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Article

Intel Cluster Ready FAQ: Customer benefits

Q: Why should we select a certified Intel Cluster Ready system and registered Intel Cluster Ready applications?

Автор: Krotz-Vogel, Werner (Intel) Последнее обновление: 06.07.2019 - 11:10
Article

Intel® Xeon® Processor E7 v3 Product Family

Автор: Nguyen, Khang T (Intel) Последнее обновление: 06.07.2019 - 16:40
Article

Parallel Programming Books

Use these parallel programming resources and books with your Intel® Xeon® processor and Intel® Xeon Phi™ processor family
Автор: Mike P. (Intel) Последнее обновление: 21.03.2019 - 12:00
Article

GROMACS recipe for symmetric Intel® MPI using PME workloads

Objectives
Автор: Heinrich Bockhorst (Intel) Последнее обновление: 06.07.2019 - 16:40
Article

Using Intel® MKL and Intel® TBB in the same application

Intel MKL 11.3 has introduced Intel TBB support.

Автор: Gennady F. (Blackbelt) Последнее обновление: 01.08.2019 - 09:22
Article

面向使用 PME 工作负载的对称英特尔® MPI 的 GROMACS 方案

目标

该文件包(脚本及其说明)提供了针对对称英特尔运行的构建和运行环境。 该文件实际上是自述 (README) 文件包。 对称指采用至强™ 可执行文件和至强融核™ 可执行文件,两者通过英特尔 MPI 同时运行以传输 MPI 消息和集体数据。

Автор: Heinrich Bockhorst (Intel) Последнее обновление: 06.07.2019 - 16:40
Article

Books - Message Passing Interface (MPI)

This article looks at several books that introduce developers to the topics of Message Passing Interface (MPI), parallel programming, and OpenMP*.
Автор: Mike P. (Intel) Последнее обновление: 12.12.2018 - 18:00
Блоги

Exposing Processor Features to Dynamic Languages

Intel® for its part invests countless hours and billions of transistors to add features in our silicon products which will speed up people's lives. If only they knew how to take advantage of it! Part of our job in dynamic languages is what I call "putting the cookies on the bottom shelf". Make this advanced technology easily consumable, and show you the value of it so you can be sure to use it.
Автор: David S. (Blackbelt) Последнее обновление: 04.07.2019 - 19:43
Блоги

The JITter Conundrum - Just in Time for Your Traffic Jam

In interpreted languages, it just takes longer to get stuff done - I earlier gave the example where the Python source code a = b + c would result in a BINARY_ADD byte code which takes 78 machine instructions to do the add, but it's a single native ADD instruction if run in compiled language like C or C++. How can we speed this up? Or as the performance expert would say, how do I decrease...
Автор: David S. (Blackbelt) Последнее обновление: 04.07.2019 - 20:00
Article

Caffe* Training on Multi-node Distributed-memory Systems Based on Intel® Xeon® Processor E5 Family

Caffe is a deep learning framework developed by the Berkeley Vision and Learning Center (BVLC) and one of the most popular community frameworks for image recognition. Caffe is often used as a benchmark together with AlexNet*, a neural network topology for image recognition, and ImageNet*, a database of labeled images.
Автор: Gennady F. (Blackbelt) Последнее обновление: 05.07.2019 - 14:54