NEW CASE STUDY: An international research group is harnessing the power of big data, supercomputing and global research network infrastructure to transform the way we model the Earth’s processes.
The Basin GENESIS Hub project, led by the EarthByte Group at the School of Geosciences at the University of Sydney, is carrying out research that helps explain how sedimentary basins have formed and changed over hundreds of millions of years.
With project partners including the California Institute of Technology, Curtin University, University of Melbourne and Geoscience Australia, the researchers are gauging the resource and energy potential of individual sedimentary basins on the north-west shelf of Australia, Papua New Guinea and the Atlantic Ocean continental margins.
The researchers are using open-source software to model planetary processes over tens of millions of years in 5D – layering time and estimates of uncertainty on top of 3D. Visualisation software is then applied to the analysis to create 4D animations that demonstrate the results.
The project’s modelling is extremely data intensive: for example, their mantle convection models go back 410 million years, and require large input files in 1 million year intervals – such as plate velocities, age of seafloor and continents. These huge data sets must be shared between project partners for analysis.
To manage such large volumes of data, the project relies on some of the most powerful network and computing resources available in the world today.
Thanks to research and education networks, high-speed connections link the national and international nodes, as well as the main supercomputer resource at the National Computational Infrastructure (NCI) facility, located at the Australian National University.
In Australia, the University of Sydney and the NCI supercomputing facility are both connected to AARNet, whose national and international connectivity helps ensure seamless and reliable connectivity between the nodes.
AARNet’s Cloudstor service then provides the project with a solution for sharing large raw datasets, model outputs and visualisations with international colleagues.
Dr Sabin Zahirovic, a Post-Doctoral Researcher at the University of Sydney, explains how the international collaboration relies on Cloudstor.
“CloudStor is essential for sharing very large files – ones that would be impossible to send in e-mail, and would very quickly clog up other cloud-based accounts. As CloudStor is part of the AARNet network, I can very quickly upload huge files, and then conveniently send a plain hyperlink to collaborators.”
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