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Instructor:
Malgorzata Peszynska
Class:
MWF 9:00-9:50, Gilkey 115, CRN: 27146 (MTH 655) or 27147 (MTH 659)
Course information:
In this class, we develop methods for solving large
scale scientific computing problems. Rigorous mathematical background
as well as implementation details will be given for topics such as i)
solving large nonlinear systems of equations, ii) multigrid method,
and iii) domain decomposition methods. Also, a iv) primer on numerical
optimization will be developed touching on both the traditional
gradient based methods as well as on heuristic approaches such as
Simulated Annealing. Other topics may be included as time permits.
The class will include hands-on-lab in which students will learn the
basics of scientific and parallel computing.
STUDENTS: The course is intended for graduate students of
mathematics and other disciplines but no specific preparation beyond
solid undergraduate background in mathematics will be
assumed. Knowledge of numerical methods, and familiarity with computer
programming are a plus but are not required. Most examples will come
from models of real life phenomena but no prior knowledge of the
models or their discretizations will be assumed.
GRADING:
- Attendance at all labs
(Fridays in MLC, Kidd 108J, computer lab)
is required. Please contact me if you have to miss a lab meeting.
- You have to complete all lab projects and turn in required lab
summary. Quality of the work will determine your grade. Go to assignments to see what is required.
- For those registered for full credit, (short) papers and/or
presentations on individually assigned projects will be required. The
projects will be assigned based on your interests.
Special arrangements for students with disabilities,
make-up exams etc.: please contact the instructor and Services for Students with
Disabilities, if relevant, and provide appropriate
documentation.
Course drop/add information is at
http://oregonstate.edu/registrar/.
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