activity
20202026
most citedVQPy: An Object-Oriented Approach to Modern Video Analytics

2 citations · 5 across the 11 of their papers we have counts for

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6 papers · 1 filter

cs.DC2025

Prism: Cost-Efficient Multi-LLM Serving via GPU Memory Ballooning

Shan Yu, Yifan Qiao, Mingyuan Ma +18

Inference providers must maintain availability for many LLMs, including low-volume but essential models, making resource efficiency increasingly important as token prices fall. Ana…

cs.DC2024★ 1 cited

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…

cs.DC2024

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…

cs.DC2024

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…

cs.DC2024★ 1 cited

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,…

cs.DC2022★ 1 cited

Zenix: Efficient Execution of Bulky Serverless Applications

Zhiyuan Guo, Zachary Blanco, Junda Chen +7

Serverless computing, commonly offered as Function-as-a-Service, was initially designed for small, lean applications. However, there has been an increasing desire to run larger, mo…