COMPSCI 711 : Parallel and Distributed Computing
Science
2020 Semester Two (1205) (15 POINTS)
Course Prescription
Course Overview
This course is for students who:
1. are familiar with modern multi-paradigm software development, as taught in COMPSCI 335 (and its prerequisites) - or are willing to invest more time to catch-up missing parts by individual study;
2. are interested in algorithmic aspects of distributed computing (with brief incursions in modern parallel and cloud computing).
This course completes your skills palette with theoretical concepts related to distributed computing, supported by practical work. It also lays the ground for further postgraduate study and research.
We also suggest COMPSCI 734, as a good companion complementary course.
Capabilities Developed in this Course
| Capability 1: | Disciplinary Knowledge and Practice |
| Capability 2: | Critical Thinking |
| Capability 3: | Solution Seeking |
| Capability 4: | Communication and Engagement |
| Capability 5: | Independence and Integrity |
Learning Outcomes
- Analyse and evaluate problems and draw on the theoretical and technical knowledge to develop parallel and distributed solutions (Capability 1, 2, 3, 4 and 5)
- Describe and discuss the main models of distributed systems - synchronous vs asynchronous - their runtime complexity measures and why these matter (Capability 1, 2, 3 and 4)
- Describe and explain the complexity of distributed searches under different distributed models (Capability 1, 2, 3 and 4)
- Correctly use different ways in representing orders in distributed systems and the complexity of different approaches (Capability 1, 2, 3 and 4)
- Discuss and evaluate the algorithmic complexity in capturing the states of distributed systems (Capability 1, 2, 3 and 4)
- Describe and discuss the problems and algorithms for reaching consensus in distributed systems and its applications (Capability 1, 2, 3 and 4)
- Discuss and critically evaluate the additional complexity and theoretical limits imposed by the system distribution (Capability 1, 2, 3 and 4)
- Explain and apply algorithms for detecting distributed termination and failures (Capability 1, 2, 3 and 4)
Assessments
| Assessment Type | Percentage | Classification |
|---|---|---|
| Assignments | 30% | Individual Coursework |
| Project | 30% | Individual Coursework |
| Final Exam | 40% | Individual Examination |
| 3 types | 100% |
| Assessment Type | Learning Outcome Addressed | |||||||||
|---|---|---|---|---|---|---|---|---|---|---|
| 1 | 2 | 3 | 4 | 5 | 6 | 7 | 8 | |||
| Assignments | ||||||||||
| Project | ||||||||||
| Final Exam | ||||||||||
Key Topics
This course focuses on programming models, algorithms and techniques for developing distributed applications and systems. The topics typically include: parallel and distributed programming models, distributed searches, minimal spanning trees, distributed consensus (e.g. Byzantine agreement), the CAP theorem, logical time, distributed snapshots, failure detection, deadlock detection, termination detection, serverless cloud computing.
Learning Resources
- Lynch, Nancy (1996). Distributed Algorithms. San Francisco, CA: Morgan Kaufmann Publishers.
- Tel, Gerard (2000), Introduction to Distributed Algorithms, Cambridge University Press, Second Edition.
- Wan Fokkink (2013), Distributed Algorithms - An Intuitive Approach, MIT Press (Second Edition 2018 also available).
Workload Expectations
This course is a standard 15 point course and students are expected to spend 10 hours per week involved in each 15 point course that they are enrolled in.
For this course, you can expect 3 hours of lectures, a 1 hour tutorial, 1-6 hours of reading and thinking about the content and 1-6 hours of work on assignments and/or test preparation.
This estimation assumes students who have obtained good grades in the recommended preparation (335). Interested students who did not sat this course are also very welcome, but may or may not need to put a bit more effort.
Digital Resources
Course materials are made available in a learning and collaboration tool called Canvas which also includes reading lists and lecture recordings (where available).
Please remember that the recording of any class on a personal device requires the permission of the instructor.
Copyright
The content and delivery of content in this course are protected by copyright. Material belonging to others may have been used in this course and copied by and solely for the educational purposes of the University under license.
You may copy the course content for the purposes of private study or research, but you may not upload onto any third party site, make a further copy or sell, alter or further reproduce or distribute any part of the course content to another person.
Academic Integrity
The University of Auckland will not tolerate cheating, or assisting others to cheat, and views cheating in coursework as a serious academic offence. The work that a student submits for grading must be the student's own work, reflecting their learning. Where work from other sources is used, it must be properly acknowledged and referenced. This requirement also applies to sources on the internet. A student's assessed work may be reviewed against online source material using computerised detection mechanisms.
Inclusive Learning
All students are asked to discuss any impairment related requirements privately, face to face and/or in written form with the course coordinator, lecturer or tutor.
Student Disability Services also provides support for students with a wide range of impairments, both visible and invisible, to succeed and excel at the University. For more information and contact details, please visit the Student Disability Services’ website at http://disability.auckland.ac.nz
Special Circumstances
If your ability to complete assessed coursework is affected by illness or other personal circumstances outside of your control, contact a member of teaching staff as soon as possible before the assessment is due.
If your personal circumstances significantly affect your performance, or preparation, for an exam or eligible written test, refer to the University’s aegrotat or compassionate consideration page: https://www.auckland.ac.nz/en/students/academic-information/exams-and-final-results/during-exams/aegrotat-and-compassionate-consideration.html.
This should be done as soon as possible and no later than seven days after the affected test or exam date.
Student Feedback
During the course Class Representatives in each class can take feedback to the staff responsible for the course and staff-student consultative committees.
At the end of the course students will be invited to give feedback on the course and teaching through a tool called SET or Qualtrics. The lecturers and course co-ordinators will consider all feedback.
Your feedback helps to improve the course and its delivery for all students.
Student Charter and Responsibilities
The Student Charter assumes and acknowledges that students are active participants in the learning process and that they have responsibilities to the institution and the international community of scholars. The University expects that students will act at all times in a way that demonstrates respect for the rights of other students and staff so that the learning environment is both safe and productive. For further information visit Student Charter (https://www.auckland.ac.nz/en/students/forms-policies-and-guidelines/student-policies-and-guidelines/student-charter.html).
Disclaimer
Elements of this outline may be subject to change. The latest information about the course will be available for enrolled students in Canvas.
In this course you may be asked to submit your coursework assessments digitally. The University reserves the right to conduct scheduled tests and examinations for this course online or through the use of computers or other electronic devices. Where tests or examinations are conducted online remote invigilation arrangements may be used. The final decision on the completion mode for a test or examination, and remote invigilation arrangements where applicable, will be advised to students at least 10 days prior to the scheduled date of the assessment, or in the case of an examination when the examination timetable is published.