Sun Enterprise Course in High Performance Computing

Larger and more complex mathematical models demand greater computer performance. There is a limit for what can be accomplished by one processor so to get really high performance or to solve very large problems a super computer must be used. This is not sufficient however. One must also know what algorithms are suitable for a special computer architecture and how to implement the codes, using system software, in an efficient way.


The main themes of this course are:

The course contains several small assignments where you will test different algorithms, program packages, tools, languages and computers. Since the participants in the course usually have quite different backgrounds, we will start by looking at some basic tools such as make, ar, ld, prof and continue with a brief introduction to C and Fortran (77 and 90). This introduction will not make you a specialist in any of the subjects but it should be enough to take you through the assignments.

Many modern parallel computers consist of RISC processors connected by a fast network. So in order to get good performance on a parallel computer it is essential to understand how to tune codes for a work station.

When it comes to parallel computers the course will cover message passing using MPI and shared memory computing (loop parallelism) using OpenMP. We will focus on the Sun and SGI/Cray systems at Chalmers.

There will also be lectures on vector computers and in particular the Fujitsu and Cray systems at PDC.

This is a course for beginners in high performance computing (the third or fourth year of undergraduate studies at Chalmers) and the prerequisites are basic courses in numerical analysis and programming, and perhaps the most important, you must think that computers are fun.

The literature will consist of lecture notes, manuals and articles. I can recommend the new book: "High Performance Computing".

The first lecture will be on Monday January 18, 13.15 in MD1 at the Mathematics Centre.


Thomas Ericsson, mathematics / numerical analysis
Tel: 772 1091
E-mail:  thomas@math.chalmers.se