CS 554 / CSE 512: Parallel Numerical Algorithms (Fall 2021)
|Physical Location||1109 Siebel|
|Virtual Location||Zoom: https://illinois.zoom.us/j/81101310642 (email Edgar to ask for password)|
|Instructor||Edgar Solomonik (office: 4229 Siebel, email: email@example.com)|
|Instructor Office Hours||2-3 pm Wednesdays, 4229 Siebel + virtual via same link as lecture|
|TA||Linjian Ma (email: firstname.lastname@example.org)|
|TA Office Hours||2-3 pm Mondays, virtual via https://illinois.zoom.us/j/97556863368 (same password as lecture zoom)|
|Class recordings||Mediaspace: https://mediaspace.illinois.edu/channel/CS%2B554%2B_%2BCSE%2B512/226512163|
|Web forum||Mattermost chat: https://chat.labpna.net/cs554-fall2021 (email Edgar to ask for invite link)|
Brief Course Description
Numerical algorithms for parallel computers: parallel algorithms in numerical linear algebra (dense and sparse solvers for linear systems and the algebraic eigenvalue problem), numerical handling of ordinary and partial differential equations, and numerical optimization techniques.
Virtual and physical participation for all components the course will be made possible. Late enrollment/registration is also possible (immediate participation is welcome if registration is anticpated).
Grading: 36% project, 28% homework, 18% midterm, 18% final, may be subject to upwards curve
Projects: Submit initial proposal by Oct 20, revisions may be requested and will be due Oct 29. Students will have the option of preparing a final report or a poster presentation. Projects related to ongoing investigations or overlapping with other courses are encouraged, so long as they have some component related to this course.
Slides and notes are based on the Fall 2015 slides by Michael T. Heath. Resources relevant to the course are available also on the old course webpage by Prof. Heath. See also the previous course webpage.
- Chapter 1: Parallel Computing
- Chapter 2: Parallel Thinking
- Chapter 3: Dense Linear Systems
- Chapter 4: Sparse Linear Systems
- Chapter 5: Eigenvalue Problems
- Chapter 6: Matrix Models
Chapter 7: Differential Equations
- Ordinary Differential Equations
- Partial Differential Equations
- Particle Methods
- Electronic Structure Calculations
- Tensor Analysis