Parallel Programming

This course prepares students to explain the concepts and models of parallel computing, analyse and implement parallel algorithms on shared-memory and distributed-memory architectures, and optimise the performance of parallel programs. Study materials: Foundations of Programming Languages (FPL), Algorithmic Foundations (AL), Mathematical and Statistical Foundations (MSF), Operating Systems (OS), Networking and Communication (NC), Architecture and Organization (AR), Parallel and Distributed Computing (PDC).

Topics

1. Concepts and models of parallel computing
2. Shared-memory and distributed-memory parallel architectures
3. Shared-memory parallel programming
4. Distributed-memory parallel programming with message passing
5. Parallel algorithm design
6. Synchronisation and inter-process communication
7. Performance analysis and optimisation of parallel programs

Each course outcome derives from one programme outcome.

1. CPMK0609

   Students are able to analyse and implement parallel and distributed algorithms to improve computing performance.

   CPL06
2. CPMK-AIDE-02

   Students are able to build an applied decision basis by optimising computing performance through simultaneous processing, and apply the principles of computing ethics

   CPLP03
3. CPMK-AIDE-01

   Students are able to design and implement advanced artificial intelligence modelling to analyse diverse large-volume data through the management of structured data storage infrastructure.

   CPLP03

CPL05

Analyse and apply software engineering concepts to develop intelligent systems professionally.

CPL06

Analyse and implement fundamental concepts of mathematics, statistics, algorithms and computer systems as the foundation of computing.

CPLP03

Develop advanced artificial intelligence models and manage big data, and build applied decision support with attention to optimal performance and computing ethics.