• Offered by Research School of Computer Science
  • ANU College ANU College of Engineering and Computer Science
  • Classification Advanced
  • Course subject Computer Science
  • Areas of interest Computer Science, Information Technology
  • Academic career PGRD
  • Course convener
    • Dr Giuseppe Maria Junior Barca
  • Mode of delivery In Person
  • Offered in Second Semester 2020
    See Future Offerings

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:

Upon completion of the course, students should:
  •  appreciate the building blocks of scientific and engineering software.
  •  demonstrate a basic knowledge of numerical computing using an appropriate programming language.
  •  be competent 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 (40%); Mid semester exam (10%); Final Exam (50%)

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Workload

Thirty one-hour lectures and six two-hour tutorial/laboratory sessions

Requisite and Incompatibility

To enrol in this course you must be studying Master of Computing or have successfully completed COMP6700 or COMP6710.

Prescribed Texts

Buyya, R. High Performance Cluster Computing: Programming and Applications, Prentice Hall, Upper Saddle River, New Jersey 1999.

Dowd, K. & Severance, C. High Performance Computing, 2nd edition, O'Reilly & Associates Inc, 1998.

Fosdick, L.D. Jessup, E.R., Schauble, C.J.C. & Domik,G., An Introduction to High-Performance Scientific Computing, The MIT Press, 1996.

Heath, M.T. Scientific Computation - An Introductory Survey, McGraw-Hill, 1997.

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.

Specialisations

Fees

Tuition fees are for the academic year indicated at the top of the page.  

If you are a domestic graduate coursework or international student you will be required to pay tuition fees. Tuition fees are indexed annually. Further information for domestic and international students about tuition and other fees can be found at Fees.

Student Contribution Band:
2
Unit value:
6 units

If you are an undergraduate student and 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). You can find your student contribution amount for each course 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
Domestic fee paying students
Year Fee
2020 $4320
International fee paying students
Year Fee
2020 $5760
Note: Please note that fee information is for current year only.

Offerings, Dates and Class Summary Links

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.

Second Semester

Class number Class start date Last day to enrol Census date Class end date Mode Of Delivery Class Summary
9521 27 Jul 2020 03 Aug 2020 31 Aug 2020 30 Oct 2020 In Person N/A

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