Outline

Overview

This unit of study explores the design of a computer system at the architectural and digital logic level. Topics covered include instruction sets, computer arithmetic, performance evaluation, datapath design, pipelining, memory hierarchies including caches and virtual memory, I/O devices, and bus-based I/O systems. Students will design a pipelined reduced instruction set processor.

Unit details and rules

Academic unit	School of Electrical and Computer Engineering
Credit points	6
Prerequisites ?	None
Corequisites ?	None
Prohibitions ?	None
Assumed knowledge ?	ELEC9602. Knowledge of digital logic (logic operations, theorems and Boolean algebra, number systems, combinational logic analysis and synthesis, sequential logic, registers, counters, bus systems, state machines, design of a simple computer, and using hardware description languages such as VHDL or Verilog) is required. ELEC9607. Knowledge of microprocessor systems (embedded systems architecture, design methodology, interfacing and programming) is required
Available to study abroad and exchange students	No

Teaching staff

Coordinator	Philip Leong, philip.leong@sydney.edu.au
Lecturer(s)	Philip Leong, philip.leong@sydney.edu.au

Type	Description	Weight	Due	Length
Final exam (Take-home extended release)	Final exam Practical design of a CPU	60%	Formal exam period	48 hours
Outcomes assessed:
Skills-based evaluation	Lab 1 - ALU Implement an arithmetic logic unit (ALU).	1.25%	Week 02	2 hours
Outcomes assessed:
Skills-based evaluation	Lab 2 - Arithmetic Instructions (R and I-format) Implement register and immediate instructions for a single cycle CPU.	1.25%	Week 03	2 hours
Outcomes assessed:
Skills-based evaluation	Lab 3 - Load and Store Implement load and store instructions for a single cycle processor.	1.25%	Week 04	2 hours
Outcomes assessed:
Skills-based evaluation	Lab 4 - Branch and jump instructions Implement operational single cycle processor including branch instructions.	1.25%	Week 05	2 hours
Outcomes assessed:
Skills-based evaluation	Lab 5 - Pipelined Processor Modify single cycle processor to be pipelined.	1.25%	Week 06	2 hours
Outcomes assessed:
Skills-based evaluation	Lab 6 - Assembly language Practise assembly language programming and learn about simulator.	1.25%	Week 07	2 hours
Outcomes assessed:
Skills-based evaluation	Lab7 - Caches Cache simulation experiment.	1.25%	Week 09	2 hours
Outcomes assessed:
Assignment	Design exercise Practical design of a CPU	30%	Week 10 Due date: 16 Oct 2022 at 23:59	n/a
Outcomes assessed:
Skills-based evaluation	Lab8 - Matrix Multiplication Optimisation of matrix multiplier.	1.25%	Week 12	2 hours
Outcomes assessed:
= group assignment ? = Type E final exam ?

Assessment summary

Labs: cover basic theory for course, prelabs must be completed prior to lab session.
Assignment: design project.
Final exam: take home open book.

Detailed information for each assessment can be found on Canvas.

Assessment criteria

The University awards common result grades, set out in the Coursework Policy 2014 (Schedule 1).

As a general guide, a high distinction indicates work of an exceptional standard, a distinction a very high standard, a credit a good standard, and a pass an acceptable standard.

Result name	Mark range	Description
High distinction	85 - 100
Distinction	75 - 84
Credit	65 - 74
Pass	50 - 64
Fail	0 - 49	When you don’t meet the learning outcomes of the unit to a satisfactory standard.

For more information see guide to grades.

Late submission

In accordance with University policy, these penalties apply when written work is submitted after 11:59pm on the due date:

Deduction of 5% of the maximum mark for each calendar day after the due date.
After ten calendar days late, a mark of zero will be awarded.

This unit has an exception to the standard University policy or supplementary information has been provided by the unit coordinator. This information is displayed below:

5 percent per day.

Academic integrity

The Current Student website provides information on academic integrity and the resources available to all students. The University expects students and staff to act ethically and honestly and will treat all allegations of academic integrity breaches seriously.

We use similarity detection software to detect potential instances of plagiarism or other forms of academic integrity breach. If such matches indicate evidence of plagiarism or other forms of academic integrity breaches, your teacher is required to report your work for further investigation.

Use of generative artificial intelligence (AI) and automated writing tools

You may only use generative AI and automated writing tools in assessment tasks if you are permitted to by your unit coordinator. If you do use these tools, you must acknowledge this in your work, either in a footnote or an acknowledgement section. The assessment instructions or unit outline will give guidance of the types of tools that are permitted and how the tools should be used.

Your final submitted work must be your own, original work. You must acknowledge any use of generative AI tools that have been used in the assessment, and any material that forms part of your submission must be appropriately referenced. For guidance on how to acknowledge the use of AI, please refer to the AI in Education Canvas site.

The unapproved use of these tools or unacknowledged use will be considered a breach of the Academic Integrity Policy and penalties may apply.

Studiosity is permitted unless otherwise indicated by the unit coordinator. The use of this service must be acknowledged in your submission as detailed on the Learning Hub’s Canvas page.

Outside assessment tasks, generative AI tools may be used to support your learning. The AI in Education Canvas site contains a number of productive ways that students are using AI to improve their learning.

Learning support

Simple extensions

If you encounter a problem submitting your work on time, you may be able to apply for an extension of five calendar days through a simple extension.  The application process will be different depending on the type of assessment and extensions cannot be granted for some assessment types like exams.

