Jun Yang

According to our database, Jun Yang authored at least 18 papers between 2018 and 2024.

Collaborative distances:

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

2024

Boosting the Convergence of Reinforcement Learning-Based Auto-Pruning Using Historical Data.

Jiandong Mu, Mengdi Wang, Feiwen Zhu, Jun Yang, Wei Lin, Wei Zhang

IEEE Trans. Comput. Aided Des. Integr. Circuits Syst., February, 2024

2022

Optimizing DNN Compilation for Distributed Training With Joint OP and Tensor Fusion.

Xiaodong Yi, Shiwei Zhang, Lansong Diao, Chuan Wu, Zhen Zheng, Shiqing Fan, Siyu Wang, Jun Yang, Wei Lin

IEEE Trans. Parallel Distributed Syst., 2022

Efficient Pipeline Planning for Expedited Distributed DNN Training.

Ziyue Luo, Xiaodong Yi, Guoping Long, Shiqing Fan, Chuan Wu, Jun Yang, Wei Lin

Proceedings of the IEEE INFOCOM 2022, 2022

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, Jidong Zhai, Shuaiwen Leon Song, Wei Lin

Proceedings of the ASPLOS '22: 27th ACM International Conference on Architectural Support for Programming Languages and Operating Systems, Lausanne, Switzerland, 28 February 2022, 2022

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, Guoping Long, Jun Yang, Lixue Xia, Lansong Diao, Xiaoyong Liu, Wei Lin

Proceedings of the PPoPP '21: 26th ACM SIGPLAN Symposium on Principles and Practice of Parallel Programming, 2021

DISC: A Dynamic Shape Compiler for Machine Learning Workloads.

Kai Zhu, Wenyi Zhao, Zhen Zheng, Tianyou Guo, Pengzhan Zhao, Junjie Bai, Jun Yang, Xiaoyong Liu, Lansong Diao, Wei Lin

Proceedings of the EuroMLSys@EuroSys 2021, 2021

2020

EasyTransfer - A Simple and Scalable Deep Transfer Learning Platform for NLP Applications.

Minghui Qiu, Peng Li, Hanjie Pan, Chengyu Wang, Ang Wang, Cen Chen, Yaliang Li, Dehong Gao, Jun Huang, Yong Li, Jun Yang, Deng Cai, Wei Lin

CoRR, 2020

INT8 Winograd Acceleration for Conv1D Equipped ASR Models Deployed on Mobile Devices.

Yiwu Yao, Yuchao Li, Chengyu Wang, Tianhang Yu, Houjiang Chen, Xiaotang Jiang, Jun Yang, Jun Huang, Wei Lin, Hui Shu, Chengfei Lv

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, Wei Lin

CoRR, 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, Xiaoyong Liu, Wei Lin

CoRR, 2020

Fast Training of Deep Learning Models over Multiple GPUs.

Xiaodong Yi, Ziyue Luo, Chen Meng, Mengdi Wang, Guoping Long, Chuan Wu, Jun Yang, Wei Lin

Proceedings of the Middleware '20: 21st International Middleware Conference, 2020

A History-Based Auto-Tuning Framework for Fast and High-Performance DNN Design on GPU.

Jiandong Mu, Mengdi Wang, Lanbo Li, Jun Yang, Wei Lin, Wei Zhang

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

Optimizing distributed training deployment in heterogeneous GPU clusters.

Xiaodong Yi, Shiwei Zhang, Ziyue Luo, Guoping Long, Lansong Diao, Chuan Wu, Zhen Zheng, Jun Yang, Wei Lin

Proceedings of the CoNEXT '20: The 16th International Conference on emerging Networking EXperiments and Technologies, 2020

2019

FusionStitching: Boosting Execution Efficiency of Memory Intensive Computations for DL Workloads.

Guoping Long, Jun Yang, Wei Lin

CoRR, 2019

Characterizing Deep Learning Training Workloads on Alibaba-PAI.

Mengdi Wang, Chen Meng, Guoping Long, Chuan Wu, Jun Yang, Wei Lin, Yangqing Jia

Proceedings of the IEEE International Symposium on Workload Characterization, 2019

2018

Graph-Adaptive Pruning for Efficient Inference of Convolutional Neural Networks.

Mengdi Wang, Qing Zhang, Jun Yang, Xiaoyuan Cui, Wei Lin

CoRR, 2018

FusionStitching: Deep Fusion and Code Generation for Tensorflow Computations on GPUs.

Guoping Long, Jun Yang, Kai Zhu, Wei Lin

CoRR, 2018

Efficient Deep Learning Inference Based on Model Compression.

Qing Zhang, Mengru Zhang, Mengdi Wang, Wanchen Sui, Chen Meng, Jun Yang, Weidan Kong, Xiaoyuan Cui, Wei Lin

Proceedings of the 2018 IEEE Conference on Computer Vision and Pattern Recognition Workshops, 2018