Practical workloads on edge devices have a wide spectrum, from nW-scale, always-on sensor node to high performance deep-inference network on autonomous vehicle. To accommodate this, IME investigates heavily on silicon fabric and RISC-V based scalable SoC architecture.
IME’s Edge Computing group has developed a suite of design techniques to realize an ultra-low-power SoC. These SoC are critical for power constrained IoT applications such as machine health monitoring, neural signal processing and tire monitoring. We are also working on thousand-core Neuromorphic and Deep Learning hardware to enable new generation of pattern learning and recognition based real-world applications. These includes mobile or wearable devices, smart sensors, computers, robots and autonomous vehicles.