Improving Shplonk implementation #326
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storojs72
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adr1anh
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Feb 16, 2024
huitseeker
reviewed
Feb 16, 2024
src/provider/shplonk.rs
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| } | ||
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| let C_P: E::G1 = pi.comms.iter().map(|comm| comm.to_curve()).rlc(&q); | ||
| // TODO: revisit C_P computing later with progress in https://github.com/huitseeker/arecibo/tree/rayon-parscan | ||
| let q_powers = HyperKZG::<E, NE>::batch_challenge_powers(q, comms.len()); |
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You can make spartan::powers pub (in crate):
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| let q_powers = HyperKZG::<E, NE>::batch_challenge_powers(q, comms.len()); | |
| let q_powers = crate::spartan::powers(q, comms.len()); |
huitseeker
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Feb 17, 2024
src/provider/shplonk.rs
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Comment on lines
294
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299
| #[allow(clippy::redundant_closure)] | ||
| let C_P: E::G1 = comms | ||
| .par_iter() | ||
| .zip_eq(q_powers.par_iter()) | ||
| .fold(|| E::G1::identity(), |acc, (comm, q_i)| acc + *comm * q_i) | ||
| .sum::<E::G1>(); |
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Suggested change
| #[allow(clippy::redundant_closure)] | |
| let C_P: E::G1 = comms | |
| .par_iter() | |
| .zip_eq(q_powers.par_iter()) | |
| .fold(|| E::G1::identity(), |acc, (comm, q_i)| acc + *comm * q_i) | |
| .sum::<E::G1>(); | |
| let C_P: E::G1 = comms | |
| .par_iter() | |
| .zip_eq(q_powers.par_iter()) | |
| .fold(E::G1::identity, |acc, (comm, q_i)| acc + *comm * q_i) | |
| .sum::<E::G1>(); |
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Seems to be irrelevant after rebasing to latest dev which includes #330
adr1anh
previously approved these changes
Feb 20, 2024
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LGTM! Feel free to apply the suggestions by @huitseeker (will re-approve if necessary)
adr1anh
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Feb 20, 2024
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* avoid explicit compression/decompression * update version
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Fixes #303
This PR introduces 2 improvements:
Next PR should include careful merging Shplonk and HyperKZG implementations leaving hyperkzg.rs source file and removing shplonk.rs (fixing #302). I expect some more improving of prover performance with this merge.
Concrete results of benchmarking at this stage (Shplonk vs current HyperKZG) are following (similar to #301 (comment) - comparable verifier and improved prover):
P.S. @huitseeker, I saw your WIP branch related to parallel rlc. Please, notify me when you land that, so I can simplify
C_Pcomputing by utilising you work