Add GKR implementation of Grand Product lookups

crates/prover/Cargo.toml

@@ -23,7 +23,7 @@ starknet-crypto = "0.6.2"
 starknet-ff = "0.3.7"
 thiserror.workspace = true
 tracing.workspace = true
-rayon = {version = "1.10.0", optional = true}
+rayon = { version = "1.10.0", optional = true }
 
 [dev-dependencies]
 aligned = "0.4.2"

crates/prover/src/core/backend/cpu/lookups/gkr.rs

@@ -1,23 +1,87 @@
+use num_traits::Zero;
+
 use crate::core::backend::CpuBackend;
 use crate::core::fields::qm31::SecureField;
-use crate::core::lookups::gkr_prover::{GkrMultivariatePolyOracle, GkrOps, Layer};
+use crate::core::fields::Field;
+use crate::core::lookups::gkr_prover::{
+    correct_sum_as_poly_in_first_variable, EqEvals, GkrMultivariatePolyOracle, GkrOps, Layer,
+};
 use crate::core::lookups::mle::Mle;
+use crate::core::lookups::sumcheck::MultivariatePolyOracle;
+use crate::core::lookups::utils::UnivariatePoly;
 
 impl GkrOps for CpuBackend {
     fn gen_eq_evals(y: &[SecureField], v: SecureField) -> Mle<Self, SecureField> {
         Mle::new(gen_eq_evals(y, v))
     }
 
-    fn next_layer(_layer: &Layer<Self>) -> Layer<Self> {
-        todo!()
+    fn next_layer(layer: &Layer<Self>) -> Layer<Self> {
+        match layer {
+            Layer::GrandProduct(layer) => next_grand_product_layer(layer),
+            Layer::_LogUp(_) => todo!(),
+        }
     }
 
     fn sum_as_poly_in_first_variable(
-        _h: &GkrMultivariatePolyOracle<'_, Self>,
-        _claim: SecureField,
-    ) -> crate::core::lookups::utils::UnivariatePoly<SecureField> {
-        todo!()
+        h: &GkrMultivariatePolyOracle<'_, Self>,
+        claim: SecureField,
+    ) -> UnivariatePoly<SecureField> {
+        let n_variables = h.n_variables();
+        assert!(!n_variables.is_zero());
+        let n_terms = 1 << (n_variables - 1);
+        let eq_evals = h.eq_evals;
+        // Vector used to generate evaluations of `eq(x, y)` for `x` in the boolean hypercube.
+        let y = eq_evals.y();
+        let input_layer = &h.input_layer;
+
+        let (mut eval_at_0, mut eval_at_2) = match input_layer {
+            Layer::GrandProduct(col) => eval_grand_product_sum(eq_evals, col, n_terms),
+            Layer::_LogUp(_) => todo!(),
+        };
+
+        // Corrects the difference between two univariate sums in `t`:
+        // 1. `sum_x eq(({0}^|r|, 0, x), y) * F(r, t, x)`
+        // 2. `sum_x eq((r,       t, x), y) * F(r, t, x)`
+        {
+            eval_at_0 *= h.eq_fixed_var_correction;
+            eval_at_2 *= h.eq_fixed_var_correction;
+            correct_sum_as_poly_in_first_variable(eval_at_0, eval_at_2, claim, y, n_variables)
+        }
+    }
+}
+
+/// Evaluates `sum_x eq(({0}^|r|, 0, x), y) * inp(r, t, x, 0) * inp(r, t, x, 1)` at `t=0` and `t=2`.
+///
+/// Output of the form: `(eval_at_0, eval_at_2)`.
+fn eval_grand_product_sum(
+    eq_evals: &EqEvals<CpuBackend>,
+    input_layer: &Mle<CpuBackend, SecureField>,
+    n_terms: usize,
+) -> (SecureField, SecureField) {
+    let mut eval_at_0 = SecureField::zero();
+    let mut eval_at_2 = SecureField::zero();
+
+    for i in 0..n_terms {
+        // Input polynomial at points `(r, {0, 1, 2}, bits(i), {0, 1})`.
+        let inp_at_r0i0 = input_layer[i * 2];
+        let inp_at_r0i1 = input_layer[i * 2 + 1];
+        let inp_at_r1i0 = input_layer[(n_terms + i) * 2];
+        let inp_at_r1i1 = input_layer[(n_terms + i) * 2 + 1];
+        // Note `inp(r, t, x) = eq(t, 0) * inp(r, 0, x) + eq(t, 1) * inp(r, 1, x)`
+        //   => `inp(r, 2, x) = 2 * inp(r, 1, x) - inp(r, 0, x)`
+        let inp_at_r2i0 = inp_at_r1i0.double() - inp_at_r0i0;
+        let inp_at_r2i1 = inp_at_r1i1.double() - inp_at_r0i1;
+
+        // Product polynomial `prod(x) = inp(x, 0) * inp(x, 1)` at points `(r, {0, 2}, bits(i))`.
+        let prod_at_r2i = inp_at_r2i0 * inp_at_r2i1;
+        let prod_at_r0i = inp_at_r0i0 * inp_at_r0i1;
+
+        let eq_eval_at_0i = eq_evals[i];
+        eval_at_0 += eq_eval_at_0i * prod_at_r0i;
+        eval_at_2 += eq_eval_at_0i * prod_at_r2i;
     }
+
+    (eval_at_0, eval_at_2)
 }
 
