Postgraduate Course: Numerical Algorithms for High Performance Computing (EPCC11006)
Course Outline
| School | School of Informatics |
College | College of Science and Engineering |
| Credit level (Normal year taken) | SCQF Level 11 (Postgraduate) |
Availability | Available to all students |
| SCQF Credits | 10 |
ECTS Credits | 5 |
| Summary | The development of High Performance Computing (HPC) systems has been largely driven by the requirements of Computational Scientists running large-scale numerical simulations such as global weather forecasting or studying new materials at the atomic scale. This course covers some of the basic numerical algorithms and computational patterns used in HPC and how they are implemented and used in practice, including the use of standard packages and libraries. Where appropriate, reference will be made to parallel implementations.
All these algorithms operate on real-valued variables, not integers, so it is important to understand the issues around storing and working with floating-point numbers, including the errors that this can introduce. This is an applied course and running the algorithms in practical situations is a key component. |
| Course description |
The course will cover:
- Computational science as the third methodology
- Basic numerics, floating-point representation, errors and exceptions
- Simple ordinary differential equations
- N-body / particle methods
- Dense linear algebra, algorithms and libraries
- Partial differential equations and boundary value problems
- Sparse linear algebra
- Initial value problems and implicit methods
- Spectral methods - Fast Fourier Transforms (FFTs) and applications
- Monte Carlo methods
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Entry Requirements (not applicable to Visiting Students)
| Pre-requisites |
|
Co-requisites | |
| Prohibited Combinations | |
Other requirements | None |
Information for Visiting Students
| Pre-requisites | Students are required to be familiar with C, C++ or Fortran for practical exercises. Basic mathematical knowledge is assumed but only at final-year school level. |
| High Demand Course? |
Yes |
Course Delivery Information
|
| Academic year 2024/25, Available to all students (SV1)
|
Quota: 40 |
| Course Start |
Semester 1 |
Timetable |
Timetable |
| Learning and Teaching activities (Further Info) |
Total Hours:
100
(
Lecture Hours 20,
Supervised Practical/Workshop/Studio Hours 20,
Feedback/Feedforward Hours 1,
Formative Assessment Hours 1,
Revision Session Hours 1,
Programme Level Learning and Teaching Hours 2,
Directed Learning and Independent Learning Hours
55 )
|
| Assessment (Further Info) |
Written Exam
75 %,
Coursework
25 %,
Practical Exam
0 %
|
| Additional Information (Assessment) |
Written Exam 75%
Coursework 25% (1 Class Test).
Written examination comprised of compulsory questions (equally weighted).
Coursework (class test) is an examination question presented to the students mid-Semester |
| Feedback |
Provided via practical classes, formative class test, and following examination. |
| Exam Information |
| Exam Diet |
Paper Name |
Hours & Minutes |
|
| Main Exam Diet S1 (December) | Numerical Algorithms for HPC | 2:120 | |
Learning Outcomes
On completion of this course, the student will be able to:
- Explain why computer simulation is an essential technique in many areas of science, and understand its advantages and limitations.
- Describe how real-valued quantities are represented on a computer and understand the various sources and types of error.
- Understand how physical problems are represented in a discrete form suitable for computer simulation.
- Discuss the appropriate choice of algorithm for different problems.
- Use standard numerical libraries in their own applications.
|
Reading List
| Provided via Learn/Leganto |
Additional Information
| Graduate Attributes and Skills |
Solution Exploration, Evaluation and Prioritisation.
Computational Science Techniques. |
| Keywords | NAHPC,Numerical Algorithms,HPC,EPCC,Algebra,Algorithms,Monte Carlo,Computational Science |
Contacts
| Course organiser | Dr Arno Proeme
Tel:
Email: arno.proeme@ed.ac.uk |
Course secretary | Mr James Richards
Tel: 90131 6)51 3578
Email: J.Richards@epcc.ed.ac.uk |
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