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BOAT: Building auto-tuners with structured Bayesian optimization

Published version
Peer-reviewed

Type

Conference Object

Change log

Authors

Dalibard, V 
Schaarschmidt, M 

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

Description

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

Journal ISSN

Volume Title

Publisher

International World Wide Web Conferences Steering Committee
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)