Run by School of Computer Science and Electronic Engineering

20.000 Credits or 10.000 ECTS Credits

Semester 1

Organiser: Dr Franck Vidal

• To introduce to the principles and practice of parallel and concurrent programming on modern High Performance Computing (HPC) architectures (both CPU and GPU) (both distributed memory and shared memory).
• To be to design algorithms running on parallel architectures.
• To implement algorithms running on a specific parallel architecture.

Indicative content includes:

• Comparison between shared memory and distributed memory
• Comparison between processors architectures (inc. SIMD, MIMD, and SIMT). It will cover multi-core processors (i.e. CPUs) and many-core processors (e.g. GPUs)
• Fundamental concepts of concurrent programming, including: threads, shared variables, critical regions, atomics, semaphores, race conditions, deadlock
• Practice of parallel programming:
• Design of algorithms that use the architecture effectively
• Implementation of such algorithms using industry-standard tools and APIs, eg. CUDA, MPI, Vulcan, C++.
• Validation of the results produced by such algorithms

excellent

Equivalent to the range 70%+. Assemble critically evaluated, relevent areas of knowledge and theory to constuct professional-level solutions to tasks and questions presented. Is able to cross-link themes and aspects to draw considered conclusions. Presents outputs in a cohesive, accurate, and efficient manner.

good

Equivalent to the range 60%-69%. Is able to analyse a task or problem to decide which aspects of theory and knowledge to apply. Solutions are of a workable quality, demonstrating understanding of underlying principles. Major themes can be linked appropriately but may not be able to extend this to individual aspects. Outputs are readily understood, with an appropriate structure but may lack sophistication.

threshold

Equivalent to 50%. Uses key areas of theory or knowledge to meet the Learning Outcomes of the module. Is able to formulate an appropriate solution to accurately solve tasks and questions. Can identify individual aspects, but lacks an awareness of links between them and the wider contexts. Outputs can be understood, but lack structure and/or coherence.

1. Differentiate the different parallel programming models, typified by memory issues.

2. Recognise and describe components of HPC systems.

3. Compare and contrast different processor architectures.

4. Construct parallelised programs on both multi-core (CPUs) and many-core (GPUs) architectures using industry standards.

Type	Name	Description	Weight
	Unseen Examination		50.00
	Programming Assignment		50.00

		Hours
Lecture	2 hours per tutorial/lecture per week	24
Laboratory	1x2 hours a week	24
Private study	72 hours of laboratory preparation and reports 80 hours of self-study (inc. revision after the lectures; preparation for the assessed and non-assessed labs and the exam).	152

• Numeracy - Proficiency in using numbers at appropriate levels of accuracy
• Computer Literacy - Proficiency in using a varied range of computer software
• Self-Management - Able to work unsupervised in an efficient, punctual and structured manner. To examine the outcomes of tasks and events, and judge levels of quality and importance
• Exploring - Able to investigate, research and consider alternatives
• Critical analysis & Problem Solving - Able to deconstruct and analyse problems or complex situations. To find solutions to problems through analyses and exploration of all possibilities using appropriate methods, rescources and creativity.

• Identify emerging technologies and technology trends;
• Solve problems logically and systematically;
• Analyse and display data using appropriate methods and mathematical techniques;
• Demonstrate familiarity with relevant subject specific and general computer software packages.
• Problem solving strategies
• Deploy theory in design, implementation and evaluation of systems
• Specify, design or construct computer-based systems
• Knowledge and/or understanding of appropriate scientific and engineering principles
• Knowledge and understanding of mathematical principles
• Knowledge and understanding of computational modelling

Compulsory in courses:

• H617: MEng Computer Systs Eng (4 yrs) year 4 (MENG/CSE)
• H61P: Computer Systems Engineering with Industrial Placement year 5 (MENG/CSEP)

Optional in courses:

• H117: MComp Computer Science year 4 (MCOMP/CS)
• G4AS: MSc Advanced Computer Science year 1 (MSC/ACS)
• G5BB: MSc Advanced Data Science year 1 (MSC/ADS)