High Performance Computing: Programming GPU using CUDA Fortran PrerequisitesNew
Description
The course aims to give a very introductory overview of GPU Programming and CUDA FORTRAN language.
Target audience
- All current Cambridge University members (departments and colleges)
- Especially University alumni (PhD) and researchers who already have access to HPCS computing facilities
- Further details regarding eligibility criteria are available
Prerequisites
- Basic FORTRAN77/FORTRAN90 knowledge is required
- Basic knowledge of Unix environment
- No required knowledge of GPU computer is needed
Topics covered
- CUDA FORTRAN history
- Crash introduction to GPU Computing and CUDA C
- memory model
- execution model
- Simple CUDA FORTRAN example
- Compiling CUDA FORTRAN code
- Pinning memory and Asynchronous transfers
- Calling CUDA Libraries
- CUDA FORTRAN and OpenACC interoperability
- Multi-GPU programming
- peer-to-peer
- multiple distributed GPU and MPI
Format
- Presentations and practicals
Taught using
- CUDA FORTRAN (PGI compiler installed on HPCS systems) and PuTTY on MCS Windows
Notes
- HPCS users will have the opportunity to perform experiments directly to Wilkes
- There are few books "CUDA Fortran For Scientists and Engineers" (G. Ruetsch, M. Fatica - Morgan Kaufmann) available for students who wants to engage in long-term code porting of their FORTRAN application to CUDA FORTRAN
Duration
- One full day
Related courses
- High Performance Computing: An Introduction
- High Performance Computing: Programming GPU using Open ACC
- Unix: Introduction to the Command Line Interface (Self-paced)
Themes
Events available