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| + | ==Summary== | ||
| + | A new hybrid algorithm for LDU -factorization for large sparse matrix combining iterative solver, which can keep the same accuracy as the classical factorization, is proposed. The last Schur complement will be generated by iterative solver for multiple right-hand sides using block GCR method with the factorization in lower precision as a preconditioner, which achieves mixed precision arithmetic, and then the Schur complement will be factorized in higher precision. In this algorithm, essential procedure is decomposition of the matrix into a union of moderate and hard parts, which is realized by LDU -factorization in lower precision with symmetric pivoting and threshold postponing technique. | ||
| + | |||
| + | == Abstract == | ||
| + | <pdf>Media:Draft_Sanchez Pinedo_5687167442114_abstract.pdf</pdf> | ||
| + | |||
| + | == Full Paper == | ||
| + | <pdf>Media:Draft_Sanchez Pinedo_5687167442114_paper.pdf</pdf> | ||
Latest revision as of 16:06, 25 November 2022
Summary
A new hybrid algorithm for LDU -factorization for large sparse matrix combining iterative solver, which can keep the same accuracy as the classical factorization, is proposed. The last Schur complement will be generated by iterative solver for multiple right-hand sides using block GCR method with the factorization in lower precision as a preconditioner, which achieves mixed precision arithmetic, and then the Schur complement will be factorized in higher precision. In this algorithm, essential procedure is decomposition of the matrix into a union of moderate and hard parts, which is realized by LDU -factorization in lower precision with symmetric pivoting and threshold postponing technique.
Abstract
Full Paper
Document information
Published on 24/11/22
Accepted on 24/11/22
Submitted on 24/11/22
Volume Science Computing, 2022
DOI: 10.23967/eccomas.2022.006
Licence: CC BY-NC-SA license
