Learn more about MATLAB Distributed Computing Server

Toolbox and Server Components

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Job Managers, Workers, and Clients Third-Party Schedulers Components on Mixed Platforms or Heterogeneous Clusters mdce Service

Job Managers, Workers, and Clients

The optional job manager can run on any machine on the network. The job manager runs jobs in the order in which they are submitted, unless any jobs in its queue are promoted, demoted, canceled, or destroyed.

Each worker receives a task of the running job from the job manager, executes the task, returns the result to the job manager, and then receives another task. When all tasks for a running job have been assigned to workers, the job manager starts running the next job with the next available worker.

A MATLAB Distributed Computing Server network configuration usually includes many workers that can all execute tasks simultaneously, speeding up execution of large MATLAB jobs. It is generally not important which worker executes a specific task. Each worker evaluates tasks one at a time, returning the results to the job manager. The job manager then returns the results of all the tasks in the job to the client session.

Note   For testing your application locally or other purposes, you can configure a single computer as client, worker, and job manager. You can also have more than one worker session or more than one job manager session on a machine.

Interactions of Parallel Computing Sessions

A large network might include several job managers as well as several client sessions. Any client session can create, run, and access jobs on any job manager, but a worker session is registered with and dedicated to only one job manager at a time. The following figure shows a configuration with multiple job managers.

Configuration with Multiple Clients and Job Managers

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Third-Party Schedulers

As an alternative to using the MathWorks job manager, you can use a third-party scheduler. This could be a Microsoft^® Windows HPC Server (including CCS), Platform LSF scheduler, PBS Pro scheduler, TORQUE scheduler, mpiexec, or a generic scheduler.

Choosing Between a Scheduler and Job Manager

You should consider the following when deciding to use a scheduler or the MathWorks job manager for distributing your tasks:

• Does your cluster already have a scheduler?

  If you already have a scheduler, you may be required to use it as a means of controlling access to the cluster. Your existing scheduler might be just as easy to use as a job manager, so there might be no need for the extra administration involved.

• Is the handling of parallel computing jobs the only cluster scheduling management you need?

  The MathWorks job manager is designed specifically for MathWorks parallel computing applications. If other scheduling tasks are not needed, a third-party scheduler might not offer any advantages.

• Is there a file sharing configuration on your cluster already?

  The MathWorks job manager can handle all file and data sharing necessary for your parallel computing applications. This might be helpful in configurations where shared access is limited.

• Are you interested in batch or interactive processing?

  When you use a job manager, worker processes usually remain running at all times, dedicated to their job manager. With a third-party scheduler, workers are run as applications that are started for the evaluation of tasks, and stopped when their tasks are complete. If tasks are small or take little time, starting a worker for each one might involve too much overhead time.

• Are there security concerns?

  Your scheduler may be configured to accommodate your particular security requirements.

• How many nodes are on your cluster?

  If you have a large cluster, you probably already have a scheduler. Consult your MathWorks representative if you have questions about cluster size and the job manager.

• Who administers your cluster?

  The person administering your cluster might have a preference for how jobs are scheduled.

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Components on Mixed Platforms or Heterogeneous Clusters

Parallel Computing Toolbox software and MATLAB Distributed Computing Server software are supported on Windows^®, UNIX^® (including Linux^®), and Macintosh^® operating systems. Mixed platforms are supported, so that the clients, job managers, and workers do not have to be on the same platform. The cluster can also be comprised of both 32-bit and 64-bit machines, so long as your data does not exceed the limitations posed by the 32-bit systems.

For a complete listing of all network requirements, including those for heterogeneous environments, see the System Requirements page for MATLAB Distributed Computing Server software at

http://www.mathworks.com/products/distriben/requirements.html

In a mixed platform environment, be sure to follow the proper installation instructions for each local machine on which you are installing the software.

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mdce Service

If you are using the MathWorks job manager, every machine that hosts a worker or job manager session must also run the mdce service.

The mdce service recovers worker and job manager sessions when their host machines crash. If a worker or job manager machine crashes, when mdce starts up again (usually configured to start at machine boot time), it automatically restarts the job manager and worker sessions to resume their sessions from before the system crash.

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Product Overview

Using Parallel Computing Toolbox Software

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