Streamline Integration Using MPI-Hybrid Parallelism on a Large Multicore Architecture

Authors:
David Camp;Christoph Garth;Hank Childs;David Pugmire;Kenneth Joy
Affiliations:
Lawrence Berkeley National Laboratory, Berkeley and University of California, Davis, Davis;University of California, Davis, Davis;Lawrence Berkeley National Laboratory, Berkeley and University of California, Davis, Davis;Oak Ridge National Laboratory, Oak Ridge;University of California, Davis, Davis
Venue:
IEEE Transactions on Visualization and Computer Graphics
Year:
2011

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Abstract

Streamline computation in a very large vector field data set represents a significant challenge due to the nonlocal and data-dependent nature of streamline integration. In this paper, we conduct a study of the performance characteristics of hybrid parallel programming and execution as applied to streamline integration on a large, multicore platform. With multicore processors now prevalent in clusters and supercomputers, there is a need to understand the impact of these hybrid systems in order to make the best implementation choice. We use two MPI-based distribution approaches based on established parallelization paradigms, parallelize over seeds and parallelize over blocks, and present a novel MPI-hybrid algorithm for each approach to compute streamlines. Our findings indicate that the work sharing between cores in the proposed MPI-hybrid parallel implementation results in much improved performance and consumes less communication and I/O bandwidth than a traditional, nonhybrid distributed implementation.