Scientific Computation - Spring 2009 Welcome to the CS 3200 - Scientific Computation home page. Here you will find the latest class information, assignments, handouts, and other useful information. Scientific Computation - CS 3200 will present scientific computation relevant to computational science and engineering, with an emphasis on the process of modeling, simulation, visualization and evaluation. Possible topics related to the four areas include: (modeling) continuous and statistical modeling; (simulation) solving and linear and non-linear systems, interpolation and approximation, numerical differential equations; (visualization) scalar and vector field visualization techniques; (evaluation) connection of results back to case-studies of interest from areas such as physics, biology, etc. Basic knowledge of programming, matrix operations, and calculus. Spring Semester 2009 Instructor: Chris Johnson Email: crj@sci.utah.edu Office: 3850 Warnock Engineering Building Office Hours: 2:45 - 3:30 p.m. MW or by appointment TA: Jiarong Jiang Email: jiang@cs.utah.edu Office: CADE Lab - WEB 226 Office hours: Monday 10:00 a.m. - 12:00 p.m. Wednesday 10:00 a.m. - 12:00 p.m. Asking Questions: For questions for the Instructor or TA, please send email to: teach-cs3200@list.eng.utah.edu To send email to the class, use cs3200@list.eng.utah.edu CS 3200 Course Mechanics and Resources: CS 3200 Course Syllabus CS 3200 Time and Place: 1:25 - 2:45 p.m. Mondays and Wednesdays in WEB 103 CS 3200 Class Email List: You must subscribe to the CS 3200 class email list (cs3200@list.eng.utah.edu). To subscribe to the CS 3200 email list, send email to sympa@list.eng.utah.edu with the subject line of "subscribe cs3200 Your-Email-Address-Here". Notes Directory: This directory contains any notes or other materials that are handed out in class. Assignment Directory: This directory contains pdf files of the assignments. Data Directory: This directory contains data files used in the homeworks. Code Directory: This directory contains a listing of various codes used in the homework. Resources Directory: This directory contains files review/overview materials on Matlab, Unix, Makefiles, Matlab, etc. Grading Directory: This directory contains grading information College of Engineering Guidelines Disability Notice: The University of Utah seeks to provide equal access to its programs, services and activities for people with disabilities. If you will need accommodations in the class, reasonable prior notice needs to be given to the Center for Disability Services, 162 Olpin Union Building, 581-5020 (V/TDD). CDS will work with you and the instructor to make arrangements for accommodations. All written information in this course can be made available in alternative format with prior notification to the Center for Disability Services. References Because there does not exist a single book that covers all the materials we will cover in this class, we will use a combination of class notes, class lecture slides, and books and other references. Here is a list of those additional books, as well as other useful references. Numerical Computing with Matlab This book is a very nice overview of numerical analysis with several examples using Matlab. The book is available for free on-line. The Matlab codes used in the book are also available on-line. Scientific Computing: An Introductory Survey, Second Edition by Michael T. Heath, published by McGraw-Hill, New York, 2002. Guide To Scientific Computing, Second Edition by Peter R. Turner, published by CRC Press, 2000. Introduction to Computational Science: Modeling and Simulation for the Sciences by Angela B. Shiflet and George Shiflet, Princeton University Press, 2006. Scientific Computing with MATLAB by Alfio Quarteroni and Fausto Saleri, Springer, 2003. MATLAB Guide by Desmond J. Higham and Nicholas J. Higham, SIAM Press, 2005. Mastering MATLAB 7 by Duane C. Hanselman and Bruce L. Littlefield, Prentice Hall, 2004. Octave - an open source, freely available alternative to Matlab Matlab Tutorial from Mathworks Link to On-Line Matlab Tutorials. On-Line Matlab Tutorial - University of Texas The Visualization Handbook. edited by Charles Hansen and Chris Johnson (your instructor), Academic Press, 2004. Visualization Toolkit 4th Edition by Will Schroeder, Ken Martin and Bill Lorenson, Kitware, 2006. The Nature of Mathematical Modeling by Neil Gershenfeld, Cambridge University Press, 1998. Python Scripting for Computational Science by Hans Petter Langtangen, Springer, 2004. Python Essential Reference (3rd Edition) by David M. Beazley, Sams, 2006. SCIRun Software System A scientific problem solving environment for modeling, simulation and visualization developed by the Scientific Computing and Imaging Institute at the University of Utah. Links to Scientific Computing Software collected by Michael Heath of UIUC. Parallel Scientific Computing in C++ and MPI: A Seamless Approach to Parallel Algorithms and their Implementation by George Em Karniadakis and Robert M. Kirby, Cambridge University Press, 2003. Scientific Parallel Computing by L. Ridgway Scott, Terry Clark, Babak Bagheri, Princeton University Press, 2005. Introduction to High-Performance Scientific Computing by Lloyd D. Fosdick, Elizabeth R. Jessup, Carolyn J. C. Schauble, and Gitta Domik, MIT Press, 1996. Some disasters attributable to bad numerical computing BLAS - Basic Linear Algebra Subprograms People Here are links to some of the mathematicians, computer scientists, scientists, and engineers that we will mention during the course. Leonid Euler Brook Taylor Srinivasa Ramanujan Isaac Newton