Supercomputing Enabled Deployable Analytics for Disaster Response Article Swipe
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· 2021
· Open Access
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· DOI: https://doi.org/10.1109/hpec49654.2021.9622808
· OA: W3196232779
First responders and other forward deployed essential workers can benefit\nfrom advanced analytics. Limited network access and software security\nrequirements prevent the usage of standard cloud based microservice analytic\nplatforms that are typically used in industry. One solution is to precompute a\nwide range of analytics as files that can be used with standard preinstalled\nsoftware that does not require network access or additional software and can\nrun on a wide range of legacy hardware. In response to the COVID-19 pandemic,\nthis approach was tested for providing geo-spatial census data to allow quick\nanalysis of demographic data for better responding to emergencies. These data\nwere processed using the MIT SuperCloud to create several thousand Google Earth\nand Microsoft Excel files representative of many advanced analytics. The fast\nmapping of census data using Google Earth and Microsoft Excel has the potential\nto give emergency responders a powerful tool to improve emergency preparedness.\nOur approach displays relevant census data (total population, population under\n15, population over 65, median age) per census block, sorted by county, through\na Microsoft Excel spreadsheet (xlsx file) and Google Earth map (kml file). The\nspreadsheet interface includes features that allow users to convert between\ndifferent longitude and latitude coordinate units. For the Google Earth files,\na variety of absolute and relative colors maps of population density have been\nexplored to provide an intuitive and meaningful interface. Using several\nhundred cores on the MIT SuperCloud, new analytics can be generated in a few\nminutes.\n
