Applied High Performance Computing (MCEN90031)
Graduate courseworkPoints: 12.5Not available in 2023
To learn more, visit 2023 Course and subject delivery.
About this subject
Overview
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The use of physics-based computer simulation is a powerful tool in the scientific and engineering fields that allows for the investigation of phenomena that are often inaccessible by other means. As modern compute architectures continue to increase in terms of parallelism and power, so too can these simulations increase in scale and fidelity, but only when equipped with an understanding of the mathematics and underlying hardware, necessary to leverage this power. This subject will aim to develop such an understanding by tying together key tools and techniques used in the design of scientific software targeted at High Performance Computing (HPC) resources.
This subject will introduce several numerical methods that are ubiquitous in the solution of ordinary differential equations (e.g. Euler and Runge-Kutta methods), partial differential equations (e.g. finite difference and finite element methods), linear systems (e.g. conjugate gradient method), and apply these tools to solve governing equations commonly found in areas such as fluid dynamics and thermodynamics. This subject will investigate the development of software targeting shared memory multicore architectures with OpenMP, distributed memory architectures with MPI, and GPU accelerators with CUDA.
Intended learning outcomes
Having completed this subject the student is expected to:
- 1. Have an understanding of when and how parallelism can be exploited in an algorithm and determine the appropriate approach for implementation
- 2. Be able to apply an appropriate numerical method to solve a partial differential equation and write a program implementing this method
- 3. Have a basic foundational knowledge of the Application Programming Interfaces (APIs) provided by OpenMP, MPI, and CUDA
- 4. Be capable of connecting, compiling, and executing jobs on the University of Melbourne's HPC resource Spartan.
Generic skills
- Ability to apply knowledge of basic science and engineering fundamentals
- Ability to undertake problem identification, formulation and solution
- Capacity for independent critical thought, rational inquiry and self-directed learning.
Last updated: 20 December 2023
Eligibility and requirements
Prerequisites
All of
| Code | Name | Teaching period | Credit Points |
|---|---|---|---|
| COMP20005 | Intro. to Numerical Computation in C |
Semester 2 (On Campus - Parkville)
Semester 1 (On Campus - Parkville)
|
12.5 |
| MAST20029 | Engineering Mathematics |
Summer Term (Dual-Delivery - Parkville)
Semester 1 (On Campus - Parkville)
Semester 2 (On Campus - Parkville)
|
12.5 |
OR
Admission into the MC-MECHENG Master of Mechanical Engineering
OR
Admission into the 100pt Program course entry point in the MC-IT Master of Information Technology
AND
Selection of the Distributed Computing specialisation (formal) in the MC-IT Master of Information Technology
Corequisites
None
Non-allowed subjects
None
Inherent requirements (core participation requirements)
The University of Melbourne is committed to providing students with reasonable adjustments to assessment and participation under the Disability Standards for Education (2005), and the Assessment and Results Policy (MPF1326). Students are expected to meet the core participation requirements for their course. These can be viewed under Entry and Participation Requirements for the course outlines in the Handbook.
Further details on how to seek academic adjustments can be found on the Student Equity and Disability Support website: http://services.unimelb.edu.au/student-equity/home
Last updated: 20 December 2023
Assessment
| Description | Timing | Percentage |
|---|---|---|
Two assignments due in weeks 7 and 12, requiring 35 - 40 hours of work each (30% each).
| From Week 7 to Week 12 | 60% |
Exam, assesses ILOs 1 to 5. | End of semester | 40% |
Last updated: 20 December 2023
Dates & times
Not available in 2023
Time commitment details
200 hours
Last updated: 20 December 2023
Further information
- Texts
- Subject notes
- Related Handbook entries
This subject contributes to the following:
Type Name Course Doctor of Philosophy - Engineering Course Ph.D.- Engineering Course Master of Philosophy - Engineering Specialisation (formal) Mechanical with Business Specialisation (formal) Distributed Computing Specialisation (formal) Mechanical Specialisation (formal) Computing - Available through the Community Access Program
About the Community Access Program (CAP)
This subject is available through the Community Access Program (also called Single Subject Studies) which allows you to enrol in single subjects offered by the University of Melbourne, without the commitment required to complete a whole degree.
Please note Single Subject Studies via Community Access Program is not available to student visa holders or applicants
Entry requirements including prerequisites may apply. Please refer to the CAP applications page for further information.
Additional information for this subject
Subject coordinator approval required
- Available to Study Abroad and/or Study Exchange Students
Last updated: 20 December 2023