Presentation title

Achieving Predictable Multicore Execution of Automotive Applications Using the LET Paradigm

Authors

Alessandro Biondi and Marco Di Natale

Institution(s)

Scuola Superiore Sant'Anna, Pisa, Italy

Presentation type

Technical presentation

Abstract

The introduction of safety-critical functions in automotive systems, together with the advent of multicore platforms, brings the need to rethink the development and execution paradigms for embedded functionality. Developers need high levels of predictability, testability, and ultimately determinism in the execution of their code. The Logical Execution Time (LET) model has been introduced to improve the predictability and correctness of time-critical applications. In essence, the LET delays the program output of a task (or any function executed inside the task) at the end of the task period, trading delay for output jitter. A key observation is that the LET execution model not only avoids output jitter but has the additional benefit of scheduling precisely in time the accesses to the communications variables. This can be extremely valuable in the multicore execution of tasks communicating remotely. Indeed, the advent of multicore architectures, together with the need to ensure time predictability despite the complex memory hierarchy and the hardware resources shared by the cores, is an additional motivation for the use of the LET paradigm in conjunction with a suitable scheduling and memory access model. In this presentation, we show how an implementation of the LET model on actual multicore platforms for automotive systems brings the potential to improve time determinism at the price of a modicum run-time overhead. Multiple implementation options are discussed using the automotive AUTOSAR model and operating system standard, and a realistic application defined by Bosch for the 2017 WATERS challenge. Experimental data of executions on the Infineon Aurix TC275 platform show the feasibility of the proposed approach. The presentation also provides a discussion on further implementation optimizations and other issues related to the general problem of memory-aware analysis of automotive applications on multicores.

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Additional material

• Presentation slides: [pdf]

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