Shaohuai Shi - RankMe

103 papers A* 15A 10B 8C 1Journal 58Unranked 11

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	Castor: Optimizing Deep Learning Job Scheduling in Multi-Tenant GPU Clusters via Intelligent Colocation. IEEE Trans. Cloud Comput. Yizhou Luo, Jiaxin Lai, Shaohuai Shi, Chen Chen, Shuhan Qi, Jiajia Zhang, Qiang Wang
2026	A*	`conf`	PipeDiT: Accelerating Diffusion Transformers in Video Generation with Task Pipelining and Model Decoupling. AAAI Sijie Wang, Qiang Wang, Shaohuai Shi
2026	A*	`conf`	SALR: Sparsity-Aware Low-Rank Representation for Efficient Fine-Tuning of Large Language Models. AAAI Longteng Zhang, Sen Wu, Shuai Hou, Zhengyu Qing, Zhuo Zheng, Danning Ke, Qihong Lin, Qiang Wang, Shaohuai Shi, Xiaowen Chu
2026	J	`jnl`	Sparsity-Aware Low-Rank Representation for Efficient Fine-Tuning of Large Language Models. CoRR Longteng Zhang, Sen Wu, Shuai Hou, Zhengyu Qing, Zhuo Zheng, Danning Ke, Qihong Lin, Qiang Wang, Shaohuai Shi, Xiaowen Chu
2025	—	`conf`	DeepFill: Accelerating MLLM Training by Filling Bubbles with Frozen Encoders. ICA3PP (6) Zhengyu Qing, Shaohuai Shi, Qiang Wang
2025	J	`jnl`	DreamDDP: Accelerating Data Parallel Distributed LLM Training with Layer-wise Scheduled Partial Synchronization. CoRR Zhenheng Tang, Zichen Tang, Junlin Huang, Xinglin Pan, Rudan Yan, Yuxin Wang, Amelie Chi Zhou, Shaohuai Shi, Xiaowen Chu, Bo Li
2025	J	`jnl`	Efficient MoE Inference with Fine-Grained Scheduling of Disaggregated Expert Parallelism. CoRR Xinglin Pan, Shaohuai Shi, Wenxiang Lin, Yuxin Wang, Zhenheng Tang, Wei Wang, Xiaowen Chu
2025	—	`conf`	FSMoE: A Flexible and Scalable Training System for Sparse Mixture-of-Experts Models. ASPLOS (1) Xinglin Pan, Wenxiang Lin, Lin Zhang, Shaohuai Shi, Zhenheng Tang, Rui Wang, Bo Li, Xiaowen Chu
2025	J	`jnl`	FSMoE: A Flexible and Scalable Training System for Sparse Mixture-of-Experts Models. CoRR Xinglin Pan, Wenxiang Lin, Lin Zhang, Shaohuai Shi, Zhenheng Tang, Rui Wang, Bo Li, Xiaowen Chu
2025	J	`jnl`	HierMoE: Accelerating MoE Training with Hierarchical Token Deduplication and Expert Swap. CoRR Wenxiang Lin, Xinglin Pan, Lin Zhang, Shaohuai Shi, Xuan Wang, Xiaowen Chu
2025	J	`jnl`	Janus: Disaggregating Attention and Experts for Scalable MoE Inference. CoRR Zhexiang Zhang, Ye Wang, Xiangyu Wang, Yumiao Zhao, Jingzhe Jiang, Qizhen Weng, Shaohuai Shi, Yin Chen, Minchen Yu
2025	A	`conf`	Mast: Efficient Training of Mixture-of-Experts Transformers with Task Pipelining and Ordering. ICDCS Wenxiang Lin, Xinglin Pan, Shaohuai Shi, Xuan Wang, Bo Li, Xiaowen Chu
2025	A	`conf`	Mitigating Contention in Stream Multiprocessors for Pipelined Mixture of Experts: An SM-Aware Scheduling Approach. ICDCS Xinglin Pan, Rui Wang, Wenxiang Lin, Shaohuai Shi, Xiaowen Chu
