Computer Science

Parallel and Distributed Computing: COMPSCI 711 Semester 2, City Campus

NOTE: This site is always in flux (information may be inaccurate and may be amended by announcement in class and/or by class e-mail)


  • Michael J. Dinneen (lecturer,
  • Mano Manoharan (Lecturer,
  • Xinfeng Ye (coordinator and lecturer,


Advances in hardware architecture make parallel computing possible on PCs. This course focuses on programming models, algorithms and techniques for developing distributed applications and systems. The topics inlcude, parallel programming models, minimal spanning tree, Byzantine agreement, the CAP theorem, logical time, multicast, mutex, garbage collection, snapshot, deadlock detection, web caching, resource looking up in p2p system, and blockchain, etc.

Seeking Assistance

Assistance can be obtained from course lecturers during their published office hours. The School of Computer Science also has a team of support staff (see the posters around the labs for support contacts) who are happy to provide guidance on more general issues to do with your study in computer science.
Students are asked to discuss privately any impairment related requirements face-to-face and/or in written form with course convenor, lecturer or tutor.

Catching up on missed lectures

If you miss a lecture, you should catch up as soon as possible by reading the corresponding lecture notes. If you miss the deadline for an assignment and have a valid reason, you should see the relevant lecturer. If you miss the exam for any valid reason, or you sit the exam but believe that your performance was impaired for some reason, then you may be able to apply for an aegrotat, compassionate or special pass consideration.


100% Coursework (year 2021)


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