CoGNN: Efficient Scheduling for Concurrent GNN Training on GPUs-Reference-Cited by-同舟云学术

CoGNN: Efficient Scheduling for Concurrent GNN Training on GPUs

Published:2022-11 Issue: Volume: Page:
ISSN:
Container-title:SC22: International Conference for High Performance Computing, Networking, Storage and Analysis
language:
Short-container-title:

Author:

Sun Qingxiao¹,Liu Yi¹,Yang Hailong¹,Zhang Ruizhe¹,Dun Ming¹,Li Mingzhen¹,Liu Xiaoyan¹,Xiao Wencong²,Li Yong²,Luan Zhongzhi¹,Qian Depei¹

Affiliation:

1. Beihang University,Beijing,China

2. Unaffiliated,Beijing,China

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10046045/10045783/10046055.pdf?arnumber=10046055

Reference65 articles.

1. {GRAPHENE}: Packing and {Dependency-Aware} scheduling for {Data-Parallel} clusters;grandl;12th USENIX Symposium on Operating Systems Design and Implementation (OSDI 16),0

2. {AntMan}: Dynamic scaling on {GPU} clusters for deep learning;xiao;14th USENIX Symposium on Operating Systems Design and Implementation (OSDI 20),0

3. Estimating GPU memory consumption of deep learning models

4. Gandiva: Introspective cluster scheduling for deep learning;xiao;13th USENIX Symposium on Operating Systems Design and Implementation (OSDI 18),0

5. Inductive representation learning on large graphs;hamilton;Advances in neural information processing systems,2017

Cited by 4 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. A Survey on Graph Neural Network Acceleration: A Hardware Perspective;Chinese Journal of Electronics;2024-05

2. MixRec: Orchestrating Concurrent Recommendation Model Training on CPU-GPU platform;2023 IEEE 41st International Conference on Computer Design (ICCD);2023-11-06

3. GPU Occupancy Prediction of Deep Learning Models Using Graph Neural Network;2023 IEEE International Conference on Cluster Computing (CLUSTER);2023-10-31

4. Towards GPU Memory Efficiency for Distributed Training at Scale;Proceedings of the 2023 ACM Symposium on Cloud Computing;2023-10-30