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Research digital skills training 2021

Research Computing

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Contact

For queries related to Research Virtual Machines, contact us at:
research-vm@auckland.ac.nz
or find out more information on the ResearchHub.

Access to advanced computing infrastructure becomes more and more important for state-of-the-art research even in domains where it was not required just a few years ago, like the social sciences or the medical sciences. The Centre offers and facilitates access to several research computing services as well as consulting to help figure out which service is most suitable for your problem. Available services are High Performance Computing (HPC), virtual machines, cloud resources, and machine learning.

Research Virtual Machines

Many researchers need specialised computing facilities that support a variety of different operating systems, allow interactive use rather than relying on a typical HPC batch scheduler, and run for extended periods of time (days to months). The Centre for eResearch, in collaboration with Faculty IT departments, supports the user-facing configuration, software installation, and development of virtual machines (VMs) for computationally intensive research and research-led teaching. ITS host the hardware in a managed VM Farm and provide the networking. Together, the combined expertise helps researchers make the best usage of these systems.

 
 

Nectar Research Cloud

Nectar Cloud provides a self-service computing infrastructure giving you access to your data and applications at any time, and the ability to collaborate with others from your desktop in a fast and efficient way. “The University of Auckland is undertaking a pilot programme to provide a New Zealand hosted research cloud based on the Australian National eResearch Collaboration Tools and Resources ([Nectar](https://nectar.org.au/)) approach.

Nectar Research Cloud provides a secure platform to access computing resources and cloud storage and collaborate without the need for researchers to purchase or host their own hardware. An ‘instance’ in the Research Cloud is a virtual machine (VM), which is just like a real-life machine with an operating system, network access, and hard disk storage, only running in a remote location. Instances can be copied, modified or shared, and are available in many different configurations of CPU, GPU, RAM, and storage size. Nectar Research Cloud is provided free of charge to users.

NeSI High Performance Computing

The University of Auckland is part of the national investors in the New Zealand eScience Infrastructure (NeSI) High Performance Computing (HPC), also known as supercomputing, which allows New Zealand researchers to tackle large, difficult problems and conduct research investigations much faster.  To find out more about the HPC platform and services, please follow the link to NeSI.
 
 

Machine Learning

The Centre for eResearch (CeR) manages access to several computing systems suitable for machine learning. We can advise on the most suitable systems to use depending on your experience. For those researchers who want to experiment and learn about machine learning, we can provide Jupyter Notebook environments with common software frameworks such as TensorFlow and Keras installed with shared access to GPUs. Find out more about machine learning on the Research Hub.
 

Case studies of research computing

Hosting visualisation and analytics tools for COVID-19 studies

The Centre for eResearch is actively supporting several COVID-19 related projects at the University and on the national level during 2020 pandemic.

​Anti-corruption regulations for promoting socially responsible practices

Corruption, the abuse of public power for private gain, is considered to be the norm rather than the exception around the world and is highly unreported and difficult to track.

Develop short-term eruption warning systems for Whakaari and other volcanoes

On 9th December 2019, at 2pm, Whakaari volcano erupted unexpectedly, killing 21 tourists and guides on the island.

Genomic Virtual Lab (GVL) as a bioinformatics training platform

Genomics Virtual Laboratory is a web portal provides a growing suite of genomics analysis tools, the biologists can start working immediately with no setup required.

Skin-omics: exploring the volatile organic compounds on human skin

Skin is the largest organ of the human body. Its importance in health has only just begun to be investigated. There are hundreds of compounds on the skin surface, and they have the potential to answer many questions. These compounds can be used for diagnosis, monitoring pollutant exposure, and for understanding the skin microbiome.

Improving arrival time predictions for vehicles in a public transport network

In recent years, vehicle tracking technologies (GPS) have advanced along with communication technologies (internet, mobile apps) to the point where public transport users can see the real-time location of their buses on a map through their phones.

MFT-ICR mass spectrometry data management and analysis workflow

Mass spectrometry (MS) is an analytical technique that ionizes chemical species and sorts the ions based on their mass-to-charge ratio (m/z). In addition to the m/z value, the natural abundance of atomic isotopes provides a unique fingerprint for each ion.

Building a discrete global grid gazetteer service

A geodesic discrete global grid is a partitioning of the surface of the globe into a grid of equal area cells. An indexed hierarchy of grids at multiple interrelated levels of resolution is called a discrete global grid system (DGGS).

Shedding new light on dark matter

Professor Richard Easther from Physics Department has been asking questions about the universe for more than 20 years. He’s uncovered just as many new questions as answers in that time. “The universe is continually making space between the galaxies,” says Easther. “The explosion that started our universe is still making space today.”

Using GPUs to expand our understanding of the Solar System

Dr Sharp is collaborating with William Newman, a Professor in Physics & Astronomy at UCLA, to investigate whether the Nice model, the leading model for the Solar System’s evolution, accurately predicts the present day orbits of the giant planets, Jupiter, Saturn, Uranus and Neptune.