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001 | 152042 | ||
005 | 20250314084110.0 | ||
020 | _ | _ | |a 978-1-61499-380-3 |
024 | 7 | _ | |a 10.3233/978-1-61499-381-0-783 |2 doi |
024 | 7 | _ | |a WOS:000452120400079 |2 WOS |
037 | _ | _ | |a FZJ-2014-01862 |
100 | 1 | _ | |a Jaeger, Julien |0 P:(DE-HGF)0 |b 0 |e Corresponding Author |
111 | 2 | _ | |a International Conference on Parallel Computing |g ParCo 2013 |c Munich |d 2013-09-10 - 2013-09-13 |w Germany |
245 | _ | _ | |a Binary Instrumentation for Scalable Performance Measurement of OpenMP Applications |
260 | _ | _ | |c 2014 |b IOS Press |
295 | 1 | 0 | |a Parallel Computing: Accelerating Computational Science and Engineering (CSE) |
300 | _ | _ | |a 783 - 792 |
336 | 7 | _ | |a Contribution to a conference proceedings |b contrib |m contrib |0 PUB:(DE-HGF)8 |s 1396418051_15498 |2 PUB:(DE-HGF) |
336 | 7 | _ | |a Contribution to a book |0 PUB:(DE-HGF)7 |2 PUB:(DE-HGF) |m contb |
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 |
490 | 0 | _ | |a Advances in Parallel Computing |v 25 |
520 | _ | _ | |a In this paper we present a binary instrumentation methodology to monitor runtime events. We demonstrate our approach on OpenMP constructs for the Intel and GNU compilers. A binary-level static analysis detects the compiler patterns and the runtime function calls corresponding to OpenMP regions. To this effect we integrate the software tool MAQAO with the scalable measurement infrastructure Score-P. We design a new interface and modify both tools to support the new events. The main advantages of using binary instrumentation are the possibility to retrieve implicit runtime events, to instrument without recompilation, to be independent from the language, and not to interact with compiler optimization. Our validation experiments and first results shows that binary instrumentation has not introduced any additional overhead. |
536 | _ | _ | |a 411 - Computational Science and Mathematical Methods (POF2-411) |0 G:(DE-HGF)POF2-411 |c POF2-411 |f POF II |x 0 |
536 | _ | _ | |0 G:(DE-Juel-1)ATMLPP |a ATMLPP - ATML Parallel Performance (ATMLPP) |c ATMLPP |x 1 |
700 | 1 | _ | |a Philippen, Peter |0 P:(DE-Juel1)143710 |b 1 |u fzj |
700 | 1 | _ | |a Petit, Eric |0 P:(DE-HGF)0 |b 2 |
700 | 1 | _ | |a Rubial, Andres Charif |0 P:(DE-HGF)0 |b 3 |
700 | 1 | _ | |a Rössel, Christian |0 P:(DE-Juel1)132244 |b 4 |u fzj |
700 | 1 | _ | |a Jalby, William |0 P:(DE-HGF)0 |b 5 |
700 | 1 | _ | |a Mohr, Bernd |0 P:(DE-Juel1)132199 |b 6 |u fzj |
773 | _ | _ | |a 10.3233/978-1-61499-381-0-783 |
909 | C | O | |o oai:juser.fz-juelich.de:152042 |p VDB |
910 | 1 | _ | |a Forschungszentrum Jülich GmbH |0 I:(DE-588b)5008462-8 |k FZJ |b 1 |6 P:(DE-Juel1)143710 |
910 | 1 | _ | |a Forschungszentrum Jülich GmbH |0 I:(DE-588b)5008462-8 |k FZJ |b 4 |6 P:(DE-Juel1)132244 |
910 | 1 | _ | |a Forschungszentrum Jülich GmbH |0 I:(DE-588b)5008462-8 |k FZJ |b 6 |6 P:(DE-Juel1)132199 |
913 | 2 | _ | |a DE-HGF |b Key Technologies |l Supercomputing & Big Data |1 G:(DE-HGF)POF3-510 |0 G:(DE-HGF)POF3-511 |2 G:(DE-HGF)POF3-500 |v Computational Science and Mathematical Methods |x 0 |
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 0 |4 G:(DE-HGF)POF |3 G:(DE-HGF)POF2 |
914 | 1 | _ | |y 2014 |
920 | 1 | _ | |0 I:(DE-Juel1)JSC-20090406 |k JSC |l Jülich Supercomputing Center |x 0 |
980 | _ | _ | |a contrib |
980 | _ | _ | |a VDB |
980 | _ | _ | |a contb |
980 | _ | _ | |a I:(DE-Juel1)JSC-20090406 |
980 | _ | _ | |a UNRESTRICTED |
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