static void ggml_vk_check_results_0(ggml_backend_vk_context * ctx, ggml_compute_params * params, ggml_tensor * tensor) { | |
| if (params->ith != 0) { | |
| return; | |
| } | |
| if (params->type == GGML_TASK_TYPE_INIT || params->type == GGML_TASK_TYPE_FINALIZE || tensor->op == GGML_OP_TRANSPOSE) { | |
| return; | |
| } | |
| check_counter++; | |
| if (!(vk_output_tensor > 0 && vk_output_tensor == check_counter) && check_counter <= vk_skip_checks) { | |
| return; | |
| } | |
| std::cerr << "ggml_vk_check_results_0(" << tensor->name << ")" << std::endl; | |
| ggml_tensor * src0 = tensor->src[0]; | |
| ggml_tensor * src1 = tensor->src[1]; | |
| ggml_tensor * src2 = tensor->src[2]; | |
| struct ggml_init_params iparams = { | |
| /*.mem_size =*/ 1024*1024*1024, | |
| /*.mem_buffer =*/ NULL, | |
| /*.no_alloc =*/ false, | |
| }; | |
| struct ggml_context * ggml_ctx = ggml_init(iparams); | |
| struct ggml_tensor * src0_clone = nullptr; | |
| struct ggml_tensor * src1_clone = nullptr; | |
| struct ggml_tensor * src2_clone = nullptr; | |
| struct ggml_tensor * tensor_clone = nullptr; | |
| size_t src0_size; | |
| size_t src1_size; | |
| size_t src2_size; | |
| void * src0_buffer; | |
| void * src1_buffer; | |
| void * src2_buffer; | |
| if (src0 != nullptr) { | |
| src0_clone = ggml_dup_tensor(ggml_ctx, src0); | |
| src0_size = ggml_nbytes(src0); | |
| src0_buffer = malloc(src0_size); | |
| src0_clone->data = src0_buffer; | |
| if (src0->backend == GGML_BACKEND_TYPE_CPU) { | |
| memcpy(src0_clone->data, src0->data, src0_size); | |
| memcpy(src0_clone->nb, src0->nb, sizeof(size_t) * GGML_MAX_DIMS); | |
| } else if (src0->backend == GGML_BACKEND_TYPE_GPU) { | |
| ggml_tensor_extra_gpu * extra = (ggml_tensor_extra_gpu *) src0->extra; | |
| vk_buffer buffer_gpu = extra->buffer_gpu.lock(); | |
| uint64_t offset = extra->offset; | |
| if (!ggml_is_contiguous(src0) && ggml_vk_dim01_contiguous(src0)) { | |
| for (int i3 = 0; i3 < src0->ne[3]; i3++) { | |
| for (int i2 = 0; i2 < src0->ne[2]; i2++) { | |
| const int idx = i3*src0->ne[2] + i2; | |
| ggml_vk_buffer_read(ctx, buffer_gpu, offset + idx * src0->nb[2], ((char *)src0_clone->data + idx * src0_clone->nb[2]), src0->ne[1] * src0->nb[1]); | |
| } | |
| } | |
| src0_clone->nb[0] = src0->nb[0]; | |
| src0_clone->nb[1] = src0->nb[1]; | |
| for (int i = 2; i < GGML_MAX_DIMS; i++) { | |
| src0_clone->nb[i] = src0_clone->nb[i - 1]*src0_clone->ne[i - 1]; | |
| } | |
| } else { | |
| if (offset + src0_size >= buffer_gpu->size) { | |
| src0_size = buffer_gpu->size - offset; | |
| } | |
| ggml_vk_buffer_read(ctx, buffer_gpu, offset, src0_clone->data, src0_size); | |
| memcpy(src0_clone->nb, src0->nb, sizeof(size_t) * GGML_MAX_DIMS); | |
| } | |
| } else { | |
| GGML_ASSERT(false); | |
| } | |
| if (vk_output_tensor > 0 && vk_output_tensor == check_counter) { | |
| ggml_vk_print_tensor(ctx, src0, "src0"); | |
| } | |
| ggml_vk_check_tensor(std::string(ggml_op_name(tensor->op)) + "->src0", src0_clone); | |
| } | |
| if (src1 != nullptr) { | |
| src1_clone = ggml_dup_tensor(ggml_ctx, src1); | |
| src1_size = ggml_nbytes(src1); | |
| src1_buffer = malloc(src1_size); | |
| src1_clone->data = src1_buffer; | |
| if (src1->backend == GGML_BACKEND_TYPE_CPU) { | |
| memcpy(src1_clone->data, src1->data, src1_size); | |
