24 citations · 30 across the 3 of their papers we have counts for
3 papers
cs.CL2025
Training Report of TeleChat3-MoE
Xinzhang Liu, Chao Wang, Zhihao Yang +51
TeleChat3-MoE is the latest series of TeleChat large language models, featuring a Mixture-of-Experts (MoE) architecture with parameter counts ranging from 105 billion to over one t…
cs.LG2024★ 24 cited
MegaScale: Scaling Large Language Model Training to More Than 10,000 GPUs
Ziheng Jiang, Haibin Lin, Yinmin Zhong +29
We present the design, implementation and engineering experience in building and deploying MegaScale, a production system for training large language models (LLMs) at the scale of…
cs.NI2023★ 6 cited
Collie: Finding Performance Anomalies in RDMA Subsystems
Xinhao Kong, Yibo Zhu, Huaping Zhou +4
High-speed RDMA networks are getting rapidly adopted in the industry for their low latency and reduced CPU overheads. To verify that RDMA can be used in production, system administ…