Song Han

According to our database, Song Han authored at least 140 papers between 2015 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of three.

2024

Tiny Machine Learning: Progress and Futures.

Ji Lin, Ligeng Zhu, Wei-Ming Chen, Wei-Chen Wang, Song Han

CoRR, 2024

DistriFusion: Distributed Parallel Inference for High-Resolution Diffusion Models.

Muyang Li, Tianle Cai, Jiaxin Cao, Qinsheng Zhang, Han Cai, Junjie Bai, Yangqing Jia, Ming-Yu Liu, Kai Li, Song Han

CoRR, 2024

BitDelta: Your Fine-Tune May Only Be Worth One Bit.

James Liu, Guangxuan Xiao, Kai Li, Jason D. Lee, Song Han, Tri Dao, Tianle Cai

CoRR, 2024

EfficientViT-SAM: Accelerated Segment Anything Model Without Performance Loss.

Zhuoyang Zhang, Han Cai, Song Han

CoRR, 2024

Qplacer: Frequency-Aware Component Placement for Superconducting Quantum Computers.

Junyao Zhang, Hanrui Wang, Qi Ding, Jiaqi Gu, Reouven Assouly, William D. Oliver, Song Han, Kenneth R. Brown, Hai Helen Li, Yiran Chen

CoRR, 2024

Lightening-Transformer: A Dynamically-Operated Optically-Interconnected Photonic Transformer Accelerator.

Hanqing Zhu, Jiaqi Gu, Hanrui Wang, Zixuan Jiang, Zhekai Zhang, Rongxing Tang, Chenghao Feng, Song Han, Ray T. Chen, David Z. Pan

Proceedings of the IEEE International Symposium on High-Performance Computer Architecture, 2024

2023

Efficient Spatially Sparse Inference for Conditional GANs and Diffusion Models.

Muyang Li, Ji Lin, Chenlin Meng, Stefano Ermon, Song Han, Jun-Yan Zhu

IEEE Trans. Pattern Anal. Mach. Intell., December, 2023

Algorithm-System-Hardware Co-Design for Efficient 3D Deep Learning.

Zhijian Liu, Haotian Tang, Yujun Lin, Song Han

World Sci. Annu. Rev. Artif. Intell., 2023

DGR: Tackling Drifted and Correlated Noise in Quantum Error Correction via Decoding Graph Re-weighting.

Hanrui Wang, Pengyu Liu, Yilian Liu, Jiaqi Gu, Jonathan M. Baker, Frederic T. Chong, Song Han

CoRR, 2023

Q-Pilot: Field Programmable Quantum Array Compilation with Flying Ancillas.

Hanrui Wang, Bochen Tan, Pengyu Liu, Yilian Liu, Jiaqi Gu, Jason Cong, Song Han

CoRR, 2023

Transformer-QEC: Quantum Error Correction Code Decoding with Transferable Transformers.

Hanrui Wang, Pengyu Liu, Kevin Shao, Dantong Li, Jiaqi Gu, David Z. Pan, Yongshan Ding, Song Han

CoRR, 2023

RobustState: Boosting Fidelity of Quantum State Preparation via Noise-Aware Variational Training.

Hanrui Wang, Yilian Liu, Pengyu Liu, Jiaqi Gu, Zirui Li, Zhiding Liang, Jinglei Cheng, Yongshan Ding, Xuehai Qian, Yiyu Shi, David Z. Pan, Frederic T. Chong, Song Han

CoRR, 2023

FPQA-C: A Compilation Framework for Field Programmable Qubit Array.

Hanrui Wang, Pengyu Liu, Bochen Tan, Yilian Liu, Jiaqi Gu, David Z. Pan, Jason Cong, Umut A. Acar, Song Han

CoRR, 2023

LongLoRA: Efficient Fine-tuning of Long-Context Large Language Models.

Yukang Chen, Shengju Qian, Haotian Tang, Xin Lai, Zhijian Liu, Song Han, Jiaya Jia

CoRR, 2023

AWQ: Activation-aware Weight Quantization for LLM Compression and Acceleration.

Ji Lin, Jiaming Tang, Haotian Tang, Shang Yang, Xingyu Dang, Song Han

CoRR, 2023

DOTA: A Dynamically-Operated Photonic Tensor Core for Energy-Efficient Transformer Accelerator.

Hanqing Zhu, Jiaqi Gu, Hanrui Wang, Zixuan Jiang, Zhekai Zhang, Rongxin Tang, Chenghao Feng, Song Han, Ray T. Chen, David Z. Pan

CoRR, 2023

Offsite-Tuning: Transfer Learning without Full Model.

Guangxuan Xiao, Ji Lin, Song Han

CoRR, 2023

DISQ: Dynamic Iteration Skipping for Variational Quantum Algorithms.

