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References in periodicals archive ?
* An interference graph partitioning algorithm has been developed for virtual-cells association based on Kernighan-Lin Algorithm (KLA).
This paper provides an approach for automatic assembly code parallelization by a refined METIS-based graph partitioning method.
The graph partitioning process is performed using the algorithm provided in the Metis software library, compare [23].
In graph partitioning, a network is divided into clusters in such a way that the number of edges connecting the clusters is minimum, that is, the edges of a cluster are denser inside than outside (also referred as conductance [10]).
Our algorithm is meant to achieve graph partitioning in order to find the best compromise between power and execution time.
* The University of Florida Sparse Matrix Collection [9], selecting the sparse matrices whose description contains the keywords undirected and graph, as well as the matrices in the collection which are from (or also available in) Walshaw's Graph Partitioning Archive [28].
Kolda, "Graph Partitioning Models for Parallel Computing", Elsevier, Journal Parallel Computing--Special issue on graph partioning and parallel computing", Volume 26 Issue 12, Nov.
The 15 papers consider such topics as abusing a hypergraph partitioner for unweighted graph partitioning, graph partitioning for scalable distributed graph computations, using graph partitioning for efficient network modularity optimization, identifying base clusters and their applications to maximizing modularity, and an ensemble learning strategy for graph clustering.
(3) If the second step without a graph partitioning, go to step second
Students and features could be modelled as a bipartite graph and a simultaneous clustering could be posed as a bipartite graph partitioning problem.
Graph partitioning is a fairly new and promising approach to perceptual grouping or image segmentation.
More Specifically Given a graph G = {V,E}, where V is set of vertices and E is a set of edges between vertices, the goal of the graph partitioning is to divide G into k disjoint sub-graphs [G.sub.i] = {[V.sub.i],[E.sub.i]} in which [V.sub.i] [intersection] [V.sub.j] = [PHI] for any, and i [not equal to] j and V = [summation][v.sub.i] where i = 1...k.