9-11 September 2013
Europe/London timezone
Graphics Processing Units (GPUs) were originally designed to display computer graphics, but they have developed into extremely powerful chips capable of handling demanding, general-purpose calculations. The GPU architecture is inherently is more suited to many types of intensive parallel computations than the traditional CPU, and hence computationally demanding sections of code can be accelerated to significantly increase overall performance. This is true not just for small-scale applications run on desktop size machines, but also for the largest-scale applications on massively parallel architectures. Applications must be adapted to utilise GPUs: most lines of application source code are executed on the CPU and key computational kernels are distributed to the GPU cores. Currently, for NVIDIA GPUs, the most popular programming method is the CUDA API, which is extremely powerful but requires significant development effort. OpenCL is an alternative API, which is less mature than CUDA but has portability advantages. Recently, a new higher-level standard has emerged, OpenACC, which promises to offer higher productivity. The programmer uses "directives" in the code to provide the compiler with the information required to automatically offload code to the GPU. In this 3-day course we will introduce and provide hands-on experience of CUDA, OpenCL (with more emphasis on the former) and OpenACC. In many cases it is relatively straightforward to port a code to the GPU, but much harder to obtain good performance: we will cover a range of common GPU optimisation techniques. No prior HPC or parallel programming knowledge is assumed, but attendees must already be able to program in C, C++ or Fortran. Access will be given to appropriate hardware for all the exercises. Pre-requisite Programming Languages: Fortran, C or C++.
Starts 9 Sep 2013 09:30
Ends 11 Sep 2013 16:30
The University of Edinburgh James Clerk Maxwell Building Mayfield Road Edinburgh EH9 3JZ
This course is funded by the PRACE project and is free to all. Please register using the online form. If you have any questions, please consult the course forum page or contact epcc-support@epcc.ed.ac.uk.
Information about how to find the James Clerk Maxwell Building (JCMB) can be found on the School of Physics and Astronomy website.
Note that parking on the King's Buildings campus is by permit only, and that parking just outside on Mayfield Road is restricted before 09:15 and after 16:30 - and cars will be removed (with a hefty fee payable to get your car back) if parked there during the restricted times. Unrestricted free parking is available on nearby Hallhead Road, Ross Road, Blackbarony Road and Gordon Terrace to the east of the campus, and along the north side of the campus on West Mains Road.
A number of B&Bs and hotels can be found approximately 10 minutes' walk from EPCC, including:
* Smiths' Guest House, 77 Mayfield Road, Edinburgh EH9 3AA
* Mayfield Lodge Guest House, 75 Mayfield Road, Edinburgh EH9 3AA
* Highfield Guest House, 83 Mayfield Road, Edinburgh EH9 3AE
* Lauderville Guest House, 52 Mayfield Road, Edinburgh EH9 2NH
* Glenisla Hotel, 12 Lygon Road, Edinburgh EH16 5QB
* Glendale House Guest House, 5 Lady Road, Edinburgh EH16 5PA
There is also the Travelodge Cameron Toll, 43 Craigmillar Park, Edinburgh EH16 5PD. Note that the room price does not include breakfast.