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https://github.com/arnaucube/ark-curves-cherry-picked.git
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Initial commit
This commit is contained in:
Pratyush Mishra
357
curve-benches/src/macros/ec.rs
Normal file
357
curve-benches/src/macros/ec.rs
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@@ -0,0 +1,357 @@
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macro_rules! ec_bench {
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() => {
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#[bench]
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fn bench_g1_rand(b: &mut ::test::Bencher) {
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let mut rng = XorShiftRng::seed_from_u64(1231275789u64);
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b.iter(|| G1::rand(&mut rng));
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}
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#[bench]
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fn bench_g1_mul_assign(b: &mut ::test::Bencher) {
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const SAMPLES: usize = 1000;
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let mut rng = XorShiftRng::seed_from_u64(1231275789u64);
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let v: Vec<(G1, Fr)> = (0..SAMPLES)
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.map(|_| (G1::rand(&mut rng), Fr::rand(&mut rng)))
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.collect();
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let mut count = 0;
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b.iter(|| {
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let mut tmp = v[count].0;
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tmp *= v[count].1;
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count = (count + 1) % SAMPLES;
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tmp
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});
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}
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#[bench]
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fn bench_g1_add_assign(b: &mut ::test::Bencher) {
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const SAMPLES: usize = 1000;
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let mut rng = XorShiftRng::seed_from_u64(1231275789u64);
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let v: Vec<(G1, G1)> = (0..SAMPLES)
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.map(|_| (G1::rand(&mut rng), G1::rand(&mut rng)))
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.collect();
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let mut count = 0;
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b.iter(|| {
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let mut tmp = v[count].0;
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n_fold!(tmp, v, add_assign, count);
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count = (count + 1) % SAMPLES;
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tmp
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});
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}
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#[bench]
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fn bench_g1_add_assign_mixed(b: &mut ::test::Bencher) {
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const SAMPLES: usize = 1000;
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let mut rng = XorShiftRng::seed_from_u64(1231275789u64);
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let v: Vec<(G1, G1Affine)> = (0..SAMPLES)
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.map(|_| (G1::rand(&mut rng), G1::rand(&mut rng).into()))
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.collect();
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let mut count = 0;
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b.iter(|| {
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let mut tmp = v[count].0;
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n_fold!(tmp, v, add_assign_mixed, count);
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count = (count + 1) % SAMPLES;
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tmp
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});
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}
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#[bench]
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fn bench_g1_double(b: &mut ::test::Bencher) {
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const SAMPLES: usize = 1000;
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let mut rng = XorShiftRng::seed_from_u64(1231275789u64);
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let v: Vec<(G1, G1)> = (0..SAMPLES)
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.map(|_| (G1::rand(&mut rng), G1::rand(&mut rng)))
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.collect();
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let mut count = 0;
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b.iter(|| {
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let mut tmp = v[count].0;
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n_fold!(tmp, double_in_place);
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count = (count + 1) % SAMPLES;
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tmp
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});
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}
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#[bench]
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fn bench_g1_deser(b: &mut ::test::Bencher) {
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use ark_ec::ProjectiveCurve;
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use ark_serialize::{CanonicalDeserialize, CanonicalSerialize};
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const SAMPLES: usize = 1000;
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let mut rng = XorShiftRng::seed_from_u64(1231275789u64);
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let mut num_bytes = 0;
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let tmp = G1::rand(&mut rng).into_affine();
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let v: Vec<_> = (0..SAMPLES)
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.flat_map(|_| {
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let mut bytes = Vec::with_capacity(1000);
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tmp.serialize(&mut bytes).unwrap();
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num_bytes = bytes.len();
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bytes
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})
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.collect();
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let mut count = 0;
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b.iter(|| {
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count = (count + 1) % SAMPLES;
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let index = count * num_bytes;
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G1Affine::deserialize(&v[index..(index + num_bytes)]).unwrap()
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});
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}
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#[bench]
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fn bench_g1_ser(b: &mut ::test::Bencher) {
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use ark_ec::ProjectiveCurve;
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use ark_serialize::CanonicalSerialize;
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const SAMPLES: usize = 1000;
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let mut rng = XorShiftRng::seed_from_u64(1231275789u64);
