ParaMonte: A Cross-Language Parallel Monte Carlo and Machine Learning Library
ORAL
Abstract
We present the ParaMonte software, a suite of parallel Monte Carlo optimization, sampling, integration, and Machine Learning algorithms for probabilistic and scientific inference. Born out of Data-Driven research needs in Physics, the library's primary goal is to streamline and automate scientific inference via a language-agnostic platform-agnostic environment while emphasizing and ensuring high performance, parallelism, and scalability.
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Publication: ParaMonte: A high-performance serial/parallel Monte Carlo simulation library for C, C++, Fortran<br>https://joss.theoj.org/papers/10.21105/joss.02741
Presenters
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Amir Shahmoradi
University of Texas
Authors
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Amir Shahmoradi
University of Texas
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Fatemeh Bagheri
University of Texas at Arlington
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Joshua Osborne
University of Texas at Arlington