COMP1680 Clouds, Grids and Virtualisation

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MODULE HANDBOOKCOMP1680 Clouds, Grids and Virtualisation2021-221 | P a g e
1. Welcome message from your Module Leader …………………………………………………………….. 22. Key contacts…………………………………………………………………………………………………………… 23. Module details and learning outcomes ………………………………………………………………………. 34. Employability ………………………………………………………………………………………………………….. 35. Schedule of teaching and learning activities……………………………………………………………….. 46. Assessment……………………………………………………………………………………………………………. 47. Resit assessments ………………………………………………………………………………………………….. 58. Reading recommendations ………………………………………………………………………………………. 59. Additional module information…………………………………………………………………………………… 510. Changes to the module……………………………………………………………………………………………… 52 | P a g e
1. Welcome message from your Module Leader
Welcome to COMP1680 Clouds, Grids and Virtualisation. Research into high performancecomputing has been driven by the need to solve large-scale, increasingly complex problems forscientific applications. This technology has matured into the use of grids to manage looselycoupled, heterogeneous resources and provide virtual supercomputer facilities capable ofsupporting large scale applications. The applications of grid computing for business and casualusers did not begin to emerge until advances in virtualisation and high-speed networks led to thedevelopment of cloud computing. High performance computing is no longer perceived to be adiscipline for academics, researchers, and niche hardware manufacturers. With the introductionof affordable multi-core processors, high performance computing has become a mainstreamactivity. This technology now underpins applications in a variety of sectors, including traditionalnumerical modelling fields such as such as meteorology, aerospace and automotive engineeringand emerging fields such as search engines, financial modelling, post-production effects and soon.This handbook provides essential information that you will need during your undertaking of thismodule. It is not intended to be exhaustive but should help you to see at a glance keyinformation about the module such as the aims and learning outcomes, the proposed scheduleof delivery, assessment details, reading list and any additional resources that will be needed byyou. Please ensure that you familiarise yourself with its contents.
2. Key contactsModule Leader: Catherine Tonry Location: QM260Email: [email protected]Tel: 020 8331 7796Office hours:Tuesdays 11-12 am (QM260)Thursdays 1-2 pm (Online)Please make an appointmentModule Instructor: Andrew Kao Location: QM260Email: [email protected]Tel: 020 8331 7796Office hours: By AppointmentModule Instructor: David Pizzi Location: N/A (Visiting Lecturer)Email: [email protected]Tel: N/A (Visiting Lecturer)Office hours: N/A (Visiting Lecturer)Module Tutor: Angus Grandison Location:Email: [email protected]Tel:Office hours: By AppointmentModule Tutor: Peter Soar Location:Email: [email protected]Tel:Office hours: By Appointment
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3. Module details and learning outcomes
School/Department: Computing and Mathematical SciencesNumber of Credits: 15Term of delivery: Term 1Site of delivery: Greenwich Maritime SitePre-requisites/Co-requisites:Good programming skills in C/C++Aims:Research into high performance computing has been driven by the need to solve large-scale,increasingly complex problems for scientific applications. This technology has matured intothe use of grids to manage loosely coupled, heterogeneous resources and provide virtualsupercomputer facilities capable of supporting large scale applications. The applications ofgrid computing for business and casual users did not begin to emerge until advances invirtualisation and high speed networks led to the development of cloud computing. Highperformance computing is no longer perceived to be a discipline for academics, researchersand niche hardware manufacturers. With the introduction of affordable multi-core processors,high performance computing has become a mainstream activity. This technology nowunderpins applications in a variety of sectors, including machine learning, financial modelling,meteorogloy, aerospace and automotive engineering.Learning Outcomes:1. Demonstrate in depth understanding and critically evaluate high performance computingbased architectures and their suitability for given applications.2. Design, implement and execute applications using shared memory programmingparadigms.3. Evaluate the performance and scalability of shared memory applications.4. Describe and critically discuss the roles and applications of cloud and grid computing.
