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Journal ArticleDOI

Uniform random number generators for parallel computers

István Deák
- Vol. 15, pp 155-164
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TLDR
Generators of uniform random numbers are considered and assessed with respect to their possible use on parallel computers and two recent, commercially available computers are given special attention: the Connection Machine and the T Series.
Abstract
Almost all simulational computations require uniformly distributed random numbers. Generators of uniform random numbers are considered and assessed with respect to their possible use on parallel computers. Two recent, commercially available computers are given special attention: the Connection Machine and the T Series. Feedback shift register type generators with a large Mersenne prime are recommended for implementation on these computers.

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Citations
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Journal ArticleDOI

Algorithm 806: SPRNG: a scalable library for pseudorandom number generation

TL;DR: The random-number generator library as well as the suite of tests of randomness that is an integral part of SPRNG are discussed, as part of a description of the Scalable Parallel Random Number Generators (SPRNG).
Journal ArticleDOI

Testing parallel random number generators

TL;DR: Several tests of pseudorandom number generators, both statistical and application-based, are described and defects in several popular generators are shown.
Journal ArticleDOI

Parameterizing parallel multiplicative lagged-Fibonacci generators

TL;DR: This paper describes parallelization of the MLFG using parameterization, and discusses its implementation in the Scalable Parallel Random Number Generators (SPRNG) [ACM Trans. Math. Software 26 (2000) 436] parallel pseudorandom number generation software.
Journal ArticleDOI

A random number generator for parallel computers

TL;DR: An efficient parallelization of the Generalized Feedback Shift Register (GFSR) algorithm for generating pseudorandom numbers is presented and works on any parallel computer where the number of processors is a power of two and requires the same amount of memory per processor as required by the sequential GFSR algorithm.
References
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Book

Finite fields

Rudolf Lidl
Journal ArticleDOI

Random Numbers Generated by Linear Recurrence Modulo Two

TL;DR: Modulo-two linear recurrence technique for generating sequences of apparently random numbers that have certain regularities.
Journal ArticleDOI

Stochastic quasigradient methods and their application to system optimization

TL;DR: Stochastic quasigradient methods generalize the well-known stochastic approximation methods for uncnstrained optimization of the expectation of a random function to problems involving general constraints for deterministic nonlinear optimization problems.
Journal ArticleDOI

Generalized Feedback Shift Register Pseudorandom Number Algorithm

TL;DR: The generalized feedback shift register pseudorandom number algorithm has several advantages over all other pseudor random number generators, including an arbitrarily long period independent of the word size of the computer on which it is implemented and the “same” floating-point pseudOrandom number sequence is obtained on any machine.