Fitness Landscapes, Memetic Algorithms, and Greedy Operators for Graph Bipartitioning
Evolutionary Computation
A grid computing based approach for the power system dynamic security assessment
Computers and Electrical Engineering
Self-stabilizing algorithm for maximal graph partitioning into triangles
SSS'12 Proceedings of the 14th international conference on Stabilization, Safety, and Security of Distributed Systems
Self-stabilizing algorithm for maximal graph decomposition into disjoint paths of fixed length
Proceedings of the 4th International Workshop on Theoretical Aspects of Dynamic Distributed Systems
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Identifying the parallelism in a problem by partitioning its data and tasks among the processors of a parallel computer is a fundamental issue in parallel computing. This problem can be modeled as a graph partitioning problem in which the vertices of a graph are divided into a specified number of subsets such that few edges join two vertices in different subsets. Several new graph partitioning algorithms have been developed in the past few years, and we survey some of this activity. We describe the terminology associated with graph partitioning, the complexity of computing good separators, and graphs that have good separators. We then discuss early algorithms for graph partitioning, followed by three new algorithms based on geometric, algebraic, and multilevel ideas. The algebraic algorithm relies on an eigenvector of a Laplacian matrix associated with the graph to compute the partition. The algebraic algorithm is justified by formulating graph partitioning as a quadratic assignment problem. We list several papers that describe applications of graph partitioning to parallel scientific computing and other applications.