Meeting Times:  Mondays and Wednesdays, 4:30-5:45
Location:  KACB 2443

Instructor:  Edmond Chow
E-mail: 
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 the finite element method
• Particle simulation methods including molecular dynamics and Brownian dynamics
• Algorithms and methods for quantum chemistry
• Numerical approximation methods
• Scalable parallel solver techniques

20% Exercises (handed in but not thoroughly graded)
45% Three mini-projects
25% Final project (in-class presentation, final report)
10% Class participation

Textbook

There is no textbook for this course.