2007/07/16 by Robert G. Belleman, Jeroen Bédorf, Jeroen Bedorf +1 · 2 citations
Computer Science · Physics and Astronomy · #Computational Physics and Python Applications #Parallel Computing and Optimization Techniques #Scientific Research and Discoveries #astro-ph #physics.comp-ph
paper · pdf · doi:10.1016/j.newast.2007.07.004
published as NewAstron.13:103-112,2008 · Accepted for publication in New Astronomy
arxiv created 2007/07/16 · openalex publication_date 2007/07/31 · arxiv updated 2009/12/01 · openalex created_date 2025/10/10 · openalex updated_date 2026/08/04
We present the results of gravitational direct N-body simulations using the Graphics Processing Unit (GPU) on a commercial NVIDIA GeForce 8800GTX designed for gaming computers. The force evaluation of the N-body problem is implemented in ``Compute Unified Device Architecture'' (CUDA) using the GPU to speed-up the calculations. We tested the implementation on three different N-body codes: two direct N-body integration codes, using the 4th order predictor-corrector Hermite integrator with block time-steps, and one Barnes-Hut treecode, which uses a 2nd order leapfrog integration scheme. The integration of the equations of motions for all codes is performed on the host CPU. We find that for N > 512 particles the GPU outperforms the GRAPE-6Af, if some softening in the force calculation is accepted. Without softening and for very small integration time steps the GRAPE still outperforms the GPU. We conclude that modern GPUs offer an attractive alternative to GRAPE-6Af special purpose hardware. Using the same time-step criterion, the total energy of the N-body system was conserved better than to one in 106 on the GPU, only about an order of magnitude worse than obtained with GRAPE-6Af. For N \apgt 105 the 8800GTX outperforms the host CPU by a factor of about 100 and runs at about the same speed as the GRAPE-6Af.