32 citations · 74 across the 4 of their papers we have counts for
4 papers
A Frequency-aware Software Cache for Large Recommendation System Embeddings
Jiarui Fang, Geng Zhang, Jiatong Han +5
Deep learning recommendation models (DLRMs) have been widely applied in Internet companies. The embedding tables of DLRMs are too large to fit on GPU memory entirely. We propose a…
Colossal-AI: A Unified Deep Learning System For Large-Scale Parallel Training
Shenggui Li, Hongxin Liu, Zhengda Bian +5
The success of Transformer models has pushed the deep learning model scale to billions of parameters. Due to the limited memory resource of a single GPU, However, the best practice…
Maximizing Parallelism in Distributed Training for Huge Neural Networks
Zhengda Bian, Qifan Xu, Boxiang Wang +1
The recent Natural Language Processing techniques have been refreshing the state-of-the-art performance at an incredible speed. Training huge language models is therefore an impera…
Tesseract: Parallelize the Tensor Parallelism Efficiently
Boxiang Wang, Qifan Xu, Zhengda Bian +1
Together with the improvements in state-of-the-art accuracies of various tasks, deep learning models are getting significantly larger. However, it is extremely difficult to impleme…