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ORCIDZhuoran Song
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2020 – today
- 2024
[c31]Zhuoran Song
, Chunyu Qi, Fangxin Liu, Naifeng Jing, Xiaoyao Liang:
CMC: Video Transformer Acceleration via CODEC Assisted Matrix Condensing. ASPLOS (2) 2024: 201-215- [c30]Fangxin Liu, Ning Yang, Zhiyan Song, Zongwu Wang, Haomin Li, Shiyuan Huang, Zhuoran Song, Songwen Pei, Li Jiang:
INSPIRE: Accelerating Deep Neural Networks via Hardware-friendly Index-Pair Encoding. DAC 2024: 10:1-10:6 - [c29]Xueyuan Liu, Zhuoran Song, Hao Chen, Xing Li, Xiaoyao Liang:
MoC: A Morton-Code-Based Fine-Grained Quantization for Accelerating Point Cloud Neural Networks. DAC 2024: 42:1-42:6 - [c28]Ning Yang, Fangxin Liu, Zongwu Wang, Haomin Li, Zhuoran Song, Songwen Pei, Li Jiang:
EOS: An Energy-Oriented Attack Framework for Spiking Neural Networks. DAC 2024: 58:1-58:6 - [c27]Zhuoran Song, Chunyu Qi, Yuanzheng Yao, Peng Zhou, Yanyi Zi, Nan Wang, Xiaoyao Liang:
TSAcc: An Efficient \underline{T}empo-\underline{S}patial Similarity Aware \underline{Acc}elerator for Attention Acceleration. DAC 2024: 68:1-68:6 - [c26]Xuhang Wang, Zhuoran Song, Xiaoyao Liang:
InterArch: Video Transformer Acceleration via Inter-Feature Deduplication with Cube-based Dataflow. DAC 2024: 99:1-99:6 - [c25]Xueyuan Liu, Zhuoran Song, Guohao Dai, Gang Li, Can Xiao, Yan Xiang, Dehui Kong, Ke Xu, Xiaoyao Liang:
FusionArch: A Fusion-Based Accelerator for Point-Based Point Cloud Neural Networks. DATE 2024: 1-6 - [c24]Xueyuan Liu, Zhuoran Song, Xiang Liao, Xing Li, Tao Yang, Fangxin Liu, Xiaoyao Liang:
Sava: A Spatial- and Value-Aware Accelerator for Point Cloud Transformer. DATE 2024: 1-6 - [c23]Xuan Zhang, Zhuoran Song, Xing Li, Zhezhi He, Naifeng Jing, Li Jiang, Xiaoyao Liang:
Watt: A Write-Optimized RRAM-Based Accelerator for Attention. Euro-Par (2) 2024: 107-120 - [c22]Fangxin Liu, Ning Yang, Haomin Li, Zongwu Wang, Zhuoran Song, Songwen Pei, Li Jiang:
SPARK: Scalable and Precision-Aware Acceleration of Neural Networks via Efficient Encoding. HPCA 2024: 1029-1042 - 2023
- [j8]Zhuoran Song, Jianfeng Li, Tao Jiang, Sichen Lu:
Distribution Network Planning Method considering the Coupling of Transportation Network and Distribution Network. Scalable Comput. Pract. Exp. 24(3): 429-438 (2023) - [j7]Zhuoran Song, Jianfeng Li, Tao Jiang, Sichen Lu:
Impact of Photovoltaic Systems on Distribution Networks with Advances of Cloud, Grid and Cluster Computing. Scalable Comput. Pract. Exp. 24(4): 1145-1156 (2023) - [j6]Tao Yang, Dongyue Li, Fei Ma, Zhuoran Song, Yilong Zhao, Jiaxi Zhang, Fangxin Liu, Li Jiang:
PASGCN: An ReRAM-Based PIM Design for GCN With Adaptively Sparsified Graphs. IEEE Trans. Comput. Aided Des. Integr. Circuits Syst. 42(1): 150-163 (2023) - [j5]Zhuoran Song, Heng Lu, Li Jiang, Naifeng Jing, Xiaoyao Liang:
Real-Time Video Recognition via Decoder-Assisted Neural Network Acceleration Framework. IEEE Trans. Comput. Aided Des. Integr. Circuits Syst. 42(7): 2238-2251 (2023) - [j4]Zhuoran Song, Naifeng Jing, Xiaoyao Liang:
