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Optimization of processor allocation for domain decomposed Monte Carlo calculations

Journal Article · · Parallel Computing
 [1];  [2];  [2];  [3];  [2]
  1. Sandia National Lab. (SNL-NM), Albuquerque, NM (United States)
  2. Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States)
  3. North Carolina State Univ., Raleigh, NC (United States)
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Load imbalance plagues domain decomposed Monte Carlo calculations when sources are not uniform. Parallel efficiency for domain decomposed Monte Carlo transport calculations improves through a nonuniform allocation of processors over subdomains. In this work, we optimize the allocation with runtime diagnostics collected during a calibration step, then complete the full calculation. The diagnostic-based approach is compared to implicit filtering, an optimization algorithm for bound constrained noisy optimization problems. Finally, we consider both forward and hybrid radiation transport calculations to measure performance.
Research Organization:
Oak Ridge National Laboratory (ORNL), Oak Ridge, TN (United States)
Sponsoring Organization:
USDOE; USDOE Office of Science (SC)
Grant/Contract Number:
AC05-00OR22725
OSTI ID:
1558566
Alternate ID(s):
OSTI ID: 1682480
Journal Information:
Parallel Computing, Journal Name: Parallel Computing Journal Issue: C Vol. 87; ISSN 0167-8191
Publisher:
ElsevierCopyright Statement
Country of Publication:
United States
Language:
English

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Related Subjects

97 MATHEMATICS AND COMPUTING
Domain decomposition
Load imbalance
Monte Carlo transport
Noisy optimization