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let mut v: Vec<_> = (0..SAMPLES).map(|_| G1::rand(&mut rng)).collect();
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let v = G1::batch_normalization_into_affine(v.as_mut_slice());
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let mut bytes = Vec::with_capacity(1000);
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let mut count = 0;
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b.iter(|| {
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let tmp = v[count];
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count = (count + 1) % SAMPLES;
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bytes.clear();
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tmp.serialize(&mut bytes)
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});
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}
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#[bench]
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fn bench_g1_deser_unchecked(b: &mut ::test::Bencher) {
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use ark_ec::ProjectiveCurve;
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use ark_serialize::{CanonicalDeserialize, CanonicalSerialize};
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const SAMPLES: usize = 1000;
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let mut rng = XorShiftRng::seed_from_u64(1231275789u64);
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let mut num_bytes = 0;
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let tmp = G1::rand(&mut rng).into_affine();
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let v: Vec<_> = (0..SAMPLES)
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.flat_map(|_| {
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let mut bytes = Vec::with_capacity(1000);
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tmp.serialize_unchecked(&mut bytes).unwrap();
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num_bytes = bytes.len();
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bytes
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})
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.collect();
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let mut count = 0;
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b.iter(|| {
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count = (count + 1) % SAMPLES;
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let index = count * num_bytes;
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G1Affine::deserialize_unchecked(&v[index..(index + num_bytes)]).unwrap()
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});
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}
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#[bench]
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fn bench_g1_ser_unchecked(b: &mut ::test::Bencher) {
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use ark_serialize::{CanonicalDeserialize, CanonicalSerialize};
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const SAMPLES: usize = 1000;
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let mut rng = XorShiftRng::seed_from_u64(1231275789u64);
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let mut v: Vec<_> = (0..SAMPLES).map(|_| G1::rand(&mut rng)).collect();
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let v = G1::batch_normalization_into_affine(v.as_mut_slice());
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let mut bytes = Vec::with_capacity(1000);
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let mut count = 0;
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b.iter(|| {
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let tmp = v[count];
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count = (count + 1) % SAMPLES;
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bytes.clear();
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tmp.serialize_unchecked(&mut bytes)
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});
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}
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#[bench]
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fn bench_g2_rand(b: &mut ::test::Bencher) {
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let mut rng = XorShiftRng::seed_from_u64(1231275789u64);
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b.iter(|| G2::rand(&mut rng));
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}
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#[bench]
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fn bench_g2_mul_assign(b: &mut ::test::Bencher) {
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const SAMPLES: usize = 1000;
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let mut rng = XorShiftRng::seed_from_u64(1231275789u64);
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let v: Vec<(G2, Fr)> = (0..SAMPLES)
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.map(|_| (G2::rand(&mut rng), Fr::rand(&mut rng)))
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.collect();
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let mut count = 0;
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b.iter(|| {
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let mut tmp = v[count].0;
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tmp *= v[count].1;
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count = (count + 1) % SAMPLES;
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tmp
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});
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}
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#[bench]
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fn bench_g2_add_assign(b: &mut ::test::Bencher) {
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const SAMPLES: usize = 1000;
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let mut rng = XorShiftRng::seed_from_u64(1231275789u64);
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let v: Vec<(G2, G2)> = (0..SAMPLES)
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.map(|_| (G2::rand(&mut rng), G2::rand(&mut rng)))
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.collect();
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let mut count = 0;
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b.iter(|| {
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let mut tmp = v[count].0;
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tmp.add_assign(&v[count].1);
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count = (count + 1) % SAMPLES;
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tmp
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});
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}
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#[bench]
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fn bench_g2_add_assign_mixed(b: &mut ::test::Bencher) {
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const SAMPLES: usize = 1000;
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let mut rng = XorShiftRng::seed_from_u64(1231275789u64);
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let v: Vec<(G2, G2Affine)> = (0..SAMPLES)
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.map(|_| (G2::rand(&mut rng), G2::rand(&mut rng).into()))
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.collect();
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let mut count = 0;
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b.iter(|| {
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let mut tmp = v[count].0;
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tmp.add_assign_mixed(&v[count].1);
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count = (count + 1) % SAMPLES;
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tmp
