High Performance Computing Center North
More information will be added about the contents of the lectures!
|9-10||Lecture 4||Lecture 7||Lecture 10||Lecture 13|
|10-11||Lecture 5||Lecture 8||Lecture 11||Lecture 14|
|11-12||Lecture 6||Lecture 9||Lecture 12||Lecture 15|
|13-14||Lecture 1||Assignment 1||Assignment 2||Assignment 3|
Lectures 1-2: Basics of parallel linear algebra (Bo Kågström)
Lecture 3: Mangement of deep memory hierarchies - recursive blocking and hybrid data structures (Bo Kågström)
Lecture 4: Introduction to the HPC2N computer systems (Mikael Rännar)
Lectures 5-6: Templates for dense and sparse eigenvalue problems (Bo Kågström)
Lectures 7-9: Scientific Computing with PETSc and SLEPc (José E. Román)
Lectures 10-11: General HPC library software and tools: Dense linear algebra (Mikael Rännar)
Lecture 12: Survey of tools for developing HPC applications (Mikael Rännar)
Lectures 13-15: Graph partitioning and N-body problems (Lars Karlsson)
The assignment titles are preliminary, and the instructions will be presented later.
Assignment 1: Basic parallel linear algebra (Mikael Rännar)
Aim: To familiarize the student with message passing parallel programming using basic linear algebra as examples.
Instructions for assignment 1
Assignment 2: Sparse linear system and eigenvalue solvers (José E. Román)
Aim: To practice and learn how to use the PETSc and SLEPc toolkits.
Instructions for assignment 2
Assignment 3: Dense HPC libraries (Mikael Rännar)
Aim: To practice and learn how to use the ScaLAPACK library.
Instructions for assignment 3
All lectures will be held in MIT-huset in the following rooms:
All computer projects (assignments) in Room MA426