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A neural network design for circuit partitioning

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Published:01 June 1989Publication History

ABSTRACT

This paper proposes a neural network model for circuit bipartitioning. The massive parallelism of neural nets has been successfully exploited to balance the partitions of a circuit and to reduce the external wiring between the partitions. The experimental results obtained by neural nets are found to be comparable with that achieved by Fiduccia and Mattheyses algorithm.

References

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                cover image ACM Conferences
                DAC '89: Proceedings of the 26th ACM/IEEE Design Automation Conference
                June 1989
                839 pages
                ISBN:0897913108
                DOI:10.1145/74382

                Copyright © 1989 ACM

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                Publication History

                • Published: 1 June 1989

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                DAC '89 Paper Acceptance Rate156of465submissions,34%Overall Acceptance Rate1,770of5,499submissions,32%

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