Parallel and Multicore Computing

This subject is not offered in 2014.

200 hours

Knowledge of Operating Systems and Networks, and C Programming.

None

C programming and UNIX familiarity.

None

For the purposes of considering request for Reasonable Adjustments under the Disability Standards for Education (Cwth 2005), and Student Support and Engagement Policy, academic requirements for this subject are articulated in the Subject Overview, Learning Outcomes, Assessment and Generic Skills sections of this entry.

It is University policy to take all reasonable steps to minimise the impact of disability upon academic study, and reasonable adjustments will be made to enhance a student's participation in the University's programs. Students who feel their disability may impact on meeting the requirements of this subject are encouraged to discuss this matter with a Faculty Student Adviser and Student Equity and Disability Support: http://services.unimelb.edu.au/disability

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 (ILO)

On completion of this subject the student is expected to:

1. Have an understanding of parallel algorithms, analysis and architectures
2. Obtain experience developing parallel algorithms for various parallel architectures

• Intended Learning Outcomes (ILOs) 1 and 2 are addressed by extensive Project work of approximately 60 hours (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

None

This subject is not available as a breadth subject.

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

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.