Course Details
Course Information Package
Course Unit Title | PARALLEL AND CLOUD COMPUTING | ||||||||
Course Unit Code | ACSC521 | ||||||||
Course Unit Details | |||||||||
Number of ECTS credits allocated | 7 | ||||||||
Learning Outcomes of the course unit | By the end of the course, the students should be able to:
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Mode of Delivery | Face-to-face | ||||||||
Prerequisites | NONE | Co-requisites | NONE | ||||||
Recommended optional program components | NONE | ||||||||
Course Contents | 1. 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 |
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References |
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Planned learning activities and teaching methods | The 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 |
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Language of instruction | English | ||||||||
Work placement(s) | NO |