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

Autor: Fabio Mazzocchetti, Albert Farrés, Ramon Canal, Leonidas Kosmidis, Jaume Abella, Francisco J. Cazorla, Matteo Fusi
Přispěvatelé: Universitat Politècnica de Catalunya. Departament d'Arquitectura de Computadors, Barcelona Supercomputing Center, Universitat Politècnica de Catalunya. VIRTUOS - Virtualisation and Operating Systems
Rok vydání: 2020
Předmět:
Computer science
Probabilistic timing analysis
General Mathematics
Distributed computing
HPC applications
Real-time data processing
hpc applications
Randomization
02 engineering and technology
randomization
Ordinadors immersos
Sistemes d'
wcet
Execution time
Embedded applications
Worst-case execution time
020204 information systems
0202 electrical engineering
electronic engineering
information engineering
Computer Science (miscellaneous)
Extreme value theory
Informàtica::Arquitectura de computadors [Àrees temàtiques de la UPC]
Engineering (miscellaneous)
Measurement-based
lcsh:Mathematics
Probabilistic logic
Inversion (meteorology)
lcsh:QA1-939
Supercomputer
Embedded computer systems
020202 computer hardware & architecture
High performance computing
probabilistic timing analysis
measurement-based
Càlcul intensiu (Informàtica)
Temps real (Informàtica)
WCET
Zdroj: Mathematics
Mathematics, Vol 8, Iss 3, p 314 (2020)
Volume 8
Issue 3
UPCommons. Portal del coneixement obert de la UPC
Universitat Politècnica de Catalunya (UPC)
ISSN: 2227-7390
DOI: 10.3390/math8030314
Popis: 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 This research was funded by the Horizon 2020 Framework Programme, grant number 801137, project RECIPE
Databáze: OpenAIRE
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