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This improves evaluation / interpolation at geometric progression in case of parameters that are not all essentially identical. This also resorts more directly to the fft_small middle product when possible.
For the moment, evaluation is done, and speedup is when one of these occurs:
the number of evaluation points is less than the length used for the precomputation data
the degree of the evaluated polynomial is less than the number of evaluation points
the valuation of the evaluated polynomial is not zero (which should not happen too often, but maybe some specific usages have this)
vneiger
changed the title
Improvements eval/interp at geometric for unequal parameters
Improvements eval/interp at geometric progression for unequal parameters
Dec 5, 2025
Example timings, when precomputation has been done on 10 * (nb evaluation points). The speed-up factor is almost 10. The interesting column is the one before last, which measures the time for evaluation excluding precomputations.
Example timings, when the number of evaluations points is larger than the polynomial degree. This is the time for evaluation, excluding precomputation (which is the same before and after).
And finally, comparison of the previous implementation using mullow versus the use of fft_small midprod directly. This is a bad idea for small lengths, so I inserted some branching condition that seems to be fairly accurate at picking the fastest variant. This is the version present in the commits to be pushed in a minute.
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This improves evaluation / interpolation at geometric progression in case of parameters that are not all essentially identical. This also resorts more directly to the
fft_smallmiddle product when possible.For the moment, evaluation is done, and speedup is when one of these occurs: