Optimal Compressed Sensing and Reconstruction of Unstructured Mesh Datasets

Optimal Compressed Sensing and Reconstruction of Unstructured Mesh Datasets

Abstract Exascale computing promises quantities of data too large to efficiently store and transfer across networks in order to be able to analyze and visualize the results. We investigate compressed sensing (CS) as an in situ method to reduce the size of the data as it is being generated during a l...

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Bibliographic Details
Main Authors: Maher Salloum, Nathan D. Fabian, David M. Hensinger, Jina Lee, Elizabeth M. Allendorf, Ankit Bhagatwala, Myra L. Blaylock, Jacqueline H. Chen, Jeremy A. Templeton, Irina Tezaur
Format: Article
Language:English
Published: SpringerOpen 2017-08-01
Series:Data Science and Engineering
Subjects:
Compressed sensing
Tree wavelets
Compression
In situ
Large-scale simulation
Unstructured mesh
Online Access:http://link.springer.com/article/10.1007/s41019-017-0042-4

Internet

http://link.springer.com/article/10.1007/s41019-017-0042-4

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