Accelerating domain propagation: An efficient GPU-parallel algorithm over sparse matrices

•Currently, domain propagation in state-of-the-art MIP solvers is single thread only.•The paper presents a novel, efficient GPU algorithm to perform domain propagation.•Challenges are dynamic algorithmic behavior, dependency structures, sparsity patterns.•The algorithm is capable of running entirely...

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Vydáno v:Parallel computing Ročník 109; s. 102874
Hlavní autoři: Sofranac, Boro, Gleixner, Ambros, Pokutta, Sebastian
Médium: Journal Article
Jazyk:angličtina
Vydáno: Elsevier B.V 01.03.2022
Témata:
Bound tightening
Domain propagation
GPU
MIP
Mixed integer linear programming
Parallel algorithms
Mixed integer linear programming
MIP
GPU
Parallel algorithms
Domain propagation
Bound tightening
ISSN:0167-8191, 1872-7336
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Popis
Shrnutí:•Currently, domain propagation in state-of-the-art MIP solvers is single thread only.•The paper presents a novel, efficient GPU algorithm to perform domain propagation.•Challenges are dynamic algorithmic behavior, dependency structures, sparsity patterns.•The algorithm is capable of running entirely on the GPU with no CPU involvement.•We achieve speed-ups of around 10x to 20x, up to 180x on favorably-large instances.
ISSN:0167-8191
1872-7336
DOI:10.1016/j.parco.2021.102874