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 covered basic aspects of GPU architectures and programming. Focus was on the usage of the directive-based OpenACC programming model, which allows for portable application development. Examples of increasing complexity were used to demonstrate optimization and tuning of scientific applications. Topics covered: 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)