Invocation-driven neural approximate computing with a multiclass-classifier and multiple approximators. - Haiyue Song; Chengwen Xu; Qiang Xu 001; Zhuoran Song; Naifeng Jing; Xiaoyao Liang; Li Jiang 002 (ICCAD, 2018)

Approximate Random Dropout. - Zhuoran Song; Dongyu Ru; Ru Wang 002; Hongru Huang; Zhenghao Peng; Jing Ke; Xiaoyao Liang; Li Jiang 002 (CoRR, 2018)

Approximate Random Dropout for DNN training acceleration in GPGPU. - Zhuoran Song; Ru Wang 002; Dongyu Ru; Zhenghao Peng; Hongru Huang; Hai Zhao; Xiaoyao Liang; Li Jiang 002 (DATE, 2019)

Energy-Efficient and Quality-Assured Approximate Computing Framework Using a Co-Training Method. - Li Jiang 002; Zhuoran Song; Haiyue Song; Chengwen Xu; Qiang Xu 001; Naifeng Jing; Weifeng Zhang 003; Xiaoyao Liang (ACM Trans. Design Autom. Electr. Syst., 2019)

GPNPU: Enabling Efficient Hardware-Based Direct Convolution with Multi-Precision Support in GPU Tensor Cores. - Zhuoran Song; Jianfei Wang; Tianjian Li; Li Jiang 002; Jing Ke; Xiaoyao Liang; Naifeng Jing (DAC, 2020)

ESNreram: An Energy-Efficient Sparse Neural Network Based on Resistive Random-Access Memory. - Zhuoran Song; Yilong Zhao; Yanan Sun 003; Xiaoyao Liang; Li Jiang 002 (ACM Great Lakes Symposium on VLSI, 2020)

PRArch: Pattern-Based Reconfigurable Architecture for Deep Neural Network Acceleration. - Zhaoming Jiang; Zhuoran Song; Xiaoyao Liang; Naifeng Jing (HPCC/DSS/SmartCity, 2020)

DRQ: Dynamic Region-based Quantization for Deep Neural Network Acceleration. - Zhuoran Song; Bangqi Fu; Feiyang Wu; Zhaoming Jiang; Li Jiang 002; Naifeng Jing; Xiaoyao Liang (ISCA, 2020)

VR-DANN: Real-Time Video Recognition via Decoder-Assisted Neural Network Acceleration. - Zhuoran Song; Feiyang Wu; Xueyuan Liu 001; Jing Ke; Naifeng Jing; Xiaoyao Liang (MICRO, 2020)

ReRAM-Sharing: Fine-Grained Weight Sharing for ReRAM-Based Deep Neural Network Accelerator. - Zhuoran Song; Dongyue Li; Zhezhi He; Xiaoyao Liang; Li Jiang 002 (ISCAS, 2021)

PIPArch: Programmable Image Processing Architecture Using Sliding Array. - Feiyang Wu; Zhuoran Song; Jing Ke; Li Jiang 002; Naifeng Jing; Xiaoyao Liang (ISPA/BDCloud/SocialCom/SustainCom, 2021)

ITT-RNA: Imperfection Tolerable Training for RRAM-Crossbar-Based Deep Neural-Network Accelerator. - Zhuoran Song; Yanan Sun 003; Lerong Chen; Tianjian Li; Naifeng Jing; Xiaoyao Liang; Li Jiang 002 (IEEE Trans. Comput. Aided Des. Integr. Circuits Syst., 2021)

E2SR: an end-to-end video CODEC assisted system for super resolution acceleration. - Zhuoran Song; Zhongkai Yu; Naifeng Jing; Xiaoyao Liang (DAC, 2022)

DTQAtten: Leveraging Dynamic Token-based Quantization for Efficient Attention Architecture. - Tao Yang 031; Dongyue Li; Zhuoran Song; Yilong Zhao; Fangxin Liu; Zongwu Wang; Zhezhi He; Li Jiang 002 (DATE, 2022)

Gzippo: Highly-Compact Processing-in-Memory Graph Accelerator Alleviating Sparsity and Redundancy. - Xing Li; Rachata Ausavarungnirun; Xiao Liu 033; Xueyuan Liu 001; Xuan Zhang 001; Heng Lu; Zhuoran Song; Naifeng Jing; Xiaoyao Liang (ICCAD, 2022)

