gather - scatter ( vector addressing )
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this article is about the vector addressing type. for the i / o method, see vectored i / o .
gather - scatter instructions may not be the optimal choice of instructions when you are trying to achieve superior performance on the intel® xeon phi™ coprocessor. however, if your code uses indirect addressing or performs non - unit strided memory accesses, gather - scatter instructions may be the best option. this document reveals the operation of gather - scatter instructions and introduces - opt - gather - scatter - unroll, a new compiler switch added to intel® c + + compiler 14. 0 and intel® fortran compiler 14. 0 that may provide improvements in certain codes that use gather - scatter instructions .
note that the gather - scatter - unroll compiler switch may not provide a performance improvement for all codes. its primary target are codes that use indirect addressing or perform non - unit strided memory accesses .
high performance computers are centered around the concept of vector processing. the first super - computer generation is single processor oriented. the last trends introduce parallel processing concepts in this field (e. g. cray 2). in this context, we propose to associate a specialized processor in vector addressing to vector processors. this one takes in charge the whole computation required to access either a contiguous vector, or a sparsed vector controlled by an index vector (gather / scatter operations). an elementary vector access processor is in charge of vector operand fetching with a limited length. a modular cluster will increase length of fetched vectors .
• fetching non - contiguous data elements from memory using vector - index memory addressing. these “gather” instructions introduce a new memory - addressing form, consisting of a base register and multiple indices specified by a vector register (either xmm or ymm). data elements sizes of 32 and 64 - bits are supported, and data types for floating - point and integer elements are also supported .
on page 488, pdep and pext are parallel bits deposit and parallel bits extract. they are essentially scatter / gather instructions for bits .
fig. 13 illustrates a flow diagram of a process for packed loading and storing of data in a gather / scatter distribution in accordance with an embodiment .
as shown in the above two examples, gather - scatter instructions are generally followed by a conditional branching instruction which is used to test whether the gather - scatter is complete and re - trigger the instruction if it is not. however, this conditional branching is an added overhead to the execution of the program .
before we dive into the details of how and when to use the compiler switch and why it even works, let us review the operation of gather - scatter instructions .
the operation of the scatter instructions is very similar to that of the corresponding gather instructions. the only difference being that the instruction stores data elements into the memory instead of loading them into an output vector register. similar to the gather instructions, only those elements will be stored into memory for which the corresponding mask bits are set .
in certain cases, a programmer may know that in his application, most gather - scatter sequences take n number of invocations for completion. in such cases, the programmer may use the - gather - scatter - unroll = n compiler switch to hint the compiler to unroll the re - trigger loop n times, thereby alleviating the overhead caused by the branching instructions .
the write mask register, also known as the source mask, plays an important role in the operation of the gather. the mask register has one bit corresponding to each element that can be held by the output vector register. the elements of the mask register for which the corresponding bit is set are known as the active elements. in a gather instruction, data is loaded from memory to the vector register for only the active elements of the vector. on a given invocation of a gather instruction, the following operations are performed :
in the following code, we know (based on prior information) that all the data elements are widely scattered in memory and, in general, will need 16 invocations of the gather - scatter instructions. in this case, we can add a “ - gather - scatter - unroll = 8 ” switch to the compiler call. we use an unroll factor of 8 as this is the greatest unroll factor allowed by the compiler. the compiler will unroll the loop, alleviating the overhead incurred due to the branching instructions. the unrolled code generated by the compiler with the “ - gather - scatter - unroll = 8 ” switch is shown below :
…ulations when loading from an address that' s computed by adding two registers together, x86 can scale one of them by 2, 4, or 8, for free as part of the addressing calculation. this change makes the code generated for gather and scatter use this. for the cases where gather / scatter is based on a base pointer and an integer offset vector, the gsimprovementspass looks to see if the integer offsets are being computed as 2 / 4 / 8 times some other value. if so, it extracts the 2x / 4x / 8x part and leaves the rest there as the the offsets. the { gather, scatter } _ base _ offsets _ * functions take an i32 scale factor, which is passed to them, and then they carefully generate ir so that it hits llvm' s pattern matching for these scales. this is particular win on avx, since it saves us two 4 - wide integer multiplies. noise runs 14% faster with this. issue # 132 .
