Abstract
One of the major issues in the performance analysis of HPC codes is the difficulty to fully and accurately characterize the behavior of an application. In particular, it is essential to precisely pinpoint bottlenecks and their true causes. Additionally, providing an estimation of the possible gain obtained after fixing a particular bottleneck would surely allow for a more thorough choice of which optimizations to apply or avoid. In this paper, we present ONE View, a MAQAO module harnessing different techniques (sampling/tracing, static/dynamic analyses) to provide a comprehensive human-friendly view of performance issues and also guide the user’s optimization efforts on the most promising performance bottlenecks.
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References
Shende, S.S., Malony, A.D.: The tau parallel performance system. Int. J. High Perform. Comput. Appl
Hollingsworth, J., Buck, B.: An API for runtime code patching. J. High Perform. Comput. Appl. (2000)
INTEL VTune™Amplifier: https://software.intel.com/en-us/intel-vtune-amplifier-xe
Treibig, J., Hager, G., Wellein, G.: Likwid: a lightweight performance-oriented tool suite for x86 multicore environments. In: Parallel Processing Workshops (ICPPW) (2010)
Geimer, M., Wolf, F., Wylie, B.J., Ábrahám E., Becker, D., Mohr, B.: The scalasca performance toolset architecture. Concurrency and Computation: Practice and Experience
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. Concurrency and Computation: Practice and Experience
Knüpfer, A., Brunst, H., Doleschal, J., Jurenz, M., Lieber, M., Mickler, H., Müller, M.S., Nagel, W.E.: The vampir performance analysis tool- set. Tools for High Performance Computing
Intel Application Performance Snapshot: https://software.intel.com/sites/products/snapshots/application-snapshot/
ARM Forge: https://www.arm.com/products/development-tools/server-and-hpc/forge
INTEL Advisor: https://software.intel.com/en-us/advisor
Arm Forge: https://developer.arm.com/tools-and-software/server-and-hpc/arm-architecture-tools/arm-forge
Kim, J. et al.: QMCPACK: an open source ab initio quantum Monte Carlo package for the electronic structure of atoms, molecules and solids
Oseret, E., Charif-Rubial, A, Noudohouenou, J., Jalby, W., Lartigue, G.: CQA: a code quality analyzer tool at binary level. In: 21st International Conference on High Performance Computing, HiPC 2014, Goa, India, 17–20 Dec 2014
Fog, A.: https://www.agner.org/optimize/instruction_tables.pdf
Koliaï, S., Bendifallah, Z., Tribalat, M., Valensi, C., Acquaviva, J., Jalby, W.: Quantifying performance bottleneck cost through differential analysis. In: 27th International ACM Conference on International Conference on Supercomputing, ICS 2013, Eugene, Oregon, USA
Bendifallah, Z., Jalby, W., Noudohouenou, J., Oseret, E., Palomares, V., Charif-Rubial, A.: PAMDA: performance assessment using MAQAO toolset and differential analysis. In: 7th International Workshop on Parallel Tools for High Performance Computing. ZIH, Dresden, Germany (2013)
Acknowledgements
This work was funded by the CEA, GENCI, INTEL and UVSQ in the framework of the Exascale Computing Research collaboration, and also by the French Ministry of Industry in the framework of PERFCLOUD, ELCI and COLOC European projects.
The authors also wish to thank D. Kuck, V. Lee, J. Kim and D. Wong from INTEL for their help with the QMCPACK application.
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Jalby, W. et al. (2021). ONE View: A Fully Automatic Method for Aggregating Key Performance Metrics and Providing Users with a Synthetic View of HPC Applications. In: Mix, H., Niethammer, C., Zhou, H., Nagel, W.E., Resch, M.M. (eds) Tools for High Performance Computing 2018 / 2019. Springer, Cham. https://doi.org/10.1007/978-3-030-66057-4_12
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DOI: https://doi.org/10.1007/978-3-030-66057-4_12
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