BiELL: A bisection ELLPACK-based storage format for optimizing SpMV on GPUs |
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| Authors: | Cong Zheng Shuo Gu Tong-Xiang Gu Bing Yang Xing-Ping Liu |
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| Affiliation: | 1. Graduate School of Chinese Academy of Engineering Physics, P.O. Box 2101, Beijing, PR China;2. School of Electronic Engineering, University of Electronic Science and Technology of China, Chengdu 611731, PR China;3. Laboratory of Computational Physics, Institute of Applied Physics and Computational Mathematics, P.O. Box 8009, Beijing 100088, PR China |
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| Abstract: | Sparse matrix–vector multiplication (SpMV) is one of the most important high level operations for basic linear algebra. Nowadays, the GPU has evolved into a highly parallel coprocessor which is suited to compute-intensive, highly parallel computation. Achieving high performance of SpMV on GPUs is relatively challenging, especially when the matrix has no specific structure. For these general sparse matrices, a new data structure based on the bisection ELLPACK format, BiELL, is designed to realize the load balance better, and thus improve the performance of the SpMV. Besides, based on the same idea of JAD format, the BiJAD format can be obtained. Experimental results on various matrices show that the BiELL and BiJAD formats perform better than other similar formats, especially when the number of non-zero elements per row varies a lot. |
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| Keywords: | Sparse matrix&ndash vector multiplication GPU BiELL BiJAD |
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