| Optimization and scaling of shared-memory and message-passing implementations of the ZEUS hydrodynamics algorithm |
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Conference on High Performance Networking and Computing
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Proceedings of the 1997 ACM/IEEE conference on Supercomputing (CDROM)
table of contents
San Jose, CA
Pages: 1 - 16
Year of Publication: 1997
ISBN:0-89791-985-8
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Downloads (6 Weeks): 1, Downloads (12 Months): 7, Citation Count: 3
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ABSTRACT
We compare the performance of shared-memory and message-passing versions of the ZEUS algorithm for astrophysical fluid dynamics on a 64-processor HP/Convex Exemplar SPP-2000. Single-processor optimization is guided by timing several versions of simple loops whose structure typifies the main performance bottlenecks. Overhead is minimized in the message-passing implementation through the use of non-blocking communication operations. Our benchmark results agree reasonably well with the predictions of a simple performance model. The message-passing version of ZEUS scales better than the shared-memory one primarily because, under shared-memory, (unless data-layout directives are utilized) the domain decomposition is effectively one-dimensional.
REFERENCES
Note: OCR errors may be found in this Reference List extracted from the full text article. ACM has opted to expose the complete List rather than only correct and linked references.
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Clarke, David A., M. L. Norman, and R. A. Fiedler, "ZEUS-3D User Manual", LCA Technical Report no. 15, 1994.
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Gropp, William, E. Lusk, and A. Skjellum, "Using MPI", MIT Press, 1994.
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Stone, James M., and M. Norman, Astrophysical Journal Supplement Series, vol. 80, pp. 753-818, 1992.
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CITED BY 3
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A. Chien , M. Lauria , R. Pennington , M. Showerman , G. Iannello , M. Buchanan , K. Connelly , L. Giannini , G. Koeni , S. Krishnamurthy , Q. Liu , S. Pakin , G. Sampemane, Design and Evaluation of an HPVM-Based Windows NT Supercomputer, International Journal of High Performance Computing Applications, v.13 n.3, p.201-219, August 1999
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Hu Chen , Wenguang Chen , Jian Huang , Bob Robert , H. Kuhn, MPIPP: an automatic profile-guided parallel process placement toolset for SMP clusters and multiclusters, Proceedings of the 20th annual international conference on Supercomputing, June 28-July 01, 2006, Cairns, Queensland, Australia
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