EigenEdge: Real-Time Software Execution at the Edge with RISC-V and Hardware Accelerators

An important goal in the field of real-time computation at the edge is to achieve balance between low-latency requirements and strict low-power constraints. Into this equation, we would like to incorporate simple Application Programming Interfaces (APIs) for software development and utilization of open-source IPs that encourage reusability in the public domain. One big challenge is to bridge the gap between APIs that simplify the implementation of complex algorithms but mostly rely on CPU-centric computing paradigms, and lightweight heterogeneous hardware architectures designed for the constraints of real-time computation at the edge. We introduce a hardware/software co-design approach that combines software applications designed with Eigen, a powerful open-source C++ library that abstracts linear-algebra workloads, and real-time execution on heterogeneous System-on-Chip (SoC) architectures. We use ESP, an open-source SoC design platform that allows us to integrate the CVA6 RISC-V processor and custom hardware accelerators. With FPGA-based experiments, we show that our approach provides significant performance and energy efficiency gains, while maintaining the simplification provided by high-level software development.