ON SOLVING ENERGY-DEPENDENT PARTITIONED REAL SYMMETRIC MATRIX EIGENVALUE PROBLEM BY A PARALLEL GENETIC ALGORITHM

被引：1
|
作者：
Sharma, Rahul [1 ]
Nandy, Subhajit [1 ,2 ]
Bhattacharyya, S. P. [1 ]
机构：
[1] Indian Assoc Cultivat Sci, Dept Phys Chem, Kolkata 700032, India
[2] Andrews High HS Sch, Kolkata 700031, India
来源：
JOURNAL OF THEORETICAL & COMPUTATIONAL CHEMISTRY | 2008年 / 7卷 / 06期
关键词：
Symmetric matrix eigenvalue problem; parallel genetic algorithm; partitioning techniques; energy-dependent partitioning; Lowdin's method;
D O I：
10.1142/S0219633608004428
中图分类号：
O6 [化学];
学科分类号：
0703 ;
摘要：
An energy-dependent partitioning scheme is explored for extracting a small number of eigenvalues of a real symmetric matrix with the help of a serial as well as parallel genetic algorithm (GA). The proposed method is tested on two matrices (up to 2000 x 2000) with an increasing number of processors in a master- slave architecture. A comparison is made with the Jacobi-Davidson method in serial mode as implemented in the JDQZ-package. Different partition sizes are used. Traditionally used Lowdin's method is also tested in both serial and parallel modes. The advantages and disadvantages of the parallel GA-based method in solving the partitioned eigenvalue problem are analyzed.
引用
收藏
页码：1103 / 1120
页数：18
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