Performance analysis of a reduced data movement algorithm for neutron cross section data in Monte Carlo simulations

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Abstract

Current Monte Carlo neutron transport applications use continuous energy cross section data to provide the statistical foundation for particle trajectories. This “classical” algorithm requires storage and random access of very large data structures. Recently, Forget et al. [1] reported on a fundamentally new approach, based on multipole expansions, that distills cross section data down to a more abstract mathematical format. Their formulation greatly reduces memory storage and improves data locality at the cost of also increasing floating point computation. In the present study, we abstract the multipole representation into a “proxy application”, which we then use to determine the hardware performance parameters of the algorithm relative to the classical continuous energy algorithm. This study is done to determine the viability of both algorithms on current and next-generation high performance computing platforms.

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Tramm, J. R., Siegel, A. R., Forget, B., & Josey, C. (2015). Performance analysis of a reduced data movement algorithm for neutron cross section data in Monte Carlo simulations. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 8759, pp. 39–56). Springer Verlag. https://doi.org/10.1007/978-3-319-15976-8_3

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