Affiliated Education Activities
Visual Analysis Lab

Virginia Tech

1. NSF-Science and Technology Center Summer Undergraduate Research Program (SURP)

2. UH3004 / (NoteBook) Undergraduate Honors Class: High Performance and Scientific Computing

3. ESM4714 (formerly ESM5984) / (NoteBook) /
    Student Projects ( 91/ 92/ 93/ 94/ 95/ 96/ 97): Scientifc Visual Analysis with Multimedia

4. Independent Projects Completed in the Viz Lab.

 
Instructors: Christopher Beattie, Department of Mathematics and 
             Calvin Ribbens, Department of Computer Science.

More information on UH3004: High Performance and Scientific Computing

This Honors Colloquium in "High Performance Scientific Computing" is being offered for the first time in Spring, 1995. Co-taught by Professors Chris Beattie (Math) and Cal Ribbens (Computer Science), the course is based on materials developed at the University of Colorado. The focus is on computational science, vector and parallel computers, and scientific visualization.

The past decade has seen the rise of computational science as a major component of science and engineering. While computing has been an important tool in many disciplines for almost fifty years, the role of computation has grown especially significant with the recent widespread availability of large-scale, high-performance computers (i.e., "supercomputers," "massively parallel computers," etc.). For example, aircraft designers now use computational models to validate, and in some cases replace, wind tunnel experiments to study air flow around proposed designs. In this and many other disciplines computational methods have joined experimental and theoretical approaches as a third major paradigm for doing science and engineering.

The main goal of this course is to give students an understanding of high-performance computing systems, of the algorithms designed to run on them, and of the important issues which must be dealt with in modern large-scale scientific computation. Furthermore, we are studying these systems, algorithms, and issues without divorcing them from the motivating problem contexts.  High-performance scientific computing is an exciting and rapidly-changing field. We hope to give a sense of where computation fits into the work of science, and of where science fits into the work of computing.

Given the time constraints of one semester we cannot hope to cover a great many topics in detail. Instead our approach is to choose two high-performance machines and two (nearly) real-world problems, and study them in some depth. The machines we at are the Cray Y-MP and the Intel Paragon. The problems are taken from molecular dynamics and advection. We also examine the role of high-end workstations in modern scientific computing. Finally, since virtually all nontrivial scientific computations produce and/or consume large amounts of data, we introduce some concepts and tools used in the increasingly important field of scientific visualization.

 
Instructors: Ron Kriz, Director, Laboratory for Scientific Visual Analysis 
             Jason Lockhart, Director, Multimedia Laboratory
             College of Engineering
             College of Architecture & Urban Studies

Class Notebook for students: General Information, Exercises and Assignments.

During the spring semester, a course titled, "Scientific Visual Data Analysis with Multimedia" (class syllabus) is taught by Dr. Ron Kriz and Mr. Jason Lockhart. The first half of the class is taught in the Visual Analysis Lab and the second half is taught in the Multimedia Lab. During this course, there are three guest lectures, one on data structures by Duane Taylor, one on Chaos and Fractals by Scott Hendricks, and one on Chemical Structures by Tim Pickering.

The course is designed to introduce the student to new state-of-the-art computer graphic tools for scientific analysis and multmedia presentation of the results. The course focuses on how to use (not develop) graphic tools in research activities. The lectures demonstrate how visual tools were first used by scientists such as Galileo and others in their scientific investigations and how we can extend these time-honored principles to the computer graphic workstation.

In this course, students develop an increased understanding of how to use visual tools for interpretation and analysis of large data sets where relationships between physical properties can be better understood or possibly new relationships could be discovered. Students learn how to use multimedia software to effectively communicate these research results to others. Emphasis is placed on how to create an effective multimedia presentation. Most of the course is one-on-one hands-on guidance from the instructors.

Other examples of using computers in educational programs at Virginia Tech.

Ron Kriz, Director of Lab introducing his class on Scientific Visualization. (Note: 24.7 Mb Quicktime movie playable on non-Macintosh machines.)