Poster: Flexible Scheduling of Network and Computing Resources for Distributed AI Tasks
Author:
Affiliation:
1. Beijing University of Posts and Telecommunications, Beijing, China
2. Politecnico di Milano, Milano, Italy
3. Politecnico di Milano, Milano, Milano, Italy
Funder
National Key R&D Program of China
the Italian Ministry of University and Research (MUR) and the European Union (EU) under the PON/REACT project
Publisher
ACM
Link
https://dl.acm.org/doi/pdf/10.1145/3672202.3673744
Reference19 articles.
1. Communication-Efficient Distributed Learning: An Overview
2. MP-RDMA: Enabling RDMA With Multi-Path Transport in Datacenters
3. Poster: Continual Network Learning
4. Kaiming He, X. Zhang, Shaoqing Ren, and Jian Sun. 2015. Deep Residual Learning for Image Recognition. 2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR) (2015), 770--778. https://api.semanticscholar.org/CorpusID:206594692
5. RDMA acceleration method for long-distance optical networks. IEICE Technical Report; IEICE;Ichikawa Junki;Tech. Rep.,2021
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