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High Performance Direct Gravitational N-body Simulations on Graphics Processing Units

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arxiv cs/0702135 v1 pith:55FW5RHT submitted 2007-02-23 cs.PF

classification cs.PF
keywords grapeparticlesbodygeforcegraphicsmodernorderprocessing
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abstract

We present the results of gravitational direct $N$-body simulations using the commercial graphics processing units (GPU) NVIDIA Quadro FX1400 and GeForce 8800GTX, and compare the results with GRAPE-6Af special purpose hardware. The force evaluation of the $N$-body problem was implemented in Cg using the GPU directly to speed-up the calculations. The integration of the equations of motions were, running on the host computer, implemented in C using the 4th order predictor-corrector Hermite integrator with block time steps. We find that for a large number of particles ($N \apgt 10^4$) modern graphics processing units offer an attractive low cost alternative to GRAPE special purpose hardware. A modern GPU continues to give a relatively flat scaling with the number of particles, comparable to that of the GRAPE. Using the same time step criterion the total energy of the $N$-body system was conserved better than to one in $10^6$ on the GPU, which is only about an order of magnitude worse than obtained with GRAPE. For $N\apgt 10^6$ the GeForce 8800GTX was about 20 times faster than the host computer. Though still about an order of magnitude slower than GRAPE, modern GPU's outperform GRAPE in their low cost, long mean time between failure and the much larger onboard memory; the GRAPE-6Af holds at most 256k particles whereas the GeForce 8800GTF can hold 9 million particles in memory.

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  1. Machine learning prediction of binary formation in three-body gravitational encounters

    astro-ph.GA 2026-07 conditional novelty 6.0 of 10

    An XGBoost classifier trained on 312,666 three-body scattering simulations predicts binary formation from initial conditions with PR-AUC 0.99 on balanced data but 0.66 on realistic imbalanced data.

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