Use the Tab and Up, Down arrow keys to select menu items.
This course combines software engineering practice for embedded systems with advanced computer architectures and memory systems. The first part considers software design principles and practices relevant to embedded software, including software architecture, concurrency, real-time operating systems, design patterns, and testing. The second part considers topics on high-performance computing, including pipelining, out of order execution, cache-memory systems, virtual memory systems, profiling, optimisation, GPUs, and quantum computing.
The goal of this course is to learn about what makes advanced computers "tick", from both hardware and software development perspectives. The embedded systems courses you've taken so far have mostly focused on the basics of creating small programs and the details of low-level hardware interactions. In this course, we'll look at how to design and implement more complex, large-scale programs, and how to improve the quality and reliability of your programs. We also look at execution architectures, such as superscalar CPUs and GPUs, and how virtual memory architectures and cache architectures operate.
At the conclusion of this course you should be able to:LO1: Specify, design, and implement complex embedded software using an efficient, principled approach. (WA1, WA2, WA3, WA4, WA5, WA6)LO2: Design and implement robust concurrent and real-time applications. (WA3, WA4, WA5)LO3: Select and apply analysis and testing techniques that will help to ensure design and implementation quality. (WA1, WA2, WA4, WA5, WA6)LO4: Use appropriate tools and techniques to manage and communicate within and work on large software projects that involve more than one developer. (WA8, WA9, WA10)LO5: Develop an advanced knowledge on a subsystem of modern microprocessors. (WA1, WA2, WA4, WA5, WA8, WA9)
This course will provide students with an opportunity to develop the Graduate Attributes specified below:
Critically competent in a core academic discipline of their award
Students know and can critically evaluate and, where applicable, apply this knowledge to topics/issues within their majoring subject.
Employable, innovative and enterprising
Students will develop key skills and attributes sought by employers that can be used in a range of applications.
Globally aware
Students will comprehend the influence of global conditions on their discipline and will be competent in engaging with global and multi-cultural contexts.
ENCE361
Students must attend one activity from each section.
Michael Hayes
Allan McInnes and Fredy Youssif
Artificial Intelligence Tools The use of Artificial Intelligence (AI) tools for each of the assessments in ENCE464 is summarised below. Students are always responsible for the accuracy of the submitted work, regardless of which tools are used. Assessment Item and Permitted use of AI Assignment 1: Generative AI Tools Are Not Restricted for This Assessment. Assignment 2: Generative AI Tools Are Not Restricted for This Assessment. Exam: Generative AI Tools cannot be used for This Assessment.In the assignment assessments, you are permitted to use generative artificial intelligence (AI) to assist you in any way within the bounds of academic integrity. You must appropriately acknowledge any use of generative AI in your work. Please include a Statement of AI use (if no AI tool has been used, then this must also be stated) at the start of the document clearly indicating which AI tools were used and how they contributed to your assessment.
Scaling of marks In order to maintain consistency across courses and fairness for students, scaling of raw marks occurs. In the Faculty of Engineering, target course GPAs are calculated based on the performance of the cohort of students in their courses in the previous year. Scaling of the raw total course marks is normally performed so that when converted to grades (using UC Grade Scale) the outgoing GPA is in line with the target GPA for a course. Scaling up or down can occur. The Grading Scale for the University: https://www.canterbury.ac.nz/study/study-support-info/study-related-topics/grading-scale Assessment Completion Students must engage satisfactorily in all required course-related assessments in order to be eligible to pass the course as defined in the General Conditions for Credit Regulations 3(a).
Lateness Penalties For Assignments, a lateness penalty of 10% (in absolute terms) per day or part day late will be deducted from the original mark. For example, an assignment deliverable with a nominal mark of 83% submitted 0-24 hours late will receive a mark of 73%, and submitted 24-48 hours late will receive 63%.
Contact HoursLectures: 36 hoursTutorials: 0 hoursWorkshops: 0 hoursLaboratories: 22 hours Independent studyReview of lectures: 10 hoursTest and exam preparation: 20 hoursAssignments: 62 hours Total 150 hours
Domestic fee $1,344.00
International fee $6,488.00
* All fees are inclusive of NZ GST or any equivalent overseas tax, and do not include any programme level discount or additional course-related expenses.
For further information see Electrical and Computer Engineering .