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The x86 instruction set has several times been extended with SIMD (Single instruction, multiple data) instruction set extensions.These extensions, starting from the MMX instruction set extension introduced with Pentium MMX in 1997, typically define sets of wide registers and instructions that subdivide these registers into fixed-size lanes and perform a computation for each lane in parallel.
The first use of SIMD instructions was in the ILLIAC IV, which was completed in 1966.. SIMD was the basis for vector supercomputers of the early 1970s such as the CDC Star-100 and the Texas Instruments ASC, which could operate on a "vector" of data with a single instruction.
Single instruction, multiple threads (SIMT) is an execution model used in parallel computing where single instruction, multiple data (SIMD) is combined with multithreading. It is different from SPMD in that all instructions in all "threads" are executed in lock-step.
In general x86 processors can load and use memory matched to the size of any register it is operating on. (The SIMD instructions also include half-load instructions.) Most 2-operand x86 instructions, including integer ALU instructions, use a standard "addressing mode byte" [13] often called the MOD-REG-R/M byte.
SIMD instructions operating on 4 x unsigned bytes or 2 x 16-bit values packed into a 32-bit register (the 64-bit variant of the DSP ASE supports larger vectors, too). SIMD operations are basic arithmetic, shifts and some multiply-accumulate type operations. MIPS SIMD architecture (MSA) Instruction set extensions designed to accelerate multimedia.
SSE contains 70 new instructions (65 unique mnemonics [1] using 70 encodings), most of which work on single precision floating-point data. SIMD instructions can greatly increase performance when exactly the same operations are to be performed on multiple data objects. Typical applications are digital signal processing and graphics processing.
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In SIMD the same operation (instruction) is applied on multiple data to manipulate data streams (a version of SIMD is vector processing where the data are organized as vectors). Another class of processors, GPUs encompass multiple SIMD streams processing. Note that SPMD and SIMD are not mutually exclusive; SPMD parallel execution can include ...