Optimizing Sparse Matrix-Vector Multiplication on GPUS via Index Compression

Xue Sun, Kai Cheng Wei, Lien Fu Lai, Sung Han Tsai, Chao Chin Wu

研究成果: Conference contribution

摘要

Sparse matrix-vector multiplication (SpMV) as one of the most significant scientific kernels has been widely used in many scientific disciplines. In practical applications, large-scale spare matrices are usually used for calculation. During these years, Graphic Processing Unit (GPU) has become a powerful platform for high-performance computing, and optimizing SpMV on GPU based systems for efficient performance is the principal interest in many researches. In this paper, we proposed a new method to optimize SpMV on GPUs via index compression. Our index compression method can reduce the index value of the access space. The memory space for recording each column index is significantly reduced from two bytes to one byte, which outperforms the previous work on access performance. The main contributions we make are as follows: (1) Only one byte for each column index is required, which can significantly reduce the working set of the column index and further improve the cache hit ration. (2) Our method can be applied to any kind of matrices, while the previous work can only apply to subset of the matrices. Computational experiments on problems according to the previous work reveal that the best performance improvement ration for ours is up to about 1.5.

原文English
主出版物標題Proceedings of 2018 IEEE 3rd Advanced Information Technology, Electronic and Automation Control Conference, IAEAC 2018
編輯Bing Xu
發行者Institute of Electrical and Electronics Engineers Inc.
頁面598-602
頁數5
ISBN(電子)9781538645086
DOIs
出版狀態Published - 2018 十二月 14
事件3rd IEEE Advanced Information Technology, Electronic and Automation Control Conference, IAEAC 2018 - Chongqing, China
持續時間: 2018 十月 122018 十月 14

出版系列

名字Proceedings of 2018 IEEE 3rd Advanced Information Technology, Electronic and Automation Control Conference, IAEAC 2018

Other

Other3rd IEEE Advanced Information Technology, Electronic and Automation Control Conference, IAEAC 2018
國家China
城市Chongqing
期間18-10-1218-10-14

All Science Journal Classification (ASJC) codes

  • Artificial Intelligence
  • Computer Networks and Communications
  • Information Systems
  • Control and Optimization
  • Instrumentation

指紋 深入研究「Optimizing Sparse Matrix-Vector Multiplication on GPUS via Index Compression」主題。共同形成了獨特的指紋。

引用此