This course provides an introduction to High Performance Computing with an orientation towards applications in science and engineering. Aspects of numerical computing and the design and construction of sophisticated scientific software will be considered. The focus will be on the C and C++ programming languages, although reflecting the reality of modern scientific computation this course will also touch on other languages such as Python, Java and FORTRAN95. The course will study high performance computer architectures, including modern parallel processors, and will describe how an algorithm interacts with these architectures. It will also look at practical methods of estimating and measuring algorithm/architecture performance.
The following topics will be addressed: the C++ programming language; basic numerical computing from aspects of floating point error analysis to algorithms for solving differential equations; the engineering of scientific software; general high performance computing concepts and architectural principles; modern scalar architectures and their memory structure; performance and programmability issues, and program analysis techniques for high performance computing; parallel computing paradigms and programming using the OpenMP standard; trends in HPC systems.
Learning Outcomes
Upon successful completion, students will have the knowledge and skills to:
- Appreciate the building blocks of scientific and engineering software.
- Demonstrate knowledge of numerical computing using an appropriate programming language.
- Be proficient in experimental computing in a numerical context and of the optimisation of algorithms on high performance architectures.
- Be able to reason about the accuracy of mathematical and numerical models of real physical phenomena.
- Have an awareness of the modern field of computational science and engineering and of the impact of high performance computing on science and industry.
- Have an understanding of the various paradigms of high performance computing and their potential for performance and programmability.
- Be capable of writing algorithms that yield good performance on high-performance architectures, and to be able to estimate and evaluate their performance.
Indicative Assessment
- Assignment(s) (40) [LO 1,2,3,4,5,6,7]
- Mid Semester Test (20) [LO 1,2,3,4,5,6,7]
- Final Exam (40) [LO 1,2,3,4,5,6,7]
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Workload
Thirty one-hour lectures and eight two-hour tutorial/laboratory sessions plus self-study to a total of 130 hours.
Inherent Requirements
None.
Requisite and Incompatibility
Prescribed Texts
See class summary.
Assumed Knowledge
Ability to develop small to medium sized programs in C/C++. Basic knowledge of computer systems. Mathematical skills equivalent to those normally taught in introductory courses at a university.
Fees
Tuition fees are for the academic year indicated at the top of the page.
Commonwealth Support (CSP) Students
If you have been offered a Commonwealth supported place, your fees are set by the Australian Government for each course. At ANU 1 EFTSL is 48 units (normally 8 x 6-unit courses). More information about your student contribution amount for each course at Fees.
- Student Contribution Band:
- 2
- Unit value:
- 6 units
If you are a domestic graduate coursework student with a Domestic Tuition Fee (DTF) place or international student you will be required to pay course tuition fees (see below). Course tuition fees are indexed annually. Further information for domestic and international students about tuition and other fees can be found at Fees.
Where there is a unit range displayed for this course, not all unit options below may be available.
| Units | EFTSL |
|---|---|
| 6.00 | 0.12500 |
Course fees
- Domestic fee paying students
| Year | Fee |
|---|---|
| 2024 | $4980 |
- International fee paying students
| Year | Fee |
|---|---|
| 2024 | $6360 |
Offerings, Dates and Class Summary Links
ANU utilises MyTimetable to enable students to view the timetable for their enrolled courses, browse, then self-allocate to small teaching activities / tutorials so they can better plan their time. Find out more on the Timetable webpage.
Class summaries, if available, can be accessed by clicking on the View link for the relevant class number.
Second Semester
| Class number | Class start date | Last day to enrol | Census date | Class end date | Mode Of Delivery | Class Summary |
|---|---|---|---|---|---|---|
| 9234 | 22 Jul 2024 | 29 Jul 2024 | 31 Aug 2024 | 25 Oct 2024 | In Person | N/A |
