Multiple-Way Network Partitioning
IEEE Transactions on Computers
The Min-cut shuffle: toward a solution for the global effect problem of Min-cut placement
DAC '88 Proceedings of the 25th ACM/IEEE Design Automation Conference
Computers and Intractability: A Guide to the Theory of NP-Completeness
Computers and Intractability: A Guide to the Theory of NP-Completeness
The Design and Analysis of Computer Algorithms
The Design and Analysis of Computer Algorithms
A linear-time heuristic for improving network partitions
DAC '82 Proceedings of the 19th Design Automation Conference
Min-Cut Partitioning on Underlying Tree and Graph Structures
IEEE Transactions on Computers
Network partitioning into tree hierarchies
DAC '96 Proceedings of the 33rd annual Design Automation Conference
A network flow approach for hierarchical tree partitioning
DAC '97 Proceedings of the 34th annual Design Automation Conference
Futures for partitioning in physical design (tutorial)
ISPD '98 Proceedings of the 1998 international symposium on Physical design
Fast Approximation Algorithms on Maxcut, k-Coloring, and k-Color Ordering for VLSI Applications
IEEE Transactions on Computers
Geometrical k-cut problem and an optimal solution for hypercubes
MATH'07 Proceedings of the 12th WSEAS International Conference on Applied Mathematics
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A generalization of the min-cut partitioning problem, called min-cost tree partitioning, is introduced. In the generalized problem. the nodes of a hypergraph G are to be mapped onto the vertices of a tree structure T, and the cost function to be minimized is the cost of routing the hyperedges of G on the edges of T. The standard min-cut problem is the simple case in which the tree T is a single edge connecting two vertices. Several VLSI design applications for this problem are discussed. An iterative improvement heuristic for this problem in which nodes of the hypergraph are moved between the vertices of the tree is described. The running time of a single pass of the heuristic for the unweighted version of the problem is Q(P*D*t/sup 3/), where P is the total number of pins in the hypergraph G, D is the maximum number of nodes in a hyperedge of G, and t is the number of vertices in the tree T. Several test results are discussed.