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

John R. Tramm, Kazutomo Yoshii, A. Siegel
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引用次数: 2

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 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.
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蒙特卡罗模拟中子截面数据的简化数据移动算法的功率分析
目前的蒙特卡罗中子输运应用使用连续能量截面数据为粒子轨迹提供统计基础。这种“经典”算法需要存储和随机访问非常大的数据结构。最近,Forget等人[1]报道了一种基于多极展开的全新方法,该方法将截面数据提取为更抽象的数学格式。它们的公式大大减少了内存存储,提高了数据的局部性,同时也增加了浮点计算的代价。在本研究中,我们确定了多极算法相对于经典连续能量算法的硬件性能参数,包括功耗。这项研究是为了衡量这两种算法在下一代高性能计算平台上的适用性。
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