3 papers
cs.DC2024
SSDTrain: An Activation Offloading Framework to SSDs for Faster Large Language Model Training
Kun Wu, Jeongmin Brian Park, Xiaofan Zhang +5
The growth rate of the GPU memory capacity has not been able to keep up with that of the size of large language models (LLMs), hindering the model training process. In particular,…
cs.DC2024
LSM-GNN: Large-scale Storage-based Multi-GPU GNN Training by Optimizing Data Transfer Scheme
Jeongmin Brian Park, Kun Wu, Vikram Sharma Mailthody +3
Graph Neural Networks (GNNs) are widely used today in recommendation systems, fraud detection, and node/link classification tasks. Real world GNNs continue to scale in size and req…
cs.DC2023
Accelerating Sampling and Aggregation Operations in GNN Frameworks with GPU Initiated Direct Storage Accesses
Jeongmin Brian Park, Vikram Sharma Mailthody, Zaid Qureshi +1
Graph Neural Networks (GNNs) are emerging as a powerful tool for learning from graph-structured data and performing sophisticated inference tasks in various application domains. Al…