Module COMP3371: COMPUTING METHODOLOGIES III

Department: Computer Science

COMP3371: COMPUTING METHODOLOGIES III

Prerequisites

• Software methodologies and Networks and Systems

Corequisites

• None

Excluded Combination of Modules

• None

Aims

• To familiarise the students with major areas of computing, giving them an in-depth knowledge of the underlying theory, the prevailing methodologies and key industrial applications.

Content

• Themes will be chosen from areas including the following:
• Parallel Programming: Approaches to exploiting multiple processing units to obtain the greatest performance for solving large-scale computational problems both in shared memory and distributed parallel computing.
• Fundamentals of numerical algorithms (including error and stability analysis, integration, and spatial discretisations) used to solve a wide range of problems in science and engineering.
• Distributed Computing: methods for coordinating actions of a collection of individual computing devices in order to perform one large task, which include message passing algorithms, leader election algorithms, and access control of shared memory.
• Theory and algorithms for the Linear and Integer Programming methodology for modeling and solving a large variety of optimisation problems arising in many practical applications.

Learning Outcomes

• An understanding of fundamental principles underlining some of the most important computing methodologies
• An understanding of the main problems arising in these areas and their solutions
• A knowledge and appreciation of some of the research related issues in these areas, including current practices, recent developments and further areas for possible exploration.

• The ability to use common methodologies to solve applied computing problems
• An ability to critically evaluate how the subject knowledge could be used in various applications

• On completion of the module, students will be able to demonstrate:
• an ability to solve problems
• an ability to learn independently
• an ability to communicate technical information.

Modes of Teaching, Learning and Assessment and how these contribute to the learning outcomes of the module

• Lectures enable students to learn core material in the different subject areas.
• Problem classes enable students to apply the material learned in lectures and enhance their understanding.
• Formative and summative assignments encourage and guide independent study.
• Summative examinations test the knowledge acquired and the students' ability to use this knowledge to solve problems.

Teaching Methods and Learning Hours

Summative Assessment

Formative Assessment:

Example formative exercises given during the course. Additional revison lectures may be arranged in the modules lecture slots in the 3rd term.

■ Attendance at all activities marked with this symbol will be monitored. Students who fail to attend these activities, or to complete the summative or formative assessment specified above, will be subject to the procedures defined in the University's General Regulation V, and may be required to leave the University