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cs.DC2026
Efficient Scaling of LLM Training with Flexible Context Parallelism
Yifan Niu, Han Xiao, Dongyi Liu +2
Scaling long-context capabilities is crucial for Large Language Models (LLMs). However, real-world data contain a large number of sequences with heterogeneous lengths. Existing tra…
cs.DC2026
PiKV: KV Cache Management System for Mixture of Experts
Dong Liu, Yanxuan Yu, Ben Lengerich +1
As large-scale language models continue to scale up in both size and context length, the memory and communication cost of key-value (KV) cache storage has become a major bottleneck…
cs.DC2025
Designing Large Foundation Models for Efficient Training and Inference: A Survey
Dong Liu, Yanxuan Yu, Yite Wang +5
This paper focuses on modern efficient training and inference technologies on foundation models and illustrates them from two perspectives: model and system design. Model and Syste…