| memcpy(src1_clone->nb, src1->nb, sizeof(size_t) * GGML_MAX_DIMS); | |
| } else if (src1->backend == GGML_BACKEND_TYPE_GPU) { | |
| ggml_tensor_extra_gpu * extra = (ggml_tensor_extra_gpu *) src1->extra; | |
| vk_buffer buffer_gpu = extra->buffer_gpu.lock(); | |
| uint64_t offset = extra->offset; | |
| if (!ggml_is_contiguous(src1) && ggml_vk_dim01_contiguous(src1)) { | |
| for (int i3 = 0; i3 < src1->ne[3]; i3++) { | |
| for (int i2 = 0; i2 < src1->ne[2]; i2++) { | |
| const int idx = i3*src1->ne[2] + i2; | |
| ggml_vk_buffer_read(ctx, buffer_gpu, offset + idx * src1->nb[2], ((char *)src1_clone->data + idx * src1_clone->nb[2]), src1->ne[1] * src1->nb[1]); | |
| } | |
| } | |
| src1_clone->nb[0] = src1->nb[0]; | |
| src1_clone->nb[1] = src1->nb[1]; | |
| for (int i = 2; i < GGML_MAX_DIMS; i++) { | |
| src1_clone->nb[i] = src1_clone->nb[i - 1]*src1_clone->ne[i - 1]; | |
| } | |
| } else { | |
| if (offset + src1_size >= buffer_gpu->size) { | |
| src1_size = buffer_gpu->size - offset; | |
| } | |
| ggml_vk_buffer_read(ctx, buffer_gpu, offset, src1_clone->data, src1_size); | |
| memcpy(src1_clone->nb, src1->nb, sizeof(size_t) * GGML_MAX_DIMS); | |
| } | |
| } else { | |
| GGML_ASSERT(false); | |
| } | |
| if (vk_output_tensor > 0 && vk_output_tensor == check_counter) { | |
| ggml_vk_print_tensor(ctx, src1, "src1"); | |
| std::cerr << "TENSOR CHECK: " << ggml_op_name(src1_clone->op) << " (check " << check_counter << ")" << std::endl; | |
| std::cerr << "src1_clone=" << tensor << " src1_clone->backend: " << src1_clone->backend << " src1_clone->type: " << ggml_type_name(src1_clone->type) << " ne0=" << src1_clone->ne[0] << " nb0=" << src1_clone->nb[0] << " ne1=" << src1_clone->ne[1] << " nb1=" << src1_clone->nb[1] << " ne2=" << src1_clone->ne[2] << " nb2=" << src1_clone->nb[2] << " ne3=" << src1_clone->ne[3] << " nb3=" << src1_clone->nb[3] << std::endl; | |
| if (src1->src[0] != nullptr) { | |
| std::cerr << "src1->src[0]=" << src1->src[0] << " op=" << ggml_op_name(src1->src[0]->op) << " type=" << ggml_type_name(src1->src[0]->type) << " backend=" << src1->src[0]->backend << " ne0=" << src1->src[0]->ne[0] << " nb0=" << src1->src[0]->nb[0] << " ne1=" << src1->src[0]->ne[1] << " nb1=" << src1->src[0]->nb[1] << " ne2=" << src1->src[0]->ne[2] << " nb2=" << src1->src[0]->nb[2] << " ne3=" << src1->src[0]->ne[3] << " nb3=" << src1->src[0]->nb[3] << std::endl; | |
| } | |
| if (src1->src[1] != nullptr) { | |
| std::cerr << "src1->src[1]=" << src1->src[1] << " op=" << ggml_op_name(src1->src[1]->op) << " type=" << ggml_type_name(src1->src[1]->type) << " backend=" << src1->src[1]->backend << " ne0=" << src1->src[1]->ne[0] << " nb0=" << src1->src[1]->nb[0] << " ne1=" << src1->src[1]->ne[1] << " nb1=" << src1->src[1]->nb[1] << " ne2=" << src1->src[1]->ne[2] << " nb2=" << src1->src[1]->nb[2] << " ne3=" << src1->src[1]->ne[3] << " nb3=" << src1->src[1]->nb[3] << std::endl; | |
| } | |
| std::cerr << std::endl << "Result:" << std::endl; | |
| ggml_vk_print_tensor_area(src1_clone, src1_clone->data, 5, 5, 0, 0); | |
| std::cerr << std::endl; | |
| std::cerr << std::endl << "Result:" << std::endl; | |
| ggml_vk_print_tensor_area(src1_clone, src1_clone->data, 5, 5, 1, 0); | |
| std::cerr << std::endl; | |
| std::vector<const ggml_tensor *> done; | |
| ggml_vk_print_graph_origin(src1_clone, done); | |
