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Title: Performance and accuracy of criticality calculations performed using WARP – A framework for continuous energy Monte Carlo neutron transport in general 3D geometries on GPUs

Abstract

In this companion paper to "Algorithmic Choices in WARP - A Framework for Continuous Energy Monte Carlo Neutron Transport in General 3D Geometries on GPUs" (doi:10.1016/j.anucene.2014.10.039), the WARP Monte Carlo neutron transport framework for graphics processing units (GPUs) is benchmarked against production-level central processing unit (CPU) Monte Carlo neutron transport codes for both performance and accuracy. We compare neutron flux spectra, multiplication factors, runtimes, speedup factors, and costs of various GPU and CPU platforms running either WARP, Serpent 2.1.24, or MCNP 6.1. WARP compares well with the results of the production-level codes, and it is shown that on the newest hardware considered, GPU platforms running WARP are between 0.8 to 7.6 times as fast as CPU platforms running production codes. Also, the GPU platforms running WARP were between 15% and 50% as expensive to purchase and between 80% to 90% as expensive to operate as equivalent CPU platforms performing at an equal simulation rate.

Authors:
 [1];  [1];  [1];  [1];  [1]
  1. Univ. of California, Berkeley, CA (United States). Dept. of Nuclear Engineering
Publication Date:
Research Org.:
Univ. of California, Berkeley, CA (United States)
Sponsoring Org.:
USDOE National Nuclear Security Administration (NNSA)
OSTI Identifier:
1344092
Alternate Identifier(s):
OSTI ID: 1429509
Grant/Contract Number:
NA0000979
Resource Type:
Journal Article: Accepted Manuscript
Journal Name:
Annals of Nuclear Energy (Oxford)
Additional Journal Information:
Journal Name: Annals of Nuclear Energy (Oxford); Journal Volume: 103; Journal Issue: C; Journal ID: ISSN 0306-4549
Publisher:
Elsevier
Country of Publication:
United States
Language:
English
Subject:
73 NUCLEAR PHYSICS AND RADIATION PHYSICS; Monte Carlo; Neutron Transport; GPU; CUDA; OptiX; Supercomputing

Citation Formats

Bergmann, Ryan M., Rowland, Kelly L., Radnović, Nikola, Slaybaugh, Rachel N., and Vujić, Jasmina L. Performance and accuracy of criticality calculations performed using WARP – A framework for continuous energy Monte Carlo neutron transport in general 3D geometries on GPUs. United States: N. p., 2017. Web. doi:10.1016/j.anucene.2017.01.027.
Bergmann, Ryan M., Rowland, Kelly L., Radnović, Nikola, Slaybaugh, Rachel N., & Vujić, Jasmina L. Performance and accuracy of criticality calculations performed using WARP – A framework for continuous energy Monte Carlo neutron transport in general 3D geometries on GPUs. United States. doi:10.1016/j.anucene.2017.01.027.
Bergmann, Ryan M., Rowland, Kelly L., Radnović, Nikola, Slaybaugh, Rachel N., and Vujić, Jasmina L. Mon . "Performance and accuracy of criticality calculations performed using WARP – A framework for continuous energy Monte Carlo neutron transport in general 3D geometries on GPUs". United States. doi:10.1016/j.anucene.2017.01.027. https://www.osti.gov/servlets/purl/1344092.
@article{osti_1344092,
title = {Performance and accuracy of criticality calculations performed using WARP – A framework for continuous energy Monte Carlo neutron transport in general 3D geometries on GPUs},
author = {Bergmann, Ryan M. and Rowland, Kelly L. and Radnović, Nikola and Slaybaugh, Rachel N. and Vujić, Jasmina L.},
abstractNote = {In this companion paper to "Algorithmic Choices in WARP - A Framework for Continuous Energy Monte Carlo Neutron Transport in General 3D Geometries on GPUs" (doi:10.1016/j.anucene.2014.10.039), the WARP Monte Carlo neutron transport framework for graphics processing units (GPUs) is benchmarked against production-level central processing unit (CPU) Monte Carlo neutron transport codes for both performance and accuracy. We compare neutron flux spectra, multiplication factors, runtimes, speedup factors, and costs of various GPU and CPU platforms running either WARP, Serpent 2.1.24, or MCNP 6.1. WARP compares well with the results of the production-level codes, and it is shown that on the newest hardware considered, GPU platforms running WARP are between 0.8 to 7.6 times as fast as CPU platforms running production codes. Also, the GPU platforms running WARP were between 15% and 50% as expensive to purchase and between 80% to 90% as expensive to operate as equivalent CPU platforms performing at an equal simulation rate.},
doi = {10.1016/j.anucene.2017.01.027},
journal = {Annals of Nuclear Energy (Oxford)},
number = C,
volume = 103,
place = {United States},
year = {Mon May 01 00:00:00 EDT 2017},
month = {Mon May 01 00:00:00 EDT 2017}
}

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