SIMDizing pairwise sum:一种平衡精度和吞吐量的求和算法

WPMVP '14 Pub Date : 2014-02-16 DOI:10.1145/2568058.2568070
Barnaby Dalton, Amy Wang, Bob Blainey
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引用次数: 3

摘要

在需要平衡准确性和吞吐量的情况下实现求和是一项具有挑战性的工作。我们提出的实验结果提供了一种何时开始担忧的感觉,以及现有各种解决方案的成本。我们还提出了一种基于两两求和的新算法,当数据不驻留在L1缓存中时,该算法的吞吐量达到最快求和算法的89%,同时超过了精度要求很高的情况下通常使用的明显较慢的补偿求和,如Kahan求和和Kahan- babuska。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
SIMDizing pairwise sums: a summation algorithm balancing accuracy with throughput
Implementing summation when accuracy and throughput need to be balanced is a challenging endevour. We present experimental results that provide a sense when to start worrying and the expense of the various solutions that exist. We also present a new algorithm based on pairwise summation that achieves 89% of the throughput of the fastest summation algorithms when the data is not resident in L1 cache while eclipsing the accuracy of signifigantly slower compensated sums like Kahan summation and Kahan-Babuska that are typically used when accuracy is important.
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