Li Todo Maggs Krauth 2020
From Werner KRAUTH
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| - | '''B. Li, S. Todo, A. C. Maggs, W. Krauth''' '''''Multithreaded event-chain Monte Carlo with local times''''' ''' arXiv:2004.11040 (2020)''' | + | '''B. Li, S. Todo, A. C. Maggs, W. Krauth''' '''''Multithreaded event-chain Monte Carlo with local times''''' '''Computer Physics Communications 261 107702 (2021)''' |
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| [http://arxiv.org/pdf/2004.11040 Electronic version (from arXiv)] | [http://arxiv.org/pdf/2004.11040 Electronic version (from arXiv)] | ||
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| + | [https://doi.org/10.1016/j.cpc.2020.107702 DOI: 10.1016/j.cpc.2020.107702] | ||
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| + | [https://www.sciencedirect.com/science/article/abs/pii/S0010465520303453 Journal version] (requires subscription) | ||
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| + | [https://github.com/jellyfysh/ParaSpheres https://github.com/jellyfysh/ParaSpheres GitHub repository] from which the ParaSpheres programs described in the paper (in Python, Fortran, C++, and shell) may be [https://en.wikipedia.org/wiki/Fork_(software_development) forked], cloned, or simply copied. | ||
Current revision
B. Li, S. Todo, A. C. Maggs, W. Krauth Multithreaded event-chain Monte Carlo with local times Computer Physics Communications 261 107702 (2021)
Abstract
We present a multithreaded event-chain Monte Carlo algorithm (ECMC) for hard spheres. Threads synchronize at infrequent breakpoints and otherwise scan for local horizon violations. Using a mapping onto absorbing Markov chains, we rigorously prove the correctness of a sequential-consistency implementation for small test suites. On x86 and ARM processors, a C++ (OpenMP) implementation that uses compare-and-swap primitives for data access achieves considerable speed-up with respect to single-threaded code. The generalized birthday problem suggests that for the number of threads scaling as the square root of the number of spheres, the horizon-violation probability remains small for a fixed simulation time. We provide C++ and Python open-source code that reproduces all our results.
Electronic version (from arXiv)
DOI: 10.1016/j.cpc.2020.107702
Journal version (requires subscription)
https://github.com/jellyfysh/ParaSpheres GitHub repository from which the ParaSpheres programs described in the paper (in Python, Fortran, C++, and shell) may be forked, cloned, or simply copied.
