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Abstract: Processing and analyzing large volumes of data plays an increasingly important role in many domains of scientific research. The complexity and irregularity of datasets in many domains make the task of developing such processing applications tedious and error-prone. (Update)
Context of citations to this paper: More
...powerful restructuring transformations can be applied. Particularly, the code resulting after applying data centric transformation [16, 21] will only require a single pass on the entire dataset. Thus, the first three key compiler analysis and transformation tasks are: 1)...
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6: Titan: a highperformance remote-sensing database - Chang, Moon et al. - 1997
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BibTeX entry: (Update)
Renato Ferreira, Gagan Agrawal, and Joel Saltz. Compiler supported high-level abstractions for sparse diskresident datasets. Submitted for publication, available at http://www/eecis.udel.edu/agrawal/p/ics01 renato.ps, 2001. http://citeseer.ist.psu.edu/ferreira01compiler.html More
@misc{ ferreira01compiler,
author = "R. Ferreira and G. Agrawal and J. Saltz",
title = "Compiler supported high-level abstractions for sparse diskresident datasets",
text = "Renato Ferreira, Gagan Agrawal, and Joel Saltz. Compiler supported high-level
abstractions for sparse diskresident datasets. Submitted for publication,
available at http://www/eecis.udel.edu/agrawal/p/ics01 renato.ps, 2001.",
year = "2001",
url = "citeseer.ist.psu.edu/ferreira01compiler.html" }
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