Application-Oblivious L7 Parsing Using Recurrent Neural Networks. - Hao Li 011; Zhengda Bian; Peng Zhang 011; Zhun Sun; Chengchen Hu; Qiang Fu 011; Tian Pan 001; Jia Lv (IEEE/ACM Trans. Netw., 2020)

Online evolutionary batch size orchestration for scheduling deep learning workloads in GPU clusters. - Zhengda Bian; Shenggui Li; Wei Wang; Yang You 001 (SC, 2021)

Maximizing Parallelism in Distributed Training for Huge Neural Networks. - Zhengda Bian; Qifan Xu; Boxiang Wang; Yang You 001 (CoRR, 2021)

2.5-dimensional distributed model training. - Boxiang Wang; Qifan Xu; Zhengda Bian; Yang You 001 (CoRR, 2021)

Colossal-AI: A Unified Deep Learning System For Large-Scale Parallel Training. - Zhengda Bian; Hongxin Liu; Boxiang Wang; Haichen Huang; Yongbin Li; Chuanrui Wang; Fan Cui; Yang You 001 (CoRR, 2021)

Tesseract: Parallelize the Tensor Parallelism Efficiently. - Boxiang Wang; Qifan Xu; Zhengda Bian; Yang You 001 (ICPP, 2022)

A Frequency-aware Software Cache for Large Recommendation System Embeddings. - Jiarui Fang; Geng Zhang; Jiatong Han; Shenggui Li; Zhengda Bian; Yongbin Li; Jin Liu; Yang You 001 (CoRR, 2022)

Colossal-AI: A Unified Deep Learning System For Large-Scale Parallel Training. - Shenggui Li; Hongxin Liu; Zhengda Bian; Jiarui Fang; Haichen Huang; Yuliang Liu; Boxiang Wang; Yang You 001 (ICPP, 2023)