Grid computing is an emerging computing paradigm. It provides the ability to perform high throughput computation by taking advantage of many computers connected through the Internet creating a virtual architecture, which is then able to distribute process execution across a parallel infrastructure. Grids perform computation on large data sets, by breaking them down into many smaller ones, or execute many more computations than would be possible on a single computer. The course will provide a comprehensive and systematic understanding of the issues, technologies and processes applicable to cluster and grid computing. It will enable the selection and application of appropriate tools, techniques and methodologies for the successful design and implementation of complex and novel cluster and grid computing applications and systems. The course will foster critical evaluation of academic research and industrial practice.
You will learn parallel programming paradigms and implementation methods used in cluster and grid computing applications. You will be exposed to cluster computing platforms and solutions to study, firstly, how to install, configure and manage computer clusters and, secondly, how to apply high-performance parallel computing using cluster architectures and models based on the latest technologies such as Beowulf and Boinc. You will also learn how to design, develop and install grid-based applications using graphical development and execution environment, such as P-GRADE and latest grid software, such as Condor-G and Globus.
- Cluster Computing
- Grid Computing
- High-Performance Parallel Computing
- Research Methods
- Software Engineering Project
- Introduction to Mobile Computing
- Semantic Web
- Web Services
Teaching and Assessment
Teaching involves a variety of approaches, including coursework, to improve your analytical and problem solving skills, usage of industry standard software tools, presentation and academic writing as part of the assignments (through which transferable skills are developed), group work, and research methods involving the use of library and Internet sources to develop your research and analysis skills. Taught modules may be assessed entirely through coursework or exams at the end of the academic year.
Graduates will find employment as consultants or developers in organisations operating in business and industry having compute- and/or data-intensive applications, for example in bioscience, engineering, finance etc. They will be expected to work as developers of cluster and grid-based applications.