Junyao Zhang, Hanrui Wang, Gokul Subramanian Ravi, Frederic T. Chong, Song Han, Frank Mueller, Yiran Chen

Proceedings of the IEEE International Conference on Quantum Computing and Engineering, 2023

QuantumSEA: In-Time Sparse Exploration for Noise Adaptive Quantum Circuits.

Tianlong Chen, Zhenyu Zhang, Hanrui Wang, Jiaqi Gu, Zirui Li, David Z. Pan, Frederic T. Chong, Song Han, Zhangyang Wang

Proceedings of the IEEE International Conference on Quantum Computing and Engineering, 2023

PockEngine: Sparse and Efficient Fine-tuning in a Pocket.

Ligeng Zhu, Lanxiang Hu, Ji Lin, Wei-Ming Chen, Wei-Chen Wang, Chuang Gan, Song Han

Proceedings of the 56th Annual IEEE/ACM International Symposium on Microarchitecture, 2023

TorchSparse++: Efficient Training and Inference Framework for Sparse Convolution on GPUs.

Haotian Tang, Shang Yang, Zhijian Liu, Ke Hong, Zhongming Yu, Xiuyu Li, Guohao Dai, Yu Wang, Song Han

Proceedings of the 56th Annual IEEE/ACM International Symposium on Microarchitecture, 2023

A Fully-Integrated Energy-Scalable Transformer Accelerator Supporting Adaptive Model Configuration and Word Elimination for Language Understanding on Edge Devices.

Zexi Ji, Hanrui Wang, Miaorong Wang, Win-San Khwa, Meng-Fan Chang, Song Han, Anantha P. Chandrakasan

Proceedings of the IEEE/ACM International Symposium on Low Power Electronics and Design, 2023

BEVFusion: Multi-Task Multi-Sensor Fusion with Unified Bird's-Eye View Representation.

Zhijian Liu, Haotian Tang, Alexander Amini, Xinyu Yang, Huizi Mao, Daniela L. Rus, Song Han

Proceedings of the IEEE International Conference on Robotics and Automation, 2023

SmoothQuant: Accurate and Efficient Post-Training Quantization for Large Language Models.

Guangxuan Xiao, Ji Lin, Mickaël Seznec, Hao Wu, Julien Demouth, Song Han

Proceedings of the International Conference on Machine Learning, 2023

EfficientViT: Lightweight Multi-Scale Attention for High-Resolution Dense Prediction.

Han Cai, Junyan Li, Muyan Hu, Chuang Gan, Song Han

Proceedings of the IEEE/CVF International Conference on Computer Vision, 2023

Design of Quantum Computer Antivirus.

Sanjay Deshpande, Chuanqi Xu, Theodoros Trochatos, Hanrui Wang, Ferhat Erata, Song Han, Yongshan Ding, Jakub Szefer

Proceedings of the IEEE International Symposium on Hardware Oriented Security and Trust, 2023

Hybrid Gate-Pulse Model for Variational Quantum Algorithms.

Zhiding Liang, Zhixin Song, Jinglei Cheng, Zichang He, Ji Liu, Hanrui Wang, Ruiyang Qin, Yiru Wang, Song Han, Xuehai Qian, Yiyu Shi

Proceedings of the 60th ACM/IEEE Design Automation Conference, 2023

TorchSparse++: Efficient Point Cloud Engine.

Haotian Tang, Shang Yang, Zhijian Liu, Ke Hong, Zhongming Yu, Xiuyu Li, Guohao Dai, Yu Wang, Song Han

Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2023

FlatFormer: Flattened Window Attention for Efficient Point Cloud Transformer.

Zhijian Liu, Xinyu Yang, Haotian Tang, Shang Yang, Song Han

Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2023

SparseViT: Revisiting Activation Sparsity for Efficient High-Resolution Vision Transformer.

Xuanyao Chen, Zhijian Liu, Haotian Tang, Li Yi, Hang Zhao, Song Han

Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2023

Machine Learning for Arterial Blood Pressure Prediction.

Jessica Zheng, Hanrui Wang, Anand Chandrasekhar, Aaron D. Aguirre, Song Han, Hae-Seung Lee, Charles G. Sodini

Proceedings of the Conference on Health, Inference, and Learning, 2023

2022

Enable Deep Learning on Mobile Devices: Methods, Systems, and Applications.

Han Cai, Ji Lin, Yujun Lin, Zhijian Liu, Haotian Tang, Hanrui Wang, Ligeng Zhu, Song Han

ACM Trans. Design Autom. Electr. Syst., 2022

PVNAS: 3D Neural Architecture Search With Point-Voxel Convolution.

Zhijian Liu, Haotian Tang, Shengyu Zhao, Kevin Shao, Song Han

IEEE Trans. Pattern Anal. Mach. Intell., 2022

TSM: Temporal Shift Module for Efficient and Scalable Video Understanding on Edge Devices.

