TY - JOUR T1 - Visualization of large data sets with the Active Data Repository JF - IEEE Computer Graphics and Applications Y1 - 2001 A1 - Kurc, T. A1 - Catalyurek,U. A1 - Chang,Chialin A1 - Sussman, Alan A1 - Saltz, J. KW - active data repository KW - ADR runtime system KW - Algorithm design and analysis KW - application-specific processing KW - C++ KW - data mining KW - data retrieval KW - data visualisation KW - Data visualization KW - distributed-memory parallel machines KW - Indexing KW - Information retrieval KW - isosurface rendering KW - Isosurfaces KW - large data sets KW - large-scale multidimensional data KW - Memory management KW - modular services KW - out-of-core data sets KW - parallel machine KW - Parallel machines KW - Partitioning algorithms KW - ray-casting-based volume rendering KW - Rendering (computer graphics) KW - Runtime KW - software libraries KW - storage management AB - We implement ray-casting-based volume rendering and isosurface rendering methods using the Active Data Repository (ADR) for visualizing out-of-core data sets. We have developed the ADR object-oriented framework to provide support for applications that employ range queries with user-defined mapping and aggregation operations on large-scale multidimensional data. ADR targets distributed-memory parallel machines with one or more disks attached to each node. It is designed as a set of modular services implemented in C++, which can be customized for application-specific processing. The ADR runtime system supports common operations such as memory management, data retrieval, and scheduling of processing across a parallel machine VL - 21 SN - 0272-1716 CP - 4 M3 - 10.1109/38.933521 ER - TY - CONF T1 - Optimizing retrieval and processing of multi-dimensional scientific datasets T2 - Parallel and Distributed Processing Symposium, 2000. IPDPS 2000. Proceedings. 14th International Y1 - 2000 A1 - Chang,Chialin A1 - Kurc, T. A1 - Sussman, Alan A1 - Saltz, J. KW - active data repository KW - Area measurement KW - Computer science KW - Data analysis KW - distributed memory parallel machines KW - Educational institutions KW - Information retrieval KW - Information Storage and Retrieval KW - infrastructure KW - Microscopy KW - Microwave integrated circuits KW - multi-dimensional scientific datasets retrieval KW - PARALLEL PROCESSING KW - Pathology KW - range queries KW - regular d-dimensional array KW - Satellites KW - Tomography AB - We have developed the Active Data Repository (ADR), an infrastructure that integrates storage, retrieval, and processing of large multi-dimensional scientific datasets on distributed memory parallel machines with multiple disks attached to each node. In earlier work, we proposed three strategies for processing range queries within the ADR framework. Our experimental results show that the relative performance of the strategies changes under varying application characteristics and machine configurations. In this work we investigate approaches to guide and automate the selection of the best strategy for a given application and machine configuration. We describe analytical models to predict the relative performance of the strategies where input data elements are uniformly distributed in the attribute space of the output dataset, restricting the output dataset to be a regular d-dimensional array JA - Parallel and Distributed Processing Symposium, 2000. IPDPS 2000. Proceedings. 14th International PB - IEEE SN - 0-7695-0574-0 M3 - 10.1109/IPDPS.2000.846013 ER -