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首页> 外文会议>IEEE International Parallel and Distributed Processing Symposium >A Performance Analysis of SIMD Algorithms for Monte Carlo Simulations of Nuclear Reactor Cores
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A Performance Analysis of SIMD Algorithms for Monte Carlo Simulations of Nuclear Reactor Cores

机译：用于核反应堆堆芯蒙特卡罗模拟的SIMD算法的性能分析

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A primary characteristic of history-based Monte Carlo neutron transport simulation is the application of MIMD-style parallelism: the path of each neutron particle is largely independent of all other particles, so threads of execution perform independent instructions with respect to other threads. This conflicts with the growing trend of HPC vendors exploiting SIMD hardware, which accomplishes better parallelism and more FLOPS per watt. Event-based neutron transport suits vectorization better than history-based transport, but it is difficult to implement and complicates data management and transfer. However, the Intel Xeon Phi architecture supports the familiar ×86 instruction set and memory model, mitigating difficulties in vector zing neutron transport codes. This paper compares the event-based and history-based approaches for exploiting SIMD in Monte Carlo neutron transport simulations. For both algorithms, we analyze performance using the three different execution models provided by the Xeon Phi (offload, native, and symmetric) within the full-featured OpenVMS framework. A representative micro-benchmark of the performance bottleneck computation shows about 10x performance improvement using the event-based method. In an optimized history-based simulation of a full-physics nuclear reactor core in OpenVMS, the MIC shows a calculation rate 1.6x higher than a modern 16-core CPU, 2.5x higher when balancing load between the CPU and 1 MIC, and 4x higher when balancing load between the CPU and 2 Macs. As far as we are aware, our calculation rate per node on a high fidelity benchmark (17, 098 particles/second) is higher than any other Monte Carlo neutron transport application. Furthermore, we attain 95% distributed efficiency when using MPI and up to 512 concurrent MIC devices.
机译：基于历史的蒙特卡洛中子输运模拟的主要特征是MIMD样式的并行性的应用：每个中子粒子的路径在很大程度上与所有其他粒子无关，因此执行线程相对于其他线程执行独立的指令。这与HPC供应商利用SIMD硬件的增长趋势相矛盾，后者实现了更好的并行性和每瓦更多的FLOPS。基于事件的中子传输比基于历史的传输更适合矢量化，但是它难以实现并使数据管理和传输复杂化。但是，Intel Xeon Phi体系结构支持熟悉的×86指令集和内存模型，从而减轻了矢量化中子传输码的困难。本文比较了在蒙特卡洛中子传输模拟中利用SIMD的基于事件和基于历史的方法。对于这两种算法，我们使用功能齐全的OpenVMS框架中Xeon Phi提供的三种不同执行模型（卸载，本机和对称）来分析性能。性能瓶颈计算的代表性微观基准表明，使用基于事件的方法可将性能提高约10倍。在基于OpenVMS的全物理核反应堆堆芯的基于历史记录的优化仿真中，MIC的计算速率比现代16核CPU高1.6倍，在CPU与1个MIC之间平衡负载时的计算速率高2.5倍，而4倍当在CPU和2台Mac之间平衡负载时，性能会更高。据我们所知，在高保真度基准（17，098个粒子/秒）上，我们每个节点的计算速率都高于其他任何蒙特卡洛中子传输应用程序。此外，当使用MPI和多达512个并发MIC设备时，我们可以获得95％的分布式效率。

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