High performance direct gravitational N-body simulations on graphics processing units II: An implementation in CUDA
Section Computational Science, University of Amsterdam, Amsterdam, The Netherlands
New Astronomy, Vol. 13, No. 2. (16 February 2008), pp. 103-112.
@article{belleman2008high,
title={High performance direct gravitational N-body simulations on graphics processing units II: An implementation in CUDA},
author={Belleman, R.G. and B{‘e}dorf, J. and Portegies Zwart, S.F.},
journal={New Astronomy},
volume={13},
number={2},
pages={103–112},
issn={1384-1076},
year={2008},
publisher={Elsevier}
}
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 speedup 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 10 6 on the GPU, only about an order of magnitude worse than obtained with GRAPE-6Af. For N 10 5 the 8800GTX outperforms the host CPU by a factor of about 100 and runs at about the same speed as the GRAPE-6Af.
October 30, 2010 by hgpu
