Accelerating SpMV Multiplication in Probabilistic Model Checkers Using GPUs

Khan, Muhammad Hannan; Hassan, Osman; Khan, Shahid

doi:10.1007/978-3-030-85315-0_6

Cited by 5 publications

(1 citation statement)

References 25 publications

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“…Major advances in computation increasingly need to be obtained via parallel software as Moore's Law comes to an end (Leiserson et al, 2020). In the last decade, GPUs have been successfully applied to accelerate various computations relevant for model checking, such as probability computations for probabilistic model checking (Bošnački et al, 2011;Wijs and Bošnački, 2012;Khan et al, 2021), counter-example construction (Wu et al, 2014), state space decomposition (Wijs et al, 2016a), parameter synthesis for stochastic systems ( Češka et al, 2016), and SAT solving (Youness et al, 2015(Youness et al, , 2020Osama et al, 2018Osama et al, , 2023Osama andWijs, 2019a,b, 2021;Prevot et al, 2021;Osama, 2022). VOXLOGICA-GPU applies model checking to analyse (medical) images (Bussi et al, 2021).…”

Section: Introductionmentioning

confidence: 99%

The fast and the capacious: memory-efficient multi-GPU accelerated explicit state space exploration with GPUexplore 3.0

Wijs,

Osama

2024

Front. High Perform. Comput.

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The GPU acceleration of explicit state space exploration, for explicit-state model checking, has been the subject of previous research, but to date, the tools have been limited in their applicability and in their practical use. Considering this research, to our knowledge, we are the first to use a novel tree database for GPUs. This novel tree database allows high-performant, memory-efficient storage of states in the form of binary trees. Besides the tree compression this enables, we also propose two new hashing schemes, compact-cuckoo and compact multiple-functions. These schemes enable the use of Cleary compression to compactly store tree roots. Besides an in-depth discussion of the tree database algorithms, the input language and workflow of our tool, called GPUexplore 3.0, are presented. Finally, we explain how the algorithms can be extended to exploit multiple GPUs that reside on the same machine. Experiments show single-GPU processing speeds of up to 144 million states per second compared to 20 million states achieved by 32-core LTSmin. In the multi-GPU setting, workload and storage distributions are optimal, and, frequently, performance is even positively impacted when the number of GPUs is increased. Overall, a logarithmic acceleration up to 1.9× was achieved with four GPUs, compared to what was achieved with one and two GPUs. We believe that a linear speedup can be easily accomplished with faster P2P communications between the GPUs.

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Section: Introductionmentioning

confidence: 99%

The fast and the capacious: memory-efficient multi-GPU accelerated explicit state space exploration with GPUexplore 3.0

Wijs,

Osama

2024

Front. High Perform. Comput.

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A GPU Tree Database for Many-Core Explicit State Space Exploration

Wijs

Osama

2023

Lecture Notes in Computer Science

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Various techniques have been proposed to accelerate explicit-state model checking with GPUs, but none address the compact storage of states, or if they do, at the cost of losing completeness of the checking procedure. We investigate how to implement a tree database to store states as binary trees in GPU memory. We present fine-grained parallel algorithms to find and store trees, experiment with a number of GPU-specific configurations, and propose a novel hashing technique, called Cleary-Cuckoo hashing, which enables the use of Cleary compression on GPUs. We are the first to assess the effectiveness of using a tree database, and Cleary compression, on GPUs. Experiments show processing speeds of up to 131 million states per second.

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GPUexplore 3.0: GPU Accelerated State Space Exploration for Concurrent Systems with Data

Wijs

Osama

2023

Lecture Notes in Computer Science

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Accelerating SpMV Multiplication in Probabilistic Model Checkers Using GPUs

Cited by 5 publications

References 25 publications

The fast and the capacious: memory-efficient multi-GPU accelerated explicit state space exploration with GPUexplore 3.0

The fast and the capacious: memory-efficient multi-GPU accelerated explicit state space exploration with GPUexplore 3.0

A GPU Tree Database for Many-Core Explicit State Space Exploration

GPUexplore 3.0: GPU Accelerated State Space Exploration for Concurrent Systems with Data

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