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Title: Cyber-Infrastructure for Data-Intensive Geospatial Computing

Abstract

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 andmore » technologically sustainable for continued support of the US energy and environment mission for the coming decades.« less


Citation Formats

Karthik, Rajasekar, Sorokine, Alexandre, Patlolla, Dilip Reddy, Liu, Cheng, Gupte, Shweta M., and Bhaduri, Budhendra L. Cyber-Infrastructure for Data-Intensive Geospatial Computing. United States: N. p., 2018. Web. doi:10.1007/978-3-319-65633-5_7.
Karthik, Rajasekar, Sorokine, Alexandre, Patlolla, Dilip Reddy, Liu, Cheng, Gupte, Shweta M., & Bhaduri, Budhendra L. Cyber-Infrastructure for Data-Intensive Geospatial Computing. United States. doi:10.1007/978-3-319-65633-5_7.
Karthik, Rajasekar, Sorokine, Alexandre, Patlolla, Dilip Reddy, Liu, Cheng, Gupte, Shweta M., and Bhaduri, Budhendra L. Mon . "Cyber-Infrastructure for Data-Intensive Geospatial Computing". United States. doi:10.1007/978-3-319-65633-5_7.
@article{osti_1462906,
title = {Cyber-Infrastructure for Data-Intensive Geospatial Computing},
author = {Karthik, Rajasekar and Sorokine, Alexandre and Patlolla, Dilip Reddy and Liu, Cheng and Gupte, Shweta M. and Bhaduri, Budhendra L.},
abstractNote = {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.},
doi = {10.1007/978-3-319-65633-5_7},
journal = {},
number = ,
volume = ,
place = {United States},
year = {2018},
month = {1}
}

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