Arrow Research search
Back to LPAR

LPAR 2018

SMTS: Distributed, Visualized Constraint Solving

Conference Paper Accepted Paper Artificial Intelligence · Logic in Computer Science

Abstract

The inherent complexity of parallel computing makes development, resource monitor- ing, and debugging for parallel constraint-solving-based applications difficult. This paper presents SMTS, a framework for parallelizing sequential constraint solving algorithms and running them in distributed computing environments. The design (i) is based on a gen- eral parallelization technique that supports recursively combining algorithm portfolios and divide-and-conquer with the exchange of learned information, (ii) provides monitoring by visually inspecting the parallel execution steps, and (iii) supports interactive guidance of the algorithm through a web interface. We report positive experiences on instantiating the framework for one SMT solver and one IC3 solver, debugging parallel executions, and visualizing solving, structure, and learned clauses of SMT instances.

Authors

Keywords

No keywords are indexed for this paper.

Context

Venue
International Conference on Logic for Programming, Artificial Intelligence and Reasoning
Archive span
1992-2024
Indexed papers
780
Paper id
993946866145018544
v2026.09.13