2025	J	`jnl`	PipeDiT: Accelerating Diffusion Transformers in Video Generation with Task Pipelining and Model Decoupling. CoRR Sijie Wang, Qiang Wang, Shaohuai Shi
2025	B	`conf`	QPO: Accelerating Memory-Efficient DNN Training with Quantization and Pipelining. ICPADS Xiang Fan, Shaohuai Shi
2025	J	`jnl`	Reasoning Language Model Inference Serving Unveiled: An Empirical Study. CoRR Qi Li, Junpan Wu, Xiang Liu, Yuxin Wang, Zeyu Li, Zhenheng Tang, Yuhan Chen, Shaohuai Shi, Xiaowen Chu
2025	J	`jnl`	RoPe-Door: Toward Robust and Persistent Backdoor Data Poisoning Attacks in Federated Learning. IEEE Netw. Ye Liu, Shan Chang, Denghui Li, Shaohuai Shi, Bo Li
2025	A*	`conf`	SP-MoE: Expediting Mixture-of-Experts Training with Optimized Pipelining Planning. INFOCOM Ne Wang, Wenxiang Lin, Lin Zhang, Shaohuai Shi, Ruiting Zhou, Bo Li
2025	—	`conf`	SQ-DeAR: Sparsified and Quantized Gradient Compression for Distributed Training. Euro-Par (3) Xinrui Yang, Shaohuai Shi
2025	—	`conf`	ScheInfer: Efficient Inference of Large Language Models with Task Scheduling on Moderate GPUs. Euro-Par (3) Wenxiang Lin, Xinglin Pan, Shaohuai Shi, Xuan Wang, Xiaowen Chu
2024	B	`conf`	Bandwidth-Aware and Overlap-Weighted Compression for Communication-Efficient Federated Learning. ICPP Zichen Tang, Junlin Huang, Rudan Yan, Yuxin Wang, Zhenheng Tang, Shaohuai Shi, Amelie Chi Zhou, Xiaowen Chu
2024	J	`jnl`	Bandwidth-Aware and Overlap-Weighted Compression for Communication-Efficient Federated Learning. CoRR Zichen Tang, Junlin Huang, Rudan Yan, Yuxin Wang, Zhenheng Tang, Shaohuai Shi, Amelie Chi Zhou, Xiaowen Chu
2024	J	`jnl`	ExpertFlow: Optimized Expert Activation and Token Allocation for Efficient Mixture-of-Experts Inference. CoRR Xin He, Shunkang Zhang, Yuxin Wang, Haiyan Yin, Zihao Zeng, Shaohuai Shi, Zhenheng Tang, Xiaowen Chu, Ivor W. Tsang, Yew-Soon Ong
2024	A*	`conf`	FedImpro: Measuring and Improving Client Update in Federated Learning. ICLR Zhenheng Tang, Yonggang Zhang, Shaohuai Shi, Xinmei Tian, Tongliang Liu, Bo Han, Xiaowen Chu
2024	J	`jnl`	FedImpro: Measuring and Improving Client Update in Federated Learning. CoRR Zhenheng Tang, Yonggang Zhang, Shaohuai Shi, Xinmei Tian, Tongliang Liu, Bo Han, Xiaowen Chu
2024	J	`jnl`	FusionLLM: A Decentralized LLM Training System on Geo-distributed GPUs with Adaptive Compression. CoRR Zhenheng Tang, Xueze Kang, Yiming Yin, Xinglin Pan, Yuxin Wang, Xin He, Qiang Wang, Rongfei Zeng, Kaiyong Zhao, Shaohuai Shi, Amelie Chi Zhou, Bo Li, Bingsheng He, Xiaowen Chu
2024	A*	`conf`	Parm: Efficient Training of Large Sparsely-Activated Models with Dedicated Schedules. INFOCOM Xinglin Pan, Wenxiang Lin, Shaohuai Shi, Xiaowen Chu, Weinong Sun, Bo Li
