THE UNIVERSITY OF HUDDERSFIELD
School of Computing and Engineering
ASSIGNMENT SPECIFICATION
Module Details
Module Code NHE2530FNW
Module Title PCA, Clusters and Grids
Course Title/s BEng (Hons) Electronic Engineering and Computer Systems
Assessment Weighting, Type and Contact Details
Title Python for Parallel computing project
Weighting 26%
Mode of working for
assessment task
Individual
Note: if the assessment task is to be completed on an individual
basis there should be no collusion or collaboration whilst working on
and subsequently submitting this assignment.
Module Leader Dr S AMAMRA SidAli.Amamra@hud.ac.uk
Module Tutor/s Dr A FARZAMNIA
Submission Submission and Feedback Details
Hand-out date 16/09/2024
How to submit your
work.
Brightspace/Turnitin
Submission date/s 17/11/2024 by 12:00 noon – if you have any technical issues
submitting your work, please contact the Module Leader as
soon as possible.
Expected amount of
independent time you
should allocate to
complete this
assessment
30 hours
Submission type and
format
Lab report (1500 words, doc/pdf).
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Submission Submission and Feedback Details
Date by which your
grade and feedback
will be returned
16/12/2024
Note: This is a maximum of three working weeks after the
submission deadline.
Additional Guidance
Information
Details
Your responsibility It is your responsibility to read and understand the University
regulations regarding conduct in assessment.
Please pay special attention to the assessment regulations
(section 10) on Academic Misconduct.
In brief: ensure that you;
1. DO NOT use the work of another student - this includes
students from previous years and other institutions, as well
as current students on the module.
2. DO NOT make your work available or leave insecure, for
other students to view or use.
3. Any examples provided by the module tutor should be
appropriately referenced, as should examples from external
sources.
Further guidance can be found in the SCEN Academic Skills
Resource and UoH Academic Integrity Resource module in
Brightspace.
Guidance on using AI: Level 1 – Not Permitted
The use of AI tools is not permitted in any part of this
assessment.
School Guidance and
Support
If you experience difficulties with this assessment or with time
management, please speak to the module tutor/s, your
Personal Academic Tutor, or the Student Progress Mentors.
Student Progress Mentor – useful links.
3
Additional Guidance
Information
Details
• Brightspace Module - SCE Student Progress Mentors
(hud.ac.uk).
• Email - sce.progress.mentors@hud.ac.uk
Booking an appointment - http://hud.ac/rgl
Requesting a Late
Submission
It is expected that you complete your assessments by the
published deadlines. However, it is recognised that there can
be unexpected circumstances which may affect you being able
to do so. In such circumstances, you may submit a request for
an extension.
Extension applications must be submitted before the published
assessment deadline has passed.
To apply for an extension, you should access the Extension
System on MyHud.
Extenuating
Circumstances (ECs)
An EC claim is appropriate in exceptional circumstances, when
an extension is not sufficient due to the nature of the request.
You can access details on the procedure for claiming ECs, on
the Registry website; Consideration of Personal Circumstances
- University of Huddersfield, where you can also access the
EC Claim Form.
You will need to submit independent, verifiable evidence for
your claim to be considered.
Once your EC claim has been reviewed you will get an EC
outcome email from Registry.
An approved EC will extend the submission date to the next
assessment period (e.g July resit period).
Late Submission
(No ECs approved)
Late submission, up to 5 working days, of the assessment
submission deadline, will result in your grade being capped to
a maximum of a pass mark.
Submission after this period, without an approved extension,
will result in a 0% grade for this assessment component.
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Additional Guidance
Information
Details
Tutor Referral
available
YES
Resources • Please note: you can access free Office365 software
and you have 500 Gb of free storage space available on
Microsoft’s OneDrive – Guidance on downloading Office
365.
• Python
5
Assignment Title
Computer Cluster and Cloud Project
1. Assignment Aims
The aim of this assignment is to investigate parallel computing / processing using
Python and it is based on practical laboratory work that consist of three distinct
components:
• Test and validation of a serial Python Program to find roots of a Quadratic
Equation.
• Parallel a serial program in the above point using Multiprocessing package
on Python.
• Parallel a serial program in the above point using Joblib package on Python.
• Compare Multiprocessing and Joblib performance on Python to parallel
serial programs.
2. Learning Outcomes:
Knowledge and Understanding Outcomes
2. Examine and compare the parallel computing packages on Python, and assess their
performance, and theoretical speed up of parallel processing applications.
Ability Outcomes
3. Deploy a parallel processing program, using Python, using environment software.
4. Evaluate different Python packages for parallel processing using appropriate
package tools, in order to justify their applicability/non-applicability in running
specific engineering or scientific application.
3. Assessment Brief
This is an individual assignment, assessed by individual laboratory report.
The following serial code (Fig.1) is to find the Roots of a Quadratic Equation. The
mathematical representation of a Quadratic Equation is ax²+bx+c = 0. A Quadratic
Equation can have two roots, and they depend entirely upon the discriminant.
• If discriminant > 0, then Two Distinct Real Roots exist for this equation
• If discriminant = 0, Two Equal and Real Roots exist.
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• And if discriminant < 0, Two Distinct Complex Roots exist
The serial program
Figure.1
Assignment objectives:
• Discuss parallel computing on Python with available different libraries?
• Please specify the difference between process and thread.
• Find out the number of your processors on your computer using the multiprocessing
package.
• Use multiprocessing package to parallel the code in Figure-1 and record the running
time. Hint: You may need to check out the pool.apply function.
• Use joblib package to parallel the code in Figure-1 and record the running time.
• Produce a laboratory report detailing
a. Research on the use of Python for parallel processing.
b. Development of a code using multiprocessing package.
c. Development of a code using joblib package.
d. Performance analysis for the developed programs.
e. Benchmarking – comparison of the developed programs.
4. Marking Scheme
The assignment work will be assessed through laboratory report.
The laboratory report should have a well-defined structure similar to the following:
Organisation and content (70%)
Date, Title
Software Used
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1. Brief Objectives
This should state clearly what the objectives of the laboratory are.
2. Diagrams
Diagram or system sketches.
3. Notes on the procedure used,
4. Programs design and test Results
a. Results obtained from these.
b. Performance comparison.
Discussion (20%)
The discussion section may need to be completed outside the timetabled session
as this section shows if you understand the meaning and limitation of your results.
The contents should cover the following points where appropriate.
a) What can be learned from the results?
b) Do the simulation results agree with the theory or expected results?
c) What are the performances between the two procedures (Packages)?
d) Could the program design be done more accurately or in a better way?
e) Is there any further work which could be done?
Conclusion (10%)
Comments on the results obtained. A paragraph should be adequate for most
sessions.
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5. Grading Rubric
Grading Rubric for NHE2404 DSP Applications Assignment
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