Requirements for Vectorizable Loops

Vectorization is one of many optimizations that are enabled by default in the latest Intel compilers. In order to be vectorized, loops must obey certain conditions, listed below. Some additional ways to help the compiler to vectorize loops are described.
Criado por Martyn Corden (Intel) Última atualização em 27/03/2019 - 14:36

OpenMP* and the Intel® IPP Library

How to configure OpenMP in the Intel IPP library to maximize multi-threaded performance of the Intel IPP primitives.
Criado por Última atualização em 31/07/2019 - 14:30

The Importance of Vectorization for Intel Microarchitectures (Fortran Example)

Reference Link and Download

Intel Vectorization Tools

Criado por Martyn Corden (Intel) Última atualização em 03/07/2019 - 20:00

Improving Averaging Filter Performance Using Intel® Cilk™ Plus

Intel® Cilk™ Plus is an extension to the C and C++ languages to support data and task parallelism.  It provides three new keywords to i

Criado por Anoop M. (Intel) Última atualização em 12/12/2018 - 18:00

Vectorizing Loops with Calls to User-Defined External Functions


Criado por Anoop M. (Intel) Última atualização em 12/12/2018 - 18:00

Explicit Vector Programming – Best Known Methods

Vectorizing improves performance, and achieving high performance can save power. Introduction to tools for vectorizing compute-intensive processing.
Criado por Última atualização em 24/04/2019 - 11:25

Alignment of Allocatable Arrays & Pointers in Intel Fortran Compiler

The Intel® Parallel Studio XE 2017 or later for Fortran Windows* and Linux* have a feature enhancement supporting ASSUME_ALIGNED directive at point of use for allocatable arrays or pointers.

Criado por Duan, Xiaoping (Intel) Última atualização em 22/03/2019 - 12:39

英特尔® Parallel Studio XE 2017概述和新功能

英特尔® Parallel Studio 2017推出若干种令人激动的功能特性以及为数不多的几种新产品。

Criado por Wei D. (Intel) Última atualização em 28/01/2019 - 00:29

Implementing a Masked SVML-like Function Explicitly in User-Defined Way

The Intel® Compiler provides SIMD intrinsics APIs for short vector math library (SVML) and starting with Intel® Advanced Vector Extensions

Criado por Última atualização em 16/07/2019 - 08:37

Fast Insights to Optimized Vectorization and Memory Using Cache-aware Roofline Analysis

Integrated into Intel® Advisor, Cache-aware Roofline Modeling (CARM) provides insight into how an application behaves by helping to determine a) how optimally it works on a given hardware, b) the m

Criado por administrar Última atualização em 12/12/2018 - 18:08