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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
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 October 8, 2025)