NDLI: Simple eigenvector-based circuit clustering can be effective [VLSI CAD]

Content Provider	IEEE Xplore Digital Library
Author	Alpert, C.J. Kahng, A.B.
Copyright Year	1996
Description	Author affiliation: Dept. of Comput. Sci., California Univ., Los Angeles, CA, USA (Alpert, C.J.)
Abstract	Clustering has proven effective in improving the quality of VLSI netlist partitioning and placement algorithms. A wide variety of clustering schemes have been proposed, including random walks, iterative matching, and fairly complicated spectral techniques. We use eigenvectors to compute a clustering, but do so in the simplest, most obvious manner. Our algorithm first computes a d-digit code for each module v/sub i/ according to the signs of the i/sup th/ entries in a set of d eigenvectors. Then, modules with the same code are assigned to the same cluster. Despite its simplicity, this new clustering algorithm is strongly motivated by theoretical results for both spectral bipartitioning and multi-dimensional vector partitioning. The algorithm also has linear time complexity (not including the eigenvector computation) and is at least as effective as previous clustering algorithms in terms of two-phase Fiduccia-Mattheyses bipartitioning.
Starting Page	683
Ending Page	686
File Size	468973
Page Count	4
File Format	PDF
ISBN	0780330730
DOI	10.1109/ISCAS.1996.542116
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	1996-05-15
Publisher Place	USA
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Circuits Clustering algorithms Partitioning algorithms Very large scale integration Iterative algorithms Computer science Vectors Runtime Sun Packaging
Content Type	Text
Resource Type	Article

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4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
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