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This implements [Supernova](https://eprint.iacr.org/2022/1758), allowing: - a 'pay-as-you-go' cost structure for folding operations, through the SuperNova folding scheme, - a final SNARK that efficiently compresses an instance of this folded proof, through batching techniques. References: - the [blog post](https://blog.lurk-lang.org/posts/arecibo-supernova/#technical-release-note-supernova-protocol-integration-into-nova) goes into our construction, and links to two more specialized notes on [the `CompressedSNARK` for Supernova](https://hackmd.io/@adr1anh/BJw1g0aBT) along with our variant of the [public input padding issue](https://hackmd.io/@adr1anh/Sy08YaVBa). - the Readme at `src/supernova/Readme.md` This backports the following Arecibo PRs: - argumentcomputer/arecibo#2 - argumentcomputer/arecibo#3 - argumentcomputer/arecibo#10 - argumentcomputer/arecibo#16 - argumentcomputer/arecibo#23 - argumentcomputer/arecibo#30 - argumentcomputer/arecibo#28 - argumentcomputer/arecibo#41 - argumentcomputer/arecibo#45 - argumentcomputer/arecibo#50 - argumentcomputer/arecibo#56 - argumentcomputer/arecibo#51 - argumentcomputer/arecibo#72 - argumentcomputer/arecibo#92 - argumentcomputer/arecibo#95 - argumentcomputer/arecibo#97 - argumentcomputer/arecibo#101 - argumentcomputer/arecibo#110 - argumentcomputer/arecibo#106 - argumentcomputer/arecibo#112 - argumentcomputer/arecibo#114 - argumentcomputer/arecibo#119 - argumentcomputer/arecibo#120 - argumentcomputer/arecibo#127 - argumentcomputer/arecibo#123 - argumentcomputer/arecibo#131 - argumentcomputer/arecibo#174 - argumentcomputer/arecibo#175 - argumentcomputer/arecibo#182 Co-authored-by: WYATT <[email protected]> Co-authored-by: Hanting Zhang <[email protected]> Co-authored-by: Ming <[email protected]> Co-authored-by: porcuquine <[email protected]> Co-authored-by: Samuel Burnham <[email protected]> Co-authored-by: Matej Penciak <[email protected]> Co-authored-by: Adrian Hamelink <[email protected]>
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#![allow(non_snake_case)] | ||
use bellpepper_core::{num::AllocatedNum, ConstraintSystem, SynthesisError}; | ||
use core::marker::PhantomData; | ||
use criterion::{measurement::WallTime, *}; | ||
use ff::PrimeField; | ||
use nova_snark::{ | ||
supernova::NonUniformCircuit, | ||
supernova::{snark::CompressedSNARK, PublicParams, RecursiveSNARK}, | ||
traits::{ | ||
circuit_supernova::{StepCircuit, TrivialTestCircuit}, | ||
snark::BatchedRelaxedR1CSSNARKTrait, | ||
snark::RelaxedR1CSSNARKTrait, | ||
Engine, | ||
}, | ||
}; | ||
use std::time::Duration; | ||
|
||
type E1 = nova_snark::provider::PallasEngine; | ||
type E2 = nova_snark::provider::VestaEngine; | ||
type EE1 = nova_snark::provider::ipa_pc::EvaluationEngine<E1>; | ||
type EE2 = nova_snark::provider::ipa_pc::EvaluationEngine<E2>; | ||
// SNARKs without computation commitmnets | ||
type S1 = nova_snark::spartan::batched::BatchedRelaxedR1CSSNARK<E1, EE1>; | ||
type S2 = nova_snark::spartan::snark::RelaxedR1CSSNARK<E2, EE2>; | ||
// SNARKs with computation commitmnets | ||
type SS1 = nova_snark::spartan::batched_ppsnark::BatchedRelaxedR1CSSNARK<E1, EE1>; | ||
type SS2 = nova_snark::spartan::ppsnark::RelaxedR1CSSNARK<E2, EE2>; | ||
|
||
// To run these benchmarks, first download `criterion` with `cargo install cargo-criterion`. | ||
// Then `cargo criterion --bench compressed-snark-supernova`. The results are located in `target/criterion/data/<name-of-benchmark>`. | ||
// For flamegraphs, run `cargo criterion --bench compressed-snark-supernova --features flamegraph -- --profile-time <secs>`. | ||
