Directive-based GPU programming with OpenACC

GPU-accelerated computing drives current scientific research. Writing fast numeric algorithms for GPUs offers high application performance by offloading compute-intensive portions of the code to the GPU. The course will cover basic aspects of GPU architectures and programming. Focus is on the usage of the directive-based OpenACC programming model which allows for portable application development. Examples of increasing complexity will be used to demonstrate optimization and tuning of scientific applications.

Topics covered will include:

• Introduction to GPU/Parallel computing
• Programming model OpenACC
• Interoperability of OpenACC with GPU libraries (like cuBLAS and cuFFT) and CUDA
• Multi-GPU Programming with MPI and OpenACC
• Tools for debugging and profiling
• Performance optimization

The course consists of lectures and interactive hands-on sessions in C or Fortran (the attendee’s choice).

If you are interested in GPU Programming with OpenACC, please also have a look at the respective modules of the CUDA Course at the beginning of the year:
GPU Programming with CUDA - Basics
GPU Programming - Advanced Topics

Prerequisities:

Some knowledge about Linux, e.g. make, command line editor, Linux shell (see for instance this overview), some experience in C

Target group:

Scientists who want to use GPU systems with OpenACC