Ji Lin, Chuang Gan, Kuan Wang, Song Han

IEEE Trans. Pattern Anal. Mach. Intell., 2022

GAN Compression: Efficient Architectures for Interactive Conditional GANs.

Muyang Li, Ji Lin, Yaoyao Ding, Zhijian Liu, Jun-Yan Zhu, Song Han

IEEE Trans. Pattern Anal. Mach. Intell., 2022

SmoothQuant: Accurate and Efficient Post-Training Quantization for Large Language Models.

Guangxuan Xiao, Ji Lin, Mickaël Seznec, Julien Demouth, Song Han

CoRR, 2022

QuEst: Graph Transformer for Quantum Circuit Reliability Estimation.

Hanrui Wang, Pengyu Liu, Jinglei Cheng, Zhiding Liang, Jiaqi Gu, Zirui Li, Yongshan Ding, Weiwen Jiang, Yiyu Shi, Xuehai Qian, David Z. Pan, Frederic T. Chong, Song Han

CoRR, 2022

TopGen: Topology-Aware Bottom-Up Generator for Variational Quantum Circuits.

Jinglei Cheng, Hanrui Wang, Zhiding Liang, Yiyu Shi, Song Han, Xuehai Qian

CoRR, 2022

PAN: Pulse Ansatz on NISQ Machines.

Zhiding Liang, Jinglei Cheng, Hang Ren, Hanrui Wang, Fei Hua, Yongshan Ding, Fred Chong, Song Han, Yiyu Shi, Xuehai Qian

CoRR, 2022

EfficientViT: Enhanced Linear Attention for High-Resolution Low-Computation Visual Recognition.

Han Cai, Chuang Gan, Song Han

CoRR, 2022

On-chip QNN: Towards Efficient On-Chip Training of Quantum Neural Networks.

Hanrui Wang, Zirui Li, Jiaqi Gu, Yongshan Ding, David Z. Pan, Song Han

CoRR, 2022

Variational Quantum Pulse Learning.

Zhiding Liang, Hanrui Wang, Jinglei Cheng, Yongshan Ding, Hang Ren, Zhengqi Gao, Zhirui Hu, Duane S. Boning, Xuehai Qian, Song Han, Weiwen Jiang, Yiyu Shi

Proceedings of the IEEE International Conference on Quantum Computing and Engineering, 2022

On-Device Training Under 256KB Memory.

Ji Lin, Ligeng Zhu, Wei-Ming Chen, Wei-Chen Wang, Chuang Gan, Song Han

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

TorchSparse: Efficient Point Cloud Inference Engine.

Haotian Tang, Zhijian Liu, Xiuyu Li, Yujun Lin, Song Han

Proceedings of Machine Learning and Systems 2022, 2022

RobustAnalog: Fast Variation-Aware Analog Circuit Design Via Multi-task RL.

Wei Shi, Hanrui Wang, Jiaqi Gu, Mingjie Liu, David Z. Pan, Song Han, Nan Sun

Proceedings of the 2022 ACM/IEEE Workshop on Machine Learning for CAD, 2022

VISTA 2.0: An Open, Data-driven Simulator for Multimodal Sensing and Policy Learning for Autonomous Vehicles.

Alexander Amini, Tsun-Hsuan Wang, Igor Gilitschenski, Wilko Schwarting, Zhijian Liu, Song Han, Sertac Karaman, Daniela Rus

Proceedings of the 2022 International Conference on Robotics and Automation, 2022

Network Augmentation for Tiny Deep Learning.

Han Cai, Chuang Gan, Ji Lin, Song Han

Proceedings of the Tenth International Conference on Learning Representations, 2022

TorchQuantum Case Study for Robust Quantum Circuits.

Hanrui Wang, Zhiding Liang, Jiaqi Gu, Zirui Li, Yongshan Ding, Weiwen Jiang, Yiyu Shi, David Z. Pan, Frederic T. Chong, Song Han

Proceedings of the 41st IEEE/ACM International Conference on Computer-Aided Design, 2022

QuantumNAS: Noise-Adaptive Search for Robust Quantum Circuits.

Hanrui Wang, Yongshan Ding, Jiaqi Gu, Yujun Lin, David Z. Pan, Frederic T. Chong, Song Han

Proceedings of the IEEE International Symposium on High-Performance Computer Architecture, 2022

QOC: quantum on-chip training with parameter shift and gradient pruning.

Hanrui Wang, Zirui Li, Jiaqi Gu, Yongshan Ding, David Z. Pan, Song Han

Proceedings of the DAC '22: 59th ACM/IEEE Design Automation Conference, San Francisco, California, USA, July 10, 2022

QuantumNAT: quantum noise-aware training with noise injection, quantization and normalization.

Hanrui Wang, Jiaqi Gu, Yongshan Ding, Zirui Li, Frederic T. Chong, David Z. Pan, Song Han

Proceedings of the DAC '22: 59th ACM/IEEE Design Automation Conference, San Francisco, California, USA, July 10, 2022

Lite Pose: Efficient Architecture Design for 2D Human Pose Estimation.

Yihan Wang, Muyang Li, Han Cai, Wei-Ming Chen, Song Han

Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2022

DeepVS: a deep learning approach for RF-based vital signs sensing.

Zongxing Xie, Hanrui Wang, Song Han, Elinor Schoenfeld, Fan Ye

Proceedings of the BCB '22: 13th ACM International Conference on Bioinformatics, Computational Biology and Health Informatics, Northbrook, Illinois, USA, August 7, 2022

2021

MCUNetV2: Memory-Efficient Patch-based Inference for Tiny Deep Learning.

Ji Lin, Wei-Ming Chen, Han Cai, Chuang Gan, Song Han

CoRR, 2021

RoQNN: Noise-Aware Training for Robust Quantum Neural Networks.

Hanrui Wang, Jiaqi Gu, Yongshan Ding, Zirui Li, Frederic T. Chong, David Z. Pan, Song Han

CoRR, 2021

TSM: Temporal Shift Module for Efficient and Scalable Video Understanding on Edge Device.

Ji Lin, Chuang Gan, Kuan Wang, Song Han

CoRR, 2021

PatchNet - Short-range Template Matching for Efficient Video Processing.

Huizi Mao, Sibo Zhu, Song Han, William J. Dally

CoRR, 2021

Delayed Gradient Averaging: Tolerate the Communication Latency for Federated Learning.

Ligeng Zhu, Hongzhou Lin, Yao Lu, Yujun Lin, Song Han

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Memory-efficient Patch-based Inference for Tiny Deep Learning.

Ji Lin, Wei-Ming Chen, Han Cai, Chuang Gan, Song Han

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

IOS: Inter-Operator Scheduler for CNN Acceleration.

Yaoyao Ding, Ligeng Zhu, Zhihao Jia, Gennady Pekhimenko, Song Han

Proceedings of Machine Learning and Systems 2021, 2021

PointAcc: Efficient Point Cloud Accelerator.

Yujun Lin, Zhekai Zhang, Haotian Tang, Hanrui Wang, Song Han

Proceedings of the MICRO '21: 54th Annual IEEE/ACM International Symposium on Microarchitecture, 2021

SemAlign: Annotation-Free Camera-LiDAR Calibration with Semantic Alignment Loss.

Zhijian Liu, Haotian Tang, Sibo Zhu, Song Han

Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems, 2021

Efficient and Robust LiDAR-Based End-to-End Navigation.

Zhijian Liu, Alexander Amini, Sibo Zhu, Sertac Karaman, Song Han, Daniela L. Rus

Proceedings of the IEEE International Conference on Robotics and Automation, 2021

LocTex: Learning Data-Efficient Visual Representations from Localized Textual Supervision.

Zhijian Liu, Simon Stent, Jie Li, John Gideon, Song Han

Proceedings of the 2021 IEEE/CVF International Conference on Computer Vision, 2021

SpAtten: Efficient Sparse Attention Architecture with Cascade Token and Head Pruning.

Hanrui Wang, Zhekai Zhang, Song Han

Proceedings of the IEEE International Symposium on High-Performance Computer Architecture, 2021

NAAS: Neural Accelerator Architecture Search.

Yujun Lin, Mengtian Yang, Song Han

Proceedings of the 58th ACM/IEEE Design Automation Conference, 2021

Anycost GANs for Interactive Image Synthesis and Editing.

Ji Lin, Richard Zhang, Frieder Ganz, Song Han, Jun-Yan Zhu

Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2021

The 2020 Low-Power Computer Vision Challenge.

Xiao Hu, Ming-Ching Chang, Yuwei Chen, Rahul Sridhar, Zhenyu Hu, Yunhe Xue, Zhenyu Wu, Pengcheng Pi, Jiayi Shen, Jianchao Tan, Xiangru Lian, Ji Liu, Zhangyang Wang, Chia-Hsiang Liu, Yu-Shin Han, Yuan-Yao Sung, Yi Lee, Kai-Chiang Wu, Wei-Xiang Guo, Rick Lee, Shengwen Liang, Zerun Wang, Guiguang Ding, Gang Zhang, Teng Xi, Yubei Chen, Han Cai, Ligeng Zhu, Zhekai Zhang, Song Han, Seonghwan Jeong, YoungMin Kwon, Tianzhe Wang, Jeffery Pan

Proceedings of the 3rd IEEE International Conference on Artificial Intelligence Circuits and Systems, 2021

2020

Deep Leakage from Gradients.

Ligeng Zhu, Song Han

Proceedings of the Federated Learning - Privacy and Incentive, 2020

Long Live TIME: Improving Lifetime and Security for NVM-Based Training-in-Memory Systems.

Yi Cai, Yujun Lin, Lixue Xia, Xiaoming Chen, Song Han, Yu Wang, Huazhong Yang

IEEE Trans. Comput. Aided Des. Integr. Circuits Syst., 2020

Energy Efficient On-Demand Dynamic Branch Prediction Models.

Milad Mohammadi, Song Han, Ehsan Atoofian, Amirali Baniasadi, Tor M. Aamodt, William J. Dally

IEEE Trans. Computers, 2020

Scanning the Issue.

H.-S. Philip Wong, Kerem Akarvardar, Dimitri A. Antoniadis, Jeffrey Bokor, Chenming Hu, Tsu-Jae King Liu, Subhasish Mitra, James D. Plummer, Sayeef S. Salahuddin, Lei Deng, Xin-Guo Li, Song Han, Luping Shi, Yuan Xie, Elias Yaacoub, Mohamed-Slim Alouini, Ahmed Douik, Hayssam Dahrouj, Tareq Y. Al-Naffouri

Proc. IEEE, 2020

Model Compression and Hardware Acceleration for Neural Networks: A Comprehensive Survey.

Lei Deng, Guoqi Li, Song Han, Luping Shi, Yuan Xie

Proc. IEEE, 2020

AutoML for Architecting Efficient and Specialized Neural Networks.

Han Cai, Ji Lin, Yujun Lin, Zhijian Liu, Kuan Wang, Tianzhe Wang, Ligeng Zhu, Song Han

IEEE Micro, 2020

Hardware-Centric AutoML for Mixed-Precision Quantization.

Kuan Wang, Zhijian Liu, Yujun Lin, Ji Lin, Song Han

Int. J. Comput. Vis., 2020

Tiny Transfer Learning: Towards Memory-Efficient On-Device Learning.

Han Cai, Chuang Gan, Ligeng Zhu, Song Han

CoRR, 2020

APQ: Joint Search for Network Architecture, Pruning and Quantization Policy.

Tianzhe Wang, Kuan Wang, Han Cai, Ji Lin, Zhijian Liu, Song Han

CoRR, 2020

Domain-specific hardware accelerators.

William J. Dally, Yatish Turakhia, Song Han

Commun. ACM, 2020

Differentiable Augmentation for Data-Efficient GAN Training.

Shengyu Zhao, Zhijian Liu, Ji Lin, Jun-Yan Zhu, Song Han

Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

MCUNet: Tiny Deep Learning on IoT Devices.

Ji Lin, Wei-Ming Chen, Yujun Lin, John Cohn, Chuang Gan, Song Han

Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

TinyTL: Reduce Memory, Not Parameters for Efficient On-Device Learning.

Han Cai, Chuang Gan, Ligeng Zhu, Song Han

Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

Lite Transformer with Long-Short Range Attention.

Zhanghao Wu, Zhijian Liu, Ji Lin, Yujun Lin, Song Han

Proceedings of the 8th International Conference on Learning Representations, 2020

Once-for-All: Train One Network and Specialize it for Efficient Deployment.

Han Cai, Chuang Gan, Tianzhe Wang, Zhekai Zhang, Song Han

Proceedings of the 8th International Conference on Learning Representations, 2020

SpArch: Efficient Architecture for Sparse Matrix Multiplication.

Zhekai Zhang, Hanrui Wang, Song Han, William J. Dally

Proceedings of the IEEE International Symposium on High Performance Computer Architecture, 2020

Searching Efficient 3D Architectures with Sparse Point-Voxel Convolution.

Haotian Tang, Zhijian Liu, Shengyu Zhao, Yujun Lin, Ji Lin, Hanrui Wang, Song Han

Proceedings of the Computer Vision - ECCV 2020, 2020

DataMix: Efficient Privacy-Preserving Edge-Cloud Inference.

Zhijian Liu, Zhanghao Wu, Chuang Gan, Ligeng Zhu, Song Han

Proceedings of the Computer Vision - ECCV 2020, 2020

GCN-RL Circuit Designer: Transferable Transistor Sizing with Graph Neural Networks and Reinforcement Learning.

Hanrui Wang, Kuan Wang, Jiacheng Yang, Linxiao Shen, Nan Sun, Hae-Seung Lee, Song Han

Proceedings of the 57th ACM/IEEE Design Automation Conference, 2020

APQ: Joint Search for Network Architecture, Pruning and Quantization Policy.

Tianzhe Wang, Kuan Wang, Han Cai, Ji Lin, Zhijian Liu, Hanrui Wang, Yujun Lin, Song Han

Proceedings of the 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2020

HAT: Hardware-Aware Transformers for Efficient Natural Language Processing.

