1,411 research outputs found
MPWide: a light-weight library for efficient message passing over wide area networks
We present MPWide, a light weight communication library which allows
efficient message passing over a distributed network. MPWide has been designed
to connect application running on distributed (super)computing resources, and
to maximize the communication performance on wide area networks for those
without administrative privileges. It can be used to provide message-passing
between application, move files, and make very fast connections in
client-server environments. MPWide has already been applied to enable
distributed cosmological simulations across up to four supercomputers on two
continents, and to couple two different bloodflow simulations to form a
multiscale simulation.Comment: accepted by the Journal Of Open Research Software, 13 pages, 4
figures, 1 tabl
A CyberGIS Integration and Computation Framework for High‐Resolution Continental‐Scale Flood Inundation Mapping
We present a Digital Elevation Model (DEM)-based hydrologic analysis methodology for continental flood inundation mapping (CFIM), implemented as a cyberGIS scientific workflow in which a 1/3rd arc-second (10m) Height Above Nearest Drainage (HAND) raster data for the conterminous U.S. (CONUS) was computed and employed for subsequent inundation mapping. A cyberGIS framework was developed to enable spatiotemporal integration and scalable computing of the entire inundation mapping process on a hybrid supercomputing architecture. The first 1/3rd arc-second CONUS HAND raster dataset was computed in 1.5 days on the CyberGIS ROGER supercomputer. The inundation mapping process developed in our exploratory study couples HAND with National Water Model (NWM) forecast data to enable near real-time inundation forecasts for CONUS. The computational performance of HAND and the inundation mapping process was profiled to gain insights into the computational characteristics in high-performance parallel computing scenarios. The establishment of the CFIM computational framework has broad and significant research implications that may lead to further development and improvement of flood inundation mapping methodologies
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