Youshan Miao

Publication Activity (10 Years)

Years Active: 2012-2024
Publications (10 Years): 25

Top Topics

Top Venues

IEEE Trans. Parallel Distributed Syst.

Publications

Zhiqi Lin, Youshan Miao, Guanbin Xu, Cheng Li, Olli Saarikivi, Saeed Maleki, Fan Yang
Tessel: Boosting Distributed Execution of Large DNN Models via Flexible Schedule Search. HPCA (2024)
Zhiqi Lin, Youshan Miao, Quanlu Zhang, Fan Yang, Yi Zhu, Cheng Li, Saeed Maleki, Xu Cao, Ning Shang, Yilei Yang, Weijiang Xu, Mao Yang, Lintao Zhang, Lidong Zhou
nnScaler: Constraint-Guided Parallelization Plan Generation for Deep Learning Training. OSDI (2024)
Guodong Liu, Youshan Miao, Zhiqi Lin, Xiaoxiang Shi, Saeed Maleki, Fan Yang, Yungang Bao, Sa Wang
Aceso: Efficient Parallel DNN Training through Iterative Bottleneck Alleviation. EuroSys (2024)
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
SuperScaler: Supporting Flexible DNN Parallelization via a Unified Abstraction. CoRR (2023)
Zhiqi Lin, Youshan Miao, Guanbin Xu, Cheng Li, Olli Saarikivi, Saeed Maleki, Fan Yang
Tessel: Boosting Distributed Execution of Large DNN Models via Flexible Schedule Search. CoRR (2023)
Yijia Zhang, Yibo Han, Shijie Cao, Guohao Dai, Youshan Miao, Ting Cao, Fan Yang, Ningyi Xu
Adam Accumulation to Reduce Memory Footprints of both Activations and Gradients for Large-scale DNN Training. CoRR (2023)
Yijia Zhang, Yibo Han, Shijie Cao, Guohao Dai, Youshan Miao, Ting Cao, Fan Yang, Ningyi Xu
Adam Accumulation to Reduce Memory Footprints of Both Activations and Gradients for Large-Scale DNN Training. ECAI (2023)
Abhinav Jangda, Jun Huang, Guodong Liu, Amir Hossein Nodehi Sabet, Saeed Maleki, Youshan Miao, Madanlal Musuvathi, Todd Mytkowicz, Olli Saarikivi
Breaking the computation and communication abstraction barrier in distributed machine learning workloads. ASPLOS (2022)
Cheng Luo, Lei Qu, Youshan Miao, Peng Cheng, Yongqiang Xiong
CrossoverScheduler: Overlapping Multiple Distributed Training Applications in a Crossover Manner. CoRR (2021)
Xiaonan Nie, Shijie Cao, Xupeng Miao, Lingxiao Ma, Jilong Xue, Youshan Miao, Zichao Yang, Zhi Yang, Bin Cui
Dense-to-Sparse Gate for Mixture-of-Experts. CoRR (2021)
Zhihui Zhang, Jingwen Leng, Shuwen Lu, Youshan Miao, Yijia Diao, Minyi Guo, Chao Li, Yuhao Zhu
ZIPPER: Exploiting Tile- and Operator-level Parallelism for General and Scalable Graph Neural Network Acceleration. CoRR (2021)
Abhinav Jangda, Jun Huang, Guodong Liu, Amir Hossein Nodehi Sabet, Saeed Maleki, Youshan Miao, Madanlal Musuvathi, Todd Mytkowicz, Olli Saarikivi
CoCoNet: Co-Optimizing Computation and Communication for Distributed Machine Learning. CoRR (2021)
Taehyun Kim, Changho Hwang, KyoungSoo Park, Zhiqi Lin, Peng Cheng, Youshan Miao, Lingxiao Ma, Yongqiang Xiong
