Yang, X, Li, S, Yuan, F et al. (3 more authors) (2023) Optimizing Multi-grid Computation and Parallelization on Multi-cores. In: Proceedings of the ACM International Conference on Supercomputing. International Conference on Supercomputing, 21-23 Jun 2023, Orlando, Florida, USA. ICS '23: Proceedings of the 37th International Conference on Supercomputing . ACM , New York, New York , pp. 227-239. ISBN 9798400700569
Abstract
Multigrid algorithms are widely used to solve large-scale sparse linear systems, which is essential for many high-performance workloads. The symmetric Gauss-Seidel (SYMGS) method is often responsible for the performance bottleneck of MG. This paper presents new methods to parallelize and enhance the computation and parallelization efficiency of the SYMGS and MG algorithms on multi-core CPUs. Our solution employs a matrix splitting strategy and a revised computation formula to decrease the computation operations and memory accesses in SYMGS. With this new SYMGS strategy, we can then merge the two most time-consuming components of MG. On top of these, we propose a new asynchronous parallelization scheme to reduce the synchronization overhead when parallelizing SYMGS. We demonstrate the benefit of our techniques by integrating them with the HPCG benchmark and two real-life applications. Evaluation conducted on four architectures, including three ARMv8 and one x86, shows that our techniques greatly surpass the performance of engineer- and vendor-tuned implementations across various workloads and platforms.
Metadata
Item Type: | Proceedings Paper |
---|---|
Authors/Creators: |
|
Copyright, Publisher and Additional Information: | This item is protected by copyright. This is an author produced version of a conference paper accepted for publication in Proceedings of the ACM International Conference on Supercomputing, made available under the terms of the Creative Commons Attribution License (CC-BY), which permits unrestricted use, distribution and reproduction in any medium, provided the original work is properly cited. |
Keywords: | Multigrid, symmetric Gauss-Seidel, Asynchronous parallelization |
Dates: |
|
Institution: | The University of Leeds |
Academic Units: | The University of Leeds > Faculty of Engineering & Physical Sciences (Leeds) > School of Computing (Leeds) |
Depositing User: | Symplectic Publications |
Date Deposited: | 05 May 2023 13:02 |
Last Modified: | 16 May 2024 12:54 |
Published Version: | https://dl.acm.org/doi/abs/10.1145/3577193.3593726 |
Status: | Published |
Publisher: | ACM |
Series Name: | ICS '23: Proceedings of the 37th International Conference on Supercomputing |
Identification Number: | 10.1145/3577193.3593726 |
Related URLs: | |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:198955 |