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Network Pruning for Bit-Serial Accelerators 期刊论文
IEEE TRANSACTIONS ON COMPUTER-AIDED DESIGN OF INTEGRATED CIRCUITS AND SYSTEMS, 2023, 卷号: 42, 期号: 5, 页码: 1597-1609
作者:  Zhao, Xiandong;  Wang, Ying;  Liu, Cheng;  Shi, Cong;  Tu, Kaijie;  Zhang, Lei
收藏  |  浏览/下载：7/0  |  提交时间：2023/12/04
AI accelerators  neural networks (NNs)  NN compression  
Variation Enhanced Attacks Against RRAM-Based Neuromorphic Computing System 期刊论文
IEEE TRANSACTIONS ON COMPUTER-AIDED DESIGN OF INTEGRATED CIRCUITS AND SYSTEMS, 2023, 卷号: 42, 期号: 5, 页码: 1588-1596
作者:  Lv, Hao;  Li, Bing;  Zhang, Lei;  Liu, Cheng;  Wang, Ying
收藏  |  浏览/下载：7/0  |  提交时间：2023/12/04
Security  Hardware  Neuromorphic engineering  Computational modeling  Circuit faults  Resistance  Immune system  Adversarial attack  fault injection attack  neuromorphic computing system (NCS)  processing in memory  reliability  resistive memory  
On-Line Fault Protection for ReRAM-Based Neural Networks 期刊论文
IEEE TRANSACTIONS ON COMPUTERS, 2023, 卷号: 72, 期号: 2, 页码: 423-437
作者:  Li, Wen;  Wang, Ying;  Liu, Cheng;  He, Yintao;  Liu, Lian;  Li, Huawei;  Li, Xiaowei
收藏  |  浏览/下载：14/0  |  提交时间：2023/07/12
Training  Fault detection  Computational modeling  Image edge detection  Memristors  Neural networks  Kernel  Deep neural network  hard fault  ReRAM  reliability  soft fault  
Dadu-SV: Accelerate Stereo Vision Processing on NPU 期刊论文
IEEE EMBEDDED SYSTEMS LETTERS, 2022, 卷号: 14, 期号: 4, 页码: 191-194
作者:  Min, Feng;  Wang, Ying;  Xu, Haobo;  Huang, Junpei;  Wang, Yujie;  Zou, Xingqi;  Lu, Meixuan;  Han, Yinhe
收藏  |  浏览/下载：14/0  |  提交时间：2023/07/12
Hardware acceleration  neural computing  neural processing unit (NPU)  semiglobal matching (SGM)  stereo vision  
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  
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)  
CAP: Communication-Aware Automated Parallelization for Deep Learning Inference on CMP Architectures 期刊论文
IEEE TRANSACTIONS ON COMPUTERS, 2022, 卷号: 71, 期号: 7, 页码: 1626-1639
作者:  Zou, Kaiwei;  Wang, Ying;  Cheng, Long;  Qu, Songyun;  Li, Huawei;  Li, Xiaowei
收藏  |  浏览/下载：29/0  |  提交时间：2022/12/07
Kernel  Computer architecture  Multicore processing  Deep learning  System-on-chip  Parallel processing  Real-time systems  Neural networks  parallel processing  real-time and embedded systems  single-chip multiprocessors  reinforcement learning  structured sparsity  
Toward Efficient Computing for Robotics: From a Circuit and System View 期刊论文
IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS II-EXPRESS BRIEFS, 2022, 卷号: 69, 期号: 7, 页码: 3051-3056
作者:  Xu, Haobo;  Yang, Yuxin;  Min, Feng;  Huang, Junpei;  Chen, Xiaoming;  Han, Yinhe;  Sun, Ninghui
收藏  |  浏览/下载：23/0  |  提交时间：2022/12/07
Robots  Kinematics  Planning  Field programmable gate arrays  Image edge detection  Estimation  Circuits and systems  Robotics  accelerator  hardware  kinematics  motion planning  perception  
Thread: Towards fine-grained precision reconfiguration in variable-precision neural network accelerator 期刊论文
IEICE ELECTRONICS EXPRESS, 2019, 卷号: 16, 期号: 14, 页码: 6
作者:  Zhang, Shichang;  Wang, Ying;  Chen, Xiaoming;  Han, Yinhe;  Wang, Yujie;  Li, Xiaowei
收藏  |  浏览/下载：77/0  |  提交时间：2019/12/10
DNN accelerator  variable bit-precision  bit-serial  bit-parallel  fine-grained precision