DiVinE-CUDA - A Tool for GPU Accelerated LTL Model Checking

TL;DR

This paper introduces DiVinE-CUDA, a GPU-accelerated tool for LTL model checking that leverages CUDA to efficiently detect accepting cycles, significantly improving performance over traditional methods.

Contribution

The paper presents a novel GPU-based implementation of the accepting cycle detection algorithm for LTL model checking, optimized for NVIDIA CUDA architecture.

Findings

Outperforms non-accelerated algorithms in cycle detection speed

Demonstrates effective use of parallel CUDA algorithms for model checking

Discusses current limitations and future improvements

Abstract

In this paper we present a tool that performs CUDA accelerated LTL Model Checking. The tool exploits parallel algorithm MAP adjusted to the NVIDIA CUDA architecture in order to efficiently detect the presence of accepting cycles in a directed graph. Accepting cycle detection is the core algorithmic procedure in automata-based LTL Model Checking. We demonstrate that the tool outperforms non-accelerated version of the algorithm and we discuss where the limits of the tool are and what we intend to do in the future to avoid them.