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GPU-Accelerated Synthesis of Probabilistic Programs

The result's identifiers

  • Result code in IS VaVaI

    <a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216305%3A26230%2F22%3APU144844" target="_blank" >RIV/00216305:26230/22:PU144844 - isvavai.cz</a>

  • Result on the web

  • DOI - Digital Object Identifier

Alternative languages

  • Result language

    angličtina

  • Original language name

    GPU-Accelerated Synthesis of Probabilistic Programs

  • Original language description

    We consider automated synthesis methods for finite-state probabilistic programs satisfying a given temporal specification. Our goal is to accelerate the synthesis process using massively parallel graphical processing units (GPUs). The involved analysis of families of candidate programs is the main computational bottleneck of the process. We thus propose a state-level GPU-parallelisation of the model-checking algorithms for Markov chains and Markov decision processes that leverages the related but distinct topology of the candidate programs. For structurally complex families, we achieve a speedup of the analysis over one order of magnitude. This already leads to a considerable acceleration of the overall synthesis process and paves the way for further improvements.

  • Czech name

  • Czech description

Classification

  • Type

    D - Article in proceedings

  • CEP classification

  • OECD FORD branch

    10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)

Result continuities

  • Project

    <a href="/en/project/GJ20-02328Y" target="_blank" >GJ20-02328Y: CAQtuS: Computer-Aided Quantitative Synthesis</a><br>

  • Continuities

    P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)

Others

  • Publication year

    2022

  • Confidentiality

    S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Data specific for result type

  • Article name in the collection

    International Conference on Computer Aided Systems Theory (EUROCAST'22)

  • ISBN

    978-3-031-25312-6

  • ISSN

  • e-ISSN

  • Number of pages

    11

  • Pages from-to

    256-266

  • Publisher name

    Springer Nature Switzerland AG

  • Place of publication

    Cham

  • Event location

    Las Palmas de Gran Canaria, Canary Islands

  • Event date

    Feb 20, 2022

  • Type of event by nationality

    WRD - Celosvětová akce

  • UT code for WoS article