// The results are located in `target/criterion/profile/<name-of-benchmark>`. | ||
cfg_if::cfg_if! { | ||
if #[cfg(feature = "flamegraph")] { | ||
criterion_group! { | ||
name = compressed_snark_supernova; | ||
config = Criterion::default().warm_up_time(Duration::from_millis(3000)).with_profiler(pprof::criterion::PProfProfiler::new(100, pprof::criterion::Output::Flamegraph(None))); | ||
targets = bench_one_augmented_circuit_compressed_snark, bench_two_augmented_circuit_compressed_snark, bench_two_augmented_circuit_compressed_snark_with_computational_commitments | ||
} | ||
} else { | ||
criterion_group! { | ||
name = compressed_snark_supernova; | ||
config = Criterion::default().warm_up_time(Duration::from_millis(3000)); | ||
targets = bench_one_augmented_circuit_compressed_snark, bench_two_augmented_circuit_compressed_snark, bench_two_augmented_circuit_compressed_snark_with_computational_commitments | ||
} | ||
} | ||
} | ||
|
||
criterion_main!(compressed_snark_supernova); | ||
|
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// This should match the value in test_supernova_recursive_circuit_pasta | ||
// TODO: This should also be a table matching the num_augmented_circuits in the below | ||
const NUM_CONS_VERIFIER_CIRCUIT_PRIMARY: usize = 9844; | ||
const NUM_SAMPLES: usize = 10; | ||
|
||
struct NonUniformBench<E1, E2, S> | ||
where | ||
E1: Engine<Base = <E2 as Engine>::Scalar>, | ||
E2: Engine<Base = <E1 as Engine>::Scalar>, | ||
S: StepCircuit<E2::Scalar> + Default, | ||
{ | ||
num_circuits: usize, | ||
num_cons: usize, | ||
_p: PhantomData<(E1, E2, S)>, | ||
} | ||
|
||
impl<E1, E2, S> NonUniformBench<E1, E2, S> | ||
where | ||
E1: Engine<Base = <E2 as Engine>::Scalar>, | ||
E2: Engine<Base = <E1 as Engine>::Scalar>, | ||
S: StepCircuit<E2::Scalar> + Default, | ||
{ | ||
fn new(num_circuits: usize, num_cons: usize) -> Self { | ||
Self { | ||
num_circuits, | ||
num_cons, | ||
_p: Default::default(), | ||
} | ||
} | ||
} | ||
|
||
impl<E1, E2, S> | ||
NonUniformCircuit<E1, E2, NonTrivialTestCircuit<E1::Scalar>, TrivialTestCircuit<E2::Scalar>> | ||
for NonUniformBench<E1, E2, S> | ||
where | ||
E1: Engine<Base = <E2 as Engine>::Scalar>, | ||
E2: Engine<Base = <E1 as Engine>::Scalar>, | ||
S: StepCircuit<E2::Scalar> + Default, | ||
{ | ||
fn num_circuits(&self) -> usize { | ||
self.num_circuits | ||
} | ||
|
||
fn primary_circuit(&self, circuit_index: usize) -> NonTrivialTestCircuit<E1::Scalar> { | ||
assert!( | ||
circuit_index < self.num_circuits, | ||
"Circuit index out of bounds: asked for {circuit_index}, but there are only {} circuits.", | ||
self.num_circuits | ||
); | ||
|
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NonTrivialTestCircuit::new(self.num_cons) | ||
} | ||
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fn secondary_circuit(&self) -> TrivialTestCircuit<E2::Scalar> { | ||
Default::default() | ||
} | ||
} | ||
|
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/// Benchmarks the compressed SNARK at a provided number of constraints | ||
/// | ||
/// Parameters | ||
/// - `num_augmented_circuits`: the number of augmented circuits in this configuration | ||
/// - `group`: the criterion benchmark group | ||
/// - `num_cons`: the number of constraints in the step circuit | ||
fn bench_compressed_snark_internal_with_arity< | ||
S1: BatchedRelaxedR1CSSNARKTrait<E1>, | ||
S2: RelaxedR1CSSNARKTrait<E2>, | ||
>( | ||
group: &mut BenchmarkGroup<'_, WallTime>, | ||
num_augmented_circuits: usize, | ||
num_cons: usize, | ||
