Postgraduate Programme and Module Handbook 2025-2026
Module COMP53015: Advanced Computer Systems
Department: Computer Science
COMP53015: Advanced Computer Systems
Type | Tied | Level | 5 | Credits | 15 | Availability | Not available in 2025/2026 | Module Cap | None. |
---|
Tied to | G5T609 |
---|---|
Tied to | G5T709 |
Prerequisites
- None
Corequisites
- None
Excluded Combination of Modules
- None
Aims
- To develop a systematic understanding of current hardware architectures, their interplay with programming models, system programs and application performance tuning.
- To appreciate how performance of computer systems are affected by their architecture and system programming.
- To develop practical skills in application development, server provisioning and orchestration in the context of large-scale computing with an intense focus on networking.
Content
- Computer architecture: processor architectures, memory systems (caches) (6L + 2P)
- High-Performance Computing Platforms and Power-Performance Analysis (6L + 2P)
- Advanced Compiler Optimisation and Hardware-Software Interfacing (6L + 2P)
- Advanced computing and networking paradigms: Cloud, edge, fog and software-defined networking (6L + 2P)
Learning Outcomes
Subject-specific Knowledge:
- By the end of this module, students should be able to demonstrate:
- an understanding of the relationship between hardware architectures and High-Level Programming Languages.
- an understanding of complex performance issues of current computers.
- an understanding of modern computing paradigms, and how to design and implement codes to perform optimally on these paradigms.
- an understanding of several networking systems used in modern computational paradigms.
Subject-specific Skills:
- By the end of this module, students should be able to demonstrate:
- an awareness of current technology, design analysis, and commercial practice and the ability to bring these together to provide innovative solutions for digital systems.
- a critical understanding of potential performance pitfalls, specific codes and skills to improve existing solutions.
Key Skills:
- By the end of this module, students should be able to demonstrate:
- a capacity for self-learning in familiar and unfamiliar situations.
- general problem-solving skills.
- familiarity with programming paradigms for modern wide-vector CPUs, and their translation to GPUs.
- familiarity with modern network based computational models.
Modes of Teaching, Learning and Assessment and how these contribute to the learning outcomes of the module
- Lectures enable students to learn the core material relevant to the topic and computer classes enable students to apply their learning to practical examples.
- The summative assessment and formative exercises encourage students to focus their ability to independently analyse and solve problems.
Teaching Methods and Learning Hours
Activity | Number | Frequency | Duration | Total/Hours | |
---|---|---|---|---|---|
Lectures | 9 | 1 per week | 2 hours | 18 | |
Lectures | 8 | 1 per week | 1 hour | 8 | |
Computer Classes | 8 | 1 per week | 1 hour | 8 | |
Preparation and Reading | 116 | ||||
Total | 150 |
Summative Assessment
Component: Coursework | Component Weighting: 100% | ||
---|---|---|---|
Element | Length / duration | Element Weighting | Resit Opportunity |
General Test | 100% |
Formative Assessment:
Via computer classes
■ 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