NDLI: Materialized community ground models for large-scale earthquake simulation

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Materialized community ground models for large-scale earthquake simulation

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Materialized community ground models for large-scale earthquake simulation

Content Provider	ACM Digital Library
Author	López, Julio Schlosser, Steven W. Bielak, Jacobo Taborda, Ricardo Ryan, Michael P. O'Hallaron, David R.
Abstract	Large-scale earthquake simulation requires source datasets which describe the highly heterogeneous physical characteristics of the earth in the region under simulation. Physical characteristic datasets are the first stage in a simulation pipeline which includes mesh generation, partitioning, solving, and visualization. In practice, the data is produced in an ad-hoc fashion for each set of experiments, which has several significant shortcomings including lower performance, decreased repeatability and comparability, and a longer time to science, an increasingly important metric. As a solution to these problems, we propose a new approach for providing scientific data to ground motion simulations, in which ground model datasets are fully materialized into octress stored on disk, which can be more efficiently queried (by up to two orders of magnitude) than the underlying community velocity model programs. While octrees have long been used to store spatial datasets, they have not yet been used at the scale we propose. We further propose that these datasets can be provided as a service, either over the Internet or, more likely, in a datacenter or supercomputing center in which the simulations take place. Since constructing these octrees is itself a challenge, we present three data-parallel techniques for efficiently building them, which can significantly decrease the build time from days or weeks to hours using commodity clusters. This approach typifies a broader shift toward science as a service techniques in which scientific computation and storage services become more tightly intertwined.
Starting Page	1
Ending Page	12
Page Count	12
File Format	PDF
ISBN	9781424428359
Language	English
Publisher	Association for Computing Machinery (ACM)
Publisher Date	2008-11-15
Access Restriction	Subscribed
Content Type	Text
Resource Type	Article

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4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
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