- author = "W. B. Langdon and M. Harman",
- title = "Genetically Improved {CUDA} kernels for {StereoCamera}",
- institution = "Department of Computer Science, University College London",
- year = "2014",
- type = "Research Note",
- number = "RN/14/02",
- address = "Gower Street, London WC1E 6BT, UK",
- month = "20 " # feb,
- keywords = "genetic algorithms, genetic programming, genetic improvement, GI, GP, gismoe, SBSE, software optimisation, nVidia, GPU, GPGPU, Tesla, GeForce GTX 580, evolutionary programming, software engineering",
-
URL = "
http://www.cs.ucl.ac.uk/fileadmin/UCL-CS/research/Research_Notes/Langdon_RN1402.pdf",
- size = "24 pages",
- abstract = "Genetic Programming (GP) may dramatically increase the performance of software written by domain experts. GP and autotuning are used to optimise and refactor legacy GPGPU C code for modern parallel graphics hardware and software. Speed ups of more than six times on recent nVidia GPU cards are reported compared to the original kernel on the same hardware.",
-
notes = "
GP code ftp://ftp.cs.ucl.ac.uk//genetic/gp-code/StereoCamera_1_1.tar.gz Training images ftp://ftp.cs.ucl.ac.uk//genetic/gp-code/StereoImages.tar.gz
StereoCamera v1.0b with bugfix and tuned for K20c Tesla at ftp://ftp.cs.ucl.ac.uk//genetic/gp-code/StereoCamera_v1_1c.zip Cf \cite{langdon:2014:EuroGP}",