| } | |
| ggml_vk_check_tensor(std::string(ggml_op_name(tensor->op)) + "->src1", src1_clone); | |
| } | |
| if (src2 != nullptr) { | |
| src2_clone = ggml_dup_tensor(ggml_ctx, src2); | |
| src2_size = ggml_nbytes(src2); | |
| src2_buffer = malloc(src2_size); | |
| src2_clone->data = src2_buffer; | |
| if (src2->backend == GGML_BACKEND_TYPE_CPU) { | |
| memcpy(src2_clone->data, src2->data, src2_size); | |
| memcpy(src2_clone->nb, src2->nb, sizeof(size_t) * GGML_MAX_DIMS); | |
| } else if (src2->backend == GGML_BACKEND_TYPE_GPU) { | |
| ggml_tensor_extra_gpu * extra = (ggml_tensor_extra_gpu *) src2->extra; | |
| vk_buffer buf = extra->buffer_gpu.lock(); | |
| uint64_t offset = extra->offset; | |
| if (!ggml_is_contiguous(src2) && ggml_vk_dim01_contiguous(src2)) { | |
| for (int i3 = 0; i3 < src2->ne[3]; i3++) { | |
| for (int i2 = 0; i2 < src2->ne[2]; i2++) { | |
| const int idx = i3*src2->ne[2] + i2; | |
| ggml_vk_buffer_read(ctx, buf, offset + idx * src2->nb[2], ((char *)src2_clone->data + idx * src2_clone->nb[2]), src2->ne[1] * src2->nb[1]); | |
| } | |
| } | |
| src2_clone->nb[0] = src2->nb[0]; | |
| src2_clone->nb[1] = src2->nb[1]; | |
| for (int i = 2; i < GGML_MAX_DIMS; i++) { | |
| src2_clone->nb[i] = src2_clone->nb[i - 1]*src2_clone->ne[i - 1]; | |
| } | |
| } else { | |
| if (offset + src2_size >= buf->size) { | |
| src2_size = buf->size - offset; | |
| } | |
| ggml_vk_buffer_read(ctx, buf, offset, src2_clone->data, src2_size); | |
| memcpy(src2_clone->nb, src2->nb, sizeof(size_t) * GGML_MAX_DIMS); | |
| } | |
| } else { | |
| GGML_ASSERT(false); | |
| } | |
| if (vk_output_tensor > 0 && vk_output_tensor == check_counter) { | |
| ggml_vk_print_tensor(ctx, src2, "src2"); | |
| std::cerr << "TENSOR CHECK: " << ggml_op_name(src2_clone->op) << " (check " << check_counter << ")" << std::endl; | |
| std::cerr << "src2_clone=" << tensor << " src2_clone->backend: " << src2_clone->backend << " src2_clone->type: " << ggml_type_name(src2_clone->type) << " ne0=" << src2_clone->ne[0] << " nb0=" << src2_clone->nb[0] << " ne1=" << src2_clone->ne[1] << " nb1=" << src2_clone->nb[1] << " ne2=" << src2_clone->ne[2] << " nb2=" << src2_clone->nb[2] << " ne3=" << src2_clone->ne[3] << " nb3=" << src2_clone->nb[3] << std::endl; | |
| if (src2->src[0] != nullptr) { | |
| std::cerr << "src2->src[0]=" << src2->src[0] << " op=" << ggml_op_name(src2->src[0]->op) << " type=" << ggml_type_name(src2->src[0]->type) << " backend=" << src2->src[0]->backend << " ne0=" << src2->src[0]->ne[0] << " nb0=" << src2->src[0]->nb[0] << " ne1=" << src2->src[0]->ne[1] << " nb1=" << src2->src[0]->nb[1] << " ne2=" << src2->src[0]->ne[2] << " nb2=" << src2->src[0]->nb[2] << " ne3=" << src2->src[0]->ne[3] << " nb3=" << src2->src[0]->nb[3] << std::endl; | |
| } | |
| if (src2->src[1] != nullptr) { | |
| std::cerr << "src2->src[1]=" << src2->src[1] << " op=" << ggml_op_name(src2->src[1]->op) << " type=" << ggml_type_name(src2->src[1]->type) << " backend=" << src2->src[1]->backend << " ne0=" << src2->src[1]->ne[0] << " nb0=" << src2->src[1]->nb[0] << " ne1=" << src2->src[1]->ne[1] << " nb1=" << src2->src[1]->nb[1] << " ne2=" << src2->src[1]->ne[2] << " nb2=" << src2->src[1]->nb[2] << " ne3=" << src2->src[1]->ne[3] << " nb3=" << src2->src[1]->nb[3] << std::endl; | |
| } | |
