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The Intel® C++ Compiler 19.0 and the Intel® Fortran Compiler 19.1 support the OpenMP* SIMD SCAN feature for inclusive and exclusive scans.
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Virtual Vector Function Supported in Intel® C++ Compiler 17.0

Intel® C++ Compiler 17.0 starts supporting virtual vector functions.

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学习如何在英特尔® 至强融核™ 处理器中使用 MPI-3 共享内存
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Code Sample included: Learn how to use MPI-3 shared memory feature using the corresponding APIs on the Intel® Xeon Phi™ processor.
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No longer does Moore’s Law result in higher frequencies and improved scalar application performance; instead, higher transistor counts lead to increased parallelism, both through more cores and thr

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Get a background on vectorization and learn different techniques to evaluate its effectiveness.
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In this pair of articles on performance and memory covers basic concepts to provide guidance to developers seeking 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.
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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.
Criado por David M. Última atualização em 15/10/2019 - 16:40
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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.
Criado por David M. Última atualização em 15/10/2019 - 16:40