3 citations · 4 across the 2 of their papers we have counts for
3 papers
cs.LG2021
Large Graph Convolutional Network Training with GPU-Oriented Data Communication Architecture
Seung Won Min, Kun Wu, Sitao Huang +5
Graph Convolutional Networks (GCNs) are increasingly adopted in large-scale graph-based recommender systems. Training GCN requires the minibatch generator traversing graphs and sam…
cs.LG2021★ 3 cited
PyTorch-Direct: Enabling GPU Centric Data Access for Very Large Graph Neural Network Training with Irregular Accesses
Seung Won Min, Kun Wu, Sitao Huang +5
With the increasing adoption of graph neural networks (GNNs) in the machine learning community, GPUs have become an essential tool to accelerate GNN training. However, training GNN…
cs.DC2020★ 1 cited
TEMPI: An Interposed MPI Library with a Canonical Representation of CUDA-aware Datatypes
Carl Pearson, Kun Wu, I-Hsin Chung +2
MPI derived datatypes are an abstraction that simplifies handling of non-contiguous data in MPI applications. These datatypes are recursively constructed at runtime from primitive…