Analysis of Sparse Matrix Data Formats and Locality on Graphical Processing Unit (GPU) Performance

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Provided by: International Journal of Advanced Research in Computer Science and Software Engineering (IJARCSSE)
Topic: Data Management
Format: PDF
The graphical processing unit is gaining popularity as a powerful commodity processor for computational modeling analysis in many engineering and scientific applications. Majority of scientific and engineering computational analysis codes are based on techniques such as the finite element method that results in large memory bound sparse matrix linear equation systems. The associated sparse matrices are stored in different sparse matrix compression formats in computational analysis software code developments. Solution of such large sparse matrix linear system of equations are integral and time consuming part of the computations which are solved via iterative solution approaches such as the pre-conditioned conjugate gradient method.
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