A Monte Carlo volumetric-ray-casting estimator for global fluence tallies on GPUs

Sweezy, Jeremy Ed

doi:10.1016/j.jcp.2018.06.032

A Monte Carlo volumetric-ray-casting estimator for global fluence tallies on GPUs

Journal Article · Thu Aug 16 00:00:00 EDT 2018 · Journal of Computational Physics

DOI:https://doi.org/10.1016/j.jcp.2018.06.032· OSTI ID:1659164

Sweezy, Jeremy Ed ^[1]

Los Alamos National Lab. (LANL), Los Alamos, NM (United States)

A Monte Carlo fluence estimator has been designed to take advantage of the computational power of graphical processing units (GPUs). This new estimator, termed the volumetric-ray-casting estimator, is an extension of the expectation estimator. It can be used as a replacement of the track-length estimator for the estimation of global fluence. Calculations for this estimator are performed on the GPU while the Monte Carlo random walk is performed on the central processing unit (CPU). This method lowers the implementation cost for GPU acceleration of existing Monte Carlo particle transport codes as there is little modification of the particle history logic flow. Three test problems have been evaluated to assess the performance of the volumetric-ray-casting estimator for neutron transport on GPU hardware in comparison to the standard track-length estimator on CPU hardware. Evaluation of neutron transport through air in a criticality accident scenario showed that the volumetric-ray-casting estimator achieved 23 times the performance of the track-length estimator using a single core CPU paired with a GPU and 15 times the performance of the track-length estimator using an eight core CPU paired with a GPU. Finally, simulation of a pressurized water reactor fuel assembly showed that the performance improvement was 6 times within the fuel and 7 times within the control rods using an eight core CPU paired with a single GPU.

View Accepted Manuscript (DOE)

Research Organization:: Los Alamos National Laboratory (LANL), Los Alamos, NM (United States)

Sponsoring Organization:: USDOE National Nuclear Security Administration (NNSA)

Grant/Contract Number:: 89233218CNA000001; AC52-06NA25396

OSTI ID:: 1659164

Alternate ID(s):: OSTI ID: 1703191
OSTI ID: 23087709

Report Number(s):: LA-UR--17-22573

Journal Information:: Journal of Computational Physics, Journal Name: Journal of Computational Physics Vol. 372; ISSN 0021-9991

Publisher:: ElsevierCopyright Statement

Country of Publication:: United States

Language:: English

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74 ATOMIC AND MOLECULAR PHYSICS
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Monte Carlo methods
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A Monte Carlo volumetric-ray-casting estimator for global fluence tallies on GPUs

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