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Article

On the Use of Probabilistic Worst-Case Execution Time Estimation for Parallel Applications in High Performance Systems

1
Barcelona Supercomputing Center (BSC), Cr. Jordi Girona 31, 08034 Barcelona, Spain
2
Department of Computer Architecture, Facultat d’Informàtica de Barcelona, Universitat Politècnica de Catalunya, Campus Nord UPC, Cr. Jordi Girona 1-3, 08034 Barcelona, Spain
*
Authors to whom correspondence should be addressed.
Mathematics 2020, 8(3), 314; https://doi.org/10.3390/math8030314
Received: 7 January 2020 / Revised: 21 February 2020 / Accepted: 25 February 2020 / Published: 1 March 2020
(This article belongs to the Special Issue Supercomputing and Mathematics)
Some high performance computing (HPC) applications exhibit increasing real-time requirements, which call for effective means to predict their high execution times distribution. This is a new challenge for HPC applications but a well-known problem for real-time embedded applications where solutions already exist, although they target low-performance systems running single-threaded applications. In this paper, we show how some performance validation and measurement-based practices for real-time execution time prediction can be leveraged in the context of HPC applications on high-performance platforms, thus enabling reliable means to obtain real-time guarantees for those applications. In particular, the proposed methodology uses coordinately techniques that randomly explore potential timing behavior of the application together with Extreme Value Theory (EVT) to predict rare (and high) execution times to, eventually, derive probabilistic Worst-Case Execution Time (pWCET) curves. We demonstrate the effectiveness of this approach for an acoustic wave inversion application used for geophysical exploration. View Full-Text
Keywords: WCET; probabilistic timing analysis; randomization; measurement-based; HPC applications WCET; probabilistic timing analysis; randomization; measurement-based; HPC applications
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MDPI and ACS Style

Fusi, M.; Mazzocchetti, F.; Farres, A.; Kosmidis, L.; Canal, R.; Cazorla, F.J.; Abella, J. On the Use of Probabilistic Worst-Case Execution Time Estimation for Parallel Applications in High Performance Systems. Mathematics 2020, 8, 314. https://doi.org/10.3390/math8030314

AMA Style

Fusi M, Mazzocchetti F, Farres A, Kosmidis L, Canal R, Cazorla FJ, Abella J. On the Use of Probabilistic Worst-Case Execution Time Estimation for Parallel Applications in High Performance Systems. Mathematics. 2020; 8(3):314. https://doi.org/10.3390/math8030314

Chicago/Turabian Style

Fusi, Matteo, Fabio Mazzocchetti, Albert Farres, Leonidas Kosmidis, Ramon Canal, Francisco J. Cazorla, and Jaume Abella. 2020. "On the Use of Probabilistic Worst-Case Execution Time Estimation for Parallel Applications in High Performance Systems" Mathematics 8, no. 3: 314. https://doi.org/10.3390/math8030314

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