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});
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}
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#[bench]
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fn bench_g2_double(b: &mut ::test::Bencher) {
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const SAMPLES: usize = 1000;
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let mut rng = XorShiftRng::seed_from_u64(1231275789u64);
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let v: Vec<(G2, G2)> = (0..SAMPLES)
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.map(|_| (G2::rand(&mut rng), G2::rand(&mut rng)))
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.collect();
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let mut count = 0;
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b.iter(|| {
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let mut tmp = v[count].0;
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tmp.double_in_place();
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count = (count + 1) % SAMPLES;
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tmp
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});
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}
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#[bench]
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fn bench_g2_deser(b: &mut ::test::Bencher) {
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use ark_ec::ProjectiveCurve;
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use ark_serialize::{CanonicalDeserialize, CanonicalSerialize};
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const SAMPLES: usize = 1000;
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let mut rng = XorShiftRng::seed_from_u64(1231275789u64);
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let mut num_bytes = 0;
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let tmp = G2::rand(&mut rng).into_affine();
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let v: Vec<_> = (0..SAMPLES)
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.flat_map(|_| {
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let mut bytes = Vec::with_capacity(1000);
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tmp.serialize(&mut bytes).unwrap();
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num_bytes = bytes.len();
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bytes
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})
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.collect();
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let mut count = 0;
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b.iter(|| {
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count = (count + 1) % SAMPLES;
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let index = count * num_bytes;
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G2Affine::deserialize(&v[index..(index + num_bytes)]).unwrap()
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});
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}
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#[bench]
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fn bench_g2_ser(b: &mut ::test::Bencher) {
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use ark_serialize::{CanonicalDeserialize, CanonicalSerialize};
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const SAMPLES: usize = 1000;
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let mut rng = XorShiftRng::seed_from_u64(1231275789u64);
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let mut v: Vec<_> = (0..SAMPLES).map(|_| G2::rand(&mut rng)).collect();
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let v = G2::batch_normalization_into_affine(v.as_mut_slice());
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let mut bytes = Vec::with_capacity(1000);
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let mut count = 0;
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b.iter(|| {
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let tmp = v[count];
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count = (count + 1) % SAMPLES;
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bytes.clear();
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tmp.serialize(&mut bytes)
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});
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}
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#[bench]
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fn bench_g2_deser_unchecked(b: &mut ::test::Bencher) {
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use ark_ec::ProjectiveCurve;
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use ark_serialize::{CanonicalDeserialize, CanonicalSerialize};
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const SAMPLES: usize = 1000;
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let mut rng = XorShiftRng::seed_from_u64(1231275789u64);
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let mut num_bytes = 0;
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let tmp = G2::rand(&mut rng).into_affine();
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let v: Vec<_> = (0..SAMPLES)
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.flat_map(|_| {
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let mut bytes = Vec::with_capacity(1000);
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tmp.serialize_unchecked(&mut bytes).unwrap();
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num_bytes = bytes.len();
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bytes
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})
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.collect();
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let mut count = 0;
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b.iter(|| {
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count = (count + 1) % SAMPLES;
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let index = count * num_bytes;
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G2Affine::deserialize_unchecked(&v[index..(index + num_bytes)]).unwrap()
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});
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}
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#[bench]
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fn bench_g2_ser_unchecked(b: &mut ::test::Bencher) {
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use ark_ec::ProjectiveCurve;
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use ark_serialize::CanonicalSerialize;
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const SAMPLES: usize = 1000;
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let mut rng = XorShiftRng::seed_from_u64(1231275789u64);
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let mut v: Vec<_> = (0..SAMPLES).map(|_| G2::rand(&mut rng)).collect();
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let v = G2::batch_normalization_into_affine(v.as_mut_slice());
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let mut bytes = Vec::with_capacity(1000);
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let mut count = 0;
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b.iter(|| {
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let tmp = v[count];
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count = (count + 1) % SAMPLES;
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bytes.clear();
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tmp.serialize_unchecked(&mut bytes)
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});
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}
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};
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}
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