Bit Flipping Errors in High Performance Linpack at Exascale and Beyond

Erlin Yao, Guangming Tan
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Abstract

For the High Performance Linpack (HPL) benchmark at the coming Exascale and beyond, silent errors like bit flipping in memory are expected to become inevitable. However, since bit flipping errors are difficult to be detected and located, their impact to the numerical correctness of HPL has not been evaluated thoroughly and quantitatively, while the impact at Exascale is especially susceptible. In this paper, an initial quantitative analysis of the impact of bit flipping errors to the numerical correctness of HPL has been investigated. To validate the numerical correctness of computed solution using HPL, there is a residual check after the approximate solution obtained. This paper has shown that in the case of only one bit flipping to any element in the original data matrix, if the flipped position is not the leading position of exponent, the residual check in HPL will almost surely pass at the scale of Exa flops and beyond. Experiments on modified HPL in single precision at small scales have verified the theoretical results in double precision at Exascale. The results obtained in this paper can provide a better understanding to the impact of bit flipping errors to numerical correctness of scientific computing applications.
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Exascale及以上的高性能Linpack中的位翻转错误
对于即将到来的百亿亿级及更高级别的高性能Linpack (HPL)基准测试,内存中的位翻转等无声错误预计将不可避免。然而,由于比特翻转错误难以检测和定位,它们对HPL数值正确性的影响尚未得到全面和定量的评估,而在Exascale上的影响尤其容易受到影响。本文初步定量分析了位翻转误差对HPL数值正确性的影响。为了验证HPL计算解的数值正确性,在得到近似解后进行残差检验。本文证明了在只有1位翻转到原始数据矩阵中的任何元素的情况下,如果翻转位置不是指数的前导位置,则HPL中的残差检查几乎肯定会在Exa或更大的浮点数范围内通过。在小尺度单精度改进HPL上的实验验证了双精度的理论结果。本文的研究结果可以更好地理解比特翻转误差对科学计算应用数值正确性的影响。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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