| std::cerr << std::endl << "Result:" << std::endl; | |
| ggml_vk_print_tensor_area(src2_clone, src2_clone->data, 5, 5, 0, 0); | |
| std::cerr << std::endl; | |
| std::cerr << std::endl << "Result:" << std::endl; | |
| ggml_vk_print_tensor_area(src2_clone, src2_clone->data, 5, 5, 1, 0); | |
| std::cerr << std::endl; | |
| std::vector<const ggml_tensor *> done; | |
| ggml_vk_print_graph_origin(src2_clone, done); | |
| } | |
| ggml_vk_check_tensor(std::string(ggml_op_name(tensor->op)) + "->src2", src2_clone); | |
| } | |
| if (tensor->op == GGML_OP_MUL_MAT) { | |
| tensor_clone = ggml_mul_mat(ggml_ctx, src0_clone, src1_clone); | |
| } else if (tensor->op == GGML_OP_MUL) { | |
| tensor_clone = ggml_mul(ggml_ctx, src0_clone, src1_clone); | |
| } else if (tensor->op == GGML_OP_SCALE) { | |
| tensor_clone = ggml_scale(ggml_ctx, src0_clone, ((float *)tensor->op_params)[0]); | |
| } else if (tensor->op == GGML_OP_SQR) { | |
| tensor_clone = ggml_sqr(ggml_ctx, src0_clone); | |
| } else if (tensor->op == GGML_OP_CLAMP) { | |
| tensor_clone = ggml_clamp(ggml_ctx, src0_clone, ((float *)tensor->op_params)[0], ((float *)tensor->op_params)[1]); | |
| } else if (tensor->op == GGML_OP_ADD) { | |
| tensor_clone = ggml_add(ggml_ctx, src0_clone, src1_clone); | |
| } else if (tensor->op == GGML_OP_NORM) { | |
| tensor_clone = ggml_norm(ggml_ctx, src0_clone, *(float *)tensor->op_params); | |
| } else if (tensor->op == GGML_OP_RMS_NORM) { | |
| tensor_clone = ggml_rms_norm(ggml_ctx, src0_clone, *(float *)tensor->op_params); | |
| } else if (tensor->op == GGML_OP_SOFT_MAX) { | |
| if (src1 != nullptr) { | |
| tensor_clone = ggml_soft_max_ext(ggml_ctx, src0_clone, src1_clone, src2_clone, ((float *)tensor->op_params)[0], ((float *)tensor->op_params)[1]); | |
| } else { | |
| tensor_clone = ggml_soft_max(ggml_ctx, src0_clone); | |
| } | |
| } else if (tensor->op == GGML_OP_DIAG_MASK_INF) { | |
| tensor_clone = ggml_diag_mask_inf(ggml_ctx, src0_clone, *(int *)tensor->op_params); | |
| } else if (tensor->op == GGML_OP_ROPE) { | |
| const int n_dims = ((int32_t *) tensor->op_params)[1]; | |
| const int mode = ((int32_t *) tensor->op_params)[2]; | |
| const int n_ggml_ctx = ((int32_t *) tensor->op_params)[3]; | |
| const int n_orig_ggml_ctx = ((int32_t *) tensor->op_params)[4]; | |
| float freq_base = ((float *) tensor->op_params)[5]; | |
| float freq_scale = ((float *) tensor->op_params)[6]; | |
| float ext_factor = ((float *) tensor->op_params)[7]; | |
| float attn_factor = ((float *) tensor->op_params)[8]; | |
| float beta_fast = ((float *) tensor->op_params)[9]; | |
| float beta_slow = ((float *) tensor->op_params)[10]; | |
| tensor_clone = ggml_rope_custom(ggml_ctx, src0_clone, src1_clone, n_dims, mode, n_ggml_ctx, n_orig_ggml_ctx, freq_base, freq_scale, ext_factor, attn_factor, beta_fast, beta_slow); | |
| } else if (tensor->op == GGML_OP_UNARY) { | |
| switch (ggml_get_unary_op(tensor)) { | |
| case GGML_UNARY_OP_SILU: | |
| tensor_clone = ggml_silu(ggml_ctx, src0_clone); | |
| break; | |
| case GGML_UNARY_OP_GELU: | |
| tensor_clone = ggml_gelu(ggml_ctx, src0_clone); | |
| break; | |
| case GGML_UNARY_OP_RELU: | |
| tensor_clone = ggml_relu(ggml_ctx, src0_clone); | |
| break; | |
| default: | |
| std::cerr << "Missing vk_check_results OP: " << ggml_op_name(tensor->op) << std::endl; | |
| GGML_ASSERT(false); | |