as with the gather instruction, memory is accessed at a granularity of 64 bytes, and hence all the elements present in a given 64 bytes of memory are “scattered” in a single invocation of the scatter instruction. again, a scatter instruction will generally be re - executed (i. e. re - triggered) until all the required data has been stored to memory .
i suspect that for these ones, it' s going to be good - this looks too fundamental to the sorts of changes first described in larrabee programming guides. the hope is that many of these functions (conditional loads, scatter / gather, etc) will allow a much larger proportion of loops to be parallelized than is currently the case. obviously not everything is amenable to parallelization due to serial dependencies, but having scatter / gather to do multiple load / store stuff makes it a lot easier .
6. the method of claim 5, wherein a plurality of addresses of the second plurality of non - contiguous locations in the memory of the data elements to scatter are distributed in separate register file elements of the vector computation register file .
due to the special behavior of the mask register, it can be used to allow conditional looping of the gather instruction until all the elements from a given write mask have been successfully loaded. a typical usage of a gather instruction along with the re - trigger loop is shown below :
in this example, since the compiler has no prior information as to the order that data elements of arr2 will be accessed, the compiler will generate gather - scatter instructions to load the different data elements into a vector register and to store those data elements back to memory once the data elements have been incremented. without the switch, the code generate by the compiler will look similar to the following :
each processing slice within the processing element 400 includes a memory access pipeline (load / store pipeline) and an arithmetic pipeline. managing flow through the lsu 420 as a load / store pipeline can enable computation of one address per vector data element or sub - element, and facilitates the gathering and scattering of data from and to memory. gather / scatter capabilities provide access to data stored in non - contiguous memory locations by realizing multiple vector data element accesses simultaneously, despite their disjoint distribution in non - contiguous memory. the processing element 400 provides the ability to perform associated fixed - point effective address (i. e. , virtual address) computations to support gather - scatter functionality. the arithmetic pipeline through the alu 418 can include a robust assortment of floating - point and fixed - point operations to support a variety of workloads .
• vector shift instructions with per - element shift count. data elements sizes of 32 and 64 - bits are supported .
the sparse scatter, denoted y | _ x \ leftarrow x is the reverse operation. it copies the nonzero values of sparse x into the corresponding locations in the dense vector y, i. e. y (idx (i) ) = x (i) .
packing a second number of the data elements into less than the width of the register file elements of the vector computation register file .
consider the vgatherdps instruction which gathers a float32 vector using signed dword indices. the inputs and outputs of the vgatherdps instruction are shown below :
if multiple data elements required by the gather sequence are present in the 64 bytes then all the corresponding elements of the output register are updated with the values from the accessed memory .
miura k. (2011) fujitsu vector computers. in: padua d. (eds) encyclopedia of parallel computing. springer, boston, ma
> primitives for permutations of bits, see section 1. 29. 2 on page 81. a bit - gather and a bit - scatter instruction for sub - words of all sizes a power of 2 would allow for arbitrary permutations (see [ fxt: bits / bitgather. h ] and [ fxt: bits / bitseparate. h ] for versions working on complete words) .
in embodiments, processing elements are implemented as vector processors. in a vector processor, memory accesses and arithmetic instructions can act upon full vectors or generally continuous portions of vectors, where vectors enable parallel processing on multiple data elements. for some operations, memory accesses or calculations for randomly distributed elements of the vectors may be immaterial. to reduce traffic through a memory hierarchy, and the associated energy consumed, by unnecessary memory accesses, the vector processors include vector mask register files for use in predication of instructions and as targets of comparison instructions. predication of instructions allows for selective execution of certain elements of the vectors based on a mask .
