论文标题
PETAR：用于建模大规模碰撞恒星系统的高性能N体制代码
PeTar: a high-performance N-body code for modeling massive collisional stellar systems
论文作者
论文摘要
大规模碰撞恒星系统（例如球状簇（GC））的数值模拟非常耗时。到目前为止，仅使用Nbody6 ++ GPU代码进行了少量的具有少量二进制文件的GC的逼真的百货GC（5％）。这样的模型在基于GPU的超级计算机上花费了半年的计算时间。在这项工作中，我们通过结合Barnes-Hut Tree，Hermite Integrator和Show Down算法正则化（SDAR）的方法来开发新的N体密码PETAR。该代码可以准确处理多个系统的任意部分（例如二进制，三元组），同时通过使用MPI，OpenMP，SIMD指令和GPU的混合并行化方法来保持高性能。一些基准表明Petar和Nbody6 ++ GPU在全球结构，二元轨道和逃生剂的长期演变上有很好的共识。在配置高度配置的GPU台式计算机上，使用PETAR使用PETAR中的全明星的表现比NBody6 ++ GPU快11倍。此外，在Cray XC50超级计算机上，PETAR级别的尺度会增加。涵盖了超紧凑矮人和核星团簇的100万个体型问题，可以解决。
The numerical simulations of massive collisional stellar systems, such as globular clusters (GCs), are very time-consuming. Until now, only a few realistic million-body simulations of GCs with a small fraction of binaries (5%) have been performed by using the NBODY6++GPU code. Such models took half a year computational time on a GPU based super-computer. In this work, we develop a new N-body code, PeTar, by combining the methods of Barnes-Hut tree, Hermite integrator and slow-down algorithmic regularization (SDAR). The code can accurately handle an arbitrary fraction of multiple systems (e.g. binaries, triples) while keeping a high performance by using the hybrid parallelization methods with MPI, OpenMP, SIMD instructions and GPU. A few benchmarks indicate that PeTar and NBODY6++GPU have a very good agreement on the long-term evolution of the global structure, binary orbits and escapers. On a highly configured GPU desktop computer, the performance of a million-body simulation with all stars in binaries by using PeTar is 11 times faster than that of NBODY6++GPU. Moreover, on the Cray XC50 supercomputer, PeTar well scales when number of cores increase. The ten million-body problem, which covers the region of ultra compact dwarfs and nuclearstar clusters, becomes possible to be solved.
