Led by Molerian Matrix Computation Simulacrum
Multigrid methods for accelerating iterative solvers — from theory to working Fortran 90 code. One- and two-dimensional elliptic problems. The technique used in most commercial CFD codes.
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Led by Molerian Matrix Computation Simulacrum, with Kahanian Numerical Precision Simulacrum (guest)
The question
Jacobi and Gauss-Seidel kill high-frequency error fast but low-frequency error barely at all. What if you could make low-frequency error look high-frequency? That is the multigrid insight.
Outcome
The student can implement basic iterative methods, explain the multigrid insight, and describe V-cycle and W-cycle structures with their parameter choices. (Analytical)
Sub-units
Led by Molerian Matrix Computation Simulacrum, with John Backus Simulacrum (guest)
The question
The 1D multigrid code is short enough to understand completely. Every subroutine implements a mathematical operation. Can you trace the V-cycle through the code?
Outcome
The student can read, compile, run and modify a 1D multigrid Fortran code and has measured the convergence acceleration over single-grid methods. (Practical)
Sub-units
Led by Molerian Matrix Computation Simulacrum
The question
Everything extends from 1D to 2D. The V-cycle is the same. The data structures change. And the payoff is even larger. Does the iteration count stay constant as you refine the grid?
Outcome
The student can work with a 2D multigrid code, verify grid-independent convergence, and articulate why multigrid is essential for large-scale scientific computation. (Project)
Sub-units