note that during a single invocation of the gather instruction, only 64 bytes of memory are accessed and the output register is updated with only those elements that are present in these 64 bytes. since gather instructions are generally used to fetch data elements that are dispersed in memory, it is unlikely that the all required data elements will be present in the accessed 64 bytes of memory. hence, it is generally required for the programmer to execute gather statements in a loop until all the required data elements have been loaded into the output register. as each data element is gathered, the corresponding bit in the write mask register is reset. the completion of the gather sequence is signaled by the write mask register being zero, i. e. when all the bits of the mask register have been cleared (zero) .
david a patterson, lecture 6: vector processing, 1998, 60 pages, retrieved from the internet on may 7, 2015, retrieved from url < urltoken > .
pdep uses a mask in the second source operand (the third operand) to transfer / scatter contiguous low order bits in the first source operand (the second operand) into the destination (the first operand) .
these are extremely interesting instructions. it' s worth noting, however, that things like gather / scatter live and die by the quality of their implementation. i would hope that these are considered worth delivering high - quality implementations, but let' s just say that intel has occasionally been known to deliver complex instructions that are all but useless due to poor latency and reciprocal throughput. sse4. 2, i' m looking at you .
although the example process 1300 of fig. 13 has been described in reference to gathering data elements followed by scattering data elements, it will be understood that data elements can be scattered and then gathered. furthermore, multiple gather and scatter load / store commands can be initiated in parallel across multiple processing slices in the processing element 400. scattering and gathering can reference a common data set to read / modify / store distributed data values or can operate on different data sets, where a first data set is gathered - read, processed, and a resulting second data set is scattered - written to different non - contiguous memory locations. additionally, scattering and gathering may be performed independently of each other, where non - contiguous data is gathered, processed and stored contiguously (no - scatter) or contiguous data can be read (no gather), processed, and scattered - written non - contiguously .
matsuura t, miura k, makino m (1985) supervector performance without toil: fortran implemented vector algorithms on the vp - 100 / 200. comput phys commun 37: 101–107
at the processing slice level, computation can occur on floating - point and fixed - point data types at, for example, a 64 - bit granularity in a temporal simd manner on 64 - bit vector elements, and in a temporal and spatial simd manner on narrower vector sub - elements, which can be 32 - bits, 16 - bits, or 8 - bits wide .
packing and loading the set of data elements into a set of register file elements of a third register file entry of the vector computation register file by the processing element based on the second instruction .
miura k (1986) fujitsu s supercomputer: facom vector processor system. in: fernbach s (ed) supercomputers: class vi systems, hardware and software. north - holland, amsterdam, pp 137–152
scattering and storing, by the processing element, the plurality of data elements to a plurality of non - contiguous locations in the memory based on the instruction and a plurality of addresses in parallel with performing the at least one sub - instruction accessing the register file entries of the scalar computation register file, wherein each of the plurality of data elements is individually addressable and is narrower than a width of the plurality of register file elements of the vector computation register file, wherein an address of one of the non - contiguous locations in the memory of each of the data elements to scatter is distributed in each of at least two separate register file elements of a first register file entry of the register file entries of the vector computation register file .
7. the method of claim 6, wherein the addresses of the second plurality of non - contiguous locations in the memory of the data elements to scatter are different addresses than the addresses of the first plurality of non - contiguous locations in the memory from which the data elements are gathered .
for the case where the element size is 2, 4, or 8, we' d like take advantage of the free scale by 2 / 4 / 8 in the x86 address calculation ops. it should be pretty straightforward to update one of the gather / scatter optimizations to do this; the trick is to emit a pattern that llvm identifies. early experiments suggest that for the i32 offset case, the key is to sext to i64 first, then do a scalar multiply by 2 / 4 / 8, then gep with base address and the offset before the load / store .
