• Offered by Research School of Computer Science
  • ANU College ANU College of Engineering and Computer Science
  • Course subject Computer Science
  • Areas of interest Computer Science, Information Technology, Software Engineering

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.

Other Information

Course offered Semester 1 in alternate, even-numbered years.

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 have completed COMP2100 or COMP2500 or COMP2300; and COMP2600 or 6 units of 2000 level MATH courses; and 6 units of 2000 level COMP courses.

Prescribed Texts

There will be no set text book for COMP3320/6464 in 2008, but we will draw on material from a variety of sources.

Dowd, Kevin & Severance, Charles High Performance Computing, O'Reilly, 2nd edition, 1998.

Hyde, Randall Write Great Code Volume 1: Understanding the Machine No Starch Press

Hyde, Randall Write Great Code Volume 2: Thinking Low-Level, Writing High-Level, No Starch Press

Scott, L.R., Clark, T. & Bagheri, B. Scientific Parallel Computing, Princeton University Press.

Shiflet, A.B. & Shiflet, G.W. Introduction to Computational Science: Modeling and Simulation for the Sciences , Princeton University Press

Garg, Rajat P. & Sharapov, Ilya Techniques for Optimizing Applications: High Performance Computing , Prentice Hall.

Hennessy, John L., Patterson, David A. & Kaufmann, Morgan Computer Architecture: A Quantitative Approach .

Barton, John R. & Nackman, Lee R. Scientific and Engineering C++: An introduction with Advanced Techniques and Examples, Addison Wesley.

Fosdick, Lloyd D., Jessep, Elizabeth R., Schauble, Carolyn J. C, & Domik, Gitta. An Introduction to High-Performance Scientific ComputingThe MIT Press, 1996.

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

Majors

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
2017 $3660
International fee paying students
Year Fee
2017 $4878
Note: Please note that fee information is for current year only.

Offerings and Dates

The list of offerings for future years is indicative only

First Semester

Class number Class start date Last day to enrol Census date Class end date Mode Of Delivery Class Summary
4169 19 Feb 2018 27 Feb 2018 31 Mar 2018 25 May 2018 In Person N/A

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