ACM40640 High Performance Computing (ICHEC)

Academic Year 2022/2023

This module introduces key topics in high performance computing (HPC), including parallel programming. Prior programming experience; basic knowledge of UNIX/Linux shell is expected.

• Evolution of computer architecture
• High performance computing concepts and scientific applications
• Parallel decomposition
• Shared memory multiprocessing programming (OpenMP)
• The Message Passing Interface (MPI)
• Hybrid programming (OpenMP + MPI)
• Numerical libraries & high performance I/O libraries (e.g. NetCDF, HDF5)
• Introduction to multi-threading accelerators

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Curricular information is subject to change

Learning Outcomes:

Indicative Learning Outcomes:
On successful completion of this module, students should be able to:
• Understand key HPC concepts and how they are applied in scientific research.
• Devise parallel strategies to solve computational problems.
• Develop basic parallel applications using OpenMP and/or MPI.
• Leverage numerical, I/O libraries for better performing code.

Student Effort Hours: 
Student Effort Type Hours


Autonomous Student Learning


Online Learning




Approaches to Teaching and Learning:
Lectures, tutorials, enquiry and problem-based learning 
Requirements, Exclusions and Recommendations

Not applicable to this module.

Module Requisites and Incompatibles
Not applicable to this module.
Assessment Strategy  
Description Timing Open Book Exam Component Scale Must Pass Component % of Final Grade
Assignment: Coding assignments Throughout the Trimester n/a Standard conversion grade scale 40% No


Class Test: Lab-based coding test Unspecified n/a Standard conversion grade scale 40% No


Continuous Assessment: A maximum of 10% will be given for working on "In-class Exercises" throughout the trimester. There is 1% per In-class Exercise and a maximum of twelve will be given in total. Throughout the Trimester n/a Pass/Fail Grade Scale No


Carry forward of passed components
Resit In Terminal Exam
Autumn No
Please see Student Jargon Buster for more information about remediation types and timing. 
Feedback Strategy/Strategies

• Feedback individually to students, post-assessment
• Group/class feedback, post-assessment

How will my Feedback be Delivered?

Not yet recorded.

Name Role
Adam Ralph Lecturer / Co-Lecturer
Assoc Professor Barry Wardell Lecturer / Co-Lecturer
Mr Christopher Werner Lecturer / Co-Lecturer
Dr Nuria Garcia Ordiales Tutor
Mr Andrew Gloster Tutor
Buket Gursoy Tutor
Dr Kenneth Hanley Tutor
Mr Ciaran O'Rourke Tutor
Mr Oisin Robinson Tutor
Mr Jake Williams Tutor
Dr Simon Wong Tutor