Efficient Deep Learning Inference Based on Model Compression. - Qing Zhang; Mengru Zhang; Mengdi Wang; Wanchen Sui; Chen Meng; Jun Yang 052; Weidan Kong; Xiaoyuan Cui; Wei Lin 016 (CVPR Workshops, 2018)

FusionStitching: Deep Fusion and Code Generation for Tensorflow Computations on GPUs. - Guoping Long; Jun Yang 052; Kai Zhu; Wei Lin 016 (CoRR, 2018)

Graph-Adaptive Pruning for Efficient Inference of Convolutional Neural Networks. - Mengdi Wang; Qing Zhang; Jun Yang 052; Xiaoyuan Cui; Wei Lin 016 (CoRR, 2018)

Characterizing Deep Learning Training Workloads on Alibaba-PAI. - Mengdi Wang; Chen Meng; Guoping Long; Chuan Wu 001; Jun Yang 052; Wei Lin 016; Yangqing Jia (IISWC, 2019)

FusionStitching: Boosting Execution Efficiency of Memory Intensive Computations for DL Workloads. - Guoping Long; Jun Yang 052; Wei Lin 016 (CoRR, 2019)

Optimizing distributed training deployment in heterogeneous GPU clusters. - Xiaodong Yi 001; Shiwei Zhang 002; Ziyue Luo; Guoping Long; Lansong Diao; Chuan Wu 001; Zhen Zheng; Jun Yang 052; Wei Lin 016 (CoNEXT, 2020)

A History-Based Auto-Tuning Framework for Fast and High-Performance DNN Design on GPU. - Jiandong Mu; Mengdi Wang; Lanbo Li; Jun Yang 052; Wei Lin 016; Wei Zhang 012 (DAC, 2020)

Fast Training of Deep Learning Models over Multiple GPUs. - Xiaodong Yi 001; Ziyue Luo; Chen Meng; Mengdi Wang; Guoping Long; Chuan Wu 001; Jun Yang 052; Wei Lin 016 (Middleware, 2020)

Auto-MAP: A DQN Framework for Exploring Distributed Execution Plans for DNN Workloads. - Siyu Wang; Yi Rong; Shiqing Fan; Zhen Zheng; Lansong Diao; Guoping Long; Jun Yang 052; Xiaoyong Liu; Wei Lin 016 (CoRR, 2020)

FusionStitching: Boosting Memory Intensive Computations for Deep Learning Workloads. - Zhen Zheng; Pengzhan Zhao; Guoping Long; Feiwen Zhu; Kai Zhu; Wenyi Zhao; Lansong Diao; Jun Yang 052; Wei Lin 016 (CoRR, 2020)

INT8 Winograd Acceleration for Conv1D Equipped ASR Models Deployed on Mobile Devices. - Yiwu Yao; Yuchao Li; Chengyu Wang 001; Tianhang Yu; Houjiang Chen; Xiaotang Jiang; Jun Yang 052; Jun Huang 007; Wei Lin 016; Hui Shu; Chengfei Lv (CoRR, 2020)

EasyTransfer - A Simple and Scalable Deep Transfer Learning Platform for NLP Applications. - Minghui Qiu; Peng Li 056; Hanjie Pan; Chengyu Wang 001; Ang Wang; Cen Chen 001; Yaliang Li; Dehong Gao; Jun Huang 007; Yong Li 020; Jun Yang 052; Deng Cai 001; et al. (CoRR, 2020)

DISC: A Dynamic Shape Compiler for Machine Learning Workloads. - Kai Zhu; Wenyi Zhao; Zhen Zheng; Tianyou Guo; Pengzhan Zhao; Junjie Bai; Jun Yang 052; Xiaoyong Liu; Lansong Diao; Wei Lin 016 (EuroMLSys@EuroSys, 2021)

DAPPLE: a pipelined data parallel approach for training large models. - Shiqing Fan; Yi Rong; Chen Meng; Zongyan Cao; Siyu Wang; Zhen Zheng; Chuan Wu 001; Guoping Long; Jun Yang 052; Lixue Xia; Lansong Diao; Xiaoyong Liu; et al. (PPoPP, 2021)

AStitch: enabling a new multi-dimensional optimization space for memory-intensive ML training and inference on modern SIMT architectures. - Zhen Zheng; Xuanda Yang; Pengzhan Zhao; Guoping Long; Kai Zhu; Feiwen Zhu; Wenyi Zhao; Xiaoyong Liu; Jun Yang 052; Jidong Zhai; Shuaiwen Leon Song; Wei Lin 016 (ASPLOS, 2022)

Efficient Pipeline Planning for Expedited Distributed DNN Training. - Ziyue Luo; Xiaodong Yi 001; Guoping Long; Shiqing Fan; Chuan Wu 001; Jun Yang 052; Wei Lin 016 (INFOCOM, 2022)

Optimizing DNN Compilation for Distributed Training With Joint OP and Tensor Fusion. - Xiaodong Yi 001; Shiwei Zhang 002; Lansong Diao; Chuan Wu 001; Zhen Zheng; Shiqing Fan; Siyu Wang; Jun Yang 052; Wei Lin 016 (IEEE Trans. Parallel Distributed Syst., 2022)

Boosting the Convergence of Reinforcement Learning-Based Auto-Pruning Using Historical Data. - Jiandong Mu; Mengdi Wang; Feiwen Zhu; Jun Yang 052; Wei Lin 016; Wei Zhang 012 (IEEE Trans. Comput. Aided Des. Integr. Circuits Syst., 2024)