Author

Lei Liu

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Preprint Aug 2026

DepTGL: A Parallel Framework for Memory-based TGNN Training with Adaptive Temporal Data Dependency Management

Memory-based Temporal Graph Neural Networks (M-TGNNs) maintain recursively updated node states to capture fine-grained temporal interactions. However, existing distributed frameworks lack effective mechanisms for managing the temporal data dependencies inherent in these models. As a result, they must enforce strict chr...

Lin-Fang Chen, Zhen Song, Lei Liu et al. · 0 citations

#graph neural networks Preprint Jul 2026

FAST: A Holistic Framework for Optimizing Memory-I/O, Computation, and Sampling in Temporal GNN Training

FAST is presented, a holistic framework that accelerates end-to-end TGNN training by jointly optimizing sampling, memory I/O, and computation and designs thread-efficient graph operators tailored to sparse temporal subgraphs, improving GPU cache locality and reducing the latency of aggregation and edge softmax.

Yu Cai, Qingrui Zhu, Lei Liu et al. · 0 citations