Back to Search Start Over

HULK-V: a Heterogeneous Ultra-low-power Linux capable RISC-V SoC

Authors :
Valente, Luca
Tortorella, Yvan
Sinigaglia, Mattia
Tagliavini, Giuseppe
Capotondi, Alessandro
Benini, Luca
Rossi, Davide
Publication Year :
2022

Abstract

IoT applications span a wide range in performance and memory footprint, under tight cost and power constraints. High-end applications rely on power-hungry Systems-on-Chip (SoCs) featuring powerful processors, large LPDDR/DDR3/4/5 memories, and supporting full-fledged Operating Systems (OS). On the contrary, low-end applications typically rely on Ultra-Low-Power ucontrollers with a "close to metal" software environment and simple micro-kernel-based runtimes. Emerging applications and trends of IoT require the "best of both worlds": cheap and low-power SoC systems with a well-known and agile software environment based on full-fledged OS (e.g., Linux), coupled with extreme energy efficiency and parallel digital signal processing capabilities. We present HULK-V: an open-source Heterogeneous Linux-capable RISC-V-based SoC coupling a 64-bit RISC-V processor with an 8-core Programmable Multi-Core Accelerator (PMCA), delivering up to 13.8 GOps, up to 157 GOps/W and accelerating the execution of complex DSP and ML tasks by up to 112x over the host processor. HULK-V leverages a lightweight, fully digital memory hierarchy based on HyperRAM IoT DRAM that exposes up to 512 MB of DRAM memory to the host CPU. Featuring HyperRAMs, HULK-V doubles the energy efficiency without significant performance loss compared to featuring power-hungry LPDDR memories, requiring expensive and large mixed-signal PHYs. HULK-V, implemented in Global Foundries 22nm FDX technology, is a fully digital ultra-low-cost SoC running a 64-bit Linux software stack with OpenMP host-to-PMCA offload within a power envelope of just 250 mW.<br />Comment: This paper has been accepted as full paper at DATE23 https://www.date-conference.com/date-2023-accepted-papers#Regular-Papers

Details

Database :
arXiv
Publication Type :
Report
Accession number :
edsarx.2211.14944
Document Type :
Working Paper
Full Text :
https://doi.org/10.23919/DATE56975.2023.10137252