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Source an environment script such as iccvars_intel64.sh in the compiler bin/intel64 directory, or iccvars_ia32.sh in the bin/ia32 directory, as appropriate. Open an Intel® Compiler command line window.So, how significant is the performance enhancement? To evaluate performance enhancement yourself, run example1: The source line number (92 in the above example) refers to either the beginning or the end of the loop.
INTEL C COMPILER VECTORIZATION OPTION CODE
Where does the vectorization speedup come from? Consider the following sample code fragment, where a, b and c are integer arrays: for (i=0 i icl /Qvec-report1 MultArray.c
INTEL C COMPILER VECTORIZATION OPTION MAC OS
The vectorization can also be affected by certain options, such as /arch or /Qx (Windows) or -m or -x (Linux and Mac OS X). Vectorization may call library routines that can result in additional performance gain on Intel microprocessors than on non-Intel microprocessors. Using the -vec (Linux and Mac OS* X) or the /Qvec (Windows*) option enables vectorization at default optimization levels for both Intel® microprocessors and non-Intel microprocessors. However, it is useful to note that in some cases, certain keywords or directives may be applied in the code for auto-vectorization to occur.Īutomatic vectorization is supported on IA-32 and Intel® 64 architectures. This process is referred to as auto-vectorization only to emphasize that the compiler identifies and optimizes suitable loops on its own, without requiring any special action by you. Because the packed instructions operate on more than one data element at a time, the loop executes more efficiently. SIMD instructions operate on multiple data elements in one instruction and make use of the 128-bit SIMD floating-point registers.Īutomatic vectorization occurs when the Intel® Compiler generates packed SIMD instructions to unroll a loop. So, what is vectorization? The process of converting an algorithm from a scalar implementation, which does an operation one pair of operands at a time, to a vector process where a single instruction can refer to a vector (series of adjacent values) is called vectorization. The vectorizer detects operations in the program that can be done in parallel, and then converts the sequential operations, like one SIMD instruction that processes 2, 4, 8 or up to 16 elements, to parallel, depending on the data type. The automatic vectorizer (also called the auto-vectorizer) is a component of the Intel® compiler that automatically uses SIMD instructions in the Intel® Streaming SIMD Extensions (Intel® SSE, SSE2, SSE3 and SSE4 Vectorizing Compiler and Media Accelerators), and the Supplemental Streaming SIMD Extensions (SSSE3) instruction sets, and the Intel® Advanced Vector Extension instruction set.