17. the method of claim 16, wherein the plurality of addresses of the non - contiguous locations in the memory of the data elements to scatter are different addresses than the plurality of addresses of the set of non - contiguous locations in the memory from which the set of data elements are gathered .
fig. 13 depicts an example process 1300 for packed loading and storing of data in a gather / scatter distribution in an active memory device, such as the active memory devices of figs. 1 - 3. the blocks depicted in fig. 13 may be performed by one of the processing elements of figs. 1 - 4 in an active memory device. for example, the blocks may be performed by a processing element in an active memory device, where the processing element accesses portions of memory (e. g. , memory vaults sharing a stack with the processing element) and performs operations on data accessed from the memory. for purposes of explanation, the processing element is described in reference to processing element 400 of fig. 4. although fig. 13 is described relative to an active memory device, it will be understood that the process of fig. 13 can be implemented in systems that include a processing element 400 in communication with memory in other configurations, such as memory located remotely from the processing element 400. accordingly, the processing element 400 need not be located within an active memory device and can perform gather / scatter operations on remotely located memory including, for example, memory located in a separate active memory device .
fig. 7 is similar to the example of fig. 6, where data in memory 702 has the same width as the register file elements 704 a - 704 f of register file entry 705 in vector register file 703, but with the data is scattered in memory 702 rather than contiguous. since processing element 400 supports the gathering and scattering of data from / to memory, the processing element 400 can load data element values a - f in fig. 7 into the register file elements 704 a - 704 f of register file entry 705, with the result being that the data ends up in the vector register file 703 exactly the same as it did in vector register file 603 in fig. 6 when the data was contiguous in memory 602 .
fig. 9 is similar to the example of fig. 8, where data in memory 902 has a narrower width than the register file elements 904 a - 904 f of register file entry 905 in vector register file 903, but with the data scattered in memory 902 rather than contiguous. since processing element 400 supports the gathering and scattering of data to / from memory including narrower width data, the processing element 400 can load data element values a - f in fig. 9 into the register file elements 904 a - 904 f of register file entry 905, with the result being that the data ends up in the vector register file 903 exactly the same as it did in vector register file 803 in fig. 8 when the data was contiguous in memory 802 .
• cross - lane functionalities are provided with several new instructions for broadcast and permute operations. some of the 256 - bit vector integer instruc - tions promoted from legacy sse instruction sets also exhibit cross - lane behavior, e. g. vpmovz / vpmovs family .
miura k, uchida k (1984) facom vector processor vp - 100 / vp - 200. in: kowalik js (ed) high - speed computation, nato asi series f: computer and systems sciences, vol 7. springer, berlin, pp 127–138
13. the method of claim 12, wherein the vector computation register file is accessible by the load - store unit and the arithmetic - logic unit, wherein each of the plurality of addresses comprises a greater width than a width of each of the plurality of data elements .
miura k, nagakura h, tamura h (1991) vp2000 series dual scalar and quadruple scalar models supercomputer systems – a new concept in vector processing. in: proceedings of compcon spring 91, san francisco, ca. ieee computer society press, washington, dc, pp 294–302
16. the method of claim 15, wherein packing and loading the set of data elements into the set of register file elements by the processing element based on the second instruction further comprises distributing the set of packed data elements into fewer register file elements than are consumed by a plurality of addresses of the set of the non - contiguous locations in the memory to gather .
fujitsu vector machines are the series of supercomputers developed by fujitsu from 1976 to 1999. they are based on the pipeline architecture, and vpp systems have also incorporated a high degree of parallelism with distributed memory in the system architecture, utilizing the full crossbar network for non - blocking system interconnect .
overall it' s like a wet dream for bit - bashers. pdep? pext? byte field extract? scatter? 256 - bit integer simd? i was almost too excited to speak when i first skimmed this (moderated somewhat by the 2013 release date and lingering concerns that some of the better insns will have latency 8 and reciprocal throughput 5 or something disappointing like that) .
