{"product_id":"processing-large-remote-sensing-image-data-sets-on-beowulf-clusters-open-file-report-2003-216-9781288745883","title":"Processing Large Remote Sensing Image Data Sets on Beowulf Clusters: Open-File Report 2003-216","description":"\u003cp\u003e • Author(s): United U. S. Department of the Interior | Et Al | Daniel R. Steinwand\u003cbr\u003e • Publisher: Bibliogov\u003cbr\u003e • Publisher Imprint: Bibliogov\u003cbr\u003e • BISAC: General\u003c\/p\u003e\u003cp\u003eHigh-performance computing is often concerned with the speed at which floating- point calculations can be performed. The architectures of many parallel computers and\/or their network topologies are based on these investigations. Often, benchmarks resulting from these investigations are compiled with little regard to how a large dataset would move about in these systems. This part of the Beowulf study addresses that concern by looking at specific applications software and system-level modifications. Applications include an implementation of a smoothing filter for time-series data, a parallel implementation of the decision tree algorithm used in the Landcover Characterization project, a parallel Kriging algorithm used to fit point data collected in the field on invasive species to a regular grid, and modifications to the Beowulf project's resampling algorithm to handle larger, higher resolution datasets at a national scale. Systems-level investigations include a feasibility study on Flat Neighborhood Networks and modifications of that concept with Parallel File Systems.\u003c\/p\u003e","brand":"Bibliogov","offers":[{"title":"Paperback","offer_id":47598139179159,"sku":"9781288745883","price":1429.0,"currency_code":"INR","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0666\/3471\/1191\/files\/9781288745883.webp?v=1774999819","url":"https:\/\/atlanticbooks.com\/products\/processing-large-remote-sensing-image-data-sets-on-beowulf-clusters-open-file-report-2003-216-9781288745883","provider":"Atlantic Books","version":"1.0","type":"link"}