Serial and parallel kernelization of Multiple Hitting Set parameterized by the Dilworth number, implemented on the GPU Full article
Journal |
Journal of Computer and System Sciences
ISSN: 1090-2724 |
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Output data | Year: 2024, Volume: 139, Article number : 103479, Pages count : 18 DOI: 10.1016/j.jcss.2023.103479 | ||||||||||
Tags | NP-hard problem, Data reduction, Problem kernelization, Parallel algorithm, Computational experiment, GPU, Parameterized complexity | ||||||||||
Authors |
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Affiliations |
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Funding (2)
1 | Mathematical Center in Akademgorodok | 075-15-2019-1675 |
2 | Russian Foundation for Basic Research | 18-501-12031 NNIO_a |
Abstract:
The NP-hard Multiple Hitting Set problem is the problem of finding a minimum-cardinality set intersecting each of the sets in a given input collection a given number of times. Generalizing a well-known data reduction algorithm due to Weihe, we show a problem kernel for Multiple Hitting Set parameterized by the Dilworth number, a graph parameter introduced by Foldes and Hammer in 1978 yet seemingly so far unexplored in the context of parameterized complexity theory. Using matrix multiplication, we speed up the algorithm to quadratic sequential time and logarithmic parallel time. We experimentally evaluate our algorithms. By implementing our algorithm on GPUs, we show the feasibility of realizing kernelization algorithms on SIMD (Single Instruction, Multiple Data) architectures.
Cite:
van Bevern R.
, Kirilin A.M.
, Skachkov D.A.
, Smirnov P.V.
, Tsidulko O.Y.
Serial and parallel kernelization of Multiple Hitting Set parameterized by the Dilworth number, implemented on the GPU
Journal of Computer and System Sciences. 2024. V.139. 103479 :1-18. DOI: 10.1016/j.jcss.2023.103479 WOS Scopus РИНЦ OpenAlex
Serial and parallel kernelization of Multiple Hitting Set parameterized by the Dilworth number, implemented on the GPU
Journal of Computer and System Sciences. 2024. V.139. 103479 :1-18. DOI: 10.1016/j.jcss.2023.103479 WOS Scopus РИНЦ OpenAlex
Dates:
Submitted: | Sep 17, 2021 |
Accepted: | Aug 23, 2023 |
Published online: | Sep 12, 2023 |
Published print: | Feb 15, 2024 |
Identifiers:
Web of science: | WOS:001086672700001 |
Scopus: | 2-s2.0-85172014632 |
Elibrary: | 64856247 |
OpenAlex: | W3199867152 |
Citing:
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