| Unit name | Advanced Computational Physics |
|---|---|
| Unit code | PHYSM0032 |
| Credit points | 10 |
| Level of study | M/7 |
| Teaching block(s) |
Teaching Block 4 (weeks 1-24) |
| Unit director | Dr. Hanna |
| Open unit status | Not open |
| Pre-requisites |
Level 6 unit in computing, either PHYS38012: Computational Physics, or PHYS30009: Introduction to Computational Physics, or equivalent. |
| Co-requisites |
None. |
| School/department | School of Physics |
| Faculty | Faculty of Science |
This unit is designed for students with an interest in computational methods who wish to learn the basics of parallel programming, and parallel computational methods for physics. The course is aimed at students with a working knowledge of either the C (C++) or Python programming languages.
Aims: To introduce concepts of high performance computing for physicists, including parallel computing and use of GPU arrays, and to gain practical experience in the use of such methods to solve physics problems. The course will be aimed at students who might go forward to research in computational physics, and would want to obtain maximum benefit from the current generation of supercomputers.
General Description: The course will consist of a set of lectures and on-line tutorials, and supported by regular drop-in sessions. Assessment will be via a mini-project. The following topics will be covered:
Application examples:
Mini-projects will be available in the application areas detailed above.
After taking this unit, students should have a thorough grasp of parallel computing architectures for applications in physics research, as well as parallel algorithms for linear algebra and techniques for performing physics simulations across multiple processors. They should also be aware of the scalability of these techniques and the need to tune the size of the simulation to optimise its efficiency on a given computer system. They should be able to construct a working parallel program to solve a given physical problem, and be able to critically analyse the results obtained from the program in the context of the physics being studied.
Transferable Skills: Parallel programming techniques for application in physical sciences research or in a commercial (industrial) context.
The unit will be taught through a combination of
Formative assessment through on-line tutorials and exercises which will be submitted for marking.
Summative assessment will consist of a mini-project (100%) consisting of a copy of the student's computer program and a structured technical report (maximum 2000 words) reviewing the results obtained using it.
If this unit has a Resource List, you will normally find a link to it in the Blackboard area for the unit. Sometimes there will be a separate link for each weekly topic.
If you are unable to access a list through Blackboard, you can also find it via the Resource Lists homepage. Search for the list by the unit name or code (e.g. PHYSM0032).
How much time the unit requires
Each credit equates to 10 hours of total student input. For example a 20 credit unit will take you 200 hours
of study to complete. Your total learning time is made up of contact time, directed learning tasks,
independent learning and assessment activity.
See the Faculty workload statement relating to this unit for more information.
Assessment
The Board of Examiners will consider all cases where students have failed or not completed the assessments required for credit.
The Board considers each student's outcomes across all the units which contribute to each year's programme of study. If you have self-certificated your absence from an
assessment, you will normally be required to complete it the next time it runs (this is usually in the next assessment period).
The Board of Examiners will take into account any extenuating circumstances and operates
within the Regulations and Code of Practice for Taught Programmes.
