A Heuristic Procedure for the Partitioning and Mapping of Computer Logic Graphs

Russo, R.L.; Oden, P. H.; Wolff, P. K.

doi:10.1109/t-c.1971.223157

Cited by 48 publications

(11 citation statements)

References 7 publications

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“…into K zones is to enumerate all (N) possible partitions. In practice this is not possible except for small values of N. For example, there are in with Table III excess of 101260 different ways in which Iooo objects can be combined to form twenty groups (Russo, Oden and Wolff, 1971). Cliff and Haggett (1970) and Keane (1975) provide formulae for the region-building problem.…”

Section: Solving the Automatic-zoning Problemmentioning

confidence: 99%

A Geographical Solution to Scale and Aggregation Problems in Region-Building, Partitioning and Spatial Modelling

Openshaw¹

1977

Transactions of the Institute of British Geographers

349

185

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Section: Solving the Automatic-zoning Problemmentioning

confidence: 99%

A Geographical Solution to Scale and Aggregation Problems in Region-Building, Partitioning and Spatial Modelling

Openshaw¹

1977

Transactions of the Institute of British Geographers

349

185

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“…Partitioning of graphs occurs in computer logic partitioning [1,2], paging of computer programs [3,4], and may also find application in the area of classification [5]. Graph partitioning is the problem of dividing the vertices of a graph into a given number of disjoint subsets such that the number of nodes in each subset is less than a given number, while the number of cut edges, i.e., edges connecting nodes in different subsets, is a minimum.…”

Section: Introductionmentioning

confidence: 99%

Lower Bounds for the Partitioning of Graphs

1973

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“…In VLSI design, the first in-depth discussion about logic replication is given by Russo et al (1971), where they propose a heuristic approach. Later, Kring and Newton (1991) and Murgai et al (1991) extend the Fidduccia and Mattheyses (FM) iterative improvement algorithm to allow vertices to be duplicated during partitioning.…”

Section: Introductionmentioning

confidence: 99%

Constrained Min-Cut Replication for K-Way Hypergraph Partitioning

Yazici

Aykanat

2014

INFORMS Journal on Computing

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R eplication is a widely-used technique in information retrieval and database systems for providing fault tolerance and reducing parallelization and processing costs. Combinatorial models based on hypergraph partitioning are proposed for various problems arising in information retrieval and database systems. We consider the possibility of using vertex replication to improve the quality of hypergraph partitioning. In this study, we focus on the constrained min-cut replication (CMCR) problem, where we are initially given a maximum replication capacity and a K-way hypergraph partition with an initial imbalance ratio. The objective in the CMCR problem is finding the optimal vertex replication sets for each part of the given partition such that the initial cut size of the partition is minimized, where the initial imbalance is either preserved or reduced under the given replication capacity constraint. In this study, we present a complexity analysis of the CMCR problem and propose a model based on a unique blend of coarsening and integer linear programming (ILP) schemes. This coarsening algorithm is derived from a novel utilization of the Dulmage-Mendelsohn decomposition. Experiments show that the ILP formulation coupled with the Dulmage-Mendelsohn decomposition-based coarsening provides high quality results in practical execution times for reducing the cut size of a given K-way hypergraph partition.

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A Heuristic Procedure for the Partitioning and Mapping of Computer Logic Graphs

Cited by 48 publications

References 7 publications

A Geographical Solution to Scale and Aggregation Problems in Region-Building, Partitioning and Spatial Modelling

A Geographical Solution to Scale and Aggregation Problems in Region-Building, Partitioning and Spatial Modelling

Lower Bounds for the Partitioning of Graphs

Constrained Min-Cut Replication for K-Way Hypergraph Partitioning

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