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Parallel and Multicore Computing (COMP90025)
Graduate courseworkPoints: 12.5On Campus (Parkville)
About this subject
- Overview
- Eligibility and requirements
- Assessment
- Dates and times
- Further information
- Timetable(opens in new window)
Contact information
Semester 2
Dr Aaron Harwood
email: aharwood@unimelb.edu.au
Overview
Availability | Semester 2 |
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Fees | Look up fees |
AIMS
The subject aims to introduce students to parallel algorithms and their analysis. Fundamental principles of parallel computing are discussed. Various parallel architectures and programming platforms are introduced. Parallel algorithms for different architectures, as well as parallel algorithms addressing specific scientific problems are critically analysed.
INDICATIVE CONTENT
Topics include: principles of parallel computing, PRAM model, PRAM algorithms, parallel architectures, OpenMP, shared memory algorithms, systolic algorithms, parallel communication patterns, PVM/MPI, scientific applications, hypercube, graph embeddings and extended parallel computing models.
Intended learning outcomes
INTENDED LEARNING OUTCOMES (ILO)
On completion of this subject the student is expected to:
- Have an understanding of parallel algorithms, analysis and architectures
- Obtain experience developing parallel algorithms for various parallel architectures
Generic skills
On completion of this subject the student should have the following skills:
- Ability to undertake problem identification, formulation and solution
- Capacity for independent critical thought, rational inquiry and self-directed learning
- Profound respect for truth and intellectual integrity, and for the ethics of scholarship.
Last updated: 3 November 2022
Eligibility and requirements
Prerequisites
None
Corequisites
None
Non-allowed subjects
None
Recommended background knowledge
Knowledge of Operating Systems and Networks, and C Programming. UNIX familiarity.
Inherent requirements (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
Last updated: 3 November 2022
Assessment
Additional details
- Intended Learning Outcomes (ILOs) 1 and 2 are addressed by extensive Project work requiring approximately 50 - 55 hours or work (40%), which involves programming exercises, measurements and analysis, architecture specific programming and written work
- ILO 1 is also addressed by one 3-hour end of semester examination (60%).
Hurdle requirement: To pass the subject, students must obtain at least:
- 50% overall.
- 20/40 in the Project work
- 30/60 in the end-of-semester written examination.
Last updated: 3 November 2022
Dates & times
- Semester 2
Principal coordinator Aaron Harwood Mode of delivery On Campus (Parkville) Contact hours 3 hours per week; Non-contact time commitment: 84 hours Total time commitment 200 hours Teaching period 23 July 2018 to 21 October 2018 Last self-enrol date 3 August 2018 Census date 31 August 2018 Last date to withdraw without fail 21 September 2018 Assessment period ends 16 November 2018 Semester 2 contact information
Dr Aaron Harwood
email: aharwood@unimelb.edu.au
Time commitment details
200 hours
Last updated: 3 November 2022
Further information
- Texts
Prescribed texts
None
- Subject notes
LEARNING AND TEACHING METHODS
The subject will be delivered through a combination of lectures, tutorials and project work. The project work involves developing parallel algorithms implemented on a variety of parallel architectures and report writing.
INDICATIVE KEY LEARNING RESOURCES
Students will have access to lecture notes and lecture slides. The subject LMS site also contains links to recommended literature and current survey papers of parallel computing. Students will make use of parallel computer systems.
CAREERS / INDUSTRY LINKS
The subject provides the fundamentals in parallel computing that support a career in areas such as HPC Systems Administrator, HPC Programmer, Specialist Programmer, Systems Administrator, Numerical Modelling and Analytics Developer.
- Related Handbook entries
This subject contributes to the following:
Type Name Course Master of Science (Computer Science) Course Master of Philosophy - Engineering Course Master of Data Science Course Doctor of Philosophy - Engineering Course Ph.D.- Engineering Course Master of Information Technology Specialisation (formal) Distributed Computing Specialisation (formal) Software - 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.
Last updated: 3 November 2022