- author = "Denis Robilliard and Virginie Marion and Cyril Fonlupt",
- title = "High performance genetic programming on GPU",
- year = "2009",
- booktitle = "Proceedings of the 2009 workshop on Bio-inspired algorithms for distributed systems",
- editor = "Gianluigi Folino and Natalio Krasnogor and Carlo Mastroianni and Franco Zambonelli",
- pages = "85--94",
- month = jun # " 15-19",
- note = "paper invited for the FGCS special issue",
- publisher = "ACM",
- address = "Barcelona, Spain",
- isbn13 = "978-1-60558-584-0",
-
URL = "
http://portal.acm.org/citation.cfm?id=1555284.1555299",
-
DOI = "
doi:10.1145/1555284.1555299",
- keywords = "genetic algorithms, genetic programming, GPU, graphics processing units, parallel processing",
- abstract = "The availability of low cost powerful parallel graphics cards has stimulated the port of Genetic Programming (GP) on Graphics Processing Units (GPUs). Our work focuses on the possibilities offered by Nvidia G80 GPUs when programmed in the CUDA language. We compare two parallelisation schemes that evaluate several GP programs in parallel. We show that the fine grain distribution of computations over the elementary processors greatly impacts performances. We also present memory and representation optimisations that further enhance computation speed, up to 2.8 billion GP operations per second. The code has been developed with the well known ECJ library.",
-
notes = "BADS 2009 http://bads.icar.cnr.it/
ECJ trees replaced by byte per opcode linearised RPN \cite{langdon:2008:eurogp}. nVidia GeForce 8800 GTX reserved for computations (separate card to drive X-11 windows monitor display). BlockGP always faster than ThreadGP. 32 threads per CUDA block. Thread divergence due to if: 6-multiplexer, 11-mux, intertwined spirals. Sextic regression (2797 million GPop/s, 144 speed up over 2.6Ghz PC).
+-*/ sin cos exp log and or not if iflte. ERCs. Interpreted programs in shared memory (referred to as {"}cache{"}).",
