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Abstract: This paper presents a general methodology for the efficient parallelization of existing data cube construction algorithms. We describe two different partitioning strategies, one for top-down and one for bottomup cube algorithms. Both partitioning strategies assign subcubes to individual processors in such a way that the loads assigned to the processors are balanced. Our methods reduce inter processor communication overhead by partitioning the load in advance instead of computing each individual ... (Update)
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BibTeX entry: (Update)
F. Dehne, T. Eavis, S. Hambrusch, and A. Rau-Chaplin, "Parallelizing the data cube," Distributed and Parallel Databases, vol. 11, no. 2, pp. 181--201, 2002. 236 CHEN ET AL. http://citeseer.ist.psu.edu/dehne02parallelizing.html More
@article{ dehne01parallelizing,
author = "Frank Dehne and Todd Eavis and Susanne Hambrusch and Andrew Rau-Chaplin",
title = "Parallelizing the Data Cube",
journal = "Lecture Notes in Computer Science",
volume = "1973",
pages = "129--??",
year = "2001",
url = "citeseer.ist.psu.edu/dehne02parallelizing.html" }
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