DocumentCode :
694339
Title :
Research on parallel model for sparse matrix-vector iterative multiplication
Author :
Jingzhu Li ; Peng Zou ; Qingbo Wu
Author_Institution :
Sch. of Comput. Sci., Nat. Univ. of Defense Technol., Changsha, China
fYear :
2013
fDate :
12-13 Oct. 2013
Firstpage :
122
Lastpage :
125
Abstract :
The most effective algorithms of solving large sparse linear system are Block Wiedemann and Block Lanczos, sparse matrix-vector multiplication iterations is the main process of these algorithms, to achieve parallel computing of its process, we have established three different parallel algorithm models and analyzed the characteristic features of their computing and communication, and through the analysis and comparison of time-cost, we choose the optimal model.
Keywords :
iterative methods; linear systems; matrix multiplication; parallel algorithms; sparse matrices; vectors; Block Lanczos; Block Wiedemann; large sparse linear system; parallel algorithm model; parallel computing; sparse matrix-vector iterative multiplication; Computational modeling; Data models; Educational institutions; Load modeling; Mathematical model; Sparse matrices; Vectors; Block Lanczos; Block Wiedemann; Large sparse linear equations; Parallel Computing; sparse matrix-vector iterative multiplication;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Computer Science and Network Technology (ICCSNT), 2013 3rd International Conference on
Conference_Location :
Dalian
Type :
conf
DOI :
10.1109/ICCSNT.2013.6967077
Filename :
6967077
Link To Document :
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