Genetic programming on graphics processing units
| Autor: | Virginie Marion-Poty, Cyril Fonlupt, Denis Robilliard |
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| Rok vydání: | 2009 |
| Předmět: |
Scheme (programming language)
Computer science Genetic programming Parallel computing Computer Science Applications Theoretical Computer Science Computational science CUDA Parallel processing (DSP implementation) Hardware and Architecture CUDA Pinned memory Code (cryptography) General-purpose computing on graphics processing units Graphics computer Software computer.programming_language |
| Zdroj: | Genetic Programming and Evolvable Machines. 10:447-471 |
| ISSN: | 1573-7632 1389-2576 |
| DOI: | 10.1007/s10710-009-9092-3 |
| Popis: | 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. In a first work we have showed that this setup allows to develop fine grain parallelization schemes to evaluate several GP programs in parallel, while obtaining speedups for usual training sets and program sizes. Here we present another parallelization scheme and optimizations about program representation and use of GPU fast memory. This increases the computation speed about three times faster, up to 4 billion GP operations per second. The code has been developed within the well known ECJ library and is open source. |
| Databáze: | OpenAIRE |
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