Collaborators : Cadence Design Systems
Custom hardware-based neural network accelerators have been known to surpass their general-purpose processor equivalents in terms of both throughput and energy-efficiency. On-chip inference on edge devices for IOT and other AI applications has also gained traction. In this project, we are looking into application-tailored accelerators co-designed with efficient network training models and their efficient integration on edge-devices.