%0 Computer Program
%A Feld, Christian
%A Jäkel, René
%A Lorenz, Daniel
%A Wesarg, Bert
%A Schmidl, Dirk
%A Tschüter, Ronny
%A Oleynik, Yury
%A Wagner, Michael
%A Eschweiler, Dominic
%A Spazier, Johannes
%A Knüpfer, Andreas
%A Shende, Sameer
%A Millstein, Suzanne
%A Biersdorff, Scott
%A Geimer, Markus
%A Schlütter, Marc
%A Schmitt, Felix
%A Ziegenbalg, Johannes
%A Zhukov, Ilya
%A Dietrich, Robert
%A Geyer, Robin
%A Saviankou, Pavel
%A Knobloch, Michael
%A Mijaković, Robert
%A Schöne, Robert
%A Winkler, Frank
%A Ilsche, Thomas
%A Hermanns, Marc-André
%A Brendel, Ronny
%A Oeste, Sebastian
%A Herold, Christian
%A Sigl, Severin
%A Hilbrich, Tobias
%A Williams, Bill
%A Klotz, Sven
%A Corbin, Gregor
%A Reuter, Jan André
%A Grund, Alexander
%A Sander, Maximilian
%A Frenzel, Jan
%T Score-P: Scalable performance measurement infrastructure for parallel codes (v9.2); 9.2
%M FZJ-2025-03036
%D 2025
%X 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.
%K Performance measurement (Other)
%K Score-P (Other)
%K instrumentation (Other)
%K sampling (Other)
%K HPC (Other)
%K profiling (Other)
%K tracing (Other)
%F PUB:(DE-HGF)33
%9 Software
%R 10.5281/ZENODO.15873865
%U https://juser.fz-juelich.de/record/1044134