 /// Returns evaluations `eq(x, y) * v` for all `x` in `{0, 1}^n`.
@@ -40,15 +104,24 @@ fn gen_eq_evals(y: &[SecureField], v: SecureField) -> Vec<SecureField> {
     evals
 }
 
+fn next_grand_product_layer(layer: &Mle<CpuBackend, SecureField>) -> Layer<CpuBackend> {
+    let res = layer.array_chunks().map(|&[a, b]| a * b).collect();
+    Layer::GrandProduct(Mle::new(res))
+}
+
 #[cfg(test)]
 mod tests {
     use num_traits::{One, Zero};
 
     use crate::core::backend::CpuBackend;
+    use crate::core::channel::Channel;
     use crate::core::fields::m31::BaseField;
     use crate::core::fields::qm31::SecureField;
-    use crate::core::lookups::gkr_prover::GkrOps;
+    use crate::core::lookups::gkr_prover::{prove_batch, GkrOps, Layer};
+    use crate::core::lookups::gkr_verifier::{partially_verify_batch, Gate, GkrArtifact, GkrError};
+    use crate::core::lookups::mle::Mle;
     use crate::core::lookups::utils::eq;
+    use crate::core::test_utils::test_channel;
 
     #[test]
     fn gen_eq_evals() {
@@ -69,4 +142,24 @@ mod tests {
             ]
         );
     }
+
+    #[test]
+    fn grand_product_works() -> Result<(), GkrError> {
+        const N: usize = 1 << 5;
+        let values = test_channel().draw_felts(N);
+        let product = values.iter().product::<SecureField>();
+        let col = Mle::<CpuBackend, SecureField>::new(values);
+        let input_layer = Layer::GrandProduct(col.clone());
+        let (proof, _) = prove_batch(&mut test_channel(), vec![input_layer]);
+
+        let GkrArtifact {
+            ood_point: r,
+            claims_to_verify_by_instance,
+            ..
+        } = partially_verify_batch(vec![Gate::GrandProduct], &proof, &mut test_channel())?;
+
+        assert_eq!(proof.output_claims_by_instance, [vec![product]]);
+        assert_eq!(claims_to_verify_by_instance, [vec![col.eval_at_point(&r)]]);
+        Ok(())
+    }
 }

crates/prover/src/core/lookups/gkr_prover.rs

@@ -12,10 +12,12 @@ use super::sumcheck::MultivariatePolyOracle;
 use super::utils::{eq, random_linear_combination, UnivariatePoly};
 use crate::core::backend::{Col, Column, ColumnOps};
 use crate::core::channel::Channel;
+use crate::core::fields::m31::BaseField;
 use crate::core::fields::qm31::SecureField;
+use crate::core::fields::FieldExpOps;
 use crate::core::lookups::sumcheck;
 
