Consolidating Automotive Applications on Clustered Many-Core Platforms
2017 (English)In: SIGDA Student Research Forum at ASP-DAC ASP-DAC SRF'17, 2017Conference paper (Refereed)
The increased proliferation of automotive systems is leading to a paradigm shift in the automotive system architecture. Several, now distributed, applications will be consolidated on fewer, more powerful platforms, containing tens or hundreds of compute cores. Clustered many-core processors are a promising candidate for such systems, since each cluster provides enough computational power to host complex applications, while their intrinsic hardware architecture isolates different cluster from each other. The described PhD project works towards methods that allow the consolidation of automotive applications on clustered many-core architectures, while all their timing requirements are maintained. A contention-free execution framework is proposed that successfully diminishes the access-delays due to contention on shared resources within a cluster. In order to integrate complex end-to-end constraints on multi-rate chains, a method is proposed that allows the analysis of such chains and generates job-level dependencies. Such job-level dependencies can then be used to integrate the end-to-end constraints into the proposed execution framework. The applicability of the proposed methods to industrial problems is demonstrated via industrial case studies.
Place, publisher, year, edition, pages
Electrical Engineering, Electronic Engineering, Information Engineering
IdentifiersURN: urn:nbn:se:mdh:diva-34104OAI: oai:DiVA.org:mdh-34104DiVA: diva2:1056573
SIGDA Student Research Forum at ASP-DAC ASP-DAC SRF'17, 17-19 Jan 2017, Chiba, Japan
ProjectsPREMISE - Predictable Multicore Systems