现代数值加速器的计算引力动力学
Computational Gravitational Dynamics with Modern Numerical Accelerators
摘要：
我们回顾了最近的优化重力$N$体内核上运行它们的图形处理单元（GPU），单主机和大规模并行平台。对于每一个主要的$N$体技术，直接求和和树代码，我们讨论的优化策略，这是不同的每个算法。由于两者的精度以及性能特征不同，混合这两种算法是必不可少的，当模拟一个大的$N$体系统与高密度结构包含很少的粒子，和低密度结构包含许多粒子。我们演示了如何通过分裂底层的哈密顿量来实现这一点，随后我们通过模拟一组11个合并星系的核中有大量的黑洞来演示混合代码的效率和准确性。
英文摘要：
We review the recent optimizations of gravitational $N$-body kernels for running them on graphics processing units (GPUs), on single hosts and massive parallel platforms. For each of the two main $N$-body techniques, direct summation and tree-codes, we discuss the optimization strategy, which is different for each algorithm. Because both the accuracy as well as the performance characteristics differ, hybridizing the two algorithms is essential when simulating a large $N$-body system with high-density structures containing few particles, and with low-density structures containing many particles. We demonstrate how this can be realized by splitting the underlying Hamiltonian, and we subsequently demonstrate the efficiency and accuracy of the hybrid code by simulating a group of 11 merging galaxies with massive black holes in the nuclei.
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