MSTAR -- a fast parallelised algorithmically regularised integrator with minimum spanning tree coordinates

Antti Rantala; Pauli Pihajoki; Matias Mannerkoski; Peter H. Johansson; Thorsten Naab

doi:10.1093/mnras/staa084

paper

MSTAR -- a fast parallelised algorithmically regularised integrator with minimum spanning tree coordinates

arXiv:2001.03180 · doi:10.1093/mnras/staa084

Abstract

We present the novel algorithmically regularised integration method MSTAR for high accuracy ( $∣Δ E / E ∣ ≳ 1 0^{- 14}$ ) integrations of N-body systems using minimum spanning tree coordinates. The two-fold parallelisation of the $O (N_{part}^{2})$ force loops and the substep divisions of the extrapolation method allows for a parallel scaling up to $N_{CPU} = 0.2 \times N_{part}$ . The efficient parallel scaling of MSTAR makes the accurate integration of much larger particle numbers possible compared to the traditional algorithmic regularisation chain (AR-CHAIN) methods, e.g. $N_{part} = 5000$ particles on $400$ CPUs for $1$ Gyr in a few weeks of wall-clock time. We present applications of MSTAR on few particle systems, studying the Kozai mechanism and N-body systems like star clusters with up to $N_{part} = 1 0^{4}$ particles. Combined with a tree or a fast multipole based integrator the high performance of MSTAR removes a major computational bottleneck in simulations with regularised subsystems. It will enable the next generation galactic-scale simulations with up to $1 0^{9}$ stellar particles (e.g. $m_{⋆} = 100 M_{⊙}$ for a $M_{⋆} = 1 0^{11} M_{⊙}$ galaxy) including accurate collisional dynamics in the vicinity of nuclear supermassive black holes.

20 pages, 16 figures, accepted for publication in MNRAS

MSTAR -- a fast parallelised algorithmically regularised integrator with minimum spanning tree coordinates

Abstract

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