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Make CAReduce more SIMD and memory friendly #1385

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@ricardoV94 ricardoV94 commented Apr 30, 2025

This PR does two major changes:

  1. Adds a branch with intermediate allocators when reducing over a contiguous dimension that is SIMD friendly.
  2. Allocate output buffer aligned with input dimensions, instead of always allocating C-order.

Performance is now comparable or better than numpy


📚 Documentation preview 📚: https://pytensor--1385.org.readthedocs.build/en/1385/

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