Academic Journal
MallobSat: Scalable SAT Solving by Clause Sharing.
| Τίτλος: | MallobSat: Scalable SAT Solving by Clause Sharing. |
|---|---|
| Συγγραφείς: | Schreiber, Dominik, Sanders, Peter |
| Πηγή: | Journal of Artificial Intelligence Research; 2024, Vol. 80, p1437-1495, 59p |
| Θεματικοί όροι: | Scalability, Parallel processing, Iterative methods (Mathematics), Distributed computing, Electronic data processing |
| Περίληψη: | SAT solving in large distributed environments has previously led to some famous results and to impressive speedups for selected inputs. However, in terms of general-purpose SAT solving, prior approaches still cannot make efficient use of a large number of processors. We aim to address this issue with a complete and systematic overhaul of the distributed solver HordeSat with a focus on its algorithmic building blocks. In particular, we present a communication-efficient approach to clause sharing, careful buffering and filtering of produced clauses, and effective orchestration of state-of-the-art solver backends. In extensive evaluations, our approach named MallobSat significantly outperforms an updated HordeSat, doubling its mean speedup. Our clause sharing results in effective parallelization even if all threads execute identical solver programs that only differ based on which clauses they import at which times. We thus argue that MallobSat is not a portfolio solver with the added bonus of clause sharing but rather a clause-sharing solver where adding some explicit diversification is useful but not essential. We also discuss the last four iterations of the International SAT Competition (2020–2023), where our system ranked very favorably, and identify several previously unsolved competition problems that MallobSat solved successfully. Last but not least, our approach is malleable, i.e., supports running on a fluctuating set of resources, which allows us to combine parallel job processing and parallel SAT solving in a flexible manner for best resource efficiency. [ABSTRACT FROM AUTHOR] |
| Copyright of Journal of Artificial Intelligence Research is the property of AI Access Foundation and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.) | |
| Βάση Δεδομένων: | Complementary Index |
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| Items | – Name: Title Label: Title Group: Ti Data: MallobSat: Scalable SAT Solving by Clause Sharing. – Name: Author Label: Authors Group: Au Data: <searchLink fieldCode="AR" term="%22Schreiber%2C+Dominik%22">Schreiber, Dominik</searchLink><br /><searchLink fieldCode="AR" term="%22Sanders%2C+Peter%22">Sanders, Peter</searchLink> – Name: TitleSource Label: Source Group: Src Data: Journal of Artificial Intelligence Research; 2024, Vol. 80, p1437-1495, 59p – Name: Subject Label: Subject Terms Group: Su Data: <searchLink fieldCode="DE" term="%22Scalability%22">Scalability</searchLink><br /><searchLink fieldCode="DE" term="%22Parallel+processing%22">Parallel processing</searchLink><br /><searchLink fieldCode="DE" term="%22Iterative+methods+%28Mathematics%29%22">Iterative methods (Mathematics)</searchLink><br /><searchLink fieldCode="DE" term="%22Distributed+computing%22">Distributed computing</searchLink><br /><searchLink fieldCode="DE" term="%22Electronic+data+processing%22">Electronic data processing</searchLink> – Name: Abstract Label: Abstract Group: Ab Data: SAT solving in large distributed environments has previously led to some famous results and to impressive speedups for selected inputs. However, in terms of general-purpose SAT solving, prior approaches still cannot make efficient use of a large number of processors. We aim to address this issue with a complete and systematic overhaul of the distributed solver HordeSat with a focus on its algorithmic building blocks. In particular, we present a communication-efficient approach to clause sharing, careful buffering and filtering of produced clauses, and effective orchestration of state-of-the-art solver backends. In extensive evaluations, our approach named MallobSat significantly outperforms an updated HordeSat, doubling its mean speedup. Our clause sharing results in effective parallelization even if all threads execute identical solver programs that only differ based on which clauses they import at which times. We thus argue that MallobSat is not a portfolio solver with the added bonus of clause sharing but rather a clause-sharing solver where adding some explicit diversification is useful but not essential. We also discuss the last four iterations of the International SAT Competition (2020–2023), where our system ranked very favorably, and identify several previously unsolved competition problems that MallobSat solved successfully. Last but not least, our approach is malleable, i.e., supports running on a fluctuating set of resources, which allows us to combine parallel job processing and parallel SAT solving in a flexible manner for best resource efficiency. [ABSTRACT FROM AUTHOR] – Name: Abstract Label: Group: Ab Data: <i>Copyright of Journal of Artificial Intelligence Research is the property of AI Access Foundation and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.) |
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| RecordInfo | BibRecord: BibEntity: Identifiers: – Type: doi Value: 10.1613/jair.1.15827 Languages: – Code: eng Text: English PhysicalDescription: Pagination: PageCount: 59 StartPage: 1437 Subjects: – SubjectFull: Scalability Type: general – SubjectFull: Parallel processing Type: general – SubjectFull: Iterative methods (Mathematics) Type: general – SubjectFull: Distributed computing Type: general – SubjectFull: Electronic data processing Type: general Titles: – TitleFull: MallobSat: Scalable SAT Solving by Clause Sharing. Type: main BibRelationships: HasContributorRelationships: – PersonEntity: Name: NameFull: Schreiber, Dominik – PersonEntity: Name: NameFull: Sanders, Peter IsPartOfRelationships: – BibEntity: Dates: – D: 01 M: 05 Text: 2024 Type: published Y: 2024 Identifiers: – Type: issn-print Value: 10769757 Numbering: – Type: volume Value: 80 Titles: – TitleFull: Journal of Artificial Intelligence Research Type: main |
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