2024	J	`jnl`	Parm: Efficient Training of Large Sparsely-Activated Models with Dedicated Schedules. CoRR Xinglin Pan, Wenxiang Lin, Shaohuai Shi, Xiaowen Chu, Weinong Sun, Bo Li
2024	A	`conf`	Performance Analysis and Optimizations of Matrix Multiplications on ARMv8 Processors. DATE Hucheng Liu, Shaohuai Shi, Xuan Wang, Zoe L. Jiang, Qian Chen
2024	A	`conf`	ScheMoE: An Extensible Mixture-of-Experts Distributed Training System with Tasks Scheduling. EuroSys Shaohuai Shi, Xinglin Pan, Qiang Wang, Chengjian Liu, Xiaozhe Ren, Zhongzhe Hu, Yu Yang, Bo Li, Xiaowen Chu
2024	B	`conf`	Scheduling Deep Learning Jobs in Multi-Tenant GPU Clusters via Wise Resource Sharing. IWQoS Yizhou Luo, Qiang Wang, Shaohuai Shi, Jiaxin Lai, Shuhan Qi, Jiajia Zhang, Xuan Wang
2024	J	`jnl`	Scheduling Deep Learning Jobs in Multi-Tenant GPU Clusters via Wise Resource Sharing. CoRR Yizhou Luo, Qiang Wang, Shaohuai Shi, Jiaxin Lai, Shuhan Qi, Jiajia Zhang, Xuan Wang
2024	B	`conf`	Sparse Gradient Communication with AlltoAll for Accelerating Distributed Deep Learning. ICPP Jing Peng, Zihan Li, Shaohuai Shi, Bo Li
2024	J	`jnl`	Task Scheduling for Efficient Inference of Large Language Models on Single Moderate GPU Systems. CoRR Wenxiang Lin, Xinglin Pan, Shaohuai Shi, Xuan Wang, Xiaowen Chu
2023	J	`jnl`	A Generic Multi-Player Transformation Algorithm for Solving Large-Scale Zero-Sum Extensive-Form Adversarial Team Games. CoRR Chen Qiu, Yulin Wu, Weixin Huang, Botao Liu, Shaohuai Shi, Xuan Wang
2023	A*	`conf`	Accelerating Distributed K-FAC with Efficient Collective Communication and Scheduling. INFOCOM Lin Zhang, Shaohuai Shi, Bo Li
2023	A	`conf`	DeAR: Accelerating Distributed Deep Learning with Fine-Grained All-Reduce Pipelining. ICDCS Lin Zhang, Shaohuai Shi, Xiaowen Chu, Wei Wang, Bo Li, Chengjian Liu
2023	J	`jnl`	Decoupling the All-Reduce Primitive for Accelerating Distributed Deep Learning. CoRR Lin Zhang, Shaohuai Shi, Xiaowen Chu, Wei Wang, Bo Li, Chengjian Liu
2023	J	`jnl`	Dissecting the Runtime Performance of the Training, Fine-tuning, and Inference of Large Language Models. CoRR Longteng Zhang, Xiang Liu, Zeyu Li, Xinglin Pan, Peijie Dong, Ruibo Fan, Rui Guo, Xin Wang, Qiong Luo, Shaohuai Shi, Xiaowen Chu
2023	J	`jnl`	Eva: A General Vectorized Approximation Framework for Second-order Optimization. CoRR Lin Zhang, Shaohuai Shi, Bo Li
2023	A*	`conf`	Eva: Practical Second-order Optimization with Kronecker-vectorized Approximation. ICLR Lin Zhang, Shaohuai Shi, Bo Li
2023	A	`conf`	Evaluation and Optimization of Gradient Compression for Distributed Deep Learning. ICDCS Lin Zhang, Longteng Zhang, Shaohuai Shi, Xiaowen Chu, Bo Li
2023	J	`jnl`	Evaluation and Optimization of Gradient Compression for Distributed Deep Learning. CoRR Lin Zhang, Longteng Zhang, Shaohuai Shi, Xiaowen Chu, Bo Li
