distributed.rand - Create distributed array of uniformly distributed pseudo-random numbers
Syntax
R = distributed.rand(n)
R = distributed.rand(m, n, ...)
R
= distributed.rand([m, n, ...])
R = distributed.rand(..., classname)
Description
R = distributed.rand(n) creates an n-by-n
codistributed array of underlying class double.
R = distributed.rand(m, n, ...) or R
= distributed.rand([m, n, ...]) creates an m-by-n-by-...
distributed array of underlying class double.
R = distributed.rand(..., classname) specifies
the class of the distributed array R. Valid choices
are the same as for the regular rand function: 'double' (the
default), 'single', 'int8', 'uint8', 'int16', 'uint16', 'int32', 'uint32', 'int64',
and 'uint64'.
Remarks
When you use rand on the workers in the MATLAB
pool, or in a distributed or parallel job (including pmode), each
worker or lab sets its random generator seed to a value that depends
only on the lab index or task ID. Therefore, the array on each lab
is unique for that job. However, if you repeat the job, you get the
same random data.
Examples
Create a 1000-by-1000 distributed matrix of random values of
class double:
R = distributed.rand(1000);
See Also
rand MATLAB function
reference page
codistributed.rand, distributed.randn, distributed.sprand, distributed.sprandn
 | distributed.ones | | distributed.randn |  |
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