Create codistributed sparse array of uniformly distributed pseudo-random values
CS = codistributed.sprandn(m,n,density)
CS = sprandn(n,codist)
CS = codistributed.sprandn(m,n,density)
creates
an m
-by-n
sparse codistributed
array with approximately density*m*n
normally distributed
nonzero double entries.
Optional arguments to codistributed.sprandn
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 = sprandn(n,codist)
is the same as CS
= codistributed.sprandn(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.sprandn(8,8,0.2,codistributor1d()); end
With four workers,
spmd(4) CS = codistributed.sprandn(1000,1000,0.001); 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 worker contains a 1000-by-250
local piece of CS
.
spmd(4) codist = codistributor1d(2,1:numlabs); CS = sprandn(10,10,0.1,codist); end
creates a 10-by-10 codistributed double array CS
with
approximately 10 nonzeros. CS
is distributed by
its columns, and each worker contains a 10-by-labindex
local
piece of CS
.
codistributed.speye
| codistributed.sprand
| distributed.sprandn
| rand
| randn
| sparse
| sprandn