CVA6 RISC-V Virtualization: Architecture, Microarchitecture, and Design Space Exploration

• Published in: IEEE transactions on very large scale integration (VLSI) systems 2023-11, Vol.31 (11), p.1-14
• Main Authors: Sa, Bruno, Valente, Luca, Martins, Jose, Rossi, Davide, Benini, Luca, Pinto, Sandro
• Format: Article
• Language: English
• Subjects: Cloud computing; Computer architecture; Configuration management; CVA6; Design space exploration; design space exploration (DSE); Embedded systems; Field programmable gate arrays; Hardware; Hypervisor; Memory management; memory management unit (MMU); Microarchitecture; MMU; Registers; RISC; RISC-V; Space exploration; System on chip; Technology assessment; TLB; translation lookaside buffer (TLB); Virtual machine monitors; Virtualization
• ISSN: 1063-8210; 1557-9999
• DOI: 10.1109/TVLSI.2023.3302837

Virtualization is a key technology used in a wide range of applications, from cloud computing to embedded systems. Over the last few years, mainstream computer architectures were extended with hardware virtualization support, giving rise to a set of virtualization technologies (e.g., Intel VT and Arm VE) that are now proliferating in modern processors and systems on chip (SoCs). In this article, we describe our work on hardware virtualization support in the RISC-V CVA6 core. Our contribution is multifold and encompasses architecture, microarchitecture, and design space exploration (DSE). In particular, we highlight the design of a set of microarchitectural enhancements i.e., G-stage translation lookaside buffer (GTLB) and second-level TLB (L2 TLB) to alleviate the virtualization performance overhead. We also perform a DSE and accompanying postlayout simulations (based on 22-nm FDX technology) to assess performance, power, and area (PPA). Furthermore, we map design variants on a field-programmable gate array (FPGA) platform (Genesys 2) to assess the functional performance-area tradeoff. Based on the DSE, we select an optimal design point for the CVA6 with hardware virtualization support. For this optimal hardware configuration, we collected functional performance results by running the MiBench benchmark on Linux atop Bao hypervisor for a single-core configuration. We observed a performance speedup of up to 16% (approximately 12.5% on average) compared with virtualization-aware nonoptimized design at the minimal cost of 0.78% in area and 0.33% in power. Finally, all works described in this article are publicly available and open-sourced for the community to further evaluate additional design configurations and software stacks.