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2012
Springer

Boosting Design Space Explorations with Existing or Automatically Learned Knowledge

7 years 7 months ago
Boosting Design Space Explorations with Existing or Automatically Learned Knowledge
Abstract. During development, processor architectures can be tuned and configured by many different parameters. For benchmarking, automatic design space explorations (DSEs) with heuristic algorithms are a helpful approach to find the best settings for these parameters according to multiple objectives, e.g. performance, energy consumption, or real-time constraints. But if the setup is slightly changed and a new DSE has to be performed, it will start from scratch, resulting in very long evaluation times. To reduce the evaluation times we extend the NSGA-II algorithm in this article, such that automatic DSEs can be supported with a set of transformation rules defined in a highly readable format, the fuzzy control language (FCL). Rules can be specified by an engineer, thereby representing existing knowledge. Beyond this, a decision tree classifying high-quality configurations can be constructed automatically and translated into transformation rules. These can also be seen as very valu...
Ralf Jahr, Horia Calborean, Lucian Vintan, Theo Un
Added 25 Apr 2012
Updated 25 Apr 2012
Type Journal
Year 2012
Where MMB
Authors Ralf Jahr, Horia Calborean, Lucian Vintan, Theo Ungerer
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