Hanrui Wang, Zhanghao Wu, Zhijian Liu, Han Cai, Ligeng Zhu, Chuang Gan, Song Han

Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics, 2020

2019

Modeling and Optimization for Self-powered Non-volatile IoT Edge Devices with Ultra-low Harvesting Power.

Chen Pan, Mimi Xie, Song Han, Zhi-Hong Mao, Jingtong Hu

ACM Trans. Cyber Phys. Syst., 2019

Training Kinetics in 15 Minutes: Large-scale Distributed Training on Videos.

Ji Lin, Chuang Gan, Song Han

CoRR, 2019

Once for All: Train One Network and Specialize it for Efficient Deployment.

Han Cai, Chuang Gan, Song Han

CoRR, 2019

Design Automation for Efficient Deep Learning Computing.

Song Han, Han Cai, Ligeng Zhu, Ji Lin, Kuan Wang, Zhijian Liu, Yujun Lin

CoRR, 2019

SysML: The New Frontier of Machine Learning Systems.

Alexander Ratner, Dan Alistarh, Gustavo Alonso, David G. Andersen, Peter Bailis, Sarah Bird, Nicholas Carlini, Bryan Catanzaro, Eric S. Chung, Bill Dally, Jeff Dean, Inderjit S. Dhillon, Alexandros G. Dimakis, Pradeep Dubey, Charles Elkan, Grigori Fursin, Gregory R. Ganger, Lise Getoor, Phillip B. Gibbons, Garth A. Gibson, Joseph E. Gonzalez, Justin Gottschlich, Song Han, Kim M. Hazelwood, Furong Huang, Martin Jaggi, Kevin G. Jamieson, Michael I. Jordan, Gauri Joshi, Rania Khalaf, Jason Knight, Jakub Konecný, Tim Kraska, Arun Kumar, Anastasios Kyrillidis, Jing Li, Samuel Madden, H. Brendan McMahan, Erik Meijer, Ioannis Mitliagkas, Rajat Monga, Derek Gordon Murray, Dimitris S. Papailiopoulos, Gennady Pekhimenko, Theodoros Rekatsinas, Afshin Rostamizadeh, Christopher Ré, Christopher De Sa, Hanie Sedghi, Siddhartha Sen, Virginia Smith, Alex Smola, Dawn Song, Evan R. Sparks, Ion Stoica, Vivienne Sze, Madeleine Udell, Joaquin Vanschoren, Shivaram Venkataraman, Rashmi Vinayak, Markus Weimer, Andrew Gordon Wilson, Eric P. Xing, Matei Zaharia, Ce Zhang, Ameet Talwalkar

CoRR, 2019

Deep Leakage from Gradients.

Ligeng Zhu, Zhijian Liu, Song Han

Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

MicroNet for Efficient Language Modeling.

Zhongxia Yan, Hanrui Wang, Demi Guo, Song Han

Proceedings of the NeurIPS 2019 Competition and Demonstration Track, 2019

Park: An Open Platform for Learning-Augmented Computer Systems.

Hongzi Mao, Parimarjan Negi, Akshay Narayan, Hanrui Wang, Jiacheng Yang, Haonan Wang, Ryan Marcus, Ravichandra Addanki, Mehrdad Khani Shirkoohi, Songtao He, Vikram Nathan, Frank Cangialosi, Shaileshh Bojja Venkatakrishnan, Wei-Hung Weng, Song Han, Tim Kraska, Mohammad Alizadeh

Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

Point-Voxel CNN for Efficient 3D Deep Learning.

Zhijian Liu, Haotian Tang, Yujun Lin, Song Han

Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

Defensive Quantization: When Efficiency Meets Robustness.

Ji Lin, Chuang Gan, Song Han

Proceedings of the 7th International Conference on Learning Representations, 2019

ProxylessNAS: Direct Neural Architecture Search on Target Task and Hardware.

Han Cai, Ligeng Zhu, Song Han

Proceedings of the 7th International Conference on Learning Representations, 2019

On-Device Image Classification with Proxyless Neural Architecture Search and Quantization-Aware Fine-Tuning.

Han Cai, Tianzhe Wang, Zhanghao Wu, Kuan Wang, Ji Lin, Song Han

Proceedings of the 2019 IEEE/CVF International Conference on Computer Vision Workshops, 2019

TSM: Temporal Shift Module for Efficient Video Understanding.

Ji Lin, Chuang Gan, Song Han

Proceedings of the 2019 IEEE/CVF International Conference on Computer Vision, 2019

A Fine-Grained Sparse Accelerator for Multi-Precision DNN.

Shulin Zeng, Yujun Lin, Shuang Liang, Junlong Kang, Dongliang Xie, Yi Shan, Song Han, Yu Wang, Huazhong Yang

Proceedings of the 2019 ACM/SIGDA International Symposium on Field-Programmable Gate Arrays, 2019

Fast Inference of Deep Neural Networks for Real-time Particle Physics Applications.

