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Multi-Node Acceleration for Large-Scale GCNs 期刊论文
IEEE TRANSACTIONS ON COMPUTERS, 2022, 卷号: 71, 期号: 12, 页码: 3140-3152
作者:  Sun, Gongjian;  Yan, Mingyu;  Wang, Duo;  Li, Han;  Li, Wenming;  Ye, Xiaochun;  Fan, Dongrui;  Xie, Yuan
收藏  |  浏览/下载：26/0  |  提交时间：2023/07/12
Deep learning  graph neural network  hardware accelerator  multi-node system  communication optimization  
JBNN: A Hardware Design for Binarized Neural Networks Using Single-Flux-Quantum Circuits 期刊论文
IEEE TRANSACTIONS ON COMPUTERS, 2022, 卷号: 71, 期号: 12, 页码: 3203-3214
作者:  Fu, Rongliang;  Huang, Junying;  Wu, Haibin;  Ye, Xiaochun;  Fan, Dongrui;  Ho, Tsung-Yi
收藏  |  浏览/下载：15/0  |  提交时间：2023/07/12
Superconducting  single-flux-quantum  accelerator  binarized neural network  
Re-FeMAT: A Reconfigurable Multifunctional FeFET-Based Memory Architecture 期刊论文
IEEE TRANSACTIONS ON COMPUTER-AIDED DESIGN OF INTEGRATED CIRCUITS AND SYSTEMS, 2022, 卷号: 41, 期号: 11, 页码: 5071-5084
作者:  Zhang, Xiaoyu;  Liu, Rui;  Song, Tao;  Yang, Yuxin;  Han, Yinhe;  Chen, Xiaoming
收藏  |  浏览/下载：13/0  |  提交时间：2023/07/12
Convolutional neural network (CNN)  ferroelectric field-effect transistor (FeFET)  few-shot learning  in-memory processing  ternary content-addressable memory (TCAM)  
HyCA: A Hybrid Computing Architecture for Fault-Tolerant Deep Learning 期刊论文
IEEE TRANSACTIONS ON COMPUTER-AIDED DESIGN OF INTEGRATED CIRCUITS AND SYSTEMS, 2022, 卷号: 41, 期号: 10, 页码: 3400-3413
作者:  Liu, Cheng;  Chu, Cheng;  Xu, Dawen;  Wang, Ying;  Wang, Qianlong;  Li, Huawei;  Li, Xiaowei;  Cheng, Kwang-Ting
收藏  |  浏览/下载：25/0  |  提交时间：2022/12/07
Circuit faults  Computational modeling  Deep learning  Hardware  Redundancy  Neural networks  Computer architecture  Deep learning accelerator (DLA)  fault detection  fault tolerance  hybrid computing architecture (HyCA)  
FlexPDA: A Flexible Programming Framework for Deep Learning Accelerators 期刊论文
JOURNAL OF COMPUTER SCIENCE AND TECHNOLOGY, 2022, 卷号: 37, 期号: 5, 页码: 1200-1220
作者:  Liu, Lei;  Ma, Xiu;  Liu, Hua-Xiao;  Li, Guang-Li;  Liu, Lei
收藏  |  浏览/下载：14/0  |  提交时间：2023/07/12
deep learning accelerator  programming framework  domain-specific language  
An Efficient Deep Learning Accelerator Architecture for Compressed Video Analysis 期刊论文
IEEE TRANSACTIONS ON COMPUTER-AIDED DESIGN OF INTEGRATED CIRCUITS AND SYSTEMS, 2022, 卷号: 41, 期号: 9, 页码: 2808-2820
作者:  Wang, Yongchen;  Wang, Ying;  Li, Huawei;  Li, Xiaowei
收藏  |  浏览/下载：31/0  |  提交时间：2022/12/07
Streaming media  Neural networks  Image coding  Decoding  Metadata  Deep learning  Hardware  Neural network acceleration  specialized accelerator  video analysis  
Portrait: A holistic computation and bandwidth balanced performance evaluation model for heterogeneous systems 期刊论文
SUSTAINABLE COMPUTING-INFORMATICS & SYSTEMS, 2022, 卷号: 35, 页码: 8
作者:  Wu, Jingya;  Lu, Wenyan;  Yan, Guihai;  Li, Xiaowei
收藏  |  浏览/下载：27/0  |  提交时间：2022/12/07
Accelerators  Heterogeneous systems  Bandwidth contention  Hardware hazard  PCIe  
Hardware-software co-exploration with racetrack memory based in-memory computing for CNN inference in embedded systems 期刊论文
JOURNAL OF SYSTEMS ARCHITECTURE, 2022, 卷号: 128, 页码: 20
作者:  Choong, Benjamin Chen Ming;  Luo, Tao;  Liu, Cheng;  He, Bingsheng;  Zhang, Wei;  Zhou, Joey Tianyi
收藏  |  浏览/下载：19/0  |  提交时间：2022/12/07
Artificial intelligence  Hardware-software co-design  Deep learning  Embedded systems  Emerging memory  
A synergistic reinforcement learning-based framework design in driving automation 期刊论文
COMPUTERS & ELECTRICAL ENGINEERING, 2022, 卷号: 101, 页码: 15
作者:  Qi, Yuqiong;  Hu, Yang;  Wu, Haibin;  Li, Shen;  Ye, Xiaochun;  Fan, Dongrui
收藏  |  浏览/下载：27/0  |  提交时间：2022/12/07
Autonomous Driving  Heterogeneous Multicore AI Accelerator  Criteria  Reinforcement Learning  Scheduling  
Saving Energy of RRAM-Based Neural Accelerator Through State-Aware Computing 期刊论文
IEEE TRANSACTIONS ON COMPUTER-AIDED DESIGN OF INTEGRATED CIRCUITS AND SYSTEMS, 2022, 卷号: 41, 期号: 7, 页码: 2115-2127
作者:  He, Yintao;  Wang, Ying;  Li, Huawei;  Li, Xiaowei
收藏  |  浏览/下载：27/0  |  提交时间：2022/12/07
Computer architecture  Microprocessors  Resistance  Power demand  Training  Biological neural networks  Optimization  Low power (LP)  neural networks  processing-in-memory  resistive random-access memory (RRAM)