CS590C: Introduction to Scientific Computing
MWF, 10:30 AM, REC 309
164D, Computer Science Building;
Office Hours: Monday 11:30 AM - 12:30 PM, Wednesday 11:30 AM - 12:30 PM.
(Office hours can also be arranged by appointment).
Office Hours: Monday, Friday 2:00 PM - 3:00 PM, Tuesday 11:00 AM - 12:00 PM.
The course will be drawing on the following sources and will be supplemented
with papers and lecture notes.
The CSEP book at Oak Ridge
or another site at
Oak Ridge, or
Iterative Methods for Sparse Linear Systems, Yousef Saad,
PWS Publishing, 1996.
Introduction to Linear Algebra, Gilbert Strang, Wellesley-Cambridge Press,
Scientific computing : an introduction with parallel computing,
Gene Golub, James M. Ortega, Boston : Academic Press, c1993.
resources, class notes from other universities
at UTK) and class notes.
The course handouts will be available electronically at the URL
Students are expected to check this page periodically for supplementary
material, assignments and projects. If you do not have access to the web,
contact your professor.
4 Homework sets 20%
(no late homeworks accepted)
Group project 20%
(Project spans the length of the semester)
1 Midterm 25% (in-class; date to be announced)
Hardware and software evolution.
Review of elementary mathematical background
(Basic Linear Algebra, Differential Equations, Mathematical Modeling
of Physical Systems)
Using computational tools for problem solving
(Maxima, Matlab, Mathematica)
Using libraries (LINPACK, LAPACK, EISPACK, ScaLAPACK, BLAS)
(Finite difference / finite element methods); Sparse linear systems
from discretized differential equations.
Solving sparse linear systems
Iterative methods (ITPACK)
Direct methods (Cholesky / LU factorization)
- Accelerating convergence of iterative methods (preconditioning).
(Boundary element methods); Dense linear systems from discretized
particle dynamics simulations
Solution of dense linear systems.
Introduction to structured matrix computations, problem characteristics
leadign to structured matrices (Toeplitz and Block-Toeplitz methods)
Computational envorinments: Languages and tools, scientific visualization,
- High Performance Computing, HPC programming environments, Grand