Star-P® Demonstrations
Registration is required to view these demonstrations.
Parallel Programming For Engineers, Scientists and Analysts |
Start here if you are new to Star-P®. Understand Star-P basics: value proposition product structure and operations.
Level: Introductory (7:06) |
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Star-P Product Demonstration |
Star-P's easy-to-use data and task-parallel features are demonstrated. FFTs, inv and matrix multiplication are run in serial MATLAB® and then accelerated in Star-P.
Level: Introductory (7:03) |
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Star-P at a Glance |
Understand the main components of the Star-P platform; client, server, computation engine functions and Star-P connect.
Level: Introductory (4:31) |
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Parallel Computing with Star-P |
This presentation provides an overview of the Star-P product showing how minimal code changes allow serial applications
to run in parallel on SMPs and clusters.
Level: Introductory (8:37) |
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Large Number Crunching |
This demonstration shows interactive, parallel processing of very large arrays in MATLAB. Single and two dimensional FFTs are calculated in real-time.
Level: Intermediate (3:31) |
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Star-P On-Demand Demonstration |
Use Star-P On Demand is demonstrated by running an application first on a local desktop and then remotely "in the cloud." See how easy it is to use server based computing to accelerate your analysis.
Level: Introductory (6:45) |
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Real Time Image Tracking |
See how image tracking in MATLAB can be accelerated by the use of ppeval. Images are processed in parallel.
Level: Introductory (2:20) |
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Image Compression using SVD |
Singular value decomposition is used in image processing, signal processing, bioinformatics but is computationally intensive. This image compression example shows how Star-P's data-parallel capabilities can be used to accelerate the application with minimal code changes.
Level: Intermediate (3:09) |
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Scaling and Performance |
Benchmark results from a wide range of disciplines including microwave and radar, finance, brain scans and linear algebra. |  |
Singular Value Decomposition in Image Processing Using Star-P |
This demonstration shows how SVD can be used to compress images and then shows how Star-P's data-parallel implementation of SVD substantially accelerates that processing and enables work with very large images.
Level: Intermediate (10:21) |
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MRI Brain Scan Analysis using Star-P |
The analysis of MRI data can be greatly accelerated by the use of HPC. This demo shows how simple modifications to existing MATLAB codes enable orders of magnitude of speed-up.
Level: Intermediate (6:53) |
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Google PageRank™ Algorithm |
Using a sample data set derived from the MIT web site, this demonstration shows how a page ranking algorithm can be easily transformed to run in parallel.
Level: Intermediate (5:06) |
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Extending Apps with Star-P |
Provides an overview of how to integrate C++, C and FORTRAN routines into the Star-P environment.
Level: Advanced (7:03) |
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Computing Wave Propagation using Star-P and Python |
Using array and linear algebra functionality from NumPy, Star-P is used to parallelize a wave propagation problem.
Level: Intermediate (4:34) |
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Parallelizing MATLAB with Star-P Part I |
Sean Mortazavi from Microsoft and Interactive Supercomputing's Ronnie Hoogerwerf discuss parallelizing MATLAB® code with Star-P. |  |
Parallelizing MATLAB with Star-P Part II |
Sean Mortazavi from Microsoft and Interactive Supercomputing's Ronnie Hoogerwerf discuss parallelizing MATLAB® code with Star-P. |  |