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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.
Authored by Martyn Corden (Intel) Last updated on 03/27/2019 - 14:36
Article

Loop Modifications to Enhance Data-Parallel Performance

When confronted with nested loops, the granularity of the computations that are assigned to threads will directly affect performance. Loop transformations such as splitting and merging nested loops can make parallelization easier and more productive.
Authored by admin Last updated on 07/05/2019 - 14:47
Article

Granularity and Parallel Performance

One key to attaining good parallel performance is choosing the right granularity for the application. Granularity is the amount of real work in the parallel task. If granularity is too fine, then performance can suffer from communication overhead.
Authored by admin Last updated on 07/05/2019 - 19:52
Article

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.
Authored by Last updated on 07/31/2019 - 14:30
Article

Programming and Compiling for Intel® Many Integrated Core Architecture

This article discussions parallelization and provides links that will help you understand your programming environment and evaluate the suitability of your app.
Authored by AmandaS (Intel) Last updated on 03/26/2019 - 10:07
Article

Efficient Parallelization

This article is part of the Intel® Modern Code Developer Community documentation which supports developers in leveraging application performance in code through a systematic step-by-step optimization framework methodology. This article addresses: Thread level parallelization.
Authored by Ronald W Green (Blackbelt) Last updated on 03/21/2019 - 12:00
Article

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

Authored by Anoop M. (Intel) Last updated on 12/12/2018 - 18:00
Article

Webinar: Fortran Standard Parallel Programming Features

Fortran Standard Parallel Programming Features in Intel Compilers
Authored by Last updated on 07/04/2019 - 10:00
Article

Vectorizing Loops with Calls to User-Defined External Functions

Introduction

Authored by Anoop M. (Intel) Last updated on 12/12/2018 - 18:00
Article

循环修改增强数据并行性能

When confronted with nested loops, the granularity of the computations that are assigned to threads will directly affect performance. Loop transformations such as splitting and merging nested loops can make parallelization easier and more productive.
Authored by admin Last updated on 07/05/2019 - 14:48