Reichl, F. X., Slivovsky, F., & Szeider, S. (2024). eSLIM: Circuit Minimization with SAT Based Local Improvement. In 27th International Conference on Theory and Applications of Satisfiability Testing (pp. 23:1-23:14). Schloss Dagstuhl. https://doi.org/10.4230/LIPIcs.SAT.2024.23
E192-01 - Forschungsbereich Algorithms and Complexity E056-13 - Fachbereich LogiCS E056-23 - Fachbereich Innovative Combinations and Applications of AI and ML (iCAIML)
-
Published in:
27th International Conference on Theory and Applications of Satisfiability Testing (SAT 2024)
-
ISBN:
978-3-95977-334-8
-
Volume:
305
-
Date (published):
2024
-
Event name:
27th International Conference on Theory and Applications of Satisfiability Testing (SAT 2024)
en
Event date:
21-Aug-2024 - 24-Aug-2024
-
Event place:
Pune, India
-
Number of Pages:
14
-
Publisher:
Schloss Dagstuhl, Leibniz-Zentrum für Informatik
-
Peer reviewed:
Yes
-
Keywords:
Circuit Minimization; Exact Synthesis; QBF; SLIM
en
Abstract:
eSLIM is a tool for circuit minimization that utilizes Exact Synthesis and the SAT-based local improvement method (SLIM) to locally improve circuits. eSLIM improves upon the earlier prototype CIOPS that uses Quantified Boolean Formulas (QBF) to succinctly encode resynthesis of multi-output subcircuits subject to don’t cares. This paper describes two improvements. First, it presents a purely propos...
eSLIM is a tool for circuit minimization that utilizes Exact Synthesis and the SAT-based local improvement method (SLIM) to locally improve circuits. eSLIM improves upon the earlier prototype CIOPS that uses Quantified Boolean Formulas (QBF) to succinctly encode resynthesis of multi-output subcircuits subject to don’t cares. This paper describes two improvements. First, it presents a purely propositional encoding based on a Boolean relation characterizing the input-output behavior of the subcircuit under don’t cares. This allows the use of a SAT solver for resynthesis, substantially reducing running times when applied to functions from the IWLS 2023 competition, where eSLIM placed second. Second, it proposes circuit partitioning techniques in which don’t cares for a subcircuit are captured only with respect to an enclosing window, rather than the entire circuit. Circuit partitioning trades completeness for efficiency, and successfully enables the application of exact synthesis to some of the largest circuits in the EPFL suite, leading to improvements over the current best implementation for several instances.
en
Project title:
Learning to Solve Quantified Boolean Formulas: ICT19--060 (WWTF Wiener Wissenschafts-, Forschu und Technologiefonds)