2023	J	`jnl`	FedML Parrot: A Scalable Federated Learning System via Heterogeneity-aware Scheduling on Sequential and Hierarchical Training. CoRR Zhenheng Tang, Xiaowen Chu, Ryan Yide Ran, Sunwoo Lee, Shaohuai Shi, Yonggang Zhang, Yuxin Wang, Alex Qiaozhong Liang, Salman Avestimehr, Chaoyang He
2023	J	`jnl`	FusionAI: Decentralized Training and Deploying LLMs with Massive Consumer-Level GPUs. CoRR Zhenheng Tang, Yuxin Wang, Xin He, Longteng Zhang, Xinglin Pan, Qiang Wang, Rongfei Zeng, Kaiyong Zhao, Shaohuai Shi, Bingsheng He, Xiaowen Chu
2023	J	`jnl`	GossipFL: A Decentralized Federated Learning Framework With Sparsified and Adaptive Communication. IEEE Trans. Parallel Distributed Syst. Zhenheng Tang, Shaohuai Shi, Bo Li, Xiaowen Chu
2023	J	`jnl`	LoRA-FA: Memory-efficient Low-rank Adaptation for Large Language Models Fine-tuning. CoRR Longteng Zhang, Lin Zhang, Shaohuai Shi, Xiaowen Chu, Bo Li
2023	A*	`conf`	PipeMoE: Accelerating Mixture-of-Experts through Adaptive Pipelining. INFOCOM Shaohuai Shi, Xinglin Pan, Xiaowen Chu, Bo Li
2023	J	`jnl`	Reliable and Efficient In-Memory Fault Tolerance of Large Language Model Pretraining. CoRR Yuxin Wang, Shaohuai Shi, Xin He, Zhenheng Tang, Xinglin Pan, Yang Zheng, Xiaoyu Wu, Amelie Chi Zhou, Bingsheng He, Xiaowen Chu
2023	J	`jnl`	Scalable K-FAC Training for Deep Neural Networks With Distributed Preconditioning. IEEE Trans. Cloud Comput. Lin Zhang, Shaohuai Shi, Wei Wang, Bo Li
2022	J	`jnl`	An Efficient Split Fine-tuning Framework for Edge and Cloud Collaborative Learning. CoRR Shaohuai Shi, Qing Yang, Yang Xiang, Shuhan Qi, Xuan Wang
2022	—	`conf`	EASNet: Searching Elastic and Accurate Network Architecture for Stereo Matching. ECCV (32) Qiang Wang, Shaohuai Shi, Kaiyong Zhao, Xiaowen Chu
2022	J	`jnl`	EASNet: Searching Elastic and Accurate Network Architecture for Stereo Matching. CoRR Qiang Wang, Shaohuai Shi, Kaiyong Zhao, Xiaowen Chu
2022	J	`jnl`	Nebula-I: A General Framework for Collaboratively Training Deep Learning Models on Low-Bandwidth Cloud Clusters. CoRR Yang Xiang, Zhihua Wu, Weibao Gong, Siyu Ding, Xianjie Mo, Yuang Liu, Shuohuan Wang, Peng Liu, Yongshuai Hou, Long Li, Bin Wang, Shaohuai Shi, Yaqian Han, Yue Yu, Ge Li, Yu Sun, Yanjun Ma, Dianhai Yu
2022	J	`jnl`	Scalable K-FAC Training for Deep Neural Networks with Distributed Preconditioning. CoRR Lin Zhang, Shaohuai Shi, Wei Wang, Bo Li
2022	A*	`conf`	Virtual Homogeneity Learning: Defending against Data Heterogeneity in Federated Learning. ICML Zhenheng Tang, Yonggang Zhang, Shaohuai Shi, Xin He, Bo Han, Xiaowen Chu
2022	J	`jnl`	Virtual Homogeneity Learning: Defending against Data Heterogeneity in Federated Learning. CoRR Zhenheng Tang, Yonggang Zhang, Shaohuai Shi, Xin He, Bo Han, Xiaowen Chu
