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Code Sample: Exploring MPI for Python* on Intel® Xeon Phi™ Processor

Learn how to write an MPI program in Python*, and take advantage of Intel® multicore architectures using OpenMP threads and Intel® AVX512 instructions.
Authored by Nguyen, Loc Q (Intel) Last updated on 07/06/2019 - 16:30
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针对英特尔® 至强™ 处理器 E5 系列的 Caffe* 评分优化

为了不断优化英特尔® 架构的深度学习工作负载,我们的工程师探索不同的路径,以达到最高性能。

Authored by Gennady F. (Blackbelt) Last updated on 03/21/2019 - 12:28
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英特尔® 至强融核™ 处理器优化教程

In this tutorial, we demonstrate some possible ways to optimize an application to run on the Intel® Xeon Phi™ processor
Authored by Nguyen, Loc Q (Intel) Last updated on 03/21/2019 - 12:00
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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 07/06/2019 - 16:30
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Improve Application Performance on an Intel® Xeon Phi™ Processor

Learn techniques for vectorizing code, adding thread-level parallelism, and enabling memory optimization.
Authored by Nguyen, Loc Q (Intel) Last updated on 06/14/2019 - 11:50
Article

Recipe: Building and Running GROMACS* on Intel® Processors

This recipe describes how to get, build, and run the GROMACS* code on Intel® Xeon® and Intel® Xeon Phi™ processors for better performance on a single node.
Authored by Smahane Douyeb. (Intel) Last updated on 03/21/2019 - 12:08
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Performance of Classic Matrix Multiplication Algorithm on Intel® Xeon Phi™ Processor System

Matrix multiplication (MM) of two matrices is one of the most fundamental operations in linear algebra. The algorithm for MM is very simple, it could be easily implemented in any programming language. This paper shows that performance significantly improves when different optimization techniques are applied.
Authored by Last updated on 06/14/2019 - 11:50
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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 07/06/2019 - 16:30
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Caffe* Scoring Optimization for Intel® Xeon® Processor E5 Series

    In continued efforts to optimize Deep Learning workloads on Intel® architecture, our engineers explore various paths leading to the maximum performance.

Authored by Gennady F. (Blackbelt) Last updated on 03/21/2019 - 12:28
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Direct N-body Simulation

Exercise in performance optimization on Intel Architecture, including Intel® Xeon Phi™ processors.
Authored by Mike P. (Intel) Last updated on 03/21/2019 - 12:00