Efficient Language-Based Parallelization of Computational Problems Using Cilk Plus

Stpiczyński, Przemysław

doi:10.1007/978-3-319-78054-2_24

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2018

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“…Memory which allows to share data between the CPU and the coprocessor. It is perfect for exchanging irregular data with limited size, when explicit synchronization is not used frequently [16].…”

Section: Tbb (Threading Building Blocks)mentioning

confidence: 99%

Language-based vectorization and parallelization using intrinsics, OpenMP, TBB and Cilk Plus

Stpiczyński

2018

J Supercomput

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The aim of this paper is to evaluate OpenMP, TBB and Cilk Plus as basic language-based tools for simple and efficient parallelization of recursively defined computational problems and other problems that need both task and data parallelization techniques. We show how to use these models of parallel programming to transform a source code of Adaptive Simpson's Integration to programs that can utilize multiple cores of modern processors. Using the example of Belman-Ford algorithm for solving single-source shortest path problems, we advise how to improve performance of data parallel algorithms by tuning data structures for better utilization of vector extensions of modern processors. Manual vectorization techniques based on Cilk array notation and intrinsics are presented. We also show how to simplify such optimization using Intel SIMD Data Layout Template containers.

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Section: Tbb (Threading Building Blocks)mentioning

confidence: 99%