a vector processor may support multiple memory accesses in parallel. when data types being accessed have different widths, particularly smaller than a nominal width, gathering the data in parallel and storing the data in parallel can result in inefficient use of memory, such as leaving potentially unusable gaps between data elements stored and read from memory .
fig. 11 shows an embodiment, whereby narrower data is scattered throughout memory 1102, yet is still loaded and packed into fewer register file elements 1104 a - 1104 c of register file entry 1105 in vector register file 1103 than in register file elements 904 a - 904 f of register file entry 905 of fig. 9 .
fig. 12 illustrates an example of packed loading and storing of data in a gather / scatter distribution in accordance with an embodiment. in fig. 12, narrower data is scattered throughout memory 1202, yet is still loaded and packed into fewer register file elements 1204 a - 1204 c of register file entry 1205 in vector register file 1203 than in register file elements 904 a - 904 f of register file entry 905 of fig. 9. fig. 12 also depicts that addresses of the narrow data elements can be distributed over register file elements 1206 a - 1206 u of register file entry 1207, extending to a greater number of register file elements than the number used to hold the data associated with the addresses in register file elements. for example, data element values a - u are packed into register file elements 1204 a - 1204 c of register file entry 1205, but the addresses associated with the data element values a - u are distributed between register file elements 1206 a - 1206 u of register file entry 1207. additionally, in the example of fig. 12, the width of address elements is the same as the register file elements 1206 a - 1206 u (8 bytes wide) in vector register file 1203, while the data element values are 1 byte wide. additionally, the processing element 400 can support packing and accessing less than the full width of the register file elements, such as register file element 1204 c of register file entry 1205 that only packs 5 of 8 bytes .
3. the method of claim 2, wherein packing and loading the data elements into the one or more of the register file elements further comprises distributing the packed data elements into fewer register file elements than are consumed by the addresses, and the second register file entry is subsequent to the first register file entry in the vector computation register file .
fig. 10 is an example of narrower data types arranged contiguously in memory 1002 being packed into fewer register file elements 1004 a - 1004 c of register file entry 1005 in vector register file 1003 than in register file elements 904 a - 904 f of register file entry 905 of fig. 9. the data can be loaded as if the data type was the same as in fig. 6, since it is arranged contiguously .
in exemplary embodiments, the processing element 400 supports gathering and scattering of narrow data types to / from memory into a register file, such as the vcr 414, in a packed fashion in addition to other size and distribution patterns. fig. 6 shows data which is arranged in memory 602 in a contiguous manner, and which has the same width as the register file elements 604 a - 604 f. the data is loaded into the vector elements of an entry of a vector register file 603, such as vcr 414, having a multiplicity of elements associated with each addressable entry. in the example of fig. 6, each of the register file elements 604 a - 604 f of register file entry 605 includes 8 bytes (64 bits), and data element values a - f each include 8 byes (64 - bits) arranged contiguously across 32 - bytes of memory 602 .
avx2 promotes the vast majority of 128 - bit integer simd instruction sets to operate with 256 - bit wide ymm registers. avx2 instructions are encoded using the vex prefix and require the same operating system support as avx. generally, most of the promoted 256 - bit vector integer instructions follow the 128 - bit lane operation, similar to the promoted 256 - bit floating - point simd instructions in avx. newer functionalities in avx2 generally fall into the following categories :
at block 1312, the processing element 400 scatters and stores data elements to non - contiguous locations in memory based on the second instruction. similar to gathering, scattering can be managed using the vcr 414, lsu 420, and erat 422, as well as the lsq 404. the lsq 404 can control sequencing of gathering and scattering based on addresses generated by the lsu 420 and translated by the erat 420. the addresses of the non - contiguous locations in the memory of the data elements to scatter can be different addresses than the non - contiguous locations in the memory from which the data elements are gathered .
fig. 8 shows an arrangement of a narrower data type in a contiguous manner in memory 802. the data element values a - f are loaded into register file elements 804 a - 804 f of a register file entry 805, with the extra space of the wider registers left vacant. for example, the data element values a - f are each 1 byte wide in fig. 8 while the register file elements 804 a - 804 f of a register file entry 805 are each 8 bytes wide in vector register file 803 .
