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日期:2019-12-31 07:16


Updated August 2018 1 of 3 TABLE OF CONTENTS

Main Objective of the assessment........................................................................................................................ 1

Description of the Assessment.............................................................................................................................. 1

Learning Outcomes and Marking Criteria ............................................................................................................. 1

Format of the Assessment .................................................................................................................................... 2

Submission Instructions ........................................................................................................................................ 3

Avoiding Plagiarism............................................................................................................................................... 3

Late Coursework ................................................................................................................................................... 3

Assessment Title Individual Project Development

Module Leader Allan Tucker

Distribution Date Week 4

Submission Deadline 6 January 2020

Feedback by 15 working days after submission

Contribution to overall module assessment 100%

Indicative student time working on assessment 42 Hours

Word or Page Limit (if applicable)

There is no word/page limit for this assessment, but

the best effort should be made to ensure the

submission is as concise as possible.

Assessment Type (individual or group) Individual

MAIN OBJECTIVE OF THE ASSESSMENT

In this assessment, you are required to demonstrate the appropriate practical skills and abilities to implement

solutions using modern large-scale data storage and processing infrastructures, and to critically reflect on the

concepts, theory and use of high performance computational infrastructures.

DESCRIPTION OF THE ASSESSMENT

You are required to identify and analyse a real-world problem, design and implement a solution to the

problem using Hadoop, and evaluate your implementation. The problem can be a simplified version from its

original scale, extent or level of difficulties etc. An indicative list of sample problems have been provided at

the end of this document. You may choose one of the problems in the list, but you are encouraged to identify

your own problem for the project.

The assessment has two weighted components:

1. Oral presentation (PASS / FAIL). A workshop will be held near the end of the term. Each candidate will be

allocated with 10 minutes (including question time) to present their individual project development and

demonstrate, if any, your prototype software. You should take this as an opportunity to seek feedback and

improve your project for the final submission.

2. Report (100%). A written report including the theory behind and the development of the individual project

needs to be submitted.

LEARNING OUTCOMES AND MARKING CRITERIA

Learning Outcomes:

LO1: Demonstrate the appropriate practical skills/abilities required to implement solutions using modern

large-scale data storage and processing infrastructures.

CS5607 High Performance Computational

Infrastructures

Assessment/Coursework for 2018/19

Department of Computer Science

Updated August 2018 2 of 3

LO2: Reflect critically on the concepts, theory and appropriate use of large-scale data storage and processing

infrastructures (commonly used in modern organisational environments).

Marking Criteria:

The coursework will be marked for 4 main criteria:

1. Demonstrating an understanding of the relevant theory underpinning distributed file systems &

data analysis (LO2)

2. Identifying a real data analytics problem with strong motivation for using distributed processing

methods (LO1)

3. Implementing and applying a working solution using distributed analytical techniques (LO1)

4. Critically evaluating the results of the implementation on the data with a discussion of how the

approach is different from standard non-distributed methods (e.g. relational databased, serial

data-mining) (LO2)

Grade Band E and F (E+, E, E-, F)

The candidate fails to meet the minimum requirements as outlined in the learning outcomes.

Grade Band D (D+, D, D-)

The work demonstrates significant weaknesses, but all of the learning outcomes have been met at the

minimum requirement level. The work provides evidence of some critical understanding of the concepts and

theories of large-scale data storage and processing infrastructures, and demonstrates some abilities and skills

to implement solutions using these technologies.

Grade Band C (C+, C, C-)

In addition to the requirements for a grade in D-band, the work demonstrates a critical and substantial

understanding of the concepts and theories of large-scale data storage and processing infrastructures. It

demonstrates the ability to develop an independent, systematic, logical and effective solution to the

problems identified. It also demonstrates a significant degree of competence in the appropriate use of the

relevant literature, theory, methodologies, practices, and tools, etc., to analyse the problems and evaluate

the solutions.

Grade Band B (B+, B, B-)

In addition to the requirements for a grade in C-band, the work clearly demonstrates a well-developed, critical

and substantial understanding of the concepts and theories of large-scale data storage and processing

infrastructures. It clearly demonstrates the ability to develop an independent, systematic, logical and effective

solution to the problems identified. It also demonstrates a high degree of competence in the appropriate use

of the relevant literature, theory, methodologies, practices, and tools, etc., to analyse the problems and

evaluate the solutions.

Grade Band A (A*, A+, A, A-)

In addition to the requirements for a grade in B-band, the work clearly demonstrates a sophisticated, critical

and thorough understanding of the concepts and theories of large-scale data storage and processing

infrastructures. It provides evidence of originality of thought and clearly demonstrates the ability to develop

an independent, systematic, logical and effective solution to the problems identified. It also demonstrates

excellence in the appropriate use of the relevant literature, theory, methodologies, practices, and tools, etc.,

to analyse the problems and evaluate the solutions.

FORMAT OF THE ASSESSMENT

There is no word/page limit for this assessment, but the best effort should be made to ensure the submission

is as concise as possible. You should include sections on (percentage of overall mark):

Introduction (20%) - criteria 1

Problem description & associated dataset (20%) - criteria 2

Design & Implementation (20%) - criteria 3

Results (20%) - criteria 4

Conclusions (20%) - criteria 1

Department of Computer Science

Updated August 2018 3 of 3

A mark will be assigned to each section to form an overall percentage. This will then be converted into your

final grade.

SUBMISSION INSTRUCTIONS

You must submit your coursework as a PDF file on Wiseflow by 6 Jan 2020 at 11am. You can follow the link to

Wiseflow through the module’s section on Blackboard Learn or login in directly at

https://uk.wiseflow.net/brunel. The name of your file should follow the normal convention set out in the

student handbook, and must therefore include your student ID number (e.g., 0612345.pdf). It can also

include the module code (e.g., CS2001_0612345.pdf).

AVOIDING PLAGIARISM

Please ensure that you understand the meaning of plagiarism and the seriousness of the offence. Information

on plagiarism can be found on the College’s Student Handbook.

LATE COURSEWORK

The clear expectation is that you will submit your coursework by the submission deadline stated in the study

guide. In line with the University’s policy on the late submission of coursework (revised in July 2016),

coursework submitted up to 48 hours late will be accepted, but capped at a threshold pass (D- for

undergraduate or C- for postgraduate). Work submitted over 48 hours after the stated deadline will

automatically be given a fail grade (F).

Please refer to the Computer Science Student Handbook, available on Blackboard Learn, for information on

Department of Computer Science

submitting late work, penalties applied and procedures in the case of mitigating circumstances.


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