A General Relativistic Evolution Code on CUDA Architectures
Zink, Burkhard, Center for Computation and Technology, and Department of Physics and Astronomy, Louisiana State University
I describe the implementation of a finite-differencing code for solving Einstein's field equations on a GPU, and measure speed-ups compared to a serial code on a CPU for different parallelization and caching schemes. Using the most efficient scheme, the (single precision) GPU code on an NVIDIA Quadro FX 5600 is shown to be up to 26 times faster than the a serial CPU code running on an AMD Opteron 2.4 GHz. Even though the actual speed-ups in production codes will vary with the particular problem, the results obtained here indicate that future GPUs supporting double-precision operations can potentially be a very useful platform for solving astrophysical problems.
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