2021	J	`jnl`	A Quantitative Survey of Communication Optimizations in Distributed Deep Learning. IEEE Netw. Shaohuai Shi, Zhenheng Tang, Xiaowen Chu, Chengjian Liu, Wei Wang, Bo Li
2021	A	`conf`	Accelerating Distributed K-FAC with Smart Parallelism of Computing and Communication Tasks. ICDCS Shaohuai Shi, Lin Zhang, Bo Li
2021	J	`jnl`	Accelerating Distributed K-FAC with Smart Parallelism of Computing and Communication Tasks. CoRR Shaohuai Shi, Lin Zhang, Bo Li
2021	J	`jnl`	Automated Model Design and Benchmarking of 3D Deep Learning Models for COVID-19 Detection with Chest CT Scans. CoRR Xin He, Shihao Wang, Xiaowen Chu, Shaohuai Shi, Jiangping Tang, Xin Liu, Chenggang Yan, Jiyong Zhang, Guiguang Ding
2021	A*	`conf`	Automated Model Design and Benchmarking of Deep Learning Models for COVID-19 Detection with Chest CT Scans. AAAI Xin He, Shihao Wang, Xiaowen Chu, Shaohuai Shi, Jiangping Tang, Xin Liu, Chenggang Yan, Jiyong Zhang, Guiguang Ding
2021	A*	`conf`	Exploiting Simultaneous Communications to Accelerate Data Parallel Distributed Deep Learning. INFOCOM Shaohuai Shi, Xiaowen Chu, Bo Li
2021	J	`jnl`	FADNet++: Real-Time and Accurate Disparity Estimation with Configurable Networks. CoRR Qiang Wang, Shaohuai Shi, Shizhen Zheng, Kaiyong Zhao, Xiaowen Chu
2021	J	`jnl`	MG-WFBP: Merging Gradients Wisely for Efficient Communication in Distributed Deep Learning. IEEE Trans. Parallel Distributed Syst. Shaohuai Shi, Xiaowen Chu, Bo Li
2021	—	`conf`	Towards Scalable Distributed Training of Deep Learning on Public Cloud Clusters. MLSys Shaohuai Shi, Xianhao Zhou, Shutao Song, Xingyao Wang, Zilin Zhu, Xue Huang, Xinan Jiang, Feihu Zhou, Zhenyu Guo, Liqiang Xie, Rui Lan, Xianbin Ouyang, Yan Zhang, Jieqian Wei, Jing Gong, Weiliang Lin, Ping Gao, Peng Meng, Xiaomin Xu, Chenyang Guo, Bo Yang, Zhibo Chen, Yongjian Wu, Xiaowen Chu
2020	B	`conf`	Benchmarking the Performance and Energy Efficiency of AI Accelerators for AI Training. CCGRID Yuxin Wang, Qiang Wang, Shaohuai Shi, Xin He, Zhenheng Tang, Kaiyong Zhao, Xiaowen Chu
2020	J	`jnl`	Communication Contention Aware Scheduling of Multiple Deep Learning Training Jobs. CoRR Qiang Wang, Shaohuai Shi, Canhui Wang, Xiaowen Chu
2020	A	`conf`	Communication-Efficient Decentralized Learning with Sparsification and Adaptive Peer Selection. ICDCS Zhenheng Tang, Shaohuai Shi, Xiaowen Chu
2020	J	`jnl`	Communication-Efficient Decentralized Learning with Sparsification and Adaptive Peer Selection. CoRR Zhenheng Tang, Shaohuai Shi, Xiaowen Chu
2020	A*	`conf`	Communication-Efficient Distributed Deep Learning with Merged Gradient Sparsification on GPUs. INFOCOM Shaohuai Shi, Qiang Wang, Xiaowen Chu, Bo Li, Yang Qin, Ruihao Liu, Xinxiao Zhao
