Suresh Aryangat

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Data analysis applications in areas as diverse as remote sensing and telepathology require operating on and processing very large datasets. For such applications to execute efficiently, careful attention must be paid to the storage, retrieval, and manipulation of the datasets. This paper addresses the optimizations performed by a high performance database(More)
This work investigates the leverage that can be obtained from compiler optimization techniques for efficient execution of multi-query workloads in data analysis applications. Our approach is to address multi-query optimization at the algorithmic level, by transforming a declarative specification of scientific data analysis queries into a high-level(More)
Data analysis applications such as Kronos, a remote sensing application, and the Virtual Microscope, a telepathology application, require operating on and processing large datasets. In such situations, it is important that the storage, retrieval, and manipulation of these datasets is efficiently handled. Past research has focused on the creation of database(More)
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