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Scalasca v2: Back to the Future Read chapter Read first chapter

2015 | OriginalPaper | Chapter

Combining Instrumentation and Sampling for Trace-Based Application Performance Analysis

Authors : Thomas Ilsche, Joseph Schuchart, Robert Schöne, Daniel Hackenberg

Published in: Tools for High Performance Computing 2014

Publisher: Springer International Publishing

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Abstract

Performance analysis is vital for optimizing the execution of high performance computing applications. Today different techniques for gathering, processing, and analyzing application performance data exist. Application level instrumentation for example is a powerful method that provides detailed insight into an application’s behavior. However, it is difficult to predict the instrumentation-induced perturbation as it largely depends on the application and its input data. Thus, sampling is a viable alternative to instrumentation for gathering information about the execution of an application by recording its state at regular intervals. This method provides a statistical overview of the application execution and its overhead is more predictable than with instrumentation. Taking into account the specifics of these techniques, this paper makes the following contributions: (I) A comprehensive overview of existing techniques for application performance analysis. (II) A novel tracing approach that combines instrumentation and sampling to offer the benefits of complete information where needed with reduced perturbation. We provide examples using selected instrumentation and sampling methods to detail the advantage of such mixed information and discuss arising challenges and prospects of this approach.

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previous chapter Tuning Plugin Development for the Periscope Tuning Framework
next chapter Ocelotl: Large Trace Overviews Based on Multidimensional Data Aggregation
Literature
1.
Adhianto, L., Banerjee, S., Fagan, M., Krentel, M., Marin, G., Mellor-Crummey, J., Tallent, N.R.: HPCTOOLKIT: tools for performance analysis of optimized parallel programs. Concurr. Comput.: Pract. Exp. 22(6), 685–701 (2010)
2.
Binder, W.: Portable and accurate sampling profiling for Java. Softw.: Pract. Exp. 36(6), 615–650 (2006)
3.
Buck, B., Hollingsworth, J.K.: An API for runtime code patching. Int. J. High Perform. Comput. Appl. 14, 317–329 (2000)CrossRef
4.
de Melo, A.C.: The new linux ‘perf’ tools. In: Slides from Linux Kongress, The German Unix User Group (2010)
5.
Dietrich, R., Ilsche, T., Juckeland, G.: Non-intrusive performance analysis of parallel hardware accelerated applications on hybrid architectures. In: International Conference on Parallel Processing Workshops, San Diego (2010)CrossRef
6.
Dongarra, J., Malony, A.D., Moore, S., Mucci, P., Shende, S.: Performance instrumentation and measurement for terascale systems. In: Proceedings of the 2003 International Conference on Computational Science, ICCS’03, Melbourne. Springer (2003)
7.
Geimer, M., Wolf, F., Wylie, B.J.N., Ábrahám, E., Becker, D., Mohr, B.: The Scalasca performance toolset architecture. Concurr. Comput.: Pract. Exp. 22(6), 702–719 (2010)
8.
Graham, S.L., Kessler, P.B., McKusick, M.K.: gprof: a call graph execution profiler. In: SIGPLAN Symposium on Compiler Construction, Boston (1982)CrossRef
9.
Ilsche, T., Schuchart, J., Cope, J., Kimpe, D., Jones, T., Knüpfer, A., Iskra, K., Ross, R., Nagel, W.E., Poole, S.: Optimizing I/O forwarding techniques for extreme-scale event tracing. Cluster Comput. 9, 1–18 (2013)
10.
Jain, R.K.: The Art of Computer Systems Performance Analysis: Techniques for Experimental Design, Measurement, Simulation, and Modeling. Wiley, New York (1991)MATH
