Authors / CoAuthors
Evans, B. | Wyborn, L.A.I. | Pugh, T. | Allen, C. | Antony, J. | Gohar, K. | Porter, D. | Smillie, J. | Trenham, C. | Wang, J. | Ip, A. | Bell, G.
Abstract
The National Computational Infrastructure (NCI) at the Australian National University (ANU) has co-located a priority set of over 10 PetaBytes (PBytes) of national data collections within a HPC research facility. The facility provides an integrated high-performance computational and storage platform, or a High Performance Data (HPD) platform, to serve and analyse the massive amounts of data across the spectrum of environmental collections in particular from the climate, environmental and geoscientific domains. The data is managed in concert with the government agencies, major academic research communities and collaborating overseas organisations. By co-locating the vast data collections with high performance computing environments and harmonising these large valuable data assets, new opportunities have arisen for Data-Intensive interdisciplinary science at scales and resolutions not hitherto possible.
Product Type
nonGeographicDataset
eCat Id
83074
Contact for the resource
Custodian
Owner
Custodian
Cnr Jerrabomberra Ave and Hindmarsh Dr GPO Box 378
Canberra
ACT
2601
Australia
Keywords
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- External PublicationArticle
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- High Performance Computing
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- High Performance Data
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- Cloud Computing
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- Data-Intensive Science
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- scalable data services
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- data collections
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- datasets
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- data cube
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- virtual laboratories
- Australian and New Zealand Standard Research Classification (ANZSRC)
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- Information and Computing Sciences
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- Published_Internal
Publication Date
2015-01-01T00:00:00
Creation Date
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notPlanned
Topic Category
geoscientificInformation
Series Information
Lineage
This paper was written for ISESS and examines the data collections, the underlying High Performance Data (HPD) infrastructure, the management of trusted environments, and opportunities and challenges that this new research platform at NCI offers.
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Extents
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Source Information
This paper was written for ISESS and examines the data collections