DagSemProc.09061.6.pdf
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Combinatorial Problems in High-Performance Computing: Partitioning
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Dagstuhl Seminar Proceedings, Volume 9061
Series: Dagstuhl Seminar Proceedings (DagSemProc) - License:
Creative Commons Attribution 4.0 International license
- Publication Date: 2009-07-24
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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)
https://doi.org/10.4230/DagSemProc.09061.6
https://doi.org/10.4230/DagSemProc.09061.6
Abstract
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.
Keywords
- Partitioning
- sparse matrix
- hypergraph
- parallel
- HPC
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