
doi: 10.1137/0914041
Summary: The problem of computing good graph colorings arises in many diverse applications, such as in the estimation of sparse Jacobians and in the development of efficient, parallel iterative methods for solving sparse linear systems. This paper presents an asynchronous graph coloring heuristic well suited to distributed memory parallel computers. Experimental results obtained on an Intel iPSC/860 are presented, which demonstrate that, for graphs arising from finite element applications, the heuristic exhibits scalable performance and generates colorings usually within three or four colors of the best-known linear time sequential heuristics. For bounded degree graphs, it is shown that the expected running time of the heuristic under the P-RAM computation model is bounded by \(EO(\log(n)/\log\log(n))\). This bound is an improvement over the previously known best upper bound for the expected running time of a random heuristic for the graph coloring problem.
Iterative numerical methods for linear systems, Numerical solutions to overdetermined systems, pseudoinverses, Graph theory (including graph drawing) in computer science, sparse matrices, Distributed algorithms, Parallel numerical computation, distributed memory computers, random algorithms, graph coloring heuristics
Iterative numerical methods for linear systems, Numerical solutions to overdetermined systems, pseudoinverses, Graph theory (including graph drawing) in computer science, sparse matrices, Distributed algorithms, Parallel numerical computation, distributed memory computers, random algorithms, graph coloring heuristics
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