TY - JOUR
A1 - Hoos, Holger
A1 - Kaminski, Roland
A1 - Lindauer, Marius
A1 - Schaub, Torsten
T1 - aspeed: Solver scheduling via answer set programming
JF - Theory and practice of logic programming
N2 - Although Boolean Constraint Technology has made tremendous progress over the last decade, the efficacy of state-of-the-art solvers is known to vary considerably across different types of problem instances, and is known to depend strongly on algorithm parameters. This problem was addressed by means of a simple, yet effective approach using handmade, uniform, and unordered schedules of multiple solvers in ppfolio, which showed very impressive performance in the 2011 Satisfiability Testing (SAT) Competition. Inspired by this, we take advantage of the modeling and solving capacities of Answer Set Programming (ASP) to automatically determine more refined, that is, nonuniform and ordered solver schedules from the existing benchmarking data. We begin by formulating the determination of such schedules as multi-criteria optimization problems and provide corresponding ASP encodings. The resulting encodings are easily customizable for different settings, and the computation of optimum schedules can mostly be done in the blink of an eye, even when dealing with large runtime data sets stemming from many solvers on hundreds to thousands of instances. Also, the fact that our approach can be customized easily enabled us to swiftly adapt it to generate parallel schedules for multi-processor machines.
KW - algorithm schedules
KW - answer set programming
KW - portfolio-based solving
Y1 - 2015
U6 - http://dx.doi.org/10.1017/S1471068414000015
SN - 1471-0684 (print)
SN - 1475-3081 (online)
VL - 15
SP - 117
EP - 142
PB - Cambridge Univ. Press
CY - New York
ER -
TY - GEN
A1 - Hoos, Holger
A1 - Kaminski, Roland
A1 - Lindauer, Marius
A1 - Schaub, Torsten
T1 - aspeed
BT - solver scheduling via answer set programming
T2 - Postprints der Universität Potsdam : Mathematisch-Naturwissenschaftliche Reihe
N2 - Although Boolean Constraint Technology has made tremendous progress over the last decade, the efficacy of state-of-the-art solvers is known to vary considerably across different types of problem instances, and is known to depend strongly on algorithm parameters. This problem was addressed by means of a simple, yet effective approach using handmade, uniform, and unordered schedules of multiple solvers in ppfolio, which showed very impressive performance in the 2011 Satisfiability Testing (SAT) Competition. Inspired by this, we take advantage of the modeling and solving capacities of Answer Set Programming (ASP) to automatically determine more refined, that is, nonuniform and ordered solver schedules from the existing benchmarking data. We begin by formulating the determination of such schedules as multi-criteria optimization problems and provide corresponding ASP encodings. The resulting encodings are easily customizable for different settings, and the computation of optimum schedules can mostly be done in the blink of an eye, even when dealing with large runtime data sets stemming from many solvers on hundreds to thousands of instances. Also, the fact that our approach can be customized easily enabled us to swiftly adapt it to generate parallel schedules for multi-processor machines.
T3 - Postprints der Universität Potsdam : Mathematisch-Naturwissenschaftliche Reihe - 588
KW - algorithm schedules
KW - answer set programming
KW - portfolio-based solving
Y1 - 2019
U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:kobv:517-opus4-414743
SN - 1866-8372
IS - 588
ER -