CS595:

Advanced Scientific Computing (Fall, 2008)

Wedn. 6:25-9:05pm, SB 106

Instructor: Hong Zhang, Research Professor, Department of Computer Science, IIT.
Email: hzhang@mcs.anl.gov
Web Page: www.mcs.anl.gov/~hzhang/teach/cs595
Office Hours and Location: Wedn. 3:30 - 5:30pm, SB229C

Course Description: This course is designed for graduate and upper-level undergraduate students in the fields of science and engineering. The objective is to introduce the essential analytic and algorithmic ideas, as well as broaden understanding and gain experience on advanced scientific computing. The course contains following subjects:

Overview of parallel computing.
Parallel and distributed numerical computation.
Numerical iterative techniques for solving large sparse systems, the error analysis and control.
Numerical software design, analysis, implementation and performance evaluation, including discussions on the object-oriented programming techniques.

Students are expected to gain hands-on numerical programming experience on state-of-the-art parallel computers. By the end of the course, students are required to apply the theories and techniques learned in the class to projects either in their own field (particularly encouraged) or projects suggested by the instructor. Successful course project may lead to summer internship at the Argonne National Laboratory.

Selected examples of student project (Spring, 2006):

"Build a Low Cost Parallel Computing Cluster", N. Johnston and M. McCourt
"Parallel Multigrid Poisson Solver for Applications in Fluid Dynamics and High Energy Physics", M. Boghosian
"Parallelization of a Flow in a Driven Cavity", V. Joshi
"Performance Evaluation of Sparse and Dense Solvers for Nano-Material Simulation on an IBM Cluster", M. Ali
"Build an Interface for SPRNG based on PETSc", X. Zeng

Prerequisites: Advanced calculus, linear algebra, background on numerical computing. Programming skill.

Grading: Homework: 30%, Class participation: 20%, Final project: 50%.

References:

Introduction to Parallel Computing: Design and Analysis of Algorithms, by Vipin Kuman, Ananth Grama, Anshul Gupta, and George Karypis, 2nd Ed., 2003.
Numerical Linear Algebra, by Lloyd N. Trefethen and David Bau, III, SIAM ISBN 0-89871-361-7
Iterative Methods for Sparse Linear Systems, by Yousef Saad
Advances in Software Tools for Scientific Computing, by M. Griebel et al.
Using MPI: Portable Parallel Programming with the Message-Passing Interface, by W. Gropp, E. Lusk, and A. Skjellum.
PETSc Users Manual, ANL-95/11 - Revision 2.3.3, Argonne National Laboratory, 2007, by S. Balay et al.

Lecture Notes and Assignments: blackboard.iit.edu

Course Project: