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Scalable Parallel Graph Coloring Algorithms
, 2000
"... Finding a good graph coloring quickly is often a crucial phase in the development of efficient, parallel algorithms for many scientific and engineering applications. In this paper we consider the problem of solving the graph coloring problem itself in parallel. We present a simple and fast paral ..."
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Cited by 19 (7 self)
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Finding a good graph coloring quickly is often a crucial phase in the development of efficient, parallel algorithms for many scientific and engineering applications. In this paper we consider the problem of solving the graph coloring problem itself in parallel. We present a simple and fast parallel graph coloring heuristic that is well suited for shared memory programming and yields an almost linear speedup on the PRAM model. We also present a second heuristic that improves on the number of colors used. The heuristics have been implemented using OpenMP. Experiments conducted on an SGI Cray Origin 2000 super computer using very large graphs from finite element methods and eigenvalue computations validate the theoretical run-time analysis.
PRO: a model for Parallel Resource-Optimal computation
- IN 16TH ANNUAL INTERNATIONAL SYMPOSIUM ON HIGH PERFORMANCE COMPUTING SYSTEMS AND APPLICATIONS. IEEE, THE INSTITUTE OF ELECTRICAL AND ELECTRONICS ENGINEERS
, 2002
"... We present a new parallel computation model that enables the design of resource-optimal scalable parallel algorithms and simplifies their analysis. The model rests on the novel idea of incorporating relative optimality as an integral part and measuring the quality of a parallel algorithm in terms of ..."
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Cited by 9 (4 self)
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We present a new parallel computation model that enables the design of resource-optimal scalable parallel algorithms and simplifies their analysis. The model rests on the novel idea of incorporating relative optimality as an integral part and measuring the quality of a parallel algorithm in terms of granularity.
Practical Parallel Algorithms for Graph Coloring Problems in Numerical Optimization
, 2003
"... This work was financially supported by the University of Bergen through a ..."
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Cited by 2 (1 self)
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This work was financially supported by the University of Bergen through a
A Coarse Grained Parallel Algorithm for Maximum Weight Matching in Trees
"... We present an efficient coarse grained parallel algorithm for computing a maximum weight matching in trees. A divide and conquer approach based on centroid decomposition of trees is used. Our algorithm requires O(log p) communication rounds with # # p O p and # # p O memory per processor (where ..."
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Cited by 1 (1 self)
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We present an efficient coarse grained parallel algorithm for computing a maximum weight matching in trees. A divide and conquer approach based on centroid decomposition of trees is used. Our algorithm requires O(log p) communication rounds with # # p O p and # # p O memory per processor (where p is the number of processors used and n is the size of the tree).
apport de rechercheCommunication and Memory Optimized Tree Contraction and List Ranking
"... Rapport de recherche n ° 4061 — Novembre 2000 — 9 pages Abstract: We present a simple and efficient algorithm for the Tree Contraction Problem on a Coarse Grained p-Multiprocessor. With respect to its total computing time, its demand of memory and its total inter-processor communication it is only a ..."
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Rapport de recherche n ° 4061 — Novembre 2000 — 9 pages Abstract: We present a simple and efficient algorithm for the Tree Contraction Problem on a Coarse Grained p-Multiprocessor. With respect to its total computing time, its demand of memory and its total inter-processor communication it is only a small constant factor away from optimality. Unless traditional PRAM algorithms it doesn’t use List Ranking as a necessary subroutine but specializes to List Ranking when applied to lists. Key-words: tree contraction, list ranking, coarse grained parallel algorithms
