Members of the CSC are dedicated to the cause of undergraduate and graduate training in simulation-based engineering and science, focusing on topics in Scientific Computing, Parallel Computing, and courses stressing scientific computation in various disciplines.
Specific courses with these goals include [U = undergraduate, G = graduate]:
- Math 3315 / CSE 3365 -- Scientific Computing [U]
- Math 3316 -- High-Performance Scientific Computing [U]
- Math 4370 -- Parallel Scientific Computing [U]
- Math 5315 -- Numerical Analysis [U/G]
- Math 5316 -- Matrix Computation [U/G]
- Math 6315 -- Numerical Solution of Partial Differential Equations [G]
- Math 6316 / CSE 7366 -- Numerical Linear Algebra [G]
- Math 6320 -- Iterative Methods [G]
- Math 6321 -- Numerical Solution of Ordinary Differential Equations [G]
- Math 6360 -- Computational Electromagnetics [G]
- Math 6370 -- Parallel Scientific Computing [G]
Introduction to Computational Science
- Compiled language programming in the Unix environment - (e.g. C, C++, F90).
- Direct and iterative linear solvers with an introduction to relevant software (LAPACK).
- Nonlinear solvers (Newton's method and variants, optimization).
- Quadrature and differential equations with an introduction to relevant software.
- Monte Carlo methods.
Introduction to Parallel Scientific Computing
- Shared- and distributed-memory parallel programming and performance evaluation (e.g. OpenMP, MPI).
- Parallel solver libraries (e.g. PETSc, ScaLAPACK, TriLinos, FFTW).
- Applications to solving partial differential equations and/or large scale optimization and data analysis problems.