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Curricular information is subject to change
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 Type||Hours|
|Autonomous Student Learning||
Not applicable to this module.
|Description||Timing||Component Scale||% 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||
|Resit In||Terminal Exam|
• Feedback individually to students, post-assessment
• Group/class feedback, post-assessment
Not yet recorded.
|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|
|Dr Kenneth Hanley||Tutor|
|Mr Ciaran O'Rourke||Tutor|
|Mr Oisin Robinson||Tutor|
|Mr Jake Williams||Tutor|
|Dr Simon Wong||Tutor|