Create distributed sparse array of uniformly distributed pseudo-random values
DS = distributed.sprand(m,n,density)
DS = distributed.sprand(m,n,density) creates an
n sparse distributed array with
density*m*n uniformly distributed nonzero double
Create a 1000-by-1000 sparse distributed double array
approximately 1000 nonzeros.
DS = distributed.sprand(1000,1000,0.001);
When you use
sprand on the workers in the parallel pool, or in
an independent or communicating job, each worker sets its random generator seed to a
value that depends only on the
labindex or task ID. Therefore,
the array on each worker is unique for that job. However, if you repeat the job, you
get the same random data.