User`s guide

R2010b
10-2
GPU Computing
This release provides the ability to perform calculations on a graphics processing unit
(GPU). Features include the ability to:
• Use a GPU array interface with several MATLAB built-in functions so that they
automatically execute with single- or double-precision on the GPU — functions
including mldivide, mtimes, fft, etc.
• Create kernels from your MATLAB function files for execution on a GPU
• Create kernels from your CU and PTX files for execution on a GPU
• Transfer data to/from a GPU and represent it in MATLAB with GPUArray objects
• Identify and select which one of multiple GPUs to use for code execution
For more information on all of these capabilities and the requirements to use these
features, see GPU Computing.
Job Manager Security and Secure Communications
You now have a choice of four security levels when using the job manager as your
scheduler. These levels range from no security to user authentication requiring
passwords to access jobs on the scheduler.
You also have a choice to use secure communications between the job manager and
workers.
For more detailed descriptions of these features and information about setting up job
manager security, see Set MJS Cluster Security.
The default setup uses no security, to match the behavior of past releases.
Generic Scheduler Interface Enhancements
Decode Functions Provided with Product
Generic scheduler interface decode functions for distributed and parallel jobs are now
provided with the product. The two decode functions are named:
parallel.cluster.generic.distributedDecodeFcn
parallel.cluster.generic.parallelDecodeFcn