High Performance Genetic Programming on GPU

被引：0

作者：

Robilliard, Denis ^{[1
]}

Marion, Virginie ^{[1
]}

Fonlupt, Cyril ^{[1
]}

机构：

[1] Univ Lille Nord de France, LIL, F-62228 Calais, France

来源：

WORKSHOP ON BIO-INSPIRED ALGORITHMS FOR DISTRIBUTED SYSTEMS - BADS 2009 | 2009年

关键词：

genetic algorithms; genetic programming; graphics processing units; parallel processing;

D O I：

暂无

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

The availability of low cost powerful parallel graphics cards has stimulated the port of Genetic Programming (C; P) 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 parallelization 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 optimizations 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.

引用

页码：85 / 93

页数：9

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