An efficient implementation of Bailey and Borwein's algorithm for parallel random number generation on graphics processing units

被引:2
|
作者
Beliakov, Gleb [1 ]
Johnstone, Michael [2 ]
Creighton, Doug [2 ]
Wilkin, Tim [1 ]
机构
[1] Deakin Univ, Sch Informat Technol, Burwood 3125, Australia
[2] Deakin Univ, Ctr Intelligent Syst Res, Geelong, Vic 3217, Australia
关键词
GPU; Random number generation; Normal numbers;
D O I
10.1007/s00607-012-0234-8
中图分类号
TP301 [理论、方法];
学科分类号
081202 ;
摘要
Pseudorandom number generators are required for many computational tasks, such as stochastic modelling and simulation. This paper investigates the serial and parallel implementation of a Linear Congruential Generator for Graphics Processing Units (GPU) based on the binary representation of the normal number . We adapted two methods of modular reduction which allowed us to perform most operations in 64-bit integer arithmetic, improving on the original implementation based on 106-bit double-double operations, which resulted in four-fold increase in efficiency. We found that our implementation is faster than existing methods in literature, and our generation rate is close to the limiting rate imposed by the efficiency of writing to a GPU's global memory.
引用
收藏
页码:309 / 326
页数:18
相关论文
共 50 条
  • [31] PARALLEL IMPLEMENTATION OF AN ERROR DIFFUSION HALFTONING ALGORITHM WITH A GENERAL PURPOSE GRAPHICS PROCESSING UNIT
    Seong, Becksang
    Ahn, Jaewoo
    Sung, Wonyong
    2010 IEEE INTERNATIONAL CONFERENCE ON IMAGE PROCESSING, 2010, : 3777 - 3780
  • [32] Optimizing the computation of a parallel 3D finite difference algorithm for graphics processing units
    Porter-Sobieraj, J.
    Cygert, S.
    Kikola, D.
    Sikorski, J.
    Slodkowski, M.
    CONCURRENCY AND COMPUTATION-PRACTICE & EXPERIENCE, 2015, 27 (06): : 1591 - 1602
  • [33] Global Memory Access Modelling for Efficient Implementation of the Lattice Boltzmann Method on Graphics Processing Units
    Obrecht, Christian
    Kuznik, Frederic
    Tourancheau, Bernard
    Roux, Jean-Jacques
    HIGH PERFORMANCE COMPUTING FOR COMPUTATIONAL SCIENCE - VECPAR 2010, 2011, 6449 : 151 - +
  • [34] PARALLEL PROCESSING OF RANDOM NUMBER GENERATION FOR MONTE-CARLO TURBULENCE SIMULATION
    KONIGES, AE
    LEITH, CE
    JOURNAL OF COMPUTATIONAL PHYSICS, 1989, 81 (01) : 230 - 235
  • [35] Efficient Acceleration of the Pair-HMMs Forward Algorithm for GATK HaplotypeCaller on Graphics Processing Units
    Ren, Shanshan
    Bertels, Koen
    Al-Ars, Zaid
    EVOLUTIONARY BIOINFORMATICS, 2018, 14
  • [36] Efficient Parallel Implementations of LWE-Based Post-Quantum Cryptosystems on Graphics Processing Units
    An, SangWoo
    Seo, Seog Chung
    MATHEMATICS, 2020, 8 (10) : 1 - 21
  • [37] Accelerating the Gillespie Exact Stochastic Simulation Algorithm Using Hybrid Parallel Execution on Graphics Processing Units
    Komarov, Ivan
    D'Souza, Roshan M.
    PLOS ONE, 2012, 7 (11):
  • [38] Efficient parallel implementation of the lattice Boltzmann method on large clusters of graphic processing units
    XIONG QinGang LI Bo XU Ji FANG XiaoJian WANG XiaoWei WANG LiMin HE XianFeng GE Wei State Key Laboratory of Multiphase Complex Systems Institute of Process Engineering Chinese Academy of Sciences Beijing China Graduate University of Chinese Academy of Sciences Beijing China
    Chinese Science Bulletin, 2012, 57 (07) : 707 - 715
  • [39] Efficient parallel implementation of the lattice Boltzmann method on large clusters of graphic processing units
    XIONG QinGang1
    2 Graduate University of Chinese Academy of Sciences
    Science Bulletin, 2012, (07) : 707 - 715
  • [40] Efficient parallel implementation of the lattice Boltzmann method on large clusters of graphic processing units
    Xiong QinGang
    Li Bo
    Xu Ji
    Fang XiaoJian
    Wang XiaoWei
    Wang LiMin
    He XianFeng
    Ge Wei
    CHINESE SCIENCE BULLETIN, 2012, 57 (07): : 707 - 715