High performance numerical solutions for sparse generalized systems
Conference
·
OSTI ID:125559
- Univ. of Hawaii, Honolulu, HI (United States)
A generalized block Arnoldi method for sparse generalized systems is studied. The algorithm, based on the Krylov subspace technique, transforms a pair of sparse matrices to a Hessenberg-triangular form. To avoid destroying the sparsity of the matrices, the computation of the matrix inverse and matrix product are replaced by the GMRES (generalized minimal residual algorithm for solving sparse systems), Arnoldi iterations and QR decomposition. The complexity of the resulting algorithm is O(n{sup 2}k), where n is the order of matrices E and A and k is the number of generalized Arnoldi iterations.
- OSTI ID:
- 125559
- Report Number(s):
- CONF-950212--; CNN: Contract 972-93-1-0032; Contract NCR-9210408
- Country of Publication:
- United States
- Language:
- English
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