Spectral partitioning: the more eigenvectors, the better
DAC '95 Proceedings of the 32nd annual ACM/IEEE Design Automation Conference
A gradient method on the initial partition of Fiduccia-Mattheyses algorithm
ICCAD '95 Proceedings of the 1995 IEEE/ACM international conference on Computer-aided design
VLSI circuit partitioning by cluster-removal using iterative improvement techniques
Proceedings of the 1996 IEEE/ACM international conference on Computer-aided design
Multilevel hypergraph partitioning: application in VLSI domain
DAC '97 Proceedings of the 34th annual Design Automation Conference
Multilevel circuit partitioning
DAC '97 Proceedings of the 34th annual Design Automation Conference
Large scale circuit partitioning with loose/stable net removal and signal flow based clustering
ICCAD '97 Proceedings of the 1997 IEEE/ACM international conference on Computer-aided design
Computers and Intractability: A Guide to the Theory of NP-Completeness
Computers and Intractability: A Guide to the Theory of NP-Completeness
A linear-time heuristic for improving network partitions
DAC '82 Proceedings of the 19th Design Automation Conference
An Improved Min-Cut Algonthm for Partitioning VLSI Networks
IEEE Transactions on Computers
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In this paper, a new multi-level bipartitioningalgorithm MLP, which integrates a clustering techniqueand an iterative improvement based partitioning process,is proposed to enhance the stability and the quality ofpartitioning results. The proposed clustering algorithm isused to reduce the partitioning complexity and improvedthe performance of partitioning. To generate a high-qualitypartitioning solution, a module migration basedpartitioning algorithm MMP is also proposed as thebased partitioner for the MLP algorithm. The MMPalgorithm implicitly promotes the move of clusters duringthe module migration processes by paying more attentionto the neighbors of moved modules, relaxing the sizeconstraints temporarily during the migration process, andcontrolling the module migration direction.Experimental results obtained show that the MLPalgorithm generates high-quality partitioning results. TheMLP algorithm outperforms MELO [2] and CDIPLA3 [6] by23% and 10%, respectively and is competitive with hMetis[9] and MLc [1] which have generated better results thanmany recent state-of-the-art partitioning algorithms.