| } | |
| } else if (tensor->op == GGML_OP_CPY || tensor->op == GGML_OP_DUP) { | |
| if (src1 == nullptr) { | |
| tensor_clone = ggml_dup(ggml_ctx, src0_clone); | |
| tensor_clone->type = tensor->type; | |
| } else { | |
| tensor_clone = ggml_cpy(ggml_ctx, src0_clone, src1_clone); | |
| } | |
| } else if (tensor->op == GGML_OP_CONT) { | |
| tensor_clone = ggml_cont_4d(ggml_ctx, src0_clone, tensor->ne[0], tensor->ne[1], tensor->ne[2], tensor->ne[3]); | |
| } else if (tensor->op == GGML_OP_RESHAPE) { | |
| tensor_clone = ggml_reshape_4d(ggml_ctx, src0_clone, tensor->ne[0], tensor->ne[1], tensor->ne[2], tensor->ne[3]); | |
| } else if (tensor->op == GGML_OP_VIEW) { | |
| tensor_clone = ggml_view_4d(ggml_ctx, src0_clone, tensor->ne[0], tensor->ne[1], tensor->ne[2], tensor->ne[3], tensor->nb[1], tensor->nb[2], tensor->nb[3], ((int32_t *) tensor->op_params)[0]); | |
| } else if (tensor->op == GGML_OP_PERMUTE) { | |
| int32_t * params = (int32_t *)tensor->op_params; | |
| tensor_clone = ggml_permute(ggml_ctx, src0_clone, params[0], params[1], params[2], params[3]); | |
| } else if (tensor->op == GGML_OP_TRANSPOSE) { | |
| tensor_clone = ggml_transpose(ggml_ctx, src0_clone); | |
| } else if (tensor->op == GGML_OP_GET_ROWS) { | |
| tensor_clone = ggml_get_rows(ggml_ctx, src0_clone, src1_clone); | |
| } else if (tensor->op == GGML_OP_ARGSORT) { | |
| tensor_clone = ggml_argsort(ggml_ctx, src0_clone, (ggml_sort_order) *(int *)tensor->op_params); | |
| } else { | |
| std::cerr << "Missing vk_check_results OP: " << ggml_op_name(tensor->op) << std::endl; | |
| GGML_ASSERT(false); | |
| } | |
| // Disable vulkan here to avoid the hooks in ggml.c | |
| ctx->disable = true; | |
| ggml_cgraph * cgraph = ggml_new_graph(ggml_ctx); | |
| ggml_build_forward_expand(cgraph, tensor_clone); | |
| ggml_graph_compute_with_ctx(ggml_ctx, cgraph, 8); | |
| ctx->disable = false; | |
| ggml_vk_check_tensor(ggml_op_name(tensor->op), tensor_clone); | |
| if (vk_output_tensor > 0 && vk_output_tensor == check_counter) { | |
| ggml_vk_print_tensor(ctx, tensor_clone, "tensor_clone"); | |
| } | |
| comp_size = ggml_nbytes(tensor_clone); | |
| comp_result = malloc(comp_size); | |
| memcpy(comp_result, tensor_clone->data, comp_size); | |
| memcpy(comp_nb, tensor_clone->nb, sizeof(size_t) * GGML_MAX_DIMS); | |
| if (src0 != nullptr) { | |
| free(src0_buffer); | |
| } | |
| if (src1 != nullptr) { | |
| free(src1_buffer); | |
| } | |
| if (src2 != nullptr) { | |
| free(src2_buffer); | |
| } | |
| ggml_free(ggml_ctx); | |
| } | |
| static void ggml_vk_check_results_1(ggml_backend_vk_context * ctx, ggml_compute_params * params, ggml_tensor * tensor) { | |
| if (params->ith != 0) { | |
| return; | |
| } | |
| if (params->type == GGML_TASK_TYPE_INIT || params->type == GGML_TASK_TYPE_FINALIZE || tensor->op == GGML_OP_TRANSPOSE) { | |
| return; | |
| } | |
| if (!(vk_output_tensor > 0 && vk_output_tensor == check_counter) && check_counter <= vk_skip_checks) { | |
| return; | |
| } | |
| std::cerr << "ggml_vk_check_results_1(" << tensor->name << ")" << std::endl; | |
| ggml_tensor * src0 = tensor->src[0]; | |
| ggml_tensor * src1 = tensor->src[1]; | |
| void * tensor_data = tensor->data; | |
| if (tensor->backend == GGML_BACKEND_TYPE_GPU) { | |
| size_t tensor_size = ggml_nbytes(tensor); | |
| tensor_data = malloc(tensor_size); | |
| ggml_tensor_extra_gpu * extra = (ggml_tensor_extra_gpu *) tensor->extra; | |
| vk_buffer buffer_gpu = extra->buffer_gpu.lock(); | |
| if (extra->offset + tensor_size >= buffer_gpu->size) { | |
| tensor_size = buffer_gpu->size - (extra->offset); | |
| } | |
| ggml_vk_buffer_read(ctx, buffer_gpu, extra->offset, tensor_data, tensor_size); | |
| } | |
| float first_error_result = -1.0f; | |
| float first_error_correct = -1.0f; | |
| std::array<int, 4> first_error = { -1, -1, -1, -1 }; | |
| double avg_err = 0.0; | |
| size_t counter = 0; | |
| for (int i3 = 0; i3 < tensor->ne[3]; i3++) { | |
| for (int i2 = 0; i2 < tensor->ne[2]; i2++) { | |
| for (int i1 = 0; i1 < tensor->ne[1]; i1++) { | |
| for (int i0 = 0; i0 < tensor->ne[0]; i0++) { | |
| const bool buffer_size_fit = i3*comp_nb[3] + i2*comp_nb[2] + i1*comp_nb[1] + i0*comp_nb[0] < comp_size; | |
| float correct = 0.0f; | |
| float result = 0.0f; | |
| if (buffer_size_fit) { | |
| if (tensor->type == GGML_TYPE_F32) { | |
| correct = *(float *) ((char *) comp_result + i3*comp_nb[3] + i2*comp_nb[2] + i1*comp_nb[1] + i0*comp_nb[0]); | |
| result = *(float *) ((char *) tensor_data + i3*tensor->nb[3] + i2*tensor->nb[2] + i1*tensor->nb[1] + i0*tensor->nb[0]); | |
| } else if (tensor->type == GGML_TYPE_F16) { | |
| correct = ggml_fp16_to_fp32(*(ggml_fp16_t *) ((char *) comp_result + i3*comp_nb[3] + i2*comp_nb[2] + i1*comp_nb[1] + i0*comp_nb[0])); | |
| result = ggml_fp16_to_fp32(*(ggml_fp16_t *) ((char *) tensor_data + i3*tensor->nb[3] + i2*tensor->nb[2] + i1*tensor->nb[1] + i0*tensor->nb[0])); | |
| } else { | |
| std::cerr << "comp_size=" << comp_size << " but required is " << (i3*comp_nb[3] + i2*comp_nb[2] + i1*comp_nb[1] + i0*comp_nb[0]) << std::endl; | |
| } | |
| } else { | |
| std::cerr << "Missing debug code for type " << ggml_type_name(tensor->type) << std::endl; | |
| GGML_ASSERT(false); | |
| } | |
| if ((std::isnan(correct) != std::isnan(result)) || (std::isinf(correct) != std::isinf(result)) || !buffer_size_fit) { | |
| std::cerr << "ERROR: Invalid value in " << ggml_op_name(tensor->op) << " i3=" << i3 << " i2=" << i2 << " i1=" << i1 << " i0=" << i0 << " result=" << result << " correct=" << correct << " avg_err=" << (avg_err / counter) << std::endl; | |
| std::cerr << "tensor=" << tensor << " tensor->name=" << tensor->name << " tensor->backend: " << tensor->backend << " tensor->type: " << ggml_type_name(tensor->type) << " ne0=" << tensor->ne[0] << " nb0=" << tensor->nb[0] << " ne1=" << tensor->ne[1] << " nb1=" << tensor->nb[1] << " ne2=" << tensor->ne[2] << " nb2=" << tensor->nb[2] << " ne3=" << tensor->ne[3] << " nb3=" << tensor->nb[3] << " offset=" << tensor->view_offs << std::endl; | |
| if (src0 != nullptr) { | |
| std::cerr << "src0=" << src0 << " src0->name=" << src0->name << " op=" << ggml_op_name(src0->op) << " type=" << ggml_type_name(src0->type) << " backend=" << src0->backend << " ne0=" << src0->ne[0] << " nb0=" << src0->nb[0] << " ne1=" << src0->ne[1] << " nb1=" << src0->nb[1] << " ne2=" << src0->ne[2] << " nb2=" << src0->nb[2] << " ne3=" << src0->ne[3] << " nb3=" << src0->nb[3] << " offset=" << src0->view_offs << std::endl; | |
| } | |
| if (src1 != nullptr) { | |