11.
Juckeland, G.: Trace-based performance analysis for hardware accelerators. PhD thesis, TU Dresden (2012)
12.
Knüpfer, A., Rössel, C., an Mey, D., Biersdorff, S., Diethelm, K., Eschweiler, D., Geimer, M., Gerndt, M., Lorenz, D., Malony, A.D., Nagel, W.E., Oleynik, Y., Philippen, P., Saviankou, P., Schmidl, D., Shende, S.S., Tschüter, R., Wagner, M., Wesarg, B., Wolf, F.: Score-P – a joint performance measurement run-time infrastructure for Periscope, Scalasca, TAU, and Vampir. In: Proceedings of 5th Parallel Tools Workshop, 2011, Dresden. Springer (2012)
13.
Laurenzano, M.A., Tikir, M.M., Carrington, L., Snavely, A.: Pebil: efficient static binary instrumentation for linux. In: IEEE International Symposium on Performance Analysis of Systems Software (ISPASS), White Plains (2010)
14.
Lindlan, K.A., Cuny, J., Malony, A.D., Shende, S., Juelich, F., Rivenburgh, R., Rasmussen, C., Mohr, B.: A tool framework for static and dynamic analysis of object-oriented software with templates. In: Proceedings of the International Conference on Supercomputing, Santa Fe. IEEE (2000)
15.
Malony, A.D., Shende, S.S., Morris, A., Joubert, G.R., Nagel, W.E., Peters, F.J., Plata, O., Tirado, P., Zapata, E.: Phase-based parallel performance profiling. In: Proceedings of the PARCO 2005 Conference, jülich, Malaga (2005)
16.
Mohr, B., Malony, A.D., Shende, S., Wolf, F.: Towards a performance tool interface for OpenMP: An approach based on directive rewriting. In: Proceedings to the Third Workshop on OpenMP (EWOMP), Barcelona (2001)
17.
Morris, A., Malony, A.D., Shende, S., Huck, K.A.: Design and implementation of a hybrid parallel performance measurement system. In: ICPP, San Diego, pp. 492–501 (2010)
18.
Müller, M.S., Knüpfer, A., Jurenz, M., Lieber, M., Brunst, H., Mix, H., Nagel, W.E.: Developing scalable applications with Vampir, VampirServer and VampirTrace. In: Parallel Computing: Architectures, Algorithms and Applications, vol. 15. IOS Press, Amsterdam/Washington, DC (2008)
19.
20.
Schöne, R., Tschüter, R., Ilsche, T., Hackenberg, D.: The vampirtrace plugin counter interface: introduction and examples. In: Euro-Par 2010 Parallel Processing Workshops, Ischia. Volume 6586 of Lecture Notes in Computer Science. Springer (2011)
21.
Servat, H., Llort, G., Giménez, J., Huck, K., Labarta, J.: Folding: detailed analysis with coarse sampling. In: Tools for High Performance Computing 2011, Dresden. Springer (2012)
22.
Shende, S.S., Malony, A.D.: The TAU parallel performance system. Int. J. High Perform. Comput. Appl. 20(2), 287–311 (2006)CrossRef
23.
Szebenyi, Z., Gamblin, T., Schulz, M., de Supinski, B.R., Wolf, F., Wylie, B.J.N.: Reconciling sampling and direct instrumentation for unintrusive call-path profiling of MPI programs. In: Proceedings of the 25th IEEE International Parallel & Distributed Processing Symposium (IPDPS), Anchorage, May 2011
24.
Szebenyi, Z., Wolf, F., Wylie, B.J.N.: Space-efficient time-series call-path profiling of parallel applications. In: Proceedings of the International Conference on Supercomputing, Yorktown Heights, Nov 2009. ACM (2009)
25.
Wylie, B.J.N., Geimer, M., Mohr, B., Böhme, D., Szebenyi, Z., Wolf, F.: Large-scale performance analysis of Sweep3D with the Scalasca toolset. Parallel Process. Lett. 20(4), 397–414 (2010)CrossRefMathSciNet
Metadata
Title
Combining Instrumentation and Sampling for Trace-Based Application Performance Analysis
Authors
Thomas Ilsche
Joseph Schuchart
Robert Schöne
Daniel Hackenberg
Copyright Year
2015
Book
Tools for High Performance Computing 2014

Print ISBN: 978-3-319-16011-5

Electronic ISBN: 978-3-319-16012-2

Copyright Year: 2015

DOI
https://doi.org/10.1007/978-3-319-16012-2_6

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