Module Details
| Module Code: |
SOFT8040 |
| Title: |
Edge and Distributed Computing
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Long Title:
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Edge and Distributed Computing
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| NFQ Level: |
Advanced |
| Valid From: |
Semester 2 - 2021/22 ( January 2022 ) |
| Field of Study: |
4814 - Computer Software
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| Module Description: |
This module will develop computation solutions for Smart Product and Networked Systems, on either local or cloud based systems. The student will analyse smart product compute requirements, determine how to partition them and distribute the compute requirements either locally or on the cloud.
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| Learning Outcomes |
| On successful completion of this module the learner will be able to: |
| # |
Learning Outcome Description |
| LO1 |
Critically evaluate different design approaches within microprocessors and cloud computation platforms based on their intended end use. |
| LO2 |
Analyse, compare and specify processing platforms (local and/or remote), appropriate for typical high performance smart product use cases. |
| LO3 |
Partition a smart product development problem into appropriate elements and objects, and design solutions using local and/or cloud platforms, tools and languages. |
| LO4 |
Design and implement object models, in an appropriate language to implement advanced local or cloud distributed program architectures. |
| LO5 |
Demonstrate an appreciation of the legal, ethical and business considerations in the choice of computing & processing platforms and algorithms. |
| Dependencies |
Module Recommendations
This is prior learning (or a practical skill) that is strongly recommended before enrolment in this module. You may enrol in this module if you have not acquired the recommended learning but you will have considerable difficulty in passing (i.e. achieving the learning outcomes of) the module. While the prior learning is expressed as named MTU module(s) it also allows for learning (in another module or modules) which is equivalent to the learning specified in the named module(s).
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Incompatible Modules
These are modules which have learning outcomes that are too similar to the learning outcomes of this module. You may not earn additional credit for the same learning and therefore you may not enrol in this module if you have successfully completed any modules in the incompatible list.
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| No incompatible modules listed |
Co-requisite Modules
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| No Co-requisite modules listed |
Requirements
This is prior learning (or a practical skill) that is mandatory before enrolment in this module is allowed. You may not enrol on this module if you have not acquired the learning specified in this section.
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| No requirements listed |
| Indicative Content |
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Processing/Compute Architectures
Local & Cloud Implementations of CPU/MPU architectures. CISC, RISC, vector processing, comparison, issues, Harvard architectures, von Neumann, Processing bottlenecks, pipelining, distribution
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Design for End Use
Self Build or Cloud or Hybrid. : Microprocessors/Microcontrollers, interrupt handling, and OS interaction, OS Platform designs, security implications, standard Vs. RealTime and Cloud Service Implementations. Comparison and selection for applications
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High Level Requirements/Problem Partitioning
Requirements leading to application implementation models, appropriate systems architecture, local vs distributed, persistence, reliability, security and data protection
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System and Component Modelling
Use case modelling, UML, CASE Tools, applications, component design.
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Advanced Programming Concepts
Component/object distribution, process/task synchronisation, error handling/processing, multi-threading, memory protection.
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Ethical and legal considerations
Examination of possible industry ethical and legal problems through case study, e.g. redundancy of decision making, hacking/security implications and corporate responsibility
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Module Content & Assessment
|
| Assessment Breakdown | % |
|---|
| Coursework | 50.00% |
| End of Module Formal Examination | 50.00% |
Assessments
| End of Module Formal Examination |
|
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| Reassessment Requirement |
Repeat examination
Reassessment of this module will consist of a repeat examination. It is possible that there will also be a requirement to be reassessed in a coursework element.
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The University reserves the right to alter the nature and timings of assessment
Module Workload
| Workload: Full Time |
| Workload Type |
Contact Type |
Workload Description |
Frequency |
Average Weekly Learner Workload |
Hours |
| Lab |
Contact |
Class/Lecture/Lab |
Every Week |
4.00 |
4 |
| Independent & Directed Learning (Non-contact) |
Non Contact |
Exercises and review materials |
Every Week |
3.00 |
3 |
| Total Hours |
7.00 |
| Total Weekly Learner Workload |
7.00 |
| Total Weekly Contact Hours |
4.00 |
| Workload: Part Time |
| Workload Type |
Contact Type |
Workload Description |
Frequency |
Average Weekly Learner Workload |
Hours |
| Lab |
Contact |
Class/Lecture/Lab |
Every Week |
4.00 |
4 |
| Independent & Directed Learning (Non-contact) |
Non Contact |
Exercises and review materials |
Every Week |
3.00 |
3 |
| Total Hours |
7.00 |
| Total Weekly Learner Workload |
7.00 |
| Total Weekly Contact Hours |
4.00 |
|
Module Resources
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| Recommended Book Resources |
|---|
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John L. Hennessy, David A. Patterson. (2018), Computer Architecture: A Quantitative Approach, 6. Elsevier Technology/Morgan Kaufmann, USA, [ISBN: 0128119055].
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Alan Dennis, Barbara Haley Wixom & David Tegarden. (2015), Systems Analysis and Design: An Object-Oriented Approach with UML, 5. Wiley, [ISBN: 1118804678].
| | Supplementary Article/Paper Resources |
|---|
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Emily Blem, Jaikrishnan Menon, and
Karthikeyan Sankaralingam,. (2013), Power Struggles: Revisiting the RISC vs.
CISC Debate on Contemporary ARM and x86
Architectures, IEEE International Symposium on High
Performance Computer Architecture, HPCA 2013,
| | Other Resources |
|---|
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Website, M Lipp, M Schwarz et al.. (2018), Meltdown: Reading Kernel Memory from
User Space, USA, 27th {USENIX} Security Symposium,
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Website, SparxsystemsUML Tools for software
Developers,
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