SIMDizing pairwise sums: a summation algorithm balancing accuracy with throughput

  • Authors:
  • Barnaby Dalton;Amy Wang;Bob Blainey

  • Affiliations:
  • IBM, Markham, ON, Canada;IBM, Markham, ON, Canada;IBM, Markham, ON, Canada

  • Venue:
  • Proceedings of the 2014 Workshop on Programming models for SIMD/Vector processing
  • Year:
  • 2014

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Abstract

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.