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Events - Seminars

Technical Computing with MATLAB at Lawrence Berkeley National Lab

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:

Doug Eastman, Application Engineer

10:00 a.m. - 12:00 p.m.

Session 1

Introduction to Scientific Computing with MATLAB

This seminar will focus on using the MATLAB technical computing environment and language for scientific and engineering calculations. Demonstrations will include accessing data from a variety of sources; visualizing the data and creating custom, automated figures for reports; and leveraging the thousands of built-in functions in MATLAB to quickly and accurately analyze your data. We will explore the features you can use to report your results and to create MATLAB based graphical applications that you can deploy to those who don’t have MATLAB. The seminar will also introduce the MuPAD notebook interface in Symbolic Math Toolbox and using Parallel Computing Toolbox to accelerate the execution of your MATLAB analyses. Although the seminar is geared toward new users, seasoned MATLAB users will discover new tips and features along the way.

Highlights Include:

  • Overview of MathWorks data analysis tools
  • Data analysis demo
  • Simple GUI development
  • Tools for symbolic computing
  • Solving larger problems using parallel computing
  • Questions and answers
1:00 p.m. - 3:00 p.m.

Session 2

Speeding Up Applications: Parallel Computing with MATLAB

In this session, we will demonstrate how to perform parallel and distributed computing in MATLAB to boost execution speed on computationally intensive problems and how to handle larger data sets. We will introduce you to parallel processing constructs such as parallel for-loops, distributed arrays, and message-passing functions. We will also show you how to take advantage of common trends in computer hardware, including multiprocessor machines and computer clusters.

Highlights Include: 

  • Built-in support for parallel computing
  • Go faster: Task parallel processing
  • Grow larger: Data parallel processing
  • Scaling up: Interactive to scheduled jobs
  • Tips on developing parallel code
  • Questions and answers

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