5 papers
A Dependency-Aware Multi-GPU Training Framework for Temporal Graph Neural Networks
Yang Zhao, Yue Dai, Liang Qiao +8
Temporal graph neural networks (TGNNs) achieve superior performance in many dynamic graph learning tasks. These models use node state vectors (i.e., memories) to capture and record…
TERRA: A Hierarchical Parallel Training and Memory Orchestration Framework for High-Resolution AI-based Earth Modeling
Ruohan Wu, Ziqi Zhu, Yang Zhao +6
Training high-resolution AI-based Earth forecasting models is memory-intensive. Window-based Swin Transformers reduce the quadratic cost of global attention, but existing distribut…
Clore: Interactive Pathology Image Segmentation with Click-based Local Refinement
Tiantong Wang, Minfan Zhao, Jun Shi +2
Recent advancements in deep learning-based interactive segmentation methods have significantly improved pathology image segmentation. Most existing approaches utilize user-provided…
FlashOmni: A Unified Sparse Attention Engine for Diffusion Transformers
Liang Qiao, Yue Dai, Yeqi Huang +3
Multi-Modal Diffusion Transformers (DiTs) demonstrate exceptional capabilities in visual synthesis, yet their deployment remains constrained by substantial computational demands. T…
Pruner: A Draft-then-Verify Exploration Mechanism to Accelerate Tensor Program Tuning
Liang Qiao, Jun Shi, Xiaoyu Hao +10
Tensor program tuning is essential for the efficient deployment of deep neural networks. Search-based approaches have demonstrated scalability and effectiveness in automatically fi…