Data decomposition of Monte Carlo particle transport simulations via tally servers
Author(s)
Siegel, Andrew R.; Romano, Paul Kollath; Forget, Benoit Robert Yves; Smith, Kord S.
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An algorithm for decomposing large tally data in Monte Carlo particle transport simulations is developed, analyzed, and implemented in a continuous-energy Monte Carlo code, OpenMC. The algorithm is based on a non-overlapping decomposition of compute nodes into tracking processors and tally servers. The former are used to simulate the movement of particles through the domain while the latter continuously receive and update tally data. A performance model for this approach is developed, suggesting that, for a range of parameters relevant to LWR analysis, the tally server algorithm should perform with minimal overhead on contemporary supercomputers. An implementation of the algorithm in OpenMC is then tested on the Intrepid and Titan supercomputers, supporting the key predictions of the model over a wide range of parameters. We thus conclude that the tally server algorithm is a successful approach to circumventing classical on-node memory constraints en route to unprecedentedly detailed Monte Carlo reactor simulations.
Date issued
2013-06Department
Massachusetts Institute of Technology. Department of Nuclear Science and EngineeringJournal
Journal of Computational Physics
Publisher
Elsevier
Citation
Romano, Paul K. et al. “Data Decomposition of Monte Carlo Particle Transport Simulations via Tally Servers.” Journal of Computational Physics 252 (2013): 20–36.
Version: Original manuscript
ISSN
00219991