Date: 26th Nov 09
Parallel computing toolbox from
MathWorks to enable multicore computing
MathWorks has released a new version of Parallel Computing
Toolbox that provides an improved distributed array construct
to enable MATLAB users to directly access from a MATLAB
session data that is stored on multicore computers or computer
clusters.
Parallel Computing Toolbox used with two additional MathWorks
toolboxes to accelerate specific algorithms on multiprocessing
hardware without requiring to write or modify a single line
of code.
Algorithms in Statistics Toolbox have been modified, including
the bootstrap and cross-validation algorithms, which are
resampling methods that require repeatedly evaluating statistical
functions on multiple data samples. Similarly, algorithms
in Communications Toolbox have been modified so that you
can run computationally intensive simulations of error-rate
performance models in parallel. These enhancements build
on the existing set of toolbox algorithms that take advantage
of parallel operations, such as those in Optimization Toolbox
and Genetic Algorithm and Direct Search Toolbox.
In addition, key algorithms in Statistics Toolbox and Communications
Toolbox execute fast when run in conjunction with Parallel
Computing Toolbox.
"As hardware systems become more powerful, MATLAB
users are increasingly presented with data-intensive problems
that involve highly complex data sets," said Silvina
Grad-Freilich, manager of parallel computing and application
deployment marketing at The MathWorks. "By adding parallel
computing capabilities to our products, users can more easily
take advantage of the benefits of parallelized applications
to operate their large data sets. And because users can
remain in the MATLAB environment, the cost is small and
their workflow is streamlined, leading to results sooner."
For more details visit www.mathworks.in
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