Adaptive Row-grouped CSR Format for Storing of Sparse Matrices on GPU

Martin Heller, Tomas Oberhuber
Department of mathematics, Faculty of Nuclear Sciences and Physical Engineering, Czech Technical University in Prague, Trojanova 13, Praha 2, 120 00, Czech Republic
arXiv:1203.5737v1 [cs.DC] (26 Mar 2012)


   title={Adaptive Row-grouped CSR Format for Storing of Sparse Matrices on GPU},

   author={Heller, Martin and Oberhuber, Tomas},



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We present new adaptive format for storing sparse matrices on GPU. We compare it with several other formats including CUSPARSE which is today probably the best choice for processing of sparse matrices on GPU in CUDA. Contrary to CUSPARSE which works with common CSR format, our new format requires conversion. However, multiplication of sparse-matrix and vector is significantly faster for many atrices. We demonstrate it on set of 1 600 matrices and we show for what types of matrices our format is profitable.
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