most citedFPSA: A Full System Stack Solution for Reconfigurable ReRAM-based NN Accelerator Architecture

61 citations · 103 across the 4 of their papers we have counts for

collaborators

6 papers

cs.CR2019

Neural Network Model Extraction Attacks in Edge Devices by Hearing Architectural Hints

Xing Hu, Ling Liang, Lei Deng +7

As neural networks continue their reach into nearly every aspect of software operations, the details of those networks become an increasingly sensitive subject. Even those that dep…

cs.ET201961 cited

FPSA: A Full System Stack Solution for Reconfigurable ReRAM-based NN Accelerator Architecture

Yu Ji, Youyang Zhang, Xinfeng Xie +5

Neural Network (NN) accelerators with emerging ReRAM (resistive random access memory) technologies have been investigated as one of the promising solutions to address the \textit{m…

cs.NE201921 cited

QGAN: Quantized Generative Adversarial Networks

Peiqi Wang, Dongsheng Wang, Yu Ji +5

The intensive computation and memory requirements of generative adversarial neural networks (GANs) hinder its real-world deployment on edge devices such as smartphones. Despite the…

cs.CR201916 cited

Programmable Neural Network Trojan for Pre-Trained Feature Extractor

Yu Ji, Zixin Liu, Xing Hu +2

Neural network (NN) trojaning attack is an emerging and important attack model that can broadly damage the system deployed with NN models. Existing studies have explored the outsou…

cs.CV2018

Crossbar-aware neural network pruning

Ling Liang, Lei Deng, Yueling Zeng +5

Crossbar architecture based devices have been widely adopted in neural network accelerators by taking advantage of the high efficiency on vector-matrix multiplication (VMM) operati…

cs.NE20185 cited

Bridging the Gap Between Neural Networks and Neuromorphic Hardware with A Neural Network Compiler

Yu Ji, YouHui Zhang, WenGuang Chen +1

Different from developing neural networks (NNs) for general-purpose processors, the development for NN chips usually faces with some hardware-specific restrictions, such as limited…