3 papers
cs.DC2025
MorphServe: Efficient and Workload-Aware LLM Serving via Runtime Quantized Layer Swapping and KV Cache Resizing
Zhaoyuan Su, Zeyu Zhang, Tingfeng Lan +4
Efficiently serving large language models (LLMs) under dynamic and bursty workloads remains a key challenge for real-world deployment. Existing serving frameworks and static model…
cs.DC2025
ZenFlow: Enabling Stall-Free Offloading Training via Asynchronous Updates
Tingfeng Lan, Yusen Wu, Bin Ma +7
Fine-tuning large language models (LLMs) often exceeds GPU memory limits, prompting systems to offload model states to CPU memory. However, existing offloaded training frameworks l…
cs.DB2025
ZipLLM: Efficient LLM Storage via Model-Aware Synergistic Data Deduplication and Compression
Zirui Wang, Tingfeng Lan, Zhaoyuan Su +2
Modern model hubs, such as Hugging Face, store tens of petabytes of LLMs, with fine-tuned variants vastly outnumbering base models and dominating storage consumption. Existing stor…