COURSE DESCRIPTION :
This course is an introduction to scientific computing fundamentals,
with case studies of scientific problem solving techniques.
Important topics included are:
parallel coding,
performance evaluation (operation counts, timing, memory requirements,
parallel efficiency and scalability),
discretization and roundoff errors,
convergence and stability of numerical methods,
CFL condition,
fast summation algorithms.
These topics will be introduced in the context of case studies such
as the N-body problem, the Poisson and the Heat equation, signal processing,
and of the numerical methods used to solve them.
Computer projects that we will work on
in the lab scheduled after every lecture are an integral part
of the course.
NOTE: This course is available for graduate credit. It is also
one of the two core requirements for the Graduate Certificate in
Computational Science and Engineering.
OTHER USEFUL SITES :