Challenges of Reliability Assessment and Enhancement in Autonomous Systems

09/01/2019 ∙ by Maksim Jenihhin, et al. ∙ 0

The gigantic complexity and heterogeneity of today's advanced cyber-physical systems and systems of systems is multiplied by the use of avant-garde computing architectures to employ artificial intelligence based autonomy in the system. Here, the overall system's reliability comes along with requirements for fail-safe, fail-operational modes specific to the target applications of the autonomous system and adopted HW architectures. The paper makes an overview of reliability challenges for intelligence implementation in autonomous systems enabled by HW backbones such as neuromorphic architectures, approximate computing architectures, GPUs, tensor processing units (TPUs) and SoC FPGAs.



There are no comments yet.


page 1

page 2

page 3

page 4

page 5

page 6

This week in AI

Get the week's most popular data science and artificial intelligence research sent straight to your inbox every Saturday.