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@MISC{Feld:1006647,
author = {Feld, Christian and Jäkel, R. and Lorenz, Daniel and
Wesarg, B. and Schmidl, D. and Tschüter, R. and Oleynik, Y.
and Wagner, M. and Eschweiler, D. and Spazier, J. and
Knüpfer, A. and Shende, S. and Millstein, S. and
Biersdorff, S. and Geimer, Markus and Schlütter, Marc and
Schmitt, F. and Ziegenbalg, J. and Zhukov, Ilya and
Dietrich, R. and Geyer, R. and Saviankou, Pavel and
Knobloch, Michael and Mijaković, R. and Schöne, R. and
Winkler, F. and Ilsche, T. and Hermanns, Marc-André and
Brendel, R. and Oeste, S. and Herold, C. and Sigl, S. and
Hilbrich, T. and Williams, W. and Klotz, S. and Corbin,
Gregor and Reuter, Jan},
title = {{S}core-{P}: {S}calable performance measurement
infrastructure for parallel codes (v8.1)},
reportid = {FZJ-2023-01779},
year = {2023},
abstract = {The Score-P measurement infrastructure is a highly scalable
and easy-to-use tool suite for profiling, event tracing, and
online analysis of HPC applications. Score-P offers the user
a maximum of convenience by supporting a number of analysis
tools. Currently, it works with CubeGUI, Scalasca trace
tools, Vampir, Tau, and Extra-P and is open for other tools.
Score-P comes together with the new Open Trace Format
Version 2, the Cube4 profiling format and the Opari2
instrumenter. Score-P is available under the 3-clause BSD
Open Source license.},
keywords = {Performance measurement (Other) / Score-P (Other) /
instrumentation (Other) / sampling (Other) / HPC (Other) /
profiling (Other) / tracing (Other)},
cin = {JSC},
cid = {I:(DE-Juel1)JSC-20090406},
pnm = {5112 - Cross-Domain Algorithms, Tools, Methods Labs (ATMLs)
and Research Groups (POF4-511) / ATMLPP - ATML Parallel
Performance (ATMLPP)},
pid = {G:(DE-HGF)POF4-5112 / G:(DE-Juel-1)ATMLPP},
typ = {PUB:(DE-HGF)33},
doi = {10.5281/ZENODO.7817192},
url = {https://juser.fz-juelich.de/record/1006647},
}