A Refined Distributed Parallel Algorithm For The Eigenvalue Problem Of Large-scale Matrix

被引：0

作者：

Zhao, Lu ^{[1
]}

Zhuang, Yi ^{[2
]}

Liu, Yi ^{[3
]}

Ni, Tian Quan ^{[4
]}

机构：

[1] Nanjing Univ Aeronaut & Astronaut, Coll Informat Sci & Technol, Nanjing 210016, Peoples R China

[2] Nanjing Univ Aeronaut & Astronaut, Coll Aerosp Engn, Nanjing 210016, Peoples R China

[3] Tongji Univ, Coll Aerosp Engn & Appl Mech, Shanghai 200092, Peoples R China

[4] China Shipbldg Ind Corp, Inst 723, Yangzhou 225001, Jiangsu, Peoples R China

来源：

2010 3RD INTERNATIONAL CONFERENCE ON BIOMEDICAL ENGINEERING AND INFORMATICS (BMEI 2010), VOLS 1-7 | 2010年

关键词：

eigenvalue problem; substructure method; finite element; distributed parallel algorithm; Subspace iteration algorithm; mode synthesis;

D O I：

10.1109/BMEI.2010.5639939

中图分类号：

R318 [生物医学工程];

学科分类号：

0831 ;

摘要：

In view of eigenvalue problems of large-scale matrix, this paper proposes a refined distributed parallel algorithm named RDPC-DTM based on direct transformation method and DPC-DTM algorithm which is a distributed parallel design of direct transformation method. This new method solves the problem that increasing the number of substructure could not effectively enhance the computing efficiency when the scale of matrix is too large. Numerical experiment proves that RDPC-DTM is more efficient than DPC-DTM, especially when calculating eigenvalue of super large-scale matrix. Numerical experiment also demonstrates that RDPC-DTM has higher degree of parallelism and is more suitable for cluster or MPP parallel computer compared to DPC-DTM.

引用

页码：2780 / 2784

页数：5

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