GPU Programming with CUDA

Graphics Processing Units (GPUs) were originally developed for computer gaming and other graphical tasks, but for many years have been exploited for general purpose computing in a number of areas. They offer advantages over traditional CPUs because they have greater computational capability, and use high-bandwidth memory systems (memory bandwidth is the main bottleneck for many scientific applications).

Trainer

Kevin Stratford

Kevin has a background in computational physics and joined EPCC in 2001. He teaches on courses including 'Scientific Programming with Python' and 'GPU Programming with CUDA'.

Rupert Nash

Rupert is an experienced trainer who works with CFD, C++ and GPUs, and who teaches courses including 'Modern C++' and 'GPU Programming with CUDA'.

Details

This introductory course will describe GPUs, and the advantages they offer.

It will teach participants how to start to program GPUs, which cannot be used in isolation, but are usually used in conjunction with CPUs.

Important issues affecting performance will be covered.

The course focuses on NVIDIA GPUs, and the CUDA programming language (an extension to C/C++ or Fortran). Please note the course is aimed at application programmers; it does not consider machine learning or any of the packages available in the machine learning arena.

Hands-on practical sessions are included.

You will require your laptop, and your institutional credentials to connect to eduroam. The training parctical exercises will be run on a web-based system so all you will need is a relatively recent web browser (Firefox, Chrome and Safari are known to work).

This course is free to attend.

Timetable

Provisional timetable based on previous run - may be subject to change.

Day 1

10:00 Introduction
10:20 GPU Concepts/Architectures
11:00 Break
11:20 CUDA Programming
12:00 A first CUDA exercise
13:00 Lunch
14:00 CUDA Optimisations
14:20 Optimisation Exercise
15:00 Break
15:20 Constant and Shared Memory
16:00 Exercise
17:00 Close

Day 2

10:00 Recap
10:30 OpenCL and OpenACC directives
11:00 Break
11:20 OpenCL and / or Directives Exercises
12:00 Guest Lecture Alan Gray (NVIDiA) Overview of NVIDIA Volta
13:00 Lunch
14:00 Performance portability and Kokkos
14:30 Exercise: Getting started with Kokkos patterns
15:00 Break
15:10 Kokkos memory management
15:30 Memory management exercises
16:00 Close

Course Materials

Slides and exercise material for this course will be available soon.  Materials from a previous run can be seen here.

Location

The course will be held at EPCC, University of Edinburgh

Registration

Please use the registration page to register for this course.

Questions?

If you have any questions please contact the ARCHER Helpdesk.
https://events.prace-ri.eu/event/935/