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…
FAPO: Fanout-Aware Post-Mapping Optimization for LUT-Based FPGAs
Xiaoyu Hao, Keren Zhu
Reducing logic depth during FPGA technology mapping does not necessarily eliminate fanout bottlenecks in the resulting LUT networks.Replicating heavily loaded LUTs can alleviate th…
NDFT: Accelerating Density Functional Theory Calculations via Hardware/Software Co-Design on Near-Data Computing System
Qingcai Jiang, Buxin Tu, Xiaoyu Hao +2
Linear-response time-dependent Density Functional Theory (LR-TDDFT) is a widely used method for accurately predicting the excited-state properties of physical systems. Previous wor…
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…
DARNet: Dual-Attention Residual Network for Automatic Diagnosis of COVID-19 via CT Images
Jun Shi, Huite Yi, Shulan Ruan +4
The ongoing global pandemic of Coronavirus Disease 2019 (COVID-19) poses a serious threat to public health and the economy. Rapid and accurate diagnosis of COVID-19 is crucial to p…