TY  - COMP
AU  - Feld, Christian
AU  - Jäkel, René
AU  - Lorenz, Daniel
AU  - Wesarg, Bert
AU  - Schmidl, Dirk
AU  - Tschüter, Ronny
AU  - Oleynik, Yury
AU  - Wagner, Michael
AU  - Eschweiler, Dominic
AU  - Spazier, Johannes
AU  - Knüpfer, Andreas
AU  - Shende, Sameer
AU  - Millstein, Suzanne
AU  - Biersdorff, Scott
AU  - Geimer, Markus
AU  - Schlütter, Marc
AU  - Schmitt, Felix
AU  - Ziegenbalg, Johannes
AU  - Zhukov, Ilya
AU  - Dietrich, Robert
AU  - Geyer, Robin
AU  - Saviankou, Pavel
AU  - Knobloch, Michael
AU  - Mijaković, Robert
AU  - Schöne, Robert
AU  - Winkler, Frank
AU  - Ilsche, Thomas
AU  - Hermanns, Marc-André
AU  - Brendel, Ronny
AU  - Oeste, Sebastian
AU  - Herold, Christian
AU  - Sigl, Severin
AU  - Hilbrich, Tobias
AU  - Williams, Bill
AU  - Klotz, Sven
AU  - Corbin, Gregor
AU  - Reuter, Jan André
AU  - Grund, Alexander
AU  - Sander, Maximilian
AU  - Frenzel, Jan
TI  - Score-P: Scalable performance measurement infrastructure for parallel codes (v9.2); 9.2
M1  - FZJ-2025-03036
PY  - 2025
AB  - The instrumentation and measurement framework Score-P, together with analysis tools build on top of its output formats, provides insight into massively parallel HPC applications, their communication, synchronization, I/O, and scaling behavior to pinpoint performance bottlenecks and their causes. Score-P is a highly scalable and easy-to-use tool suite for profiling (summarizing program execution) and event tracing (capturing events in chronological order) of HPC applications. The scorep instrumentation command adds instrumentation hooks into a user's application by either prepending or replacing the compile and link commands. C, C++, Fortran, and Python codes as well as contemporary HPC programming models (MPI, threading, GPUs, I/O) are supported. When running an instrumented application, measurement event data is provided by the instrumentation hooks to the measurement core. There, the events are augmented with high-accuracy timestamps and potentially hardware counters (a plugin-API allows querying additional metric sources). The augmented events are then passed to one or both of the built-in event consumers, profiling and tracing (a plugin-API allows creation of additional event consumers) which finally provide output in the formats CUBE4 and OTF2, respectively. These open and backwards-compatible output formats can be consumed by established analysis tools, e.g., like CubeGUI, the performance report explorer for Scalasca and Score-P, a generic tool for displaying a multidimensional performance space, Extra-P, an automatic performance-modelling tool that supports the user in the identification of scalability bugs, TAU's ParaProf, a portable, scalable performance analysis tool, and PerfExplorer, a framework for parallel performance data mining and knowledge discovery, Scalasca Trace Tools, a collection of trace-based performance analysis tools that have been specifically designed for use on large-scale systems featuring hundreds of thousands of CPU cores, automatically identifying potential communication and synchronization bottlenecks and offering guidance in exploring their causes, and Vampir, a trace-based framework that enables users to quickly display and analyze arbitrary program behavior. Score-P is available under the 3-clause BSD Open Source license. Version 9.2 is a bugfix release for version 9.1. For features/changes/improvements introduced in the latest version, please see the Changelog file.
KW  - Performance measurement (Other)
KW  - Score-P (Other)
KW  - instrumentation (Other)
KW  - sampling (Other)
KW  - HPC (Other)
KW  - profiling (Other)
KW  - tracing (Other)
LB  - PUB:(DE-HGF)33
DO  - DOI:10.5281/ZENODO.15873865
UR  - https://juser.fz-juelich.de/record/1044134
ER  -