fortran-nlp-kernels
Exact lexical and dense-vector similarity search for Python with Fortran backends, CPU autotuning, and workload-aware runtime dispatch.
fortran-nlp-kernels provides a Python API for exact word-shingle Jaccard search and exact dense-vector search while executing the computational kernels in compiled Fortran, OpenMP, and OpenBLAS code.
The stable 0.1.0 release introduces benchmark-informed CPU autotuning and workload-aware runtime dispatch, optional machine-specific thread calibration, versioned calibration profiles, runtime memory guardrails, and temporary OpenMP/OpenBLAS thread control. The shipped fallback policy is based on CPU performance experiments conducted on the perf-eval branch against the 0.1.0b2 implementation.
Installation
PyPI
Install the latest available stable release:
python -m pip install fortran-nlp-kernels
Run machine-specific thread calibration:
fortran-nlp-calibrate
Architecture
Python public API
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Runtime workload descriptor
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Backend resolver:-
+-- Level 1: explicit backend override
+-- Level 2: compatible machine calibration profile
+-- Level 3: packaged fallback policy
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BackendDecision
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OpenMP / OpenBLAS runtime controller
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Python validation, preprocessing, and orchestration
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nanobind C++ extension
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stable C ABI
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Fortran / OpenMP / OpenBLAS kernels