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Scaling Hierarchical N-body Simulations on GPU Clusters

Pritish Jetley, Lukasz Wesolowski, Filippo Gioachin, Laxmikant V. Kale, Thomas R. Quinn
Department of Computer Science, University of Illinois at Urbana-Champaign, Urbana, IL 61801, USA
ACM/IEEE International Conference for High Performance Computing, Networking, Storage and Analysis, 2010, SC2010, p.1-11

@article{jetley2010scaling,

   title={Scaling Hierarchical N-body Simulations on GPU Clusters},

   author={Jetley, P. and Wesolowski, L. and Gioachin, F. and Kal{‘e}, L.V. and Quinn, T.R.},

   journal={sc},

   pages={1–11},

   year={2010},

   publisher={IEEE Computer Society}

}

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This paper focuses on the use of GPGPU-based clusters for hierarchical N-body simulations. Whereas the behavior of these hierarchical methods has been studied in the past on CPU-based architectures, we investigate key performance issues in the context of clusters of GPUs. These include kernel organization and efficiency, the balance between tree traversal and force computation work, grain size selection through the tuning of offloaded work request sizes, and the reduction of sequential bottlenecks. The effects of various application parameters are studied and experiments done to quantify gains in performance. Our studies are carried out in the context of a production-quality parallel cosmological simulator called ChaNGa. We highlight the re-engineering of the application to make it more suitable for GPU-based environments. Finally, we present performance results from experiments on the NCSA Lincoln GPU cluster, including a note on GPU use in multistepped simulations.
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