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DEGREE REGULATIONS & PROGRAMMES OF STUDY 2018/2019

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DRPS : Course Catalogue : School of Informatics : Informatics

Postgraduate Course: Threaded Programming (INFR11178)

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 course is a practical introduction to parallel programming using the threading model, which is commonly used on shared memory and multicore hardware. The majority of the course is focused on teaching the use of the industry standard OpenMP API.
Course description After taking this course students should have a good practical understanding of multithreaded programming and be competent OpenMP programmers.

The course will cover the following topics:
- Basic concepts of shared memory: threads, tasks, shared/private data, synchronisation.
- Concepts of OpenMP: parallel regions, shared/private variables, parallel loops, reductions
- OpenMP parallel regions and associated clauses
- OpenMP worksharing directives, scheduling of parallel loops
- OpenMP synchronisation: barriers, critical sections, atomics, locks.
- OpenMP tasks
- Additional features of OpenMP: nesting, orphaning, threadprivate globals, OpenMP 4.0 features
- OpenMP implementations
- Memory models.

Lectures will be followed by tutored practical sessions illustrating the key concepts. Students will have the choice of using either C or Fortran in the practical programming sessions on OpenMP.
Entry Requirements (not applicable to Visiting Students)
Pre-requisites Co-requisites
Prohibited Combinations Other requirements Students are required to be familiar with C or Fortran for practical exercises.

There are limited spaces on this course. Students not on the MSc in High Performance Computing or MSc High Performance Computing with Data Science should contact the course secretary to confirm availability and confirm that they have the required prerequisites before being enrolled on the course.
Information for Visiting Students
Pre-requisitesStudents are required to be familiar with C or Fortran for practical exercises.
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 14, Supervised Practical/Workshop/Studio Hours 10, Programme Level Learning and Teaching Hours 2, Directed Learning and Independent Learning Hours 74 )
Assessment (Further Info) Written Exam 0 %, Coursework 100 %, Practical Exam 0 %
Additional Information (Assessment) 100% Coursework, split into two assignments. Feedback will be given on the first assignment before students are expected to start work on the second.
Feedback Students receive detailed individual text-based feedback on all components of the coursework. The coursework is split into two parts, with feedback given on the first part before students are expected to start work on the second part. Students may contact the course co-ordinator to discuss the feedback further in person if required.

Feedback is also provided through the practical classes.
No Exam Information
Learning Outcomes
On completion of this course, the student will be able to:
  1. Understand the key concepts of multithreaded programming
  2. Have a knowledge of the syntax and semantics of the OpenMP API.
  3. Be able to write a correct OpenMP program in C/C++ or Fortran.
  4. Have an appreciation of the advanced features of OpenMP
  5. Understand key factors affecting performance of threaded programs
Learning Resources
https://mitpress.mit.edu/books/using-openmp

https://mitpress.mit.edu/books/using-openmp%E2%80%94-next-step

Further resources provided via Learn course.
Additional Information
Graduate Attributes and Skills Effective written and diagrammatic communication.
Technical writing.
Data collection and analysis.
Reflection on learning and practice.
Adaptation to circumstances.
Solution Exploration, Evaluation and Prioritisation.
Programming.
Special Arrangements There are limited spaces on this course. Students not on the MSc in High Performance Computing or MSc High Performance Computing with Data Science should contact the course secretary to confirm availability and confirm that they have the required prerequisites before being enrolled on the course.

The course is available to PhD students for class-only study. PhD students requiring a form of assessment (e.g. SUPA/School of Physics and Astronomy CDT students) must contact the course secretary to confirm method of enrolment.
Additional Class Delivery Information Two lectures per week (weeks 1-7), one practical per week (weeks 1-10).
KeywordsOpenMP,Threads,TP,EPCC,HPC,High Performance Computing,Parallel,Programming,Parallelism
Contacts
Course organiserDr Mark Bull
Tel: (0131 6)50 6717
Email: markb@epcc.ed.ac.uk
Course secretaryMr Ben Morse
Tel: (0131 6)51 3398
Email: Ben.Morse@ed.ac.uk
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