MCALIB: Measuring Sensitivity to Rounding Error with Monte Carlo Programming

• Autores: Michael Frechtling, Philip H. W. Leong
• Localización: ACM transactions on programming languages and systems, ISSN 0164-0925, Vol. 37, Nº 2, 2015
• Idioma: inglés
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• Resumen

  • Runtime analysis provides an effective method for measuring the sensitivity of programs to rounding errors. To date, implementations have required significant changes to source code, detracting from their widespread application. In this work, we present an open source system that automates the quantitative analysis of floating point rounding errors through the use of C-based source-to-source compilation and a Monte Carlo arithmetic library. We demonstrate its application to the comparison of algorithms, detection of catastrophic cancellation, and determination of whether single precision floating point provides sufficient accuracy for a given application. Methods for obtaining quantifiable measurements of sensitivity to rounding error are also detailed.