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| Hauptseite > Publikationsdatenbank > Scalasca Trace Tools: Toolset for scalable performance analysis of large-scale parallel applications (v2.6.1) > print |
| Hauptseite > Publikationsdatenbank > Scalasca Trace Tools: Toolset for scalable performance analysis of large-scale parallel applications (v2.6.1) > print |
| 001 | 917090 | ||
| 005 | 20250314084121.0 | ||
| 024 | 7 | _ | |a 10.5281/ZENODO.7440854 |2 doi |
| 037 | _ | _ | |a FZJ-2023-00332 |
| 100 | 1 | _ | |a Geimer, Markus |0 P:(DE-Juel1)132112 |b 0 |e Corresponding author |u fzj |
| 245 | _ | _ | |a Scalasca Trace Tools: Toolset for scalable performance analysis of large-scale parallel applications (v2.6.1) |
| 250 | _ | _ | |a 2.6.1 |
| 260 | _ | _ | |c 2022 |
| 336 | 7 | _ | |a Software |2 DCMI |
| 336 | 7 | _ | |a Software |b sware |m sware |0 PUB:(DE-HGF)33 |s 1673522422_11434 |2 PUB:(DE-HGF) |
| 336 | 7 | _ | |a MISC |2 BibTeX |
| 336 | 7 | _ | |a Computer Program |0 6 |2 EndNote |
| 336 | 7 | _ | |a OTHER |2 ORCID |
| 336 | 7 | _ | |a Software |2 DataCite |
| 520 | _ | _ | |a Scalasca is a software tool that supports the performance optimization of parallel programs by measuring and analyzing their runtime behaviour. The analysis identifies potential performance bottlenecks – in particular those concerning communication and synchronization – and offers guidance in exploring their causes. Scalasca supports the performance optimization of simulation codes on a wide range of current HPC platforms. Its powerful analysis and intuitive result presentation guides the developer through the tuning process. Scalasca targets mainly scientific and engineering applications based on the programming interfaces MPI and OpenMP, including hybrid applications based on a combination of the two. The tool has been specifically designed for use on large-scale systems, but is also well suited for small- and medium-scale HPC platforms. The software is available for free download under the New BSD open-source license. |
| 536 | _ | _ | |a 5112 - Cross-Domain Algorithms, Tools, Methods Labs (ATMLs) and Research Groups (POF4-511) |0 G:(DE-HGF)POF4-5112 |c POF4-511 |f POF IV |x 0 |
| 536 | _ | _ | |0 G:(DE-Juel-1)ATMLPP |a ATMLPP - ATML Parallel Performance (ATMLPP) |c ATMLPP |x 1 |
| 588 | _ | _ | |a Dataset connected to DataCite |
| 650 | _ | 7 | |a performance analysis |2 Other |
| 650 | _ | 7 | |a Score-P |2 Other |
| 650 | _ | 7 | |a Cube |2 Other |
| 650 | _ | 7 | |a HPC |2 Other |
| 650 | _ | 7 | |a MPI |2 Other |
| 650 | _ | 7 | |a OpenMP |2 Other |
| 650 | _ | 7 | |a trace tools |2 Other |
| 700 | 1 | _ | |a Mohr, Bernd |0 P:(DE-Juel1)132199 |b 1 |u fzj |
| 700 | 1 | _ | |a Corbin, Gregor |0 P:(DE-Juel1)188670 |b 2 |u fzj |
| 700 | 1 | _ | |a Daoud, Nour |0 P:(DE-Juel1)188664 |b 3 |u fzj |
| 700 | 1 | _ | |a Feld, Christian |0 P:(DE-Juel1)132244 |b 4 |u fzj |
| 700 | 1 | _ | |a Hermanns, Marc-André |0 P:(DE-HGF)0 |b 5 |
| 700 | 1 | _ | |a Knobloch, Michael |0 P:(DE-Juel1)132163 |b 6 |u fzj |
| 700 | 1 | _ | |a Reuter, Jan Andre |0 P:(DE-Juel1)167509 |b 7 |u fzj |
| 700 | 1 | _ | |a Saviankou, Pavel |0 P:(DE-Juel1)132249 |b 8 |u fzj |
| 700 | 1 | _ | |a Schlütter, Marc |0 P:(DE-Juel1)142180 |b 9 |u fzj |
| 700 | 1 | _ | |a Visser, Anke |0 P:(DE-Juel1)132282 |b 10 |u fzj |
| 700 | 1 | _ | |a Wylie, Brian J. N. |0 P:(DE-Juel1)132302 |b 11 |u fzj |
| 700 | 1 | _ | |a Zhukov, Ilya |0 P:(DE-Juel1)144419 |b 12 |u fzj |
| 773 | _ | _ | |a 10.5281/ZENODO.7440854 |
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| 913 | 1 | _ | |a DE-HGF |b Key Technologies |l Engineering Digital Futures – Supercomputing, Data Management and Information Security for Knowledge and Action |1 G:(DE-HGF)POF4-510 |0 G:(DE-HGF)POF4-511 |3 G:(DE-HGF)POF4 |2 G:(DE-HGF)POF4-500 |4 G:(DE-HGF)POF |v Enabling Computational- & Data-Intensive Science and Engineering |9 G:(DE-HGF)POF4-5112 |x 0 |
| 914 | 1 | _ | |y 2022 |
| 920 | 1 | _ | |0 I:(DE-Juel1)JSC-20090406 |k JSC |l Jülich Supercomputing Center |x 0 |
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