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Estimating Computational Noise

Stefan Wild (wild***at***mcs.anl.gov)
Jorge Moré (more***at***mcs.anl.gov)

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

Category 1: Other Topics (Other )

Category 2: Nonlinear Optimization

Category 3: Optimization Software and Modeling Systems (Other )

Citation: Preprint ANL/MCS-P1721-0210, Argonne National Laboratory Mathematics and Computer Science Division, February 2010. To appear in SISC.

Download: [PDF]

Entry Submitted: 03/01/2010
Entry Accepted: 03/01/2010
Entry Last Modified: 03/10/2011

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