activity
20182020
most citedFPSA: A Full System Stack Solution for Reconfigurable ReRAM-based NN Accelerator Architecture

61 citations · 84 across the 5 of their papers we have counts for

collaborators

5 papers

cs.DC2020★ 1 cited

AIPerf: Automated machine learning as an AI-HPC benchmark

Zhixiang Ren, Yongheng Liu, Tianhui Shi +6

The plethora of complex artificial intelligence (AI) algorithms and available high performance computing (HPC) power stimulates the expeditious development of AI components with he…

cs.NE2020★ 1 cited

Brain-inspired global-local learning incorporated with neuromorphic computing

Yujie Wu, Rong Zhao, Jun Zhu +11

Two main routes of learning methods exist at present including error-driven global learning and neuroscience-oriented local learning. Integrating them into one network may provide…

cs.ET2019★ 61 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.CR2019★ 16 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.NE2018★ 5 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…