@conference {17880, title = {Optimizing retrieval and processing of multi-dimensional scientific datasets}, booktitle = {Parallel and Distributed Processing Symposium, 2000. IPDPS 2000. Proceedings. 14th International}, year = {2000}, month = {2000///}, pages = {405 - 410}, publisher = {IEEE}, organization = {IEEE}, abstract = {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}, keywords = {active data repository, Area measurement, Computer science, Data analysis, distributed memory parallel machines, Educational institutions, Information retrieval, Information Storage and Retrieval, infrastructure, Microscopy, Microwave integrated circuits, multi-dimensional scientific datasets retrieval, PARALLEL PROCESSING, Pathology, range queries, regular d-dimensional array, Satellites, Tomography}, isbn = {0-7695-0574-0}, doi = {10.1109/IPDPS.2000.846013}, author = {Chang,Chialin and Kurc, T. and Sussman, Alan and Saltz, J.} } @conference {17896, title = {Efficient runtime support for parallelizing block structured applications}, booktitle = {Scalable High-Performance Computing Conference, 1994., Proceedings of the}, year = {1994}, month = {1994/05//}, pages = {158 - 167}, abstract = {Scientific and engineering applications often involve structured meshes. These meshes may be nested (for multigrid codes) and/or irregularly coupled (called multiblock or irregularly coupled regular mesh problems). We describe a runtime library for parallelizing these applications on distributed memory parallel machines in an efficient and machine-independent fashion. This runtime library is implemented on several different systems. This library can be used by application programmers to port applications by hand and can also be used by a compiler to handle communication for these applications. Our experimental results show that our primitives have low runtime communication overheads. We have used this library to port a multiblock template and a multigrid code. Effort is also underway to port a complete multiblock computational fluid dynamics code using our library}, keywords = {application programmers, block structured applications, distributed memory parallel machines, distributed memory systems, engineering applications, irregularly coupled regular mesh problems, machine-independent, multiblock, multiblock computational fluid dynamics code, multiblock template, multigrid codes, Parallel machines, parallel programming, Physics computing, runtime communication overhead, Runtime library, runtime support, scientific applications, software reusability, structured meshes}, doi = {10.1109/SHPCC.1994.296639}, author = {Agrawal,G. and Sussman, Alan and Saltz, J.} }