Durham University
Programme and Module Handbook

Postgraduate Programme and Module Handbook 2018-2019 (archived)

Module COMP52130: Core II B: Advanced Scientific and High Performance Computing

Department: Computer Science

COMP52130: Core II B: Advanced Scientific and High Performance Computing

Type Tied Level 5 Credits 30 Availability Not available in 2018/19

Prerequisites

Corequisites

Excluded Combination of Modules

Aims

  • Provide advanced knowledge and critical understanding of paradigms, fundamental ideas, tools and methods of program performance analysis
  • Provide advanced knowledge and critical understanding of paradigms, technologies, tools and trends in performance engineering incl skills how to use advanced HPC programming techniques
  • Provide advanced knowledge and critical understanding of paradigms, fundamental ideas, algorithms and methods behind the modelling and simulation of continuous systems (partial differential equations)
  • Provide advanced knowledge and critical understanding of paradigms, fundamental ideas, algorithms and methods behind the modelling and simulation of discrete systems

Content

  • Performance models and analysis
  • Performance engineering techniques in High-Performance Computing and accelerator programming
  • Scientific Computing for Partial Differential Equations
  • Scientific Computing for Discrete Systems (graph-based models, combinatorial optimisation, algorithms and complexity)

Learning Outcomes

Subject-specific Knowledge:
  • understanding and critical reflection of advanced ideas and techniques behind the performance analysis and on performance statements of scientific computing and data analysis codes
  • understanding and critical reflection of advanced paradigms and relevant techniques in high-performance computing and accelerator programming
  • understanding and critical reflection of advanced ideas, numerical techniques and algorithms used to study discrete models
  • understanding and critical reflection of advanced ideas, numerical techniques and algorithms used to study continuous models
Subject-specific Skills:
  • basic familiarity with state-of-the-art software toolboxes to solve large-scale equation systems
  • competent and educated selection and statements on potential performance of specific codes plus skills to identify shortcomings of existing solutions
  • competent and educated selection and application of programming languages and analysis tools for specific problems
  • competence to translate continuous and discrete problem descriptions into algorithmic formulations; competent and educated selection of appropriate solution algorithms
Key Skills:
  • familiarity with advanced paradigms and modern concepts underlying scientific computing both for discrete and continuous systems as well as High-Performance Computing

Modes of Teaching, Learning and Assessment and how these contribute to the learning outcomes of the module

Teaching Methods and Learning Hours

Activity Number Frequency Duration Total/Hours
Lectures in Performance Analysis 4 1 per week 60 minutes 4
Practical Classes in Performance Analysis 12 3 per week 60 minutes 12
Lectures in Performance Engineering 8 2 per week 60 minutes 8
Practical Classes in Performance Engineering 8 2 per week 60 minutes 8
Lectures in Modelling and Simulation of Continuous Systems 12 3 per week 60 minutes 12
Practical Classes in Modelling and Simulation of Continuous Systems 4 1 per week 60 minutes 4
Lectures in Modelling and Simulation of Discrete Systems 12 3 per week 60 minutes 12
Practical Classes in Modelling and Simulation of Discrete Systems 4 1 per week 60 minutes 4
Preparation, reading, and self-study 236

Summative Assessment

Component: Coursework Component Weighting: 100%
Element Length / duration Element Weighting Resit Opportunity
Discrete Systems with Performance Analysis and Engineering 5 weeks 50%
Continuous Systems with Performance Analysis and Engineering 5 weeks 50%

Formative Assessment:

Formative feedback is given as part of the coursework feedback. The linear algebra workshop is purely formative. Yet, content is used in the lectures.


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