13 citations · 20 across the 5 of their papers we have counts for
5 papers
SysBench: Can Large Language Models Follow System Messages?
Yanzhao Qin, Tao Zhang, Yanjun Shen +8
Large Language Models (LLMs) have become instrumental across various applications, with the customization of these models to specific scenarios becoming increasingly critical. Syst…
Improving Automatic Parallel Training via Balanced Memory Workload Optimization
Yujie Wang, Youhe Jiang, Xupeng Miao +5
Transformer models have emerged as the leading approach for achieving state-of-the-art performance across various application domains, serving as the foundation for advanced large-…
OSDP: Optimal Sharded Data Parallel for Distributed Deep Learning
Youhe Jiang, Fangcheng Fu, Xupeng Miao +2
Large-scale deep learning models contribute to significant performance improvements on varieties of downstream tasks. Current data and model parallelism approaches utilize model re…
OpenBox: A Python Toolkit for Generalized Black-box Optimization
Huaijun Jiang, Yu Shen, Yang Li +5
Black-box optimization (BBO) has a broad range of applications, including automatic machine learning, experimental design, and database knob tuning. However, users still face chall…
DeGNN: Characterizing and Improving Graph Neural Networks with Graph Decomposition
Xupeng Miao, Nezihe Merve Gürel, Wentao Zhang +17
Despite the wide application of Graph Convolutional Network (GCN), one major limitation is that it does not benefit from the increasing depth and suffers from the oversmoothing pro…