MEDO leverages a novel multi-stream data offloading architecture, featuring parallel data streams and approximate LRU queues, to maximize throughput and efficiently handle diverse workloads and incorporates a lightweight, adaptive offloading agent that dynamically optimizes data placement decisions and fine-grained sys...
Jing Wang, Han-Zhang Yang, Chao Li et al.· Proceedings of the Internati...· 0 citations
The scale of data-intensive workloads in intelligent datacenters has grown rapidly in recent years, intensifying the need for efficient data movement within disaggregated memory pools across memory and storage subsystems. However, most existing solutions focus primarily on optimizing communication between compute nodes...
Jing Wang, Han-Zhang Yang, Chao Li et al.· Proceedings of the Internati...· 0 citations
The increasing use of renewable energy in data centers creates an opportunity to reduce the carbon footprint of energy-intensive LLM inference workloads. Unlike traditional stable power supply, renewable generation fluctuates over time, making it difficult to match computation demand with available energy. However, exi...
Chang Liu, Jiacheng Liu, Xiaofeng Hou et al.· Fall Joint Computer Conferen...· 0 citations
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