packing and loading the data elements into one or more of the register file elements of a second register file entry of the register file entries of the vector computation register file by the processing element based on the instruction, such that at least two of the data elements gathered from the first plurality of non - contiguous locations in the memory are packed and loaded into a single register file element of the second register file entry as a plurality of packed data elements in parallel with performing the at least one sub - instruction accessing the register file entries of the scalar computation register file .
at block 1304, the processing element 400 gathers a plurality of individually addressable data elements from non - contiguous locations in the memory which are narrower than a nominal width of register file elements in the processing element 400 based on the instruction. for example, the vcr 414 of the processing element 400 can include a plurality of register file entries, where each of the register file entries includes a plurality of register file elements. in the example of fig. 12, each register file element per register file entry has a width of 8 bytes (64 bits) and supports data elements as narrow as 1 byte (8 bits). addresses of the non - contiguous locations in the memory of the data elements to gather may be distributed in separate register file elements of a register file entry in the vcr 414. the lsu 420 can use the addresses from the vcr 414 to gather data elements from non - contiguous locations in memory, where each address in the vcr 414 can map to an independent data element to be gathered as part of a single instruction. as previously described, the lsu 420 can operate in parallel with other units, such as alu 418. the addresses in the vcr 414 can be translated into a physical address by the erat 422. as can be seen in the example of fig. 12, the addresses in the vcr 414 can have a greater width than a width of the data elements (e. g. , 8 bytes vs. 1 byte) .
in an embodiment, the active memory devices include stateless processing elements within a memory cube. processing elements appear to a program in the main processor as long latency functional units. the processing elements themselves are programmable engines, comprising an instruction buffer, an instruction unit, including branching capability and instruction decode, a mixture of vector, scalar, and mask register files, a plurality of load / store units for the movement of data between memory and the register files, and a plurality of execution units for the arithmetic and logical processing of various data types. also included are address translation capabilities for converting program virtual addresses to real addresses, a unified load / store queue to sequence data movement between the memory and the processing elements, and a processor communications unit, for communication with the main processor .
programs configured to execute on the processing element 400 can contain data types of different widths, and the data may be located in a contiguous manner in memory, or it may be scattered about in a random fashion. the processing element 400, which supports multiple - sized data types within its register files such as in vcr 414 and scr 416, can load its register files with any data type that is arranged in a contiguous manner. the processing element 400 can also support the gathering and scattering of each data type into one entry or vector element of the register files. rather than limiting register file entries or elements to a fixed bit width or leaving vacant space within an entry or element when loading a data type of a size less than the nominal width of the register file, the processing element 400 can pack smaller data types, whether or not they are arranged in a contiguous manner in memory .
fig. 4 depicts an example of a processing element 400 coupled to an interconnect network 402 as an embodiment of one of the processing elements of figs. 1 - 3. the processing element 400 is a programmable vector processing element, situated in an active memory device, such as one of the active memory devices of figs. 1 - 3. in the example of fig. 4, the processing element 400 includes a load - store queue (lsq) 404 coupled to the interconnect network 402 and to an instruction buffer 406. the instruction buffer 406 is also coupled to a lane control unit (lcu) 408 and a decoder 410. a processor communication unit (pcu) 412 provides a communication interface between the processing element 400 and the main processor or other processing elements through the interconnect network 402. the lsq 404 is also coupled to a vector computation register file (vcr) 414 and a scalar computation register file (scr) 416. the vcr 414 and scr 416 are coupled through multiple multiplexers to an arithmetic logic unit (alu) 418 and a memory - access unit 420, also referred to as a load - store unit (lsu) 420. the alu 418 is coupled to itself and to the lsu 420 through multiplexers, and is also coupled to the vcr 414 and the scr 416. the lsu 420 may also be coupled to itself, to the lsq 404, to an effective - to - real address translation unit (erat) 422, to the vcr 414 and to the scr 416 (all connections not depicted). the erat 422 is also coupled to the lsq 404. as will be appreciated, numerous other connections and elements can be included in the processing element 400. for example, connections between the decoder 410 and other elements are not depicted for clarity. additionally, depicted connections in fig. 4 can be modified or omitted, such as the depicted connection between decoder 410 and pcu 412 .
