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Heuristic Optimization Methods for Improving Performance of Recursive General Purpose Applications on GPUs

Shinichi Yamagiwa, Koichi Wada, Leonel Sousa
INESC-ID/IST, Lisbon, Portugal
International Symposium on Parallel and Distributed Computing, 2008. ISPDC ’08

@conference{yamagiwa2008heuristic,

   title={Heuristic Optimization Methods for Improving Performance of Recursive General Purpose Applications on GPUs},

   author={Yamagiwa, S. and Wada, K. and Sousa, L.},

   booktitle={2008 International Symposium on Parallel and Distributed Computing},

   pages={325–332},

   year={2008},

   organization={IEEE}

}

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Due to the demand of high definition graphics presentation in gaming and video market, graphics processing units (GPUs) have drastically increased their computational capacities. General-purpose computation on GPUs uses the fragment shader multicore of these processing units to concurrently process data streams. However, the I/O overheads in recursive GPGPU applications have a negative impact in the performance of those systems. This paper proposes the remap method to improve the performance of general purpose recursive applications on GPUs, by decreasing the I/O overheads imposed by the VRAM/GPU interface. It is shown that significant performance improvements are achieved by applying the remap method to realistic recursive applications.
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