Hyperscale FPGA-as-a-service architecture for large-scale distributed graph neural network
Shuangchen Li, Dimin Niu, Yuhao Wang, Wei Han, Zhe Zhang, Tianchan Guan, Yijin Guan, Heng Liu, Linyong Huang, Zhaoyang Du, Fei Xue, Yuanwei Fang, Hongzhong Zheng, Yuan Xie
Abstract
Graph neural network (GNN) is a promising emerging application for link prediction, recommendation, etc. Existing hardware innovation is limited to single-machine GNN (SM-GNN), however, the enterprises usually adopt huge graph with large-scale distributed GNN (LSD-GNN) that has to be carried out with distributed in-memory storage. The LSD-GNN is very different from SM-GNN in terms of system architecture demand, workflow and operators, and hence characterizations.
Topics & Concepts
Computer scienceWorkflowField-programmable gate arrayArchitectureGraphDistributed computingEmbedded systemTheoretical computer scienceDatabaseArtVisual artsAdvanced Graph Neural NetworksGraph Theory and AlgorithmsNetwork Packet Processing and Optimization