Zobrazeno 1 - 10
of 79
pro vyhledávání: '"Zhong Yuchen"'
Heterogeneous Graph Neural Networks (HGNNs) leverage diverse semantic relationships in Heterogeneous Graphs (HetGs) and have demonstrated remarkable learning performance in various applications. However, current distributed GNN training systems often
Externí odkaz:
http://arxiv.org/abs/2408.09697
Publikováno v:
IEEE Transactions on Parallel and Distributed Systems ( Volume: 35, Issue: 9, September 2024)
As the size of deep learning models gets larger and larger, training takes longer time and more resources, making fault tolerance more and more critical. Existing state-of-the-art methods like CheckFreq and Elastic Horovod need to back up a copy of t
Externí odkaz:
http://arxiv.org/abs/2302.06173
Autor:
Hu, Hanpeng, Jiang, Chenyu, Zhong, Yuchen, Peng, Yanghua, Wu, Chuan, Zhu, Yibo, Lin, Haibin, Guo, Chuanxiong
Distributed training using multiple devices (e.g., GPUs) has been widely adopted for learning DNN models over large datasets. However, the performance of large-scale distributed training tends to be far from linear speed-up in practice. Given the com
Externí odkaz:
http://arxiv.org/abs/2205.02473
Image pixel aliasing caused by insufficient sampling is a long-standing problem in the field of computer graphics. It has always been the goal of researchers to seek anti-aliasing algorithms with high speed and good effect. Due to the deficiencies in
Externí odkaz:
http://arxiv.org/abs/2203.03870
Autor:
Qin, Jing, Ou, Dinghua, Yang, Ziheng, Gao, Xuesong, Zhong, Yuchen, Yang, Wanyu, Wu, Jiayi, Yang, Yajie, Xia, Jianguo, Liu, Yongpeng, Sun, Jun, Deng, Ouping
Publikováno v:
In Science of the Total Environment 15 June 2024 929
Communication overhead severely hinders the scalability of distributed machine learning systems. Recently, there has been a growing interest in using gradient compression to reduce the communication overhead of the distributed training. However, ther
Externí odkaz:
http://arxiv.org/abs/2105.07829
Publikováno v:
In International Journal of Hydrogen Energy 7 February 2024 54:1110-1119
Publikováno v:
In Theoretical and Applied Fracture Mechanics December 2023 128
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