Accelerating NBODY6 with a GPU-Enabled Particle-Particle Particle-Tree Scheme

TL;DR

This paper presents a GPU-accelerated modification of the NBODY6 code that significantly speeds up star cluster simulations with minimal accuracy loss, enabling more efficient modeling of dense stellar systems.

Contribution

A novel GPU-enabled Barnes-Hut implementation integrated into NBODY6, enhancing computational speed for large-scale star cluster simulations.

Findings

Outperforms original NBODY6 for systems with over 300,000 particles.

Runs more than twice as fast for 1 million particle systems.

Maintains similar energy conservation levels.

Abstract

We describe a modified version of the NBODY6 code for simulating star clusters which greatly improves computational efficiency while sacrificing little in the way of accuracy. The distant force calculator is replaced by a GPU-enabled Barnes-Hut code, and integration is done with a standard leap frog scheme. Short-range forces continue to use the CPU-based fourth-order Hermite predictor-corrector scheme of NBODY6. Our code outperforms NBODY6 for systems with more than $3 \times 10^5$ particles and runs more than a factor 2 faster for systems of $10^6$ particles with similar energy conservation. Our code should be useful for simulating realistic dense stellar clusters, such as globular clusters or galactic nuclei.