Chen Zhang

Publication Activity (10 Years)

Years Active: 2013-2024
Publications (10 Years): 26

Top Topics

Top Venues

Publications

Chen Zhang, Rongchao Dong, Haojie Wang, Runxin Zhong, Jike Chen, Jidong Zhai
MAGPY: Compiling Eager Mode DNN Programs by Monitoring Execution States. USENIX ATC (2024)
Yuyang Jin, Haojie Wang, Runxin Zhong, Chen Zhang, Xia Liao, Feng Zhang, Jidong Zhai
Graph-Centric Performance Analysis for Large-Scale Parallel Applications. IEEE Trans. Parallel Distributed Syst. 35 (7) (2024)
Yue Guan, Yuxian Qiu, Jingwen Leng, Fan Yang, Shuo Yu, Yunxin Liu, Yu Feng, Yuhao Zhu, Lidong Zhou, Yun Liang, Chen Zhang, Chao Li, Minyi Guo
Amanda: Unified Instrumentation Framework for Deep Neural Networks. ASPLOS (1) (2024)
Cong Guo, Jiaming Tang, Weiming Hu, Jingwen Leng, Chen Zhang, Fan Yang, Yunxin Liu, Minyi Guo, Yuhao Zhu
OliVe: Accelerating Large Language Models via Hardware-friendly Outlier-Victim Pair Quantization. ISCA (2023)
Chen Zhang, Guangyu Sun, Zhenman Fang, Peipei Zhou, Jason Cong
Caffeine: Towards Uniformed Representation and Acceleration for Deep Convolutional Neural Networks. ACM TUR-C (2023)
Cong Guo, Chen Zhang, Jingwen Leng, Zihan Liu, Fan Yang, Yunxin Liu, Minyi Guo, Yuhao Zhu
ANT: Exploiting Adaptive Numerical Data Type for Low-bit Deep Neural Network Quantization. CoRR (2022)
Cong Guo, Yuxian Qiu, Jingwen Leng, Chen Zhang, Ying Cao, Quanlu Zhang, Yunxin Liu, Fan Yang, Minyi Guo
Nesting Forward Automatic Differentiation for Memory-Efficient Deep Neural Network Training. CoRR (2022)
Cong Guo, Chen Zhang, Jingwen Leng, Zihan Liu, Fan Yang, Yunxin Liu, Minyi Guo, Yuhao Zhu
ANT: Exploiting Adaptive Numerical Data Type for Low-bit Deep Neural Network Quantization. MICRO (2022)
Cong Guo, Yuxian Qiu, Jingwen Leng, Xiaotian Gao, Chen Zhang, Yunxin Liu, Fan Yang, Yuhao Zhu, Minyi Guo
SQuant: On-the-Fly Data-Free Quantization via Diagonal Hessian Approximation. ICLR (2022)
Yang Wang, Chen Zhang, Zhiqiang Xie, Cong Guo, Yunxin Liu, Jingwen Leng
Dual-side Sparse Tensor Core. ISCA (2021)
Yang Wang, Chen Zhang, Zhiqiang Xie, Cong Guo, Yunxin Liu, Jingwen Leng
Dual-side Sparse Tensor Core. CoRR (2021)
Yun Li, Chen Zhang, Shihao Han, Li Lyna Zhang, Baoqun Yin, Yunxin Liu, Mengwei Xu
Boosting Mobile CNN Inference through Semantic Memory. CoRR (2021)
Yun Li, Chen Zhang, Shihao Han, Li Lyna Zhang, Baoqun Yin, Yunxin Liu, Mengwei Xu
Boosting Mobile CNN Inference through Semantic Memory. ACM Multimedia (2021)
Yihuan Mao, Yujing Wang, Chufan Wu, Chen Zhang, Yang Wang, Quanlu Zhang, Yaming Yang, Yunhai Tong, Jing Bai
LadaBERT: Lightweight Adaptation of BERT through Hybrid Model Compression. COLING (2020)
