16 citations · 16 across the 2 of their papers we have counts for
3 papers
cs.DC2025
DCP: Addressing Input Dynamism In Long-Context Training via Dynamic Context Parallelism
Chenyu Jiang, Zhenkun Cai, Ye Tian +3
Context parallelism has emerged as a key technique to support long-context training, a growing trend in generative AI for modern large models. However, existing context parallel me…
cs.DC2024★ 16 cited
HAP: SPMD DNN Training on Heterogeneous GPU Clusters with Automated Program Synthesis
Shiwei Zhang, Lansong Diao, Chuan Wu +3
Single-Program-Multiple-Data (SPMD) parallelism has recently been adopted to train large deep neural networks (DNNs). Few studies have explored its applicability on heterogeneous c…
cs.CV2023
TransXNet: Learning Both Global and Local Dynamics with a Dual Dynamic Token Mixer for Visual Recognition
Meng Lou, Shu Zhang, Hong-Yu Zhou +3
Recent studies have integrated convolutions into transformers to introduce inductive bias and improve generalization performance. However, the static nature of conventional convolu…