Achieving Predictable Multicore Execution of Automotive Applications Using the LET Paradigm

Abstract

Next generation automotive applications require support for safe, predictable, and deterministic execution. The Logical Execution Time (LET) model has been introduced to improve the predictability and correctness of time-critical applications. 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 paper, 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 platform show the feasibility of the proposed approach. The paper 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.