activity
20222024
most citedAuto-ViT-Acc: An FPGA-Aware Automatic Acceleration Framework for Vision Transformer with Mixed-Scheme Quantization

6 citations · 6 across the 5 of their papers we have counts for

collaborators

5 papers

cs.CV2024

AyE-Edge: Automated Deployment Space Search Empowering Accuracy yet Efficient Real-Time Object Detection on the Edge

Chao Wu, Yifan Gong, Liangkai Liu +7

Object detection on the edge (Edge-OD) is in growing demand thanks to its ever-broad application prospects. However, the development of this field is rigorously restricted by the d…

cs.ET2024

SuperFlow: A Fully-Customized RTL-to-GDS Design Automation Flow for Adiabatic Quantum-Flux-Parametron Superconducting Circuits

Yanyue Xie, Peiyan Dong, Geng Yuan +10

Superconducting circuits, like Adiabatic Quantum-Flux-Parametron (AQFP), offer exceptional energy efficiency but face challenges in physical design due to sophisticated spacing and…

cs.ET2023

SupeRBNN: Randomized Binary Neural Network Using Adiabatic Superconductor Josephson Devices

Zhengang Li, Geng Yuan, Tomoharu Yamauchi +8

Adiabatic Quantum-Flux-Parametron (AQFP) is a superconducting logic with extremely high energy efficiency. By employing the distinct polarity of current to denote logic `0' and `1'…

cs.ET2023

A Life-Cycle Energy and Inventory Analysis of Adiabatic Quantum-Flux-Parametron Circuits

Masoud Zabihi, Yanyue Xie, Zhengang Li +5

The production process of superconductive integrated circuits is complex and consumes significant amounts of resources and energy. Therefore, it is crucial to evaluate the environm…

cs.CV20226 cited

Auto-ViT-Acc: An FPGA-Aware Automatic Acceleration Framework for Vision Transformer with Mixed-Scheme Quantization

Zhengang Li, Mengshu Sun, Alec Lu +9

Vision transformers (ViTs) are emerging with significantly improved accuracy in computer vision tasks. However, their complex architecture and enormous computation/storage demand i…