面向使用 PME 工作负载的对称英特尔® MPI 的 GROMACS 方案


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。

Autor Heinrich Bockhorst (Intel) Última actualización 06/07/2019 - 16:40

基于英特尔® 架构加速金融应用

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Autor George Raskulinec (Intel) Última actualización 06/07/2019 - 16:40

著作 - High Performance Parallelism Pearls

A look into the contents of the two "Pearls" books, edited by James Reinders and Jim Jeffers. These books contain a collection of examples of code modernization.
Autor Mike P. (Intel) Última actualización 21/03/2019 - 12:00

基于英特尔® 至强™ 处理器 E5 产品家族的多节点分布式内存系统上的 Caffe* 培训

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.
Autor Gennady F. (Blackbelt) Última actualización 05/07/2019 - 14:55

案例研究: 面向神经细胞模拟优化代码

Intel held the Intel® Modern Code Developer Challenge that had about 2,000 students from 130 universities in 19 countries registered to participate in the Challenge. They were provided access to Intel® Xeon Phi™ coprocessors to optimize code used in a CERN openlab brain simulation research project. In this article Daniel Vea Falguera (Modern Code Developer Challenge winner) shares how he...
Autor Última actualización 06/07/2019 - 16:40
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An Intro to Multi-Level Parallelism for High-Performance Computing by Clay Breshears | Life Sciences Software Architect, Intel
Autor Clay B. (Blackbelt) Última actualización 12/12/2018 - 18:08

面向英特尔® 至强融核™ 处理器(代号“Knights Landing”)的开发人员访问计划

Intel is bringing to market, in anticipation of general availability of the Intel® Xeon Phi™ Processor (codenamed Knights Landing), the Developer Access Program (DAP). DAP is an early access program for developers worldwide to purchase an Intel Xeon Phi Processor based system.
Autor Mike P. (Intel) Última actualización 21/03/2019 - 12:00

了解面向三维同性有限差分 (3DFD) 波动方程代码的 NUMA

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。

Autor Sunny G. (Intel) Última actualización 05/07/2019 - 20:13

整理您的数据和代码: 数据和布局 - 第 2 部分

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.
Autor David M. Última actualización 06/07/2019 - 16:40

在英特尔® 数学核心函数库中引入 DNN 基元

    深度神经网络 (DNN) 处于机器学习领域的前沿。这些算法在 20 世纪 90 年代后期得到了行业的广泛采用,最初应用于诸如银行支票手写识别等任务。深度神经网络在这一任务领域已得到广泛运用,达到甚至超过了人类能力。如今,DNN 已用于图像识别、视频和自然语言处理以及解决复杂的视觉理解问题,如自主驾驶等。DNN 在计算资源及其必须处理的数据量方面要求非常苛刻。

Autor Vadim Pirogov (Intel) Última actualización 21/03/2019 - 12:08