AMSC 660 / CMSC 660 Scientific Computing I, Fall 2010

Dianne P. O'Leary

Prerequisite: Undergraduate numerical analysis. Programming assignments will be in Matlab.

Textbook: Scientific Computing with Case Studies by Dianne P. O'Leary, SIAM Press, 2009.

  • Yes, it is a disadvantage to have a book written by the instructor. Sorry.
  • The retail price of the book is $92, but SIAM members pay $64.40 (a 30% discount) if they order directly from SIAM.
  • University of Maryland students can get free membership in SIAM, since UMD is an Academic Member of SIAM.
  • Topics: Monte Carlo simulation, numerical linear algebra, nonlinear systems and continuation method, optimization, ordinary differential equations. Fundamental techniques in scientific computation with an introduction to the theory and software for each topic.

    Grading: Based on quizzes, homeworks, and project.

    Final Exam: None.

    CMSC Masters Comprehensive Exam grade: based on quiz grades

    Basic Information:

  • 2010 Course Information and Syllabus
  • Survival Guide for Scientific Computing
  • UMCP Code of Academic Integrity
  • Notes for CMSC 460. Use these if you find that your background is lacking.
  • Information about computer accounts. See also the additional pointers at the bottom of notes by Larry Herman. For your assignments, you may use GRACE or any other machine with Matlab access.
  • Accessing Matlab on the GRACE machines, with graphics. Helpful summary of things to know,of things to know, from a student.
  • Sources for Matlab information:
  • Official Matlab documentation
  • Matlab Primer: 39 pages of basic information
  • Timothy A. Davis, Kermit Sigmon, Matlab Primer, CRC Press 2005. A 200 page version of the above reference.
  • D. J. Higham and N. J. Higham, Matlab Guide, SIAM Press 2005.
  • Read the code samples on the website for the course textbook.
  • How not to go about a programming assignment by Agustín Cernuda del Río
  • Tentative Schedule for Fall 2010:

    01 Aug 31: Prelim. Sep 2: Prelim.
    02 Sep 7: Prelim. Sep 9: Monte C. HW 1 assigned.
    03 Sep 14: Monte C. Quiz 1 Sep. 16: Monte C.
    04 Sep 21: Matrix Comp. Sep 23: Matrix Comp Quiz 2
    05 Sep 28: Matrix Comp. HW 1 due. HW 2 assigned. Sep 30: Matrix Comp.
    06 Oct 5: Matrix Comp. Quiz 3 Oct 7: ODEs
    07 Oct 12: ODEs Oct 14: ODEs Quiz 4
    08 Oct 19: ODEs HW 2 due. Term project info available. Oct 21: ODEs
    09 Oct 26: ODEs Quiz 5 Oct 28: ODEs
    10 Nov 2: Optim. HW 3 assigned. Nov 4: Optim. Quiz 6
    11 Nov 9: Optim. Nov 11: Optim.
    12 Nov 16: Optim. Quiz 7 Nov 18: Optim. HW 3 due.
    13 Nov 23: Optim. Nov 25: Happy Thanksgiving!
    14 Nov 30: Optim. Quiz 8 Dec 2: Nonlin. Eqn.
    15 Dec 7: Nonlin. Eqn. Dec 9: Nonlin. Eqn. Quiz 9
    Dec 14: 12 noon: Term project due.

    2010 Lecture Notes:

  • Errors and Arithmetic
  • Dense Matrix Computations
  • q2.m Program for a RR-QR demonstration.
  • Changes on p. 23 marked in green. Optimization
  • An example of a good linesearch: cvsrch.m and cstep.m
  • Solving Nonlinear Equations
  • Homotopy example: Applying the method to a simple problem, convex optimization
  • Monte Carlo Methods
  • Ordinary Differential Equations, Part 1
  • Ordinary Differential Equations, Part 2
  • Homework

  • Homework 1
  • Homework 2
  • Homework 3
  • Quizzes: For practice, see the sample quizzes below.

  • Quiz 1 will cover pp. 5-25 in the textbook, and the Errors and Arithmetic notes. The first 7 bullets in the "Mastery" list on p. 4 of the textbook give hints.
  • Quiz 2 will cover pp. 185 - 219 in the textbook, and the Monte Carlo notes. The bullets in the "Mastery" list on pp. 185-186 of the textbook give hints. Ignore the section on counting/KRS and the section on quasi-random numbers. Pay special attention to Challenge 19.6 and the first 3 parts of Challenge 19.7.
  • Quiz 3 will cover Sections 5.1-5.5 of the textbook, and the dense matrix computations notes through the eigendecomposition. One question will involve the Gerschgorin theorem.
  • Quiz 4 will cover the SVD (Section 5.6 of the textbook, pp. 16-18 of the notes) and ODEs (Sections 20.1 through 20.2.4 of the textbook, pp. 1-16 of the notes). Table 20.1 will be given to you if needed, so don't memorize.
  • Quiz 5 will cover ODEs (Chapter 20, Chapter 21 through Challenge 21.3, and the ODE notes). Pay some attention to the Pointers, but if you need one of them, I will provide a copy for you to see.
  • Quiz 6 will cover optimization: Sections 9.1 - 9.4 and lecture notes pp. 1-13.
  • Quiz 7 will cover optimization: Sections 9.5.1., 9.5.2, 24.2, optimization lecture notes pp. 14-25, nonlinear equations lecture notes pp. 2-4.
  • Quiz 8 will cover optimization: Section 9.5.3 and Chapter 10; optimization lecture notes pp. 25-31. One question will involve formulating a particular image processing problem as an optimization problem, so familiarity with how an image is stored (see, for example, Chapter 11, "The Problem") will be helpful.
  • Quiz 9 will cover Chapters 24-26 and the nonlinear equations notes. It will be given at 10:20 on Dec 9. No one may enter the classroom after that time.
  • Sample quizzes. Many problems from the old quizzes were later included as challenges in the textbook.

    2010 Term Project Information

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