1. MATLAB Distributed, and Other Toolboxes
Rahman Tashakkori, ASU
"A Consortium to Promote Computational Science and High Performance Computing" Video Conference April 18, 2005

2. Distributed Toolbox
The MathWorks web site was the main source of the MATLAB related information on this presentation
The Distributed Computing Toolbox works with the MATLAB Distributed Computing Engine to execute coarse-grained MATLAB algorithms and Simulink models in a cluster of computers
You can prototype and develop applications in the MATLAB environment and then use the Distributed Computing Toolbox to divide them into independent tasks.
The MATLAB Distributed Computing Engine evaluates these tasks on remote MATLAB sessions.

3. Distributed Toolbox: Key Features
Distributed execution of coarse-grained MATLAB algorithms and Simulink models on remote MATLAB sessions
Control of the distributed computing process via a function-based or an object-based interface
Distributed processing on both homogeneous and heterogeneous platforms
Support for synchronous and asynchronous operations
Access to single or multiple clusters by single or multiple users

4. Distributed Toolbox

5. Creating and Submitting Jobs with the Distributed Computing Toolbox
The toolbox includes functions for defining jobs, dividing them into tasks, sending them to the MATLAB Distributed Computing Engine for execution, and retrieving the results. The complete process includes five steps:
Finding a job manager
Creating a job
Creating tasks
Submitting the job to the job queue
Retrieving results

6. Image Processing Toolbox
The Image Processing Toolbox is a collection of functions that support a wide range of image processing operations, including:
Spatial image transformations
Morphological operations
Neighborhood and block operations
Linear filtering and filter design
Transforms
Image analysis and enhancement
Image registration
Deblurring
Region of interest operations

7. Reading and displaying images
The Image Processing Toolbox supports four basic types of images:
Indexed images
Intensity images
Binary images
RGB images
Reading and Writing Image Data         Reading a Graphics Image         Writing a Graphics Image         Querying a Graphics File         Converting Image Storage Classes         Converting Graphics File Formats         Reading and Writing DICOM Files

8. Wavelet Toolbox
Wavelet analysis has become very popular in image processing. The main idea is to break an image into sub-bands in different frequency and time domain. MATLAB provides an excellent toolbox for performing wavelet analysis on both one- and two-dimensional data.

9. Bioinformatics Toolbox
The Bioinformatics Toolbox offers computational molecular biologists and other research scientists an open and extensible environment in which to explore ideas, prototype new algorithms, and build applications in drug research, genetic engineering, and other genomics and proteomics projects.
The toolbox provides access to genomic and proteomic data formats, analysis techniques, and specialized visualizations for genomic and proteomic sequence and microarray analysis. Most functions are implemented in the open MATLAB language, enabling you to customize or develop your own algorithms.

10. Bioinformatics Toolbox Key Features
Genomic, proteomic, and gene expression file formats
Internet database access
Functions for sequence alignment and manipulation
Phylogenetic tree analysis tools
Capabilities for microarray data analysis and visualization
Support for mass spectrometry preprocessing and analysis
Statistical learning functionality
The Bioinformatics Toolbox requires the Statistics Toolbox

11. Signal Processing Toolbox
The Signal Processing Toolbox is a collection of industry-standard algorithms for analog and digital signal processing. It provides graphical user interfaces for interactive design and analysis and command-line functions for advanced algorithm development.

12. SPT Key Features Comprehensive set of signal and linear system models
Tools for finite impulse response (FIR) and infinite impulse response (IIR) digital filter design, analysis, and implementation
Tools for analog filter design
Access to the most widely used transforms, such as fast Fourier and discrete cosine
Tools for spectral analysis and statistical signal processing
Functions for parametric time-series modeling
Routines for waveform generation, including a Gaussian pulse generator, a periodic sinc generator, and a pulse train generator
Extensive data windowing algorithms

13. Fully or Partially Supported MATLAB-based Research Projects ASU
An Efficient Medical Image Content-based Search Approach, May 2005
Steve Heffner’s honor’s thesis

14. Current Results Sequential (sec) Distributed (sec) 4 nodes only
Image 1
406.30
99.85
Image 2
950.56
248.66
Image 3

15. Fully or Partially Supported MATLAB-based Research Projects ASU
A Lifting-Based Knowledge Discovery in Microarray Data
Scott A. Barllowe M.S. Thesis
Current Results
Sequential (sec)
Distributed (sec)
2 nodes only
Wave Cluster
136.78
46.17