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In the scope of HPC, the name Vampir denotes a software framework that addresses the performance monitoring, visualization, and analysis of concurrent software programs by means of a technique referred to as event tracing. Originally, VAMPIR was an acronym for “Visualization and Analysis of MPI Resources.” Today, the framework no longer addresses MPI programs only. Support for many different programing paradigms and performance data sources has been included over time.
The framework consists of a monitor and a visualization component, which are sometimes independently referred to as VampirTrace and Vampir. The monitor component attaches to a running software program and records timed status information about the invocation of program subroutines, the usage of communication interfaces, and the utilization of system resources.
Discussion
Monitoring
The monitoring component (VampirTrace) is used for recording the...
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Bibliography
Nagel WE, Arnold A, Weber M, Hoppe H-Chr, Solchenbach K (1996) VAMPIR: visualization and analysis of MPI resources. Supercomput J 1(12):69–80. SARA, Amsterdam
Müller M, Knüpfer A, Jurenz M, Lieber M, Brunst H, Mix H, Nagel WE (2007) Developing scalable applications with Vampir, VampirServer and VampirTrace. In: Parallel computing: architectures, algorithms and applications, Adv Parallel Comput 15:637–644. IOS Press, Amsterdam. ISBN 978-1-58603-796-3
Knüpfer A, Brunst H, Doleschal J, Jurenz M, Mickler LH, Müller M, Nagel WE (2008) The Vampir performance analysis tool-set. In: Tools for high performance computing. Springer, Berlin, pp 139–155. ISBN 978-3-540-68561-6
Brunst H (2008) Integrative concepts for scalable distributed performance analysis and visualization of parallel programs. Dissertation, Technische Universität Dresden. ISBN 978-3-8322-6990-6
Knüpfer A (2009) Advanced memory data structures for scalable event trace analysis. Dissertation, Technische Universität Dresden, Suedwestdeutscher Verlag fuer Hochschulschriften. ISBN 978-3-838-10943-5
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Brunst, H., Knüpfer, A. (2011). Vampir. In: Padua, D. (eds) Encyclopedia of Parallel Computing. Springer, Boston, MA. https://doi.org/10.1007/978-0-387-09766-4_60
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DOI: https://doi.org/10.1007/978-0-387-09766-4_60
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