Shuang Jiang, Zhiyao Ma, Xiao Zeng, Chenren Xu, Mi Zhang, Chen Zhang, Yunxin Liu
SCYLLA: QoE-aware Continuous Mobile Vision with FPGA-based Dynamic Deep Neural Network Reconfiguration. INFOCOM (2020)
Yihuan Mao, Yujing Wang, Chufan Wu, Chen Zhang, Yang Wang, Yaming Yang, Quanlu Zhang, Yunhai Tong, Jing Bai
LadaBERT: Lightweight Adaptation of BERT through Hybrid Model Compression. CoRR (2020)
Zhuliang Yao, Shijie Cao, Wencong Xiao, Chen Zhang, Lanshun Nie
Balanced Sparsity for Efficient DNN Inference on GPU. AAAI (2019)
Chen Zhang, Guangyu Sun, Zhenman Fang, Peipei Zhou, Peichen Pan, Jason Cong
Caffeine: Toward Uniformed Representation and Acceleration for Deep Convolutional Neural Networks. IEEE Trans. Comput. Aided Des. Integr. Circuits Syst. 38 (11) (2019)
Shang Wang, Chen Zhang, Yuanchao Shu, Yunxin Liu
Live Video Analytics with FPGA-based Smart Cameras. HotEdgeVideo@MOBICOM (2019)
Shijie Cao, Lingxiao Ma, Wencong Xiao, Chen Zhang, Yunxin Liu, Lintao Zhang, Lanshun Nie, Zhi Yang
SeerNet: Predicting Convolutional Neural Network Feature-Map Sparsity Through Low-Bit Quantization. CVPR (2019)
Shijie Cao, Chen Zhang, Zhuliang Yao, Wencong Xiao, Lanshun Nie, De-chen Zhan, Yunxin Liu, Ming Wu, Lintao Zhang
Efficient and Effective Sparse LSTM on FPGA with Bank-Balanced Sparsity. FPGA (2019)
Jason Cong, Zhenman Fang, Yuchen Hao, Peng Wei, Cody Hao Yu, Chen Zhang, Peipei Zhou
Best-Effort FPGA Programming: A Few Steps Can Go a Long Way. CoRR (2018)
Zhuliang Yao, Shijie Cao, Wencong Xiao, Chen Zhang, Lanshun Nie
Balanced Sparsity for Efficient DNN Inference on GPU. CoRR (2018)
Yijin Guan, Ningyi Xu, Chen Zhang, Zhihang Yuan, Jason Cong
Using Data Compression for Optimizing FPGA-Based Convolutional Neural Network Accelerators. APPT (2017)
Chen Zhang, Di Wu, Jiayu Sun, Guangyu Sun, Guojie Luo, Jason Cong
Energy-Efficient CNN Implementation on a Deeply Pipelined FPGA Cluster. ISLPED (2016)
Chen Zhang, Zhenman Fang, Peipei Zhou, Peichen Pan, Jason Cong
Caffeine: towards uniformed representation and acceleration for deep convolutional neural networks. ICCAD (2016)
Chen Zhang, Peng Li, Guangyu Sun, Yijin Guan, Bingjun Xiao, Jason Cong
Optimizing FPGA-based Accelerator Design for Deep Convolutional Neural Networks. FPGA (2015)
Peng Wang, Guangyu Sun, Song Jiang, Jian Ouyang, Shiding Lin, Chen Zhang, Jason Cong
An efficient design and implementation of LSM-tree based key-value store on open-channel SSD. EuroSys (2014)
Yuxin Wang, Peng Li, Peng Zhang, Chen Zhang, Jason Cong
Memory partitioning for multidimensional arrays in high-level synthesis. DAC (2013)
Yuxin Wang, Peng Li, Peng Zhang, Chen Zhang, Jason Cong
Automatic multidimensional memory partitioning for FPGA-based accelerators (abstract only). FPGA (2013)