feat: skip zeroes in msm#168
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I forgot to commit the change in the msm when I created this PR (there was only the changes in the benches). The msm change is now committed. |
davidnevadoc
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LGTM!
I am curious about how this new version performs against the cyclone version in different scalar ranges 🤔
kilic
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| let number_of_windows = C::Scalar::NUM_BITS as usize / c + 1; | ||
| let field_byte_size = coeffs[0].as_ref().len(); |
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maybe div_ceil by 8 is better option here because we don't force consumer to send non empty vectors
Co-authored-by: David Nevado <davidnevadoc@users.noreply.github.com>
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* feat: skip zeroes in msm * Update src/msm.rs Co-authored-by: David Nevado <davidnevadoc@users.noreply.github.com> --------- Co-authored-by: David Nevado <davidnevadoc@users.noreply.github.com>
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* feat: skip zeroes in msm * Update src/msm.rs Co-authored-by: David Nevado <davidnevadoc@users.noreply.github.com> --------- Co-authored-by: David Nevado <davidnevadoc@users.noreply.github.com>
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For scalar field elements modulo p, if all coefficients `a_i` are smaller than some value x < p, their binary representations will have leading zero bits. In this case, we can skip processing the windows corresponding to these leading zeros in the bucket calculation since they would not contribute to the final result. This follows the same idea as in the implementation: privacy-ethereum/halo2curves#168
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This change only affects the
multiexp_serialMSM implementation (and not cyclone).In the multiexp serial MSM algorithm, skip the windows that pick the most significant bits whenever those bits are zeroes in all coefficients. This is done by finding the max number of bits used by the coefficients.
Extend the msm benchmark to use coefficients of different bit sizes.
Closes #150
Supersede #152 (bench comparison of this PR approach and previous PR approach: #152 (comment)
Bench results compared to main branch
From the benchmarks only 3 cases have regressed:
For
msm/multicore/256b_3andmsm/singlecore/256b_3these regressions seem acceptable because these cases take less than 500 µs.The
msm/singlecore/256b_12case is just+1.8255%so it's not too bad, compared to the significant gains we obtain for bit sizes <= 128. Also I think this result is due to noise. In all the cases as k grows the improvement decreases. So I would expect the change inmsm/singlecore/256b_14to be worse thanmsm/singlecore/256b_12(and the same withmsm/singlecore/256b_16) but that's not the case.