diff --git a/Cargo.toml b/Cargo.toml
index 6e3c6597652955e21c40416340addf866640f292..ec3431564628300cb3bfcd2f51174dabbd4972e7 100644
--- a/Cargo.toml
+++ b/Cargo.toml
@@ -65,6 +65,16 @@ harness = false
name = "commit"
harness = false
+[[bench]]
+name = "field_operations"
+path = "benches/operations/field.rs"
+harness = false
+
+[[bench]]
+name = "curve_group_operations"
+path = "benches/operations/curve_group.rs"
+harness = false
+
[[example]]
name = "bench_commit"
path = "examples/benches/commit.rs"
diff --git a/benches/README.md b/benches/README.md
index 5feeb4cfe8d74614a80c9758eaddfbffcad4941a..6f72baa6bf8fd1dbae9650480564282020f72314 100644
--- a/benches/README.md
+++ b/benches/README.md
@@ -14,11 +14,34 @@ python scripts/plot/benches.py results.ndjson --bench linalg
python scripts/plot/benches.py results.ndjson --bench setup
```
+## atomic operations
+```nushell
+cargo criterion --output-format verbose --message-format json --bench field_operations out> field.ndjson
+cargo criterion --output-format verbose --message-format json --bench curve_group_operations out> curve.ndjson
+```
+```nushell
+def read-atomic-ops []: list -> record {
+ where reason == "benchmark-complete"
+ | select id mean.estimate
+ | rename --column { mean_estimate: "mean" }
+ | sort-by id
+ | update id { parse "{op} on {curve}" }
+ | flatten --all
+ | group-by op --to-table
+ | reject items.op
+ | update items { transpose -r | into record }
+ | transpose -r
+ | into record
+}
+python scripts/plot/multi_bar.py (open field.ndjson | read-atomic-ops | to json) --title "field operations" -l "time (in ns)"
+python scripts/plot/multi_bar.py (open curve.ndjson | read-atomic-ops | to json) --title "curve group operations" -l "time (in ns)"
+```
+
## oneshot benchmarks
these are benchmarks that run a single measurement, implemented as _examples_ in
`examples/benches/`.
-## commit
+### commit
```nushell
let res = cargo run --example bench_commit
| lines
diff --git a/benches/operations/curve_group.rs b/benches/operations/curve_group.rs
new file mode 100644
index 0000000000000000000000000000000000000000..7a4047f9eca71921670ab5dbc725fda2c51f0110
--- /dev/null
+++ b/benches/operations/curve_group.rs
@@ -0,0 +1,112 @@
+// see `benches/README.md`
+use std::time::Duration;
+
+use ark_ec::CurveGroup;
+use ark_ff::PrimeField;
+
+use criterion::{criterion_group, criterion_main, Criterion};
+
+fn random_sampling_template<G: CurveGroup>(c: &mut Criterion, curve: &str) {
+ let mut rng = ark_std::test_rng();
+
+ c.bench_function(&format!("random sampling on {}", curve), |b| {
+ b.iter(|| {
+ let _ = G::rand(&mut rng);
+ });
+ });
+}
+
+fn group_template<F: PrimeField, G: CurveGroup<ScalarField = F>>(c: &mut Criterion, curve: &str) {
+ let mut rng = ark_std::test_rng();
+
+ c.bench_function(&format!("addition on {}", curve), |b| {
+ b.iter(|| {
+ let g1 = G::rand(&mut rng);
+ let g2 = G::rand(&mut rng);
+ g1 + g2
+ });
+ });
+
+ c.bench_function(&format!("substraction on {}", curve), |b| {
+ b.iter(|| {
+ let g1 = G::rand(&mut rng);
+ let g2 = G::rand(&mut rng);
+ g1 - g2
+ });
+ });
+
+ c.bench_function(&format!("double on {}", curve), |b| {
+ b.iter(|| {
+ let g1 = G::rand(&mut rng);
+ g1.double()
+ });
+ });
+
+ c.bench_function(&format!("scalar multiplication on {}", curve), |b| {
+ b.iter(|| {
+ let g1 = G::rand(&mut rng);
+ let f1 = F::rand(&mut rng);
+ g1.mul(f1)
+ });
+ });
+}
+
+fn curve_group_template<F: PrimeField, G: CurveGroup<ScalarField = F>>(
+ c: &mut Criterion,
+ curve: &str,
+) {
+ let mut rng = ark_std::test_rng();
+
+ c.bench_function(&format!("into affine on {}", curve), |b| {
+ b.iter(|| {
+ let g1 = G::rand(&mut rng);
+ g1.into_affine()
+ });
+ });
+
+ c.bench_function(&format!("from affine on {}", curve), |b| {