E2-VOR: An End-to-End En/Decoder Architecture for Efficient Video Object Recognition. ACM Trans. Design Autom. Electr. Syst. 28(1): 10:1-10:21 (2023) - [j3]Zhuoran Song, Wanzhen Liu, Tao Yang, Fangxin Liu, Naifeng Jing, Xiaoyao Liang:
A Point Cloud Video Recognition Acceleration Framework Based on Tempo-Spatial Information. IEEE Trans. Parallel Distributed Syst. 34(12): 3224-3237 (2023) - [c21]Zhuoran Song, Naifeng Jing, Xiaoyao Liang:
PRADA: Point Cloud Recognition Acceleration via Dynamic Approximation. ACM TUR-C 2023: 49-50 - [c20]Xiaolong Lin, Gang Li, Zizhao Liu, Yadong Liu, Fan Zhang, Zhuoran Song, Naifeng Jing, Xiaoyao Liang:
AdaS: A Fast and Energy-Efficient CNN Accelerator Exploiting Bit-Sparsity. DAC 2023: 1-6 - [c19]Zhuoran Song, Heng Lu, Gang Li, Li Jiang, Naifeng Jing, Xiaoyao Liang:
PRADA: Point Cloud Recognition Acceleration via Dynamic Approximation. DATE 2023: 1-6 - [c18]Xuhang Wang, Zhuoran Song, Xiaoyao Liang:
RealArch: A Real-Time Scheduler for Mapping Multi-Tenant DNNs on Multi-Core Accelerators. ICCD 2023: 158-165 - [c17]Xuan Zhang, Zhuoran Song, Xing Li, Zhezhi He, Li Jiang, Naifeng Jing, Xiaoyao Liang:
HyAcc: A Hybrid CAM-MAC RRAM-based Accelerator for Recommendation Model. ICCD 2023: 375-382 - [c16]Chunyu Qi, Zilong Li, Zhuoran Song, Xiaoyao Liang:
ViTframe: Vision Transformer Acceleration via Informative Frame Selection for Video Recognition. ICCD 2023: 383-390 - [c15]Xuhang Wang, Zhuoran Song, Qiyue Huang, Xiaoyao Liang:
DEQ: Dynamic Element-wise Quantization for Efficient Attention Architecture. ICCD 2023: 623-630 - 2022
- [c14]Zhuoran Song, Zhongkai Yu, Naifeng Jing, Xiaoyao Liang:
E2SR: an end-to-end video CODEC assisted system for super resolution acceleration. DAC 2022: 229-234 - [c13]Tao Yang, Dongyue Li, Zhuoran Song, Yilong Zhao, Fangxin Liu, Zongwu Wang, Zhezhi He, Li Jiang:
DTQAtten: Leveraging Dynamic Token-based Quantization for Efficient Attention Architecture. DATE 2022: 700-705 - [c12]Xing Li, Rachata Ausavarungnirun, Xiao Liu, Xueyuan Liu, Xuan Zhang, Heng Lu, Zhuoran Song, Naifeng Jing, Xiaoyao Liang:
Gzippo: Highly-Compact Processing-in-Memory Graph Accelerator Alleviating Sparsity and Redundancy. ICCAD 2022: 115:1-115:9 - [c11]Heng Lu, Zhuoran Song, Xing Li, Naifeng Jing, Xiaoyao Liang:
GCNTrain: A Unified and Efficient Accelerator for Graph Convolutional Neural Network Training. ICCD 2022: 730-737 - [c10]Gang Li, Weixiang Xu, Zhuoran Song, Naifeng Jing, Jian Cheng, Xiaoyao Liang:
Ristretto: An Atomized Processing Architecture for Sparsity-Condensed Stream Flow in CNN. MICRO 2022: 1434-1450 - [i4]Zhuoran Song, Yihong Xu, Zhezhi He, Li Jiang, Naifeng Jing, Xiaoyao Liang:
CP-ViT: Cascade Vision Transformer Pruning via Progressive Sparsity Prediction. CoRR abs/2203.04570 (2022) - [i3]Zhuoran Song, Yihong Xu, Han Li, Naifeng Jing, Xiaoyao Liang, Li Jiang:
