Courses Offered

COMP3358 Distributed and Parallel Computing

2025-26

Instructor(s):

Cui H.M.

(Class A)

No. of credit(s):

Recommended Learning Hours:

Lecture:	26.0
Tutorial:	13.0

Pre-requisite(s):

COMP3230 or COMP3234

Co-requisite(s):

Mutually exclusive with:

Remarks:

Course Learning Outcomes

1.	[Distributed and Parallel Computing Concepts] Students are able to apply distributed and parallel computing concepts, to make correct conceptual choices, and to design software architectures for solving real-world problems.
2.	[Distributed Fault-tolerant Architectures] Students are able to design and implement distributed software architectures that are efficient and fault-tolerant, and to deploy them on modern clouds.
3.	[Parallel Computing Architectures] Students are able to design and implement parallel software architectures to process the drastically increasing amount of data in an efficient, scalable, and fault-tolerant manner.

Mapping from Course Learning Outcomes to Programme Learning Outcomes
	PLO a	PLO b	PLO c	PLO d	PLO g	PLO j
CLO 1	T,P	T,P	T,P
CLO 2			T,P	T,P	T,P	T,P
CLO 3			T,P	T,P	T,P	T,P

T - Teach, P - Practice
For BEng(CompSc) Programme Learning Outcomes, please refer to here.

Syllabus

Calendar Entry:
This course introduces the basic concepts and modern software architectures on distributed and parallel computing. Topics include: computer network primitives, distributed transactions and two-phase commits, webservices, parallelism and scalability models, distributed consistency models, distributed fault-tolerance, actor and monads, Facebook photo cache, Amazon key-value stores, Google Map-reduce, Spark, and TensorFlow.

Detailed Description:

Distributed and Parallel Computing Concepts	Mapped to CLOs
Computer network primitives (remote procedure calls and message queues)	1
Distributed transactions, ACID, and two-phase commits	1
Amdahl’s laws, strong and weak consistency models	1
Actors and monads	1
Distributed Fault-tolerant Architectures	Mapped to CLOs
Distributed consensus algorithms and architectures	2
Distributed virtual machine primary-backup algorithms and architectures	2
Amazon EC2 clouds and DynamoDB stores	2
Webservices	2
Parallel Computing Architectures	Mapped to CLOs
Facebook photo cache	3
Map-reduce paradigm and Hadoop	3
Spark	3
TensorFlow	3

Assessment:
Continuous Assessment: 50%
Written Examination: 50%

Teaching Plan

Please refer to the corresponding Moodle course.

Moodle Course(s)

Courses Offered

COMP3358 Distributed and Parallel Computing

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