) { | ||
let bench: NonUniformBench<E1, E2, TrivialTestCircuit<<E2 as Engine>::Scalar>> = | ||
NonUniformBench::new(num_augmented_circuits, num_cons); | ||
let pp = PublicParams::setup(&bench, &*S1::ck_floor(), &*S2::ck_floor()); | ||
|
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let num_steps = 3; | ||
let z0_primary = vec![<E1 as Engine>::Scalar::from(2u64)]; | ||
let z0_secondary = vec![<E2 as Engine>::Scalar::from(2u64)]; | ||
let mut recursive_snark_option: Option<RecursiveSNARK<E1, E2>> = None; | ||
let mut selected_augmented_circuit = 0; | ||
|
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for _ in 0..num_steps { | ||
let mut recursive_snark = recursive_snark_option.unwrap_or_else(|| { | ||
RecursiveSNARK::new( | ||
&pp, | ||
&bench, | ||
&bench.primary_circuit(0), | ||
&bench.secondary_circuit(), | ||
&z0_primary, | ||
&z0_secondary, | ||
) | ||
.unwrap() | ||
}); | ||
|
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if selected_augmented_circuit == 0 || selected_augmented_circuit == 1 { | ||
let res = recursive_snark.prove_step( | ||
&pp, | ||
&bench.primary_circuit(selected_augmented_circuit), | ||
&bench.secondary_circuit(), | ||
); | ||
res.expect("Prove step failed"); | ||
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let res = recursive_snark.verify(&pp, &z0_primary, &z0_secondary); | ||
res.expect("Verify failed"); | ||
} else { | ||
unimplemented!() | ||
} | ||
|
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selected_augmented_circuit = (selected_augmented_circuit + 1) % num_augmented_circuits; | ||
recursive_snark_option = Some(recursive_snark) | ||
} | ||
|
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assert!(recursive_snark_option.is_some()); | ||
let recursive_snark = recursive_snark_option.unwrap(); | ||
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let (prover_key, verifier_key) = CompressedSNARK::<_, _, _, _, S1, S2>::setup(&pp).unwrap(); | ||
|
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// Benchmark the prove time | ||
group.bench_function("Prove", |b| { | ||
b.iter(|| { | ||
assert!(CompressedSNARK::<_, _, _, _, S1, S2>::prove( | ||
black_box(&pp), | ||
black_box(&prover_key), | ||
black_box(&recursive_snark) | ||
) | ||
.is_ok()); | ||
}) | ||
}); | ||
|
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let res = CompressedSNARK::<_, _, _, _, S1, S2>::prove(&pp, &prover_key, &recursive_snark); | ||
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assert!(res.is_ok()); | ||
let compressed_snark = res.unwrap(); | ||
|
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// Benchmark the verification time | ||
group.bench_function("Verify", |b| { | ||
b.iter(|| { | ||
assert!(black_box(&compressed_snark) | ||
.verify( | ||
black_box(&pp), | ||
black_box(&verifier_key), | ||
black_box(&z0_primary), | ||
black_box(&z0_secondary), | ||
) | ||
.is_ok()); | ||
}) | ||
}); | ||
} | ||
|
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fn bench_one_augmented_circuit_compressed_snark(c: &mut Criterion) { | ||
// we vary the number of constraints in the step circuit | ||
for &num_cons_in_augmented_circuit in [ | ||
NUM_CONS_VERIFIER_CIRCUIT_PRIMARY, | ||
16384, | ||
32768, | ||
65536, | ||
131072, | ||
262144, | ||
524288, | ||
1048576, | ||
] | ||
.iter() | ||
{ | ||
// number of constraints in the step circuit | ||
let num_cons = num_cons_in_augmented_circuit - NUM_CONS_VERIFIER_CIRCUIT_PRIMARY; | ||
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let mut group = c.benchmark_group(format!( | ||
"CompressedSNARKSuperNova-1circuit-StepCircuitSize-{num_cons}" | ||
