40 citations · 40 across the 3 of their papers we have counts for
3 papers
cs.DC2023
HitGNN: High-throughput GNN Training Framework on CPU+Multi-FPGA Heterogeneous Platform
Yi-Chien Lin, Bingyi Zhang, Viktor Prasanna
As the size of real-world graphs increases, training Graph Neural Networks (GNNs) has become time-consuming and requires acceleration. While previous works have demonstrated the po…
cs.DC2023
HyScale-GNN: A Scalable Hybrid GNN Training System on Single-Node Heterogeneous Architecture
Yi-Chien Lin, Viktor Prasanna
Graph Neural Networks (GNNs) have shown success in many real-world applications that involve graph-structured data. Most of the existing single-node GNN training systems are capabl…
cs.DC2021★ 40 cited
HP-GNN: Generating High Throughput GNN Training Implementation on CPU-FPGA Heterogeneous Platform
Yi-Chien Lin, Bingyi Zhang, Viktor Prasanna
Graph Neural Networks (GNNs) have shown great success in many applications such as recommendation systems, molecular property prediction, traffic prediction, etc. Recently, CPU-FPG…