Fortran kernels for NLP

A developer released fortran-nlp-kernels, a Python package that uses Fortran backends for exact lexical and vector similarity search. The package supports Jaccard similarity search and inner product, cosine and L2 vector search, with serial and OpenMP backends, Python bindings via C ABI and nanobind, benchmark-informed CPU autotuning with workload-aware runtime dispatch, and PyPI wheels. The developer said the project began as a personal experiment exploring modern Fortran outside traditional HPC and scientific computing and became a packaged library.

Hi everyone, I recently released fortran-nlp-kernels, a Python package that uses Fortran backends for exact lexical and vector similarity search. Current features: - Jaccard similarity search - Inner product, cosine and L2 vector search - Serial and OpenMP backends - Python bindings via C ABI + nanobind - benchmark informed CPU autotuning and workload aware runtime dispatch, after extensive multicore CPU measurements - PyPI wheels This started as a personal experiment exploring modern Fortran outside traditional HPC/scientific computing and ended up becoming a packaged library. I’d appreciate any feedback, suggestions, or ideas for future directions. GitHub: PyPI: