problem stringlengths 66 76k | answer stringlengths 29 75.8k |
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Convert the following CUDA code to AMD GPU code:
cuda
#include "includes.h"
__global__ void vecProductKernel(float *d_z, const float *d_x, const float *d_y, unsigned int N)
{
int idx = blockIdx.x * blockDim.x + threadIdx.x;
if (idx < N) {
d_z[idx] = d_x[idx] * d_y[idx];
}
}
|
#include <hip/hip_runtime.h>
#include "includes.h"
__global__ void vecProductKernel(float *d_z, const float *d_x, const float *d_y, unsigned int N)
{
int idx = blockIdx.x * blockDim.x + threadIdx.x;
if (idx < N) {
d_z[idx] = d_x[idx] * d_y[idx];
}
} |
Convert the following CUDA code to AMD GPU code:
cuda
#include "includes.h"
__global__ void STREAM_Triad_double(double *a, double *b, double *c, double scalar, size_t len)
{
size_t idx = threadIdx.x + blockIdx.x * blockDim.x;
while (idx < len) {
c[idx] = a[idx]+scalar*b[idx];
idx += blockDim.x * gridDim.x;
}
}
|
#include <hip/hip_runtime.h>
#include "includes.h"
__global__ void STREAM_Triad_double(double *a, double *b, double *c, double scalar, size_t len)
{
size_t idx = threadIdx.x + blockIdx.x * blockDim.x;
while (idx < len) {
c[idx] = a[idx]+scalar*b[idx];
idx += blockDim.x * gridDim.x;
}
} |
Convert the following CUDA code to AMD GPU code:
cuda
#include <iostream>
#include "sys/time.h"
using namespace std;
double timeInSeconds (timeval& starttime, timeval& stopstime) {
return 1e-6*(1e6*(stopstime.tv_sec - starttime.tv_sec) + (stopstime.tv_usec - starttime.tv_usec));
}
__device__ double* dev_vector1 =... |
#include <hip/hip_runtime.h>
#include <iostream>
#include "sys/time.h"
using namespace std;
double timeInSeconds (timeval& starttime, timeval& stopstime) {
return 1e-6*(1e6*(stopstime.tv_sec - starttime.tv_sec) + (stopstime.tv_usec - starttime.tv_usec));
}
__device__ double* dev_vector1 = 0;
__device__ double* d... |
Convert the following CUDA code to AMD GPU code:
cuda
/******************************************************************************
*cr
*cr (C) Copyright 2010 The Board of Trustees of the
*cr University of Illinois
*cr All Rights Reserved
*cr
***********... | /******************************************************************************
*cr
*cr (C) Copyright 2010 The Board of Trustees of the
*cr University of Illinois
*cr All Rights Reserved
*cr
*****************************************************************... |
Convert the following CUDA code to AMD GPU code:
cuda
///*
// * LinearSysSolver.cpp
// *
// * Created on: Jul 8, 2013
// * Author: adm85
// */
//
//#include <vector>
//#include <iostream>
//#include <time.h>
//#include "LinearSysSolver.h"
//#include "cublas_v2.h"
//#include "cula.h"
//
//
//LinearSysSolver::Linea... |
#include <hip/hip_runtime.h>
///*
// * LinearSysSolver.cpp
// *
// * Created on: Jul 8, 2013
// * Author: adm85
// */
//
//#include <vector>
//#include <iostream>
//#include <time.h>
//#include "LinearSysSolver.h"
//#include "cublas_v2.h"
//#include "cula.h"
//
//
//LinearSysSolver::LinearSysSolver()
//{
// // T... |
Convert the following CUDA code to AMD GPU code:
cuda
// Each thread calculates fitness for one individual
// Result: vector of fitness
extern "C"
__global__ void fitness_kernel(int populationCnt, int *population,
int pointsCnt, float *pointsX, float *pointsY, float *result)
{
int i = blockIdx.x * blockDim.x +... |
#include <hip/hip_runtime.h>
// Each thread calculates fitness for one individual
// Result: vector of fitness
extern "C"
__global__ void fitness_kernel(int populationCnt, int *population,
int pointsCnt, float *pointsX, float *pointsY, float *result)
{
int i = blockIdx.x * blockDim.x + threadIdx.x;
if (i... |
Convert the following CUDA code to AMD GPU code:
cuda
#include "cuda_runtime.h"
#include <cstdio>
#include "time.h"
constexpr int segment_size = 1024;
constexpr int threads = 512;
__device__ char *pool;
void __global__ alloc(int **pointers) {
auto index = blockIdx.x * blockDim.x + threadIdx.x;
// pointers[index] ... | #include "hip/hip_runtime.h"
#include <cstdio>
#include "time.h"
constexpr int segment_size = 1024;
constexpr int threads = 512;
__device__ char *pool;
void __global__ alloc(int **pointers) {
auto index = blockIdx.x * blockDim.x + threadIdx.x;
// pointers[index] = (int *)malloc(segment_size);
pointers[index] = ... |
Convert the following CUDA code to AMD GPU code:
cuda
#include <algorithm>
#include <iostream>
#include <vector>
std::vector<double> add(std::vector<double> inarr1, std::vector<double> inarr2);
void test_integration()
{
constexpr size_t arr_size = 2 << 24;
std::cout << "Initializing test arrays...\n";
st... |
#include <hip/hip_runtime.h>
#include <algorithm>
#include <iostream>
#include <vector>
std::vector<double> add(std::vector<double> inarr1, std::vector<double> inarr2);
void test_integration()
{
constexpr size_t arr_size = 2 << 24;
std::cout << "Initializing test arrays...\n";
std::vector<double> arr1(a... |
Convert the following CUDA code to AMD GPU code:
cuda
#include "Output_Layer_GPU_Kernels.cuh"
__constant__ float anchors_416[10] = { 1.08, 1.19, 3.42, 4.41, 6.63, 11.38, 9.42, 5.11, 16.62, 10.52 };
__device__ float Sigmoid(float x)
{
float expValue = exp((double)-x);
float result = 1 / (1 + expValue);
return... | #pragma once
#include<hip/hip_runtime.h>
#include <math.h>
__device__ const int downsampleFactor = 32;
__device__ const int boundingBoxesPerGridCell = 5;
__device__ const float FLOAT_MIN = 1.17549435e-38;
//__global__ void BoundingBox_ConfidenceScores_Transform_Kernel(float* input, int inputHeight, int inputWidth);
... |
Convert the following CUDA code to AMD GPU code:
cuda
#include <stdio.h>
#include <cuda_runtime.h>
#include <assert.h>
int main(int argc, char **argv){
float *a_h, *b_h; // Host data
float *a_d, *b_d; // Device data
int N = 14, nBytes, i;
printf("Start allocating\n");
nBytes = N * sizeof(float... | #include <stdio.h>
#include <hip/hip_runtime.h>
#include <assert.h>
int main(int argc, char **argv){
float *a_h, *b_h; // Host data
float *a_d, *b_d; // Device data
int N = 14, nBytes, i;
printf("Start allocating\n");
nBytes = N * sizeof(float);
printf("Allocating in Host\n");
a_h = (... |
Convert the following CUDA code to AMD GPU code:
cuda
#include <cuda.h>
#define KERNEL_SIZE 3
#define BLOCK_SIZE 512
typedef signed int pixel_channel;
typedef unsigned long resolution;
__constant__ pixel_channel kernel_cuda[KERNEL_SIZE * KERNEL_SIZE];
pixel_channel kernel_host[KERNEL_SIZE * KERNEL_SIZE] = { -1, ... | #include <hip/hip_runtime.h>
#define KERNEL_SIZE 3
#define BLOCK_SIZE 512
typedef signed int pixel_channel;
typedef unsigned long resolution;
__constant__ pixel_channel kernel_cuda[KERNEL_SIZE * KERNEL_SIZE];
pixel_channel kernel_host[KERNEL_SIZE * KERNEL_SIZE] = { -1, -1, -1,
-1, 9, -1,
-1... |
Convert the following CUDA code to AMD GPU code:
cuda
#include <stdio.h>
__global__ void add(int a, int b, int *c) {
*c = a + b;
}
int main( void ) {
int c;
int *dev_c;
//Device Memory allocations
cudaError_t err = cudaMalloc((void**)&dev_c, sizeof(&dev_c));
if(err != cudaSuccess) {
... |
#include <hip/hip_runtime.h>
#include <stdio.h>
__global__ void add(int a, int b, int *c) {
*c = a + b;
}
int main( void ) {
int c;
int *dev_c;
//Device Memory allocations
hipError_t err = hipMalloc((void**)&dev_c, sizeof(&dev_c));
if(err != hipSuccess) {
printf("The error is %s\n",... |
Convert the following CUDA code to AMD GPU code:
cuda
#include <iostream>
#include <cuda.h>
#include <cuda_runtime.h>
#include <device_launch_parameters.h>
#include <memory>
/*CUDAлȡGPU豸*/
int main(void) {
int device_count = 0;
cudaGetDeviceCount(&device_count);
//ú֧CUDAGPU豸ĸ
if (device_count ==0)
{
printf("Th... | #include <iostream>
#include <hip/hip_runtime.h>
#include <memory>
/*CUDAлȡGPU豸*/
int main(void) {
int device_count = 0;
hipGetDeviceCount(&device_count);
//ú֧CUDAGPU豸ĸ
if (device_count ==0)
{
printf("There are no available device(s) that support CUDA\n");
}
else
{
printf("Detected %d CUDA Capable devic... |
Convert the following CUDA code to AMD GPU code:
cuda
#include <stdio.h>
#include <stdlib.h>
#include <cuda_runtime.h>
#include <device_launch_parameters.h>
#include <time.h>
#define AND 0
#define OR 1
#define NAND 2
#define NOR 3
#define XOR 4
#define XNOR 5
__global__ void computeLogicGates(char* d_input, char* d_o... | #include <stdio.h>
#include <stdlib.h>
#include <hip/hip_runtime.h>
#include <time.h>
#define AND 0
#define OR 1
#define NAND 2
#define NOR 3
#define XOR 4
#define XNOR 5
__global__ void computeLogicGates(char* d_input, char* d_output, int size) {
// calculate the index of the thread
int index = threadIdx.x ... |
Convert the following CUDA code to AMD GPU code:
cuda
#include "Matrix.cuh"
#include <cstring>
#include <fstream>
#include <ctime>
#include <device_functions.h>
#ifdef __CUDACC__
#define cuda_SYNCTHREADS() __syncthreads()
#else
#define cuda_SYNCTHREADS()
#endif
#define Zero ZeroCPU
#define PRINT_LOG false
//#define T... | #pragma once
#define BLOCK_SIZE 256
#include "hip/hip_runtime.h"
#include <stdio.h>
#include <string>
class Matrix
{
private:
unsigned int rows;
unsigned int cols;
double* mat;
public:
//getters
unsigned int getRows() const;
unsigned int getCols() const;
//constructors
Matrix(int cols, int rows, double* ma... |
Convert the following CUDA code to AMD GPU code:
cuda
#include "includes.h"
__global__ void multiply_by_itself_training_util_kernel( const float4 * __restrict input_buf, float4 * __restrict output_buf, int elem_count)
{
int elem_id = blockDim.x * blockIdx.x + threadIdx.x;
if (elem_id < elem_count)
{
float4 val = input_... |
#include <hip/hip_runtime.h>
#include "includes.h"
__global__ void multiply_by_itself_training_util_kernel( const float4 * __restrict input_buf, float4 * __restrict output_buf, int elem_count)
{
int elem_id = blockDim.x * blockIdx.x + threadIdx.x;
if (elem_id < elem_count)
{
float4 val = input_buf[elem_id];
val.x *= v... |
Convert the following CUDA code to AMD GPU code:
cuda
#include <algorithm>
#include <iostream>
#include <vector>
typedef unsigned long long data_t;
static inline void check(cudaError_t err, const char* context) {
if (err != cudaSuccess) {
std::cerr << "CUDA error: " << context << ": "
<< cu... |
#include <hip/hip_runtime.h>
#include <algorithm>
#include <iostream>
#include <vector>
typedef unsigned long long data_t;
static inline void check(hipError_t err, const char* context) {
if (err != hipSuccess) {
std::cerr << "CUDA error: " << context << ": "
<< hipGetErrorString(err) << st... |
Convert the following CUDA code to AMD GPU code:
cuda
#include <iostream>
using namespace std;
#define CUDA_CALL(ans) { gpuAssert((ans), __FILE__, __LINE__); }
inline void gpuAssert(cudaError_t code, const char *file, int line, bool abort=true)
{
if (code != cudaSuccess)
{
fprintf(stderr,"GPU assert: %s %... |
#include <hip/hip_runtime.h>
#include <iostream>
using namespace std;
#define CUDA_CALL(ans) { gpuAssert((ans), __FILE__, __LINE__); }
inline void gpuAssert(hipError_t code, const char *file, int line, bool abort=true)
{
if (code != hipSuccess)
{
fprintf(stderr,"GPU assert: %s %s %d\n", hipGetErrorString... |
Convert the following CUDA code to AMD GPU code:
cuda
extern "C"
__global__ void cuAdd(int n, float *a, float *b, float *result)
{
int i = blockIdx.x * blockDim.x + threadIdx.x;
if (i<n)
{
result[i] = a[i] + b[i];
}
}
extern "C"
__global__ void cuMult(int n, float *a, float *b, float *result)
... |
#include <hip/hip_runtime.h>
extern "C"
__global__ void cuAdd(int n, float *a, float *b, float *result)
{
int i = blockIdx.x * blockDim.x + threadIdx.x;
if (i<n)
{
result[i] = a[i] + b[i];
}
}
extern "C"
__global__ void cuMult(int n, float *a, float *b, float *result)
{
int i = blockIdx.x... |
Convert the following CUDA code to AMD GPU code:
cuda
#include<bits/stdc++.h>
using namespace std;
__global__ void vec_add(int N, int *A, int *B, int *C){
int i = threadIdx.x + blockIdx.x * blockDim.x;
// assert( i<N );
if(i < N) C[i] = A[i] + B[i];
}
int main(int argc, char *argv[]){
srand(0);
int N... |
#include <hip/hip_runtime.h>
#include<bits/stdc++.h>
using namespace std;
__global__ void vec_add(int N, int *A, int *B, int *C){
int i = threadIdx.x + blockIdx.x * blockDim.x;
// assert( i<N );
if(i < N) C[i] = A[i] + B[i];
}
int main(int argc, char *argv[]){
srand(0);
int N = 10000, block_size = 2... |
Convert the following CUDA code to AMD GPU code:
cuda
/*用gpu实现2个矩阵之间的乘法*/
#include<iostream>
#include<stdlib.h>
#include<sys/time.h>
#include<math.h>
#include"cuda_runtime.h"
using namespace std;
#define cols 1024
#define rows 1024
__global__ void multiply(float**Ad,float**Bd,float**Cd)
{
int x = blockDim.x*blockId... | /*用gpu实现2个矩阵之间的乘法*/
#include<iostream>
#include<stdlib.h>
#include<sys/time.h>
#include<math.h>
#include"hip/hip_runtime.h"
using namespace std;
#define cols 1024
#define rows 1024
__global__ void multiply(float**Ad,float**Bd,float**Cd)
{
int x = blockDim.x*blockIdx.x+threadIdx.x;
int y = blockDim.y*blockIdx.y+thr... |
Convert the following CUDA code to AMD GPU code:
cuda
#include <stdio.h>
__global__ void firstParallel()
{
printf("This is running in parallel.\n");
}
int main()
{
firstParallel<<<5, 5>>>();
cudaDeviceSynchronize();
}
|
#include <hip/hip_runtime.h>
#include <stdio.h>
__global__ void firstParallel()
{
printf("This is running in parallel.\n");
}
int main()
{
firstParallel<<<5, 5>>>();
hipDeviceSynchronize();
}
|
Convert the following CUDA code to AMD GPU code:
cuda
#include "cuda_runtime.h"
#include "device_launch_parameters.h"
#include <sys/time.h>
#include <stdio.h>
#include <stdlib.h>
#include <math.h>
__global__
void conv2(float *A, float *kernel,int inputSize, int depth, int kernelSize , int stride, int pad, float *B, ... | #include "hip/hip_runtime.h"
#include <sys/time.h>
#include <stdio.h>
#include <stdlib.h>
#include <math.h>
__global__
void conv2(float *A, float *kernel,int inputSize, int depth, int kernelSize , int stride, int pad, float *B, int outputSize) {
// 计算元素output(i,j)的值 一次卷积运算
int i = threadIdx.x + blockDim.x ... |
Convert the following CUDA code to AMD GPU code:
cuda
#include "includes.h"
__global__ void __stratifycounts(double *strata, int n, double *a, unsigned int *bi) {
__shared__ unsigned int ic[SNDVALS][SNDGRPS];
__shared__ double ss[SNDVALS];
int istart = (int)(((long long)blockIdx.x) * n / gridDim.x);
int iend = (int)((... |
#include <hip/hip_runtime.h>
#include "includes.h"
__global__ void __stratifycounts(double *strata, int n, double *a, unsigned int *bi) {
__shared__ unsigned int ic[SNDVALS][SNDGRPS];
__shared__ double ss[SNDVALS];
int istart = (int)(((long long)blockIdx.x) * n / gridDim.x);
int iend = (int)(((long long)(blockIdx.x+1... |
Convert the following CUDA code to AMD GPU code:
cuda
//#include <hayai/hayai.hpp>
//
//#include "btree.cuh"
//
//#include "concurrent-xfasttrie-fixture.cu"
//
//using BTREE = gpu::BTree<key_type, mapped_type>;
//using BTreeInsertionFixture = XTrieInsertionFixture<BTREE, Structure::BTREE>;
//using BTreeGetThreadFixture... |
#include <hip/hip_runtime.h>
//#include <hayai/hayai.hpp>
//
//#include "btree.cuh"
//
//#include "concurrent-xfasttrie-fixture.cu"
//
//using BTREE = gpu::BTree<key_type, mapped_type>;
//using BTreeInsertionFixture = XTrieInsertionFixture<BTREE, Structure::BTREE>;
//using BTreeGetThreadFixture = XTrieGetThreadFixture... |
Convert the following CUDA code to AMD GPU code:
cuda
#include "cuda_runtime.h"
#include "device_launch_parameters.h"
#include <stdio.h>
#include <stdlib.h>
#define MAX 65535
#define imin(a,b) (a<b?a:b)
const int arr_size =8;
const int threadsPerBlock = 256;
const int blocksPerGrid = imin(32,(arr_size +threadsPerBloc... | #include "hip/hip_runtime.h"
#include <stdio.h>
#include <stdlib.h>
#define MAX 65535
#define imin(a,b) (a<b?a:b)
const int arr_size =8;
const int threadsPerBlock = 256;
const int blocksPerGrid = imin(32,(arr_size +threadsPerBlock -1)/threadsPerBlock);
__global__ void kernel(float*arrA , float* arrB, float* arrC)
{... |
Convert the following CUDA code to AMD GPU code:
cuda
#include <stdio.h>
#include <stdlib.h>
#define N 5
#define BR() printf("\n")
#define BRS(str) printf("%s\n",str)
typedef struct {
int top;
int* data;
int stack_size;
}FIFO;
void exec();
void initialize_array(int*);
void print_array(int*);
int main(int argc,... |
#include <hip/hip_runtime.h>
#include <stdio.h>
#include <stdlib.h>
#define N 5
#define BR() printf("\n")
#define BRS(str) printf("%s\n",str)
typedef struct {
int top;
int* data;
int stack_size;
}FIFO;
void exec();
void initialize_array(int*);
void print_array(int*);
int main(int argc, char const *argv[]) {
... |
Convert the following CUDA code to AMD GPU code:
cuda
// nvcc -arch sm_21 -o test -run --keep --ptxas-options="-v" test.cu
#include <cuda.h>
#include <stdlib.h>
#include <stdio.h>
__global__ void transpose (int* Input, int* Output) {
}
| // nvcc -arch sm_21 -o test -run --keep --ptxas-options="-v" test.cu
#include <hip/hip_runtime.h>
#include <stdlib.h>
#include <stdio.h>
__global__ void transpose (int* Input, int* Output) {
}
|
Convert the following CUDA code to AMD GPU code:
cuda
#include <stdio.h>
#include <math.h>
#include <stdlib.h>
//Note that any functions that want to be called from the kernel must be preceeded with __device__
//Function we are integrating
__device__ float myFunction(float x){
return pow(x,4);
}
//Trapezoidal rule... |
#include <hip/hip_runtime.h>
#include <stdio.h>
#include <math.h>
#include <stdlib.h>
//Note that any functions that want to be called from the kernel must be preceeded with __device__
//Function we are integrating
__device__ float myFunction(float x){
return pow(x,4);
}
//Trapezoidal rule calculation
__device__ ... |
Convert the following CUDA code to AMD GPU code:
cuda
#include "cuda_runtime.h"
#include "stdio.h"
#include "stdlib.h"
#include "string.h"
#include "time.h"
#define A_w 50
#define A_h 50
#define B_w 32
#define B_h 32
typedef struct{
int width;
int height;
float * elements;
}Matrix;
// #define
void rightKronecke... | #include "hip/hip_runtime.h"
#include "stdio.h"
#include "stdlib.h"
#include "string.h"
#include "time.h"
#define A_w 50
#define A_h 50
#define B_w 32
#define B_h 32
typedef struct{
int width;
int height;
float * elements;
}Matrix;
// #define
void rightKronecker1(Matrix A, Matrix B, Matrix C){
for(int c_row=0;... |
Convert the following CUDA code to AMD GPU code:
cuda
/* Block size X: 32 */
__global__ void fct_ale_b2(const int maxLevels, const double dt, const double fluxEpsilon, const int * __restrict__ nLevels, const double * __restrict__ area_inv, const double * __restrict__ fct_ttf_max, const double * __restrict__ fct_ttf_min... |
#include <hip/hip_runtime.h>
/* Block size X: 32 */
__global__ void fct_ale_b2(const int maxLevels, const double dt, const double fluxEpsilon, const int * __restrict__ nLevels, const double * __restrict__ area_inv, const double * __restrict__ fct_ttf_max, const double * __restrict__ fct_ttf_min, double * __restrict__ ... |
Convert the following CUDA code to AMD GPU code:
cuda
#include "includes.h"
using namespace std;
__global__ void setValue(float *data, int idx, float value) {
if(threadIdx.x == 0) {
data[idx] = value;
}
}
|
#include <hip/hip_runtime.h>
#include "includes.h"
using namespace std;
__global__ void setValue(float *data, int idx, float value) {
if(threadIdx.x == 0) {
data[idx] = value;
}
} |
Convert the following CUDA code to AMD GPU code:
cuda
#include "includes.h"
__device__ float sigmoid(float x) {
return 1.0f / (1 + __expf(-x));
}
__global__ void sigmoidActivationForward(float* Z, float* A, int Z_x_dim, int Z_y_dim) {
int index = blockIdx.x * blockDim.x + threadIdx.x;
if (index < Z_x_dim * Z_y_dim) {... |
#include <hip/hip_runtime.h>
#include "includes.h"
__device__ float sigmoid(float x) {
return 1.0f / (1 + __expf(-x));
}
__global__ void sigmoidActivationForward(float* Z, float* A, int Z_x_dim, int Z_y_dim) {
int index = blockIdx.x * blockDim.x + threadIdx.x;
if (index < Z_x_dim * Z_y_dim) {
A[index] = sigmoid(Z[in... |
Convert the following CUDA code to AMD GPU code:
cuda
#include <stdio.h>
#include <time.h>
#include <stdlib.h>
#include <sys/time.h>
// #define NUM_PARTICLES 10000
// #define NUM_ITERATIONS 10000
// int TPB = 16;
#define SEED 10
#define EPSILON 1e-5
typedef struct {
float3 position;
float3 velocity;
} Partic... |
#include <hip/hip_runtime.h>
