Poseidon is an efficient and scalable LLM training framework designed with heterogeneity awareness, which employs two efficient, theoretically grounded strategies: stage-level pruning via early stopping with partial estimation, and layer-to-stage mapping exploiting a ridge-like distribution pattern.
Xiao-Song Chen, Shao Nie, Zhong-Min Zhao et al.· 0 citations
Cremes is proposed, an adaptive and cost-efficient scaling framework that ensures microservice recovery within the spot instance grace period and maintains SLO violation rates under preemptible environments below 6.7%.
Liao Chen, Chenyu Lin, Junlin Chen et al.· IEEE International Symposium...· 0 citations
This paper proposes psRL (prefix sharing for RL), a new training system for agentic AI designed to exploit prefix redundancy among training samples, and introduces two novel prefix-sharing mechanisms that enable flexible, fine-grained workload distribution across GPU workers.
Mian-Jie Yu, Zi-Zhao Mo, Huanyu Qu et al.· 0 citations
We use cookies to run the site and, with your consent, for analytics and to show ads.
See our Cookie Policy.