GCNTrain: A Unified and Efficient Accelerator for Graph Convolutional Neural Network Training. - Heng Lu; Zhuoran Song; Xing Li; Naifeng Jing; Xiaoyao Liang (ICCD, 2022)

Ristretto: An Atomized Processing Architecture for Sparsity-Condensed Stream Flow in CNN. - Gang Li 015; Weixiang Xu; Zhuoran Song; Naifeng Jing; Jian Cheng 001; Xiaoyao Liang (MICRO, 2022)

CP-ViT: Cascade Vision Transformer Pruning via Progressive Sparsity Prediction. - Zhuoran Song; Yihong Xu; Zhezhi He; Li Jiang 002; Naifeng Jing; Xiaoyao Liang (CoRR, 2022)

DNN Training Acceleration via Exploring GPGPU Friendly Sparsity. - Zhuoran Song; Yihong Xu; Han Li; Naifeng Jing; Xiaoyao Liang; Li Jiang 002 (CoRR, 2022)

PRADA: Point Cloud Recognition Acceleration via Dynamic Approximation. - Zhuoran Song; Naifeng Jing; Xiaoyao Liang (ACM TUR-C, 2023)

AdaS: A Fast and Energy-Efficient CNN Accelerator Exploiting Bit-Sparsity. - Xiaolong Lin; Gang Li 015; Zizhao Liu; Yadong Liu; Fan Zhang; Zhuoran Song; Naifeng Jing; Xiaoyao Liang (DAC, 2023)

PRADA: Point Cloud Recognition Acceleration via Dynamic Approximation. - Zhuoran Song; Heng Lu; Gang Li 015; Li Jiang 002; Naifeng Jing; Xiaoyao Liang (DATE, 2023)

ViTframe: Vision Transformer Acceleration via Informative Frame Selection for Video Recognition. - Chunyu Qi; Zilong Li; Zhuoran Song; Xiaoyao Liang (ICCD, 2023)

DEQ: Dynamic Element-wise Quantization for Efficient Attention Architecture. - Xuhang Wang; Zhuoran Song; Qiyue Huang; Xiaoyao Liang (ICCD, 2023)

RealArch: A Real-Time Scheduler for Mapping Multi-Tenant DNNs on Multi-Core Accelerators. - Xuhang Wang; Zhuoran Song; Xiaoyao Liang (ICCD, 2023)

HyAcc: A Hybrid CAM-MAC RRAM-based Accelerator for Recommendation Model. - Xuan Zhang 001; Zhuoran Song; Xing Li; Zhezhi He; Li Jiang 002; Naifeng Jing; Xiaoyao Liang (ICCD, 2023)

PASGCN: An ReRAM-Based PIM Design for GCN With Adaptively Sparsified Graphs. - Tao Yang 031; Dongyue Li; Fei Ma; Zhuoran Song; Yilong Zhao; Jiaxi Zhang 001; Fangxin Liu; Li Jiang 002 (IEEE Trans. Comput. Aided Des. Integr. Circuits Syst., 2023)

E2-VOR: An End-to-End En/Decoder Architecture for Efficient Video Object Recognition. - Zhuoran Song; Naifeng Jing; Xiaoyao Liang (ACM Trans. Design Autom. Electr. Syst., 2023)

Real-Time Video Recognition via Decoder-Assisted Neural Network Acceleration Framework. - Zhuoran Song; Heng Lu; Li Jiang 002; Naifeng Jing; Xiaoyao Liang (IEEE Trans. Comput. Aided Des. Integr. Circuits Syst., 2023)

Distribution Network Planning Method considering the Coupling of Transportation Network and Distribution Network. - Zhuoran Song; Jianfeng Li; Tao Jiang 002; Sichen Lu (Scalable Comput. Pract. Exp., 2023)

Impact of Photovoltaic Systems on Distribution Networks with Advances of Cloud, Grid and Cluster Computing. - Zhuoran Song; Jianfeng Li; Tao Jiang 002; Sichen Lu (Scalable Comput. Pract. Exp., 2023)

A Point Cloud Video Recognition Acceleration Framework Based on Tempo-Spatial Information. - Zhuoran Song; Wanzhen Liu; Tao Yang 031; Fangxin Liu; Naifeng Jing; Xiaoyao Liang (IEEE Trans. Parallel Distributed Syst., 2023)

