cid 947c250f623e2e7f38510cdd963eebcf732c134f20fdfe74ceb9371d967343fb · original · open access · via openalex
Title: Dagster: Parallel Structured Search Authors: Mark Alexander Burgess; Charles Gretton; Josh Milthorpe; Luke Croak; Thomas Willingham; Alwen Fernanto Tiu Venue: Proceedings of the AAAI Conference on Artificial Intelligence Year: 2023 Canonical: doi:10.1609/aaai.v37i13.27060 URL: https://doi.org/10.1609/aaai.v37i13.27060 Collector: openalex OA: true ABSTRACT We demonstrate Dagster, a system that implements a new approach to scheduling interdependent (Boolean) SAT search activities in high-performance computing (HPC) environments. Our system takes as input a set of disjunctive clauses (i.e., DIMACS CNF) and a labelled directed acyclic graph (DAG) structure describing how the clauses are decomposed into a set of interrelated problems. Component problems are solved using standard systematic backtracking search, which may optionally be coupled to (stochastic dynamic) local search and/or clause-strengthening processes. We demonstrate Dagster using a new Graph Maximal Determinant combinatorial case study. This demonstration paper presents a new case study, and is adjunct to the longer accepted manuscript at the Pacific Rim International Conference on Artificial Intelligence (2022).