Lecture 3 hours; 3 credits.
Prerequisites: CS 483 or CS 600; linear algebra.
Laboratory work required.
Linear systems of equations. Triangular systems. Matrix
factorizations. Cholesky, LU factorization. Floating Point
arithmetic. Error Analysis. Condition of a problem. High-
performance implementations. Least-squares data-fitting.
Eigenvalue problems. Graph models of Sparse matrix problems.
Elimination trees. Symbolic factorization. Chordal graphs.
Matchings.