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+# Continuous benchmarking of OpenBLAS performance
+
+We run a set of benchmarks of subset of OpenBLAS functionality.
+
+## Benchmark runner
+
+[![CodSpeed Badge](https://img.shields.io/endpoint?url=https://codspeed.io/badge.json)](https://codspeed.io/OpenMathLib/OpenBLAS/)
+
+Click on [benchmarks](https://codspeed.io/OpenMathLib/OpenBLAS/benchmarks) to see the performance of a particular benchmark over time;
+Click on [branches](https://codspeed.io/OpenMathLib/OpenBLAS/branches/) and then on the last PR link to see the flamegraphs.
+
+## What are the benchmarks
+
+We run raw BLAS/LAPACK subroutines, via f2py-generated python wrappers. The wrappers themselves are equivalent to [those from SciPy](https://docs.scipy.org/doc/scipy/reference/linalg.lapack.html).
+In fact, the wrappers _are_ from SciPy, we take a small subset simply to avoid having to build the whole SciPy for each CI run.
+
+
+## Adding a new benchmark
+
+`.github/workflows/codspeed-bench.yml` does all the orchestration on CI.
+
+Benchmarks live in the `benchmark/pybench` directory. It is organized as follows:
+
+- benchmarks themselves live in the `benchmarks` folder. Note that the LAPACK routines are imported from the `openblas_wrap` package.
+- the `openblas_wrap` package is a simple trampoline: it contains an f2py extension, `_flapack`, which talks to OpenBLAS, and exports the python names in its `__init__.py`.
+This way, the `openblas_wrap` package shields the benchmarks from the details of where a particular LAPACK function comes from. If wanted, you may for instance swap the `_flapack` extension to
+`scipy.linalg.blas` and `scipy.linalg.lapack`.
+
+To change parameters of an existing benchmark, edit python files in the `benchmark/pybench/benchmarks` directory.
+
+To add a benchmark for a new BLAS or LAPACK function, you need to:
+
+- add an f2py wrapper for the bare LAPACK function. You can simply copy a wrapper from SciPy (look for `*.pyf.src` files in https://github.com/scipy/scipy/tree/main/scipy/linalg)
+- add an import to `benchmark/pybench/openblas_wrap/__init__.py`
+
+
+## Running benchmarks locally
+
+This benchmarking layer is orchestrated from python, therefore you'll need to
+have all what it takes to build OpenBLAS from source, plus `python` and
+
+```
+$ python -mpip install numpy meson ninja pytest pytest-benchmark
+```
+
+The benchmark syntax is consistent with that of `pytest-benchmark` framework. The incantation to run the suite locally is `$ pytest benchmark/pybench/benchmarks/test_blas.py`.
+
+An ASV compatible benchmark suite is planned but currently not implemented.
+