CMC: Video Transformer Acceleration via CODEC Assisted Matrix Condensing. - Zhuoran Song; Chunyu Qi; Fangxin Liu; Naifeng Jing; Xiaoyao Liang (ASPLOS (2), 2024)

MoC: A Morton-Code-Based Fine-Grained Quantization for Accelerating Point Cloud Neural Networks. - Xueyuan Liu 001; Zhuoran Song; Hao Chen; Xing Li; Xiaoyao Liang (DAC, 2024)

INSPIRE: Accelerating Deep Neural Networks via Hardware-friendly Index-Pair Encoding. - Fangxin Liu; Ning Yang; Zhiyan Song; Zongwu Wang; Haomin Li 002; Shiyuan Huang; Zhuoran Song; Songwen Pei; Li Jiang 002 (DAC, 2024)

TSAcc: An Efficient underline{T}empo- underline{S}patial Similarity Aware underline{Acc}elerator for Attention Acceleration. - Zhuoran Song; Chunyu Qi; Yuanzheng Yao; Peng Zhou; Yanyi Zi; Nan Wang; Xiaoyao Liang (DAC, 2024)

InterArch: Video Transformer Acceleration via Inter-Feature Deduplication with Cube-based Dataflow. - Xuhang Wang; Zhuoran Song; Xiaoyao Liang (DAC, 2024)

EOS: An Energy-Oriented Attack Framework for Spiking Neural Networks. - Ning Yang; Fangxin Liu; Zongwu Wang; Haomin Li 002; Zhuoran Song; Songwen Pei; Li Jiang 002 (DAC, 2024)

FusionArch: A Fusion-Based Accelerator for Point-Based Point Cloud Neural Networks. - Xueyuan Liu 001; Zhuoran Song; Guohao Dai; Gang Li 015; Can Xiao; Yan Xiang; Dehui Kong; Ke Xu; Xiaoyao Liang (DATE, 2024)

Sava: A Spatial- and Value-Aware Accelerator for Point Cloud Transformer. - Xueyuan Liu 001; Zhuoran Song; Xiang Liao; Xing Li; Tao Yang 031; Fangxin Liu; Xiaoyao Liang (DATE, 2024)

Watt: A Write-Optimized RRAM-Based Accelerator for Attention. - Xuan Zhang 001; Zhuoran Song; Xing Li; Zhezhi He; Naifeng Jing; Li Jiang 002; Xiaoyao Liang (Euro-Par (2), 2024)

SPARK: Scalable and Precision-Aware Acceleration of Neural Networks via Efficient Encoding. - Fangxin Liu; Ning Yang; Haomin Li 002; Zongwu Wang; Zhuoran Song; Songwen Pei; Li Jiang 002 (HPCA, 2024)

Early: An Importance-Aware Early Firing and Exit for SNN Acceleration. - Xuan Zhang 001; Zhuoran Song; Peng Zhou; Xing Li; Xueyuan Liu 001; Xiaolong Lin; Zhezhi He; Li Jiang 002; Naifeng Jing; Xiaoyao Liang (ICCD, 2024)

SRender: Boosting Neural Radiance Field Efficiency via Sensitivity-Aware Dynamic Precision Rendering. - Zhuoran Song; Houshu He; Fangxin Liu; Yifan Hao 001; Xinkai Song; Li Jiang 002; Xiaoyao Liang (MICRO, 2024)

Environmental Condition Aware Super-Resolution Acceleration Framework in Server-Client Hierarchies. - Zhuoran Song; Zhongkai Yu; Xinkai Song; Yifan Hao 001; Li Jiang 002; Naifeng Jing; Xiaoyao Liang (ACM Trans. Archit. Code Optim., 2024)

Janus: A Flexible Processing-in-Memory Graph Accelerator Toward Sparsity. - Xing Li; Zhuoran Song; Rachata Ausavarungnirun; Xiao Liu 033; Xueyuan Liu 001; Xuan Zhang 001; Xuhang Wang; Jiayao Ling; Gang Li 015; Naifeng Jing; Xiaoyao Liang (IEEE Trans. Comput. Aided Des. Integr. Circuits Syst., 2024)

TAIL: Exploiting Temporal Asynchronous Execution for Efficient Spiking Neural Networks with Inter-Layer Parallelism. - Haomin Li 002; Fangxin Liu; Zongwu Wang; Dongxu Lyu; Shiyuan Huang; Ning Yang; Qi Sun; Zhuoran Song; Li Jiang 002 (DATE, 2025)

