Understanding the Design Space of Sparse/Dense Multiphase Dataflows for Mapping Graph Neural Networks on Spatial Accelerators-Reference-Cited by-同舟云学术

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Understanding the Design Space of Sparse/Dense Multiphase Dataflows for Mapping Graph Neural Networks on Spatial Accelerators

Published:2021-09-01 Issue: Volume: Page:
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Author:

Garg Raveesh¹,Qin Eric¹,Martinez Francisco²,Guirado Robert³,Jain Akshay⁴,Abadal Sergi³,Abellan Jose⁵,Acacio Manuel²,Alarcon Eduard³,Rajamanickam Sivasankaran⁶,Krishna Tushar⁷

Affiliation:

1. Georgia Institute of Technology, Atlanta, GA (United States)

2. Universidad de Murcia (Spain)

3. Univ. Politecnica de Catalunya (Spain)

4. Neutroon, Barcelona (Spain)

5. Universidad Católica de Murcia (Spain)

6. Sandia National Lab. (SNL-NM), Albuquerque, NM (United States)

7. Georgia Inst. of Technology, Atlanta, GA (United States)

Publisher

Office of Scientific and Technical Information (OSTI)

Cited by 3 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. Parallel and Distributed Graph Neural Networks: An In-Depth Concurrency Analysis;IEEE Transactions on Pattern Analysis and Machine Intelligence;2024-05

2. Ontology Based Agriculture Data Mining using IWO and RNN;2023 6th International Conference on Information Systems and Computer Networks (ISCON);2023-03-03

3. Accelerating Graph Neural Networks in Pytorch with HLS and Deep Dataflows;Applied Reconfigurable Computing. Architectures, Tools, and Applications;2023

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