High Performance computing using GPU

A summer course giving in 2008 focusing on high performance computing on streaming architectures.

Course administrators are: Dag Lindbo, Henrik Holst and Tomas Oppelstrup.

Course examinator: Johan Hoffman.

We will present news here related to the course. We will also have a mailing list here (not yet available).

News

The first meeting is on Tuesday 2/6 at 10 AM in room 304 (PDC).

Introduction to streaming, massively concurrent architecture (stream processing)
Formulating suitable data parallel algorithms
Use of CUDA SDK.
After the course the students will be able to implement computational kernels on the CUDA architecture.

There will be four lectures during June.

Introduction to GPU computing (Dr. Erik Lindahl)
Introduction to CUDA SDK (Dag), CUBLAS (Tomas) and Fortran interoperability (Henrik)
Data structures and Advanced examples. Prof. Jesper Oppelstrup will give retrospect on massively concurrent architectures from the past.
Presentation of student projects

Monte Carlo for option pricing.
Iterative method for linear system of equations - Either standalone or as a kernel of a bigger code.
Explicit finite difference methods - Choose you favourite PDE or ODE and solve it.
Image processing. Implement some filtering methods of your choice.
...Your own ideas!

CUDA, Supercomputing for the Masses (ddj.com)
CUDA Programming guide v 1.1 (nvidia.com)
Free E-books: GPU gems 1 (nvidia.com) and GPU gems 2 (nvidia.com). We will try to provide copies of relevant chapters not available online (GPU Gems vol 2-3).
Additional links:
- CUDA Zone (nvidia.com)
- General GPGPU research (gpgpu.org) - Not CUDA specific.