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Add benchmarks for precomputed multiscalar multiplication.

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This commit is contained in:
Henry de Valence 2019-01-24 13:29:28 -08:00
parent 98e713ef91
commit 00675b4c56
1 changed files with 128 additions and 22 deletions
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150
benches/dalek_benchmarks.rs
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@ -25,9 +25,7 @@ mod edwards_benches {
fn compress(c: &mut Criterion) {
let B = &constants::ED25519_BASEPOINT_POINT;
c.bench_function("EdwardsPoint compression", move |b| {
b.iter(|| B.compress())
});
c.bench_function("EdwardsPoint compression", move |b| b.iter(|| B.compress()));
}
fn decompress(c: &mut Criterion) {
@ -63,16 +61,40 @@ mod edwards_benches {
});
}
criterion_group!{
name = edwards_benches;
config = Criterion::default();
targets =
compress,
decompress,
consttime_fixed_base_scalar_mul,
consttime_variable_base_scalar_mul,
vartime_double_base_scalar_mul,
}
}
mod multiscalar_benches {
use super::*;
use curve25519_dalek::edwards;
use curve25519_dalek::edwards::EdwardsPoint;
use curve25519_dalek::traits::MultiscalarMul;
use curve25519_dalek::traits::VartimeMultiscalarMul;
fn construct(n: usize) -> (Vec<Scalar>, Vec<EdwardsPoint>) {
let mut rng = OsRng::new().unwrap();
let scalars: Vec<Scalar> = (0..n).map(|_| Scalar::random(&mut rng)).collect();
let points: Vec<EdwardsPoint> = scalars
.iter()
.map(|s| s * &constants::ED25519_BASEPOINT_TABLE)
.collect();
(scalars, points)
}
fn consttime_multiscalar_mul(c: &mut Criterion) {
c.bench_function_over_inputs(
"Constant-time variable-base multiscalar multiplication",
|b, &&size| {
let mut rng = OsRng::new().unwrap();
let scalars: Vec<Scalar> = (0..size).map(|_| Scalar::random(&mut rng)).collect();
let points: Vec<EdwardsPoint> = scalars
.iter()
.map(|s| s * &constants::ED25519_BASEPOINT_TABLE)
.collect();
let (scalars, points) = construct(size);
b.iter(|| EdwardsPoint::multiscalar_mul(&scalars, &points));
},
&MULTISCALAR_SIZES,
@ -83,29 +105,112 @@ mod edwards_benches {
c.bench_function_over_inputs(
"Variable-time variable-base multiscalar multiplication",
|b, &&size| {
let mut rng = OsRng::new().unwrap();
let scalars: Vec<Scalar> = (0..size).map(|_| Scalar::random(&mut rng)).collect();
let points: Vec<EdwardsPoint> = scalars
.iter()
.map(|s| s * &constants::ED25519_BASEPOINT_TABLE)
.collect();
let (scalars, points) = construct(size);
b.iter(|| EdwardsPoint::vartime_multiscalar_mul(&scalars, &points));
},
&MULTISCALAR_SIZES,
);
}
fn precomputed_ct_straus_helper(c: &mut Criterion, dynamic_fraction: f64) {
let label = format!(
"Constant-time mixed-base Straus ({:.2}pct dyn)",
100.0*dynamic_fraction,
);
c.bench_function_over_inputs(
&label,
move |b, &&total_size| {
let dynamic_size = ((total_size as f64) * dynamic_fraction) as usize;
let static_size = total_size - dynamic_size;
let (static_scalars, static_points) = construct(static_size);
let (dynamic_scalars, dynamic_points) = construct(dynamic_size);
use curve25519_dalek::edwards::PrecomputedStraus;
use curve25519_dalek::traits::PrecomputedMultiscalarMul;
let precomp = PrecomputedStraus::new(&static_points);
b.iter(|| {
precomp.mixed_multiscalar_mul(
&static_scalars,
&dynamic_scalars,
&dynamic_points,
)
});
},
&MULTISCALAR_SIZES,
);
}
fn precomputed_vt_straus_helper(c: &mut Criterion, dynamic_fraction: f64) {
let label = format!(
"Variable-time mixed-base Straus ({:.2}pct dyn)",
100.0*dynamic_fraction,
);
c.bench_function_over_inputs(
&label,
move |b, &&total_size| {
let dynamic_size = ((total_size as f64) * dynamic_fraction) as usize;
let static_size = total_size - dynamic_size;
let (static_scalars, static_points) = construct(static_size);
let (dynamic_scalars, dynamic_points) = construct(dynamic_size);
use curve25519_dalek::edwards::VartimePrecomputedStraus;
use curve25519_dalek::traits::VartimePrecomputedMultiscalarMul;
let precomp = VartimePrecomputedStraus::new(&static_points);
b.iter(|| {
precomp.vartime_mixed_multiscalar_mul(
&static_scalars,
&dynamic_scalars,
&dynamic_points,
)
});
},
&MULTISCALAR_SIZES,
);
}
fn precomputed_ct_straus_00_pct_dynamic(c: &mut Criterion) {
precomputed_ct_straus_helper(c, 0.0);
}
fn precomputed_ct_straus_20_pct_dynamic(c: &mut Criterion) {
precomputed_ct_straus_helper(c, 0.2);
}
fn precomputed_ct_straus_50_pct_dynamic(c: &mut Criterion) {
precomputed_ct_straus_helper(c, 0.5);
}
fn precomputed_vt_straus_00_pct_dynamic(c: &mut Criterion) {
precomputed_vt_straus_helper(c, 0.0);
}
fn precomputed_vt_straus_20_pct_dynamic(c: &mut Criterion) {
precomputed_vt_straus_helper(c, 0.2);
}
fn precomputed_vt_straus_50_pct_dynamic(c: &mut Criterion) {
precomputed_vt_straus_helper(c, 0.5);
}
criterion_group!{
name = edwards_benches;
config = Criterion::default();
name = multiscalar_benches;
// Lower the sample size to run the benchmarks faster
config = Criterion::default().sample_size(15);
targets =
compress,
decompress,
consttime_fixed_base_scalar_mul,
consttime_variable_base_scalar_mul,
vartime_double_base_scalar_mul,
consttime_multiscalar_mul,
vartime_multiscalar_mul,
precomputed_ct_straus_00_pct_dynamic,
precomputed_ct_straus_20_pct_dynamic,
precomputed_ct_straus_50_pct_dynamic,
precomputed_vt_straus_00_pct_dynamic,
precomputed_vt_straus_20_pct_dynamic,
precomputed_vt_straus_50_pct_dynamic,
}
}
@ -208,4 +313,5 @@ criterion_main!(
montgomery_benches::montgomery_benches,
ristretto_benches::ristretto_benches,
edwards_benches::edwards_benches,
multiscalar_benches::multiscalar_benches,
);