Helios: An Efficient Out-of-core GNN Training System on Terabyte-scale Graphs with In-memory Performance

J Sun, M Sun, Z Zhang, J Xie, Z Shi, Z Yang… - arXiv preprint arXiv …, 2023 - arxiv.org
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 …

OUTRE: An OUT-of-Core De-REdundancy GNN Training Framework for Massive Graphs within A Single Machine

Z Sheng, W Zhang, Y Tao, B Cui - Proceedings of the VLDB Endowment, 2024 - dl.acm.org
Sampling-based Graph Neural Networks (GNNs) have become the de facto standard for
handling various graph learning tasks on large-scale graphs. As the graph size grows larger …

BGS: Accelerate GNN training on multiple GPUs

Y Tan, Z Bai, D Liu, Z Zeng, Y Gan, A Ren… - Journal of Systems …, 2024 - Elsevier
Abstract Emerging Graph Neural Networks (GNNs) have made significant progress in
processing graph-structured data, yet existing GNN frameworks face scalability issues when …

FlashFlex: Accommodating Large Language Model Training over Heterogeneous Environment

R Yan, Y Jiang, W Tao, X Nie, B Cui, B Yuan - arXiv preprint arXiv …, 2024 - arxiv.org
Training large language model (LLM) is a computationally intensive task, which is typically
conducted in data centers with homogeneous high-performance GPUs. This paper explores …

In situ neighborhood sampling for large-scale GNN training

Y Song, PH Chen, Y Lu, N Abrar, V Kalavri - Proceedings of the 20th …, 2024 - dl.acm.org
Graph Neural Network (GNN) training algorithms commonly perform neighborhood
sampling to construct fixed-size mini-batches for weight aggregation on GPUs. State-of-the …

Exploring Page-based RDMA for Irregular GPU Workloads. A case study on NVMe-backed GNN Execution

B Wagley, P Markthub, J Crea, B Wu… - Proceedings of the 16th …, 2024 - dl.acm.org
Paged memory systems for GPUs like NVIDIA's Unified Virtual Memory, offer a simple
method for programmers to create out-of-core programs on GPUs. In the case of storage …