PELLR: A Permutated ELLPACK-R Format for SpMV on GPUs

• 作者: Tongxiang Gu Zhiqi Wang
• 来源期刊: 电脑和通信(英文)
• 学科: 工学
• 关键词: SpMV GPU STORAGE FORMAT HIGH PERFORMANCE
• 年，卷（期）: 2020,（4）
• 页码范围: 44-58
• 页数: 15页
• 分类号: TP3

摘要

The sparse matrix vector multiplication (SpMV) is inevitable in almost all kinds of scientific computation, such as iterative methods for solving linear systems and eigenvalue problems. With the emergence and development of Graphics Processing Units (GPUs), high efficient formats for SpMV should be constructed. The performance of SpMV is mainly determinted by the storage format for sparse matrix. Based on the idea of JAD format, this paper improved the ELLPACK-R format, reduced the waiting time between different threads in a warp, and the speed up achieved about 1.5 in our experimental results. Compared with other formats, such as CSR, ELL, BiELL and so on, our format performance of SpMV is optimal over 70 percent of the test matrix. We proposed a method based on parameters to analyze the performance impact on different formats. In addition, a formula was constructed to count the computation and the number of iterations.