+ b.iter(|| {
+ let g1_affine = G::rand(&mut rng).into_affine();
+ let _: G = g1_affine.into();
+ });
+ });
+
+ c.bench_function(&format!("affine addition on {}", curve), |b| {
+ b.iter(|| {
+ let g1_affine = G::rand(&mut rng).into_affine();
+ let g2_affine = G::rand(&mut rng).into_affine();
+ g1_affine + g2_affine
+ });
+ });
+
+ c.bench_function(&format!("affine scalar multiplication on {}", curve), |b| {
+ b.iter(|| {
+ let g1_affine = G::rand(&mut rng).into_affine();
+ let f1 = F::rand(&mut rng);
+ g1_affine * f1
+ });
+ });
+}
+
+macro_rules! bench {
+ ($c:ident, $b:ident, G1=$g:ident, name=$n:expr) => {
+ random_sampling_template::<$c::$g>($b, $n);
+ group_template::<$c::Fr, $c::$g>($b, $n);
+ curve_group_template::<$c::Fr, $c::$g>($b, $n);
+ };
+}
+
+fn bench(c: &mut Criterion) {
+ bench!(ark_bls12_381, c, G1 = G1Projective, name = "BLS12-381");
+ bench!(ark_bn254, c, G1 = G1Projective, name = "BN-254");
+ bench!(ark_pallas, c, G1 = Projective, name = "PALLAS");
+}
+
+criterion_group!(
+ name = benches;
+ config = Criterion::default()
+ .warm_up_time(Duration::from_secs_f32(0.5))
+ .sample_size(10);
+ targets = bench
+);
+criterion_main!(benches);
diff --git a/benches/operations/field.rs b/benches/operations/field.rs
new file mode 100644
index 0000000000000000000000000000000000000000..f5d85bbd1c7b9a455eb4fd1517168f4c12d80e58
--- /dev/null
+++ b/benches/operations/field.rs
@@ -0,0 +1,132 @@
+// see `benches/README.md`
+use std::time::Duration;
+
+use ark_ff::PrimeField;
+
+use criterion::{criterion_group, criterion_main, Criterion};
+
+fn random_sampling_template<F: PrimeField>(c: &mut Criterion, curve: &str) {
+ let mut rng = ark_std::test_rng();
+
+ c.bench_function(&format!("random sampling on {}", curve), |b| {
+ b.iter(|| {
+ let _ = F::rand(&mut rng);
+ });
+ });
+}
+
+fn additive_group_template<F: PrimeField>(c: &mut Criterion, curve: &str) {
+ let mut rng = ark_std::test_rng();
+
+ c.bench_function(&format!("addition on {}", curve), |b| {
+ b.iter(|| {
+ let f1 = F::rand(&mut rng);
+ let f2 = F::rand(&mut rng);
+ f1 + f2
+ });
+ });
+
+ c.bench_function(&format!("substraction on {}", curve), |b| {
+ b.iter(|| {
+ let f1 = F::rand(&mut rng);
+ let f2 = F::rand(&mut rng);
+ f1 - f2
+ });
+ });
+
+ c.bench_function(&format!("double on {}", curve), |b| {
+ b.iter(|| {
+ let f1 = F::rand(&mut rng);
+ f1.double()
+ });
+ });
+
+ c.bench_function(&format!("multiplication on {}", curve), |b| {
+ b.iter(|| {
+ let f1 = F::rand(&mut rng);
+ let f2 = F::rand(&mut rng);
+ f1 * f2
+ });
+ });
+}
+
+fn field_template<F: PrimeField>(c: &mut Criterion, curve: &str) {
+ let mut rng = ark_std::test_rng();
+
+ c.bench_function(&format!("square on {}", curve), |b| {
+ b.iter(|| {
+ let f1 = F::rand(&mut rng);
+ f1.square()
+ });
+ });
+
+ c.bench_function(&format!("inverse on {}", curve), |b| {
+ b.iter(|| {
+ let f1 = F::rand(&mut rng);
+ f1.inverse()
+ });
+ });
+
+ c.bench_function(&format!("legendre on {}", curve), |b| {
+ b.iter(|| {
+ let f1 = F::rand(&mut rng);
+ f1.legendre()
+ });
+ });
+
+ c.bench_function(&format!("sqrt on {}", curve), |b| {
+ b.iter(|| {
+ let f1 = F::rand(&mut rng);
+ if f1.legendre().is_qr() {
+ let _ = f1.sqrt();
+ }
+ });
+ });
+}
+
+fn prime_field_template<F: PrimeField>(c: &mut Criterion, curve: &str) {
+ let mut rng = ark_std::test_rng();
+
+ c.bench_function(&format!("exponentiation on {}", curve), |b| {
+ b.iter(|| {
+ let f1 = F::rand(&mut rng);
+ f1.pow(F::MODULUS)
+ });
+ });
+}
+
+fn conversions_template<F: PrimeField>(c: &mut Criterion, curve: &str) {
+ let mut rng = ark_std::test_rng();
+
+ c.bench_function(&format!("bigint conversion on {}", curve), |b| {
+ b.iter(|| {
+ let f1 = F::rand(&mut rng);