at block 1310, the processing element 400 unpacks data elements from the register file entry based on the second instruction. the unpacking of the data elements from the register file entry by the processing element 400 based on the second instruction can include reading the packed data elements as narrower data types (e. g. , 1 byte) and reading the addresses as wider data types (e. g. , 8 bytes). the processing element 400 can unpack at least a first number of data elements filling the nominal width of register file elements, such as 8 1 - byte data elements from register file element 1204 a of register file entry 1205, and unpack a second number of data elements occupying less than the nominal width of register file elements, such as 5 1 - byte data elements from register file element 1204 c of register file entry 1205, where the register file elements in the vector register file 1203 are 8 bytes wide in the example of fig. 12 .
at block 1306, the processing element 400 packs and loads the data elements into a register file entry based on the instruction, such that at least two of the data elements gathered from non - contiguous locations in the memory are packed and loaded into a single register file element. packing and loading the data elements into the register file elements by the processing element 400 based on the instruction can include distributing the packed data elements into fewer register file elements than are consumed by the addresses. for example, in fig. 12, each address is one 8 - byte entry distributed over register file elements 1206 a - 1206 u of register file entry 1207, for a total of 21 full register file elements in register file entry 1207. the data elements associated with the addresses are packed 8: 1 into three register file elements 1204 a - 1204 c of register file entry 1205, for a total of two full and one partial register file elements. therefore, only 21 bytes are occupied for data elements in the example of fig. 12, while 168 bytes are occupied for addresses. moreover, the data elements in fig. 12 are loaded in a contiguous order in the vector register file 1203 even though they are scattered at non - contiguous locations in the memory 1202. the processing element 400 can pack at least a first number of data elements to fill the nominal width of register file elements (e. g. , 8 1 - byte data elements to fill an 8 - byte register file element width for register file element 1204 a), and can also pack a second number of data elements into less than the nominal width of register file elements (e. g. , 5 - byte data elements packed into an 8 - byte register file element width for register file element 1204 c) .
this is a computer translation of the original content. it is provided for general information only and should not be relied upon as complete or accurate .
at least a single active element starting from the least significant active bit in the source mask is selected .
64 bytes of memory corresponding to the selected element is accessed. note that the accessed element will always access 64 bytes of memory .
the mask bits in the write mask register corresponding to the updated elements in the output register are reset to 0 .
# zmm0 – index register # r8 - base address # k1 - mask register # zmm6 – output register # 4 - scale. . l10: vgatherdps (% r8, % zmm0, 4), % zmm6 {% k1 } jkzd. . l9, % k1 vgatherdps (% r8, % zmm0, 4), % zmm6 {% k1 } jknzd. . l10, % k1. . l9 :
# zmm0 – index register # r12 - base address # k3 - mask register # zmm6 – input register # 4 - scale. . l14: vscatterdps% zmm7, (% r12, % zmm6, 4) {% k3 } jkzd. . l13, % k3 vscatterdps% zmm7, (% r12, % zmm6, 4) {% k3 } jknzd. . l14, % k3. . l13 :
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• avx2 complements the avx instructions that are typed for floating - point operation with a full compliment of equivalent set for operating with 32 / 64 - bit integer data elements .
apl and j have
transpose
instructions that let you rearrange the dimensions of a multidimensional array. i figured out awhile back how that could be done without having to move all the individual elements in memory; basically, keep track of the' step size' between elements on each axis, and you can shuffle them around as much as you like. of course, once you' ve done that, you' re jumping back and forth all over the array to pull in each element when / where you want it .
