Efficient Solver Scheduling and Selection for Satisfiability Modulo Theories (SMT) Problems.
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F61988987%3A17610%2F24%3AA2502N61" target="_blank" >RIV/61988987:17610/24:A2502N61 - isvavai.cz</a>
Result on the web
<a href="https://www.scitepress.org/Papers/2024/123936/123936.pdf" target="_blank" >https://www.scitepress.org/Papers/2024/123936/123936.pdf</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.5220/0012393600003654" target="_blank" >10.5220/0012393600003654</a>
Alternative languages
Result language
angličtina
Original language name
Efficient Solver Scheduling and Selection for Satisfiability Modulo Theories (SMT) Problems.
Original language description
This paper introduces innovative concepts for improving the process of selecting solvers from a portfolio to tackle Satisfiability Modulo Theories (SMT) problems. We propose a novel solver scheduling approach that significantly enhances solving performance, measured by the PAR-2 metric, on selected benchmarks. Our investigation reveals that, in certain cases, scheduling based on a crude statistical analysis of training data can perform just as well, if not better, than a machine learning predictor. Additionally, we present a dynamic scheduling approach that adapts in real-time, taking into account the changing likelihood of solver success. These findings shed light on the nuanced nature of solver selection and scheduling, providing insights into situations where data-driven methods may not offer clear advantages.
Czech name
—
Czech description
—
Classification
Type
D - Article in proceedings
CEP classification
—
OECD FORD branch
10102 - Applied mathematics
Result continuities
Project
—
Continuities
S - Specificky vyzkum na vysokych skolach
Others
Publication year
2024
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Article name in the collection
Proceedings of the 13th International Conference on Pattern Recognition Applications and Methods (ICPRAM 2024)
ISBN
978-989-758-684-2
ISSN
2184-4313
e-ISSN
—
Number of pages
10
Pages from-to
360-369
Publisher name
SCITEPRESS
Place of publication
Řím
Event location
Itálie
Event date
Feb 24, 2024
Type of event by nationality
WRD - Celosvětová akce
UT code for WoS article
—