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DRPS : Course Catalogue : School of Informatics : Informatics

Postgraduate Course: Design and Analysis of Parallel Algorithms (INFR11179)

Course Outline
SchoolSchool of Informatics CollegeCollege of Science and Engineering
Credit level (Normal year taken)SCQF Level 11 (Postgraduate) AvailabilityAvailable to all students
SCQF Credits10 ECTS Credits5
SummaryThis module introduces theoretical design principles and analysis techniques that enable the creation and evaluation of efficient, scalable and portable algorithms for parallel computers. Concrete examples will span a range of application areas and architectural models seeking wherever possible to exploit commonality through appropriate abstraction.
Course description Syllabus:
Introduction: Conceptual frameworks for parallelism, message passing, shared address space, PRAM. Cost models for parallel algorithms. Cost efficiency and scalability. Inter-model emulation. Simple examples.
Problem solving strategies: Embarrassing parallelism, divide & conquer, pipelining, step-by-step parallelisation. Amdahl's Law. Gustafson's law.
Useful primitives: Collective communications, reduction, prefix.
Algorithms in selected problem areas, for example: Sorting (bitonic mergesort, hyperquicksort). Matrix oriented algorithms (multiplication, solving linear systems). Graph algorithms (spanning trees, single source & all-to-all shortest paths).
Entry Requirements (not applicable to Visiting Students)
Pre-requisites Co-requisites
Prohibited Combinations Other requirements None
Information for Visiting Students
High Demand Course? Yes
Course Delivery Information
Academic year 2018/19, Available to all students (SV1) Quota:  80
Course Start Semester 1
Timetable Timetable
Learning and Teaching activities (Further Info) Total Hours: 100 ( Lecture Hours 20, Summative Assessment Hours 2, Programme Level Learning and Teaching Hours 2, Directed Learning and Independent Learning Hours 76 )
Assessment (Further Info) Written Exam 100 %, Coursework 0 %, Practical Exam 0 %
Additional Information (Assessment) 100% Written Examination
Feedback Formative feedback: Two sets of pencil-and-paper problems submitted during the semester with feedback returned within three weeks and feedback on exam papers.
Exam Information
Exam Diet Paper Name Hours & Minutes
Main Exam Diet S1 (December)Design and Analysis of Parallel Algorithms2:00
Learning Outcomes
On completion of this course, the student will be able to:
  1. Define the structure of, and cost models associated with, the PRAM, mesh and hypercube models of parallel computation.
  2. Define the metrics of cost, speed-up and efficiency and use these as conceptual tools with which to analyse and discriminate between alternative candidate parallel algorithms for given problems; demonstrate, by the use of appropriately chosen examples, the importance of scalability in parallel algorithm design.
  3. Explain and, with appropriate use of diagrams, sketch the structure and operation of well known parallel algorithms in a range of application areas, including sorting, matrix and graph based problems.
  4. Apply a range of parallel algorithm design techniques (including divide-and-conquer and pipelining) to previously unseen problems, in order to create new parallel algorithms, which they will be able to describe using an informal mix of pseudo-code, textual explanation and diagrams.
Reading List
The recommended textbook for the course is A. Grama, A. Gupta, G. Karypis & V. Kumar 'Introduction to Parallel Computing', (2nd Ed), 2003.
Additional Information
Graduate Attributes and Skills Solution Exploration, Evaluation and Prioritisation.
Critical thinking
Communication of complex ideas in accessible language
Working in an interdisciplinary field
Programming and Scripting
Additional Class Delivery Information 2 lectures per week
KeywordsAlgorithms,DAPA,Parallel,EPCC,HPC,High Performance Computing,Parallelism,Parallel Computing
Course organiserDr Daniel Holmes
Course secretaryMr Ben Morse
Tel: (0131 6)51 3398
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