预测smp上的性能。一个案例研究:SGI权力挑战

N. Amato, J. Perdue, M. Mathis, A. Pietracaprina, G. Pucci
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引用次数: 12

摘要

我们研究了典型SMP的SGI-Power挑战的性能预测问题。在这样的平台上,内存访问的成本取决于它们的位置和处理器之间的争用。通过运行一套精心设计的微基准测试,我们提供了定量证据,表明内存层次结构对性能的影响远远大于与争用相关的其他现象。我们还拟合了三个基于BSP模型变体的成本函数,它们不考虑层次结构,以及一个用硬件计数器表示的新定义函数F,它捕获了内存层次结构和争用效应。我们在合成基准和应用程序基准上测试了所有函数的准确性,结果表明,与其他函数不同,F在所有情况下都达到了极好的准确性。虽然硬件计数器仅在运行时可用,但我们提供的证据表明,函数F仍然可以通过在小输入规模的试点运行中推断计数器的值来用作预测工具。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Predicting performance on SMPs. A case study: the SGI Power Challenge
We study the issue of performance prediction on the SGI-Power Challenge, a typical SMP. On such a platform, the cost of memory accesses depends on their locality and on contention among processors. By running a carefully designed suite of microbenchmarks, we provide quantitative evidence that memory hierarchy effects impact performance far more substantially than other phenomena related to contention. We also fit three cost functions based on variants of the BSP model, which do not account for the hierarchy, and a newly defined function F expressed in terms of hardware counters, which captures both memory hierarchy and contention effects. We test the accuracy of all the functions on both synthetic and application benchmarks showing that, unlike the other functions, F achieves an excellent level of accuracy in all cases. Although hardware counters are only available at run-time, we give evidence that function F can still be employed as a prediction tool by extrapolating values of the counters from pilot runs on small input sizes.
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