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Static Hardware Partitioning on RISC-V - Shortcomings, Limitations, and Prospects

  • On embedded processors that are increasingly equipped with multiple CPU cores, static hardware partitioning is an established means of consolidating and isolating workloads onto single chips. This architectural pattern is suitable for mixed-criticality workloads that need to satisfy both, real-time and safety requirements, given suitable hardware properties. In this work, we focus on exploiting contemporary virtualisation mechanisms to achieve freedom from interference respectively isolation between workloads. Possibilities to achieve temporal and spatial isolation-while maintaining real-time capabilities-include statically partitioning resources, avoiding the sharing of devices, and ascertaining zero interventions of superordinate control structures. This eliminates overhead due to hardware partitioning, but implies certain hardware capabilities that are not yet fully implemented in contemporary standard systems. To address such hardware limitations, the customisable and configurable RISC-V instruction set architecture offers the possibility of swift, unrestricted modifications. We present findings on the current RISC-V specification and its implementations that necessitate interventions of superordinate control structures. We identify numerous issues adverse to implementing our goal of achieving zero interventions respectively zero overhead: On the design level, and especially with regards to handling interrupts. Based on micro-benchmark measurements, we discuss the implications of our findings, and argue how they can provide a basis for future extensions and improvements of the RISC-V architecture.

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Metadaten
Author:Ralf Ramsauer, Stefan Huber, Konrad Schwarz, Jan Kiszka, Wolfgang MauererORCiDGND
DOI:https://doi.org/10.48550/arXiv.2208.02703
ArXiv Id:http://arxiv.org/abs/arXiv:2208.02703v1
Document Type:Preprint
Language:English
Year of first Publication:2022
Release Date:2022/08/10
Konferenzangabe:IEEE 8th World Forum on the Internet of Things (WF-IoT), Nov. 03 - 18, 2022, Yokohama, Japan
Institutes:Fakultät Informatik und Mathematik
Fakultät Informatik und Mathematik / Labor für Digitalisierung (LFD)
research focus:Digitalisierung
Licence (German):Keine Lizenz - Es gilt das deutsche Urheberrecht: § 53 UrhG