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fix: eagerly build precomputed SpMV tables, remove OnceCell (v0.68.0 → v0.68.1) #484

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fix: eagerly build precomputed SpMV tables, remove OnceCell (v0.68.0 → v0.68.1) #484

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2 changes: 1 addition & 1 deletion Cargo.toml
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Original file line number Diff line number Diff line change
@@ -1,6 +1,6 @@
[package]
name = "nova-snark"
version = "0.68.0"
version = "0.68.1"
authors = ["Srinath Setty <srinath@microsoft.com>"]
edition = "2021"
description = "High-speed recursive arguments from folding schemes"
Expand Down
196 changes: 99 additions & 97 deletions src/r1cs/mod.rs
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Original file line number Diff line number Diff line change
Expand Up @@ -27,23 +27,46 @@ use sparse::PrecomputedSparseMatrix;
pub use sparse::SparseMatrix;

/// A type that holds the shape of the R1CS matrices
#[derive(Clone, Debug, Serialize, Deserialize)]
#[derive(Clone, Debug, Serialize)]
pub struct R1CSShape<E: Engine> {
pub(crate) num_cons: usize,
pub(crate) num_vars: usize,
pub(crate) num_io: usize,
pub(crate) A: SparseMatrix<E::Scalar>,
pub(crate) B: SparseMatrix<E::Scalar>,
pub(crate) C: SparseMatrix<E::Scalar>,
#[serde(skip, default = "OnceCell::new")]
#[serde(skip)]
pub(crate) digest: OnceCell<E::Scalar>,
/// Precomputed SpMV accelerators (built lazily on first use)
#[serde(skip, default = "OnceCell::new")]
precomputed_A: OnceCell<PrecomputedSparseMatrix<E::Scalar>>,
#[serde(skip, default = "OnceCell::new")]
precomputed_B: OnceCell<PrecomputedSparseMatrix<E::Scalar>>,
#[serde(skip, default = "OnceCell::new")]
precomputed_C: OnceCell<PrecomputedSparseMatrix<E::Scalar>>,
#[serde(skip)]
precomputed_A: PrecomputedSparseMatrix<E::Scalar>,
#[serde(skip)]
precomputed_B: PrecomputedSparseMatrix<E::Scalar>,
#[serde(skip)]
precomputed_C: PrecomputedSparseMatrix<E::Scalar>,
}

// Custom Deserialize: rebuild precomputed SpMV tables from the matrices.
impl<'de, E: Engine> Deserialize<'de> for R1CSShape<E> {
fn deserialize<D: serde::Deserializer<'de>>(deserializer: D) -> Result<Self, D::Error> {
#[derive(Deserialize)]
struct R1CSShapeRaw<F: ff::PrimeField> {
num_cons: usize,
num_vars: usize,
num_io: usize,
A: SparseMatrix<F>,
B: SparseMatrix<F>,
C: SparseMatrix<F>,
}
let raw = R1CSShapeRaw::<E::Scalar>::deserialize(deserializer)?;
Ok(Self::make(
raw.num_cons,
raw.num_vars,
raw.num_io,
raw.A,
raw.B,
raw.C,
))
}
}

impl<E: Engine> SimpleDigestible for R1CSShape<E> {}
Expand Down Expand Up @@ -140,6 +163,38 @@ impl<E: Engine> R1CSShape<E> {
&self.C
}

/// Internal constructor: builds precomputed SpMV tables eagerly.
fn make(
num_cons: usize,
num_vars: usize,
num_io: usize,
A: SparseMatrix<E::Scalar>,
B: SparseMatrix<E::Scalar>,
C: SparseMatrix<E::Scalar>,
) -> Self {
let (precomputed_A, (precomputed_B, precomputed_C)) = rayon::join(
|| PrecomputedSparseMatrix::from_sparse(&A),
|| {
rayon::join(
|| PrecomputedSparseMatrix::from_sparse(&B),
|| PrecomputedSparseMatrix::from_sparse(&C),
)
},
);
Self {
num_cons,
num_vars,
num_io,
A,
B,
C,
digest: OnceCell::new(),
precomputed_A,
precomputed_B,
precomputed_C,
}
}

/// Create an object of type `R1CSShape` from the explicitly specified R1CS matrices
pub fn new(
num_cons: usize,
Expand Down Expand Up @@ -169,18 +224,7 @@ impl<E: Engine> R1CSShape<E> {
is_valid(num_cons, num_vars, num_io, &B)?;
is_valid(num_cons, num_vars, num_io, &C)?;

Ok(R1CSShape {
num_cons,
num_vars,
num_io,
A,
B,
C,
digest: OnceCell::new(),
precomputed_A: OnceCell::new(),
precomputed_B: OnceCell::new(),
precomputed_C: OnceCell::new(),
})
Ok(Self::make(num_cons, num_vars, num_io, A, B, C))
}

/// Computes the maximum number of generators needed for a set of R1CS shapes.
Expand Down Expand Up @@ -351,21 +395,6 @@ impl<E: Engine> R1CSShape<E> {
.expect("Failure in retrieving digest")
}

