Parallel Computing Support for Random Number Generation
What is Parallel Computing?
Parallel computing is the technique of
using multiple processors on a single problem. The primary reason
to use parallel computing is to shorten the computation time.
The following functions use random number generators and support
both parallel and serial computation. They supply two options to
control random number generation, whether in serial and parallel mode.
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Reproducing Computations
The previous functions include the 'UseSubstreams' option.
This option provides a quick and easy way to reproduce computations
performed using random number generators. Use this option to rerun
a command with reproducible results, whether using serial or parallel
computation. This option is available only with RandStream types that support substreams.
The default is not to use substreams, since reproducing random number
streams is not commonly desired.
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Assigning Random Number Generators
The previous functions also include the 'Streams' option.
use 'Streams' to assign specific random number
streams to each processor used in the function evaluation, both in
serial and parallel mode. The default is to use the default random
number stream on each processor. The option can be used to control
statistical behavior in your code and in function libraries that
you use.
For more information on each of these options, see the function
reference pages.
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 | Common Generation Methods | | Representing Sampling Distributions Using Markov Chain Samplers |  |
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