activity
20182023
most citedAchieving Super-Linear Speedup across Multi-FPGA for Real-Time DNN Inference

87 citations · 219 across the 19 of their papers we have counts for

collaborators
Showing 2020Show all

6 papers · 1 filter

cs.LG2020★ 3 cited

Personalized Deep Learning for Ventricular Arrhythmias Detection on Medical IoT Systems

Zhenge Jia, Zhepeng Wang, Feng Hong +3

Life-threatening ventricular arrhythmias (VA) are the leading cause of sudden cardiac death (SCD), which is the most significant cause of natural death in the US. The implantable c…

eess.IV2020★ 1 cited

Towards Cardiac Intervention Assistance: Hardware-aware Neural Architecture Exploration for Real-Time 3D Cardiac Cine MRI Segmentation

Dewen Zeng, Weiwen Jiang, Tianchen Wang +6

Real-time cardiac magnetic resonance imaging (MRI) plays an increasingly important role in guiding various cardiac interventions. In order to provide better visual assistance, the…

cs.LG2020★ 9 cited

Standing on the Shoulders of Giants: Hardware and Neural Architecture Co-Search with Hot Start

Weiwen Jiang, Lei Yang, Sakyasingha Dasgupta +2

Hardware and neural architecture co-search that automatically generates Artificial Intelligence (AI) solutions from a given dataset is promising to promote AI democratization; howe…

cs.LG2020★ 3 cited

Enabling On-Device CNN Training by Self-Supervised Instance Filtering and Error Map Pruning

Yawen Wu, Zhepeng Wang, Yiyu Shi +1

This work aims to enable on-device training of convolutional neural networks (CNNs) by reducing the computation cost at training time. CNN models are usually trained on high-perfor…

cs.LG2020★ 7 cited

Intermittent Inference with Nonuniformly Compressed Multi-Exit Neural Network for Energy Harvesting Powered Devices

Yawen Wu, Zhepeng Wang, Zhenge Jia +2

This work aims to enable persistent, event-driven sensing and decision capabilities for energy-harvesting (EH)-powered devices by deploying lightweight DNNs onto EH-powered devices…

cs.AR2020

Low Overhead Online Data Flow Tracking for Intermittently Powered Non-volatile FPGAs

Xinyi Zhang, Clay Patterson, Yongpan Liu +3

Energy harvesting is an attractive way to power future IoT devices since it can eliminate the need for battery or power cables. However, harvested energy is intrinsically unstable.…