|Year of offer||2019|
|Subject level||Graduate coursework|
|Fees||Subject EFTSL, Level, Discipline & Census Date|
With the ever increasing power of modern computers, the use of computer simulation is becoming more common in engineering practice. This course will introduce topics in high performance computing through a number of applications in science and engineering, including problems in linear algebra, partial differential equations (e.g. computational fluid dynamics), molecular dynamics, and agent based modelling. These applications will necessitate the inclusion of some theory regarding numerical methods for ordinary and partial differential equations (e.g. finite difference and finite element methods), but the key focus of the course will be on how large scale problems can be decomposed onto supercomputing architectures and introducing aspects of large scale visualization.
This course will include study of various numerical methods used in engineering practice and how these applied to solving computational problems and hence programmed for execution on a supercomputer. The course will include both the higher level mathematics as well as practical issues associated with using a supercomputer.
Intended learning outcomes
INTENDED LEARNING OUTCOMES (ILO)
Having completed this subject the student is expected to be able to -
- Determine the complexity of a given parallel algorithm
- Determine the appropriate architecture for a particular problem and implement code to decompose the problem
- Develop numerical methods for solving ordinary and partial differential equations
- Implement software for shared memory multi-core systems with the OpenMP application programming interface
- Implement software for distributed memory supercomputers with MPI application programming interface.
- Ability to apply knowledge of basic science and engineering fundamentals
- Ability to undertake problem identification, formulation and solution
- Capacity for independent critical thought, rational inquiry and self-directed learning.
Eligibility and requirements
Both of the following -
|Code||Name||Teaching period||Credit Points|
or admission into the 100 point Master of IT MC-IT (Distributed Computing) Program
Core participation requirements
The University of Melbourne is committed to providing students with reasonable adjustments to assessment and participation under the Disability Standards for Education (2005), and the Assessment and Results Policy (MPF1326). Students are expected to meet the core participation requirements for their course. These can be viewed under Entry and Participation Requirements for the course outlines in the Handbook.
Further details on how to seek academic adjustments can be found on the Student Equity and Disability Support website: http://services.unimelb.edu.au/student-equity/home
- Two assignments due in weeks 7 and 12, requiring 35 - 40 hours of work each (30% each, 60% total).
- End of semester exam (40%), assesses ILOs 1 to 5.
Dates & times
- Semester 2
Principal coordinator Stephen Moore Mode of delivery On Campus — Parkville Contact hours 36 hours of lectures and workshops Total time commitment 200 hours Teaching period 29 July 2019 to 27 October 2019 Last self-enrol date 9 August 2019 Census date 31 August 2019 Last date to withdraw without fail 27 September 2019 Assessment period ends 22 November 2019
Semester 2 contact information
Time commitment details
There are no specifically prescribed or recommended texts for this subject.
- Subject notes
LEARNING AND TEACHING METHODS
This subject will be delivered through a combination of lectures and tutorials.
INDICATIVE KEY LEARNING RESOURCES
Resources include a selection of textbooks, a course reader, lecture slides, example codes
CAREERS / INDUSTRY LINKS
- Related Handbook entries
This subject contributes to the following:
Type Name Course Master of Philosophy - Engineering Course Doctor of Philosophy - Engineering Course Ph.D.- Engineering Specialisation (formal) Computing Specialisation (formal) Mechanical Specialisation (formal) Mechanical with Business Specialisation (formal) Distributed Computing
- Available through the Community Access Program
About the Community Access Program (CAP)
This subject is available through the Community Access Program (also called Single Subject Studies) which allows you to enrol in single subjects offered by the University of Melbourne, without the commitment required to complete a whole degree.
Entry requirements including prerequisites may apply. Please refer to the CAP applications page for further information.
Additional information for this subject
Subject coordinator approval required
- Available to Study Abroad and/or Study Exchange Students
This subject is available to students studying at the University from eligible overseas institutions on exchange and study abroad. Students are required to satisfy any listed requirements, such as pre- and co-requisites, for enrolment in the subject.