Performance measurement and runtime tuning tools are both vital in the HPC software ecosystem and use similar techniques: the analyzed application is interrupted at specific events and information on the current system state is gathered to be either recorded or used for tuning. One of the established performance measurement tools is Score-P. It supports numerous HPC platforms and parallel programming paradigms. To extend Score-P with support for different back-ends, create a common framework for measurement and tuning of HPC applications, and to enable the re-use of common software components such as implemented instrumentation techniques, this paper makes the following contributions: (I) We describe the Score-P metric plugin interface, which enables programmers to augment the event stream with metric data from supplementary data sources that are otherwise not accessible for Score-P. (II) We introduce the flexible Score-P substrate plugin interface that can be used for custom processing of the event stream according to the specific requirements of either measurement, analysis, or runtime tuning tasks. (III) We provide examples for both interfaces that extend Score-P’s functionality for monitoring and tuning purposes.
| Identifer | oai:union.ndltd.org:DRESDEN/oai:qucosa:de:qucosa:30327 |
| Date | 18 October 2017 |
| Creators | Schöne, Robert, Tschüter, Ronny, Ilsche, Thomas, Schuchart, Joseph, Hackenberg, Daniel, Nagel, Wolfgang E. |
| Contributors | Technische Universität Dresden, Universität Stuttgart |
| Publisher | Springer International Publishing AG |
| Source Sets | Hochschulschriftenserver (HSSS) der SLUB Dresden |
| Language | English |
| Detected Language | English |
| Type | doc-type:bookPart, info:eu-repo/semantics/bookPart, doc-type:Text |
| Source | Niethammer, Christoph, Gracia, José, Hilbrich,Tobias, Knüpfer, Andreas, M. Resch, Michael, Nagel, Wolfgang E. (Hrsg.), Tools for High Performance Computing 2016 - Proceedings of the 10th International Workshop on Parallel Tools for High Performance Computing, October 2016, Stuttgart. Cham: Springer International Publishing, 2017. S. 59-82. ISBN: 978-3-319-56702-0 |
| Rights | info:eu-repo/semantics/openAccess |
| Relation | 10.1007/978-3-319-56702-0_4, info:eu-repo/grantAgreement/Europäische Union (EU)/Horizon 2020/671657//Runtime Exploitation of Application Dynamism for Energy-efficient eXascale computing/READEX, info:eu-repo/grantAgreement/Bundesministerium für Bildung und Forschung (BMBF)/Deutsche Forschungsgemeinschaft (DFG)/01TH13001//Scalable Tools for the Analysis and Optimization of Energy Consumption in HPC/SCORE-E |
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