ECS 231, Winter 2010
Large Scale Scientific Computing

Instructor:

Zhaojun Bai, 3005 Kemper Hall, 752-4874, bai@cs.ucdavis.edu

Lecture:

10:30am - 11:50am, Tue.Thur., ...

Office Hours :

TBA

Prerequisite

ECS130 or consent of instructor. A solid knowledge of undergraduate linear algebra, and some experience with writing computer programs (in Matlab, C and/or Fortran).

Catalog Description

Algorithms and techniques for large-scale scientific computation, including basics for high performance computing, iterative methods, discrete approximation, fast Fourier transform, Poisson solvers, particle methods, spectral graph partition and its applications.

Goals of the Course

To learn about concepts and general techniques that are essential for modern methods, and to be able to apply them in a particular domain of large-scale scientific computation.

Syllabus

1. Introduction
2. Floating point arithemtic
3. BLAS
4. Vector and matrix norms
5. Review of frequently used matrix decompositions
6. Krylov subspace projection methods (Lanczos, Arnoldi)
7. Preconditioning techniques
8. Graph partition and data clustering by spectral methods
9. Selected topics (Direct sparse solver, fast Poisson solvers, ...)

Textbook

Lecture Notes

Grading:

• Homeworks: 70%
• Final project: 30%

On-line Info:

Class annoucements and handouts will be available at this site:
http://www.cs.ucdavis.edu/~bai/ECS231/