A parallel computer implementation of fast low-rank QR approximation of the Biot-Savart law

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In this paper we present a low-rank QR method for evaluating the discrete Biot-Savart law on parallel computers. It is assumed that the known current density and the unknown magnetic field are both expressed in a finite element expansion, and we wish to compute the degrees-of-freedom (DOF) in the basis function expansion of the magnetic field. The matrix that maps the current DOF to the field DOF is full, but if the spatial domain is properly partitioned the matrix can be written as a block matrix, with blocks representing distant interactions being low rank and having a compressed QR representation. ... continued below

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White, D A; Fasenfest, B J & Stowell, M L November 7, 2005.

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In this paper we present a low-rank QR method for evaluating the discrete Biot-Savart law on parallel computers. It is assumed that the known current density and the unknown magnetic field are both expressed in a finite element expansion, and we wish to compute the degrees-of-freedom (DOF) in the basis function expansion of the magnetic field. The matrix that maps the current DOF to the field DOF is full, but if the spatial domain is properly partitioned the matrix can be written as a block matrix, with blocks representing distant interactions being low rank and having a compressed QR representation. The matrix partitioning is determined by the number of processors, the rank of each block (i.e. the compression) is determined by the specific geometry and is computed dynamically. In this paper we provide the algorithmic details and present computational results for large-scale computations.

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  • Presented at: Progress in Electromagnetics Research Symposium, Cambridge, MA, United States, Mar 26 - Mar 29, 2006

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  • Report No.: UCRL-CONF-216989
  • Grant Number: W-7405-ENG-48
  • Office of Scientific & Technical Information Report Number: 887290
  • Archival Resource Key: ark:/67531/metadc885986

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  • November 7, 2005

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  • Sept. 21, 2016, 2:29 a.m.

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  • Nov. 30, 2016, 4:12 p.m.

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White, D A; Fasenfest, B J & Stowell, M L. A parallel computer implementation of fast low-rank QR approximation of the Biot-Savart law, article, November 7, 2005; Livermore, California. (digital.library.unt.edu/ark:/67531/metadc885986/: accessed August 18, 2017), University of North Texas Libraries, Digital Library, digital.library.unt.edu; crediting UNT Libraries Government Documents Department.