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.
本文将介绍一些技巧，帮助软件开发人员识别并修复使用最新英特尔软件开发工具时遇到的与 NUMA 相关的应用性能问题。
Vectorization Advisor is like having a trusted friend look over your code and give you advice based on what he sees. As you’ll see in this article, user feedback on the tool has included, “there are significant speedups produced by following advisor output, I'm already sold on this tool!”
学习如何在英特尔® 至强融核™ 处理器中使用 MPI-3 共享内存