| Description |
1 online resource (23 pages) : color illustrations. |
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text txt rdacontent |
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computer c rdamedia |
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online resource cr rdacarrier |
| Series |
NREL/CP ; 2C00-80263 |
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Conference paper (National Renewable Energy Laboratory (U.S.)) ; 2C00-80263.
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| Note |
"February 2022." |
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"Presented at the SIAM Annual Meeting, July 19-23, 2021"--Cover. |
| Bibliography |
Includes bibliographical references (pages 21-23). |
| Funding |
DE-AC36-08GO28308 |
| Note |
Description based on online resource; title from PDF title page (NREL, viewed June 8, 2022). |
| Summary |
Gauss-Seidel (GS) relaxation is often employed as a preconditioner for a Krylov solver or as a smoother for Algebraic Multigrid (AMG). However, the requisite sparse triangular solve is difficult to parallelize on many-core architectures such as graphics processing units (GPUs). In the present study, the performance of the sequential GS relaxation based on a triangular solve is compared with two-stage variants, replacing the direct triangular solve with a fixed number of inner Jacobi-Richardson (JR) iterations. When a small number of inner iterations is sufficient to maintain the Krylov convergence rate, the two-stage GS (GS2) often outperforms the sequential algorithm on many-core architectures. The GS2 algorithm is also compared with JR. When they perform the same number of ops for SpMV (e.g. three JR sweeps compared to two GS sweeps with one inner JR sweep), the GS2 iterations, and the Krylov solver preconditioned with GS2, may converge faster than the JR iterations. Moreover, for some problems (e.g. elasticity), it was found that JR may diverge with a damping factor of one, whereas two-stage GS may improve the convergence with more inner iterations. Finally, to study the performance of the two-stage smoother and preconditioner for a practical problem, these were applied to incompressible uid ow simulations on GPUs. |
| Subject |
Graphics processing units -- Testing.
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Parallel programming (Computer science)
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Parallel processing (Electronic computers)
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Programmation parallèle (Informatique)
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Parallélisme (Informatique)
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Parallel processing (Electronic computers)
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Parallel programming (Computer science)
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| Indexed Term |
algebraic multigrid |
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AMG |
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Gauss-Seidel |
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krylov |
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preconditioners |
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smoothers |
| Added Author |
National Renewable Energy Laboratory (U.S.), issuing body.
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| Standard No. |
1845268 OSTI ID |
| Gpo Item No. |
0430-P-04 (online) |
| Sudoc No. |
E 9.17:NREL/CP-2 C 00-80263 |
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