- author = "Tony E. Lewis and George D. Magoulas",
- title = "{TMBL} Kernels for {CUDA GPUs} Compile Faster Using {PTX}",
- booktitle = "GECCO 2011 Computational intelligence on consumer games and graphics hardware (CIGPU)",
- year = "2011",
- editor = "Simon Harding and W. B. Langdon and Man Leung Wong and Garnett Wilson and Tony Lewis",
- isbn13 = "978-1-4503-0690-4",
- keywords = "genetic algorithms, genetic programming, GPU, Artificial Intelligence, Automatic Programming, program synthesis, Performance, Tweaking Mutation Behaviour Learning (TMBL), Parallel Thread EXecution (PTX), Graphics Card, Graphics Processing Unit, GPU, CUDA",
- pages = "455--462",
- month = "12-16 " # jul,
- organisation = "SIGEVO",
- address = "Dublin, Ireland",
- publisher = "ACM",
- publisher_address = "New York, NY, USA",
-
DOI = "
doi:10.1145/2001858.2002033",
- size = "8 pages",
- abstract = "Many of the most effective attempts to harness the power of the Graphics Processing Unit (GPU) to accelerate Genetic Programming (GP) have dynamically compiled code for individuals as they are to be evaluated. This approach executes very quickly on the GPU but is slow to compile, hence only vast data-sets fully reap its rewards. To reduce compilation time, we generate and compile code in the lower-level language PTX. We investigate this in the context of implementing Tweaking Mutation Behaviour Learning (TMBL) on the GPU. We find that for programs of 300 instructions, using PTX reduces the compile time 5.861 times and even increases the evaluation speed by 23.029percent",
-
notes = "wk308d-lewis.pdf Computational Intelligence on
Consumer Games and Graphics Hardware Also known as
\cite{2002033} Distributed on CD-ROM at GECCO-2011.
ACM Order Number 910112.",