2020	J	`jnl`	Communication-Efficient Distributed Deep Learning: A Comprehensive Survey. CoRR Zhenheng Tang, Shaohuai Shi, Xiaowen Chu, Wei Wang, Bo Li
2020	J	`jnl`	Communication-Efficient Distributed Deep Learning: Survey, Evaluation, and Challenges. CoRR Shaohuai Shi, Zhenheng Tang, Xiaowen Chu, Chengjian Liu, Wei Wang, Bo Li
2020	B	`conf`	Efficient Sparse-Dense Matrix-Matrix Multiplication on GPUs Using the Customized Sparse Storage Format. ICPADS Shaohuai Shi, Qiang Wang, Xiaowen Chu
2020	J	`jnl`	Efficient Sparse-Dense Matrix-Matrix Multiplication on GPUs Using the Customized Sparse Storage Format. CoRR Shaohuai Shi, Qiang Wang, Xiaowen Chu
2020	A*	`conf`	FADNet: A Fast and Accurate Network for Disparity Estimation. ICRA Qiang Wang, Shaohuai Shi, Shizhen Zheng, Kaiyong Zhao, Xiaowen Chu
2020	J	`jnl`	FADNet: A Fast and Accurate Network for Disparity Estimation. CoRR Qiang Wang, Shaohuai Shi, Shizhen Zheng, Kaiyong Zhao, Xiaowen Chu
2020	A	`conf`	Layer-Wise Adaptive Gradient Sparsification for Distributed Deep Learning with Convergence Guarantees. ECAI Shaohuai Shi, Zhenheng Tang, Qiang Wang, Kaiyong Zhao, Xiaowen Chu
2020	J	`jnl`	Towards Scalable Distributed Training of Deep Learning on Public Cloud Clusters. CoRR Shaohuai Shi, Xianhao Zhou, Shutao Song, Xingyao Wang, Zilin Zhu, Xue Huang, Xinan Jiang, Feihu Zhou, Zhenyu Guo, Liqiang Xie, Rui Lan, Xianbin Ouyang, Yan Zhang, Jieqian Wei, Jing Gong, Weiliang Lin, Ping Gao, Peng Meng, Xiaomin Xu, Chenyang Guo, Bo Yang, Zhibo Chen, Yongjian Wu, Xiaowen Chu
2019	A*	`conf`	A Convergence Analysis of Distributed SGD with Communication-Efficient Gradient Sparsification. IJCAI Shaohuai Shi, Kaiyong Zhao, Qiang Wang, Zhenheng Tang, Xiaowen Chu
2019	A	`conf`	A Distributed Synchronous SGD Algorithm with Global Top-k Sparsification for Low Bandwidth Networks. ICDCS Shaohuai Shi, Qiang Wang, Kaiyong Zhao, Zhenheng Tang, Yuxin Wang, Xiang Huang, Xiaowen Chu
2019	J	`jnl`	A Distributed Synchronous SGD Algorithm with Global Top-k Sparsification for Low Bandwidth Networks. CoRR Shaohuai Shi, Qiang Wang, Kaiyong Zhao, Zhenheng Tang, Yuxin Wang, Xiang Huang, Xiaowen Chu
2019	—	`conf`	Computer-Aided Clinical Skin Disease Diagnosis Using CNN and Object Detection Models. IEEE BigData Xin He, Xiaoming Liu, Zhili Wu, Wu Yu, Xiaowen Chu, Shihao Wang, Shaohuai Shi, Zhenheng Tang, Yuxin Wang, Zhihao Zhao, Jing Dai, Ronghao Ni, Xiaofeng Zhang
2019	J	`jnl`	Computer-Aided Clinical Skin Disease Diagnosis Using CNN and Object Detection Models. CoRR Xin He, Shihao Wang, Shaohuai Shi, Zhenheng Tang, Yuxin Wang, Zhihao Zhao, Jing Dai, Ronghao Ni, Xiaofeng Zhang, Xiaoming Liu, Zhili Wu, Wu Yu, Xiaowen Chu