4. Employability
Skills Gained:Open-MP programmingKnowledge of cloud and grid computingKnowledge of architecture of parallel computing systemsYou can find out more about the Greenwich Employability Passport at:Greenwich Employability Passport for studentsInformation about the Career Centre is available at: Career transition and jobsearch
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5. Schedule of teaching and learning activities
Week Begining Lecture(s) Lecturer27 September 2021 Introduction to course C. TonryIntroduction to C04 October 2021 Why Parallel Computing C. Tonry11 October 2021Parallel Programming modelsC .TonryPerformance Measures18 October 2021 Cloud Computing Lecture 1 D. Pizzi25 October 2021Introduction to Open MPC. TonryOpen MP Runtime Libraries01 November 2021 Open MP Environment variables and directives C. Tonry08 November 2021 Solving Linear Systems C. Tonry15 November 2021 Cloud Computing Lecture 2 D. Pizzi22 November 2021 1D Jacobi and Gauss-Seidel Example Codes C. Tonry29 November 2021 OpenMP performance C Tonry06 December 2021 Parallel Programming and MPI A. Kao13 December 2021 Coursework Support C. Tonry
In addition to the teaching and learning activities within the module, additionalstudy support can be seen at: Academic Skills
6. Assessment
The overall pass mark for this module is 50%.
Assessment ScheduleAssessment Due date1 Weight Learning OutcomesCloud Computing Coursework 1/12/2021 40% 1,4OpenMP Coursework 15/12/2021 60% 1,2,3
1. Return of marked work with feedback will normally be given up to 15 working days after thedue date indicated. In exceptional circumstances where you experience a delay in receivingthis then you will be informed by the tutor.
For further information around assessments, please refer to the Student Handbook.Extenuating circumstances and student supportThe University recognises there are times when serious and unexpected matters which are beyonda student’s control (such as serious illness or injury, death in family) impact on their academicperformance and ability to complete assessments by the deadline. Guidance on claiming extenuationcan be found at: Extenuating circumstances5 | P a g e
7. Resit assessments
Assessment ScheduleAssessment Due date1 Weight Learning OutcomesCloud Computing Coursework 15/07/2022 40% 1,4OpenMP Coursework 15/07/2022 60% 1,2,3
8. Reading recommendations
The following are suggested readings for the module. Additional, more detailedreading recommendations will be provided for the module topics.
Author
Title
Publisher
ISBN
Paul Deitel,Harvey Deitel
C: How to Program
PearsonEducation
978-1292110974
Peter Pacheco
An Introduction to ParallelProgramming
MorganKaufmann
978-123742605
BarbaraChapman,Gabriele Jost,Ruud van derPas
Using OpenMP portable sharedmemory parallel programming
MIT Press
978-262533027
BarrieSosinsky
Cloud Computing Bible
Wiley
978-470903568
Peter Pacheco
Parallel Programming with MPI
MorganKaufmann
978-1558603394
Rohit Chandra
Parallel Programming in OpenMP
MorganKaufmann
978-1558606715
9. Additional module information
There are no module specific costs associated with this course.
10. Changes to the module
At the University of Greenwich, we value feedback from students as well as ExternalExaminers and other stakeholders and we use this information to help us improveour provision. Please insert an example of a response to feedback.Important note: The University of Greenwich will do all that it reasonably can todeliver the module and support your learning as specified in our handbooks andother information provided. However, under some circumstances, changes mayhave to be made. This may include modifications to the:• content and syllabus of modules, including in relation to placements• timetable, location and number of classes• content or method of delivery of your module• timing and method of assessments.This might be because of, for example:• academic changes within subject areas6 | P a g e• the unanticipated departure or absence of members of university staff• where the numbers expected on a module are so low that it is not possibleto deliver an appropriate quality of education for students enrolled on it.• industrial action by university staff or third parties• the acts of any government or local authority• acts of terrorism.In these circumstances, the University will take all reasonable steps to minimisedisruption by making reasonable modifications. However, to the full extent that it ispossible under the general law, the University excludes liability for any loss and/ordamage suffered by any applicant or student due to these circumstances.

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