Apply the concepts of parallelism and distributed memory computing to your code to improve software performance. This paper expands on concepts discussed in Part 1, to consider parallelism, both vectorization (single instruction multiple data SIMD) as well as shared memory parallelism (threading), and distributed memory computing.
This article focuses on the steps to improve software performance with vectorization. Included are examples of full applications along with some simpler cases to illustrate the steps to vectorization.
Version : Intel® Parallel Studio XE 2018 for Windows Update 2, Intel®
This page provides system requirements and release notes for Intel® System Studio.
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.
Compiler Methodology for Intel® MIC Architecture