Meeting Times:  Tues and Thurs, 1:35-2:55
Location:  ES&T L1105

Instructor:  Edmond Chow
E-mail:  (the best way to reach me)
Office Hours:  By appointment

This course will cover many of the major computational methods used in numerical simulation in science and engineering. The goal is for students to gain familiarity with methods developed in applied mathematics and how these methods are used in various applications. This course helps prepare students in high-performance computing for careers in large-scale numerical simulation where codes are developed by interdisciplinary teams. This course will also be of interest to graduate students in science and engineering disciplines who are interested in numerical simulation.

Students will be given the opportunity to enhance their learning of new methods through programming exercises and using simulation software. Some class time will be devoted to these hands-on activities.

Prerequisites

Numerical Methods (e.g., CX/MATH 4640) and Graduate-level Numerical Linear Algebra (CSE/MATH 6643 and/or CSE/MATH 6644). Experience with Matlab. Familiarity with parallel computing, e.g., MPI and OpenMP.

Topics

• PDE governing equations of science and engineering
• Discretization methods including finite element method
• Numerical approximation methods
• Scalable parallel solver techniques
• Particle simulation methods including molecular dynamics and Brownian dynamics
• Algorithms and methods for quantum chemistry

30% Project: report due Sun. April 17; presentations April 21 and 26
20% Exam 1: in class Tues. Feb. 9
20% Exam 2: in class Thurs. March 10
20% Exam 3: in class Tues. April 19
10% Class Participation

Topics for projects will be given in class.

Exams are open-notes, but no books. No electronic aids.

Auditors: no project is necessary, but you must score at least 20/100 on 2 of the 3 exams.

Textbook

There is no textbook for this course.