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Ahead-Of-Real-Time (ART): A Methodology for Static Reduction of Worst-Case Execution Time

Cattaneo, Daniele; Magnani, Gabriele; Cherubin, Stefano; Agosta, Giovanni

Authors

Daniele Cattaneo

Gabriele Magnani

Stefano Cherubin

Giovanni Agosta



Abstract

Precision tuning is an approximate computing technique for trading precision with lower execution time, and it has been increasingly important in embedded and high-performance computing applications. In particular, embedded applications benefit from lower precision in order to reduce or remove the dependency on computationally-expensive data types such as floating point. Amongst such applications, an important fraction are mission-critical tasks, such as control systems for vehicles or medical use-cases. In this context, the usefulness of precision tuning is limited by concerns about verificability of real-time and quality-of-service constraints. However, with the introduction of optimisations techniques based on integer linear programming and rigorous WCET (Worst-Case Execution Time) models, these constraints not only can be verified automatically, but it becomes possible to use precision tuning to automatically enforce these constraints even when not previously possible. In this work, we show how to combine precision tuning with WCET analysis to enforce a limit on the execution time by using a constraint-based code optimisation pass with a state-of-the-art precision tuning framework.

Presentation Conference Type Conference Paper (Published)
Conference Name NG-RES workshop
Start Date Jun 22, 2022
End Date Jun 22, 2022
Online Publication Date Jun 11, 2022
Publication Date Jun 11, 2022
Deposit Date Jun 11, 2022
Publicly Available Date Jun 14, 2022
Publisher Schloss Dagstuhl - Leibniz-Zentrum für Informatik
Volume 98
Pages 4:1-4:10
Series Title Open Access Series in Informatics (OASIcs)
Series ISSN 2190-6807
Book Title Third Workshop on Next Generation Real-Time Embedded Systems (NG-RES 2022)
ISBN 978-3-95977-221-1
DOI https://doi.org/10.4230/OASIcs.NG-RES.2022.4
Keywords Approximate Computing, Precision Tuning, Worst-Case Execution Time
Public URL http://researchrepository.napier.ac.uk/Output/2878253
Publisher URL https://drops.dagstuhl.de/opus/volltexte/2022/16112/

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