Learn more about Parallel Computing Toolbox

Programming Tips and Notes

On this page…
Saving or Sending Objects Current Working Directory of a MATLAB Worker Using clear functions Running Tasks That Call Simulink Software Using the pause Function Transmitting Large Amounts of Data Interrupting a Job Speeding Up a Job

Saving or Sending Objects

Do not use the save or load function on Parallel Computing Toolbox objects. Some of the information that these objects require is stored in the MATLAB session persistent memory and would not be saved to a file.

Similarly, you cannot send a parallel computing object between parallel computing processes by means of an object's properties. For example, you cannot pass a job manager, job, task, or worker object to MATLAB workers as part of a job's JobData property.

Back to Top

Current Working Directory of a MATLAB Worker

The current directory of a MATLAB worker at the beginning of its session is

CHECKPOINTBASE\HOSTNAME_WORKERNAME_mlworker_log\work

where CHECKPOINTBASE is defined in the mdce_def file, HOSTNAME is the name of the node on which the worker is running, and WORKERNAME is the name of the MATLAB worker session.

For example, if the worker named worker22 is running on host nodeA52, and its CHECKPOINTBASE value is C:\TEMP\MDCE\Checkpoint, the starting current directory for that worker session is

C:\TEMP\MDCE\Checkpoint\nodeA52_worker22_mlworker_log\work

Back to Top

Using clear functions

Executing

clear functions

clears all Parallel Computing Toolbox objects from the current MATLAB session. They still remain in the job manager. For information on recreating these objects in the client session, see Recovering Objects.

Back to Top

Running Tasks That Call Simulink Software

The first task that runs on a worker session that uses Simulink software can take a long time to run, as Simulink is not automatically started at the beginning of the worker session. Instead, Simulink starts up when first called. Subsequent tasks on that worker session will run faster, unless the worker is restarted between tasks.

Back to Top

Using the pause Function

On worker sessions running on Macintosh or UNIX operating systems, pause(inf) returns immediately, rather than pausing. This is to prevent a worker session from hanging when an interrupt is not possible.

Back to Top

Transmitting Large Amounts of Data

Operations that involve transmitting many objects or large amounts of data over the network can take a long time. For example, getting a job's Tasks property or the results from all of a job's tasks can take a long time if the job contains many tasks.

Back to Top

Interrupting a Job

Because jobs and tasks are run outside the client session, you cannot use Ctrl+C (^C) in the client session to interrupt them. To control or interrupt the execution of jobs and tasks, use such functions as cancel, destroy, demote, promote, pause, and resume.

Back to Top

Speeding Up a Job

You might find that your code runs slower on multiple workers than it does on one desktop computer. This can occur when task startup and stop time is not negligible relative to the task run time. The most common mistake in this regard is to make the tasks too small, i.e., too fine-grained. Another common mistake is to send large amounts of input or output data with each task. In both of these cases, the time it takes to transfer data and initialize a task is far greater than the actual time it takes for the worker to evaluate the task function.

Back to Top

Programming with User Configurations

Using the Parallel Profiler

© 1984-2009- The MathWorks, Inc.    -   Site Help   -   Patents   -   Trademarks   -   Privacy Policy   -   Preventing Piracy   -   RSS