Special consideration

If exceptional circumstances mean you can’t complete an assessment, you need consideration for a longer period of time, or if you have essential commitments which impact your performance in an assessment, you may be eligible for special consideration or special arrangements.

Special consideration applications will not be affected by a simple extension application.

Using AI responsibly

Co-created with students, AI in Education includes lots of helpful examples of how students use generative AI tools to support their learning. It explains how generative AI works, the different tools available and how to use them responsibly and productively.

Weekly schedule

WK	Topic	Learning activity
Week 01	Performance	Lecture (5 hr)
Week 02	Instruction set architecture	Lecture and tutorial (5 hr)
Week 03	Hardware description languages	Lecture and tutorial (5 hr)
Week 04	Single cycle processor	Lecture and tutorial (5 hr)
Week 05	Single cycle processor (ctd)	Lecture and tutorial (5 hr)
Week 06	Pipelining	Lecture and tutorial (5 hr)
Week 07	Pipelining (ctd)	Lecture and tutorial (5 hr)
Week 08	Memory systems	Lecture and tutorial (5 hr)
Week 09	Memory hierarchy	Lecture and tutorial (5 hr)
Week 10	Virtual memory	Lecture and tutorial (5 hr)
Week 11	Case study	Lecture and tutorial (5 hr)
Week 12	Case study (ctd)	Lecture and tutorial (5 hr)
Week 13	Summary	Lecture and tutorial (5 hr)

Study commitment

Typically, there is a minimum expectation of 1.5-2 hours of student effort per week per credit point for units of study offered over a full semester. For a 6 credit point unit, this equates to roughly 120-150 hours of student effort in total.

Required readings

All readings for this unit can be accessed through the Library eReserve, available on Canvas.

David Patterson and John Hennessy, Computer Organization and Design RISC-V Edition, 2nd Edition, ISBN 978-0-12-820331-6 Morgan Kaufmann, Dec 2020.

Learning outcomes

Learning outcomes are what students know, understand and are able to do on completion of a unit of study. They are aligned with the University's graduate qualities and are assessed as part of the curriculum.

Outcomes
Graduate qualities

At the completion of this unit, you should be able to:

LO1. Understand the literature in computer architecture design
LO2. Develop communication skills through the assignment
LO3. Work in teams through assignments and deal with project managements issues of completing a design exercise
LO4. Understand how economic issues affect computer designers
LO5. Design a pipelined RISC processor with memory hierarchy
LO6. Critically evaluate different pipelining schemes, memory designs and instruction sets
LO7. Model and benchmark the performance of different computer architectures.

Graduate qualities

The graduate qualities are the qualities and skills that all University of Sydney graduates must demonstrate on successful completion of an award course. As a future Sydney graduate, the set of qualities have been designed to equip you for the contemporary world.

GQ1	Depth of disciplinary expertise Deep disciplinary expertise is the ability to integrate and rigorously apply knowledge, understanding and skills of a recognised discipline defined by scholarly activity, as well as familiarity with evolving practice of the discipline.
GQ2	Critical thinking and problem solving Critical thinking and problem solving are the questioning of ideas, evidence and assumptions in order to propose and evaluate hypotheses or alternative arguments before formulating a conclusion or a solution to an identified problem.
GQ3	Oral and written communication Effective communication, in both oral and written form, is the clear exchange of meaning in a manner that is appropriate to audience and context.
GQ4	Information and digital literacy Information and digital literacy is the ability to locate, interpret, evaluate, manage, adapt, integrate, create and convey information using appropriate resources, tools and strategies.
GQ5	Inventiveness Generating novel ideas and solutions.
GQ6	Cultural competence Cultural Competence is the ability to actively, ethically, respectfully, and successfully engage across and between cultures. In the Australian context, this includes and celebrates Aboriginal and Torres Strait Islander cultures, knowledge systems, and a mature understanding of contemporary issues.
GQ7	Interdisciplinary effectiveness Interdisciplinary effectiveness is the integration and synthesis of multiple viewpoints and practices, working effectively across disciplinary boundaries.
GQ8	Integrated professional, ethical, and personal identity An integrated professional, ethical and personal identity is understanding the interaction between one’s personal and professional selves in an ethical context.
GQ9	Influence Engaging others in a process, idea or vision.

Outcome map

Learning outcomes	Graduate qualities
Learning outcomes

Responding to student feedback

This section outlines changes made to this unit following staff and student reviews.

Minor tidying up of inconsistencies

Disclaimer

The University reserves the right to amend units of study or no longer offer certain units, including where there are low enrolment numbers.

To help you understand common terms that we use at the University, we offer an online glossary.

Current students

Overview

Overview

Unit details and rules

Teaching staff

Assessment

Assessment

Assessment summary

Assessment criteria

Late submission

Academic integrity

Learning support

Learning support

Simple extensions

Special consideration

Using AI responsibly

Weekly schedule

Weekly schedule

Study commitment

Required readings

Learning outcomes

Learning outcomes

Graduate qualities

Outcome map

Responding to student feedback

Responding to student feedback

Disclaimer

On this page

Useful links

ELEC9608: Computer Architecture

Semester 2, 2022 [Normal day] - Remote

Overview

Overview

Unit details and rules

Teaching staff

Assessment

Assessment

Assessment summary

Assessment criteria

Late submission

Academic integrity

Learning support

Learning support

Simple extensions

Special consideration

Using AI responsibly

Weekly schedule

Weekly schedule

Study commitment

Required readings

Learning outcomes

Learning outcomes

Graduate qualities

Outcome map

Responding to student feedback

Responding to student feedback

Disclaimer

On this page

Useful links