Javier M. Duarte, Song Han, Philip C. Harris, Sergo Jindariani, Edward Kreinar, Benjamin Kreis, Vladimir Loncar, Jennifer Ngadiuba, Maurizio Pierini, Dylan S. Rankin, Ryan A. Rivera, Sioni Summers, Nhan Tran, Zhenbin Wu

Proceedings of the 2019 ACM/SIGDA International Symposium on Field-Programmable Gate Arrays, 2019

A Configurable Multi-Precision CNN Computing Framework Based on Single Bit RRAM.

Zhenhua Zhu, Hanbo Sun, Yujun Lin, Guohao Dai, Lixue Xia, Song Han, Yu Wang, Huazhong Yang

Proceedings of the 56th Annual Design Automation Conference 2019, 2019

HAQ: Hardware-Aware Automated Quantization With Mixed Precision.

Kuan Wang, Zhijian Liu, Yujun Lin, Ji Lin, Song Han

Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2019

2018

Angel-Eye: A Complete Design Flow for Mapping CNN Onto Embedded FPGA.

Kaiyuan Guo, Lingzhi Sui, Jiantao Qiu, Jincheng Yu, Junbin Wang, Song Yao, Song Han, Yu Wang, Huazhong Yang

IEEE Trans. Comput. Aided Des. Integr. Circuits Syst., 2018

Learning to Design Circuits.

Hanrui Wang, Jiacheng Yang, Hae-Seung Lee, Song Han

CoRR, 2018

HAQ: Hardware-Aware Automated Quantization.

Kuan Wang, Zhijian Liu, Yujun Lin, Ji Lin, Song Han

CoRR, 2018

Temporal Shift Module for Efficient Video Understanding.

Ji Lin, Chuang Gan, Song Han

CoRR, 2018

Fast inference of deep neural networks in FPGAs for particle physics.

Javier M. Duarte, Song Han, Philip C. Harris, Sergo Jindariani, Edward Kreinar, Benjamin Kreis, Jennifer Ngadiuba, Maurizio Pierini, Ryan A. Rivera, Nhan Tran, Zhenbin Wu

CoRR, 2018

Path-Level Network Transformation for Efficient Architecture Search.

Han Cai, Jiacheng Yang, Weinan Zhang, Song Han, Yong Yu

Proceedings of the 35th International Conference on Machine Learning, 2018

Efficient Sparse-Winograd Convolutional Neural Networks.

Xingyu Liu, Jeff Pool, Song Han, William J. Dally

Proceedings of the 6th International Conference on Learning Representations, 2018

Deep Gradient Compression: Reducing the Communication Bandwidth for Distributed Training.

Yujun Lin, Song Han, Huizi Mao, Yu Wang, Bill Dally

Proceedings of the 6th International Conference on Learning Representations, 2018

AMC: AutoML for Model Compression and Acceleration on Mobile Devices.

Yihui He, Ji Lin, Zhijian Liu, Hanrui Wang, Li-Jia Li, Song Han

Proceedings of the Computer Vision - ECCV 2018, 2018

Bandwidth-efficient deep learning.

Song Han, William J. Dally

Proceedings of the 55th Annual Design Automation Conference, 2018

Long live TIME: improving lifetime for training-in-memory engines by structured gradient sparsification.

Yi Cai, Yujun Lin, Lixue Xia, Xiaoming Chen, Song Han, Yu Wang, Huazhong Yang

Proceedings of the 55th Annual Design Automation Conference, 2018

2017

Software-Hardware Codesign for Efficient Neural Network Acceleration.

Kaiyuan Guo, Song Han, Song Yao, Yu Wang, Yuan Xie, Huazhong Yang

IEEE Micro, 2017

Deep Generative Adversarial Networks for Compressed Sensing Automates MRI.

Morteza Mardani, Enhao Gong, Joseph Y. Cheng, Shreyas Vasanawala, Greg Zaharchuk, Marcus T. Alley, Neil Thakur, Song Han, William J. Dally, John M. Pauly, Lei Xing

CoRR, 2017

Exploring the Regularity of Sparse Structure in Convolutional Neural Networks.

Huizi Mao, Song Han, Jeff Pool, Wenshuo Li, Xingyu Liu, Yu Wang, William J. Dally

CoRR, 2017

Research for practice: cryptocurrencies, blockchains, and smart contracts; hardware for deep learning.

Peter Bailis, Arvind Narayanan, Andrew Miller, Song Han

Commun. ACM, 2017

Trained Ternary Quantization.

Chenzhuo Zhu, Song Han, Huizi Mao, William J. Dally

Proceedings of the 5th International Conference on Learning Representations, 2017

Efficient Sparse-Winograd Convolutional Neural Networks.

Xingyu Liu, Song Han, Huizi Mao, William J. Dally

Proceedings of the 5th International Conference on Learning Representations, 2017

DSD: Dense-Sparse-Dense Training for Deep Neural Networks.