-pub trait GkrOps: MleOps<SecureField> {
+pub trait GkrOps: MleOps<BaseField> + MleOps<SecureField> {
     /// Returns evaluations `eq(x, y) * v` for all `x` in `{0, 1}^n`.
     ///
     /// Note [`Mle`] stores values in bit-reversed order.
@@ -85,13 +87,16 @@ impl<B: ColumnOps<SecureField>> Deref for EqEvals<B> {
 /// [LogUp]: https://eprint.iacr.org/2023/1284.pdf
 pub enum Layer<B: GkrOps> {
     _LogUp(B),
-    _GrandProduct(B),
+    GrandProduct(Mle<B, SecureField>),
 }
 
 impl<B: GkrOps> Layer<B> {
     /// Returns the number of variables used to interpolate the layer's gate values.
     fn n_variables(&self) -> usize {
-        todo!()
+        match self {
+            Self::_LogUp(_) => todo!(),
+            Self::GrandProduct(mle) => mle.n_variables(),
+        }
     }
 
     /// Produces the next layer from the current layer.
@@ -112,7 +117,28 @@ impl<B: GkrOps> Layer<B> {
 
     /// Returns each column output if the layer is an output layer, otherwise returns an `Err`.
     fn try_into_output_layer_values(self) -> Result<Vec<SecureField>, NotOutputLayerError> {
-        todo!()
+        if !self.is_output_layer() {
+            return Err(NotOutputLayerError);
+        }
+
+        Ok(match self {
+            Self::GrandProduct(col) => {
+                vec![col.at(0)]
+            }
+            Self::_LogUp(_) => todo!(),
+        })
+    }
+
+    /// Returns a transformed layer with the first variable of each column fixed to `assignment`.
+    fn fix_first_variable(self, x0: SecureField) -> Self {
+        if self.n_variables() == 0 {
+            return self;
+        }
+
+        match self {
+            Self::_LogUp(_) => todo!(),
+            Self::GrandProduct(mle) => Self::GrandProduct(mle.fix_first_variable(x0)),
+        }
     }
 
     /// Represents the next GKR layer evaluation as a multivariate polynomial which uses this GKR
@@ -145,9 +171,13 @@ impl<B: GkrOps> Layer<B> {
     fn into_multivariate_poly(
         self,
         _lambda: SecureField,
-        _eq_evals: &EqEvals<B>,
+        eq_evals: &EqEvals<B>,
     ) -> GkrMultivariatePolyOracle<'_, B> {
-        todo!()
+        GkrMultivariatePolyOracle {
+            eq_evals,
+            input_layer: self,
+            eq_fixed_var_correction: SecureField::one(),
+        }
     }
 }
 
@@ -164,15 +194,26 @@ pub struct GkrMultivariatePolyOracle<'a, B: GkrOps> {
 
 impl<'a, B: GkrOps> MultivariatePolyOracle for GkrMultivariatePolyOracle<'a, B> {
     fn n_variables(&self) -> usize {
-        todo!()
+        self.input_layer.n_variables() - 1
     }
 
-    fn sum_as_poly_in_first_variable(&self, _claim: SecureField) -> UnivariatePoly<SecureField> {
-        todo!()
+    fn sum_as_poly_in_first_variable(&self, claim: SecureField) -> UnivariatePoly<SecureField> {
+        B::sum_as_poly_in_first_variable(self, claim)
     }
 
-    fn fix_first_variable(self, _challenge: SecureField) -> Self {
-        todo!()
+    fn fix_first_variable(self, challenge: SecureField) -> Self {
+        if self.n_variables() == 0 {
+            return self;
+        }
+
+        let z0 = self.eq_evals.y()[self.eq_evals.y().len() - self.n_variables()];
+        let eq_fixed_var_correction = self.eq_fixed_var_correction * eq(&[challenge], &[z0]);
+
+        Self {
+            eq_evals: self.eq_evals,
+            eq_fixed_var_correction,
+            input_layer: self.input_layer.fix_first_variable(challenge),
+        }
     }
 }
 
@@ -188,7 +229,14 @@ impl<'a, B: GkrOps> GkrMultivariatePolyOracle<'a, B> {
     ///
     /// For more context see <https://people.cs.georgetown.edu/jthaler/ProofsArgsAndZK.pdf> page 64.
     fn try_into_mask(self) -> Result<GkrMask, NotConstantPolyError> {
-        todo!()
+        if self.n_variables() != 0 {
+            return Err(NotConstantPolyError);
+        }
+
+        match self.input_layer {
+            Layer::_LogUp(_) => todo!(),
+            Layer::GrandProduct(mle) => Ok(GkrMask::new(vec![mle.to_cpu().try_into().unwrap()])),
+        }
     }
 }
 
