A multi-objective partitioning algorithm for large-scale graph based on NSGA-II
H Cui, F Cao, R Liu - Expert Systems with Applications, 2025 - Elsevier
Graph partitioning plays a crucial role in distributed graph computation. The existing
algorithms often formulate the partition problem as a single objective optimization problem …
algorithms often formulate the partition problem as a single objective optimization problem …
Performance optimization of heterogeneous computing for large-scale dynamic graph data
H Wang, W Guo, M Zhang - The Journal of Supercomputing, 2025 - Springer
The performance of machines has not been fully exploited when processing large-scale
dynamic graph in heterogeneous GPU clusters. To improve the performance of graph …
dynamic graph in heterogeneous GPU clusters. To improve the performance of graph …
TLGPA: Two-Level Graph Partitioning Algorithm under Multi-Machine Multi-Card System
H Cui, S Lv - 2024 27th International Conference on Computer …, 2024 - ieeexplore.ieee.org
Recently, the distributed graph processing systems are widely deployed on the cluster of
computers with multiple accelerating cards, but as the basis of these systems, the traditional …
computers with multiple accelerating cards, but as the basis of these systems, the traditional …
GraphDHT: Scaling Graph Neural Networks' Distributed Training on Edge Devices on a Peer-to-Peer Distributed Hash Table Network
C Gupta - 2024 - vtechworks.lib.vt.edu
This thesis presents an innovative strategy for distributed Graph Neural Network (GNN)
training, leveraging a peer-to-peer network of heterogeneous edge devices interconnected …
training, leveraging a peer-to-peer network of heterogeneous edge devices interconnected …