"Introduction to Matlab for Graduate Students"
February 24 - 9, 4:30pm - 6:30pm

E-classroom, 225 Lewis Science Library

Speaker: Eric Cady, Mechanical and Aerospace Engineering, Princeton

This hands-on mini-course introduces graduate students to the use of MATLAB. Familiarity with undergraduate mathematics will be assumed.

Topics covered include:

• * The basics of MATLAB (using the interface, writing and running scripts, importing data)
• * Plotting data (2D & 3D plots, modifying appearances of plots)
• * Numerical mathematics (linear algebra, numerical integration, numerical solutions to ODEs)
• * Advanced tools and toolboxes (code profiling and debuggers, curve fitting, statistical analysis, symbolic math, etc.)

"Introduction to Parallel Debugging"
March 24, 4:30pm - 6:30pm

E-classroom, 225 Lewis Science Library

Speaker: Dr. Stephane Ethier, Computational Scientist, PPPL

This hands-on mini-course will introduce the participants to different approaches in tackling the task of parallel debugging, including the use of advanced parallel debuggers, such as Totalview and DDT.

Overview: Debugging single processor code is already a daunting task that usually consumes a lot of development time. Luckily, many debugging tools are available to help the developer pinpoint the problem by controlling the state of execution. When dealing with large multi-processor code, however, this task becomes a true challenge for which the usual tools sometimes fail to provide a satisfactory solution when used exclusively.

"Introduction to Visualization using VisIt"
April 28, 4:30pm - 6:30pm

E-classroom, 225 Lewis Science Library

Speaker: Dr. Simon Su, Visualization Analyst, PICSciE

This hands-on mini-course will introduce the participants to use VisIt to visualize their data, including how to load their data into VisIt, configure VisIt for parallel visualization using PICSciE-TIGRESS HPC facilities, and how to do basic plots with the sample data.

Overview: Verifying results and determine accuracy of the output of a large simulation can some time be a challenging process given the sheer size of the data generated by the numerical simulation. In most cases, the preliminary step in simulation results verification involves some kind of visualization with the simulation data. However, most complex simulations are producing data in size that can no longer be handled by a single stand-alone desktop machine. VisIt was developed to address these next generation visualization challenges. The scalability of VisIt allows it to be used to visualize a simple data with a few byte in size to complex data set that is a few gigabytes per time step.

"Introduction to Visualizing with Paraview"
May 12, 9:00am - 4:00pm

E-classroom, 225 Lewis Science Library

Speaker: Dr. Andrew Bauer, Research Staff, Kitware, Inc.

This hands-on mini-course will introduce participants to visualizing scientific data with ParaView (paraview.org) which is an open-source, multi-platform data analysis and visualization application.

Overview: Analyzing output from large scale numerical simulations can be a daunting task. This can include both the visualization as well as the quantitative analysis of the results. ParaView can be used to quickly build visualizations to analyze data using both qualitative and quantitative techniques. The data exploration can be done interactively in 3D or programmatically using ParaView’s batch processing capabilities. ParaView was developed to analyze extremely large datasets using distributed memory computing resources. It can be run on supercomputers to analyze datasets of terascale as well as on laptops for smaller data.

Dr. Andrew Bauer obtained his B.S. in Mechanical Engineering from Binghamton University in 1996. He earned his Ph.D. from the University at Buffalo in 2003, with his dissertation on Efficient Solution Procedures for Adaptive Finite Element Methods – Applications to Elliptic Problems. His work has been published in several peer-reviewed, international conferences and journals. His current work with Kitware, Inc. involves enabling technologies for large-scale, PDE-based numerical simulations with main focus is on efficient simulation setup & in-situ visualization.

Please email Andrea Rubinstein, alrubins@princeton.edu to register.

Fall 2004 - Spring 2005