2019	J	`jnl`	Layer-wise Adaptive Gradient Sparsification for Distributed Deep Learning with Convergence Guarantees. CoRR Shaohuai Shi, Zhenheng Tang, Qiang Wang, Kaiyong Zhao, Xiaowen Chu
2019	A*	`conf`	MG-WFBP: Efficient Data Communication for Distributed Synchronous SGD Algorithms. INFOCOM Shaohuai Shi, Xiaowen Chu, Bo Li
2019	J	`jnl`	MG-WFBP: Merging Gradients Wisely for Efficient Communication in Distributed Deep Learning. CoRR Shaohuai Shi, Xiaowen Chu, Bo Li
2019	J	`jnl`	Understanding Top-k Sparsification in Distributed Deep Learning. CoRR Shaohuai Shi, Xiaowen Chu, Ka Chun Cheung, Simon See
2018	B	`conf`	A DAG Model of Synchronous Stochastic Gradient Descent in Distributed Deep Learning. ICPADS Shaohuai Shi, Qiang Wang, Xiaowen Chu, Bo Li
2018	J	`jnl`	Highly Scalable Deep Learning Training System with Mixed-Precision: Training ImageNet in Four Minutes. CoRR Xianyan Jia, Shutao Song, Wei He, Yangzihao Wang, Haidong Rong, Feihu Zhou, Liqiang Xie, Zhenyu Guo, Yuanzhou Yang, Liwei Yu, Tiegang Chen, Guangxiao Hu, Shaohuai Shi, Xiaowen Chu
2018	J	`jnl`	MG-WFBP: Efficient Data Communication for Distributed Synchronous SGD Algorithms. CoRR Shaohuai Shi, Xiaowen Chu, Bo Li
2018	J	`jnl`	Modeling and Evaluation of Synchronous Stochastic Gradient Descent in Distributed Deep Learning on Multiple GPUs. CoRR Shaohuai Shi, Qiang Wang, Xiaowen Chu, Bo Li
2018	—	`conf`	Performance Modeling and Evaluation of Distributed Deep Learning Frameworks on GPUs. DASC/PiCom/DataCom/CyberSciTech Shaohuai Shi, Qiang Wang, Xiaowen Chu
2017	J	`jnl`	Improving the Performance of Fully Connected Neural Networks by Out-of-Place Matrix Transpose. CoRR Shaohuai Shi, Pengfei Xu, Xiaowen Chu
2017	—	`conf`	Performance Evaluation of Deep Learning Tools in Docker Containers. BigCom Pengfei Xu, Shaohuai Shi, Xiaowen Chu
2017	J	`jnl`	Performance Evaluation of Deep Learning Tools in Docker Containers. CoRR Pengfei Xu, Shaohuai Shi, Xiaowen Chu
2017	J	`jnl`	Performance Modeling and Evaluation of Distributed Deep Learning Frameworks on GPUs. CoRR Shaohuai Shi, Xiaowen Chu
2017	J	`jnl`	Speeding up Convolutional Neural Networks By Exploiting the Sparsity of Rectifier Units. CoRR Shaohuai Shi, Xiaowen Chu
2017	B	`conf`	Supervised Learning Based Algorithm Selection for Deep Neural Networks. ICPADS Shaohuai Shi, Pengfei Xu, Xiaowen Chu
2016	—	`conf`	Benchmarking State-of-the-Art Deep Learning Software Tools. CCBD Shaohuai Shi, Qiang Wang, Pengfei Xu, Xiaowen Chu
2016	J	`jnl`	Benchmarking State-of-the-Art Deep Learning Software Tools. CoRR Shaohuai Shi, Qiang Wang, Pengfei Xu, Xiaowen Chu
2011	—	`conf`	Mixed Precision Method for GPU-based FFT. CSE Shuhan Qi, Xuan Wang, Shaohuai Shi
2010	C	`conf`	The GPU-based String Matching System in Advanced AC Algorithm. CIT Jiang-Feng Peng, Hu Chen, Shaohuai Shi