- author = "William B. Langdon and Justyna Petke and Aymeric Blot and David Clark",
- title = "Genetically Improved Software with fewer Data Caches Misses",
- booktitle = "Proceedings of the 2023 Genetic and Evolutionary Computation Conference",
- year = "2023",
- address = "Lisbon, Portugal",
- series = "GECCO '23",
- month = "15-19 " # jul,
- organisation = "SIGEVO",
- publisher = "Association for Computing Machinery",
- publisher_address = "New York, NY, USA",
- note = "forthcoming",
- keywords = "genetic algorithms, genetic programming, genetic improvement, local search, SBSE, GP, linear representation, software resilience, automatic code optimisation, tabu, nonstationary noise, perf, world wide location, plus codes, zip code, OpenCV, image segmentation: Poster",
- isbn13 = "979-8-4007-0120-7",
-
URL = "
http://www.cs.ucl.ac.uk/staff/W.Langdon/ftp/papers/langdon_2023_GECCO.pdf",
-
DOI = "
doi:10.1145/3583133.3590542",
- size = "4 pages",
- abstract = "Using MAGPIE (Machine Automated General Performance Improvement via Evolution of software) we show genetic improvement GI can reduce the cache load of existing computer programs. Cache miss reduction is tested on two industrial open source C programs (Google Open Location Code OLC and Uber Hexagonal Hierarchical Spatial Index H3) and two C++ 2D photograph image processing tasks, counting pixels and OpenCV SEEDS segmentation algorithm. Magpie patches functionally generalise. In one case they reduce data misses on the highest performance L1 cache by 47 percent.",
-
notes = "Four page version of
\cite{langdon:2023:cache}
GECCO-2023 A Recombination of the 3nd International Conference on Genetic Algorithms (ICGA) and the 28th Annual Genetic Programming Conference (GP)",
