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Multilevel Circuit Partitioning (1998)
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| Venue: | IN PROC. OF THE 34TH ACM/IEEE DESIGN AUTOMATION CONFERENCE |
| Citations: | 89 - 8 self |
BibTeX
@INPROCEEDINGS{Alpert98multilevelcircuit,
author = {Charles J. Alpert and Jen-hsin Huang and Andrew B. Kahng},
title = {Multilevel Circuit Partitioning},
booktitle = {IN PROC. OF THE 34TH ACM/IEEE DESIGN AUTOMATION CONFERENCE},
year = {1998},
pages = {530--533},
publisher = {}
}
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Abstract
Many previous works in partitioning have used some underlying clustering algorithm to improve performance. As problem sizes reach new levels of complexity, a single application of a clustering algorithm is insufficient to produce excellent solutions. Recent work has illustrated the promise of multilevel approaches. A multilevel partitioning algorithm recursively clusters the instance until its size is smaller than a given threshold, then unclusters the instance while applying a partitioning refinement algorithm. In this paper, we propose a new multilevel partitioning algorithm that exploits some of the latest innovations of classical iterative partitioning approaches. Our method also uses a new technique to control the number of levels in our matching-based clustering algorithm. Experimental results show that our heuristic outperforms numerous existing bipartitioning heuristics with improvements ranging from 6.9 to 27.9 % for 100 runs and 3.0 to 20.6 % for just ten runs (while also using less CPU time). Further, our algorithm generates solutions better than the best known mincut bipartitionings for seven of the ACM/SIGDA benchmark circuits, including golem3 (which has over 100 000 cells). We also present quadrisection results which compare favorably to the partitionings obtained by the GORDIAN cell placement tool. Our work in multilevel quadrisection has been used as the basis for an effective cell placement package.
Keyphrases
multilevel circuit partitioning algorithm generates solution multilevel quadrisection gordian cell placement tool matching-based clustering algorithm known mincut bipartitionings partitioning refinement algorithm acm sigda benchmark circuit excellent solution heuristic outperforms new level many previous work clustering algorithm recent work present quadrisection result new technique cpu time new multilevel effective cell placement package multilevel approach single application classical iterative partitioning approach experimental result
