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Parameter Tuning of a Hybrid Treecode-FMM on GPUs

Rio Yokota, L. A. Barba
Dept. Mechanical Engineering, Boston University, 15 St. Mary’s Street, Boston, Massachusetts
Characterizing Applications for Heterogeneous Exascale Systems (CACHES’11), at the 25th International Conference on Supercomputing (ACM/SIGARCH), 2011

@article{yokota2011parameter,

   title={Parameter Tuning of a Hybrid Treecode-FMM on GPUs},

   author={Yokota, R. and Barba, L.},

   year={2011}

}

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Treecodes are O(N log N) hierarchical N-body algorithms, which have traditionally been used for applications in astrophysics, in a low-accuracy regime. Fast multipole methods (FMM) are O(N) hierarchical N-body algorithms that have been used in a variety of applications, often in the high-accuracy regime. Both algorithms are known to perform well on massively parallel heterogeneous systems, with the treecode showing stronger speed-ups due to higher computational intensity. We propose a hybridization of the two algorithms and aim to determine whether such approach can best either algorithm on its own. We study the behavior of the hybrid treecode-FMM for different accuracies, along with its performance on GPUs.
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