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High-Performancs Sparse Matrix-Vector Multiplication on GPUS for Structured Grid Computations

Godwin, Jeswin Samuel
http://rave.ohiolink.edu/etdc/view?acc_num=osu1357280824

Abstract Details

2013, Master of Science, Ohio State University, Computer Science and Engineering.
In this thesis, we address efficient sparse matrix-vector multiplication for matrices arising from structured grid problems with high degrees of freedom at each grid node. Sparse matrix-vector multiplication is a critical step in the iterative solution of sparse linear systems of equations arising in the solution of partial differential equations using uniform grids for discretization. With uniform grids, the resulting linear system Ax = b has a matrix A that is sparse with a very regular structure. The specific focus of this thesis is on sparse matrices that have a block structure due to the large number of unknowns at each grid point. Sparse matrix storage formats such as Compressed Sparse Row (CSR) and Diagonal format (DIA) are not the most effective for such matrices. In this thesis, we present a new sparse matrix storage format that takes advantage of the diagonal structure of matrices for stencil operations on structured grids. Unlike other formats such as the Diagonal storage format (DIA), we specifically optimize for the case of higher degrees of freedom, where formats such as DIA are forced to explicitly represent many zero elements in the sparse matrix. We develop efficient sparse matrix-vector multiplication for structured grid computations on GPU architectures using CUDA.
Sadayappan P (Advisor)
Srinivasan Parthasarathy (Committee Member)
41 p.
Computer Engineering; Computer Science
"SPMV; GPU; Structured Grid; Column-Diagonal"

Recommended Citations

Citations

  • Godwin, J. S. (2013). High-Performancs Sparse Matrix-Vector Multiplication on GPUS for Structured Grid Computations [Master's thesis, Ohio State University]. OhioLINK Electronic Theses and Dissertations Center. http://rave.ohiolink.edu/etdc/view?acc_num=osu1357280824

    APA Style (7th edition)

  • Godwin, Jeswin Samuel. High-Performancs Sparse Matrix-Vector Multiplication on GPUS for Structured Grid Computations. 2013. Ohio State University, Master's thesis. OhioLINK Electronic Theses and Dissertations Center, http://rave.ohiolink.edu/etdc/view?acc_num=osu1357280824.

    MLA Style (8th edition)

  • Godwin, Jeswin Samuel. "High-Performancs Sparse Matrix-Vector Multiplication on GPUS for Structured Grid Computations." Master's thesis, Ohio State University, 2013. http://rave.ohiolink.edu/etdc/view?acc_num=osu1357280824

    Chicago Manual of Style (17th edition)

osu1357280824
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© 2013, all rights reserved.
This open access ETD is published by The Ohio State University and OhioLINK.