Sub-categories
COMP60900: MSc Dissertation Area
Project Supervision

  • Today's highest performance computers embody substantial amounts of parallel hardware, to the extent that the latest generation of machines harness the power of thousands of cooperating processors. The programming of such highly parallel hardware has proved to be difficult: progress has been slow and achieved mostly by "trial-and-error".
    This course unit studies the base technologies for High Performance Computing and allows ``hands-on'' experience of a state-of-the-art parallel computer to be gained. The course unit explores, through a combination of directed reading, lectures, group-based laboratories and a group-based mini-project, a framework for the development, analysis and performance tuning of parallel algorithms for the solution of numerical problems.



  • This course covers the design of low-power embedded systems based around the ARM 32-bit microprocessor core. It will be taught primarily through self-study on-line material, supported by seminars and practical exercises.


  • The aim of this course unit is to provide understanding of concepts underlying current developments in mobile communication systems and wireless computer networks.

  • This unit will give students a foundation in the subject of machine vision. This will involve gaining familiarity with algorithms for low-level and intermediate-level processing and considering the organisation of practical systems. Particular emphasis will be placed on the importance of representation in making explicit prior knowledge, control strategy and interpretting hypotheses.
    This course unit treats vision as a process of inference from noisy and uncertain data and emphasizes probabilistic and statistical approaches. As such, it will also give students a foundation in the statistical methods of image analysis.
    Topics covered in the course include perception of 3D scene structure from stereo; image filtering, smoothing, edge detection; segmentation and grouping; learning, recognition, and search; tracking and motion estimation; behaviour modelling.

  • This course unit will introduce students to a wide range of software patterns, with particular emphasis on design patterns and e-business patterns. As well as a theoretical understanding of patterns students will gain practical experience of applying them through laboratory case studies.