8 citations · 33 across the 21 of their papers we have counts for
6 papers · 1 filter
Gandalf: Flash Shall Not Die! Increasing Flash Storage Lifetime for KV Cache Offloading in LLM Serving
Maharani A. P. Irawan, Kuntai Du, Jiayi Yao +4
KV caching reduces the serving cost of large language models (LLMs), but the growing KV cache footprint is increasingly exceeds GPU and host-memory capacity. Therefore, people use…
LMCache: An Efficient KV Cache Layer for Enterprise-Scale LLM Inference
Yuhan Liu, Yihua Cheng, Jiayi Yao +8
KV cache has traditionally been stored in GPU memory to accelerate the decoding phase of large language model (LLM) inference. However, it is increasingly necessary to move KV cach…
METIS: Fast Quality-Aware RAG Systems with Configuration Adaptation
Siddhant Ray, Rui Pan, Zhuohan Gu +5
RAG (Retrieval Augmented Generation) allows LLMs (large language models) to generate better responses with external knowledge, but using more external knowledge often improves gene…
LLMSteer: Improving Long-Context LLM Inference by Steering Attention on Reused Contexts
Zhuohan Gu, Jiayi Yao, Kuntai Du +1
As large language models (LLMs) show impressive performance on complex tasks, they still struggle with longer contextual understanding and high computational costs. To balance effi…
CacheBlend: Fast Large Language Model Serving for RAG with Cached Knowledge Fusion
Jiayi Yao, Hanchen Li, Yuhan Liu +6
Large language models (LLMs) often incorporate multiple text chunks in their inputs to provide the necessary contexts. To speed up the prefill of the long LLM inputs, one can pre-c…
OneAdapt: Fast Configuration Adaptation for Video Analytics Applications via Backpropagation
Kuntai Du, Yuhan Liu, Yitian Hao +5
Deep learning inference on streaming media data, such as object detection in video or LiDAR feeds and text extraction from audio waves, is now ubiquitous. To achieve high inference…