gpu上各向异性散射处理下特征中子输运计算的大规模并行方法

Namjae Choi, Junsuk Kang, H. Joo
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引用次数: 11

摘要

即使在CPU计算能力和高性能计算方面取得了重大进展,直接的全核中子输运计算对于工业应用仍然是不可行的。此外,目前CPU技术的改进趋势正受到热和功率限制的挑战。因此,异构计算作为反应堆物理的替代方案正日益受到关注。本文提出了一种在gpu上进行各向异性散射处理的加速特征中子输运计算方法。该方法在首尔国立大学开发的直接全核中子输运计算程序nTRACER中实现。VERA基准问题#5 P1和P2计算的性能结果表明,与具有16核并行计算的原始CPU求解器相比,在CPU支持足够的GPU上加速10-13倍。结果表明,如果CPU - GPU并发性和单精度得到合理利用,即使是入门级商用GPU也可以作为有效的反应堆物理分析手段。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Massively Parallel Method of Characteristics Neutron Transport Calculation with Anisotropic Scattering Treatment on GPUs
Even for the significant advances in CPU computing power and high performance computing, direct whole-core neutron transport calculation still remains unfeasible for the industrial applications. Furthermore, the improving trend of CPU technology is being challenged nowadays by thermal and power constraints. Thus, heterogeneous computing is increasingly receiving attention as an alternative for reactor physics. This work suggests a method to accelerate method of characteristics neutron transport calculation with anisotropic scattering treatment on GPUs. The method was implemented in nTRACER, a direct whole-core neutron transport calculation code being developed by Seoul National University. Performance results on VERA benchmark problem #5 P1 and P2 calculation presented 10-13 times speedup on GPU with adequate support of CPU compared to original CPU solver with 16-core parallel calculation. It was demonstrated that even an entry-level commercial GPU can be used as an effective means of reactor physics analysis if CPU -- GPU concurrency and single precision are properly utilized.
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