Cluster and Cloud Computing (COMP90024)
Graduate courseworkPoints: 12.5On Campus (Parkville)
About this subject
Contact information
Semester 1
Prof Richard Sinnott
email: rsinnott@unimelb.edu.au
Overview
| Availability | Semester 1 |
|---|---|
| Fees | Look up fees |
AIMS
The growing popularity of the Internet along with the availability of powerful computers and high-speed networks as low-cost commodity components are changing the way we do parallel and distributed computing (PDC). Cluster and Cloud Computing are two approaches for PDC. Clusters employ cost-effective commodity components for building powerful computers within local-area networks. Recently, “cloud computing” has emerged as the new paradigm for delivery of computing as services in a pay-as-you-go-model via the Internet. These approaches are used to tackle may research problems with particular focus on "big data" challenges that arise across a variety of domains.
Some examples of scientific and industrial applications that use these computing platforms are: system simulations, weather forecasting, climate prediction, automobile modelling and design, high-energy physics, movie rendering, business intelligence, big data computing, and delivering various business and consumer applications on a pay-as-you-go basis.
This subject will enable students to understand these technologies, their goals, characteristics, and limitations, and develop both middleware supporting them and scalable applications supported by these platforms.
This subject is an elective subject in the Master of Information Technology. It can also be taken as an Advanced Elective subject in the Master of Engineering (Software).
INDICATIVE CONTENT
- Cluster computing: elements of parallel and distributed computing, cluster systems architecture, resource management and scheduling, single system image, parallel programming paradigms, cluster programming with MPI
- Utility computing: foundations and grid computing technologies
- Cloud computing: cloud platforms, Virtualization, Cloud Application Programming Models (Task, Thread, and MapReduce), Cloud applications, and future directions in utility and cloud computing
- "Big data" processing and analytics in distributed environments
Please view this video for further information: Cluster and Cloud Computing
Intended learning outcomes
INTENDED LEARNING OUTCOMES (ILO)
On completion of this subject the student is expected to:
- Be able to understand emerging distributed technologies
- Be able to design large-scale distributed systems
- Be able to implement high-performance cluster and cloud applications
Generic skills
On completion of this subjects students should have the following skills:
- Have improved skills in teamwork and presentation of results
- Be able to undertake problem identification, formulation and solution
- Have a capacity for independent critical thought, rational inquiry and self-directed learning
- Have a profound respect for truth and intellectual integrity, and for the ethics of scholarship.
Last updated: 4 March 2025
Eligibility and requirements
Prerequisites
One of
| Code | Name | Teaching period | Credit Points |
|---|---|---|---|
| COMP90007 | Internet Technologies |
Semester 1 (On Campus - Parkville)
Semester 2 (On Campus - Parkville)
|
12.5 |
| COMP90038 | Algorithms and Complexity |
Semester 2 (On Campus - Parkville)
Semester 1 (On Campus - Parkville)
|
12.5 |
| COMP90041 | Programming and Software Development |
Semester 2 (On Campus - Parkville)
Semester 1 (On Campus - Parkville)
|
12.5 |
OR
Admission into one of the following:
- MC-SOFTENG Master of Software Engineering
- MC-ENG Master of Engineering
- 100pt Program course entry point in the MC-IS Master of Information Systems, 150pt Program course entry point in the MC-IS Master of Information Systems
- 100pt Program course entry point in the MC-IT Master of Information Technology, 150pt Program course entry point in the MC-IT Master of Information Technology
- MC-SCICMP Master of Science (Computer Science)
- MC-CS Master of Computer Science
- MC-DATASC Master of Data Science
Corequisites
None
Non-allowed subjects
None
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: 4 March 2025
Assessment
| Description | Timing | Percentage |
|---|---|---|
Individual Cluster Computing Assignment, requiring approximately 25 - 30 hours programming and 2000 word report
| 10% | |
Group-based Cloud programming assignment system, requiring approximately 50-55 hours programming and 5000 word report
| 40% | |
A written examination
| End of semester | 50% |
Additional details
Hurdle requirement: To pass the subject students must obtain at least:
- 25/50 in assignment/project work
- And 25/50 in the end-of-semester written examination.
Intended Learning Outcome (ILO) 1 is addressed in all assessment components. ILO 2 is addressed in the project work, ILO 3 in the first assignment.
Last updated: 4 March 2025
Dates & times
- Semester 1
Principal coordinator Richard Sinnott Mode of delivery On Campus (Parkville) Contact hours 36 hours, comprising one 2-hour lecture and one 1-hour tutorial per week Total time commitment 200 hours Teaching period 3 March 2025 to 1 June 2025 Last self-enrol date 14 March 2025 Census date 31 March 2025 Last date to withdraw without fail 9 May 2025 Assessment period ends 27 June 2025 Semester 1 contact information
Prof Richard Sinnott
email: rsinnott@unimelb.edu.au
Time commitment details
200 hours
What do these dates mean
Visit this webpage to find out about these key dates, including how they impact on:
- Your tuition fees, academic transcript and statements.
- And for Commonwealth Supported students, your:
- Student Learning Entitlement. This applies to all students enrolled in a Commonwealth Supported Place (CSP).
Subjects withdrawn after the census date (including up to the ‘last day to withdraw without fail’) count toward the Student Learning Entitlement.
Last updated: 4 March 2025
Further information
- Texts
- Subject notes
LEARNING AND TEACHING METHODS
The subject will be delivered through a combination of lectures, workshops and both individual and team-based learning. In team-based learning, groups of students will jointly develop Cloud-based big data processing applications.
INDICATIVE KEY LEARNING RESOURCES
Students will have access to lecture notes and slides. The subject LMS site also contains links to recommended literature and current survey papers of cluster and cloud computing principles. Demonstrations of the technologies covered in the course will be presented in the workshops.
CAREERS / INDUSTRY LINKS
Adoption of the technologies taught in this subject, and in particular cloud computing, is growing quickly. The vast majority of major organisations in the ICT market offer now utilise Cloud based solutions. Therefore, there are many opportunities for professionals that understand these technologies and are able to develop applications that can scale up/down on the Cloud. Examples of companies playing a major role in Cloud computing area include: Amazon, IBM, Microsoft, Google, Oracle, CA, VMWare, and Citrix amongst many others. The course also covers big data technologies and security - both of which are in great demand in industry at present. - Related Handbook entries
This subject contributes to the following:
Type Name Course Master of Science (Computer Science) Course Master of Data Science Course Ph.D.- Engineering Course Doctor of Philosophy - Engineering Course Master of Philosophy - Engineering Specialisation (formal) Software Specialisation (formal) Mechatronics - 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.
Please note Single Subject Studies via Community Access Program is not available to student visa holders or applicants
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
Last updated: 4 March 2025