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Power Profiling of a Reduced Data Movement Algorithm for Neutron Cross Section Data in Monte Carlo Simulations by John R. Tramm; Kazutomo Yoshii; Andrew R. Siegel is a scholarly article available to read on EtoBox.

What is Power Profiling of a Reduced Data Movement Algorithm for Neutron Cross Section Data in Monte Carlo Simulations about?

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 determine the hardware performance parameters, including power usage, of the multipole algorithm relative to the classical continuous energy algorithm. This study is done to guage the suitability of both algorithms for use on next-generation high performance computing platforms.

Author

John R. Tramm; Kazutomo Yoshii; Andrew R. Siegel

Publisher

IEEE

Published

2014

Language

EN