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An Exploration of OpenCL for a Numerical Relativity Application

Niket K. Choudhary, Rakesh Ginjupalli, Sandeep Navada, Gaurav Khanna
Physics Department, University of Massachusetts Dartmouth, North Dartmouth, MA 02747
arXiv:1010.3816v1 [gr-qc] (19 Oct 2010)

@article{choudhary2010exploration,

   title={An Exploration of OpenCL for a Numerical Relativity Application},

   author={Choudhary, N.K. and Ginjupalli, R. and Navada, S. and Khanna, G.},

   journal={Arxiv preprint arXiv:1010.3816},

   year={2010}

}

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Currently there is considerable interest in making use of many-core processor architectures, such as Nvidia and AMD graphics processing units (GPUs) for scientific computing. In this work we explore the use of the Open Computing Language (OpenCL) for a typical Numerical Relativity application: a time-domain Teukolsky equation solver (a linear, hyperbolic, partial differential equation solver using finite-differencing). OpenCL is the only vendor-agnostic and multi-platform parallel computing framework that has been adopted by all major processor vendors. Therefore, it allows us to write portable source-code and run it on a wide variety of compute hardware and perform meaningful comparisons. The outcome of our experimentation suggests that it is relatively straightforward to obtain order-of-magnitude gains in overall application performance by making use of many-core GPUs over multi-core CPUs and this fact is largely independent of the specific hardware architecture and vendor. We also observe that a single high-end GPU can match the performance of a small-sized, message-passing based CPU cluster.
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