Consolidating Automotive Real-Time Applications on Many-Core Platforms

University dissertation from Västerås : Malardalen University

Abstract: Automotive systems have transitioned from basic transportation utilities to sophisticated systems. The rapid increase in functionality comes along with a steep increase in software complexity. This manifests itself in a surge of the number of functionalities as well as the complexity of existing functions. To cope with this transition, current trends shift away from today’s distributed architectures towards integrated architectures, where previously distributed functionality is consolidated on fewer, more powerful, computers. This can ease the integration process, reduce the hardware complexity, and ultimately save costs.One promising hardware platform for these powerful embedded computers is the many-core processor. A many-core processor hosts a vast number of compute cores, that are partitioned on tiles which are connected by a Network-on-Chip. These natural partitions can provide exclusive execution spaces for different applications, since most resources are not shared among them. Hence, natural building blocks towards temporally and spatially separated execution spaces exist as a result of the hardware architecture.Additionally to the traditional task local deadlines, automotive applications are often subject to timing constraints on the data propagation through a chain of semantically related tasks. Such requirements pose challenges to the system designer as they are only able to verify them after the system synthesis (i.e. very late in the design process).In this thesis, we present methods that transform complex timing constraints on the data propagation delay to precedence constraints between individual jobs. An execution framework for the cluster of the many-core is proposed that allows access to cluster external memory while it avoids contention on shared resources by design. A partitioning and configuration of the Network-on-Chip provides isolation between the different applications and reduces the access time from the clusters to external memory. Moreover, methods that facilitate the verification of data propagation delays in each development step are provided.