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Abstract: Applications that make use of very large scientific datasets have become an increasingly important subset of scientific applications. In these applications, datasets are often multi-dimensional, i.e., data items are associated with points in a multi-dimensional attribute space, and access to data items is described by range queries. The basic processing involves mapping input data items to output data items, and some form of aggregation of all the input data items that project to the each... (Update)
Context of citations to this paper: More
...[28, 29] describe an architecture for op6 timizing access to large volumes of scientific data stored on tapes. The Active Data Repository [17] and DataCutter [4] optimize storage, retrieval, and processing of very large multidimensional datasets. The main difference between our...
.... storage and processing of multi perspective images, we employ an object oriented framework called the Active Data Repository (ADR) [3, 4, 7, 8], that has been developed at the University of Maryland for managing and processing large amounts of scientific data on a parallel...
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BibTeX entry: (Update)
T. Kurc, C. Chang, R. Ferreira, A. Sussman, and J. Saltz. Querying very large multi-dimensional datasets in ADR. Technical Report CS-TR-4022 and UMIACS-TR-99-29, Universityof Maryland, Department of Computer Science and UMIACS, May 1999. To appear in SC'99. http://citeseer.ist.psu.edu/article/kurc99querying.html More
@inproceedings{ kurc99querying,
author = "Tahsin Kurc and Chialin Chang and Renato Ferreira and Alan Sussman",
title = "Querying Very Large Multi-dimensional Datasets in {ADR}",
booktitle = "Proceedings of SC99: High Performance Networking and Computing",
publisher = "ACM Press and IEEE Computer Society Press",
address = "Portland, OR",
year = "1999",
url = "citeseer.ist.psu.edu/article/kurc99querying.html" }
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