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This article is part of the Intel® Modern Code Developer Community documentation which supports developers in leveraging application performance in code through a systematic step-by-step optimization framework methodology. This article addresses: Thread level parallelization.
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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.
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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.
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This case study examines the situation where the problem decomposition is the same for threading as it is for Message Passing Interface* (MPI); that is, the threading parallelism is elevated to the same level as MPI parallelism.
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Parallel Universe Magazine - Issue 18, June 2014

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Parallel Universe Magazine - Issue 12, November 2012

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Parallel Universe Magazine - Issue 14, June 2013

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Parallel Universe Magazine - Issue 15, August 2013

Criado por administrar Última atualização em 12/12/2018 - 18:08
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Parallel Universe Magazine - Issue 16, November 2013

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