Axesfast

Axesfast is a term used in computer science to describe methods and, in some contexts, software libraries that optimize operations performed along coordinate axes. The central principle is that many data processing tasks can benefit from axis-aligned data access patterns, enabling better cache locality, vectorization, and parallel execution.

Typical techniques include reorganizing data layout into axis-fast memory layouts, blocking and tiling along axes, and using SIMD (single instruction, multiple data) instructions to process multiple elements in parallel. Algorithms may be specialized for one- or multi-dimensional arrays, including matrix operations, geometric queries, and image processing pipelines.

Axesfast concepts are applied in fields such as computer graphics, computational geometry, and data analytics, where operations like axis-aligned filtering, projections, or scans are common.

Implementation considerations include hardware features (CPU vector units, memory bandwidth), language and library support (C/C++, Rust, or high-level frameworks), and portability. Performance gains rely on data size, dimensionality, and access patterns; results vary across platforms.

While the term axesfast is not tied to a single standardized project, several libraries and research projects describe similar axis-optimized approaches under different names. The concept emphasizes exploiting axis-aligned structure to improve performance.

See also axis-aligned bounding box, SIMD, data locality, tiling.