Towards End-to-End GPU Acceleration of PCTL Model Checking

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Abstract

So far, existing probabilistic model checkers have been programmed to run on a CPU. While earlier work has accelerated some procedures of model checking with GPUs, such as matrix-vector multiplication for probabilistic model checking, we are the first to construct an end-to-end GPU-accelerated probabilistic model checker, where every step of the model checking process, from constructing a Discrete-Time Markov Chain to the verification of a Probabilistic Computation Tree Logic (PCTL) formula, occurs on the GPU, and where all relevant data is located in GPU memory. In this paper, we discuss the challenges imposed by the GPU architecture and memory constraints and how we overcame them, present intermediate performance results for a supported fragment of PCTL, and discuss the challenges that remain to support full PCTL property checking.

Original languageEnglish
Title of host publicationPrinciples of Verification: Cycling the Probabilistic Landscape
Subtitle of host publicationEssays Dedicated to Joost-Pieter Katoen on the Occasion of His 60th Birthday
EditorsNils Jansen, Sebastian Junges, Benjamin Lucien Kaminski, Chrisoph Matheja, Thomas Noll, Tim Quatmann, Mariëlle Stoelinga, Matthias Volk
PublisherSpringer
Chapter14
Pages314-337
Number of pages24
Volume2
ISBN (Electronic)978-3-031-75775-4
ISBN (Print)978-3-031-75774-7
DOIs
Publication statusPublished - 2025

Publication series

NameLecture Notes in Computer Science
Volume15261 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Bibliographical note

Publisher Copyright:
© The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.

Keywords

  • Discrete-Time Markov Chains
  • GPU
  • PCTL model checking
  • probabilistic model checking
  • Temporal logic

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