Date:
Location:
RMB 323
MathWorks will be visiting campus for complimentary MATLAB seminars on Thursday, August 18th. These technical sessions will demonstrate how MATLAB is used as a flexible platform for mathematical modeling tasks and parallel computing. Faculty, researchers, staff, and students of all levels are all encouraged to join us. The full agenda is included below.
To learn more or to register, please click onto the following: http://www.mathworks.com/seminars/kentucky2011
Session 1: Mathematical Modeling with MATLAB
Presenter: Saket Kharsikar, Application Engineer
9:00 – 9:30 a.m.
Registration and sign-in. Walk-ins are welcome.
9:30a.m. – 12noon
Mathematical models are critical to understanding and accurately simulating the behavior of complex systems. They enable important tasks such as forecasting system behavior for various “what if” scenarios, characterizing system response, and designing control systems.
This session will show how you can use MATLAB products for mathematical modeling tasks, including:
• Developing models using data fitting and first-principle modeling techniques
• Optimizing the accuracy of models
• Simulating models and postprocessing results
• Documenting and sharing models
You will also learn about different approaches you can use to develop models, including developing models programmatically using the MATLAB language, deriving closed-form analytical equations using symbolic computation, and leveraging prebuilt graphical tools for specific modeling tasks such as curve and surface fitting.
Session 2: Parallel Computing with MATLAB
1:00 p.m. – 1:30 p.m.
Registration and sign-in. Walk-ins are welcome.
1:30p.m. - 3:30p.m.
In this session, you will learn how to solve computationally and data-intensive problems using multicore processors and computer clusters. We will introduce you to high-level programming constructs that allow you to parallelize your applications to boost execution speed. We will show you how to overcome the memory limits of your desktop computer and solve problems that require manipulating very large matrices by distributing your data. We will also illustrate how you can run the same application on a single machine using the Parallel Computing Toolbox and on a large scale computing resource such as a cluster, using the MATLAB Distributed Computing Server.
This session will cover:
• Toolboxes with built-in support for parallel computing
• Creating parallel applications to speed up independent tasks
• Programming with distributed arrays to work with large data sets
• Scaling up to computer clusters, grid environments or clouds
• Tips on developing parallel algorithms