Some computational challenges of developing efficient parallel algorithms for data-dependent computations in thermal-hydraulics supercomputer applications

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The Transient Reactor Analysis Code (TRAC), which features a two- fluid treatment of thermal-hydraulics, is designed to model transients in water reactors and related facilities. One of the major computational costs associated with TRAC and similar codes is calculating constitutive coefficients. Although the formulations for these coefficients are local the costs are flow-regime- or data-dependent; i.e., the computations needed for a given spatial node often vary widely as a function of time. Consequently, poor load balancing will degrade efficiency on either vector or data parallel architectures when the data are organized according to spatial location. Unfortunately, a general automatic solution ... continued below

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Pages: (13 p)

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Woodruff, S.B. January 1, 1992.

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The Transient Reactor Analysis Code (TRAC), which features a two- fluid treatment of thermal-hydraulics, is designed to model transients in water reactors and related facilities. One of the major computational costs associated with TRAC and similar codes is calculating constitutive coefficients. Although the formulations for these coefficients are local the costs are flow-regime- or data-dependent; i.e., the computations needed for a given spatial node often vary widely as a function of time. Consequently, poor load balancing will degrade efficiency on either vector or data parallel architectures when the data are organized according to spatial location. Unfortunately, a general automatic solution to the load-balancing problem associated with data-dependent computations is not yet available for massively parallel architectures. This document discusses why developers algorithms, such as a neural net representation, that do not exhibit algorithms, such as a neural net representation, that do not exhibit load-balancing problems.

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Pages: (13 p)

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OSTI; NTIS; INIS; GPO Dep.

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  • International topical meeting on reactor thermal hydraulics: towards the next generation of nuclear power plants, Salt Lake City, UT (United States), 20-24 Sep 1992

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  • Other: DE92011368
  • Report No.: LA-UR-92-859
  • Report No.: CONF-920903--4
  • Grant Number: W-7405-ENG-36
  • Office of Scientific & Technical Information Report Number: 5110504
  • Archival Resource Key: ark:/67531/metadc1060853

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  • January 1, 1992

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  • Jan. 22, 2018, 7:23 a.m.

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  • Feb. 1, 2018, 7:05 p.m.

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Woodruff, S.B. Some computational challenges of developing efficient parallel algorithms for data-dependent computations in thermal-hydraulics supercomputer applications, article, January 1, 1992; New Mexico. (digital.library.unt.edu/ark:/67531/metadc1060853/: accessed December 12, 2018), University of North Texas Libraries, Digital Library, digital.library.unt.edu; crediting UNT Libraries Government Documents Department.