Accurate Sum and Dot Product

Takeshi Ogita, Siegfried M. Rump, Shin’ichi Oishi
2005
1 reference

Abstract

Algorithms for summation and dot product of floating-point numbers are presented which are fast in terms of measured computing time. We show that the computed results are as accurate as if computed in twice or K-fold working precision, $K\ge 3$. For twice the working precision our algorithms for summation and dot product are some 40% faster than the corresponding XBLAS routines while sharing similar error estimates. Our algorithms are widely applicable because they require only addition, subtraction, and multiplication of floating-point numbers in the same working precision as the given data. Higher precision is unnecessary, algorithms are straight loops without branch, and no access to mantissa or exponent is necessary.

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1 reference

Code References

python/cpython
1 file
Modules/mathmodule.c
1
https://doi.org/10.1137/030601818
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