HPC2N
High Performance Computing Center North
More information will be added about the contents of the lectures!
Week 12
Day | Monday | Tuesday | Wednesday | Thursday | Friday |
---|---|---|---|---|---|
17 | 18 | 19 | 20 | 21 | |
Time | |||||
8-9 | |||||
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 | |
12-13 | Lunch | Lunch | Lunch | Lunch | Lunch |
13-14 | Lecture 1 | Assignment 1 | Assignment 2 | Assignment 3 | |
14-15 | Lecture 2 | ||||
15-16 | Lecture 3 | ||||
16-17 |
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:
Monday: MC413
Tuesday: MA478
Wednesday: MC413
Thursday: MA478
Friday: MA478
All computer projects (assignments) in Room MA426