Conference Paper/Proceeding/Abstract 578 views 35 downloads
Scalable N-Queens Solving on GPGPUs via Interwarp Collaborations
Filippos Pantekis,
Phillip James,
Oliver Kullmann 
2022 Tenth International Symposium on Computing and Networking (CANDAR)
Swansea University Authors:
Filippos Pantekis, Phillip James, Oliver Kullmann
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DOI (Published version): 10.1109/candar57322.2022.00029
Abstract
In this paper we present how recent hardware revisions and newly introduced approaches to thread collaboration in NVIDIA GPUs and the CUDA toolkit can be used to design an extensible, scalable GPU-based solver for the N-Queens problem. We discuss various design choices ranging from memory structure,...
| Published in: | 2022 Tenth International Symposium on Computing and Networking (CANDAR) |
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| ISBN: | 978-1-6654-7531-0 978-1-6654-7530-3 |
| ISSN: | 2379-1888 2379-1896 |
| Published: |
IEEE
2022
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| Online Access: |
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| URI: | https://cronfa.swan.ac.uk/Record/cronfa61915 |
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| Abstract: |
In this paper we present how recent hardware revisions and newly introduced approaches to thread collaboration in NVIDIA GPUs and the CUDA toolkit can be used to design an extensible, scalable GPU-based solver for the N-Queens problem. We discuss various design choices ranging from memory structure, to low-level optimisations on newer GPU hardware that result in strong performance when solving the N-Queens problem using an optimised solving algorithm that can be applied to other similar in nature problems. |
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| College: |
Faculty of Science and Engineering |
| Funders: |
EPSRC, EP/S015523/1 |