The NeCTAR Research Cloud expects a large expansion in 2014 with capacity trebling to around 30,000 CPU cores thanks to more research cloud nodes joining the federated effort and existing cloud nodes expanding their offerings.
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Characterisation Virtual Laboratory
The “21st century microscope” will not be a single instrument; rather it will be an orchestration of specialised imaging technologies, data storage facilities, and specialised data processing engines. The Characterisation Virtual Laboratory will be a powerful platform essential to the future capability of Australian scientists by integrating Australia’s research imaging facilities with computational and data storage infrastructure and tools.
Australian scientists are increasingly using characterisation technologies that enable: higher spatial resolution and chemical resolution; higher dimensional (>3D) approaches; and examination of rapid dynamic processes. To make effective use of these capabilities, researchers must have easy access to a wide collection of sophisticated processing and analysis tools, packaged and accessible in a recognisable manner, and including research enablers such as standard test data and libraries.
The Characterisation Virtual Laboratory (CVL) will:
- integrate Australia’s imaging equipment with specialised HPC capabilities and with data collection nodes,
- provide scientists with a common environment for analysis and collaboration, and
- will be developed around three research application (‘drivers’) in multi-modal or large-scale imaging in neuroscience, structural biology, and energy materials.
Each driver is being led by a world-class research group, is supported by an Australian research consortium and is in a national research priority area. The results from this development will be distributed to the community through CVL “Workbenches”.
Micro MRI and X-Ray Computed Tomography (CT) imaging has now progressed to the point where resolutions of 15um are becoming routine, typically in excised tissue. This has allowed the prospect of combining histological staining information with the MRI contrast to gain unique insights into the correlations in contrast between imaging at a micro and macro scale within a single individual. This technique has wide ranging applications to neuroscience. However, to allow this technique to be widely applied, it requires integration of microscopy and MRI data, immense computational power, and a range of specialised software tools and workflows. These components will be integrated and made available through the Neuroimaging Workbench.
Clean sources of portable, transportable and fixed energy require the creation of new materials to deliver ‘green’ energy. This initiative recognises that there exist design challenges for energy materials that transcend a wide range of length scales, from the mesoscale through to the nanoscale. The physics of wave scattering via X-rays, electrons, or ion beams requires fundamentally different techniques to generate tomographic data, depending on the length scale of interest. Our efforts will integrate an environment that enables tomographic insights across the continuum of relevant length scales and so be of wide interest to this burgeoning research community. Through this initiative scientists will be able to exploit the power of X-ray tomography to explore mesoporous architecture in materials (where the tailoring of pore size is a crucial requirement for their catalytic performance), and to exploit the power of atom probe tomography to generate tomographic information at the nanoscale – and ultimately, at atomic resolution. In this way, the Energy Materials Workbench will leverage from recent breakthrough science, and gather existing programs, algorithms and codes, to integrate the analyses and render the data. The sizable research community includes materials scientists, chemists and engineers.
The resolution of single-particle cryo-EM tomography has dramatically improved in the last couple of years and is now an essential technique for structural biology research. In contrast to Nuclear Magnetic Resonance (NMR) and X-ray crystallography, cryo-EM allows for the analysis of large complex structures that are either too large for NMR or are difficult to crystallise. It is most powerful if used in conjunction with X-ray data of smaller domains of a protein or single proteins of a protein complex that can be fitted into the higher order structure obtained by single-particle cryo-EM. The Structural Biology Workbench will develop, from existing tools, a platform for integrating cryo-EM and crystallography data.
Professor Paul Bonnington
Director - Monash e-Research Centre