parforon workers in a parallel pool
Parallel Computing Toolbox™ supports interactive parallel
computing and enables you to accelerate your workflow by running on
multiple workers in a parallel pool. When you have profiled your code
and identified slow
for-loops, you can try
increase your throughput.
For more details, see the video From
Discover basic concepts of a
and decide when to use it.
Learn how to turn a
Modify a simple
for-loop so that
it runs in parallel.
Learn the intricacies of using dependent and nonindexed
variables in a
Discover how to use objects, handles, and sliced variables
Use function handles and function calls to deal with
nesting limitations in
Use unambiguous variable names and
Distinguish between loop, sliced, broadcast, reduction,
and temporary variables in
All references to variables in
must be visible in the body of the program.
Create arrays inside or outside
to speed up code.
Learn about starting and stopping parallel pools, pool size, and cluster selection.
Specify your preferences, and automatically create a parallel pool.
parfor-loops on your
desktop and scale up to a cluster without changing your code.
You can use
parfor-loops to calculate
cumulative values, that are updated by each iteration.
Control random number generation in
by assigning a particular substream for each iteration.