Dagster: Parallel Structured Search with Case Studies

Mark Alexander Burgess*, Charles Gretton, Josh Milthorpe, Luke Croak, Thomas Willingham, Alwen Tiu

*Corresponding author for this work

    Research output: Chapter in Book/Report/Conference proceedingConference Paperpeer-review

    3 Citations (Scopus)

    Abstract

    We describe Dagster, a system that implements a new approach to scheduling interdependent (Boolean) SAT search activities in high-performance computing (HPC) environments. This system allows practitioners to solve challenging problems by efficiently distributing search effort across computing cores in a customizable way. Our solver 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 search 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 show the performance of Dagster in combinatorial case study examples, particularly the model counting of Costas arrays, and in finding solutions to large Pentomino tiling problems. We also use Dagster to exhibit a novel workflow for Bounded Model Checking of network protocols where we perform independent searches at different problem fidelities, in parallel. Low fidelity solutions trigger further independent searches for refined solutions in higher fidelity models.

    Original languageEnglish
    Title of host publicationPRICAI 2022
    Subtitle of host publicationTrends in Artificial Intelligence - 19th Pacific Rim International Conference on Artificial Intelligence, PRICAI 2022, Proceedings
    EditorsSankalp Khanna, Jian Cao, Quan Bai, Guandong Xu
    Place of PublicationCham, Switzerland
    PublisherSpringer Science+Business Media B.V.
    Pages75-89
    Number of pages15
    Edition1
    ISBN (Print)9783031208614
    DOIs
    Publication statusPublished - 2022
    Event19th Pacific Rim International Conference on Artificial Intelligence, PRICAI 2022 - Shangai, China
    Duration: 10 Nov 202213 Nov 2022

    Publication series

    NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
    Volume13629 LNCS
    ISSN (Print)0302-9743
    ISSN (Electronic)1611-3349

    Conference

    Conference19th Pacific Rim International Conference on Artificial Intelligence, PRICAI 2022
    Country/TerritoryChina
    CityShangai
    Period10/11/2213/11/22

    Fingerprint

    Dive into the research topics of 'Dagster: Parallel Structured Search with Case Studies'. Together they form a unique fingerprint.

    Cite this