PeTar: ParticlE Tree & particle-particle & Algorithmic Regularization code for simulating massive star clusters

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Ada Coda
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PeTar: ParticlE Tree & particle-particle & Algorithmic Regularization code for simulating massive star clusters

Post by Ada Coda » Thu Jul 30, 2020 10:11 pm

PeTar: ParticlE Tree & particle-particle & Algorithmic Regularization code for simulating massive star clusters

Abstract: The N-body code PETAR (ParticlE Tree & particle-particle & Algorithmic Regularization) combines the methods of Barnes-Hut tree, Hermite integrator and slow-down algorithmic regularization (SDAR). It accurately handles an arbitrary fraction of multiple systems (<i>e.g.</i> binaries, triples) while keeping a high performance by using the hybrid parallelization methods with MPI, OpenMP, SIMD instructions and GPU. PETAR has very good agreement with NBODY6++GPU results on the long-term evolution of the global structure, binary orbits and escapers and is significantly faster when used on a highly configured GPU desktop computer. PETAR scales well when the number of cores increase on the Cray XC50 supercomputer, allowing a solution to the ten million-body problem which covers the region of ultra compact dwarfs and nuclear star clusters.

Credit: Wang, Long; Iwasawa, Masaki; Nitadori, Keigo; Makino, Junichiro

Site: https://github.com/lwang-astro/PeTar
https://ui.adsabs.harvard.edu/abs/2020MNRAS.497..536W

Bibcode: 2020ascl.soft07005W

ID: ascl:2007.005
Last edited by Ada Coda on Tue Aug 11, 2020 11:58 pm, edited 1 time in total.
Reason: Updated code entry.

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