4-5 November 2020
Europe/Stockholm timezone

Modern high core count CPUs and accelerators, such as GPUs, have been shown to provide significant performance benefits in many different applications. However, for a novice, or even for a moderately experienced scientist or programmer, it is not always clear which applications could potentially benefit from these resources and which do not. For example, a Nvidia V100 GPU can perform artificial intelligence (AI) related computations in a fraction of the time it takes a regular CPU to perform the same computations but ill-informed OpenACC compiler pragmas can actually make a code run slower. Why is this? When should one invest time in parallelization and/or GPU-acceleration? How much speedup can be expected with a given application?

The main goal of this two-day course is to start answering these questions. The course also covers the basics of GPU programming and aims to provide the necessary information for avoiding the most common pitfalls.

More information, schedule, and registration can be found on the course webpage at HPC2N, Umeå University.

HPC2N, Umeå University MIT-building Campustorget 5, 4th S-907 36 Umeå Sweden
Prerequisites: The course does not require any existing GPU programming knowledge but basic understanding of the C language and parallel programming are required for the hands-ons.
Language: English
Instructors: Dr. Mirko Myllykoski (HPC2N/CS), Dr. Pedro Ojeda-May (HPC2N), Birgitte Brydsö (HPC2N)
Registration: Registration on the course website at HPC2N. Registration ends 27 October 2020, and follows the "first come – first served" principle. For the online course we can take a maximum of 35 persons. Additional registrations will be added to a waiting list.
Fee: This course is a PRACE Training Center (PTC) event. Therefore, the course is free of charge for all participants from the EU or from PRACE-member countries.