T. Kurc, U. Catalyurek, C. Chang, A. Sussman, and J. Saltz. Visualization of large datasets with the Active Data Repository. IEEE Computer Graphics and Applications, 21(4):24--33, July/August 2001. Home/Search Document Not in Database Summary Related Articles Check |
This paper is cited in the following contexts:
Exploiting Functional Decomposition for Efficient.. - Andrade, Kurc.. (2002) Self-citation (Kurc Sussman Saltz) (Correct)
....so that it can be used to completely or partially satisfy a new query. We call the use of such projection operations active caching. With this mechanism, the system has a better chance to exploit reuse than with conventional caching. Based on our experience with Kronos and other applications [2, 11, 14, 27], we have identified four kinds of projection primitives based on the type of reuse they can leverage: dimensional overlap, composable reduction operations, invertible functions, and inductive functions. Dimensional (Spatio temporal) Overlap Primitives: In applications dealing with range ....
T. Kurc, U. Catalyurek, C. Chang, A. Sussman, and J. Saltz. Visualization of large datasets with the Active Data Repository. IEEE Computer Graphics and Applications, 21(4):24--33, July/August 2001.
Processing Large-Scale Multidimensional Data in.. - Beynon, Chang.. (2002) (2 citations) Self-citation (Kurc Catalyurek Chang Sussman Saltz) (Correct)
....datasets. Examples of such applications include satellite data processing [24,27,62] full scale water contamination studies and surface subsurface petroleum reservoir simulations [44,66] visualization and processing of digitized microscopy images [3] visualization of largescale data [5,8,29,42,61], and data mining [4,7,34,68] Although the datasets used for analysis and the data products generated by applications that manipulate those datasets may differ in many ways, a close look at many dataintensive applications [17,21,31,42,44] reveals that there exist commonalities in their data ....
.... microscopy images [3] visualization of largescale data [5,8,29,42,61] and data mining [4,7,34,68] Although the datasets used for analysis and the data products generated by applications that manipulate those datasets may differ in many ways, a close look at many dataintensive applications [17,21,31,42,44] reveals that there exist commonalities in their data access patterns and processing structures. Analysis requires extracting the data of interest from the dataset, and processing and transforming it into a new data product that can be more efficiently consumed by another program or analyzed by a ....
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T. Kurc, U. Catalyurek, C. Chang, A. Sussman, and J. Saltz. Visualization of large datasets with the Active Data Repository. IEEE Computer Graphics and Applications, 21(4):24--33, July/August 2001.
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