| JOURNAL OF COMPUTATIONAL PHYSICS | 卷:252 |
| Data decomposition of Monte Carlo particle transport simulations via tally servers | |
| Article | |
| Romano, Paul K.1  Siegel, Andrew R.2  Forget, Benoit1  Smith, Kord1  | |
| [1] MIT, Dept Nucl Sci & Engn, Cambridge, MA 02139 USA | |
| [2] Argonne Natl Lab, Argonne, IL 60439 USA | |
| 关键词: Monte Carlo; Neutron transport; Data decomposition; Exascale; Tally server; | |
| DOI : 10.1016/j.jcp.2013.06.011 | |
| 来源: Elsevier | |
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【 摘 要 】
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. (C) 2013 Elsevier Inc. All rights reserved.
【 授权许可】
Free
【 预 览 】
| Files | Size | Format | View |
|---|---|---|---|
| 10_1016_j_jcp_2013_06_011.pdf | 574KB |
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