[sarah-ek]

one issue that may be affecting the result is that openmp's threadpool doesn't play well with rayon's. i've seen some perf degradation in the past (on both sides) when both are used in the same program

i plan to address that after refactoring the benches by executing each library individually

[jimbobraggins]

Very cool project! I'd suggest before running the new benchmarks to reach out to to the developers of the packages you are testing against to see if they think the benchmark you wrote is doing efficient calling conventions. I work on a large open source software project and we've had people claim they are 10x faster than us while they were really using our code in some very malformed ways.

Also stops them from grumbling after you post good results!

[sarah-ek]

fair enough. i try to stay in touch with the eigen and nalgebra developers so i have a good idea on how to write code efficiently with them. for openblas and mkl i've been trying recently to call into the lapack api (benches doing that are still unpublished at the moment), that way im using a universal interface for that kinda stuff.

and of course i do check the cpu utilization to make sure that all threads are spinning for multithreaded benchmarks, and occasionally check the assembly of the hot loops to make sure that the libraries were built properly and are dispatching to the right code. (avx2, avx512, etc) so overall i try to take it seriously and i'll give credit where credit is due when it turns out another library is faster