GPU Programming with CUDA

GPUs have evolved from a fixed pipeline graphics processing hardware into powerful programmable co-processing units capable of performing general purpose computing (sometimes referred to as GPGPU or General Purpose Computing on GPUs). In comparison with traditional CPU systems a GPU is capable of far higher (theoretical) peak performance within a smaller power window and as such many of the Top 500 supercomputers are looking at using GPU architectures.

This course will introduce the background of GPU hardware and provide hands on training for program development using the NVIDIA CUDA programming API. The training will introduce the CUDA language and optimisation techniques and provide guidance on how to access GPU hardware within the University of Sheffield Iceberg cluster.


No prior parallel programming knowledge is required however participants must be familiar with programming in C/C++.


Course date 1st July 2014 (10.00 until 16:00)

Location: Mappin Building Room F110, University of Sheffield

The course will be delivered by Dr Paul Richmond, Dr Mike Griffiths and remotely supported by Dr Alan Gray (EPCC)




If you have any questions please contact the ARCHER Helpdesk.