4 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…
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…
H-DenseFormer: An Efficient Hybrid Densely Connected Transformer for Multimodal Tumor Segmentation
Jun Shi, Hongyu Kan, Shulan Ruan +6
Recently, deep learning methods have been widely used for tumor segmentation of multimodal medical images with promising results. However, most existing methods are limited by insu…