Computational Science and Education: Courses and Degrees at CRPC Sites

For parallel computing technology to be truly useful, hardware and software developments must be coupled with educational innovation. Since its inception in 1989, one of the CRPC's primary goals has been to help train a new generation of scientists and engineers who are familiar with both scientific problem-solving and parallel computation.

At Caltech, Syracuse University, and Rice University, the CRPC has helped to establish groundbreaking computational science programs that emphasize parallel computing. Initiated in the fall of 1992, Syracuse University's School of Computer and Information Science offers a program of courses in computational science. These courses include the study of computational techniques in physics, biology, geology, mathematics, and engineering. Other courses will focus on new algorithms, languages, and models in computer science and applied mathematics. Syracuse University offers a Concentration in Computational Science for undergraduates and a Certificate in Computational Science for master's and Ph.D. candidates in any major.

At Rice University, the Computational Science and Engineering graduate degree program was started in the fall of 1991. The program offers degrees in computational science at both the master's and Ph.D. levels. Students learn methods in parallel-vector processing, scientific visualization, networking, compiler technology, programming environments, parallel algorithms, numerical methods, and modeling with an emphasis on a particular area in science or engineering. These areas will, at first, include biochemistry and cell biology (expected), chemical engineering, computational and applied mathematics, computer science, electrical and computer engineering, and statistics (expected).

CRPC researchers have also implemented graduate and undergraduate courses in parallel computing at Argonne, Caltech, Rice University, Syracuse University, and the University of Tennessee. Topics of study include parallel processing, scientific visualization, networking, compiler technology, programming environments and templates, numerical methods, structured parallel programming, and modeling with an emphasis on application in a particular science or engineering field. CRPC researchers at Argonne are using the BBN TC 2000 Butterfly to teach a semester-long course for Science and Engineering Research Semester Undergraduates. Argonne has also offered two one-week "immersion workshops" on the BBN TC 2000 Butterfly this past summer. Each course was attended by 20 graduates from Midwest colleges and universities. The BBN TC 2000 Butterfly was also used in a semester-long course principally for faculty from women's colleges and colleges with large minority populations. PCN and Compositional C++ are being used at Caltech to teach undergraduate courses in programming and algorithms. Short courses have been taught in conjunction with the annual CRPC Research Review, with SIAM and SUPERCOMPUTING conferences, and at several other symposia in each of the past three years. Other courses taught by CRPC researchers include:

Introduction to Computational Science, Danny Sorensen, Rice University
Introduction to Computational Science, Geoffrey Fox and Ernest Silbert, Syracuse University
Data Parallel Computing, Ernest Silbert, Syracuse University (taught at the graduate and undergraduate level)
Compiling for Parallel Computers, Sanjay Ranka, Syracuse University
Parallel Processing, Alok Choudhary, Syracuse University
Advanced Compilation for Vector and Parallel Computers, Ken Kennedy, Rice University
Concurrent Scientific Computing, Eric Van de Velde, Caltech
Parallel Computing Applications, Jack Dongarra, University of Tennessee

Supercomputing has expanded beyond its initial use in government labs and has been introduced to mainstream academia and industry. "Different industries are introducing parallel computers, and they need people who can use them," said Geoffrey Fox of the CRPC and the Northeast Parallel Architectures Center. The CRPC hopes to train scientists and engineers who will provide the experience necessary to take advantage of these emerging technologies.

For more information on these and other academic programs, please contact Ann Redelfs at the Center for Research on Parallel Computation, Rice University, 6100 South Main Street, Houston, TX 77005, 713-285- 5181, redelfs@cs.rice.edu .

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