3 citations · 4 across the 3 of their papers we have counts for
4 papers
Breaking the Storage-Compute Bottleneck in Billion-Scale ANNS: A GPU-Driven Asynchronous I/O Framework
Yang Xiao, Mo Sun, Ziyu Song +4
With the advancement of information retrieval, recommendation systems, and Retrieval-Augmented Generation (RAG), Approximate Nearest Neighbor Search (ANNS) gains widespread applica…
TorchGT: A Holistic System for Large-scale Graph Transformer Training
Meng Zhang, Jie Sun, Qinghao Hu +4
Graph Transformer is a new architecture that surpasses GNNs in graph learning. While there emerge inspiring algorithm advancements, their practical adoption is still limited, parti…
Helios: An Efficient Out-of-core GNN Training System on Terabyte-scale Graphs with In-memory Performance
Jie Sun, Mo Sun, Zheng Zhang +6
Training graph neural networks (GNNs) on large-scale graph data holds immense promise for numerous real-world applications but remains a great challenge. Several disk-based GNN sys…
P4SGD: Programmable Switch Enhanced Model-Parallel Training on Generalized Linear Models on Distributed FPGAs
Hongjing Huang, Yingtao Li, Jie Sun +5
Generalized linear models (GLMs) are a widely utilized family of machine learning models in real-world applications. As data size increases, it is essential to perform efficient di…