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Performance Analysis of a Reduced Data Movement Algorithm for Neutron Cross Section Data in Monte Carlo Simulations

机译:蒙特卡罗模拟中中子截面数据减少数据移动算法的性能分析

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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.
机译:目前的蒙特卡罗中子传输应用使用连续能量横截面数据来为粒子轨迹提供统计基础。这种“古典”算法需要存储和随机访问非常大的数据结构。最近,忘记等人。 [1]根据多极扩展,以基本上新的方法报告,将横截面数据蒸馏到更抽象的数学格式。它们的配方大大减少了内存存储,并以增加浮点计算的成本提高了数据局部。在本研究中,我们摘要将多极表示到“代理应用程序”中,然后我们使用来确定相对于经典连续能量算法的算法的硬件性能参数。完成该研究以确定对当前和下一代高性能计算平台上的两种算法的可行性。

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