Article · Wikipedia archive · Last revised Jul 27, 2026

Scalasca

Scalasca is a free and open-source software for measurement, analysis, and optimization of parallel program performance. It is licensed under the BSD-style license.

Last revised
Jul 27, 2026
Read time
≈ 1 min
Length
271 w
Citations
6
Source
Wikipedia ↗
Scalasca
DevelopersForschungszentrum Jülich and Technische Universität Darmstadt
Written inC, C++
Operating systemUnix-like
PlatformIA-32, x64, ARM, PowerPC
TypeProfiling
LicenseBSD
Websitewww.scalasca.org

Scalasca is a free and open-source software for measurement, analysis, and optimization of parallel program performance.1 It is licensed under the BSD-style license.2

Scalasca is mostly used for profiling scientific and engineering applications using OpenMP and/or MPI. It supports runtime analysis on supercomputers.34 The application being analysed needs first of all to be "instrumented": MPI usage is instrumented simply by linking the application to the measuring library, while OpenMP usage is instrumented by recompiling from source using Scalasca's modified compiler.56

References

References

  1. Geimer, Markus; et al. (25 April 2010). "The Scalasca performance toolset architecture". Concurrency and Computation: Practice and Experience. 22 (6): 702–719. CiteSeerX 10.1.1.183.3213. doi:10.1002/cpe.1556. S2CID 14248376. Retrieved 29 June 2016.
  2. "About". www.scalasca.org. Retrieved 2020-11-14.
  3. Knüpfer, Andreas; Rössel, Christian; Mey, Dieter an; Biersdorff, Scott; Diethelm, Kai; Eschweiler, Dominic; Geimer, Markus; Gerndt, Michael; Lorenz, Daniel (2012). "Score-P: A Joint Performance Measurement Run-Time Infrastructure for Periscope, Scalasca, TAU, and Vampir" (PDF). In Brunst, Holger; Müller, Matthias S.; Nagel, Wolfgang E.; Resch, Michael M. (eds.). Tools for High Performance Computing 2011. Berlin, Heidelberg: Springer. pp. 79–91. doi:10.1007/978-3-642-31476-6_7. ISBN 978-3-642-31476-6. S2CID 18004916.
  4. Wolf, Felix; Wylie, Brian J. N.; Ábrahám, Erika; Becker, Daniel; Frings, Wolfgang; Fürlinger, Karl; Geimer, Markus; Hermanns, Marc-André; Mohr, Bernd (2008). "Usage of the SCALASCA toolset for scalable performance analysis of large-scale parallel applications". In Resch, Michael; Keller, Rainer; Himmler, Valentin; Krammer, Bettina; Schulz, Alexander (eds.). Tools for High Performance Computing. Berlin, Heidelberg: Springer. pp. 157–167. doi:10.1007/978-3-540-68564-7_10. ISBN 978-3-540-68564-7.
  5. "Scalable performance analysis of large-scale parallel applications" (PDF). Retrieved 2020-11-14.
  6. "Performance Analysis with Scalasca" (PDF). Retrieved 2020-11-14.
External links