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Evaluating optimizations that reduce globalmemory accesses of stencil computations in GPGPUs

机译:评估减少GPGPU中模板计算的全局内存访问的优化

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摘要

This work compares the performance of optimizations that transform replicated global memoryaccesses into localmemoryaccesses on3Dstencil computations in theNVIDIATeslaK80GPGPU.The optimizations reduce global memory contention caused by the set of multiprocessors. Evaluatedoptimizations are grid tiling, inserting spatial and temporal loops into kernels, register reuse,andsomeof their combinations.Astandardized experiment evaluates performance variationwithgrid size and stencil size for each optimization. Experimental data show that codes that use theseoptimizations are up to 3.3 times faster than the classical stencil formulation. It also shows thatthemost profitable optimization varieswith grid and stencil sizes.
机译:这项工作比较了在NVIDIA TeslaK80GPGPU的3D模板计算中将复制的全局内存 r n访问转换为本地内存访问的优化的性能。 r n这些优化减少了由多处理器集引起的全局内存争用。评估的 r n优化是网格平铺,将空间和时间循环插入内核,寄存器重用,及其组合中的一些组合。标准化实验评估每个优化的性能随r ngrid尺寸和模板尺寸的变化。实验数据表明,使用这些 r noptimizations的代码的速度比传统的模板制作速度快3.3倍。它还显示 r 最有利可图的优化随网格和模具尺寸而变化。

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  • 来源
    《Concurrency, practice and experience》 |2019年第18期|e4929.1-e4929.16|共16页
  • 作者单位

    Divisao de Ciencia da Computacao, InstitutoTecnologico de Aeronautica (ITA), Sao Jose dosCampos, Sao Paulo, Brazil;

    Divisao de Ciencia da Computacao, InstitutoTecnologico de Aeronautica (ITA), Sao Jose dosCampos, Sao Paulo, Brazil;

    Divisao de Ciencia da Computacao, InstitutoTecnologico de Aeronautica (ITA), Sao Jose dosCampos, Sao Paulo, Brazil;

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  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

    GPGPU; memory hierarchy; stencil computation;

    机译:GPGPU;记忆层次结构;模板计算;

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