Advanced Computational Engineering
| Code | School | Level | Credits | Semesters |
| EEEE4115 | Electrical and Electronic Engineering | 4 | 20 | Autumn UK |
- Code
- EEEE4115
- School
- Electrical and Electronic Engineering
- Level
- 4
- Credits
- 20
- Semesters
- Autumn UK
Summary
This module covers the development of advanced engineering software projects, spanning a range of application areas. Generic Topics to be discussed include: Large-scale software management, robust design and coding techniques, accurate and efficient numerical computing for technological simulations, parallel computing techniques applicable to several classes of parallel computer e.g. multicore, distributed and graphics processing unit (GPU) based systems, database design and implementation; distributed network based computing; hardware interfacing.
Reassessment of the module, if required, will be by reassessment of the failed elements.
Target Students
MEng,MSc and PhD students of Electrical and Electronic Engineering
Classes
- One 2-hour lecture each week for 11 weeks
- One 2-hour computing each week for 11 weeks
Assessment
- 25% Coursework 1
- 12% Coursework 2
- 25% Coursework 3
- 12% Coursework 4
- 25% Coursework 5
Assessed by end of autumn semester
Educational Aims
To introduce students to the different roles and forms of software in use across the range of engineering activity; this encompasses efficient and robust numerical computation and the networking and data-management aspects of the broader engineering environment.Learning Outcomes
By the end of the module, students should be able to:
LO1 Demonstrate a critical appreciation of the relative advantages of different parallel software paradigms and be able to undertake their implementation on multicore and commodity-cluster platforms
This module contributes to the delivery of the following Engineering Council outcomes:
C1, M1, C2, M2, C3, M3, C5, M5, C6, M6, C8, M8, C11, M11, C12, M12, C13 and M13
LO2 Perform business analysis of large-scale data sets resulting in highly efficient and optimised database schema and the appropriate use of queries and reports to maximise the interfacing
LO5 Implement realistic examples on GPU platform using appropriate software
LO4 Demonstrate an appreciation of the emerging role of GPUs for practical computation and be able to implement realistic examples
LO3 Demonstrate a critical appreciation of the different approaches for the storing and manipulation of large data set using commodity-cluster platforms