Please use this identifier to cite or link to this item:
|Scopus||Web of Science®||Altmetric|
|Title:||Constructing an Optimisation Phase Using Grammatical Evolution|
|Citation:||Proceedings of the IEEE Congress on Evolutionary Computation, 2009: pp.1209-1216|
|Conference Name:||IEEE Congress on Evolutionary Computation (2009 : Trondheim, Norway)|
|B. J. Alexander and M. J. Gratton|
|Abstract:||Optimising compilers present their authors with an intractable design space. A substantial body of work has used heuristic search techniques to search this space for the purposes of adapting optimisers to their environment. To date, most of this work has focused on sequencing, tuning and guiding the actions of atomic hand-written optimisation phases. In this paper we explore the adaption of optimisers at a deeper level by demonstrating that it is feasible to automatically build a non-trivial optimisation phase, for a simple functional language, using grammatical evolution. We show that the individuals evolved compare well in performance to a hand-written optimisation phase on a range of benchmarks. We conclude with proposals of how this work and its applications can be extended.|
|Rights:||© 2009 IEEE|
|Appears in Collections:||Computer Science publications|
Files in This Item:
There are no files associated with this item.
Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.