DNN Training Acceleration via Exploring GPGPU Friendly Sparsity. CoRR abs/2203.05705 (2022) - 2021
- [j2]Zhuoran Song, Yanan Sun, Lerong Chen, Tianjian Li, Naifeng Jing, Xiaoyao Liang, Li Jiang:
ITT-RNA: Imperfection Tolerable Training for RRAM-Crossbar-Based Deep Neural-Network Accelerator. IEEE Trans. Comput. Aided Des. Integr. Circuits Syst. 40(1): 129-142 (2021) - [c9]Zhuoran Song, Dongyue Li, Zhezhi He, Xiaoyao Liang, Li Jiang:
ReRAM-Sharing: Fine-Grained Weight Sharing for ReRAM-Based Deep Neural Network Accelerator. ISCAS 2021: 1-5 - [c8]Feiyang Wu, Zhuoran Song, Jing Ke, Li Jiang, Naifeng Jing, Xiaoyao Liang:
PIPArch: Programmable Image Processing Architecture Using Sliding Array. ISPA/BDCloud/SocialCom/SustainCom 2021: 73-80 - 2020
- [c7]Zhuoran Song, Jianfei Wang, Tianjian Li, Li Jiang, Jing Ke, Xiaoyao Liang, Naifeng Jing:
GPNPU: Enabling Efficient Hardware-Based Direct Convolution with Multi-Precision Support in GPU Tensor Cores. DAC 2020: 1-6 - [c6]Zhuoran Song, Yilong Zhao, Yanan Sun, Xiaoyao Liang, Li Jiang:
ESNreram: An Energy-Efficient Sparse Neural Network Based on Resistive Random-Access Memory. ACM Great Lakes Symposium on VLSI 2020: 291-296 - [c5]Zhaoming Jiang, Zhuoran Song, Xiaoyao Liang, Naifeng Jing:
PRArch: Pattern-Based Reconfigurable Architecture for Deep Neural Network Acceleration. HPCC/DSS/SmartCity 2020: 122-129 - [c4]Zhuoran Song, Bangqi Fu, Feiyang Wu, Zhaoming Jiang, Li Jiang, Naifeng Jing, Xiaoyao Liang:
DRQ: Dynamic Region-based Quantization for Deep Neural Network Acceleration. ISCA 2020: 1010-1021 - [c3]Zhuoran Song, Feiyang Wu, Xueyuan Liu, Jing Ke, Naifeng Jing, Xiaoyao Liang:
VR-DANN: Real-Time Video Recognition via Decoder-Assisted Neural Network Acceleration. MICRO 2020: 698-710
2010 – 2019
- 2019
- [j1]Li Jiang, Zhuoran Song, Haiyue Song, Chengwen Xu, Qiang Xu, Naifeng Jing, Weifeng Zhang, Xiaoyao Liang:
Energy-Efficient and Quality-Assured Approximate Computing Framework Using a Co-Training Method. ACM Trans. Design Autom. Electr. Syst. 24(6): 59:1-59:25 (2019) - [c2]Zhuoran Song, Ru Wang, Dongyu Ru, Zhenghao Peng, Hongru Huang, Hai Zhao, Xiaoyao Liang, Li Jiang:
Approximate Random Dropout for DNN training acceleration in GPGPU. DATE 2019: 108-113 - 2018
- [c1]Haiyue Song, Chengwen Xu, Qiang Xu, Zhuoran Song, Naifeng Jing, Xiaoyao Liang, Li Jiang:
Invocation-driven neural approximate computing with a multiclass-classifier and multiple approximators. ICCAD 2018: 50 - [i2]Zhuoran Song, Dongyu Ru, Ru Wang, Hongru Huang, Zhenghao Peng, Jing Ke, Xiaoyao Liang, Li Jiang:
Approximate Random Dropout. CoRR abs/1805.08939 (2018) - [i1]Haiyue Song, Chengwen Xu, Qiang Xu, Zhuoran Song, Naifeng Jing, Xiaoyao Liang, Li Jiang:
Invocation-driven Neural Approximate Computing with a Multiclass-Classifier and Multiple Approximators. CoRR abs/1810.08379 (2018)
Coauthor Index
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last updated on 2024-11-13 23:50 CET by the dblp team
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