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Unit of study_

SOFT3410: Concurrency for Software Development

Semester 2, 2020 [Normal day] - Camperdown/Darlington, Sydney

The manufacturing industry has experienced a radical shift in the way they design computers, with the integration of multiple processors on the same chip. This hardware shift now requires software developers to acquire the skills that will allow them to write efficient concurrent software. Software developers used to wait for manufacturers to increase the clock frequency of their processors to see increases in the performance of their programs, the challenge is now to exploit, in the same program, more and more processing resources rather than faster processing resources. In this unit, you will learn how to tackle the problems underlying this challenge, including developing and testing concurrent programs, synchronizing resources between concurrent threads, overcoming fairness issues and guaranteeing progress, and ensuring scalability in the level of concurrency.

Unit details and rules

Unit code SOFT3410
Academic unit Computer Science
Credit points 6
Prohibitions
? 
None
Prerequisites
? 
(INFO1105 OR INFO1905) OR ((INFO1103 OR INFO1113) AND (COMP2123 OR COMP2823))
Corequisites
? 
None
Assumed knowledge
? 

None

Available to study abroad and exchange students

Yes

Teaching staff

Coordinator Shuaiwen Song, shuaiwen.song@sydney.edu.au
Tutor(s) Alan Robertson, alan.robertson@sydney.edu.au
Tyson Thomas, tyson.thomas@sydney.edu.au
Type Description Weight Due Length
Final exam (Open book) Type C final exam Final exam
Further information will be provided on canvas.
50% Formal exam period 2 hours
Outcomes assessed: LO1 LO2 LO3 LO4 LO5 LO6 LO7 LO8 LO9 LO10 LO11 LO12
Assignment Weekly homework
weekly homework
10% Multiple weeks 2 to 4 hours
Outcomes assessed: LO1 LO2 LO3 LO4 LO5 LO6 LO7 LO8 LO9 LO10 LO11
Tutorial quiz Quiz 1
The actual instruction will be given prior to the class on canvas.
5% Week 04 TBA 30 to 60mins
Outcomes assessed: LO1 LO2
Tutorial quiz Quiz 2
The detailed instruction will be given prior to the class on canvas.
5% Week 08 TBA 30 mins to 60 mins
Outcomes assessed: LO3 LO9 LO7 LO6 LO5 LO4
Assignment Assignment 1
programming and written task
10% Week 08 10 days
Outcomes assessed: LO1 LO9 LO8 LO7 LO6 LO5 LO4 LO3 LO2
Assignment Assignment 2
programming task
20% Week 12 14 days
Outcomes assessed: LO1 LO10 LO9 LO8 LO7 LO6 LO5 LO4 LO3 LO2
Type C final exam = Type C final exam ?

Assessment summary

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 sydney.edu.au/students/guide-to-grades.

The pass requirement for this course is:

  • At least 40% in final to qualify for a pass in this course, AND
  • At least 50% final mark overall
  • Any student not meeting these requirements may be given a maximum final mark of no more than 45 regardless of their average.

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:

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: Late penalty for any online assessment is 25% per day. It is a cap based penalty: 1 day late, maximum attainable mark is 75%. 2 days late, maximum attainable mark is 50%. 3 days late, maximum attainable mark is 25%. Failure to attend for any assessment that is not an assignment will award zero marks, unless special consideration is granted.

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.

You may only use artificial intelligence and writing assistance tools in assessment tasks if you are permitted to by your unit coordinator, and if you do use them, you must also acknowledge this in your work, either in a footnote or an acknowledgement section.

Studiosity is permitted for postgraduate units unless otherwise indicated by the unit coordinator. The use of this service must be acknowledged in your submission.

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.

WK Topic Learning activity Learning outcomes
Week 01 Introduction to the class and discuss performance analysis of general parallel programs Lecture and tutorial (3 hr) LO1
Week 02 C programming basics (I) Lecture and tutorial (3 hr) LO1 LO2
Week 03 C programming basics (II) Lecture and tutorial (3 hr) LO1 LO2
Week 04 Multi-core Architectures, Performance analysis for parallel programs, memory hierarchy and optimizations Lecture and tutorial (3 hr) LO1 LO2 LO3
Week 05 Process, Signals and Pipes Lecture and tutorial (3 hr) LO1 LO2 LO3 LO4
Week 06 Concurrency problems, data structures and primitives; threads and synchronization Lecture and tutorial (3 hr) LO1 LO2 LO3 LO4 LO5
Week 07 Locks and atomic operations Lecture and tutorial (3 hr) LO1 LO2 LO3 LO4 LO5 LO6 LO7 LO9
Week 08 Shared-memory multi-core programming with OpenMP (I) Lecture and tutorial (3 hr) LO1 LO2 LO3 LO4 LO6 LO7 LO8 LO10
Week 09 Shared-memory multi-core programming with OpenMP (II) Lecture and tutorial (3 hr) LO1 LO2 LO3 LO4 LO6 LO7 LO8 LO10
Week 10 Message Passing and parallel codes on distributed systems (I) Lecture and tutorial (3 hr) LO1 LO2 LO3 LO4 LO5 LO6 LO9 LO11
Week 11 Message Passing and parallel codes on distributed systems (II) Lecture and tutorial (3 hr) LO1 LO2 LO3 LO4 LO9 LO11
Week 12 Parallel design patterns and real-world usage Lecture and tutorial (3 hr) LO12

Attendance and class requirements

Students are expected to follow the weekly lectures either in-class or using the lecture recordings, and to work through the weekly tutorial material. 

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.

 

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.

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

  • LO1. Understanding the landscape of modern multi-core and many-core computer systems, real-world examples and how this class can be used in reality
  • LO2. Understanding the basic system programming, Linux, C basic programming knowledge, C system programming, C pointers and memory management, safety issues with memory management.
  • LO3. Understanding the concurrent programming fundamentals, memory hierarchy and optimisations, and contemporary multi-core hardware
  • LO4. Understanding the challenges in developing concurrent data structures and algorithms, and contemporary multi-core hardware
  • LO5. Understanding "process" in the context of concurrent and parallel programming
  • LO6. Understanding threads and synchronisation; demonstrate ability to synchronize concurrent threads
  • LO7. demonstrate ability to program using low level atomic instructions
  • LO8. understand the concept of sharing memory across concurrent executions.
  • LO9. Understanding different locks mechanism and how to use them in parallel programming
  • LO10. Understanding shared memory programming in multi-core environment, able to write safe and efficient multithreading programs using pthread and OpenMP
  • LO11. Understanding the concept of message passing in parallel programming; able to write basic parallel codes on distributed systems using message passing interface
  • LO12. Understanding parallel design patterns.

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
GQ1 GQ2 GQ3 GQ4 GQ5 GQ6 GQ7 GQ8 GQ9

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

Lectures have been updated to match more closely with the approved curriculum contents

MPORTANT: School policy relating to Academic Dishonesty and Plagiarism.

In assessing a piece of submitted work, the School of Computer Science may reproduce it entirely, may provide a copy to another member of faculty, and/or to an external plagiarism checking service or in-house computer program and may also maintain a copy of the assignment for future checking purposes and/or allow an external service to do so.

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.