Article

Improve Vectorization Performance with Intel® AVX-512

See how the new Intel® Advanced Vector Extensions 512CD and the Intel AVX512F subsets (available in the Intel® Xeon Phi processor and in future Intel Xeon processors) lets the compiler automatically generate vector code with no changes to the code.
Authored by Alberto V. (Intel) Last updated on 07/08/2019 - 19:26
Article

Quick Analysis of Vectorization Using Intel® Advisor

Find out how to use the command-line interface in Intel® Advisor 2017 for a quick, initial analysis of loop performance that gives an overview of the hotspots in your code.
Authored by Alberto V. (Intel) Last updated on 09/30/2019 - 17:28
Article

Intel® Xeon Phi™ Processor 7200 Family Memory Management Optimizations

This paper examines software performance optimization for an implementation of a non-library version of DGEMM executing on the Intel® Xeon Phi™ processor (code-named Knights Landing, with acronym K

Authored by Last updated on 10/15/2019 - 15:30
Article

Caffe* Optimized for Intel® Architecture: Applying Modern Code Techniques

This paper demonstrates a special version of Caffe* — a deep learning framework originally developed by the Berkeley Vision and Learning Center (BVLC) — that is optimized for Intel® architecture.
Authored by Last updated on 10/15/2019 - 15:30
Article

Improve Performance with Vectorization

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.
Authored by David M. Last updated on 10/15/2019 - 15:30
Article

Thread Parallelism in Cython*

Cython* is a superset of Python* that additionally supports C functions and C types on variable and class attributes. Cython generates C extension modules, which can be used by the main Python program using the import statement.
Authored by Nguyen, Loc Q (Intel) Last updated on 10/15/2019 - 16:40