Enabling Computational Technologies for Terascale Scientific Simulations

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We develop scalable algorithms and object-oriented code frameworks for terascale scientific simulations on massively parallel processors (MPPs). Our research in multigrid-based linear solvers and adaptive mesh refinement enables Laboratory programs to use MPPs to explore important physical phenomena. For example, our research aids stockpile stewardship by making practical detailed 3D simulations of radiation transport. The need to solve large linear systems arises in many applications, including radiation transport, structural dynamics, combustion, and flow in porous media. These systems result from discretizations of partial differential equations on computational meshes. Our first research objective is to develop multigrid preconditioned iterative methods for ... continued below

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22,708 Kilobytes pages

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Ashby, S.F. August 24, 2000.

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Description

We develop scalable algorithms and object-oriented code frameworks for terascale scientific simulations on massively parallel processors (MPPs). Our research in multigrid-based linear solvers and adaptive mesh refinement enables Laboratory programs to use MPPs to explore important physical phenomena. For example, our research aids stockpile stewardship by making practical detailed 3D simulations of radiation transport. The need to solve large linear systems arises in many applications, including radiation transport, structural dynamics, combustion, and flow in porous media. These systems result from discretizations of partial differential equations on computational meshes. Our first research objective is to develop multigrid preconditioned iterative methods for such problems and to demonstrate their scalability on MPPs. Scalability describes how total computational work grows with problem size; it measures how effectively additional resources can help solve increasingly larger problems. Many factors contribute to scalability: computer architecture, parallel implementation, and choice of algorithm. Scalable algorithms have been shown to decrease simulation times by several orders of magnitude.

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22,708 Kilobytes pages

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  • Other Information: PBD: 24 Aug 2000

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  • Report No.: UCRL-ID-140219
  • Grant Number: W-7405-Eng-48
  • DOI: 10.2172/802085 | External Link
  • Office of Scientific & Technical Information Report Number: 802085
  • Archival Resource Key: ark:/67531/metadc738735

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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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  • August 24, 2000

Added to The UNT Digital Library

  • Oct. 19, 2015, 7:39 p.m.

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  • May 6, 2016, 3:17 p.m.

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Ashby, S.F. Enabling Computational Technologies for Terascale Scientific Simulations, report, August 24, 2000; California. (digital.library.unt.edu/ark:/67531/metadc738735/: accessed April 21, 2018), University of North Texas Libraries, Digital Library, digital.library.unt.edu; crediting UNT Libraries Government Documents Department.