3 papers
cs.DC2024
GeoT: Tensor Centric Library for Graph Neural Network via Efficient Segment Reduction on GPU
Zhongming Yu, Genghan Zhang, Hanxian Huang +2
In recent years, Graph Neural Networks (GNNs) have ignited a surge of innovation, significantly enhancing the processing of geometric data structures such as graphs, point clouds,…
cs.DC2023
TorchSparse++: Efficient Training and Inference Framework for Sparse Convolution on GPUs
Haotian Tang, Shang Yang, Zhijian Liu +6
Sparse convolution plays a pivotal role in emerging workloads, including point cloud processing in AR/VR, autonomous driving, and graph understanding in recommendation systems. Sin…
cs.IR2022
Analysis and Optimization of GNN-Based Recommender Systems on Persistent Memory
Yuwei Hu, Jiajie Li, Zhongming Yu +1
Graph neural networks (GNNs), which have emerged as an effective method for handling machine learning tasks on graphs, bring a new approach to building recommender systems, where t…