Multicore-based performance optimization for dense matrix computation

被引：0
|
作者：
Mao Guoyong [1 ]
Zhang, Xiaobin [2 ]
Li, Yun [2 ]
Li, Yujie [2 ]
Wei, Laizhi [2 ]
机构：
[1] Changzhou Inst Technol, Dept Elect Informat & Elect Engn, Changzhou Key Lab Res & Applicat Software Technol, Changzhou 213002, Peoples R China
[2] Yangzhou Univ, Coll Informat Engn, Yangzhou 225009, Jiangsu, Peoples R China
来源：
2010 INTERNATIONAL COLLOQUIUM ON COMPUTING, COMMUNICATION, CONTROL, AND MANAGEMENT (CCCM2010), VOL IV | 2010年
关键词：
Gaussian elimination; matrix block; multicore; parallel computing;
D O I：
暂无
中图分类号：
TP301 [理论、方法];
学科分类号：
081202 ;
摘要：
To make the traditional applications benefit from multicore processors, the traditional Gaussian Elimination algorithm is improved to enhance its parallel performance under multicore architecture by matrix partition. The stability of the original algorithm is guaranteed. The hit rate of cache is improved by adjusting the computation sequence, the experiment shows that the speedup can reach 1.8 under duo core CPU environment when evaluating the inverse of dense matrix.
引用
收藏
页码：9 / 12
页数：4
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