Langdon, William;
(2015)
Genetically Improved Software.
In: Gandomi, Amir H and Alavi, Amir H and Ryan, Conor, (eds.)
Handbook of Genetic Programming Applications.
(pp. 181-220).
Springer: Cham, Switzerland.
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Abstract
Genetic programming (GP) can dramatically increase computer programs’ performance. It can automatically port or refactor legacy code written by domain experts and specialist software engineers. After reviewing SBSE research on evolving software we describe an open source parallel StereoCamera image processing application in which GI optimisation gave a seven fold speedup on nVidia Tesla GPU hardware not even imagined when the original state-of-the-art CUDA GPGPU C++ code was written.
| Type: | Book chapter |
|---|---|
| Title: | Genetically Improved Software |
| ISBN: | 3319208829 |
| ISBN-13: | 9783319208824 |
| Open access status: | An open access version is available from UCL Discovery |
| DOI: | 10.1007/978-3-319-20883-1_8 |
| Publisher version: | https://link.springer.com/chapter/10.1007/978-3-31... |
| Language: | English |
| Additional information: | This version is the author accepted manuscript. For information on re-use, please refer to the publisher’s terms and conditions. |
| UCL classification: | UCL UCL > Provost and Vice Provost Offices > UCL BEAMS UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science > Dept of Computer Science |
| URI: | https://discovery.ucl.ac.uk/id/eprint/10198995 |
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