| std::cerr << "src1=" << src1 << " src1->name=" << src1->name << " op=" << ggml_op_name(src1->op) << " type=" << ggml_type_name(src1->type) << " backend=" << src1->backend << " ne0=" << src1->ne[0] << " nb0=" << src1->nb[0] << " ne1=" << src1->ne[1] << " nb1=" << src1->nb[1] << " ne2=" << src1->ne[2] << " nb2=" << src1->nb[2] << " ne3=" << src1->ne[3] << " nb3=" << src1->nb[3] << " offset=" << src1->view_offs << std::endl; | |
| } | |
| std::cerr << "First error: result=" << first_error_result << " correct=" << first_error_correct << " i3=" << first_error[3] << " i2=" << first_error[2] << " i1=" << first_error[1] << " i0=" << first_error[0] << std::endl; | |
| std::cerr << std::endl << "Result:" << std::endl; | |
| ggml_vk_print_tensor_area(tensor, tensor_data, i0, i1, i2, i3); | |
| std::cerr << std::endl << "Correct:" << std::endl; | |
| ggml_vk_print_tensor_area(tensor, comp_result, i0, i1, i2, i3); | |
| std::cerr << std::endl; | |
| std::vector<const ggml_tensor *> done; | |
| ggml_vk_print_graph_origin(tensor, done); | |
| GGML_ASSERT(false); | |
| } | |
| if (first_error[0] == -1 && std::fabs(correct - result) > 0.1f) { | |
| first_error[0] = i0; | |
| first_error[1] = i1; | |
| first_error[2] = i2; | |
| first_error[3] = i3; | |
| first_error_result = result; | |
| first_error_correct = correct; | |
| } | |
| // Special case, value is infinite, avoid NaN result in avg_err | |
| // NaN also appears in results, if both are nan error is 0 | |
| if (!std::isinf(correct) && !std::isinf(result) && !std::isnan(correct) && !std::isnan(result)) { | |
| avg_err += std::fabs(correct - result); | |
| } | |
| counter++; | |
| } | |
| } | |
| } | |
| } | |
| avg_err /= counter; | |
| if (vk_output_tensor > 0 && vk_output_tensor == check_counter) { | |
| std::cerr << "TENSOR CHECK: avg_err=" << avg_err << " in " << ggml_op_name(tensor->op) << " (check " << check_counter << ")" << std::endl; | |
| std::cerr << "tensor=" << tensor << " tensor->name=" << tensor->name << " tensor->backend: " << tensor->backend << " tensor->type: " << ggml_type_name(tensor->type) << " ne0=" << tensor->ne[0] << " nb0=" << tensor->nb[0] << " ne1=" << tensor->ne[1] << " nb1=" << tensor->nb[1] << " ne2=" << tensor->ne[2] << " nb2=" << tensor->nb[2] << " ne3=" << tensor->ne[3] << " nb3=" << tensor->nb[3] << " offset=" << tensor->view_offs << std::endl; | |
| if (src0 != nullptr) { | |
| std::cerr << "src0=" << src0 << " op=" << ggml_op_name(src0->op) << " type=" << ggml_type_name(src0->type) << " backend=" << src0->backend << " ne0=" << src0->ne[0] << " nb0=" << src0->nb[0] << " ne1=" << src0->ne[1] << " nb1=" << src0->nb[1] << " ne2=" << src0->ne[2] << " nb2=" << src0->nb[2] << " ne3=" << src0->ne[3] << " nb3=" << src0->nb[3] << " offset=" << src0->view_offs << std::endl; | |
| } | |
| if (src1 != nullptr) { | |
| std::cerr << "src1=" << src1 << " op=" << ggml_op_name(src1->op) << " type=" << ggml_type_name(src1->type) << " backend=" << src1->backend << " ne0=" << src1->ne[0] << " nb0=" << src1->nb[0] << " ne1=" << src1->ne[1] << " nb1=" << src1->nb[1] << " ne2=" << src1->ne[2] << " nb2=" << src1->nb[2] << " ne3=" << src1->ne[3] << " nb3=" << src1->nb[3] << " offset=" << src1->view_offs << std::endl; | |
| } | |
| std::cerr << "First error: result=" << first_error_result << " correct=" << first_error_correct << " i3=" << first_error[3] << " i2=" << first_error[2] << " i1=" << first_error[1] << " i0=" << first_error[0] << std::endl; | |
