Abstract
As supercomputers are being built from an ever increasing number of processing elements, the effort required to achieve a substantial fraction of the system peak performance is continuously growing. Tools are needed that give developers and computing center staff holistic indicators about the resource consumption of applications and potential performance pitfalls at scale. To use the full potential of a supercomputer today, applications must incorporate multilevel parallelism (threading and message passing) and carefully orchestrate file I/O. As a consequence, performance tools must also be able to monitor these system components in an integrated way and at the full machine scales. We present ipm, a modularized monitoring approach for MPI, OpenMP, file I/O, and other event sources.
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Acknowledgements
This work was supported by the Bavaria-California Technology Center (BaCaTec) throughout the project “Performance and Workload Characterization for Multi-Core Supercomputers” and by the NSF under award OCI-0721397. This research was also supported by an allocation of advanced computing resources provided by the National Science Foundation. The computations were performed on Kraken (a Cray XT5) at the National Institute for Computational Sciences.
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Fürlinger, K., Wright, N.J., Skinner, D., Klausecker, C., Kranzlmüller, D. (2011). Effective Holistic Performance Measurement at Petascale Using IPM. In: Bischof, C., Hegering, HG., Nagel, W., Wittum, G. (eds) Competence in High Performance Computing 2010. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-24025-6_2
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DOI: https://doi.org/10.1007/978-3-642-24025-6_2
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