Machine Learning for Timing Analysis: the good, the bad and the ugly<\/strong><\/p>\n\n\n\nThe microarchitecture of processors is becoming increasingly complex and less documented, making the design of timing models for WCET calculation increasingly complicated, if not impossible. We have recently experimented with the use of machine learning techniques (ML) to predict the WCET of basic blocks. Predicted WCETs can then be integrated into static WCET calculation tools, resulting in a hybrid WCET calculation. In this keynote, I will present our experience using ML for WCET calculation, across a range of architectures, from very simple ones (MSP430, Cortex M4) to more complex architectures. Rather than presenting only what worked, which fortunately allowed us to publish, I will also discuss in this keynote the bad, and even very bad, surprises encountered during the process, and how we overcame (most of) them.<\/p>\n\n\n\n
Program:<\/p>\n\n\n\n
13:30:<\/strong> Keynote by Pr. Isabelle Puaut: Machine Learning for Timing Analysis: the good, the bad and the ugly<\/strong><\/p>\n\n\n\n14:15 – 15:05:<\/strong> Session 1: Regular papers<\/strong><\/p>\n\n\n\nThe Platin Multi-Target Worst-Case Analysis Tool<\/strong>. Emad Jacob Maroun, Eva Dengler, Christian Dietrich, Stefan Hepp, Henriette Herzog, Benedikt Huber, Jens Knoop, Daniel Wiltsche-Prokesch, Peter Puschner, Phillip Raffeck, Martin Schoeberl, Simon Schuster, Peter W\u00e4gemann<\/p>\n\n\n\nWORTEX: Worst-Case Execution Time and Energy Estimation in Low-Power Microprocessors Using Explainable ML<\/strong>. Hugo Reymond, Abderaouf Nassim Amalou, Isabelle Puaut<\/p>\n\n\n\n15:05 – 15:30:<\/strong> Break<\/p>\n\n\n\n15:30 – 17:10:<\/strong> Session 2: Invited papers<\/strong><\/p>\n\n\n\nAssessing Unchecked Factors for Certification: An Experimental approach for GPU Cache Parameters<\/strong>. C\u00e9dric Cazanove, Benjamin Lesage, Fr\u00e9d\u00e9ric Boniol, J\u00e9r\u00f4me Ermont<\/p>\n\n\n\nWorst-Case Execution Time Analysis of Lingua Franca Applications<\/strong>. Martin Schoeberl, Ehsan Khodadad, Shaokai Lin, Emad Jacob Maroun, Luca Pezzarossa, Edward A. Lee<\/p>\n\n\n\nOn the Granularity of Bandwidth Regulation in FPGA-based Heterogeneous Systems on Chip<\/strong>. Gianluca Brilli, Giacomo Valente, Alessandro Capotondi, Tania Di Mascio, Andrea Marongiu<\/p>\n\n\n\nStatistical, Stochastic or Probabilistic (Worst-Case Execution) Execution Time? \u2013 What Impact on the Multicore Composability<\/strong>. Liliana Cucu-Grosjean<\/p>\n","protected":false},"excerpt":{"rendered":"22nd International Workshop onWorst-Case Execution Time Analysis Home | Program | Call for papers | Submission instructions | Organizers The proceedings are available at: https:\/\/www.dagstuhl.de\/dagpub\/978-3-95977-346-1 Keynote by Pr. Isabelle Puaut (Univ. Rennes): Machine Learning for Timing Analysis: the good, the bad and the ugly The microarchitecture of processors is becoming increasingly complex…<\/p>\n
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