It's All Just Vectorization: einx, a Universal Notation for Tensor Operations
arXiv:2607. 27987v1 Announce Type: new Abstract: Tensor operations represent a cornerstone of modern scientific computing.
Vectorizer is a source‑to‑source tool that transforms NumPy programs containing explicit loops into vectorized array operations by rewriting loop bodies from the inside out. It uses array shapes and dataflow analysis to guide a set of rewrite rules that are correct by construction, achieving fast transformations—averaging 0.53 seconds per benchmark. In tests on 150 benchmarks, Vectorizer successfully vectorized 142 directly and 2 with minor edits, producing code that runs on average 74.83× faster than the original loop‑based implementations.
arXiv:2607. 27987v1 Announce Type: new Abstract: Tensor operations represent a cornerstone of modern scientific computing.
arXiv:2608.24738v1 Announce Type: new Abstract: Morphological transforms are long-standing tools for shape and mask processing, but the de facto reference implementation in the Python ecosystem, i.e....
Morphological transforms are long-standing tools for shape and mask processing, but the de facto reference implementation in the Python ecosystem, i.e. scipy.ndimage, is CPU-only, single-array, and th...
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