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

Journal Article · Tue Nov 01 04:00:00 EDT 2011 · IEEE Transactions on Visualization and Computer Graphics

DOI:https://doi.org/10.1109/TVCG.2010.259· OSTI ID:1045262

Camp, David ^[1]; Garth, Christoph ^[2]; Childs, Hank ^[3]; Pugmire, D. ^[4]; Joy, Kenneth ^[2]

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1. Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); Univ. of California, Davis, CA (United States)
2. Univ. of California, Davis, CA (United States)
3. Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States)
4. Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States)

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.

• Research Organization: Oak Ridge National Laboratory (ORNL), Oak Ridge, TN (United States)
• Sponsoring Organization: USDOE Office of Science (SC), Advanced Scientific Computing Research (ASCR) (SC-21); NSF
• DOE Contract Number: AC05-00OR22725
• OSTI ID: 1045262
• Journal Information: IEEE Transactions on Visualization and Computer Graphics, Journal Name: IEEE Transactions on Visualization and Computer Graphics Journal Issue: 11 Vol. 17; ISSN 1077-2626
• Publisher: IEEE
• Country of Publication: United States
• Language: English

Related Subjects

97 MATHEMATICS AND COMPUTING
ALGORITHMS
ARCHITECTURE
COMMUNICATIONS
DISTRIBUTION
HYBRID SYSTEMS
IMPLEMENTATION
PERFORMANCE
PROGRAMMING
SEEDS
SUPERCOMPUTERS
VECTOR FIELDS