User`s guide

17-5
Compatibility Considerations
In the previous version of the toolbox, the distributor function was used to define how
an array was distributed. In many cases, you can replace a call to distributor with a
call to darray. For example, if you used distributor without arguments as an input to
an array constructor,
rand(m, n, distributor());
you can update the code to read,
rand(m, n, darray());
rand Seeding Unique for Each Task or Lab
The random generator seed is now initialized based on the task ID for distributed jobs,
or the labindex for parallel jobs (including pmode). This ensures that the set of random
numbers generated for each task or lab within a job is unique, even when you have more
than 82 tasks or labs.
Compatibility Considerations
In the previous version of the distributed computing products, the rand function could by
default generate the same set of numbers for some tasks or labs when these exceeded 82
for a job.
Single-Threaded Computations on Workers
Despite the ability in MATLAB software to perform multithreaded computations on
multiple-CPU machines, the workers and labs running distributed and parallel jobs
perform only single-threaded computations, so that multiprocessor cluster machines can
better accommodate multiple workers or labs.