Title: Estimating Computational Noise
Authors: Jorge J. Moré, Stefan M. Wild
Abstract: Computational noise in deterministic simulations is as ill-defined a concept as can be found in scientific computing. When coupled with adaptive strategies, the effects of finite precision destroy smoothness of the simulation output and complicate subsequent analysis. Following the work of Hamming on roundoff errors, we present a new algorithm, ECnoise, for quantifying the noise level of a computed function. Our theoretical framework is based on stochastic noise but does not assume a specific distribution for the noise. For the deterministic simulations considered, ECnoise produces reliable results in few function evaluations and offers new insights into building blocks of large scale simulations.
Keywords: Computational Noise, Deterministic Simulations, Iterative Solvers
Thanks: This work was supported by the Office of Advanced Scientific Computing Research, Office of Science, U.S. Department of Energy, under Contract DE-AC02-06CH11357.
Status: Appears in SIAM Journal on Scientific Computing, Vol. 33 (3), pp. 1292-1314, 2011.
Fomerly Argonne National Laboratory Preprint ANL/MCS-P1721-0210
Link: [DOI 10.1137/100786125]
Additional information, including codes and data, can be found on our Estimating Computational Noise page
BibTeX:
@article{JJMSMW11,
    author      = "Jorge J. Mor\'e and Stefan M. Wild",
    title       = "Estimating Computational Noise",
    journal     = "SIAM J.~Scientific Computing",
    volume      = "33",    
    year        = "2011",
    number      = "3",
    pages       = "1292--1314",
    doi         = "10.1137/100786125"
}

	
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