We run a set of benchmarks of subset of OpenBLAS functionality.
Click on benchmarks to see the performance of a particular benchmark over time;
Click on branches and then on the last PR link to see the flamegraphs.
We run raw BLAS/LAPACK subroutines, via f2py-generated python wrappers. The wrappers themselves are equivalent to those from SciPy.
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.
.github/workflows/codspeed-bench.yml
does all the orchestration on CI.
Benchmarks live in the benchmark/pybench
directory. It is organized as follows:
benchmarks
folder. Note that the LAPACK routines are imported from the openblas_wrap
package.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
.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 toscipy.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:
*.pyf.src
files in https://github.com/scipy/scipy/tree/main/scipy/linalg)benchmark/pybench/openblas_wrap/__init__.py
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.