Units / FIT3143
FIT3143 · Parallel computing
2026 Handbook6 credit pointsLevel 3Faculty of Information Technology
Last checked: 22 Aug 2026 UTCOverview
Modern computer systems contain parallelism in both hardware and software. This unit covers parallelism in both general purpose and application specific computer architectures and the programming paradigms that allow parallelism to be exploited in software. The unit examines shared memory and message passing paradigms in hardware and software; concurrency, multithreading and synchronicity; parallel, clustered and distributed supercomputing algorithms, languages and software tools and development environments. You will learn to design and develop parallel algorithms in these paradigms, and apply technical writing and presentation to communicate parallel computing.
Areas of study: Advanced computer science
Offerings
| Campus | Teaching period | Mode |
|---|---|---|
| Clayton | Second semester | Teaching activities are on-campus (ON-CAMPUS) |
| Malaysia | Second semester | Teaching activities are on-campus (ON-CAMPUS) |
Assessment
The Handbook does not list a final examination among the assessment items. That is not a guarantee there is none.
| # | Assessment | Type | Weight | Hurdle |
|---|---|---|---|---|
| 1 | Laboratories | Demonstration | 30% | — |
| 2 | Applied Sessions | Demonstration | 20% | — |
| 3 | Applied Problem Solving Tasks (Quiz) | Quiz / Test | 50% | — |
Assessment details may change. Please refer to the assessment information in Moodle closer to the start of the teaching period.
Requisites
prerequisite
- FIT2004 — Algorithms and data structures
Learning outcomes
- Examine the design principles of parallel computing architectures;
- Evaluate and contrast different types of parallel architectures using Flynn's taxonomy;
- Analyse the design principles of distributed parallel computing systems;
- Criticise and assess common performance models used for parallel applications;
- Research and solve synchronisation problems typical in the design of parallel applications;
- Compare the fundamental principles of parallel hardware using vector processing, Graphics Processing Units (GPU) and Neural Processing Units (NPU);
- Judge modern parallel computing applications and the impact of exponential growth in hardware
Workload
This unit has a requirement of 1-2 hours per week of asynchronous learning. Minimum total expected workload to achieve the learning outcomes for this unit is 144 hours per semester typically comprising a mixture of scheduled online and face to face learning activities and independent study. Independent study may include associated reading and preparation for scheduled teaching activities.
| Activity | Duration |
|---|---|
| Laboratories | 12 hours |
| Applied sessions | 12 hours |
| Workshops | 24 hours |
Ask about FIT3143
Answered from the Handbook fields above - no AI, no guessing. Every answer links back to the source.
Community discussions about FIT3143
CommunityStudent experience, not official rules. Nothing here changes what the Handbook says.