Abstract
IPM is a profiling and workload characterization tool for MPI applications. IPM achieves its goal of minimizing the monitoring overhead by recording performance data in a fixed-size hashtable resident in memory and by carefully optimizing time-critical operations. At the same time, IPM offers very detailed and user-centric performance metrics. IPM’s performance data is delivered as an XML file that can subsequently be used to generate a detailed profiling report in HTML format, avoiding the need for custom GUI applications. Pairwise communication volume and communication topology between processes, communication time breakdown across ranks, MPI operation timings, and MPI message sizes (buffer lengths) are some of IPM’s most widely used metrics. IPM is free and distributed under the LGPL license.
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References
Shirley Browne, Jack Dongarra, N. Garner, G. Ho, and Philip J. Mucci. A portable programming interface for performance evaluation on modern processors. Int. J. High Perform. Comput. Appl., 14(3):189–204, 2000.
Holger Brunst and Bernd Mohr. Performance analysis of large-scale OpenMP and hybrid MPI/OpenMP applications with VampirNG. In Proceedings of the First International Workshop on OpenMP (IWOMP 2005), Eugene, Oregon, USA, May 2005.
Karl Fürlinger and Michael Gerndt. Periscope: Performance analysis on large-scale systems. InSiDE – Innovatives Supercomputing in Deutschland (Featured Article), 3(2, Autumn):26–29, 2005.
Markus Geimer, Felix Wolf, Brian J. N. Wylie, and Bernd Mohr. Scalable parallel trace-based performance analysis. In Proceedings of the 13th European PVM/MPI Users’ Group Meeting on Recent Advances in Parallel Virtual Machine and Message Passing Interface (EuroPVM/MPI 2006), pages 303–312, Bonn, Germany, 2006.
Allen D. Malony and Sameer S. Shende. Performance technology for complex parallel and distributed systems. pages 37–46, 2000.
MILC website, http://physics.indiana.edu/~sg/milc.html.
Wolfgang E. Nagel, Alfred Arnold, Michael Weber, Hans-Christian Hoppe, and Karl Solchenbach. VAMPIR: Visualization and analysis of MPI resources. Supercomputer, 12(1):69–90, 1996.
Sustained system performance benchmarks at NERSC, http://www.nersc.gov/projects/ssp.php.
PAPI web page: http://icl.cs.utk.edu/papi/.
Periscope project homepage http://wwwbode.cs.tum.edu/~gerndt/home/Research/PERISCOPE/Periscope.htm.
Sameer S. Shende and Allen D. Malony. The TAU parallel performance system. International Journal of High Performance Computing Applications, ACTS Collection Special Issue, 2005.
Felix Wolf and Bernd Mohr. Automatic performance analysis of hybrid MPI/OpenMP applications. In Proceedings of the 11th Euromicro Conference on Parallel, Distributed and Network-Based Processing (PDP 2003), pages 13–22. IEEE Computer Society, February 2003.
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Fürlinger, K., Wright, N.J., Skinner, D. (2010). Performance Analysis and Workload Characterization with IPM. In: Müller, M., Resch, M., Schulz, A., Nagel, W. (eds) Tools for High Performance Computing 2009. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-11261-4_3
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DOI: https://doi.org/10.1007/978-3-642-11261-4_3
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