codistributed.sprand - Create codistributed sparse array of uniformly distributed pseudo-random values

Syntax

Description

CS = codistributed.sprand(m, n, density) creates an m-by-n sparse codistributed array with approximately density*m*n uniformly distributed nonzero double entries.

Optional arguments to codistributed.sprand must be specified after the required arguments, and in the following order:

• codist — A codistributor object specifying the distribution scheme of the resulting array. If omitted, the array is distributed using the default distribution scheme. For information on constructing codistributor objects, see the reference pages for codistributor1d and codistributor2dbc.

• 'noCommunication' — Specifies that no interworker communication is to be performed when constructing the array, skipping some error checking steps.

CS = sprand(n, codist) is the same as CS = codistributed.sprand(n, codist). You can also use the optional arguments with this syntax. To use the default distribution scheme, specify a codistributor constructor without arguments. For example:

spmd
    CS = codistributed.sprand(8, 8, 0.2, codistributor1d());
end

Tips

When you use sprand 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

With four labs,

spmd(4)
    CS = codistributed.sprand(1000, 1000, .001);
end

creates a 1000-by-1000 sparse codistributed double array CS with approximately 1000 nonzeros. CS is distributed by its second dimension (columns), and each lab contains a 1000-by-250 local piece of CS.

spmd(4)
    codist = codistributor1d(2, 1:numlabs);
    CS = sprand(10, 10, .1, codist);
end

creates a 10-by-10 codistributed double array CS with approximately 10 nonzeros. CS is distributed by its columns, and each lab contains a 10-by-labindex local piece of CS.

See Also

codistributed.rand | distributed.sprandn | sprand

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