The Effect of VSIDS on SAT Solver Performance Technical Report UCSC-SOE-09-21
نویسنده
چکیده
VSIDS, a popular decision heuristic introduced in CHAFF, is compared against several simple heuristics to evaluate its effectiveness on a given set of benchmarks.
منابع مشابه
Improving SAT Solvers via Blocked Clause Decomposition
The decision variable selection policy used by the most competitive CDCL (Conflict-Driven Clause Learning) SAT solvers is either VSIDS (Variable State Independent Decaying Sum) or its variants such as exponential version EVSIDS. The common characteristic of VSIDS and its variants is to make use of statistical information in the solving process, but ignore structure information of the problem. F...
متن کاملUnderstanding VSIDS Branching Heuristics in Conflict-Driven Clause-Learning SAT Solvers
Conflict-Driven Clause-Learning (CDCL) SAT solvers crucially depend on the Variable State Independent Decaying Sum (VSIDS) branching heuristic for their performance. Although VSIDS was proposed nearly fifteen years ago, and many other branching heuristics for SAT solving have since been proposed, VSIDS remains one of the most effective branching heuristics. Despite its widespread use and repeat...
متن کاملEPiC Series in Computing
We present a method we call structure-based preferential bumping, a low-cost way to exploit formula structure in VSIDS-based SAT solvers. We show that the SAT solver Glucose, when modified with preferential bumping of certain easily identified structurally important variables, out-performs unmodified Glucose on the industrial formulas from recent SAT solver competitions.
متن کاملArgoLib v3.5: System Description for SMTComp’07∗
SAT solver. DPLL(X) part of the system is based on our SAT solver called argosat. argo-sat is a rational reconstruction of the MiniSat solver [3]. The main design goal of argo-sat was to improve code readability and flexibility of MiniSat without affecting its performance. This makes experimenting in the field of SAT research easier, and also enables us to formally prove the correctness of the ...
متن کاملPlanning as satisfiability: Heuristics
Reduction to SAT is a very successful approach to solving hard combinatorial problems in Artificial Intelligence and computer science in general. Most commonly, problem instances reduced to SAT are solved with a general-purpose SAT solver. Although there is the obvious possibility of improving the SAT solving process with application-specific heuristics, this has rarely been done successfully. ...
متن کامل