Abstract
In various applications such as hyperspectral data manipulation, MRI data exploration, or viewshed identification in digital elevation models, performing arithmetic operations on each point of a data mesh that involves other points can lead to computationally intractable problems. This paper presents SkewEngine, a tool designed to improve the performance of intensive calculations on regular 2-D data meshes, such as images, multispectral data volumes, or digital elevation models. SkewEngine addresses this problem by reorganizing the mesh in memory according to a preferred spatial direction, enabling more efficient execution of intensive calculations. It is demonstrated that SkewEngine offers significant speed improvements for various test cases, suggesting its usefulness in a broader range of applications requiring intensive data processing on regular meshes.
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