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SUMMARY:ASSET Seminar: "Efficient Sharing of AI Infrastructures with Specialized Serverless Computing"
DESCRIPTION:Abstract: \nThe efficient sharing of AI infrastructures is becoming increasingly important in both public and private data centers. This demand is driven by two key factors: the proliferation of specialized AI models tailored for different users and applications\, and the highly dynamic nature of requests\, which are often on-demand. Dedicated GPU allocation in such scenarios results in prohibitively high costs and inefficient resource utilization. \nIn this talk\, I will introduce serverless computing as a promising paradigm for addressing these challenges by enabling efficient\, on-demand sharing of AI infrastructures. I will highlight its use cases and discuss key barriers to broader adoption. Following this\, I will present ServerlessLLM\, a state-of-the-art system designed to tackle key challenges in serverless large language model (LLM) inference\, particularly cold-start latency. Specifically\, I will cover ServerlessLLM’s novel contributions\, including its checkpoint format design\, locality-aware scheduling\, and inference request live migration. Finally\, I will outline open challenges beyond efficiency\, such as fairness\, privacy\, and sustainability\, which are critical for the future of serverless AI systems. \nZoom Link (if unable to attend in-person): https://upenn.zoom.us/j/95090162762
URL:https://seasevents.nmsdev7.com/event/asset-seminar-yao-fu-university-of-edinburgh/
LOCATION:Amy Gutmann Hall\, Room 414\, 3333 Chestnut Street\, Philadelphia\, 19104\, United States
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