177 citations · 382 across the 18 of their papers we have counts for
9 papers · 1 filter
E-RNN: Design Optimization for Efficient Recurrent Neural Networks in FPGAs
Zhe Li, Caiwen Ding, Siyue Wang +8
Recurrent Neural Networks (RNNs) are becoming increasingly important for time series-related applications which require efficient and real-time implementations. The two major types…
Towards Budget-Driven Hardware Optimization for Deep Convolutional Neural Networks using Stochastic Computing
Zhe Li, Ji Li, Ao Ren +5
Recently, Deep Convolutional Neural Network (DCNN) has achieved tremendous success in many machine learning applications. Nevertheless, the deep structure has brought significant i…
Learning Topics using Semantic Locality
Ziyi Zhao, Krittaphat Pugdeethosapol, Sheng Lin +4
The topic modeling discovers the latent topic probability of the given text documents. To generate the more meaningful topic that better represents the given document, we proposed…
Efficient Recurrent Neural Networks using Structured Matrices in FPGAs
Zhe Li, Shuo Wang, Caiwen Ding +3
Recurrent Neural Networks (RNNs) are becoming increasingly important for time series-related applications which require efficient and real-time implementations. The recent pruning…
Image Dataset for Visual Objects Classification in 3D Printing
Hongjia Li, Xiaolong Ma, Aditya Singh Rathore +5
The rapid development in additive manufacturing (AM), also known as 3D printing, has brought about potential risk and security issues along with significant benefits. In order to e…
C-LSTM: Enabling Efficient LSTM using Structured Compression Techniques on FPGAs
Shuo Wang, Zhe Li, Caiwen Ding +4
Recently, significant accuracy improvement has been achieved for acoustic recognition systems by increasing the model size of Long Short-Term Memory (LSTM) networks. Unfortunately,…
C3PO: Database and Benchmark for Early-stage Malicious Activity Detection in 3D Printing
Zhe Li, Xiaolong Ma, Hongjia Li +5
Increasing malicious users have sought practices to leverage 3D printing technology to produce unlawful tools in criminal activities. Current regulations are inadequate to deal wit…
Towards Ultra-High Performance and Energy Efficiency of Deep Learning Systems: An Algorithm-Hardware Co-Optimization Framework
Yanzhi Wang, Caiwen Ding, Zhe Li +8
Hardware accelerations of deep learning systems have been extensively investigated in industry and academia. The aim of this paper is to achieve ultra-high energy efficiency and pe…
An Area and Energy Efficient Design of Domain-Wall Memory-Based Deep Convolutional Neural Networks using Stochastic Computing
Xiaolong Ma, Yipeng Zhang, Geng Yuan +5
With recent trend of wearable devices and Internet of Things (IoTs), it becomes attractive to develop hardware-based deep convolutional neural networks (DCNNs) for embedded applica…