Accelerating GNN training with locality-aware partial execution. APSys (2021)
Youhui Bai, Cheng Li, Zhiqi Lin, Yufei Wu, Youshan Miao, Yunxin Liu, Yinlong Xu
Efficient Data Loader for Fast Sampling-Based GNN Training on Large Graphs. IEEE Trans. Parallel Distributed Syst. 32 (10) (2021)
Hong Huang, Zixuan Fang, Xiao Wang, Youshan Miao, Hai Jin
Motif-Preserving Temporal Network Embedding. IJCAI (2020)
Zhihui Zhang, Jingwen Leng, Lingxiao Ma, Youshan Miao, Chao Li, Minyi Guo
Architectural Implications of Graph Neural Networks. CoRR (2020)
Lingxiao Ma, Zhiqiang Xie, Zhi Yang, Jilong Xue, Youshan Miao, Wei Cui, Wenxiang Hu, Fan Yang, Lintao Zhang, Lidong Zhou
Rammer: Enabling Holistic Deep Learning Compiler Optimizations with rTasks. OSDI (2020)
Wencong Xiao, Jilong Xue, Youshan Miao, Zhen Li, Cheng Chen, Ming Wu, Wei Li, Lidong Zhou
Distributed Graph Computation Meets Machine Learning. IEEE Trans. Parallel Distributed Syst. 31 (7) (2020)
Zhihui Zhang, Jingwen Leng, Lingxiao Ma, Youshan Miao, Chao Li, Minyi Guo
Architectural Implications of Graph Neural Networks. IEEE Comput. Archit. Lett. 19 (1) (2020)
Zhiqi Lin, Cheng Li, Youshan Miao, Yunxin Liu, Yinlong Xu
PaGraph: Scaling GNN training on large graphs via computation-aware caching. SoCC (2020)
Lingxiao Ma, Zhi Yang, Youshan Miao, Jilong Xue, Ming Wu, Lidong Zhou, Yafei Dai
NeuGraph: Parallel Deep Neural Network Computation on Large Graphs. USENIX Annual Technical Conference (2019)
Jilong Xue, Youshan Miao, Cheng Chen, Ming Wu, Lintao Zhang, Lidong Zhou
Fast Distributed Deep Learning over RDMA. EuroSys (2019)
Lingxiao Ma, Zhi Yang, Youshan Miao, Jilong Xue, Ming Wu, Lidong Zhou, Yafei Dai
Towards Efficient Large-Scale Graph Neural Network Computing. CoRR (2018)
Jilong Xue, Youshan Miao, Cheng Chen, Ming Wu, Lintao Zhang, Lidong Zhou
RPC Considered Harmful: Fast Distributed Deep Learning on RDMA. CoRR (2018)
Wencong Xiao, Jilong Xue, Youshan Miao, Zhen Li, Cheng Chen, Ming Wu, Wei Li, Lidong Zhou
: Distributed Graph Computation for Machine Learning. NSDI (2017)
Ming Wu, Fan Yang, Jilong Xue, Wencong Xiao, Youshan Miao, Lan Wei, Haoxiang Lin, Yafei Dai, Lidong Zhou
GraM: scaling graph computation to the trillions. SoCC (2015)
Youshan Miao, Wentao Han, Kaiwei Li, Ming Wu, Fan Yang, Lidong Zhou, Vijayan Prabhakaran, Enhong Chen, Wenguang Chen
ImmortalGraph: A System for Storage and Analysis of Temporal Graphs. ACM Trans. Storage 11 (3) (2015)
Wentao Han, Youshan Miao, Kaiwei Li, Ming Wu, Fan Yang, Lidong Zhou, Vijayan Prabhakaran, Wenguang Chen, Enhong Chen
Chronos: a graph engine for temporal graph analysis. EuroSys (2014)
Raymond Cheng, Ji Hong, Aapo Kyrola, Youshan Miao, Xuetian Weng, Ming Wu, Fan Yang, Lidong Zhou, Feng Zhao, Enhong Chen
Kineograph: taking the pulse of a fast-changing and connected world. EuroSys (2012)