We propose a heuristic for parallel partitioning of graphs into equi-sized components. In particular, we identify a relationship between the graph partitioning problem (GPP) and the traveling saleman ...

Abstract: Graph partitioning is important in distributing workloads on parallel compute systems, computing sparse matrix re-orderings, and designing VLSI circuits. Refinement algorithms are used to ...

The basis for these algorithms go back to the Kernighan-Lin (KL) algorithm for graph partitioning. The KL algorithm produces very good partitions but it is slow. The Fiduccia-Mattheyses (FM) algorithm ...

During my MSc years, my eventual goal was to implement graph and hypergraph partitioning using genetic algorithms on a hypercube connected parallel computer (from Intel). Once I discovered the ...

Parallel graph partitioning and load balancing are crucial techniques for improving the performance and scalability of parallel computing applications that deal with large-scale graphs, such as ...

The first step to parallelize graph algorithms in distributed graph databases is to decide how to partition the graph data across the cluster. There are two main types of partitioning strategies ...

Our parallel shortest path techniques exploit the specific geometric and graphic structures of planar st-graphs, and involve schemes for partitioning planar st-graphs into sub-graphs in a way that ...

Article citations More>>. G. Karypis and V. Kumar, “A Parallel Algorithm for Multilevel Graph Partitioning and Sparse Matrix Ordering,” Journal of Parallel and Distributed Computing, Vol. 48, 1998, pp ...

Figure 1: A graph and a partition into two subsets S, S _ . In this case, the two subsets have equal number of vertices; such a partition is called a bisection. The number of edges crossing the cut is ...

Faster execution of parallel graph algorithms; ... Computer science theory tells us that finding the best overall graph partitioning, if we could even define “best,” is usually very slow, ...