/// Eagerly build the precomputed SpMV tables for A, B, C.
/// Call this once during setup so that folding steps don't pay the
/// one-time construction cost on their first multiply_vec_pair call.
pub fn precompute_sparse_matrices(&self) {
self
.precomputed_A
.get_or_init(|| PrecomputedSparseMatrix::from_sparse(&self.A));
self
.precomputed_B
.get_or_init(|| PrecomputedSparseMatrix::from_sparse(&self.B));
self
.precomputed_C
.get_or_init(|| PrecomputedSparseMatrix::from_sparse(&self.C));
}

// Checks regularity conditions on the R1CSShape, required in Spartan-class SNARKs
// Returns false if num_cons or num_vars are not powers of two, or if num_io > num_vars
#[inline]
Expand All @@ -385,19 +414,14 @@ impl<E: Engine> R1CSShape<E> {
return Err(NovaError::InvalidWitnessLength);
}

let pa = self
.precomputed_A
.get_or_init(|| PrecomputedSparseMatrix::from_sparse(&self.A));
let pb = self
.precomputed_B
.get_or_init(|| PrecomputedSparseMatrix::from_sparse(&self.B));
let pc = self
.precomputed_C
.get_or_init(|| PrecomputedSparseMatrix::from_sparse(&self.C));

let (Az, (Bz, Cz)) = rayon::join(
|| pa.multiply_vec(z),
|| rayon::join(|| pb.multiply_vec(z), || pc.multiply_vec(z)),
|| self.precomputed_A.multiply_vec(z),
|| {
rayon::join(
|| self.precomputed_B.multiply_vec(z),
|| self.precomputed_C.multiply_vec(z),
)
},
);

Ok((Az, Bz, Cz))
Expand All @@ -420,22 +444,12 @@ impl<E: Engine> R1CSShape<E> {
return Err(NovaError::InvalidWitnessLength);
}

let pa = self
.precomputed_A
.get_or_init(|| PrecomputedSparseMatrix::from_sparse(&self.A));
let pb = self
.precomputed_B
.get_or_init(|| PrecomputedSparseMatrix::from_sparse(&self.B));
let pc = self
.precomputed_C
.get_or_init(|| PrecomputedSparseMatrix::from_sparse(&self.C));

let ((Az1, Az2), ((Bz1, Bz2), (Cz1, Cz2))) = rayon::join(
|| pa.multiply_vec_pair(z1, z2),
|| self.precomputed_A.multiply_vec_pair(z1, z2),
|| {
rayon::join(
|| pb.multiply_vec_pair(z1, z2),
|| pc.multiply_vec_pair(z1, z2),
|| self.precomputed_B.multiply_vec_pair(z1, z2),
|| self.precomputed_C.multiply_vec_pair(z1, z2),
)
},
);
Expand Down Expand Up @@ -632,18 +646,14 @@ impl<E: Engine> R1CSShape<E> {
// check if the number of variables are as expected, then
// we simply set the number of constraints to the next power of two
if self.num_vars == m {
return R1CSShape {
num_cons: m,
num_vars: m,
num_io: self.num_io,
A: self.A.clone(),
B: self.B.clone(),
C: self.C.clone(),
digest: OnceCell::new(),
precomputed_A: OnceCell::new(),
precomputed_B: OnceCell::new(),
precomputed_C: OnceCell::new(),
};
return Self::make(
m,
m,
self.num_io,
self.A.clone(),
self.B.clone(),
self.C.clone(),
);
}

// otherwise, we need to pad the number of variables and renumber variable accesses
Expand Down Expand Up @@ -671,18 +681,14 @@ impl<E: Engine> R1CSShape<E> {
let B_padded = apply_pad(self.B.clone());
let C_padded = apply_pad(self.C.clone());

R1CSShape {
num_cons: num_cons_padded,
num_vars: num_vars_padded,
num_io: self.num_io,
A: A_padded,
B: B_padded,
C: C_padded,
digest: OnceCell::new(),
precomputed_A: OnceCell::new(),
precomputed_B: OnceCell::new(),
precomputed_C: OnceCell::new(),
}
Self::make(
num_cons_padded,
num_vars_padded,
self.num_io,
A_padded,
B_padded,
C_padded,
)
}

/// Pads the `R1CSShape` so that `num_cons` and `num_vars` are each
Expand Down Expand Up @@ -723,18 +729,14 @@ impl<E: Engine> R1CSShape<E> {
let B_padded = apply_pad(self.B.clone());
let C_padded = apply_pad(self.C.clone());

R1CSShape {
num_cons: num_cons_padded,
num_vars: num_vars_padded,
num_io: self.num_io,
A: A_padded,
B: B_padded,
C: C_padded,
digest: OnceCell::new(),
precomputed_A: OnceCell::new(),
precomputed_B: OnceCell::new(),
precomputed_C: OnceCell::new(),
}
Self::make(
num_cons_padded,
num_vars_padded,
self.num_io,
A_padded,
B_padded,
C_padded,
)
}

/// Samples a new random `RelaxedR1CSInstance`/`RelaxedR1CSWitness` pair
Expand Down
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