Song Han, Jeff Pool, Sharan Narang, Huizi Mao, Enhao Gong, Shijian Tang, Erich Elsen, Peter Vajda, Manohar Paluri, John Tran, Bryan Catanzaro, William J. Dally

Proceedings of the 5th International Conference on Learning Representations, 2017

ESE: Efficient Speech Recognition Engine with Sparse LSTM on FPGA.

Song Han, Junlong Kang, Huizi Mao, Yiming Hu, Xin Li, Yubin Li, Dongliang Xie, Hong Luo, Song Yao, Yu Wang, Huazhong Yang, William (Bill) J. Dally

Proceedings of the 2017 ACM/SIGDA International Symposium on Field-Programmable Gate Arrays, 2017

An FPGA Design Framework for CNN Sparsification and Acceleration.

Sicheng Li, Wei Wen, Yu Wang, Song Han, Yiran Chen, Hai Li

Proceedings of the 25th IEEE Annual International Symposium on Field-Programmable Custom Computing Machines, 2017

Exploring the Granularity of Sparsity in Convolutional Neural Networks.

Huizi Mao, Song Han, Jeff Pool, Wenshuo Li, Xingyu Liu, Yu Wang, William J. Dally

Proceedings of the 2017 IEEE Conference on Computer Vision and Pattern Recognition Workshops, 2017

2016

Generate Image Descriptions based on Deep RNN and Memory Cells for Images Features.

Shijian Tang, Song Han

CoRR, 2016

SqueezeNet: AlexNet-level accuracy with 50x fewer parameters and <1MB model size.

Forrest N. Iandola, Matthew W. Moskewicz, Khalid Ashraf, Song Han, William J. Dally, Kurt Keutzer

CoRR, 2016

DSD: Regularizing Deep Neural Networks with Dense-Sparse-Dense Training Flow.

Song Han, Jeff Pool, Sharan Narang, Huizi Mao, Shijian Tang, Erich Elsen, Bryan Catanzaro, John Tran, William J. Dally

CoRR, 2016

Deep Compression: Compressing Deep Neural Network with Pruning, Trained Quantization and Huffman Coding.

Song Han, Huizi Mao, William J. Dally

Proceedings of the 4th International Conference on Learning Representations, 2016

ESE: Efficient Speech Recognition Engine with Compressed LSTM on FPGA.

Song Han, Junlong Kang, Huizi Mao, Yiming Hu, Xin Li, Yubin Li, Dongliang Xie, Hong Luo, Song Yao, Yu Wang, Huazhong Yang, William J. Dally

CoRR, 2016

Angel-Eye: A Complete Design Flow for Mapping CNN onto Customized Hardware.

Kaiyuan Guo, Lingzhi Sui, Jiantao Qiu, Song Yao, Song Han, Yu Wang, Huazhong Yang

Proceedings of the IEEE Computer Society Annual Symposium on VLSI, 2016

EIE: Efficient Inference Engine on Compressed Deep Neural Network.

Song Han, Xingyu Liu, Huizi Mao, Jing Pu, Ardavan Pedram, Mark A. Horowitz, William J. Dally

Proceedings of the 43rd ACM/IEEE Annual International Symposium on Computer Architecture, 2016

Deep compression and EIE: Efficient inference engine on compressed deep neural network.

Song Han, Xingyu Liu, Huizi Mao, Jing Pu, Ardavan Pedram, Mark Horowitz, Bill Dally

Proceedings of the 2016 IEEE Hot Chips 28 Symposium (HCS), 2016

From model to FPGA: Software-hardware co-design for efficient neural network acceleration.

Kaiyuan Guo, Lingzhi Sui, Jiantao Qiu, Song Yao, Song Han, Yu Wang, Huazhong Yang

Proceedings of the 2016 IEEE Hot Chips 28 Symposium (HCS), 2016

Real-Time Pedestrian Detection and Tracking on Customized Hardware.

Junbin Wang, Ke Yan, Kaiyuan Guo, Jincheng Yu, Lingzhi Sui, Song Yao, Song Han, Yu Wang

Proceedings of the 14th ACM/IEEE Symposium on Embedded Systems for Real-Time Multimedia, 2016

2015

Learning both Weights and Connections for Efficient Neural Networks.

Song Han, Jeff Pool, John Tran, William J. Dally

CoRR, 2015

On-Demand Dynamic Branch Prediction.

Milad Mohammadi, Song Han, Tor M. Aamodt, William J. Dally

IEEE Comput. Archit. Lett., 2015

Learning both Weights and Connections for Efficient Neural Network.

Song Han, Jeff Pool, John Tran, William J. Dally

Proceedings of the Advances in Neural Information Processing Systems 28: Annual Conference on Neural Information Processing Systems 2015, 2015