The shift toward multicore architectures has ushered in a new era of shared memory parallelism for scientific applications. This transition has introduced challenges for the nuclear engineering community, as it seeks to design high-fidelity full-core reactor physics simulation tools. This article describes the parallel transport sweep algorithm in the OpenMOC method of characteristics (MOC) neutron transport code for multicore platforms using OpenMP. Strong and weak scaling studies are performed for both Intel Xeon and IBM Blue Gene/Q (BG/Q) multicore processors. The results demonstrate 100% parallel efficiency for 12 threads on 12 cores on Intel Xeon platforms and over 90% parallel efficiency with 64 threads on 16 cores on the IBM BG/Q. These results illustrate the potential for hardware acceleration for MOC neutron transport on modern multicore and future many-core architectures. In addition, this work highlights the pitfalls of programming for multicore architectures, with a focal point on false sharing.
AskewJR (1972) A Characteristics Formulation of the Neutron Transport Equation in Complicated Geometries. Techincal Report. AAEW-M 1108, UK Atomic Energy Establishment.
2.
BakerCDavidsonGEvansTM. (2012) High performance radiation transport simulations: preparing for TITAN. In: Supercomputing 2012, Salt Lake City, UT, 10-16 November 2012. Los Alamitos, CA: IEEE Computer Society Press.
3.
BoydWShanerSLiL. (2014) The OpenMOC method of characteristics neutral particle transport code. Annals of Nuclear Energy68: 43–52.
4.
BoydWSmithKForgetB (2013) A massively parallel method of characteristic neutral particle transport code for GPUs. In: Proceedings of the International Conference on Mathematics and Computational Methods Applied to Nuclear Science and Engineering, Sun Valley, ID, USA.
5.
BoydIII WRD (2014) Massively Parallel Algorithms for Method of Characteristics Neutral Particle Transport on Shared Memory Computer Architectures. M.S. Thesis, Massachusetts Institute of Technology, Cambridge, MA, USA.
6.
BrowneSDongarraJGarnerN. (2000) A portable programming interface for performance evaluation on modern processors. International Journal of High Performance Computing Applications14(3): 189–204.
7.
GongCLiuJChiL. (2011) GPU accelerated simulations of 3D deterministic particle transport using discrete ordinate method. Journal of Computational Physics230(15): 6010–6022.
8.
HorelikNSiegelAForgetB. (2014) Monte Carlo domain decomposition for robust nuclear reactor analysis. Parallel Computing40(10): 646–660.
9.
JungYSJooHG (2009) Decoupled planar MOC solution for dynamic group constant generation in direct three-dimensional core calculations. In: Proceedings of the International Conference on Mathematics and Computational Methods Applied to Nuclear Science and Engineering, Saratoga Spring, NY, USA.
10.
KochunasBM (2013) A Hybrid Parallel Algorithm for the 3-D Method of Characteristics Solution of the Boltzmann Transport Equation on High Performance Compute Clusters. Ph.D. Dissertation, University of Michigan, Ann Arbor, MI, USA.
11.
KochunasBCollinsBJabaayD. (2013) Overview of Development and Design of MPACT: Michigan Parallel Characteristics Transport Code, Technical Report. La Grange Park: American Nuclear Society, 2013.
12.
LewisEEMillerWF (1984) Computational Methods of Neutron Transport. New York: Wiley.
13.
LewisEEPalmiottiGTaiwoTA. (2003) Benchmark Specifications for Deterministic MOX Fuel Assembly Transport Calculations Without Spatial Homogenization. Technical Report. Organisation for Economic Co-operation and Development’s Nuclear Energy Agency.
NelsonAG (2009) Monte Carlo Methods for Neutron Transport on Graphics Processing Units Using CUDA. M.S. Thesis, Pennsylvania State University, PA, USA.
RomanoPKForgetB (2013) Parallel fission bank algorithms in Monte Carlo criticality calculations. Nuclear Science and Engineering170: 125–135.
18.
SiegelARSmithKRomanoPK. (2014) Multi-core performance studies of a Monte Carlo neutron transport code. International Journal of High Performance Computing Applications28(1): 87–96.
19.
SmithKS (1983) Nodal method storage reduction by non-linear iteration. Transactions of the American Nuclear Society44: 265.
20.
SmithKSRhodesJD (2000) CASMO-4 characteristics methods for two-dimensional PWR and BWR core calculations. Transactions of the American Nuclear Society83: 294.
21.
SmithKSRhodesJD (2002) Full-core, 2-D, LWR core calculations with CASMO-4E. In: Proceedings of PHYSOR, Seoul, South Korea, 7-10 October 2002.
22.
TrammJSiegelAR (2013) Memory bottlenecks and memory contention in multi-core Monte Carlo transport codes. In: Joint International Conference on Supercomputing in Nuclear Applications and Monte Carlo, La Cité des Sciences et de l’Industrie, Paris, France, 27-31 October 2013.
23.
YamamotoAKitamuraYYamaneY (2004) Computational efficiencies of approximated exponential functions for transport calculations of the characteristics method. Annals of Nuclear Energy2: 1027–1037.
24.
YangXSatvatN (2012) MOCUM: a two-dimensional method of characteristics code based on constructive solid geometry and unstructured meshing for general geometries. Annals of Nuclear Energy46: 20–28.
25.
U.S. DOE (1993) DOE Fundamentals Handbook: Nuclear Physics and Reactor Theory, Technical Report. Washington: U.S. Dept. of Energy.
