This title appears in the Scientific Report :
2009
Please use the identifier:
http://hdl.handle.net/2128/3666 in citations.
Konzeption eines Softwaresystems zur Prognose von Benchmarking-Ergebnissen paralleler Programme im Scientific Computing
Konzeption eines Softwaresystems zur Prognose von Benchmarking-Ergebnissen paralleler Programme im Scientific Computing
In today’s research environment scientific computing acts as an interface between theory and experiment. Large simulations are calculated on supercomputers. Therefore it is quite important for scientists how an application program behaves on a certain computer. But that is also true for the manageme...
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Personal Name(s): | Meier, Stefanie (Corresponding author) |
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Contributing Institute: |
Jülich Supercomputing Center; JSC |
Imprint: |
Jülich
Forschungszentrum Jülich GmbH Zentralbibliothek, Verlag
2009
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Physical Description: |
IV, 94 p. |
Dissertation Note: |
Aachen, FH, Standort Jülich, Masterarbeit, 2009 |
Document Type: |
Master Thesis |
Research Program: |
Scientific Computing |
Series Title: |
Berichte des Forschungszentrums Jülich
4298 |
Subject (ZB): | |
Link: |
OpenAccess |
Publikationsportal JuSER |
In today’s research environment scientific computing acts as an interface between theory and experiment. Large simulations are calculated on supercomputers. Therefore it is quite important for scientists how an application program behaves on a certain computer. But that is also true for the management and administrators of a computer center who want to meet the needs of their users. Especially during a procurement process for a new supercomputer it is fundamental to estimate the performance of that computer. Normally, benchmark suites are used to measure the performance of a supercomputer. But on a future computer these benchmarks cannot be run, so one is interested in having a prediction. In this master thesis, benchmarking is introduced in the context of supercomputing. Questions which benchmarking should answer are reviewed. Several possibilities of performing a prediction for benchmark results are shown. It seems that Artificial Intelligence is a promising method for this kind of prognosis and is investigated further. In detail, expert systems together with ontologies and artificial neural networks are taken into account and compared with each other. After a decision for one of these methods, it is used in an extensive test series. In the last part of this thesis the conception of a software system for prediction of application benchmarks on new computer systems is built on the performed tests. |