Parallel solving symmetric eigenproblems

In this paper parallel solving symmetric eigenproblems, which include standard and generalized eigenvalue problems, is discussed. For standard eigenvalue problem and tridiagonal eigenvalue problem is not the key point. For symmetric-definite generalized eigenvalue problem, which arises in solving ma...

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Published inFifth International Conference on Algorithms and Architectures for Parallel Processing, 2002. Proceedings pp. 434 - 437
Main Authors Xing-qin Cao, Xue-bin Chi, Ming Gu
Format Conference Proceeding
LanguageEnglish
Published IEEE 2002
Subjects
Algorithms
Computer networks
Computer science
Concurrent computing
Eigenvalues and eigenfunctions
Mathematics
Physics computing
Quantum computing
Standardization
Symmetric matrices
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Summary:In this paper parallel solving symmetric eigenproblems, which include standard and generalized eigenvalue problems, is discussed. For standard eigenvalue problem and tridiagonal eigenvalue problem is not the key point. For symmetric-definite generalized eigenvalue problem, which arises in solving many actual application problems, we give a new parallel computational method for reducing the generalized eigenproblem to standard one. The parallel algorithm is fully considered in reducing the communications. The numerical measurement is given in SGI/Cray T3E and Hitachi SR2201. Some computational results are compared with ScaLAPACK.
ISBN:0769515126
9780769515120
DOI:10.1109/ICAPP.2002.1173615