The Weather Research Forecasting (WRF) domain consists of complex workflows that demand the use of Distributed Computing Infrastructure (DCI). Weather forecasting requires that weather researchers use different set of initial conditions and one or a combination of physics models on the same set of input data. For these type of simulations an ensemble based computing approach becomes imperative. Most DCIs have local job-schedulers that have no smart way of dealing with the execution of an ensemble type of computational problem as the job-schedulers are built to cater to the bare essentials of resource allocation. This means the weather scientists have to submit multiple jobs to the job-scheduler. In this dissertation we use Pilot-Job based tools to decouple work-load submission and resource allocation therefore streamlining the complex workflows in Weather Research and Forecasting domain and reduce their overall time to completion. We also achieve location independent job execution, data movement, placement and processing. Next, we create the necessary enablers to run an ensemble of tasks bearing the capability to run on multiple heterogeneous distributed computing resources there by creating the opportunity to minimize the overall time consumed in running the models. Our experiments show that the tools developed exhibit very good, strong and weak scaling characteristics. These results bear the potential to change the way weather researchers are submitting traditional WRF jobs to the DCIs by giving them a powerful weapon in their arsenal that can exploit the combined power of various heterogeneous DCIs that could otherwise be difficult to harness owing to interoperability issues.
Subject (authority = RUETD)
Topic
Electrical and Computer Engineering
RelatedItem (type = host)
TitleInfo
Title
Rutgers University Electronic Theses and Dissertations
Identifier (type = RULIB)
ETD
Identifier
ETD_6083
PhysicalDescription
Form (authority = gmd)
electronic resource
InternetMediaType
application/pdf
InternetMediaType
text/xml
Extent
1 online resource (x, 40 p. : ill.)
Note (type = degree)
M.S.
Note (type = bibliography)
Includes bibliographical references
Subject (authority = ETD-LCSH)
Topic
Weather forecasting
Subject (authority = ETD-LCSH)
Topic
Cyberinfrastructure
Subject (authority = ETD-LCSH)
Topic
Computer networks
Note (type = statement of responsibility)
by Dinesh Prasanth Ganapathi
RelatedItem (type = host)
TitleInfo
Title
Graduate School - New Brunswick Electronic Theses and Dissertations
Identifier (type = local)
rucore19991600001
Location
PhysicalLocation (authority = marcorg); (displayLabel = Rutgers, The State University of New Jersey)
Rutgers University. Graduate School - New Brunswick
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Type
License
Name
Author Agreement License
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