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The MathWorks today announced four enhancements in MATLAB® and Distributed Computing Toolbox that deliver increased performance and large data set handling. MATLAB now includes support for multithreaded computation for multicore systems and 64-bit Solaris platforms. Distributing Computing Toolbox now offers capabilities for developing applications that interleave parallel and serial code andinteractively prototyping parallel algorithms on a desktop computer by running four local MATLAB sessions.

These enhancements help today’s engineers and scientists model increasingly complex systems in less time by letting them develop parallel applications independently of the resources that are available for execution. With MATLAB and Distributed Computing Toolbox, they can prototype parallel applications on their multicore desktop computers using up to four processors and four MATLAB sessions. For more computing power, these applications can scale to a computer cluster without any code change by utilizing the MATLAB Distributed Computing Engine. The applications can also include serial code that is executed in the desktop machine.

With the multithreading feature, MATLAB applications using element-wise and linear algebra functions can take advantage of multicore machines by running multiple threads simultaneously for improved performance. Lastly, with 64-bit Solaris support, engineers using MATLAB can also leverage the benefits of 64-bit computing to develop applications involving large data sets and computationally intensive tasks.

“With the new Distributed Computing Toolbox enhancements, users can extend their MATLAB programs to utilize clusters with little or no code changes while working in their familiar interactive MATLAB environment,” said Silvina Grad-Freilich, manager of parallel computing marketing at The MathWorks.   “The new parallel for loop construct makes it very simple for users to distribute work right from the MATLAB command prompt. These new capabilities enhance problem solving abilities of engineers and scientists without letting the complexities of parallel programming get in the way.”

“Our group of biochemists, biologists, and physicists uses MATLAB because it lets us focus on solving complex problems over programming details,” said Andreas Korinek, researcher at the Max Planck Institute of Biochemistry. “Distributed Computing Toolbox enabled us to speed up our processing almost 20 to 30 times. We were able to use our cluster productively from the MATLAB environment itself without having to be experts in parallel programming or learning another programming language.”