Youshan Miao

According to our database, Youshan Miao authored at least 25 papers between 2012 and 2024.

Collaborative distances:

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

2024

Tessel: Boosting Distributed Execution of Large DNN Models via Flexible Schedule Search.

Zhiqi Lin, Youshan Miao, Guanbin Xu, Cheng Li, Olli Saarikivi, Saeed Maleki, Fan Yang

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

Aceso: Efficient Parallel DNN Training through Iterative Bottleneck Alleviation.

Guodong Liu, Youshan Miao, Zhiqi Lin, Xiaoxiang Shi, Saeed Maleki, Fan Yang, Yungang Bao, Sa Wang

Proceedings of the Nineteenth European Conference on Computer Systems, 2024

2023

SuperScaler: Supporting Flexible DNN Parallelization via a Unified Abstraction.

Zhiqi Lin, Youshan Miao, Guodong Liu, Xiaoxiang Shi, Quanlu Zhang, Fan Yang, Saeed Maleki, Yi Zhu, Xu Cao, Cheng Li, Mao Yang, Lintao Zhang, Lidong Zhou

CoRR, 2023

Adam Accumulation to Reduce Memory Footprints of Both Activations and Gradients for Large-Scale DNN Training.

Yijia Zhang, Yibo Han, Shijie Cao, Guohao Dai, Youshan Miao, Ting Cao, Fan Yang, Ningyi Xu

Proceedings of the ECAI 2023 - 26th European Conference on Artificial Intelligence, September 30 - October 4, 2023, Kraków, Poland, 2023

2022

Breaking the computation and communication abstraction barrier in distributed machine learning workloads.

Abhinav Jangda, Jun Huang, Guodong Liu, Amir Hossein Nodehi Sabet, Saeed Maleki, Youshan Miao, Madanlal Musuvathi, Todd Mytkowicz, Olli Saarikivi

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

Efficient Data Loader for Fast Sampling-Based GNN Training on Large Graphs.

Youhui Bai, Cheng Li, Zhiqi Lin, Yufei Wu, Youshan Miao, Yunxin Liu, Yinlong Xu

IEEE Trans. Parallel Distributed Syst., 2021

Dense-to-Sparse Gate for Mixture-of-Experts.

Xiaonan Nie, Shijie Cao, Xupeng Miao, Lingxiao Ma, Jilong Xue, Youshan Miao, Zichao Yang, Zhi Yang, Bin Cui

CoRR, 2021

ZIPPER: Exploiting Tile- and Operator-level Parallelism for General and Scalable Graph Neural Network Acceleration.

Zhihui Zhang, Jingwen Leng, Shuwen Lu, Youshan Miao, Yijia Diao, Minyi Guo, Chao Li, Yuhao Zhu

CoRR, 2021

CoCoNet: Co-Optimizing Computation and Communication for Distributed Machine Learning.

Abhinav Jangda, Jun Huang, Guodong Liu, Amir Hossein Nodehi Sabet, Saeed Maleki, Youshan Miao, Madanlal Musuvathi, Todd Mytkowicz, Olli Saarikivi

CoRR, 2021

CrossoverScheduler: Overlapping Multiple Distributed Training Applications in a Crossover Manner.

Cheng Luo, Lei Qu, Youshan Miao, Peng Cheng, Yongqiang Xiong

CoRR, 2021

Accelerating GNN training with locality-aware partial execution.

Taehyun Kim, Changho Hwang, KyoungSoo Park, Zhiqi Lin, Peng Cheng, Youshan Miao, Lingxiao Ma, Yongqiang Xiong

Proceedings of the APSys '21: 12th ACM SIGOPS Asia-Pacific Workshop on Systems, 2021

2020

Distributed Graph Computation Meets Machine Learning.

Wencong Xiao, Jilong Xue, Youshan Miao, Zhen Li, Cheng Chen, Ming Wu, Wei Li, Lidong Zhou

IEEE Trans. Parallel Distributed Syst., 2020

Architectural Implications of Graph Neural Networks.

