Intel® Fortran Compiler Classic and Intel® Fortran Compiler Developer Guide and Reference

ID 767251
Date 11/07/2023
Public

A newer version of this document is available. Customers should click here to go to the newest version.

Document Table of Contents

Automatic Vectorization

The automatic vectorizer (also called the auto-vectorizer) is a component of the compiler that automatically uses SIMD instructions in the Intel® Streaming SIMD Extensions (Intel® SSE, Intel® SSE2, Intel® SSE3 and Intel® SSE4), Supplemental Streaming SIMD Extensions (SSSE3) instruction sets, Intel® Advanced Vector Extensions (Intel® AVX, Intel® AVX2) instruction sets, and Intel® Advanced Vector Extensions 512 (Intel® AVX-512) instruction set. The vectorizer detects operations in the program that can be done in parallel and converts the sequential operations to parallel; for example, the vectorizer converts the sequential SIMD instruction that processes up to 16 elements into a parallel operation, depending on the data type.

Automatic vectorization occurs when the compiler generates packed SIMD instructions to unroll a loop. Because the packed instructions operate on more than one data element at a time, the loop executes more efficiently. This process is referred to as auto-vectorization only to emphasize that the compiler identifies and optimizes suitable loops on its own, without external input. 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.

The compiler supports a variety of auto-vectorizing hints that can help the compiler to generate effective vector instructions. Automatic vectorization is supported on Intel® 64 architectures. Intel® Advisor, a separate tool included in the Intel® oneAPI Base Toolkit, provides a Vectorization Advisor feature that can analyze the compiler's optimization reports and make recommendations for enhancing vectorization.

NOTE:

This option enables vectorization at default optimization levels for both Intel® microprocessors and non-Intel microprocessors. Vectorization may call library routines that can result in additional performance gain on Intel® microprocessors than on non-Intel microprocessors. The vectorization can also be affected by certain options, such as -arch or -x (Linux), or /arch or /Qx (Windows).