@@ -319,3 +367,72 @@ fn gen_layers<B: GkrOps>(input_layer: Layer<B>) -> Vec<Layer<B>> {
     assert_eq!(layers.len(), n_variables + 1);
     layers
 }
+
+/// Corrects and interpolates GKR instance sumcheck round polynomials that are generated with the
+/// precomputed `eq(x, y)` evaluations provided by `Layer::into_multivariate_poly()`.
+///
+/// Let `y` be a fixed vector of length `n` and let `z` be a subvector comprising of the last `k`
+/// elements of `y`. Returns the univariate polynomial `f(t) = sum_x eq((t, x), z) * p(t, x)` for
+/// `x` in the boolean hypercube `{0, 1}^(k-1)` when provided with:
+///
+/// * `claim` equalling `f(0) + f(1)`.
+/// * `eval_at_0/2` equalling `sum_x eq(({0}^(n-k+1), x), y) * p(t, x)` at `t=0,2` respectively.
+///
+/// Note that `f` must have degree <= 3.
+///
+/// For more context see `Layer::into_multivariate_poly()` docs.
+/// See also <https://ia.cr/2024/108> (section 3.2).
+///
+/// # Panics
+///
+/// Panics if:
+/// * `k` is zero or greater than the length of `y`.
+/// * `z_0` is zero.
+pub fn correct_sum_as_poly_in_first_variable(
+    eval_at_0: SecureField,
+    eval_at_2: SecureField,
+    claim: SecureField,
+    y: &[SecureField],
+    k: usize,
+) -> UnivariatePoly<SecureField> {
+    assert_ne!(k, 0);
+    let n = y.len();
+    assert!(k <= n);
+
+    let z = &y[n - k..];
+
+    // Corrects the difference between two sums:
+    // 1. `sum_x eq(({0}^(n-k+1), x), y) * p(t, x)`
+    // 2. `sum_x eq((0, x), z) * p(t, x)`
+    let eq_y_to_z_correction_factor = eq(&vec![SecureField::zero(); n - k], &y[0..n - k]).inverse();
+
+    // Corrects the difference between two sums:
+    // 1. `sum_x eq((0, x), z) * p(t, x)`
+    // 2. `sum_x eq((t, x), z) * p(t, x)`
+    let eq_correction_factor_at = |t| eq(&[t], &[z[0]]) / eq(&[SecureField::zero()], &[z[0]]);
+
+    // Let `v(t) = sum_x eq((0, x), z) * p(t, x)`. Apply trick from
+    // <https://ia.cr/2024/108> (section 3.2) to obtain `f` from `v`.
+    let t0: SecureField = BaseField::zero().into();
+    let t1: SecureField = BaseField::one().into();
+    let t2: SecureField = BaseField::from(2).into();
+    let t3: SecureField = BaseField::from(3).into();
+
+    // Obtain evals `v(0)`, `v(1)`, `v(2)`.
+    let mut y0 = eq_y_to_z_correction_factor * eval_at_0;
+    let mut y1 = (claim - y0) / eq_correction_factor_at(t1);
+    let mut y2 = eq_y_to_z_correction_factor * eval_at_2;
+
+    // Interpolate `v` to find `v(3)`. Note `v` has degree <= 2.
+    let v = UnivariatePoly::interpolate_lagrange(&[t0, t1, t2], &[y0, y1, y2]);
+    let mut y3 = v.eval_at_point(t3);
+
+    // Obtain evals of `f(0)`, `f(1)`, `f(2)`, `f(3)`.
+    y0 *= eq_correction_factor_at(t0);
+    y1 *= eq_correction_factor_at(t1);
+    y2 *= eq_correction_factor_at(t2);
+    y3 *= eq_correction_factor_at(t3);
+
+    // Interpolate `f(t)`. Note `f(t)` has degree <= 3.
+    UnivariatePoly::interpolate_lagrange(&[t0, t1, t2, t3], &[y0, y1, y2, y3])
+}