Course Outlines 2018-19
Our graduate courses are offered each year based on the interest of the students in the department. If you have any questions or comments, please contact Audrey via email (firstname.lastname@example.org).
Fall Term Courses - 2018AM9561A - A Graduate Introduction to Numerical Analysis
Schedule: Mondays 12:30pm-1:30pm, Wednesdays and Fridays 8:30am-9:30am, MC 204.AM9563A - Computer Algebra
Schedule: Tuesdays 1:30pm-3:30pm, and Thursdays 1:30pm-2:30pm, AHB 1B04.SC9601 - Scientific Computing PhD Seminar Course
Overview: This seminar is a required course for the Scientific Computing collaborative program. It consists of seminars on interdisciplinary scientific computing methods given by students, researchers, and Compute-Canada/Sharcnet seminars.
Winter Term Courses - 2019AM9505B - Partial Differential Equations
Schedule: Tuesdays 2:00pm-3:30pm, and Thursdays 2:00-3:30pm, MC 204.
Brief overview: Emphasis will be placed on understanding solutions and major phenomena for PDE. The course will be a balanced treatment about modeling and problem solving with PDE. Maple will be used to numerically and analytically solve problems. It will also be used to graph solutions to illustrate phenomena encountered during the course. This will be mostly through the use of programs that will be provided. No prior knowledge of Maple will be assumed. There will be some guest lectures in the course from the department, to emphasize the breadth and unity of the subject.
Schedule: Tuesdays 2:30pm-5:30pm, WSC 240.
Brief topics that may be covered:
- Random Number Generators
- Monte Carlo Integration: Hit/Miss Integration
- Random Walks (RW)
- Solving Laplace's Equation (and other DE's) using RW
- Percolation and modelling of Forest Fires
- Cellular Automata: Lattice Gas, Kauffman Model
- Monte Carlo Simulation: Ising Model
- Damage spreading, Fractals, Chaos
- Molecular Dynamics: Hard Spheres and more
- Other interesting things I like
Schedule: Mondays, Wednesdays, and Fridays 1:30pm-2:30pm, MC 204.
Brief topics overview:
- Introduction and Disclaimers
- Finite elements introduced as bars forming a truss
- Some mathematical aspects
- Towards a systematic method
- The matrix approach
- Two-dimensional heat flow
- Variational form
- The Galerkin approach
- Element computation
- Other topics not in the main text book
Schedule: Mondays 3:00pm-4:30pm, and Thursdays 10:30am-12:00pm, MC 204.
Brief overview: The goal of this course is both to introduce students to high performance computing methods, and in particular parallel programming paradigms. Students will work on projects using MPI and CUDA, OpenCL, and some basic Monte Carlo and stocastic methods.