Optimal caching of large multi-dimensional datasets

We propose a novel organization for multi-dimensional data based on the conceptof macro-voxels. This organization improves computer performance by enhancingspatial and temporal locality. Caching of macro-voxels not only reduces therequired 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.Ph.D., Electrical and Computer Engineering -- Drexel University, 200

On Optimal Temporal Locality of Stencil Codes

Iterative solvers such as the Jacobi and Gauss-Seidel relaxation methods are important, but time-consuming building blocks of many scientific and engineering applications. The performance problems are largely due to cache misses, and can be reduced by tiling the codes. Whereas previous research has shown the usefulness of tiling by experimentally comparing the run times of tiled and original codes, it did not tackle the question as to whether further improvements are possible. In this paper, we give a negative answer, regarding the exploitation of temporal locality in one step of a 2dimensional stencil code. We derive upper and lower bounds that match up to a factor of about 1 + 2/M, where M is the cache size. For the upper bounds, we investigate some modifications of tiling. 1