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Article

Books - 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.
Автор: Mike P. (Intel) Последнее обновление: 30.09.2019 - 17:30
Article

Weather Research and Forecasting Model Optimized for Knights Landing

The Weather Research and Forecasting (WRF) Model is a numerical weather prediction (NWP) system designed for both atmospheric research and operational forecasting needs. It is made up of about a half million lines of code, predominantly in Fortran*.
Автор: Последнее обновление: 30.09.2019 - 17:28
Article

Free access to Intel® Compilers, Performance libraries, Analysis tools and more...

Intel® Parallel Studio XE is a very popular product from Intel that includes the Intel® Compilers, Intel® Performance Libraries, tools for analysis, debugging and tuning, tools for MPI and the Intel® MPI Library. Did you know that some of these are available for free? Here is a guide to “what is available free” from the Intel Parallel Studio XE suites.
Автор: админ Последнее обновление: 30.09.2019 - 17:28
Article

OMP_PROC_BIND is Now Supported on Compatible Non-Intel Processors

The newest versions of the Intel® C++ and Fortran compilers now support OpenMP* environment variable OMP_PROC_BIND on compatible non-Intel processors for Linux* and Windows* platfo

Автор: Kenneth Craft (Intel) Последнее обновление: 08.10.2019 - 18:20
Article

Case Study: BerkeleyGW using Intel® Xeon Phi™ Processors

BerkeleyGW is a Materials Science application for calculating the excited state properties of materials such as band gaps, band structures, absoprtion spectroscopy, photoemission spectroscopy and m

Автор: Mike P. (Intel) Последнее обновление: 15.10.2019 - 15:30
Article

Hybrid Parallelism: Parallel Distributed Memory and Shared Memory Computing

There are two principal methods of parallel computing: distributed memory computing and shared memory computing. As more processor cores are dedicated to large clusters solving scientific and engineering problems, hybrid programming techniques combining the best of distributed and shared memory programs are becoming more popular.
Автор: David M. Последнее обновление: 15.10.2019 - 16:40
Article

Putting Your Data and Code in Order: Data and layout - Part 2

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.
Автор: David M. Последнее обновление: 15.10.2019 - 16:40