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Evaluating Heuristic Scheduling Algorithms for High Performance Parallel Processing
Responsible organisation
2003 (English)Conference paper, (Refereed) Published
Abstract [en]

Most cluster systems used in high performance computing do not allow process relocation at run-time. Finding an allocation that results in minimal completion time is NP-hard and (non-optimal) heuristic algorithms have to be used. One major drawback with heuristics is that we do not know if the result is close to optimal or not. Here, we present a method for finding an upper bound on the minimal completion time for a given program. The bound helps the user to determine when it is worth-while to continue the heuristic search for better allocations. Based on some parameters derived from the program, as well as some parameters describing the hardware platform, the method produces the minimal completion time bound. A practical demonstration of the method is presented using a tool that produces the bound.

Place, publisher, year, edition, pages
Tokyo: Springer , 2003.
Keyword [en]
Upper bound, Completeness, Heuristic method, Optimal algorithm, Algorithm performance, NP hard problem, Parallel algorithm, Scheduling, User assistance, Program execution, High performance, Parallel processing
National Category
Computer Science
Identifiers
URN: urn:nbn:se:bth-9601ISI: 000188038200012Local ID: oai:bth.se:forskinfoBC91DB89EBC56B3BC1256E28003AD760ISBN: 3-540-20359-1 (print)OAI: oai:DiVA.org:bth-9601DiVA: diva2:837492
Conference
5th International Symposium on High Performance Computing
Available from: 2012-09-18 Created: 2004-01-27 Last updated: 2015-06-30Bibliographically approved

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Lundberg, Lars
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Citation style
  • apa
  • harvard1
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  • vancouver
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Output format
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