Rounding error using low precision approximate random variables

Fuente: arXiv
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Main Authors: Sheridan-Methven, Oliver, Giles, Michael
Format: Preprint
Published: 2020
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author Sheridan-Methven, Oliver
Giles, Michael
author_facet Sheridan-Methven, Oliver
Giles, Michael
contents For numerical approximations to stochastic differential equations using the Euler-Maruyama scheme, we propose incorporating approximate random variables computed using low precisions, such as single and half precision. We propose and justify a model for the rounding error incurred, and produce an average case error bound for two and four way differences, appropriate for regular and nested multilevel Monte Carlo estimations. By considering the variance structure of multilevel Monte Carlo correction terms in various precisions with and without a Kahan compensated summation, we compute the potential speed ups offered from the various precisions. We find single precision offers the potential for approximate speed improvements by a factor of 7 across a wide span of discretisation levels. Half precision offers comparable improvements for several levels of coarse simulations, and even offers improvements by a factor of 10-12 for the very coarsest few levels.
format Preprint
id arxiv_https___arxiv_org_abs_2012_09739
institution arXiv
publishDate 2020
record_format arxiv
spellingShingle Rounding error using low precision approximate random variables
Sheridan-Methven, Oliver
Giles, Michael
Numerical Analysis
65G50, 65C10, 41A10, 65C05, 65Y20, 60H35, 65B10, 65L70, 34M30, 97N20, 65C30
For numerical approximations to stochastic differential equations using the Euler-Maruyama scheme, we propose incorporating approximate random variables computed using low precisions, such as single and half precision. We propose and justify a model for the rounding error incurred, and produce an average case error bound for two and four way differences, appropriate for regular and nested multilevel Monte Carlo estimations. By considering the variance structure of multilevel Monte Carlo correction terms in various precisions with and without a Kahan compensated summation, we compute the potential speed ups offered from the various precisions. We find single precision offers the potential for approximate speed improvements by a factor of 7 across a wide span of discretisation levels. Half precision offers comparable improvements for several levels of coarse simulations, and even offers improvements by a factor of 10-12 for the very coarsest few levels.
title Rounding error using low precision approximate random variables
topic Numerical Analysis
65G50, 65C10, 41A10, 65C05, 65Y20, 60H35, 65B10, 65L70, 34M30, 97N20, 65C30
url https://arxiv.org/abs/2012.09739