)); | ||
group.sample_size(NUM_SAMPLES); | ||
|
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bench_compressed_snark_internal_with_arity::<S1, S2>(&mut group, 1, num_cons); | ||
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group.finish(); | ||
} | ||
} | ||
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fn bench_two_augmented_circuit_compressed_snark(c: &mut Criterion) { | ||
// we vary the number of constraints in the step circuit | ||
for &num_cons_in_augmented_circuit in [ | ||
NUM_CONS_VERIFIER_CIRCUIT_PRIMARY, | ||
16384, | ||
32768, | ||
65536, | ||
131072, | ||
262144, | ||
524288, | ||
1048576, | ||
] | ||
.iter() | ||
{ | ||
// number of constraints in the step circuit | ||
let num_cons = num_cons_in_augmented_circuit - NUM_CONS_VERIFIER_CIRCUIT_PRIMARY; | ||
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let mut group = c.benchmark_group(format!( | ||
"CompressedSNARKSuperNova-2circuit-StepCircuitSize-{num_cons}" | ||
)); | ||
group.sample_size(NUM_SAMPLES); | ||
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bench_compressed_snark_internal_with_arity::<S1, S2>(&mut group, 2, num_cons); | ||
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group.finish(); | ||
} | ||
} | ||
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fn bench_two_augmented_circuit_compressed_snark_with_computational_commitments(c: &mut Criterion) { | ||
// we vary the number of constraints in the step circuit | ||
for &num_cons_in_augmented_circuit in [ | ||
NUM_CONS_VERIFIER_CIRCUIT_PRIMARY, | ||
16384, | ||
32768, | ||
65536, | ||
131072, | ||
262144, | ||
524288, | ||
1048576, | ||
] | ||
.iter() | ||
{ | ||
// number of constraints in the step circuit | ||
let num_cons = num_cons_in_augmented_circuit - NUM_CONS_VERIFIER_CIRCUIT_PRIMARY; | ||
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let mut group = c.benchmark_group(format!( | ||
"CompressedSNARKSuperNova-Commitments-2circuit-StepCircuitSize-{num_cons}" | ||
)); | ||
group.sample_size(NUM_SAMPLES); | ||
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bench_compressed_snark_internal_with_arity::<SS1, SS2>(&mut group, 2, num_cons); | ||
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group.finish(); | ||
} | ||
} | ||
#[derive(Clone, Debug, Default)] | ||
struct NonTrivialTestCircuit<F: PrimeField> { | ||
num_cons: usize, | ||
_p: PhantomData<F>, | ||
} | ||
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impl<F> NonTrivialTestCircuit<F> | ||
where | ||
F: PrimeField, | ||
{ | ||
pub fn new(num_cons: usize) -> Self { | ||
Self { | ||
num_cons, | ||
_p: Default::default(), | ||
} | ||
} | ||
} | ||
impl<F> StepCircuit<F> for NonTrivialTestCircuit<F> | ||
where | ||
F: PrimeField, | ||
{ | ||
fn arity(&self) -> usize { | ||
1 | ||
} | ||
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fn circuit_index(&self) -> usize { | ||
0 | ||
} | ||
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fn synthesize<CS: ConstraintSystem<F>>( | ||
&self, | ||
cs: &mut CS, | ||
pc: Option<&AllocatedNum<F>>, | ||
z: &[AllocatedNum<F>], | ||
) -> Result<(Option<AllocatedNum<F>>, Vec<AllocatedNum<F>>), SynthesisError> { | ||
// Consider a an equation: `x^{2 * num_cons} = y`, where `x` and `y` are respectively the input and output. | ||
let mut x = z[0].clone(); | ||
let mut y = x.clone(); | ||
for i in 0..self.num_cons { | ||
y = x.square(cs.namespace(|| format!("x_sq_{i}")))?; | ||
x = y.clone(); | ||
} | ||
Ok((pc.cloned(), vec![y])) | ||
} | ||
} |
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