F20DP Distributed & Parallel Technologies

Dr Rob StewartDr Hans Wolfgang Loidl

Course co-ordinator(s): Dr Rob Stewart (Edinburgh), Dr Hans Wolfgang Loidl (Edinburgh).

Aims:

  • To explore technologies and techniques underlying advanced software development for parallel and distributed systems.
  • Review the principal abstractions, methods and techniques used in distributed and parallel programming.
  • Develop an understanding of parallel programming on heterogeneous architectures including accelerators such as GPUs

Detailed Information

Course Description: Link to Official Course Descriptor.

Pre-requisites: Academic knowledge of fundamentals of operating systems, computer networks and software engineering equivalent to an ordinary degree in Computer Science, basic knowledge of programming in C.

Location: Edinburgh.

Semester: 2.

Syllabus:

Distributed Technologies: Distribution concepts; low-level, mid-level and high-level distributed technologies; emerging distribution and coordination technologies. Parallel Technologies: Design of parallel systems, parallel performance analysis; programming heterogeneous systems; practical imperative parallel programming; practical declarative parallel programming

Learning Outcomes: Subject Mastery

Understanding, Knowledge and Cognitive Skills Scholarship, Enquiry and Research (Research-Informed Learning)

  • Understanding of foundational concepts of distributed and parallel software
  • Knowledge of contemporary techniques for constructing practical distributed and parallel systems using both declarative and imperative languages
  • Parallel performance tuning using appropriate tools and methodologies
  • Appreciation of relationship between imperative and declarative models of parallelism

Learning Outcomes: Personal Abilities

Industrial, Commercial & Professional Practice Autonomy, Accountability & Working with Others Communication, Numeracy & ICT

  • Critically analyse parallel and distributed problems.
  • Generate, interpret and evaluate parallel performance graphs
  • Develop original and creative parallel problem solutions
  • Demonstrate reflection on core concepts and technologies, e.g. understanding of applicability of, and limitations to, parallel and distributed systems

Assessment Methods:

Assessment: Examination: (weighting – 70%) Coursework: (weighting – 30%)
Re-assessment: None

SCQF Level: 10.

Credits: 15.