Skip to main content
Department of Information Technology

Parallel Algorithms for Scientific Computing

The course focuses on parallel algorithms for scientific computing problems (and not on parallel programming). We will cover parallel algorithms for a range of problem classes in Scientific Computing, from linear algebra (with a focus on sparse problems related to solving PDE), iterative solvers, multigrid, and particle interaction problems (Barnes-Hut, multipole etc).

Passing the course nominally gives 5 hp credits, but by completing an optional project it can also give 7,5 hp credits. The examination will consist of a written exam and written reports on the two assignments. The examination for the optional project consists of a written report.

Teachers: Sverker Holmgren, Maya Neytcheva, and Dimitar Lukarski

Schedule

Basic sparse linear algebra

  • Sparse formats and representation (DL). April 11, 13-15, room 2145. slides
  • Sparse matrix-vector multiplication (SH). May 8, 13-15, room 2344. slides

Sparse linear systems

Parallel preconditioners - convergence acceleration

Methods for particle-like problems (pairwise interactions)

Assignment 1: a written report should be delivered to Maya Neytcheva not later than by June 12, 2013.

Assignment 2: Article review

Updated  2015-10-01 23:58:35 by Kurt Otto.