Full metadata record
DC Field | Value | Language |
---|---|---|
dc.contributor.author | 마상백 | - |
dc.date.accessioned | 2020-04-16T07:27:51Z | - |
dc.date.available | 2020-04-16T07:27:51Z | - |
dc.date.issued | 2004-06 | - |
dc.identifier.citation | INTERNATIONAL JOURNAL OF HIGH SPEED COMPUTING, v. 12, No. 1, Page. 55-68 | en_US |
dc.identifier.issn | 0129-0533 | - |
dc.identifier.uri | https://www.worldscientific.com/doi/abs/10.1142/S0129053304000232 | - |
dc.identifier.uri | https://repository.hanyang.ac.kr/handle/20.500.11754/151056 | - |
dc.description.abstract | In this paper we compare various parallel preconditioners for solving large sparse nonsymmetric linear systems. They are Block Jacobi, Point-SSOR, ILU(0) in the wavefront order, ILU(0) in the multi-color order, SPAI(SParse Approximate Inverse), and Multi-Color Block SOR. The Block jacobi and Point-SSOR are well-known, and ILU(0) is a one of the most popular preconditioner, but it is inherently {\em serial}. ILU(0) in the wavefront order maximizes the parallelism, and ILU(0) in the multi-color order achieves the parallelism of order($N$), where $N$ is the order of the matrix. The SPAI tries to capture the approximate inverse in sparse form, which, then, is expected to be a scalable preconditioner. Finally, we implemented the Multi-Color Block SOR preconditioner combined with direct sparse matrix solver. For the Laplacian matrix the SOR method is known to have a nondeteriorating rate of convergence when used with Multi-Color ordering. Since most of the time is spent on the diagonal inversion, which is done on each processor, we expect it to be a good scalable preconditioner. Finally, due to the blocking effect, it will be effective for ill-conditioned problems. Experiments were conducted for the Finite Difference discretizations of two problems with various meshsizes varying up to 1024 x 1024 , and for an ill-conditioned matrix from the shell problem from the Harwell-Boeing collection. CRAY-T3E with 128 nodes was used. MPI library was used for interprocess communications. The results show that Multi-Color Block SOR and ILU(0) with Multi-Color ordering give the best performances for the finite difference matrices and for the shell problem only the Multi-Color Block SOR and Block Jacobi converges. Based on this we recommend that the Multi-Color Block SOR is the most robust preconditioner out of the preconditioners considered. | en_US |
dc.description.sponsorship | The author would like to acknowledge the numerous advices of Prof. Youcef Saad, and also the Korea KISTI, which provided the computer facilities and an excellent research environment to conduct this research. | en_US |
dc.language.iso | en_US | en_US |
dc.publisher | WORLD SCIENTIFIC PUBL CO PTE LTD | en_US |
dc.subject | Parallel | en_US |
dc.subject | preconditioner | en_US |
dc.subject | sparse | en_US |
dc.subject | linear | en_US |
dc.subject | ILU(0) | en_US |
dc.subject | Mulit-Color Block SOR | en_US |
dc.title | COMPARISONS OF THE PARALLEL PRECONDITIONERS FOR LARGE NONSYMMETRIC SPARSE LINEAR SYSTEMS ON A PARALLEL COMPUTER | en_US |
dc.type | Article | en_US |
dc.identifier.doi | 10.1142/S0129053304000232 | - |
dc.relation.journal | INTERNATIONAL JOURNAL OF HIGH SPEED COMPUTING | - |
dc.contributor.googleauthor | MA, SANGBACK | - |
dc.relation.code | 2012214810 | - |
dc.sector.campus | E | - |
dc.sector.daehak | COLLEGE OF COMPUTING[E] | - |
dc.sector.department | DIVISION OF COMPUTER SCIENCE | - |
dc.identifier.pid | sangback2001 | - |
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