ELEC 6003 Neuromorphic Accelerators
Credit Points 10
Legacy Code 800231
Coordinator Mark Wang Opens in new window
Description Problem-oriented thinking and distributed system design are essential for neuromorphic engineers. This subject is designed to provide students with sufficient understanding to neuromorphic processor. Students will be able to implement spiking neural networks by programming neuromorphic processors The lab work and programming assignments focus on different key aspects of programming neuromorphic processor: Neural modelling, Python programming, debugging code and hardware/software co-simulation. The workshops focus on the concrete implementation of neural networks.
School Graduate Research School
Discipline Electronic Engineering
Student Contribution Band HECS Band 2 10cp
Check your fees via the Fees page.
Level Postgraduate Coursework Level 6 subject
Restrictions Must be enrolled in 8124 Master of Applied Neuromorphic Engineering
Assumed Knowledge
Proficient in Python, basic in neural computing, basic in spiking neural networks.
Learning Outcomes
- Design Spiking Neural Networks (SNNs) systems for efficient on-chip computing
- Implement SNNs using the Neuromorphic Processors�f programming framework
- Critically appraise novel solutions for efficient neural network systems
- Effectively communicate the significance and impact of neuromorphic processors to non-specialist audience
- Accurately compile professional lab reports detailing the methodology employed in implementing the SNN architecture
Subject Content
- Parallel computing
- Differences between Neuromorphic Accelerator architectures and conventional von-Neumann architecture
* Features of Spiking Neural Networks
- Difference between Spiking Neural Networks and conventional numerical computing systems
* Programming frameworks of Neuromorphic processors
Assessment
The following table summarises the standard assessment tasks for this subject. Please note this is a guide only. Assessment tasks are regularly updated, where there is a difference your Learning Guide takes precedence.
| Type | Length | Percent | Threshold | Individual/Group Task | Mandatory |
|---|---|---|---|---|---|
| Practical | 1000 words | 25 | N | Individual | Y |
| Practical | 1200 words | 30 | N | Individual | Y |
| Practical | 1500 words | 30 | N | Group | Y |
| Presentation | 5 minutes | 15 | N | Individual | Y |
Teaching Periods
Spring (2024)
Parramatta City - Macquarie St
On-site
Subject Contact Mark Wang Opens in new window
View timetable Opens in new window
Spring (2025)
Parramatta City - Macquarie St
On-site
Subject Contact Mark Wang Opens in new window