This short course will provide an introduction to GPU computing with HIP aimed at scientific application programmers wishing to develop their own software. The course will give a background on the difference between CPU and GPU architectures as a prelude to introductory exercises in HIP programming. The course will discuss the execution of kernels, memory management, among other topics.

The course will not discuss programming with compiler directives, but does provide a concrete basis of understanding of the underlying principles of the HIP model which is useful for programmers ultimately wishing to make use of OpenMP or OpenACC. The course will not consider graphics programming, nor will it consider machine learning packages.

Note that the course is also appropriate for those wishing to use NVIDIA GPUs via the CUDA API, although we will not specifically use CUDA.

Pre-requisite Programming Languages:

Attendees must be able to program in C or C++ (course examples and exercises will limit themselves to C). A familiarity with threaded programming models would be useful, but no previous knowledge of GPU programming is required.

Course attendees do not need GPU hardware, access to ARCHER2 will be provided.


Participants must bring a laptop with a Mac, Linux, or Windows operating system (not a tablet, Chromebook, etc.) that they have administrative privileges on.

They are also required to abide by the ARCHER2 Code of Conduct.


Details to follow