Performance Analysis of KVM Hypervisor Using a Self-Driving Developer Kit | IEEE Conference Publication | IEEE Xplore

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


Abstract:

Virtualization plays an increasingly important role in safety-critical embedded systems like modern vehicles due to its numerous advantages like cost reduction, better sc...Show More

Abstract:

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.
Date of Conference: 17-20 October 2022
Date Added to IEEE Xplore: 09 December 2022
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Conference Location: Brussels, Belgium

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