Learn about the use of Graphical Processing Units (GPUs) for scientific computation. Due to the large games market GPUs are very attractive in terms of their price/performance ratio, but are challenging to program as the user has to manage hundreds of parallel threads.
The course covers:
- The basic concepts and programming techniques relevant to applied high performance computing (HPC) and parallel computing
- The use of Graphical Processing Units (GPUs) for scientific computation
- CUDA, a common extension to C for GPU programming.
There are also a number of practical sessions.
You are not expected to have prior experience of HPC or parallel programming to take this course, but you will need to be familiar with programming in Fortran, C or C++.
This course is not scheduled at the moment. Course materials are available via the internal wiki page
Find out more - WikiFree or Paid for:
Free
Product Features
- One day course
- Online documentation
- Small group and teacher
Applicable Disciplines
- Agricultural and Biological Sciences
- Business, Management and Accounting
- Computer Sciences
- Energy
- Health Professions
- Material Science
- Neuroscience
- Physics and Astronomy
- Arts and Humanities
- Chemical Engineering
- Earth and Planetary Sciences
- Engineering
- Immunology and Microbiology
- Mathematics
- Nursing
- Psychology
- Biochemistry, Genetics and Molecular Biology
- Chemistry
- Economics, Econometrics and Finance
- Environmental Science
- Medicine
- Pharmacology, Toxicology and Pharmaceutics
- Social Sciences
- Veterinary
Terms & Conditions
If you are unable to attend a course you have booked, please cancel through the University's Event Booking service. Attendance is recorded and failure to attend without prior notice may affect your future bookings. Standby places are offered to people on the waiting list, so please arrive in good time or your place may be reallocated as a standby.
Technical Requirements
- N/A
Skills Required
- Familiarity with programming in Fortran, C or C++