BOAT: Building auto-tuners with structured Bayesian optimization
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Peer-reviewed
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Abstract
Due to their complexity, modern systems expose many con-figuration parameters which users must tune to maximizeperformance. Auto-tuning has emerged as an alternative inwhich a black-box optimizer iteratively evaluates configura-tions to find efficient ones. Unfortunately, for many systems,such as distributed systems, evaluating performance takestoo long and the space of configurations is too large for theoptimizer to converge within a reasonable time
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Keywords
4606 Distributed Computing and Systems Software, 46 Information and Computing Sciences
Journal Title
26th International World Wide Web Conference, WWW 2017
Conference Name
WWW '17: 26th International World Wide Web Conference
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Publisher
International World Wide Web Conferences Steering Committee
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Sponsorship
Engineering and Physical Sciences Research Council (EP/P004024/1)
Engineering and Physical Sciences Research Council (EP/M508007/1)
Engineering and Physical Sciences Research Council (EP/H003959/1)
Engineering and Physical Sciences Research Council (EP/M508007/1)
Engineering and Physical Sciences Research Council (EP/H003959/1)