74 citations · 87 across the 3 of their papers we have counts for
4 papers
Measuring and Improving the Use of Graph Information in Graph Neural Networks
Yifan Hou, Jian Zhang, James Cheng +4
Graph neural networks (GNNs) have been widely used for representation learning on graph data. However, there is limited understanding on how much performance GNNs actually gain fro…
Serving DNN Models with Multi-Instance GPUs: A Case of the Reconfigurable Machine Scheduling Problem
Cheng Tan, Zhichao Li, Jian Zhang +5
Multi-Instance GPU (MIG) is a new feature introduced by NVIDIA A100 GPUs that partitions one physical GPU into multiple GPU instances. With MIG, A100 can be the most cost-efficient…
G-Tran: Making Distributed Graph Transactions Fast
Hongzhi Chen, Changji Li, Chenguang Zheng +4
Graph transaction processing raises many unique challenges such as random data access due to the irregularity of graph structures, low throughput and high abort rate due to the rel…
Understanding Graph Neural Networks from Graph Signal Denoising Perspectives
Guoji Fu, Yifan Hou, Jian Zhang +3
Graph neural networks (GNNs) have attracted much attention because of their excellent performance on tasks such as node classification. However, there is inadequate understanding o…