Cluster and Cloud Computing (COMP90024)

AIMS

The growing popularity of the Internet along with the availability of powerful computers and high-speed networks as low-cost commodity components are changing the way we do parallel and distributed computing (PDC). Cluster and Cloud Computing are two approaches for PDC. Clusters employ cost-effective commodity components for building powerful computers within local-area networks. Recently, “cloud computing” has emerged as the new paradigm for delivery of computing as services in a pay-as-you-go-model via the Internet. These approaches are used to tackle may research problems with particular focus on "big data" challenges that arise across a variety of domains.

Some examples of scientific and industrial applications that use these computing platforms are: system simulations, weather forecasting, climate prediction, automobile modelling and design, high-energy physics, movie rendering, business intelligence, big data computing, and delivering various business and consumer applications on a pay-as-you-go basis.

This subject will enable students to understand these technologies, their goals, characteristics, and limitations, and develop both middleware supporting them and scalable applications supported by these platforms.

This subject is an elective subject in the Master of Information Technology.   It can also be taken as an Advanced Elective subject in the Master of Engineering (Software).

INDICATIVE CONTENT

• Cluster computing: elements of parallel and distributed computing, cluster systems architecture, resource management and scheduling, single system image, parallel programming paradigms, cluster programming with MPI
• Utility computing: foundations and grid computing technologies
• Cloud computing: cloud platforms, Virtualization, Cloud Application Programming Models (Task, Thread, and MapReduce), Cloud applications, and future directions in utility and cloud computing
• "Big data" processing and analytics in distributed environments.