Random Number Generators Conventions
This document makes no specific differentiation
between random, pseudorandom, and quasi-random numbers, nor between random,
pseudorandom, and quasi-random number generators unless the context requires
otherwise. For details, refer to the ‘ web page.
Random
Numbers
’ section in
VS Notesdocument provided at the Intel® oneAPI Math Kernel Library
All generators of nonuniform distributions, both
discrete and continuous, are built on the basis of the uniform distribution
generators, called Basic Random Number Generators (BRNGs). The pseudorandom numbers with
nonuniform distribution are obtained through an appropriate transformation of
the uniformly distributed pseudorandom numbers. Such transformations are
referred to as
generation methods. For a given distribution,
several generation methods can be used. See
VS Notes for the
description of methods available for each generator.
An RNG task determines environment in which random
number generation is performed, in particular parameters of the BRNG and its
internal state. Output of VS generators is a stream of random numbers that are
used in Monte Carlo simulations. A
random stream descriptor
and a
random stream
are used as synonyms of an
RNG task
in the document unless the context requires otherwise.
The
random stream
descriptor specifies which BRNG should be used in a given transformation
method. See the
Random Streams and RNGs in Parallel
Computation
section of
VS Notes.
The term
computational node means a logical or physical
unit that can process data in parallel.