Automatic construction of parallel portfolios via algorithm configuration

Since 2004, increases in computational power described by Moore's law have substantially been realized in the form of additional cores rather than through faster clock speeds. To make effective use of modern hardware when solving hard computational problems, it is therefore necessary to employ...

Celý popis

Uloženo v:
Podrobná bibliografie
Vydáno v:Artificial intelligence Ročník 244; s. 272 - 290
Hlavní autoři: Lindauer, Marius, Hoos, Holger, Leyton-Brown, Kevin, Schaub, Torsten
Médium: Journal Article
Jazyk:angličtina
Vydáno: Amsterdam Elsevier B.V 01.03.2017
Elsevier Science Ltd
Témata:
Algorithm configuration
Algorithm portfolios
Automated parallelization
Combinatorial analysis
Computation
Configuration management
Moore's law
Parallel SAT solving
Programming by optimization
Solvers
Algorithm portfolios
Parallel SAT solving
Programming by optimization
Automated parallelization
Algorithm configuration
ISSN:0004-3702, 1872-7921
On-line přístup:Získat plný text
Tagy: Přidat tag
Žádné tagy, Buďte první, kdo vytvoří štítek k tomuto záznamu!
Popis
Shrnutí:Since 2004, increases in computational power described by Moore's law have substantially been realized in the form of additional cores rather than through faster clock speeds. To make effective use of modern hardware when solving hard computational problems, it is therefore necessary to employ parallel solution strategies. In this work, we demonstrate how effective parallel solvers for propositional satisfiability (SAT), one of the most widely studied NP-complete problems, can be produced automatically from any existing sequential, highly parametric SAT solver. Our Automatic Construction of Parallel Portfolios (ACPP) approach uses an automatic algorithm configuration procedure to identify a set of configurations that perform well when executed in parallel. Applied to two prominent SAT solvers, Lingeling and clasp, our ACPP procedure identified 8-core solvers that significantly outperformed their sequential counterparts on a diverse set of instances from the application and hard combinatorial category of the 2012 SAT Challenge. We further extended our ACPP approach to produce parallel portfolio solvers consisting of several different solvers by combining their configuration spaces. Applied to the component solvers of the 2012 SAT Challenge gold medal winning SAT Solver pfolioUZK, our ACPP procedures produced a significantly better-performing parallel SAT solver.
Bibliografie:ObjectType-Article-1
SourceType-Scholarly Journals-1
ObjectType-Feature-2
content type line 14
ISSN:0004-3702
1872-7921
DOI:10.1016/j.artint.2016.05.004