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Combining Performance Aspects of Irregular Gauss-Seidel Via Sparse Tiling

  • Conference paper
Languages and Compilers for Parallel Computing (LCPC 2002)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 2481))

Abstract

Finite Element problems are often solved using multigrid techniques. The most time consuming part of multigrid is the iterative smoother, such as Gauss-Seidel. To improve performance, iterative smoothers can exploit parallelism, intra-iteration data reuse, and inter-iteration data reuse. Current methods for parallelizing Gauss-Seidel on irregular grids, such as multi-coloring and owner-computes based techniques, exploit parallelism and possibly intra-iteration data reuse but not inter-iteration data reuse. Sparse tiling techniques were developed to improve intra-iteration and inter-iteration data locality in iterative smoothers. This paper describes how sparse tiling can additionally provide parallelism. Our results show the effectiveness of Gauss-Seidel parallelized with sparse tiling techniques on shared memory machines, specifically compared to owner-computes based Gauss-Seidel methods. The latter employ only parallelism and intra-iteration locality. Our results support the premise that better performance occurs when all three performance aspects (parallelism, intra-iteration, and inter-iteration data locality) are combined.

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Authors and Affiliations

  1. University of California, San Diego, 9500, Gilman Dr. La Jolla, CA, 92093-0114, USA

    Michelle Mills Strout, Larry Carter, Jeanne Ferrante, Jonathan Freeman & Barbara Kreaseck

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  1. Michelle Mills Strout
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  2. Larry Carter
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  3. Jeanne Ferrante
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  4. Jonathan Freeman
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  5. Barbara Kreaseck
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Editors and Affiliations

  1. Deptartment of Computer Science, University of Maryland, 4135 A.V. Williams Bldg., College Park, 20742, MD, USA

    Bill Pugh

  2. Dept. of Computer Science, Univ. of Maryland at College Park,  

    Chau-Wen Tseng

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Strout, M.M., Carter, L., Ferrante, J., Freeman, J., Kreaseck, B. (2005). Combining Performance Aspects of Irregular Gauss-Seidel Via Sparse Tiling. In: Pugh, B., Tseng, CW. (eds) Languages and Compilers for Parallel Computing. LCPC 2002. Lecture Notes in Computer Science, vol 2481. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11596110_7

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  • DOI: https://doi.org/10.1007/11596110_7

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-30781-5

  • Online ISBN: 978-3-540-31612-1

  • eBook Packages: Computer ScienceComputer Science (R0)

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