| std::cerr << std::endl << "Result:" << std::endl; | |
| ggml_vk_print_tensor_area(tensor, tensor_data, 5, 5, 0, 0); | |
| std::cerr << std::endl << "Correct:" << std::endl; | |
| ggml_vk_print_tensor_area(tensor, comp_result, 5, 5, 0, 0); | |
| std::cerr << std::endl; | |
| std::cerr << std::endl << "Result:" << std::endl; | |
| ggml_vk_print_tensor_area(tensor, tensor_data, 5, 5, 1, 0); | |
| std::cerr << std::endl << "Correct:" << std::endl; | |
| ggml_vk_print_tensor_area(tensor, comp_result, 5, 5, 1, 0); | |
| std::cerr << std::endl; | |
| std::vector<const ggml_tensor *> done; | |
| ggml_vk_print_graph_origin(tensor, done); | |
| } | |
| if (avg_err > 0.05 || std::isnan(avg_err)) { | |
| std::cerr << "ERROR: avg_err=" << avg_err << " in " << ggml_op_name(tensor->op) << " (check " << check_counter << ")" << std::endl; | |
| std::cerr << "tensor=" << tensor << " tensor->name=" << tensor->name << " tensor->backend: " << tensor->backend << " tensor->type: " << ggml_type_name(tensor->type) << " ne0=" << tensor->ne[0] << " nb0=" << tensor->nb[0] << " ne1=" << tensor->ne[1] << " nb1=" << tensor->nb[1] << " ne2=" << tensor->ne[2] << " nb2=" << tensor->nb[2] << " ne3=" << tensor->ne[3] << " nb3=" << tensor->nb[3] << " offset=" << tensor->view_offs << std::endl; | |
| if (src0 != nullptr) { | |
| std::cerr << "src0=" << src0 << " op=" << ggml_op_name(src0->op) << " type=" << ggml_type_name(src0->type) << " backend=" << src0->backend << " ne0=" << src0->ne[0] << " nb0=" << src0->nb[0] << " ne1=" << src0->ne[1] << " nb1=" << src0->nb[1] << " ne2=" << src0->ne[2] << " nb2=" << src0->nb[2] << " ne3=" << src0->ne[3] << " nb3=" << src0->nb[3] << " offset=" << src0->view_offs << std::endl; | |
| } | |
| if (src1 != nullptr) { | |
| std::cerr << "src1=" << src1 << " op=" << ggml_op_name(src1->op) << " type=" << ggml_type_name(src1->type) << " backend=" << src1->backend << " ne0=" << src1->ne[0] << " nb0=" << src1->nb[0] << " ne1=" << src1->ne[1] << " nb1=" << src1->nb[1] << " ne2=" << src1->ne[2] << " nb2=" << src1->nb[2] << " ne3=" << src1->ne[3] << " nb3=" << src1->nb[3] << " offset=" << src1->view_offs << std::endl; | |
| } | |
| std::cerr << "First error: result=" << first_error_result << " correct=" << first_error_correct << " i3=" << first_error[3] << " i2=" << first_error[2] << " i1=" << first_error[1] << " i0=" << first_error[0] << std::endl; | |
| std::cerr << std::endl << "Result:" << std::endl; | |
| ggml_vk_print_tensor_area(tensor, tensor_data, first_error[0], first_error[1], first_error[2], first_error[3]); | |
| std::cerr << std::endl << "Correct:" << std::endl; | |
| ggml_vk_print_tensor_area(tensor, comp_result, first_error[0], first_error[1], first_error[2], first_error[3]); | |
| std::cerr << std::endl; | |
| std::vector<const ggml_tensor *> done; | |
| ggml_vk_print_graph_origin(tensor, done); | |
| GGML_ASSERT(false); | |
| } else { | |
| std::cerr << check_counter << " " << tensor->name << " op=" << ggml_op_name(tensor->op) << " backend=" << tensor->backend << " avg_err=" << avg_err << std::endl; | |
| } | |
| free(comp_result); | |
| comp_result = nullptr; | |
| comp_size = 0; | |
| if (tensor->backend == GGML_BACKEND_TYPE_GPU) { | |
| free(tensor_data); | |
| } | |
| } | |