Cyber-Infrastructure for Data-Intensive Geospatial Computing
- ORNL
With the recent advent of heterogeneous High-performance Computing (HPC) to handle EO “Big Data” workloads, there is a need for a unified Cyber-infrastructure (CI) platform that can bridge the best of many HPC worlds. In this chapter, we discuss such a CI platform being developed at Geographic Information Science and Technology (GIST) group using novel and innovative techniques, and emerging technologies that are scalable to large-scale supercomputers. The CI platform utilizes a wide variety of computing such as GPGPU, distributed, real-time and cluster computing, which are being brought together architecturally to enable data-driven analysis, scientific understanding of earth system models, and research collaboration. This development addresses the need for close integration of EO and other geospatial information in the face of growing volumes of the data, and facilitates spatio-temporal analysis of disparate and dynamic data streams. Horizontal scalability and linear throughput are supported in the heart of the platform itself. It is being used to support very broad application areas, ranging from high-resolution settlement mapping, national bioenergy infrastructure to urban information and mobility systems. The platform provides spatio-temporal decision support capabilities in planning, policy and operational missions for US federal agencies. Also, the platform is designed to be functionally and technologically sustainable for continued support of the US energy and environment mission for the coming decades.
- Research Organization:
- Oak Ridge National Laboratory (ORNL), Oak Ridge, TN (United States)
- Sponsoring Organization:
- USDOE
- DOE Contract Number:
- AC05-00OR22725
- OSTI ID:
- 1462906
- Country of Publication:
- United States
- Language:
- English
Emerging trends in monitoring landscapes and energy infrastructures with big spatial data
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journal | April 2015 |
iGlobe
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conference | January 2011 |
Data science and cyberinfrastructure: critical enablers for accelerated development of hierarchical materials
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journal | October 2014 |
Same4hpc
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conference | November 2014 |
Accelerating satellite image based large-scale settlement detection with GPU
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conference | January 2012 |
TRANSIMS: Transportation analysis and simulation system | report | July 1995 |
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