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

Matteo Fusi, Fabio Mazzocchetti, Albert Farres, Leonidas Kosmidis, Ramon Canal, Francisco J. Cazorla and Jaume Abella
Additional contact information
Matteo Fusi: Barcelona Supercomputing Center (BSC), Cr. Jordi Girona 31, 08034 Barcelona, Spain
Fabio Mazzocchetti: Barcelona Supercomputing Center (BSC), Cr. Jordi Girona 31, 08034 Barcelona, Spain
Albert Farres: Barcelona Supercomputing Center (BSC), Cr. Jordi Girona 31, 08034 Barcelona, Spain
Leonidas Kosmidis: Barcelona Supercomputing Center (BSC), Cr. Jordi Girona 31, 08034 Barcelona, Spain
Ramon Canal: Barcelona Supercomputing Center (BSC), Cr. Jordi Girona 31, 08034 Barcelona, Spain
Francisco J. Cazorla: Barcelona Supercomputing Center (BSC), Cr. Jordi Girona 31, 08034 Barcelona, Spain
Jaume Abella: Barcelona Supercomputing Center (BSC), Cr. Jordi Girona 31, 08034 Barcelona, Spain

Mathematics, 2020, vol. 8, issue 3, 1-21

Abstract: 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.

Keywords: WCET; probabilistic timing analysis; randomization; measurement-based; HPC applications (search for similar items in EconPapers)
JEL-codes: C (search for similar items in EconPapers)
Date: 2020
References: View references in EconPapers View complete reference list from CitEc
Citations:

Downloads: (external link)
https://www.mdpi.com/2227-7390/8/3/314/pdf (application/pdf)
https://www.mdpi.com/2227-7390/8/3/314/ (text/html)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:gam:jmathe:v:8:y:2020:i:3:p:314-:d:326736

Access Statistics for this article

Mathematics is currently edited by Ms. Emma He

More articles in Mathematics from MDPI
Bibliographic data for series maintained by MDPI Indexing Manager ().