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.
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Requisite and Incompatibility
To enrol in this course you must: be studying Master of Computing or Master of Computing (Advanced) OR have successfully completed (COMP6710 or COMP7710 or COMP1110 or COMP1140). Incompatible with COMP3320.
Referenced entries (5)
Links and code mentions retain their original context above. They may describe options, prerequisites or exclusions.
- COMP6710 · 2027
- COMP7710 · 2027
- COMP1110 · 2027 · saved source not linked
- COMP1140 · 2027 · saved source not linked
- COMP3320 · 2027 · saved source not linked
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.
Published offerings
Future offerings are indicative. Only recognised 2027 sessions with a published class number are offered in the enrolment demo.
| Year | Session | Class number | Class start date | Last day to enrol | Census date | Class end date | Mode Of Delivery | Class Summary |
|---|---|---|---|---|---|---|---|---|
| 2027 | Second Semester | 10379 | 26 Jul 2027 | 02 Aug 2027 | 31 Aug 2027 | 29 Oct 2027 | In Person | N/A |
| 2028 | Second Semester | 11078 | 24 Jul 2028 | 31 Jul 2028 | 31 Aug 2028 | 27 Oct 2028 | In Person | N/A |
Complete offering text
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. The list of offerings for future years is indicative only. Class summaries, if available, can be accessed by clicking on the View link for the relevant class number. 2027 2028 Second Semester Class number Class start date Last day to enrol Census date Class end date Mode Of Delivery Class Summary 10379 26 Jul 2027 02 Aug 2027 31 Aug 2027 29 Oct 2027 In Person N/A Second Semester Class number Class start date Last day to enrol Census date Class end date Mode Of Delivery Class Summary 11078 24 Jul 2028 31 Jul 2028 31 Aug 2028 27 Oct 2028 In Person N/A
Source evidence (1 saved copy)
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assets/Courses/Computer Systems/6000/High Performance Scientific Computing/High Performance Scientific Computing - ANU.html
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