Putting Your Data and Code in Order: Data and layout - Part 2

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.
作者: David M. 最后更新时间: 2019/10/15 - 16:40

Optimizing Big Data processing with Haswell 256-bit Integer SIMD instructions

Big Data requires processing huge amounts of data. Intel Advanced Vector Extensions 2 (aka AVX2) promoted most Intel AVX 128-bits integer SIMD instruction sets to 256-bits.

作者: gaston-hillar (Blackbelt) 最后更新时间: 2019/10/15 - 17:38

Optimized Pseudo Random Number Generators with Intel® Advanced Vector Extensions 2

Intel® Math Kernel Library includes powerful and versatile random number generators that have been optimized to take full advantage of Intel

作者: gaston-hillar (Blackbelt) 最后更新时间: 2019/10/15 - 17:40

BKMs on the Use of the SIMD Directive

We had an ask from one of the various "Birds of a Feather" meetings Intel® holds at venues such as at the Super Computing* (SC) and International Super Computing* (ISC) conferences.

作者: 最后更新时间: 2019/10/15 - 17:45

Accelerating Financial Applications on Intel® architecture

Learn more about an in-depth analysis of code modernization performance conducted by optimizing original CPU code and re-running tests on the latest GPU/CPU hardware.
作者: George Raskulinec (Intel) 最后更新时间: 2019/10/17 - 14:37