2 citations · 5 across the 11 of their papers we have counts for
4 papers · 1 filter
ConServe: Fine-Grained GPU Harvesting for LLM Online and Offline Co-Serving
Yifan Qiao, Shu Anzai, Shan Yu +10
Large language model (LLM) serving demands low latency and high throughput, but high load variability makes it challenging to achieve high GPU utilization. In this paper, we identi…
DRust: Language-Guided Distributed Shared Memory with Fine Granularity, Full Transparency, and Ultra Efficiency
Haoran Ma, Yifan Qiao, Shi Liu +7
Despite being a powerful concept, distributed shared memory (DSM) has not been made practical due to the extensive synchronization needed between servers to implement memory cohere…
A Tale of Two Paths: Toward a Hybrid Data Plane for Efficient Far-Memory Applications
Lei Chen, Shi Liu, Chenxi Wang +9
With rapid advances in network hardware, far memory has gained a great deal of traction due to its ability to break the memory capacity wall. Existing far memory systems fall into…
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,…