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Multilevel hypergraph partitioning: application in VLSI domain

Published: 13 June 1997 Publication History

Abstract

In this paper, we present a new hypergraph partitioning algorithmthat is based on the multilevel paradigm. In the multilevel paradigm,a sequence of successively coarser hypergraphs is constructed. Abisection of the smallest hypergraph is computed and it is used toobtain a bisection of the original hypergraph by successively projectingand refining the bisection to the next level finer hypergraph.We evaluate the performance both in terms of the size of the hyper-edgecut on the bisection as well as run time on a number of VLSIcircuits. Our experiments show that our multilevel hypergraph partitioningalgorithm produces high quality partitioning in relativelysmall amount of time. The quality of the partitionings produced byour scheme are on the average 4% to 23% better than those producedby other state-of-the-art schemes. Furthermore, our partitioning algorithmissignificantly faster, often requiring 4 to 15 times less timethan that required by the other schemes. Our multilevel hypergraphpartitioning algorithm scales very well for large hypergraphs. Hypergraphswith over 100,000 vertices can be bisected in a few minuteson today's workstations. Also, on the large hypergraphs, ourscheme outperforms other schemes (in hyperedge cut) quite consistentlywith larger margins (9% to 30%).

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cover image ACM Conferences
DAC '97: Proceedings of the 34th annual Design Automation Conference
June 1997
788 pages
ISBN:0897919203
DOI:10.1145/266021
Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Published: 13 June 1997

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DAC97: The 34th Design Automation Conference
June 9 - 13, 1997
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DAC '97 Paper Acceptance Rate 139 of 400 submissions, 35%;
Overall Acceptance Rate 1,770 of 5,499 submissions, 32%

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  • (2024)Community detection in hypergraphs via mutual information maximizationScientific Reports10.1038/s41598-024-55934-514:1Online publication date: 23-Mar-2024
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