A Comparison of QMR, CGS and TFQMR on a Distributed Memory Machine
A Comparison of QMR, CGS and TFQMR on a Distributed Memory Machine
For the solution of systems of linear equations with general non-Hermitian nonsingular coefficient matrices, an implementation of three different algorithms on a parallel machine with distributed memory is proposed. Each of the three algorithms, QMR, CGS and TFQMR, contains two matrix-vector product...
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Personal Name(s): | Bücker, Martin |
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Basermann, Achim | |
Contributing Institute: |
Jülich Supercomputing Center; JSC Zentralinstitut für Angewandte Mathematik; ZAM |
Published in: | 1994 |
Imprint: |
Jülich
Zentralinstitut für Angewandte Mathematik
1994
|
Physical Description: |
14 p. |
Document Type: |
Report |
Research Program: |
ohne Topic |
Publikationsportal JuSER |
For the solution of systems of linear equations with general non-Hermitian nonsingular coefficient matrices, an implementation of three different algorithms on a parallel machine with distributed memory is proposed. Each of the three algorithms, QMR, CGS and TFQMR, contains two matrix-vector products that dominate the execution time. While the matrix-vector products of CGS and TFQMR are dependent this is not valid for QMR. The two matrix-vector products of QMR can be computed simultaneously. This paper shows how the performance of a parallel implementation is increased by exploiting this property. Timing results of all three algorithms on an Intel PARAGON XP/S 10 system are presented. |