MSc in Web and Smart Systems / Ступінь Магістра в Галузі Веб і Мобільних Систем

Course Details

Course Information Package

Course Unit TitlePARALLEL AND CLOUD COMPUTING
Course Unit CodeACSC521
Course Unit Details
Number of ECTS credits allocated7
Learning Outcomes of the course unitBy the end of the course, the students should be able to:
  1. Classify parallel processing systems and distinguish between the shared memory and message passing systems.
  2. Outline the characteristics and evaluate current cluster and large scale parallel systems.
  3. Use OpenMP and MPI to write programs for high performance computing applications.
  4. Explain the core concepts of distributed computing.
  5. Justify the shift to the cloud computing paradigm and outline the influence of the enabling technologies in cloud computing.
  6. Distinguish between and outline the services provided by the current main Cloud Computing platforms.
  7. Use a public cloud computing platform to develop applications for parallel processing and distribute storage systems.
  8. Identify the emerging research challenges in cloud computing related to security, quality of service and energy efficient systems.
Mode of DeliveryFace-to-face
PrerequisitesNONECo-requisitesNONE
Recommended optional program componentsNONE
Course Contents1.  Parallel Programming
-  Shared Memory Systems. Symmetric Multiprocessors and cache coherent NUMA systems. Programming with OpenMP.
-  Clusters, distributed memory systems, message passing and heterogeneous systems. Programming with MPI.
2.  Grid and Cloud Computing :
-  Distributed Programming Issues: virtualization, abstraction, statelessness, chunkiness, scalability, message passing, and distributed file systems. Programming models (MapReduce, Hadoop)
-  Motivation for Grid and Cloud computing.  Types of Clouds and current Cloud platforms (Amazon Web Services – Amazon Elastic Compute Cloud, Microsoft Azure, and Google App Engine).
-  Cloud Storage: Relational and non-relational data, blobs, tables and queues.
Cloud application development using Microsoft Azure and Cloud parallel programming applications using Dryad ans DryadLINQ.
Recommended and/or required reading:
Textbooks
  • M. Quinn, (2004),Parallel Programming in C with MPI and OpenMP, McGraw Hill, 2004
  • D. Chappel, (2010), Introducing the Windows Azure Platform, Microsoft.
References
  • Tom White, (2010),Hadoop: The Definitive Guide (2ndEdition), O'Reilly Media
  • An extensive reading list of relevant academic papers
Planned learning activities and teaching methodsThe taught part of course is delivered to the students by means of lectures, conducted with the help of computer presentations. Lecture notes and presentations are available through the web for students to use in combination with the textbooks. Furthermore theoretical principles are explained by means of specific examples and solution of specific problems.
Lectures are supplemented with supervised computer programming laboratory sessions.
Assessment methods and criteria
Assignments40%
Project work20%
Final Exam40%
Language of instructionEnglish
Work placement(s)NO

 Друк  E-mail