research
∙
01/16/2023
PIGEON: Optimizing CUDA Code Generator for End-to-End Training and Inference of Relational Graph Neural Networks
Relational graph neural networks (RGNNs) are graph neural networks (GNNs...
share
research
∙
07/13/2022
Fast Numerical Integration Techniques for 2.5-Dimensional Inverse Problems
Inverse scattering involving microwave and ultrasound waves require nume...
research
∙
11/10/2021
Graph Neural Network Training with Data Tiering
Graph Neural Networks (GNNs) have shown success in learning from graph-s...
research
∙
03/04/2021
Large Graph Convolutional Network Training with GPU-Oriented Data Communication Architecture
Graph Convolutional Networks (GCNs) are increasingly adopted in large-sc...
research
∙
01/20/2021
PyTorch-Direct: Enabling GPU Centric Data Access for Very Large Graph Neural Network Training with Irregular Accesses
With the increasing adoption of graph neural networks (GNNs) in the mach...
research
∙
09/15/2020
Petascale XCT: 3D Image Reconstruction with Hierarchical Communications on Multi-GPU Nodes
X-ray computed tomography is a commonly used technique for noninvasive i...
research
∙
07/28/2020