Star-P Performance on IBM Linux Clusters | Parallel Application Development for MATLAB® and Python Users


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Breakthrough Performance for MATLAB®, Python and Other Desktop Applications!

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Star-P® Performance on IBM Linux Clusters
		Summary By leveraging Star-P, users can continue to make highly effective use of their interactive desktop computing systems, even as they dramatically scale up the size and complexity of their computational models. Users will benefit from the productivity, ease of use, and familiarity of their desktop systems, while still achieving high levels of performance due to the transparent use of a backend supercomputer under the covers. Get the White Paper

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White Paper Library
Discover how Star-P users are experiencing a 10X-100X performance increase.

Application Library
See application notes for a broad range of algorithms and models.

Going Parallel Kit
The downloadable kit contains a Case Study, White Paper, and Product Overview.

Star-P Interactive Tour
Online presentations and demos show how Star-P significantly accelerates parallel code development.

IDC Case Study
This IDC Buyer Case Study examines the usage of Star-P at Air Force Research Lab (AFRL).

Key Questions to Ask Your Parallel Software Vendor
Explore the factors to determine the best parallel tool for your unique needs.

Parallel MATLAB® Survey
The survey, published in the Proceedings of the IEEE, reviews 27 parallel MATLAB® projects.

FREE Technical Assessment!
Get a free technical assessment on parallelizing your desktop code!

Star-P Brochure (PDF - 3MB)

Star-P + MATLAB® Data Sheet (PDF)

MATLAB® functions (PDF)

MATLAB® Toolbox functions (PDF)

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