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Title: Multigroup Monte Carlo on GPUs: Comparison of history- and event-based algorithms

Journal Article · · Annals of Nuclear Energy (Oxford)
ORCiD logo [1]; ORCiD logo [1]; ORCiD logo [1]
  1. Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States)
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This article presents an investigation of the performance of different multigroup Monte Carlo transport algorithms on GPUs with a discussion of both history-based and event-based approaches. Several algorithmic improvements are introduced for both approaches. By modifying the history-based algorithm that is traditionally favored in CPU-based MC codes to occasionally filter out dead particles to reduce thread divergence, performance exceeds that of either the pure history-based or event-based approaches. The impacts of several algorithmic choices are discussed, including performance studies on Kepler and Pascal generation NVIDIA GPUs for fixed source and eigenvalue calculations. Single-device performance equivalent to 20–40 CPU cores on the K40 GPU and 60–80 CPU cores on the P100 GPU is achieved. Last, in addition, nearly perfect multi-device parallel weak scaling is demonstrated on more than 16,000 nodes of the Titan supercomputer.

Research Organization:
Oak Ridge National Laboratory (ORNL), Oak Ridge, TN (United States). Oak Ridge Leadership Computing Facility (OLCF)
Sponsoring Organization:
USDOE National Nuclear Security Administration (NNSA); USDOE Office of Science (SC)
Grant/Contract Number:
AC05-00OR22725; 17-SC-20-SC
OSTI ID:
1414707
Alternate ID(s):
OSTI ID: 1549006
Journal Information:
Annals of Nuclear Energy (Oxford), Vol. 113, Issue C; ISSN 0306-4549
Publisher:
ElsevierCopyright Statement
Country of Publication:
United States
Language:
English
Citation Metrics:
Cited by: 8 works
Citation information provided by
Web of Science

Figures / Tables (22)

Listing 1(p. 8)figure Listing 1
Figure 1(p. 9)figure Figure 1
Algorithm 1(p. 12)figure Algorithm 1
Algorithm 2(p. 12)figure Algorithm 2
Algorithm 3(p. 12)figure Algorithm 3
Figure 2(p. 13)figure Figure 2
Algorithm 4(p. 14)figure Algorithm 4
Figure 3(p. 15)figure Figure 3
Figure 4(p. 18)figure Figure 4
Figure 5(p. 18)figure Figure 5
Algorithm 5(p. 20)figure Algorithm 5
Figure 6(p. 21)figure Figure 6
Figure 7(p. 23)figure Figure 7
Table 1(p. 25)table Table 1
Figure 8(p. 26)figure Figure 8
Table 2(p. 26)table Table 2
Figure 9(p. 27)figure Figure 9
Table 3(p. 28)table Table 3
Table 4(p. 28)table Table 4
Figure 10(p. 30)figure Figure 10
Figure 11(p. 32)figure Figure 11
Figure 12(p. 32)figure Figure 12

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