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
收藏
页码:85 / 93
页数:9
相关论文
共 50 条
  • [1] Performance Characterization of High-Level Programming Models for GPU Graph Analytics
    Wu, Yuduo
    Wang, Yangzihao
    Pan, Yuechao
    Yang, Carl
    Owens, John D.
    2015 IEEE INTERNATIONAL SYMPOSIUM ON WORKLOAD CHARACTERIZATION (IISWC), 2015, : 66 - 75
  • [2] GPU-Parallel SubTree Interpreter for Genetic Programming
    Cano, Alberto
    Ventura, Sebastian
    GECCO'14: PROCEEDINGS OF THE 2014 GENETIC AND EVOLUTIONARY COMPUTATION CONFERENCE, 2014, : 887 - 893
  • [3] Improving the performance of GPU-based genetic programming through exploitation of on-chip memory
    Darren M. Chitty
    Soft Computing, 2016, 20 : 661 - 680
  • [4] Improving the performance of GPU-based genetic programming through exploitation of on-chip memory
    Chitty, Darren M.
    SOFT COMPUTING, 2016, 20 (02) : 661 - 680
  • [5] A SIMD interpreter for genetic programming on GPU graphics cards
    Langdon, W. B.
    Banzhaf, Wolfgang
    GENETIC PROGRAMMING, PROCEEDINGS, 2008, 4971 : 73 - +
  • [6] Meta-programming and Auto-tuning in the Search for High Performance GPU Code
    Vollmer, Michael
    Svensson, Bo Joel
    Holk, Eric
    Newton, Ryan R.
    FHPC'15 PROCEEDINGS OF THE 4TH ACM SIGPLAN WORKSHOP ON FUNCTIONAL HIGH-PERFORMANCE COMPUTING, 2015, : 1 - 11
  • [7] Taking GPU Programming Models to Task for Performance Portability
    Davis, Joshua H.
    Sivaraman, Pranav
    Kitson, Joy
    Parasyris, Konstantinos
    Menon, Harshitha
    Minn, Isaac
    Georgakoudis, Giorgis
    Bhatele, Abhinav
    arXiv,
  • [8] High Performance Computing in GPU
    Piccoli, Maria F.
    JOURNAL OF COMPUTER SCIENCE & TECHNOLOGY, 2012, 12 (02): : 91 - 93
  • [9] Genetic Algorithm on GPU Performance Optimization Issues
    Paukste, Andrius
    INTELLIGENT DATA ENGINEERING AND AUTOMATED LEARNING - IDEAL 2013, 2013, 8206 : 529 - 536
  • [10] High-performance Cartesian Genetic Programming on GPU for the Inference of Gene Regulatory Networks using scRNA-Seq Time-Series Data
    Santana Prachedes, Luciana Nascimento
    Henriques da Silva, Jose Eduardo
    Bernardino, Heder Soares
    de Oliveira, Itamar Leite
    PROCEEDINGS OF THE 2022 GENETIC AND EVOLUTIONARY COMPUTATION CONFERENCE COMPANION, GECCO 2022, 2022, : 2063 - 2070