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Events - Seminars

Technical Computing with MATLAB at the University of Miami

Seminar Overview

Please join The MathWorks for a complimentary seminar.



Thank you for your interest in MathWorks Seminars. There are no dates currently scheduled for this Seminar. For more information on our seminars and products contact MathWorks sales or please visit:


Agenda
Presenter:

Saket Kharsikar, Application Engineer

8:45 a.m. - 9:00 a.m.

Registration and sign-in. Walk-ins are welcome.

9:00 a.m. - 11:30 a.m.

Room Location:  Whitten University Center, Flamingo D

Session 1:

Data Acquisition, Analysis, and Visualization using MATLAB (MATLAB overview)

During this session we will use examples to demonstrate how to acquire, analyze, and visualize data through mathematical, statistical, and engineering functions that support common engineering operations. This session is designed to be an overview of the MATLAB technical computing environment. R2009b will be used for this demonstration.

Highlights include:

• Importing data from various sources
• Performing statistical analysis
• Automating analysis via automatic m-code generation
• Building GUIs and generating reports

1:15 p.m. - 1:30 p.m.

Registration and sign-in. Walk-ins are welcome.

1:30 p.m. - 3:30 p.m.

Room Location: SLAB Seminar Room at the Rosenstiel School of Marine and Atmospheric Science, University of Miami

Session 2:

Speeding Up MATLAB Applications with Parallel Computing

We will discuss and demonstrate how to perform parallel and distributed computing in MATLAB to boost execution speed on computationally and data-intensive problems. We will introduce you to parallel processing constructs such as parallel for-loops, distributed arrays, parallel numerical algorithms and message-passing functions that let you implement task and data parallel algorithms in MATLAB at a high level without programming for specific hardware and network architectures.

Highlights include:

  • Applications of parallel computing
  • Implicit multi-threaded computations
  • Interactive task and data parallel applications
  • Interactive applications to scheduled applications
  • Scaling your work up to a computer cluster

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