Combinatorial Problems in High-Performance Computing: Partitioning

Authors Rob Bisseling, Tristan van Leeuwen, Umit V. Catalyurek

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Rob Bisseling
Tristan van Leeuwen
Umit V. Catalyurek

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Rob Bisseling, Tristan van Leeuwen, and Umit V. Catalyurek. Combinatorial Problems in High-Performance Computing: Partitioning. In Combinatorial Scientific Computing. Dagstuhl Seminar Proceedings, Volume 9061, pp. 1-5, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2009)


This extended abstract presents a survey of combinatorial problems encountered in scientific computations on today's high-performance architectures, with sophisticated memory hierarchies, multiple levels of cache, and multiple processors on chip as well as off-chip. For parallelism, the most important problem is to partition sparse matrices, graph, or hypergraphs into nearly equal-sized parts while trying to reduce inter-processor communication. Common approaches to such problems involve multilevel methods based on coarsening and uncoarsening (hyper)graphs, matching of similar vertices, searching for good separator sets and good splittings, dynamical adjustment of load imbalance, and two-dimensional matrix splitting methods.
  • Partitioning
  • sparse matrix
  • hypergraph
  • parallel
  • HPC


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