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Scientific Software Sustainability for Stochastic Codes---ZENO, an Example from NIST

Published

Author(s)

Walid Keyrouz, Michael V. Mascagni

Abstract

We consider the unique issues related to software sustainability that accompany scientific codes that employ stochastic algorithms. These are codes that often implement Monte Carlo methods (MCMs). We will focus our attention on ZENO, a code of interest at NIST that uses MCMs to compute materials properties.
Citation
Computational Science and Engineering Software Sustainability and Productivity Challenges

Keywords

Stochastic algorithms, Monte Carlo methods, Software sustainability

Citation

Keyrouz, W. and Mascagni, M. (2015), Scientific Software Sustainability for Stochastic Codes---ZENO, an Example from NIST, Computational Science and Engineering Software Sustainability and Productivity Challenges, [online], https://www.nitrd.gov/csessp/ (Accessed July 14, 2024)

Issues

If you have any questions about this publication or are having problems accessing it, please contact reflib@nist.gov.

Created October 15, 2015, Updated April 30, 2019