Domain decomposition in the GPU-accelerated Shift Monte Carlo code

Hamilton, Steven P.; Evans, Thomas M.; Royston, Katherine E.; Biondo, Elliott D.

doi:10.1016/j.anucene.2021.108687

Domain decomposition in the GPU-accelerated Shift Monte Carlo code

Journal Article · Mon Sep 20 00:00:00 EDT 2021 · Annals of Nuclear Energy (Oxford)

DOI:https://doi.org/10.1016/j.anucene.2021.108687· OSTI ID:1845803

^[1]; ^[1]; ^[1]; ^[1]

Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States)

The GPU solver within the Shift continuous-energy Monte Carlo neutron transport code has been extended to provide domain decomposition in addition to domain replication to enable the solution of problems with memory requirements exceeding the capacity of a single GPU. The strategy follows the Multiple Set, Overlapping Domain (MSOD) approach that is used in Shift’s CPU solver and integrates into the event-based algorithm used for Shift’s GPU solver. Furthermore, the ability to assign processors to spatial domains non-uniformly has been maintained. In this work, two different approaches for communicating particle data between domains are considered, and multiple criteria for load balancing problems have been investigated. Numerical results are presented for both fresh and depleted small modular nuclear reactor (SMR) cores. A parallel efficiency of approximately 80% was achieved with up to 16 spatial domains measured relative to full domain replication. A scaling study on the Summit supercomputer demonstrates a weak scaling parallel efficiency of over 90% on over 24000 GPUs.

Research Organization:: Oak Ridge National Laboratory (ORNL), Oak Ridge, TN (United States)

Sponsoring Organization:: USDOE Office of Science (SC)

Grant/Contract Number:: AC05-00OR22725

OSTI ID:: 1845803

Alternate ID(s):: OSTI ID: 1821065

Journal Information:: Annals of Nuclear Energy (Oxford), Journal Name: Annals of Nuclear Energy (Oxford) Journal Issue: 1 Vol. 166; ISSN 0306-4549

Publisher:: ElsevierCopyright Statement

Country of Publication:: United States

Language:: English

References (13)

Monte Carlo methods for radiation transport analysis on vector computers Brown, Forrest B.; Martin, William R. Progress in Nuclear Energy, Vol. 14, Issue 3 https://doi.org/10.1016/0149-1970(84)90024-6	journal	January 1984
OpenMC: A state-of-the-art Monte Carlo code for research and development Romano, Paul K.; Horelik, Nicholas E.; Herman, Bryan R. Annals of Nuclear Energy, Vol. 82 https://doi.org/10.1016/j.anucene.2014.07.048	journal	August 2015
MC21 v.6.0 – A continuous-energy Monte Carlo particle transport code with integrated reactor feedback capabilities Griesheimer, D. P.; Gill, D. F.; Nease, B. R. Annals of Nuclear Energy, Vol. 82 https://doi.org/10.1016/j.anucene.2014.08.020	journal	August 2015
Algorithmic choices in WARP – A framework for continuous energy Monte Carlo neutron transport in general 3D geometries on GPUs Bergmann, Ryan M.; Vujić, Jasmina L. Annals of Nuclear Energy, Vol. 77 https://doi.org/10.1016/j.anucene.2014.10.039	journal	March 2015
Multigroup Monte Carlo on GPUs: Comparison of history- and event-based algorithms Hamilton, Steven P.; Slattery, Stuart R.; Evans, Thomas M. Annals of Nuclear Energy, Vol. 113 https://doi.org/10.1016/j.anucene.2017.11.032	journal	March 2018
Nuclide depletion capabilities in the Shift Monte Carlo code Davidson, Gregory G.; Pandya, Tara M.; Johnson, Seth R. Annals of Nuclear Energy, Vol. 114 https://doi.org/10.1016/j.anucene.2017.11.042	journal	April 2018
Continuous-energy Monte Carlo neutron transport on GPUs in the Shift code Hamilton, Steven P.; Evans, Thomas M. Annals of Nuclear Energy, Vol. 128 https://doi.org/10.1016/j.anucene.2019.01.012	journal	June 2019
Implementation, capabilities, and benchmarking of Shift, a massively parallel Monte Carlo radiation transport code Pandya, Tara M.; Johnson, Seth R.; Evans, Thomas M. Journal of Computational Physics, Vol. 308 https://doi.org/10.1016/j.jcp.2015.12.037	journal	March 2016
Domain decomposition for GPU-Based continuous energy Monte Carlo power reactor calculation Choi, Namjae; Joo, Han Gyu Nuclear Engineering and Technology, Vol. 52, Issue 11 https://doi.org/10.1016/j.net.2020.04.024	journal	November 2020
Monte Carlo domain decomposition for robust nuclear reactor analysis Horelik, Nicholas; Siegel, Andrew; Forget, Benoit Parallel Computing, Vol. 40, Issue 10 https://doi.org/10.1016/j.parco.2014.10.001	journal	December 2014
Optimization of processor allocation for domain decomposed Monte Carlo calculations Ellis, J. Austin; Evans, Thomas M.; Hamilton, Steven P. Parallel Computing, Vol. 87 https://doi.org/10.1016/j.parco.2019.06.001	journal	September 2019
Exascale applications: skin in the game Alexander, Francis; Almgren, Ann; Bell, John Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences, Vol. 378, Issue 2166 https://doi.org/10.1098/rsta.2019.0056	journal	January 2020
Parallel Fission Bank Algorithms in Monte Carlo Criticality Calculations Romano, Paul K.; Forget, Benoit Nuclear Science and Engineering, Vol. 170, Issue 2 https://doi.org/10.13182/NSE10-98	journal	February 2012

Similar Records

Status of GPU capabilities within the Shift Monte Carlo radiation transport code

Conference · Tue Dec 31 23:00:00 EST 2024 · OSTI ID:2538455

Continuous-energy Monte Carlo neutron transport on GPUs in the Shift code

Journal Article · Wed Jan 16 23:00:00 EST 2019 · Annals of Nuclear Energy (Oxford) · OSTI ID:1492181

Evaluating asynchronous Schwarz solvers on GPUs

Journal Article · Mon Aug 10 00:00:00 EDT 2020 · International Journal of High Performance Computing Applications · OSTI ID:1778413

Related Subjects

97 MATHEMATICS AND COMPUTING
Domain decomposition
GPU
Monte Carlo

Domain decomposition in the GPU-accelerated Shift Monte Carlo code

Citation Formats

References (13)

Similar Records

Related Subjects