Abstract
The CEPBA tools environment is a performance analysis environment that initially focused on trace visualization and analysis. Current development efforts try to go beyond the presentation of simple statistics by introducing more intelligence in the analysis of the raw data.
The paper presents an overview of three recent developments in this area. First, we show how spectral analysis techniques can be used to isolate sufficiently small regions of a trace that characterize the behavior of the whole run. Second, we describe how clustering analysis techniques can be used to identify temporal and spatial structure in parallel programs, an essential component to ease the job of the analyst, but also to automatically derive a broad range of both precise and focused metrics from a single run of a program. Then we describe how sampling and tracing data acquisition techniques can interoperate to generate with very low overhead extremely precise metrics about the temporal behavior of a program.
The development rests upon the trace based CEPBA-Tools environment, using the Paraver visualization capabilities to check the quality and usefulness of the techniques. Once identified, they can be implemented on-line aiming at maximizing the amount of information obtained from a run. We report the work being done on top of MRNET in this direction.
We consider that by applying and combining these and other techniques from various data analysis and mining fields, performance analysis tools will be able to effectively address the huge challenge posed by future exascale systems.
Access provided by Autonomous University of Puebla. Download to read the full chapter text
Chapter PDF
Similar content being viewed by others
Keywords
- Parallel Program
- Cluster Analysis Technique
- Spectral Analysis Technique
- Precise Metrics
- Data Acquisition Technique
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.
References
H. Servat, G. Llort, J. Gimenez, J. Labarta: Detailed performance analysis using coarse grain sampling 2nd Workshop on Productivity and Performance. PROPER 2009.
J. Gonzalez, J. Gimenez and J. Labarta: Automatic Detection of Parallel Applications Computation Phases. Proceedings of the 23rd IEEE International Parallel and Distributed Processing Symposium (IPDPS’09), (2009)
J. Gonzalez, J. Gimenez and J. Labarta: Automatic evaluation of the computation structure of parallel applications. PDCAT 2009.
Casas, M.; Badia, R. M.; Labarta, J. Automatic Structure Extraction from MPI Applications Tracefiles. Euro-Par 2007. 3–12
J. Labarta, S. Girona, V. Pillet, T. Cortes and L. Gregoris: DiP: A Parallel Program Development Environment. Proc. of 2nd International EuroPar Conference (EuroPar 96) (1996)
W. E. Nagel, A. Arnold, M. Weber, H. C. Hoppe and K. Solchenbach: VAMPIR: Visualization and Analysis of MPI Resources. Supercomputer, vol. 12, n. 1, 69–80, (1996).
G. Llort, J. Gonzalez, H. Servat, J. Gimenez and J. Labarta. On-line detection of large-scale parallel application’s structure IPDPS 2010.
S. Shende and A. D. Malony: The TAU Parallel Performance System. International Journal of High Performance Computing Applications, Volume 20 Number 2 Summer 2006. 287–311
P. C. Roth, D. C. Arnold, and B. P. Miller: MRNet: A Software-Based Multicast/Reduction Network for Scalable Tools. SC2003, Phoenix, Arizona, November 2003
Browne, S., Dongarra, J., Garner, N., London, K., Mucci, P.: A Scalable Cross-Platform Infrastructure for Application Performance Tuning Using Hardware Counters. Proceedings of SuperComputing 2000 (SC’00), Dallas, TX, November 2000
A. Mericas et al.: CPI analysis on POWER5, Part 2: Introducing the CPI breakdown model. https://www.ibm.com/developerworks/library/pa-cpipower2/
Labarta J., Gimenez J.: Performance Analysis: From Art to Science. In Parallel Processing for Scientific Computing. M. Heroux and R. Raghavan and H.D. Simon Eds. SIAM. 2006. 9–32.
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2010 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Labarta, J. (2010). New Analysis Techniques in the CEPBA-Tools Environment. 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_9
Download citation
DOI: https://doi.org/10.1007/978-3-642-11261-4_9
Published:
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-11260-7
Online ISBN: 978-3-642-11261-4
eBook Packages: Computer ScienceComputer Science (R0)