#include <stdio.h>
#include <time.h>
#include <stdlib.h>
#include <sys/time.h>
// #define NUM_PARTICLES 10000
// #define NUM_ITERATIONS 10000
// int TPB = 16;
#define SEED 10
#define EPSILON 1e-5
typedef struct {
float3 position;
float3 velocity;
} Particle;
// Deterministical... |
Convert the following CUDA code to AMD GPU code:
cuda
__device__ void rot_x(float3 *vec, float angle)
{
float tmp;
tmp = vec->y;
vec->y = tmp * cosf(angle) + vec->z * -sinf(angle);
vec->z = tmp * sinf(angle) + vec->z * cosf(angle);
}
__device__ void rot_y(float3 *vec, float angle)
{
float tmp;
tmp =... |
#include <hip/hip_runtime.h>
__device__ void rot_x(float3 *vec, float angle)
{
float tmp;
tmp = vec->y;
vec->y = tmp * cosf(angle) + vec->z * -sinf(angle);
vec->z = tmp * sinf(angle) + vec->z * cosf(angle);
}
__device__ void rot_y(float3 *vec, float angle)
{
float tmp;
tmp = vec->x;
vec->x = tmp ... |
Convert the following CUDA code to AMD GPU code:
cuda
#include "includes.h"
__global__ void cuSetupSincKernel_kernel(float *r_filter_, const int i_filtercoef_, const float r_soff_, const float r_wgthgt_, const int i_weight_, const float r_soff_inverse_, const float r_beta_, const float r_decfactor_inverse_, const float... |
#include <hip/hip_runtime.h>
#include "includes.h"
__global__ void cuSetupSincKernel_kernel(float *r_filter_, const int i_filtercoef_, const float r_soff_, const float r_wgthgt_, const int i_weight_, const float r_soff_inverse_, const float r_beta_, const float r_decfactor_inverse_, const float r_relfiltlen_inverse_)
... |
Convert the following CUDA code to AMD GPU code:
cuda
#include "includes.h"
using namespace std;
struct compressed_sparse_column {
int* data;
int* row;
int* column;
int* index_column;
int* index_row_start;
int* index_row_end;
};
struct graph {
compressed_sparse_column* dataset;
bool* roots;
bool* leaves;
bool* singl... |
#include <hip/hip_runtime.h>
#include "includes.h"
using namespace std;
struct compressed_sparse_column {
int* data;
int* row;
int* column;
int* index_column;
int* index_row_start;
int* index_row_end;
};
struct graph {
compressed_sparse_column* dataset;
bool* roots;
bool* leaves;
bool* singletons;
int vertices;
int... |
Convert the following CUDA code to AMD GPU code:
cuda
#include "includes.h"
__global__ void gpu_transpo_kernel_naive(u_char *Source, u_char *Resultat, unsigned width, unsigned height){
int j = blockIdx.x*blockDim.x + threadIdx.x;
int i = blockIdx.y*blockDim.y + threadIdx.y;
if ((i<0)||(i>=height)||(j<0)||(j>=width)) {... |
#include <hip/hip_runtime.h>
#include "includes.h"
__global__ void gpu_transpo_kernel_naive(u_char *Source, u_char *Resultat, unsigned width, unsigned height){
int j = blockIdx.x*blockDim.x + threadIdx.x;
int i = blockIdx.y*blockDim.y + threadIdx.y;
if ((i<0)||(i>=height)||(j<0)||(j>=width)) {}
else {
Resultat[j*heig... |
Convert the following CUDA code to AMD GPU code:
cuda
#include <cstdio>
#include <cstdlib>
#include <time.h>
#include "cuda_timer.cuh"
#define SafeTimerCall(err) __safeTimerCall(err, __FILE__, __LINE__)
inline void __safeTimerCall(cudaError err, const char *file, const int line) {
#pragma warning(push)
#pragma warni... | #include <hip/hip_runtime.h>
class CudaTimer
{
private:
hipEvent_t _begEvent;
hipEvent_t _endEvent;
public:
CudaTimer();
~CudaTimer();
void start();
void stop();
float value();
};
|
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