GDLL: A Scalable and Share Nothing Architecture Based Distributed Graph Neural Networks Framework

GDLL: A Scalable and Share Nothing Architecture Based Distributed Graph Neural Networks Framework

<p dir="ltr">Deep learning has recently been shown to be effective in uncovering hidden patterns in non-Euclidean space, where data is represented as graphs with complex object relationships and interdependencies. Because of the implicit data dependence in the big graphs with million...

Full description

Saved in:
Bibliographic Details
Main Author: Duong Thi Thu Van (19499206) (author)
Other Authors: Muhammad Numan Khan (6689816) (author), Tariq Habib Afridi (19499209) (author), Irfan Ullah (847820) (author), Aftab Alam (5158601) (author), Young-Koo Lee (19420543) (author)
Published: 2022
Subjects:
Engineering
Communications engineering
Information and computing sciences
Computer vision and multimedia computation
Machine learning
Graph neural networks
GNN
big graph learning
distributed GNN
large scale graph
graph learning
Training
Computational modeling
Servers
Libraries
Social networking (online)
Scalability
Message passing
Tags: Add Tag
No Tags, Be the first to tag this record!
Be the first to leave a comment!
You must be logged in first

Similar Items