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Please use this identifier to cite or link to this item: http://hdl.handle.net/1860/307

Title: Optimal caching of large multi-dimensional datasets
Authors: Obalappa, Dinesh
Keywords: Electrical and computer engineering;Cache memory;Multidimensional databases
Issue Date: 9-Jun-2004
Abstract: We propose a novel organization for multi-dimensional data based on the concept of macro-voxels. This organization improves computer performance by enhancing spatial and temporal locality. Caching of macro-voxels not only reduces the required storage space but also leads to an efficient organization of the dataset resulting in faster data access. We have developed a macro-voxel caching theory that predicts the optimal macro-voxel sizes required for minimum cache size and access time. The model also identifies a region of trade-off between time and storage, which can be exploited in making an efficient choice of macro-voxel size for this scheme. Based on the macro-voxel caching model, we have implemented a macro-voxel I/O layer in C, intended to be used as an interface between applications and datasets. It is capable of both scattered access, typical in online applications, and row/column access, typical in batched applications. We integrated this I/O layer in the ALIGN program (online application) which aligns images based on 3D distance maps; this improved access time by a factor of 3 when accessing local disks and a factor of 20 for remote disks. We also applied the macro-voxel caching scheme on SPEC.s Seismic (batched application) benchmark datasets which improved the read process by a factor of 8.
URI: http://dspace.library.drexel.edu/handle/1860/307
Appears in Collections:Drexel Theses and Dissertations

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