Module 22755 (2009)
Syllabus page 2009/2010
06-22755
Programming Massively Parallel Architectures
Level 4/M
Links | Outline | Aims | Outcomes | Prerequisites | Teaching | Assessment | Books | Detailed Syllabus
The Module Description is a strict subset of this Syllabus Page. (The University module description has not yet been checked against the School's.)
Relevant Links
Outline
This module covers the basics of programming massively parallel processors as commonly found in graphics processing units (GPUs). The module is focussed on the architecture of such devices and their use in speeding-up common (non-graphical) computational tasks. Recent developments in GPU architectures made this task substantially easier and newly available programming tools allow for high-level straightforward programming of these systems. The module will provide a largely practical introduction to the topic. Lectures will address the basic architectural principles of modern GPUs andrelevant algorithms and programming techniques. The exercises will be practical programming based on the CUDA framework for Nvidia GPUs.
Aims
The aims of this module are to:
- understand GPU architecture
- understand what applications areas are most suitable to parallel programming
- practical understanding of parallel algorithms
- practical understanding of parallel programming techniques
- concrete skills in programming Nvidia GPUs using the CUDA framework
- skills in using the software tools provided by the CUDA framework
Learning Outcomes
| On successful completion of this module, the student should be able to: | Assessed by: | |
| 1 | describe and explain modern GPU architecture | Examination |
| 2 | describe and explain applications of parallel programming | Examination |
| 3 | describe and explain the CUDA programming model | Examination |
| 4 | design simple parallel algorithms | Examination and continuous assessment |
| 5 | implement more advanced parallel algorithms using CUDA | Continuous assessment |
| 6 | use CUDA tools to debug and profile programs | Continuous assessment |
Restrictions, Prerequisites and Corequisites
Restrictions:
For 2009/10, the module can only accommodate a certain maximum number of students, depending on how much equipment can be purchased. If too many students opt for this module, a test will be conducted to limit the numbers of students.
Prerequisites:
None
Co-requisites:
None, but systems level programming skills will be helpful.
Teaching
Teaching Methods:
2 hrs/week lectures; 2 hrs/week practical sessions
Contact Hours:
Assessment
- Sessional: Normal (sessional): 1.5 hr examination (80%), continuous assessment (20%)
- Supplementary (where allowed): By examination only (100%)
Recommended Books
| Title | Author(s) | Publisher, Date |
| Multigrid Methods on GPUs | Peter Thoman | VDM Verlag, |
| GPU Gems 3: Programming Techniques for High-Performance Graphics and General-Purpose Computation | Hubert Nguyen | Addison Wesley, |
Detailed Syllabus
- Contrasting CPU and GPU architectures
- The CUDA programming model
- A first example: matrix multiplication
- The CUDA memory model
- GPU as part of the PC architecture
- Detailed threading model
- Detailed memory model
- Control flow on the GPU
- Floating-point aspects
- Parallel programming concepts
- Parallel algorithms
- Reduction
- Advanced features
Last updated: 21 Aug 2009
Source file: /internal/modules/COMSCI/2009/xml/22755.xml
Links | Outline | Aims | Outcomes | Prerequisites | Teaching | Assessment | Books | Detailed Syllabus