Parallel processing of numerical transport algorithms

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The multigroup, discrete ordinates representation for the linear transport equation enjoys widespread computational use and popularity. Serial solution schemes and numerical algorithms developed over the years provide a timely framework for parallel extension. On the Denelcor HEP, we investigate the parallel structure and extension of a number of standard S/sub n/ approaches. Concurrent inner sweeps, coupled acceleration techniques, synchronized inner-outer loops, and chaotic iteration are described, and results of computations are contrasted. The multigroup representation and serial iteration methods are also detailed. The basic iterative S/sub n/ method lends itself to parallel tasking, portably affording an effective medium for performing ... continued below

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Pages: 16

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Wienke, B.R. & Hiromoto, R.E. January 1, 1984.

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Description

The multigroup, discrete ordinates representation for the linear transport equation enjoys widespread computational use and popularity. Serial solution schemes and numerical algorithms developed over the years provide a timely framework for parallel extension. On the Denelcor HEP, we investigate the parallel structure and extension of a number of standard S/sub n/ approaches. Concurrent inner sweeps, coupled acceleration techniques, synchronized inner-outer loops, and chaotic iteration are described, and results of computations are contrasted. The multigroup representation and serial iteration methods are also detailed. The basic iterative S/sub n/ method lends itself to parallel tasking, portably affording an effective medium for performing transport calculations on future architectures. This analysis represents a first attempt to extend serial S/sub n/ algorithms to parallel environments and provides good baseline estimates on ease of parallel implementation, relative algorithm efficiency, comparative speedup, and some future directions. We find basic inner-outer and chaotic iteration strategies both easily support comparably high degrees of parallelism. Both accommodate parallel rebalance and diffusion acceleration and appear as robust and viable parallel techniques for S/sub n/ production work.

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Pages: 16

Notes

NTIS, PC A02/MF A01; 1.

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  • Conference on vector and parallel processors in computational science II, Oxford, UK, 28 Aug 1984

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  • Other: DE84016825
  • Report No.: LA-UR-84-2609
  • Report No.: CONF-8408100-1
  • Grant Number: W-7405-ENG-36
  • Office of Scientific & Technical Information Report Number: 6522775
  • Archival Resource Key: ark:/67531/metadc1212849

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Office of Scientific & Technical Information Technical Reports

Reports, articles and other documents harvested from the Office of Scientific and Technical Information.

Office of Scientific and Technical Information (OSTI) is the Department of Energy (DOE) office that collects, preserves, and disseminates DOE-sponsored research and development (R&D) results that are the outcomes of R&D projects or other funded activities at DOE labs and facilities nationwide and grantees at universities and other institutions.

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  • January 1, 1984

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  • July 5, 2018, 11:11 p.m.

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  • Oct. 16, 2018, 1:48 p.m.

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Wienke, B.R. & Hiromoto, R.E. Parallel processing of numerical transport algorithms, article, January 1, 1984; United States. (digital.library.unt.edu/ark:/67531/metadc1212849/: accessed January 22, 2019), University of North Texas Libraries, Digital Library, digital.library.unt.edu; crediting UNT Libraries Government Documents Department.