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I think the current report is very hard to read.
It might be helpful to specify very clearly what the baseline is, that is the meaning of 1 in all the plots - it's your own C++ implementation.
For a comparison with scikit-learn I think doing sklearn speed / your c++ speed would be easier to read as it shows your speedup factor, not our slow-down factor.
Finally, I don't see the number of cores in your benchmark, which is pretty crucial since most of our implementations are single-threaded. Yes, that's a big issue, but saying "we're 100x faster" without saying "on 100 CPUs instead of 1" is quite misleading.
It might be helpful to have a chart of speedup vs number of CPUs.
The text was updated successfully, but these errors were encountered:
As discussed here: scikit-learn/scikit-learn#14247 (comment)
I think the current report is very hard to read.
It might be helpful to specify very clearly what the baseline is, that is the meaning of 1 in all the plots - it's your own C++ implementation.
For a comparison with scikit-learn I think doing sklearn speed / your c++ speed would be easier to read as it shows your speedup factor, not our slow-down factor.
Finally, I don't see the number of cores in your benchmark, which is pretty crucial since most of our implementations are single-threaded. Yes, that's a big issue, but saying "we're 100x faster" without saying "on 100 CPUs instead of 1" is quite misleading.
It might be helpful to have a chart of speedup vs number of CPUs.
The text was updated successfully, but these errors were encountered: