Summer School Course: Design and Analysis of Time-Critical Systems

Lecturer: Jan Reineke

Abstract

Cyber-physical systems (CPS) are characterized by the interaction of physical and software components. Sensors provide information about the state of the physical world and actuators enable software components to influence their physical environment. Physical components naturally evolve in real time following the rules of physics. As a consequence, to achieve objectives in the physical world, the software components of a CPS also need to perform their computations within limited amounts of real time.

Often CPS are safety-critical. Then, it is imperative to verify their functional correctness, including their timing behavior. This course conveys challenges and solutions in the design and analysis of time-critical systems:

- Analysis: How can the timing behavior of an application on a particular microarchitecture be safely bounded? We will first learn about timing-analysis techniques at the level of individual tasks; then we will see emerging compositional techniques to analyze a whole application's timing on a multi-core architecture, accounting for platform-related overheads due to shared resources such as caches and buses.

- Design: How should future multicore architectures be designed to enable precise and efficient timing analysis? We will discuss competing notions of timing predictability, including determinism and monotonicity. Then we will take a look at current academic and commercial projects, such as the PTARM and the Kalray MPPA-256 that aim to achieve predictability.

This course was held as part of the Thirteenth International Summer School on Advanced Computer Architecture and Compilation for High-Performance and Embedded Systems (ACACES 2017) in Fiuggi, Italy.

Schedule

Date Title
July 10, 2017 Introduction to Real-Time Systems
July 10, 2017 WCET Analysis: A Primer
July 11, 2017 Cache Analysis and Predictability
July 13, 2017 Response-Time Analysis with a Focus on Shared Resources
July 14, 2017 Timing Predictability and Analyzability + Case Studies: PTARM and Kalray MPPA-256