학술논문

A 40-nm 646.6TOPS/W Sparsity-Scaling DNN Processor for On-Device Training
Document Type
Conference
Source
2022 IEEE Symposium on VLSI Technology and Circuits (VLSI Technology and Circuits) VLSI Technology and Circuits (VLSI Technology and Circuits), 2022 IEEE Symposium on. :40-41 Jun, 2022
Subject
Components, Circuits, Devices and Systems
Training
Neural networks
Data compression
Very large scale integration
Energy efficiency
Language
ISSN
2158-9682
Abstract
This work presents the first deep-neural-network (DNN) processor that supports sparsity-scaling training (SST). SST enables a sparsity of 92.4-to-97.8% with a