1 citations · 1 across the 4 of their papers we have counts for
4 papers
Stackelberg Game with Multi-Agent Transformer for ISRS-Aware Resource Re-optimization in Multi-Band Optical Networks
Jiaxin Liu, Rentao Gu, Miao Zhu +3
The rapid expansion of generative AI is driving computing infrastructures toward interconnected AI data centers. Multi-band optical networks have become the backbone of such connec…
MatchRDMA: A Segmented and Rate-Matched Long-Haul RDMA Scheme for Geo-distributed LLM Training over OTN
Jun Dai, Xiaorun Wang, Xingde Li +6
We propose MatchRDMA, a proactive, segmented, and rate-matched long-haul RDMA scheme for geo-distributed LLM training over OTN. By coordinating source and destination OTN rates, it…
GeoPipe: a Geo-distributed LLM Training Framework with enhanced Pipeline Parallelism in a Lossless RDMA-enabled Datacenter Optical Transport Network
Jun Dai, Xiaorun Wang, Kexiong Fang +3
The proliferation of Large Language Models (LLMs) with exponentially growing parameters is making cross-data center (DC) training an inevitable trend. However, viable strategies fo…
Poster: Flexible Scheduling of Network and Computing Resources for Distributed AI Tasks
Ruikun Wang, Jiawei Zhang, Qiaolun Zhang +5
Many emerging Artificial Intelligence (AI) applications require on-demand provisioning of large-scale computing, which can only be enabled by leveraging distributed computing servi…