2 papers
cs.LG2025
Every FLOP Counts: Scaling a 300B Mixture-of-Experts LING LLM without Premium GPUs
Ling Team, Binwei Zeng, Chao Huang +71
In this technical report, we tackle the challenges of training large-scale Mixture of Experts (MoE) models, focusing on overcoming cost inefficiency and resource limitations preval…
cs.DC2024
LayerKV: Optimizing Large Language Model Serving with Layer-wise KV Cache Management
Yi Xiong, Hao Wu, Changxu Shao +6
The expanding context windows in large language models (LLMs) have greatly enhanced their capabilities in various applications, but they also introduce significant challenges in ma…