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Tuning Computer Systems with Structured Bayesian Optimization

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Abstract: Computer systems are notoriously difficult to tune. In this talk, I will present Structured Bayesian Optimization, a framework which lets users expose the tunable parameters of their programs so they can be automatically optimized. To help the optimization converge in a reasonable time, users can expose the structure available, in the form of a probabilistic model simulating the execution of the system. I will present some of our case studies and discuss possible future applications.

This talk is part of the Computer Laboratory NetOS Group Talklets series.

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