3 citations · 9 across the 5 of their papers we have counts for
4 papers · 1 filter
Tropical: Enhancing SLO Attainment in Disaggregated LLM Serving via SLO-Aware Multiplexing
Jinming Ma, Jiefei Chen, Xiuhong Li +5
To guarantee service quality in transformer based large language model (LLM) serving, it is essential to meet the latency constraints of both the prefill phase (measured by Time-to…
MuxServe: Flexible Spatial-Temporal Multiplexing for Multiple LLM Serving
Jiangfei Duan, Runyu Lu, Haojie Duanmu +5
Large language models (LLMs) have demonstrated remarkable performance, and organizations are racing to serve LLMs of varying sizes as endpoints for use-cases like chat, programming…
Parcae: Proactive, Liveput-Optimized DNN Training on Preemptible Instances
Jiangfei Duan, Ziang Song, Xupeng Miao +5
Deep neural networks (DNNs) are becoming progressively large and costly to train. This paper aims to reduce DNN training costs by leveraging preemptible instances on modern clouds,…
SpotServe: Serving Generative Large Language Models on Preemptible Instances
Xupeng Miao, Chunan Shi, Jiangfei Duan +4
The high computational and memory requirements of generative large language models (LLMs) make it challenging to serve them cheaply. This paper aims to reduce the monetary cost for…