Performance Analysis of KVM Hypervisor Using a Self-Driving Developer Kit

Virtualization plays an increasingly important role in safety-critical embedded systems like modern vehicles due to its numerous advantages like cost reduction, better scalability, or easier safety verification. These advantages come at the cost of additional performance overhead. While performance...

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Bibliographic Details
Published inIECON 2022 – 48th Annual Conference of the IEEE Industrial Electronics Society pp. 1 - 7
Main Authors Muller, Thilo, Askaripoor, Hadi, Knoll, Alois
Format Conference Proceeding
LanguageEnglish
Published IEEE 17.10.2022
Subjects
Autonomous Driving
Benchmarking
Costs
Embedded systems
Hypervisor
Industrial electronics
KVM
Nvidia Drive AGX
Performance evaluation
Safety
Safety-critical Systems
Scalability
Virtual machine monitors
Virtualization
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Summary:Virtualization plays an increasingly important role in safety-critical embedded systems like modern vehicles due to its numerous advantages like cost reduction, better scalability, or easier safety verification. These advantages come at the cost of additional performance overhead. While performance evaluation of virtualization solutions for server applications has been the subject of research for a long time, it is still not adequately investigated for embedded use cases. We present the first work to analyze the performance of KVM, an open-source hypervisor, on an Nvidia Drive AGX, a developer kit for self-driving vehicles. Experimental measurements show that the computational overhead restricts the number of partitions. Also, poor memory and file I/O performance suggest that KVM is not usable for practical applications with the Nvidia Drive AGX.
ISSN:2577-1647
DOI:10.1109/IECON49645.2022.9968908