wow, i can' t wait to play around with pdep and pext instructions .
i want to use them for speeding up some critical code for compression / decompresison, the current code is not straightforward .
the document is pretty easy to navigate if you know which instructions you want to look up .
pext uses a mask in the second source operand (the third operand) to transfer either contiguous or non - contiguous bits in the first source operand (the second operand) to contiguous low order bit positions in the destination (the first operand) .
these days it' s the arm instruction set i care about. strange how fast x86 dropped off my radar .
downmodders are really out of control here lately. obviously i' m not saying that
cares about x86 anymore. it just very quickly went from the years of being only game in town to a sideshow
what server software i do write is in very hll like ruby but i actually find myself looking at arm disassembly sometimes now for apps .
maybe the feeling is that your personal statement of discontent with x86 is not really relevant to the story that new instructions have been added to x86. this is probably why you were downvoted. if you want to leave a comment with a similar essence, perhaps you should try commenting on one or two new instructions that are [ interesting | upsetting | repetitive ] to you ahead of your statement that you don' t care about arm anymore .
since i started writing software professionally over ten years ago x86 was the only instruction set that mattered outside of a few niche domains. now it' s all but irrelevant in the fastest growing market. for those of us that have lived in the shadow of wintel our entire professional lives the last few years have seen some dizzying changes .
so the big picture for me is that developments in x86 are now minor news .
enauczanie to usługa elektroniczna oparta na popularnym systemie moodle, umożliwiająca szeroko rozumiane kształcenie zdalne, odbywanie zaliczeń testów weryfikujących wiedzę oraz dostęp do wirtualnych laboratoriów. nowoczesna platforma dydaktyczna oferuje obecnie blisko 1200 kursów z różnych dziedzin wiedzy, obsługując ponad 20 tysięcy użytkowników rocznie .
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this system was organized as an asymmetric multiprocessor system which consists of the mainframe computer facom 230–75 and the array processor unit. the clock was 90 ns, and the peak performance of apu is 22 mflop / s for addition / subtraction and 11 mflop / s for ...
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{ [ document. course. dept _ acro ] } { [ document. course. course _ num ] }
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arrangements for program control, e. g. control units using stored programs, i. e. using an internal store of processing equipment to receive or retain programs
embodiments relate to packed loading and storing of data. an aspect includes a method for packed loading and storing of data distributed in a system that includes memory and a processing element. the method includes fetching and decoding an instruction for execution by the processing element. the processing element gathers a plurality of individually addressable data elements from non - contiguous locations in the memory which are narrower than a nominal width of register file elements in the processing element based on the instruction. the data elements are packed and loaded into register file elements of a register file entry by the processing element based on the instruction, such that at least two of the data elements gathered from the non - contiguous locations in the memory are packed and loaded into a single register file element of the register file entry.
gather-scatter is a type of memory addressing that often arises when addressing vectors in sparse linear algebra operations . it is the vector-equivalent of register indirect addressing , with gather involving indexed reads and scatter indexed writes . vector processors ( and some simd units in cpus ) have hardware support for gather-scatter operations , providing instructions such as load vector indexed for gather and store vector indexed for scatter . 
gather-scatter is a type of memory addressing that often arises when addressing vectors in sparse linear algebra operations. it is the vector-equivalent of register indirect addressing, with gather involving indexed reads and scatter indexed writes. vector processors (and some simd units in cpus) have hardware support for gather-scatter operations, providing instructions such as load vector indexed for gather and store vector indexed for scatter.
gather-scatter is a type of memory addressing that often arises when addressing vectors in sparse linear algebra operations. it is the vector-equivalent of register indirect addressing, with gather involving indexed reads and scatter indexed writes. vector processors (and some simd units in cpus) have hardware support for gather-scatter operations, providing instructions such as load vector indexed for gather and store vector indexed for scatter.