Random numbers for parallel computers: requirements and methods, with emphasis on gpus

DOI10.1016/j.matcom.2016.05.005OpenAlexW2416145065WikidataQ60347109 ScholiaQ60347109MaRDI QIDQ2229030

David Munger, Pierre L'Ecuyer, Richard Simard, Boris N. Oreshkin

Publication date: 19 February 2021

Published in: Mathematics and Computers in Simulation (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.matcom.2016.05.005

zbMATH Keywords

simulationMonte Carloparallel computingrandom number generatorsmultiple streams

Mathematics Subject Classification ID

Probabilistic methods, stochastic differential equations (65Cxx)

Related Items (6)

Random number generators produce collisions: Why, how many and more ⋮ A search for good pseudo-random number generators: survey and empirical studies ⋮ Exponential decay of correlations functions in MIXMAX generator of pseudorandom numbers ⋮ Spectral Analysis of the MIXMAX Random Number Generators ⋮ Improving the statistical quality of random number generators by applying a simple ratio transformation ⋮ On the probability of overlap of random subsequences of pseudorandom number generators

Uses Software

• R
• SPRNG
• MersenneTwister
• HASPRNG
• RngSteam
• TestU01
• RngStreams
• GASPRNG
• MRG32k3a
• xorgens
• SFMT
• RngStreams
• ContactCenters

Cites Work

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• Improved long-period generators based on linear recurrences modulo 2
• Handbook of computational statistics. Concepts and methods.
• Pseudo-random number generation for Brownian dynamics and dissipative particle dynamics simulations on GPU devices
• HASPRNG: hardware accelerated scalable parallel random number generators
• Parallelization of random number generators and long-range correlations
• Pseudo-random trees: Multiple independent sequence generators for parallel and branching computations
• Good random number generators are (not so) easy to find
• A random number generator based on the combination of four LCGs
• Uniform random number generation
• Combined generators with components from different families
• Using rngstreams for parallel random number generation in C++ and R
• Large-Order Multiple Recursive Generators with Modulus 2³¹ − 1
• Efficient Jump Ahead for 𝔽₂-Linear Random Number Generators
• On the Lattice Structure of a Special Class of Multiple Recursive Random Number Generators
• Variants of Mersenne Twister Suitable for Graphic Processors
• Random Number Generators on Vector Supercomputers and Other Advanced Architectures
• TestU01
• Structural Properties for Two Classes of Combined Random Number Generators
• Tables of maximally equidistributed combined LFSR generators
• Mersenne twister
• Combined Multiple Recursive Random Number Generators
• Bad Lattice Structures for Vectors of Nonsuccessive Values Produced by Some Linear Recurrences
• Implementing a random number package with splitting facilities
• Good Parameters and Implementations for Combined Multiple Recursive Random Number Generators
• On the xorshift random number generators
• Maximally equidistributed combined Tausworthe generators

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