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| R2011b Documentation → Parallel Computing Toolbox | |
Learn more about Parallel Computing Toolbox |
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| Contents | Index |
This table summarizes what is new in Version 5.0 (R2010b):
| New Features and Changes | Version Compatibility Considerations | Fixed Bugs and Known Problems |
|---|---|---|
Yes | Yes — Details labeled as Compatibility Considerations, below. See also Summary. | Bug
Reports |
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.
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 Setting Job Manager Security.
The default setup uses no security, to match the behavior of past releases.
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
These functions are included on the workers' path. If your submit functions make use of the definitions in these decode functions, you do not have to provide your own decode functions. For example, to use the standard decode function for distributed jobs, in your submit function set MDCE_DECODE_FUNCTION to 'parallel.cluster.generic.distributedDecodeFcn'. For information on using the generic scheduler interface with submit and decode functions, see Use the Generic Scheduler Interface.
This release provides new sets of example scripts for using the generic scheduler interface. As in previous releases, the currently supported scripts are provided in the folder
matlabroot/toolbox/distcomp/examples/integration
In this location there is a folder for each type of scheduler:
condor — Condor®
lsf — Platform LSF®
pbs — PBS
sge — Sun™ Grid Engine
ssh — generic UNIX®-based scripts
winmpiexec — mpiexec on Windows
For the updated scheduler folders (lsf, pbs, sge), subfolders within each specify scripts for different cluster configurations: shared, nonshared, remoteSubmission.
For more information on the scripts and their updates, see the README file provided in each folder, or see Supplied Submit and Decode Functions.
Compatibility Considerations. For those schedulers types with updated scripts in this release (lsf, pbs, sge), the old versions of the scripts are provided in the folder matlabroot/toolbox/distcomp/examples/integration/old. These old scripts might be removed in future releases.
Batch jobs can now run functions as well as scripts. For more information, see the batch reference page.
The batch function and the functional form of matlabpool now accept a scheduler object as their first input argument to specify which scheduler to use for allocation of compute resources. For more information, see the batch and matlabpool reference pages.
The qr function now supports distributed arrays. For restrictions on this functionality, type
help distributed/qr
The mldivide function (\) now supports rectangular distributed arrays. Formerly, only square matrices were supported as distributed arrays.
When operating on a square distributed array, if the second input argument (or right-hand side of the operator) is replicated, mldivide now returns a distributed array.
Compatibility Considerations. In previous releases, mldivide returned a replicated array when the second (or right-hand side) input was replicated. Now it returns a distributed array.
The chol function now supports the 'lower' option when operating on distributed arrays. For information on using chol with distributed arrays, type
help distributed/chol
When returning only one output matrix, the eig and svd functions now return a distributed array when the input is distributed. This behavior is now consistent with outputs when requesting more than one matrix, which returned distributed arrays in previous releases.
Compatibility Considerations. In previous releases, eig and svd returned a replicated array when you requested a single output. Now they return a distributed array if the output is a single matrix. The behavior when requesting more than one output is not changed.
In addition to their original support for 1-D distribution schemes, the functionsctranspose and transpose now support 2-D block-cyclic ('2dbc') distributed arrays.
Distributed and codistributed arrays now support nan, NaN, inf and Inf for not-a-number and infinity values with the following functions:
| Infinity Value | Not-a-Number |
|---|---|
| codistributed.Inf | codistributed.NaN |
| codistributed.inf | codistributed.nan |
| distributed.Inf | distributed.NaN |
| distributed.inf | distributed.nan |
Parallel Computing Toolbox software now supports Microsoft Windows HPC Server 2008 R2. There is no change in interface compared to using HPC Server 2008. Configurations and other toolbox utilities use the same settings to support both HPC Server 2008 and HPC Server 2008 R2.
The user identified by the MDCEUSER parameter in the mdce_def file is now granted all necessary privileges on a Windows system when you install the mdce process. For information about what permissions are granted and how to reset them, see Setting the User.
In past releases, you were required to set the MDCEUSER permissions manually. Now this is done automatically when installing the mdce process.
 | Version 5.1 (R2011a) Parallel Computing Toolbox Software | Version 4.3 (R2010a) Parallel Computing Toolbox Software |  |
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