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Parallel Universe Magazine #12: Advanced Vectorization

This blog contains additional content for the article "Advanced Vectorization" from Parallel Universe #12:

Autor Georg Zitzlsberger (Intel) Última actualización 29/07/2015 - 20:02
Article

Webinar: Get Ready for Intel® Math Kernel Library on Intel® Xeon Phi™ Coprocessors

Intel recently unveiled the new Intel® Xeon Phi™ product – a coprocessor based on the Intel® Many Integrated Core architecture.

Autor Zhang Z. (Intel) Última actualización 29/07/2015 - 20:03
Article

Mapping of Intel® MPI Library versions to bundle suites

Introduction: Mapping the Intel® MPI Library numbers to specific suites and update versions

Autor Gergana S. (Intel) Última actualización 29/07/2015 - 20:03
Article

借助基于 MPICH 的应用使用英特尔® MPI 库 5.0

优势

不同的 MPI 实现具备不同的优势。 因此在特定集群环境中,采用其他 MPI 实现的 HPC 应用可能能够提供更高的性能。

 英特尔® MPI 库 具备以下优势:

Autor Dmitry Sivkov (Intel) Última actualización 29/07/2015 - 20:03
Article

Using Intel® MPI Library 5.0 with MPICH based applications

Why it is needed?
Autor Dmitry Sivkov (Intel) Última actualización 29/07/2015 - 20:03
Article

Hybrid applications: Intel MPI Library and OpenMP*

Tips and tricks on how to get the optimal performance settings for your mixed Intel MPI/OpenMP applications.
Autor Gergana S. (Intel) Última actualización 29/07/2015 - 20:03
Article

Using the Intel® MPI Library in a server/client setup

A guide for using the MPI_Comm_accept and MPI_Comm_connect functions to form a server/client program suite with the Intel® MPI Library.
Autor James T. (Intel) Última actualización 29/07/2015 - 20:03
Article

Intel® Threading Building Blocks: Scalable Programming for Multi-Core

Intel’s new parallel programming model is a new set of Libraries developed by Intel Software and Solutions Group in order to help developers write scalable code without worrying about managing threads.
Autor Arch D. Robison (Intel) Última actualización 29/07/2015 - 20:05
Article

Granularity and Parallel Performance

One key to attaining good parallel performance is choosing the right granularity for the application. Granularity is the amount of real work in the parallel task. If granularity is too fine, then performance can suffer from communication overhead.
Autor admin Última actualización 29/07/2015 - 20:05
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