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Developing Advanced Computing Course Materials for Distributed Audiences

Developing Advanced Computing Course Materials for Distributed Audiences. Texas Advanced Computing Center (TACC) The University of Texas at Austin. TACC Advanced Computing Technology Areas. High Performance Computing (HPC) numerically intensive computing: produces data

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Developing Advanced Computing Course Materials for Distributed Audiences

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  1. Developing Advanced Computing Course Materials for Distributed Audiences Texas Advanced Computing Center (TACC) The University of Texas at Austin

  2. TACC Advanced ComputingTechnology Areas • High Performance Computing (HPC) numerically intensive computing: produces data • Visualization & Data Analysis (VDA) rendering data into information & knowledge • Data Information Systems (DIS) managing and analyzing data for information & knowledge • Distributed and Grid Computing (DGC) Integrating diverse resources, data, and people to produce and share knowledge – requires networks!

  3. Why are these courses important? • Classes that prepare students to use advanced computing resources as they are used in computational, applications-driven research and development are relatively rare in university curricula. • With the emergence of grid computing technologies and the development of integrated cyberinfrastructure promising new capabilities for knowledge discovery, classes that provide a solid, practical foundation for using cyberinfrastructure in research and development are even more important for both academic and industry careers.

  4. Courses • Introduction to Scientific/Technical Computing • Parallel Computing for Science & Engineering • Visualization & Data Analysis for Science & Engineering • Distributed & Grid Computing for Science and Engineering

  5. Introduction to Scientific/Technical Computing • This course will cover a wide variety of techniques and methods applicable to many scientific disciplines. The course will begin with an introduction to the traditional mainstays of scientific and technical computing: basics of computer architecture; the UNIX environment; floating-point arithmetic; numerical methods including integration, interpolation, linear algebra, ordinary and partial differential equations, and optimization, and non-linear solution algorithms. Basic visualization and data analysis tools will be presented as well.

  6. Parallel Computing For Science & Engineering • The course beings with a comprehensive introduction to parallel computing theory, and discuss hardware features and software components essential for parallel computing. Next, OpenMP and MPI programming paradigms are introduced and prepare students for a study of key algorithms and provides an explanation of applications in various fields. The course will focus on application development, performance, and scalability throughout. In addition, it will prepare students to formulate and develop parallel algorithms to implement them as effective applications for parallel computing systems.

  7. Visualization & Data Analysis for Science & Engineering • The course begins with a comprehensive introduction to the theory behind visualization and data analysis. The applied nature of this class will focus on application development and achieving performance. The class provides not only an introduction to the theory of scientific visualization but also the context to test and develop understanding of these theoretical principals.

  8. Distributed & Grid Computing for Science & Engineering • This class begins with an introduction to the principles and characteristics of grid computing in addition to technologies that facilitate deploying and using grid resources. The course will also review current international, national and campus grid building activities and leverage the lessons learned from the deployment of these state-of-the-art grids. Finally, the course will present the future plans and trends in grid computing, so students will have information and insight on what to track as they complete this class and use grid computing in research or commercial environments.

  9. Delivery Mechanisms • In person • Delivered at UT Austin, eventually in ‘smart’ classrooms with videoconferencing technologies • Classes will become part of the UT CS Dept course catalog and cross-listed in other departments for maximum exposure • Remote usage • Course slides and assigments packaged in common formats (MS Office / OpenOffice, PDF, etc.) for download • Course lectures recorded to capture spoken lectures and Q&A from class (common formats) • Lectures also recorded with video (common formats) • Eventually, also broadcast in real-time (AG, Conference XP)

  10. EPIC: Engaging People in CyberinfrastructureCurriculum Development Project • EPIC: www.eotepic.org • Multi-institution EOT project (ends Summer 06) • Goal is to build human capacity by creating awareness of the opportunities offered through cyberinfrastructure (CI) and by educating and training a diverse group of people. • TACC will deliver these classes using EPIC funding and collaborations to additional institutions

  11. Questions? • Contact us: • Jay Boisseau: boisseau@tacc.utexas.edu • Karl Schulz: karl@tacc.utexas.edu • Kelly Gaither: kelly@tacc.utexas.edu

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