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An LLM server in three numbers
A note on recent work with Asser Tantawi. A queueing model of LLM inference with three hardware parameters, accurate enough to drive an autoscaler and simple enough to tune itself.
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When a pipeline should stop working
Part three of a second series on my PhD work. In multi-step update processing, busy servers can waste power on results that make no one better informed.
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The best time to read memory
Part two of a second series on my PhD work. The optimal policy for sampling shared memory turns out to be a threshold with a closed form.
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Sometimes fresher means waiting
Part one of a second series on my PhD work. Why a decision process that reads shared data and computes on it should sometimes sit idle before reading again.
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Freshness has a memory bill
Part three of a series on my PhD work. How much memory Read-Copy-Update spends to keep information fresh, and why the bill stays bounded.