This is an archived handbook for a previous year. The current undergraduate and postgraduate handbooks can be viewed using the links above.
Postgraduate Handbook 2021-2022 (archived)
Module COMP52315: Performance Engineering and Advanced Algorithms
Department: Computer Science
COMP52315: Performance Engineering and Advanced Algorithms
| Type | Level | Credits | Availability | Module Cap | Location |
|---|---|---|---|---|---|
| Tied | 5 | 15 | Available in 2021/2022 | None. | Durham |
Tied To
Pre-requisites
- Core Ib
Corequisites
- n/a
Excluded Combinations
- n/a
Aims
- Provide advanced knowledge and critical understanding of paradigms, fundamental ideas, tools and methods of program performance analysis and engineering
- Provide advanced knowledge and critical understanding of paradigms, fundamental ideas and methods behind advanced algorithms
Content
- Performance Analysis and Engineering
- Advanced Algorithms
Learning Outcomes
Subject-specific Knowledge
- Understanding and critical reflection of advanced ideas and techniques behind the performance analysis and performance of scientific computing and data analysis codes
- Understanding and critical reflection of advanced engineering algorithms in high-performance computing and data analysis
Subject-specific Skills
- Basic familiarity with state-of-the-art algorithms to solve large-scale and data intense challenges
- Competent and educated selection and statements on potential performance of specific codes plus skills to improve existing solutions
Key Skills
- Familiarity with advanced paradigms and modern algorithms underlying scientific computing as well as High-Performance Computing
Modes of Teaching, Learning and Assessment and how these contribute to the learning outcomes of the module
- n/a
Teaching Methods and Learning Hours
| Activity | Number | Frequency | Duration | Total Hours | Attendance Monitored |
|---|---|---|---|---|---|
| Lectures for Performance Engineering | 12 | 2 per week | 60 minutes | 12 | |
| Practical Classes for Performance Engineering | 4 | 2 per week | 60 minutes | 4 | |
| Lectures for Advanced Algorithms | 12 | 2 per week | 60 minutes | 12 | |
| Practical Classes for Advanced Algorithms | 4 | 2 per week | 60 minutes | 4 | |
| Self Study | 118 | ||||
| Total | 150 | ||||
Summative Assessment
| Component | Component Weighting | Element | Length/Duration | Element Weighting | Resit Opportunity |
|---|---|---|---|---|---|
| Summative Coursework | 100% | Performance Engineering Coursework | 1 week | 50% | |
| Advanced Algorithms Coursework | 1 week | 50% |
Formative Assessment
n/a
Students who do not attend monitored activities shown under Teaching Methods
and Learning Hours, or who fail to complete the summative or formative
assessment(s) specified above, may be subject to the Academic Progress
procedures defined in the University's General Regulation V, and may be
required to leave the University.