+ f1.into_bigint()
+ });
+ });
+}
+
+macro_rules! bench {
+ ($c:ident, $b:ident, F=$f:ident, name=$n:expr) => {
+ random_sampling_template::<$c::$f>($b, $n);
+ additive_group_template::<$c::$f>($b, $n);
+ field_template::<$c::$f>($b, $n);
+ prime_field_template::<$c::$f>($b, $n);
+ conversions_template::<$c::$f>($b, $n);
+ };
+}
+
+fn bench(c: &mut Criterion) {
+ bench!(ark_bls12_381, c, F = Fr, name = "BLS12-381");
+ bench!(ark_bn254, c, F = Fr, name = "BN-254");
+ bench!(ark_pallas, c, F = Fr, name = "PALLAS");
+}
+
+criterion_group!(
+ name = benches;
+ config = Criterion::default()
+ .warm_up_time(Duration::from_secs_f32(0.5))
+ .sample_size(10);
+ targets = bench
+);
+criterion_main!(benches);
diff --git a/scripts/plot/multi_bar.py b/scripts/plot/multi_bar.py
new file mode 100644
index 0000000000000000000000000000000000000000..2cbee35add2192151b86ec840b16907d5bc18eb7
--- /dev/null
+++ b/scripts/plot/multi_bar.py
@@ -0,0 +1,125 @@
+# see `benches/README.md`
+from typing import Dict, List
+
+import matplotlib.pyplot as plt
+import numpy as np
+import json
+import sys
+import argparse
+
+
+# convert raw data into groups and measurements
+#
+# # Example
+# input:
+# ```json
+# {
+# "age": {
+# "alice": 31,
+# "bob": 28,
+# "charlie": 44
+# },
+# "height": {
+# "alice": 1.50,
+# "bob": 1.82,
+# "charlie": 1.65
+# },
+# "weight": {
+# "alice": 65.3,
+# "bob": 98.1,
+# "charlie": 68.7
+# }
+# }
+# ```
+#
+# output:
+# ```
+# groups = ["age", "height", "weight"]
+# measurements = {
+# "alice": [1.50, 31, 65.3],
+# "bob": [1.82, 28, 98.1],
+# "charlie": [1.65, 44, 68.7]
+# }
+# ```
+def extract(data: Dict[str, Dict[str, float]]) -> (List[str], Dict[str, List[float]]):
+ groups = list(data.keys())
+
+ measurements = {}
+ for x in data[groups[0]].keys():
+ measurements[x] = [data[g][x] for g in groups]
+
+ return (groups, measurements)
+
+
+# plot multi bars
+#
+# # Example
+# input can be the output of [`extract`]
+def plot_multi_bar(
+ groups: List[str],
+ measurements: Dict[str, List[float]],
+ title: str,
+ y_label: str,
+ labels_locations: List[float] = None,
+ width: float = 0.25,
+ nb_legend_cols: int = 3,
+ legend_loc: str = "upper left",
+ plot_layout: str = "constrained",
+ save: str = None,
+):
+ if labels_locations is None:
+ labels_locations = np.arange(len(groups))
+
+ fig, ax = plt.subplots(layout=plot_layout)
+
+ multiplier = 0
+ for attribute, measurement in measurements.items():
+ offset = width * multiplier
+ rects = ax.bar(labels_locations + offset, measurement, width, label=attribute)
+ ax.bar_label(rects, padding=3)
+ multiplier += 1
+
+ ax.set_ylabel(y_label)
+ ax.set_title(title)
+ ax.set_xticks(labels_locations + width, groups)
+ ax.legend(loc=legend_loc, ncols=nb_legend_cols)
+
+ if save is not None:
+ fig.set_size_inches((16, 9), forward=False)
+ fig.savefig(save, dpi=500)
+
+ print(f"plot saved as `{save}`")
+ else:
+ plt.show()
+
+
+if __name__ == "__main__":
+ parser = argparse.ArgumentParser()
+ parser.add_argument("data", type=str, help="""
+ the actual data to show in a multibar plot, here is an example:
+ {
+ "age": {
+ "alice": 31,
+ "bob": 28,
+ "charlie": 44
+ },
+ "height": {
+ "alice": 1.50,
+ "bob": 1.82,
+ "charlie": 1.65
+ },
+ "weight": {
+ "alice": 65.3,
+ "bob": 98.1,
+ "charlie": 68.7
+ }
+ }
+ """)
+ parser.add_argument("--title", "-t", type=str, help="the title of the multibar plot")
+ parser.add_argument("--label", "-l", type=str, help="the measurement label of the multibar plot")
+ parser.add_argument("--save", "-s", type=str, help="a path to save the figure to")
+ args = parser.parse_args()
+
+ groups, measurements = extract(json.loads(args.data))
+
+ plot_multi_bar(groups, measurements, args.title, args.label, save=args.save)