The Deep-Tree Approach: An Improved Parallel Matlab Implementation of the Multi-resolution Approximation for Massive Spatial Data on High-Performance Computing Systems

We implement a parallel version of the Multi-resolution Approximation (MRA) in Matlab for distributed computing environments. This implementation builds upon and improves our previous Shallow-Tree approach, facilitating computations with data sets on the order of 50 million observations while reducing execution times by up to 75%. We observe less sensitivity to computing cluster and model parameter settings allowing for more flexible specification.

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Author Blake, Lewis R.
Huang, Huang
Vanderwende, Brian
Hammerling, Dorit M.
Publisher UCAR/NCAR - Library
Publication Date 2021-05-17T00:00:00
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Topic Category geoscientificInformation
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Metadata Date 2023-08-18T18:06:39.274161
Metadata Record Identifier edu.ucar.opensky::technotes:586
Metadata Language eng; USA
Suggested Citation Blake, Lewis R., Huang, Huang, Vanderwende, Brian, Hammerling, Dorit M.. (2021). The Deep-Tree Approach: An Improved Parallel Matlab Implementation of the Multi-resolution Approximation for Massive Spatial Data on High-Performance Computing Systems. UCAR/NCAR - Library. http://n2t.net/ark:/85065/d7dj5k1r. Accessed 25 June 2025.

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