SqueezeJet-3: An Accelerator Utilizing FPGA MPSoCs for Edge CNN Applications

Most FPGA-based Convolutional Neural Network (CNN) hardware accelerators target the datacenter rather than edge processing units. To further fill this gap, this work presents SqueezeJet-3 - a novel FPGA-based embedded system, consisting of software and hardware, for accelerating edge CNN inference. Even though SqueezeJet-3 is optimized for accelerating small ImageNet class CNNs, such as SqueezeNet v1.1, on low-end lowcost FPGA SoC devices, it can also be used for the acceleration of larger CNNs, such as the VGG16. Evaluation of our accelerator reveals better or comparable performance with that triggered by the current state-of-the-art similar tools and systems.