Zhihui Zhang, Jingwen Leng, Lingxiao Ma, Youshan Miao, Chao Li, Minyi Guo

IEEE Comput. Archit. Lett., 2020

Rammer: Enabling Holistic Deep Learning Compiler Optimizations with rTasks.

Lingxiao Ma, Zhiqiang Xie, Zhi Yang, Jilong Xue, Youshan Miao, Wei Cui, Wenxiang Hu, Fan Yang, Lintao Zhang, Lidong Zhou

Proceedings of the 14th USENIX Symposium on Operating Systems Design and Implementation, 2020

Motif-Preserving Temporal Network Embedding.

Hong Huang, Zixuan Fang, Xiao Wang, Youshan Miao, Hai Jin

Proceedings of the Twenty-Ninth International Joint Conference on Artificial Intelligence, 2020

PaGraph: Scaling GNN training on large graphs via computation-aware caching.

Zhiqi Lin, Cheng Li, Youshan Miao, Yunxin Liu, Yinlong Xu

Proceedings of the SoCC '20: ACM Symposium on Cloud Computing, 2020

2019

NeuGraph: Parallel Deep Neural Network Computation on Large Graphs.

Lingxiao Ma, Zhi Yang, Youshan Miao, Jilong Xue, Ming Wu, Lidong Zhou, Yafei Dai

Proceedings of the 2019 USENIX Annual Technical Conference, 2019

Fast Distributed Deep Learning over RDMA.

Jilong Xue, Youshan Miao, Cheng Chen, Ming Wu, Lintao Zhang, Lidong Zhou

Proceedings of the Fourteenth EuroSys Conference 2019, Dresden, Germany, March 25-28, 2019, 2019

2018

Towards Efficient Large-Scale Graph Neural Network Computing.

Lingxiao Ma, Zhi Yang, Youshan Miao, Jilong Xue, Ming Wu, Lidong Zhou, Yafei Dai

CoRR, 2018

RPC Considered Harmful: Fast Distributed Deep Learning on RDMA.

Jilong Xue, Youshan Miao, Cheng Chen, Ming Wu, Lintao Zhang, Lidong Zhou

CoRR, 2018

2017

Tux²: Distributed Graph Computation for Machine Learning.

Wencong Xiao, Jilong Xue, Youshan Miao, Zhen Li, Cheng Chen, Ming Wu, Wei Li, Lidong Zhou

Proceedings of the 14th USENIX Symposium on Networked Systems Design and Implementation, 2017

2015

ImmortalGraph: A System for Storage and Analysis of Temporal Graphs.

Youshan Miao, Wentao Han, Kaiwei Li, Ming Wu, Fan Yang, Lidong Zhou, Vijayan Prabhakaran, Enhong Chen, Wenguang Chen

ACM Trans. Storage, 2015

GraM: scaling graph computation to the trillions.

Ming Wu, Fan Yang, Jilong Xue, Wencong Xiao, Youshan Miao, Lan Wei, Haoxiang Lin, Yafei Dai, Lidong Zhou

Proceedings of the Sixth ACM Symposium on Cloud Computing, 2015

2014

Chronos: a graph engine for temporal graph analysis.

Wentao Han, Youshan Miao, Kaiwei Li, Ming Wu, Fan Yang, Lidong Zhou, Vijayan Prabhakaran, Wenguang Chen, Enhong Chen

Proceedings of the Ninth Eurosys Conference 2014, 2014

2012

Kineograph: taking the pulse of a fast-changing and connected world.

Raymond Cheng, Ji Hong, Aapo Kyrola, Youshan Miao, Xuetian Weng, Ming Wu, Fan Yang, Lidong Zhou, Feng Zhao, Enhong Chen

Proceedings of the European Conference on Computer Systems, 2012