RTL-Arrow: Hardware-to-Cloud Bridge
For hardware security researchers, it addresses the bottleneck of manually parsing execution traces, but the solution is incremental and domain-specific.
The paper proposes RTL-Arrow, a framework that converts hardware simulation outputs (value change dumps) into cloud-ready dataframes to streamline hardware-software verification and reduce development time for security researchers.
Hardware Security at Willamette is a Willamette University affiliated research group studying the hardware-software interface of security critical services. Within our program, we noticed many researchers spent considerable development time learning to understand and manually parse traces-of-execution of hardware designs which are used to identifying whether vulnerabilities or weaknesses arise at the hardware, software, or interface level. We propose the "RTL-Arrow" framework, a framework to compile performant binaries which bridge the hardware/data divide. We translate the outputs of simulated hardware execution, as "value change dumps" into modern data science workflows as cloud-ready "dataframes", to standardize program verification across the hardware and software levels. We describe our approach, its benefits, and lessons learned from the process of packaging and distributing these libraries for our security research program.