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Computational Science: Solving Science Problems with Computers

This course explores the field of computational science, introducing students to the tools, concepts, and collaborative work involved in solving scientific problems using computers. It provides hands-on projects and demonstrates the difference between scientific computing, programming, and math. The course also touches upon cutting-edge supercomputing applied to real research problems. This class is not an in-depth study of parallel computation or numerical methods. Access to a Unix machine and installation of Mathematica (VT network software) are required.

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Computational Science: Solving Science Problems with Computers

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  1. CS4414 Issues in Scientific Computing Alexey Onufriev Departments of CS and Physics VT

  2. Computational Science now: a paradigm shift Experiment From the Greeks to the recent past, e.g. figuring out Earth’s radius (Eratosthenes, 240 BC) theory Now Computation

  3. How it works Image credit: http://www.physics.orst.edu/~rubin/INSTANCES/index.html

  4. Computational Science/Scientific Computing in the grand scheme of things. Natural Science Computer Science Computational Science Math Applied math Computational Science: solving science problems with computers Pure CS: software and hardware, Stand-alone algorithms (just like math)

  5. Examples • Human Genome • Stealth Fighter • MRI • LHS • Weather Forecasts • Protein Folding • ??? (input from class)

  6. What can computational science accomplish? • Speed up finding a solution • Find additional solutions • Find solutions otherwise impossible to find • Discover new fundamental laws???

  7. What is this class about? • Gives you a taste of what scientific computing is, via a realistic hands-on project (and homeworks). • Shows you how scientific computing is different from programming or math. • Introduces a number of useful tools and concepts • Teaches you how to work as part of a team • Will give you a glimpse of cutting edge supercomputing applied to a real research problem

  8. What this class is not: • In-depth parallel computation course (e.g. CS5234) • In-depth numerical methods, where you learn everything there is to know about one or two common methods (e.g. finite elements, CS5484). • Focused on high performance libraries (e.g. LINPACK), you will get a good idea of what these are.

  9. Specifics. Course structure. • Class websitehttp://courses.cs.vt.edu/cs4414/S15/

  10. The nitty-gritty • By next class: • Access to a unix machine • Install latest Mathematica (VT network software) • Pre-reqs, force adds

  11. Enjoy!

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