CSCI4160 Distributed and Parallel Computing


Course code CSCI4160
Course title Distributed and Parallel Computing
Course description This course introduces concepts, models, and implementations related to distributed and parallel computing. Topics include parallel and distributed programming, system architectures, synchronization, and concurrency control techniques.
Unit(s) 3
Course level Undergraduate
Pre-requisite  CSCI3150 or ESTR3102
Exclusion  ESTR4104
Semester 1 or 2
Grading basis Graded
Grade Descriptors A/A-:  EXCELLENT – exceptionally good performance and far exceeding expectation in all or most of the course learning outcomes; demonstration of superior understanding of the subject matter, the ability to analyze problems and apply extensive knowledge, and skillful use of concepts and materials to derive proper solutions.
B+/B/B-:  GOOD – good performance in all course learning outcomes and exceeding expectation in some of them; demonstration of good understanding of the subject matter and the ability to use proper concepts and materials to solve most of the problems encountered.
C+/C/C-: FAIR – adequate performance and meeting expectation in all course learning outcomes; demonstration of adequate understanding of the subject matter and the ability to solve simple problems.
D+/D: MARGINAL – performance barely meets the expectation in the essential course learning outcomes; demonstration of partial understanding of the subject matter and the ability to solve simple problems.
F: FAILURE – performance does not meet the expectation in the essential course learning outcomes; demonstration of serious deficiencies and the need to retake the course.
Learning outcomes 1) Understand key distributed and parallel concepts including consistency, clock, commit, replication, synchronization, and consensus
2) Hands-on programming experience in distributed and parallel programming
3) Hands-on system experience in distributed systems and parallel hardware
(for reference only)
Essay test or exam: 40%
Assignments: 30%
Project: 30%
Recommended Reading List 1) Tanenbaum, Andrew, and Maarten van Steen. Distributed Systems: Principles and Paradigms. Upper Saddle River, NJ: Prentice Hall, 2002. ISBN: 9780130888938.
2) Distributed Systems: Concepts and Design (5th Edition) 5th Edition by George Coulouris (Author), Jean Dollimore (Author), Tim Kindberg (Author), Gordon Blair (Author)
3) An introduction to Parallel Programming. Peter Pacheco. Morgan Kaufmann.


CSCIN programme learning outcomes Course mapping
Upon completion of their studies, students will be able to:  
1. identify, formulate, and solve computer science problems (K/S); T
2. design, implement, test, and evaluate a computer system, component, or algorithm to meet desired needs (K/S);
3. receive the broad education necessary to understand the impact of computer science solutions in a global and societal context (K/V);
4. communicate effectively (S/V);
5. succeed in research or industry related to computer science (K/S/V);
6. have solid knowledge in computer science and engineering, including programming and languages, algorithms, theory, databases, etc. (K/S); T
7. integrate well into and contribute to the local society and the global community related to computer science (K/S/V);
8. practise high standard of professional ethics (V);
9. draw on and integrate knowledge from many related areas (K/S/V);
Remarks: K = Knowledge outcomes; S = Skills outcomes; V = Values and attitude outcomes; T = Teach; P = Practice; M = Measured