Hauptseite > Publikationsdatenbank > A new optimization phase for scientific workflow management systems > print |
001 | 201129 | ||
005 | 20210129215637.0 | ||
024 | 7 | _ | |a 10.1109/eScience.2012.6404479 |2 doi |
037 | _ | _ | |a FZJ-2015-03434 |
100 | 1 | _ | |a Holl, Sonja |0 P:(DE-Juel1)132139 |b 0 |e Corresponding Author |u fzj |
111 | 2 | _ | |a 2012 IEEE 8th International Conference on E-Science (e-Science) |c Chicago |d 2012-10-08 - 2012-10-12 |w IL |
245 | _ | _ | |a A new optimization phase for scientific workflow management systems |
260 | _ | _ | |c 2012 |b IEEE |
295 | 1 | 0 | |a 2012 IEEE 8th International Conference on E-Science : [Proceedings] - IEEE, 2012. |
300 | _ | _ | |a 1 - 8 |
336 | 7 | _ | |a Contribution to a conference proceedings |b contrib |m contrib |0 PUB:(DE-HGF)8 |s 1433946205_12154 |2 PUB:(DE-HGF) |
336 | 7 | _ | |a Conference Paper |0 33 |2 EndNote |
336 | 7 | _ | |a CONFERENCE_PAPER |2 ORCID |
336 | 7 | _ | |a Output Types/Conference Paper |2 DataCite |
336 | 7 | _ | |a conferenceObject |2 DRIVER |
336 | 7 | _ | |a INPROCEEDINGS |2 BibTeX |
520 | _ | _ | |a Scientific workflows have emerged as an important tool for combining computational power with data analysis for all scientific domains in e-science. They help scientists to design and execute complex in silico experiments. However, with increasing complexity it becomes more and more infeasible to optimize scientific workflows by trial and error. To address this issue, this paper describes the design of a new optimization phase integrated in the established scientific workflow life cycle. We have also developed a flexible optimization application programming interface (API) and have integrated it into a scientific workflow management system. A sample plugin for parameter optimization based on genetic algorithms illustrates, how the API enables rapid implementation of concrete workflow optimization methods. Finally, a use case taken from the area of structural bioinformatics validates how the optimization approach facilitates setup, execution and monitoring of workflow parameter optimization in high performance computing e-science environments. |
536 | _ | _ | |a 412 - Grid Technologies and Infrastructures (POF2-412) |0 G:(DE-HGF)POF2-412 |c POF2-412 |f POF II |x 0 |
536 | _ | _ | |a 411 - Computational Science and Mathematical Methods (POF2-411) |0 G:(DE-HGF)POF2-411 |c POF2-411 |f POF II |x 1 |
588 | _ | _ | |a Dataset connected to CrossRef Conference |
700 | 1 | _ | |a Zimmermann, Olav |0 P:(DE-Juel1)132307 |b 1 |u fzj |
700 | 1 | _ | |a Hofmann-Apitius, Martin |0 P:(DE-HGF)0 |b 2 |
773 | _ | _ | |a 10.1109/eScience.2012.6404479 |
909 | C | O | |o oai:juser.fz-juelich.de:201129 |p VDB |
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913 | 1 | _ | |a DE-HGF |b Schlüsseltechnologien |l Supercomputing |1 G:(DE-HGF)POF2-410 |0 G:(DE-HGF)POF2-411 |2 G:(DE-HGF)POF2-400 |v Computational Science and Mathematical Methods |x 1 |4 G:(DE-HGF)POF |3 G:(DE-HGF)POF2 |
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