Sparse Computing Function for GPU processing with CUDA

• Main Authors: Shih-Hwa Liu, 劉世華
• Other Authors: Rong-Guey Chang
• Format: Others
• Language: zh-TW
• Published: 2013
• Online Access: http://ndltd.ncl.edu.tw/handle/56127638081780080848

碩士 === 國立中正大學 === 資訊工程研究所 === 101 === Sparse matrix computing is an important role in mathematic computing or other graph processing. How to processing sparse matrix computing faster becoming a important issue. Sparse matrix is usually used in modern scientific knowledge and Engineering. This matrix has a special feature that most of the elements in the matrix are zero; this feature let the sparse matrix computing has many unnecessary computing. To let this kind of matrix has better computing ability, we construct a library for sparse matrix computing only, reference by fortran2003 handbook, and the CUDA on GPU is the platform which has the best Parallel Computing nowadays. We also propose five optimizing methods to improve the library which we construct for sparse matrix computing. Keywords: GPU, sparse matrix, function library