Light-DiT: An Importance-Aware Dynamic Compression Framework for Diffusion Transformers. - Cheng Gu; Gang Li 015; Xuan Zhang 001; Jiayao Ling; Xiaolong Lin; Zhuoran Song; Jian Cheng 001; Xiaoyao Liang (Euro-Par (2), 2025)

GSArch: Breaking Memory Barriers in 3D Gaussian Splatting Training via Architectural Support. - Houshu He; Gang Li 015; Fangxin Liu; Li Jiang 002; Xiaoyao Liang; Zhuoran Song (HPCA, 2025)

GIFTS: Efficient GCN Inference Framework on PyTorch-CPU via Exploring the Sparsity. - Ruiyang Chen; Xing Li; Xiaoyao Liang; Zhuoran Song (IPDPS, 2025)

Cambricon-SR: An Accelerator for Neural Scene Representation with Sparse Encoding Table. - Tianbo Liu 006; Xinkai Song; Zhifei Yue; Rui Wen; Xing Hu 001; Zhuoran Song; Yuanbo Wen; Yifan Hao 001; Wei Li 008; Zidong Du; Rui Zhang 040; Jiaming Guo; et al. (ISCA, 2025)

GCNTrain+: A Versatile and Efficient Accelerator for Graph Convolutional Neural Network Training. - Zhuoran Song; Jiabei Long; Li Jiang 002; Naifeng Jing; Xiaoyao Liang (ACM Trans. Archit. Code Optim., 2025)

Scaling Laws for Speculative Decoding. - Siyuan Yan; Mo Zhu; Guo-qing Jiang; Jianfei Wang; Jiaxing Chen; Wentai Zhang 006; Xiang Liao; Xiao Cui; Chen Zhang; Zhuoran Song; Ran Zhu (CoRR, 2025)

Accelerating Prefilling for Long-Context LLMs via Sparse Pattern Sharing. - Dan Peng; Zhihui Fu; Zewen Ye; Zhuoran Song; Jun Wang (CoRR, 2025)

HyCTor: A Hybrid CNN-Transformer Network Accelerator With Flexible Weight/Output Stationary Dataflow and Multicore Extension. - Shuai Yuan 016; Weifeng He; Zhenhua Zhu; Fangxin Liu; Zhuoran Song; Guohao Dai; Guanghui He; Yanan Sun 003 (IEEE Trans. Comput. Aided Des. Integr. Circuits Syst., 2025)

Accelerating 3D Gaussian Splatting with Neural Sorting and Axis-Oriented Rasterization. - Zhican Wang; Guanghui He; Dantong Liu; Lingjun Gao; Shell Xu Hu; Chen Zhang; Zhuoran Song; Nicholas D. Lane; Wayne Luk; Hongxiang Fan (CoRR, 2025)

RTSA: A Run-Through Sparse Attention Framework for Video Transformer. - Xuhang Wang; Zhuoran Song; Chunyu Qi; Fangxin Liu; Naifeng Jing; Li Jiang 002; Xiaoyao Liang (IEEE Trans. Computers, 2025)

Vision Transformer Acceleration via a Versatile Attention Optimization Framework. - Xuhang Wang; Qiyue Huang; Xing Li; Haozhe Jiang; Qiang Xu 001; Xiaoyao Liang; Zhuoran Song (IEEE Trans. Comput. Aided Des. Integr. Circuits Syst., 2025)

GCC: A 3DGS Inference Architecture with Gaussian-Wise and Cross-Stage Conditional Processing. - Minnan Pei; Gang Li 015; Junwen Si; Zeyu Zhu; Zitao Mo; Peisong Wang; Zhuoran Song; Xiaoyao Liang; Jian Cheng 001 (CoRR, 2025)

ASDR: Exploiting Adaptive Sampling and Data Reuse for CIM-based Instant Neural Rendering. - Fangxin Liu; Haomin Li 002; Bowen Zhu; Zongwu Wang; Zhuoran Song; Habing Guan; Li Jiang 002 (CoRR, 2025)

Load prediction and optimization of main transformer based on EEMD-BP neural network. - Wenlei Dou; Zhanjun Li; Zhuoran Song; Yongji Tong; Hongbo Zhu; Sichen Lu (Discov. Comput., 2025)