CS 6210

Matrix Computations

Fall 2015

Announcements | Syllabus | Assignments | Problem of the Day

CS 4220 Home Page

Instructor: Charles Van Loan, 423 Gates, 255-5418, cv@cs.cornell.edu. Office hours are here.

Meeting Time & Place: MWF 11:15-12:05, Phillips 307

Prerequisites: Computing assignments are in Matlab so a year's worth of programming in Python, Java, or C++ is more than enough. A solid understanding of linear algebra is essential. In that regard, here are some key words: Gaussian elimination, orthogonal matrix, eigenvalue, eigenvector, norms, independence, range, nullspace, basis. Happy to talk 1:1 if you have a concern about your background.

Description: 4 credits. Stable and efficient algorithms for linear equations, least squares, and eigenvalue problems. Direct and iterative methods are considered. The MATLAB system is used extensively.

Workload:  There is a computing assignment every two weeks (approximately.) Associated with every lecture there is a "Problem of the Day"  which should be worked out. They are not submitted for grading but you should take them very seriously. The POD's are a handy way to keep up with the course and to prepare for the final exam.

Related Courses: CS 5220 (Applications of Parallel Computers) by Professor David Bindel.

TextMatrix Computations (4th Edition) by Golub and Van Loan

Grading: There are six Matlab Assignments, a take home midterm, and a final that has a take home part and a timed, closed-book written part. Final grade is based on the assignments (55%), the take-home midterm (15%), the take-home part of the final (15%), and the written part of the final (15%).

Software: GVL4 M-Files, The Pseudospectra Gateway, The University of Florida Sparse Matrix Collection

Some Linear Algebra References:  Gil Strang's MIT Linear Algebra course videos and text are excellent. So is Carl Meyer's Matrix Analysis and Applied Linear Algebra book.

Some Matlab References: Insight Through Computing: A Matlab Introduction to Computational Science and Engineering (Van Loan and Fan), Getting Started with Matlab 7  (Pratap), Matlab: An Introduction with Applications (Gilat), Mastering Matlab7 ( Hanselman & Littlefield)

Computing: MATLAB is available on all public CIT Machines. The student edition of MATLAB  is available from Mathworks