FPGA acceleration of continual learning at the edge

• Main Author: Piyasena Gane Pathirannahelage Duvindu
• Other Authors: Lam Siew Kei
• Format: Thesis-Master by Research
• Language: English
• Published: Nanyang Technological University 2021
• Subjects: Engineering::Computer science and engineering::Hardware; Engineering::Computer science and engineering::Computing methodologies::Artificial intelligence
• Online Access: https://hdl.handle.net/10356/153778
• Institution: Nanyang Technological University

Edge AI systems are increasingly being adopted in a wide range of application domains. These systems typically deploy Convolutional Neural Network (CNN) models on edge devices to perform inference, while relying on the cloud for model training. This is due to the high computational and memory demand...