Postgraduate Course: Practical Introduction to High Performance Computing (PGPH11093)
Course Outline
| School | School of Physics and Astronomy |
College | College of Science and Engineering |
| Credit level (Normal year taken) | SCQF Level 11 (Postgraduate) |
| Course type | Online Distance Learning |
Availability | Not available to visiting students |
| SCQF Credits | 20 |
ECTS Credits | 10 |
| Summary | This course is ONLY available to students of the Data Science, Technology and Innovation (DSTI) online distance learning programme
High Performance Computing (HPC) is a fundamental technology used in solving scientific and commercial problems. Many of the grand challenges of science depend on simulations and models run on HPC facilities to make progress, for example: protein folding, the search for the Higgs boson and developing nuclear fusion. In industry, sophisticated computer models are integral to the development of products such as jet engines, wind turbines and new drugs.
Modern supercomputers are parallel computers, gaining their power from many thousands of individual processors. Developing software to run on these systems requires using new parallel programming techniques.
The course will cover all the fundamental concepts that underpin modern HPC. The course is practical in the sense that you will explore these topics by running parallel programs on real HPC systems such as the UK national supercomputer ARCHER.
The course will be delivered entirely online, and videos, notes and exercises will be released as the course progresses.
N.B. This has a non-standard duration (20 weeks) which will be incompatible with many programmes. |
| Course description |
Modern supercomputers are parallel computers, gaining their power from many thousands of individual processors. Developing software to run on these systems requires using new parallel programming technologies. The course will cover all the fundamental concepts that underpin modern HPC. The course is practical in the sense that you will explore these topic by running parallel programs on real HPC systems such as the UK national supercomputer ARCHER. The same techniques can also be applied to smaller systems such as multi-core desktops, graphics processors and computing clusters.
The course has three main themes:
1) Hardware, Architectures, System Software
How are HPC systems constructed and what impact do components play in performance of applications? What system software is used on HPC systems and how does it impact the user experience?
2) Parallel Programming
What are the key parallel programming paradigms in use on modern HPC systems and how are they implemented and made available to users in practice? How do you measure parallel performance and scaling? How do you debug and profile parallel applications?
3) Applications on HPC systems
What types of applications run on modern HPC systems and what are the limiting factors to scaling and performance in these areas? What does the future hold for HPC applications - how will they run on next generation HPC systems.
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Entry Requirements (not applicable to Visiting Students)
| Pre-requisites |
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Co-requisites | |
| Prohibited Combinations | |
Other requirements | Only available to students of the Data Science, Technology and Innovation (DSTI) online distance learning programme
The course does not require any substantial prior experience in programming. We require basic IT literacy and a basic understanding of one form of programming/scripting language (e.g.. C, C++, Java, Python, Fortran, Matlab, Visual Basic, bash).
Ahead of the course, students should complete everything before "Advanced Topics in Python" at Codacademy. (http://www.codecademy.com/tracks/python/). This is a beginner's Python course that should be straightforward for anyone with a basic understanding of another language.
During the course students will be modifying existing computer programs written in C or Fortran, and developing simple programs in Python. |
Course Delivery Information
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| Academic year 2017/18, Not available to visiting students (SS1)
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Quota: None |
| Course Start |
Semester 2 |
| Course Start Date |
15/01/2018 |
Timetable |
Timetable |
| Learning and Teaching activities (Further Info) |
Total Hours:
200
(
Lecture Hours 25,
Seminar/Tutorial Hours 15,
Online Activities 28,
Summative Assessment Hours 60,
Programme Level Learning and Teaching Hours 4,
Directed Learning and Independent Learning Hours
68 )
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| Assessment (Further Info) |
Written Exam
0 %,
Coursework
100 %,
Practical Exam
0 %
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| Additional Information (Assessment) |
Formative
- peer assessment of answers to set exercises;
- self-assessment via online multiple-choice questions to reinforce key topics.
Summative
1. Group report on aspects of HPC architectures (25%);
2. Individual report on performance analysis of HPC programs on a variety of architectures (50%);
3. Individual essay: case-study on application of HPC to a particular subject area (25%). |
| Feedback |
Not entered |
| No Exam Information |
Learning Outcomes
On completion of this course, the student will be able to:
- Understand the key components of HPC architectures and how they are put together to form complete systems
- Be able to build and test code in a Linux/Unix environment, execute in parallel and understand the stages involved.
- Compare and contrast the message-passing and multithreaded parallel programming models, and describe four key parallelisation strategies used in modern HPC codes.
- Understand the importance of performance and Amdahl's law, and measure and comment on the performance of parallel codes.
- Explain the current uses of HPC and the key issues for HPC in the future.
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Learning Resources
| There is no single compulsory course text. Pointers to appropriate material will be made available online. |
Additional Information
| Course URL |
www.epcc.ed.ac.uk/online-courses |
| Graduate Attributes and Skills |
- Critical thinking
- Communication of complex ideas in accessible language
- Working in an interdisciplinary field
- Programming and Scripting
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| Keywords | Not entered |
Contacts
| Course organiser | Dr David Henty
Tel: (0131 6)50 5960
Email: d.henty@ed.ac.uk |
Course secretary | Mr Ben Morse
Tel: (0131 6)51 3398
Email: Ben.Morse@ed.ac.uk |
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