chore: parallel clones for large data structures (#78)

src/provider/pedersen.rs

@@ -17,13 +17,22 @@ use rayon::prelude::*;
 use serde::{Deserialize, Serialize};
 
 /// A type that holds commitment generators
-#[derive(Clone, Debug, PartialEq, Eq, Serialize, Deserialize, Abomonation)]
+#[derive(Debug, PartialEq, Eq, Serialize, Deserialize, Abomonation)]
 #[abomonation_omit_bounds]
 pub struct CommitmentKey<G: Group> {
   #[abomonate_with(Vec<[u64; 8]>)] // this is a hack; we just assume the size of the element.
   ck: Vec<G::PreprocessedGroupElement>,
 }
 
+/// [CommitmentKey]s are often large, and this helps with cloning bottlenecks
+impl<G: Group> Clone for CommitmentKey<G> {
+  fn clone(&self) -> Self {
+    Self {
+      ck: self.ck.par_iter().cloned().collect(),
+    }
+  }
+}
+
 impl<G: Group> Len for CommitmentKey<G> {
   fn length(&self) -> usize {
     self.ck.len()

src/r1cs/sparse.rs

@@ -12,7 +12,7 @@ use serde::{Deserialize, Serialize};
 
 /// CSR format sparse matrix, We follow the names used by scipy.
 /// Detailed explanation here: <https://stackoverflow.com/questions/52299420/scipy-csr-matrix-understand-indptr>
-#[derive(Clone, Debug, PartialEq, Eq, Serialize, Deserialize, Abomonation)]
+#[derive(Debug, PartialEq, Eq, Serialize, Deserialize, Abomonation)]
 #[abomonation_bounds(where <F as PrimeField>::Repr: Abomonation)]
 pub struct SparseMatrix<F: PrimeField> {
   #[abomonate_with(Vec<F::Repr>)]
@@ -26,6 +26,18 @@ pub struct SparseMatrix<F: PrimeField> {
   pub cols: usize,
 }
 
+/// [SparseMatrix]s are often large, and this helps with cloning bottlenecks
+impl<F: PrimeField> Clone for SparseMatrix<F> {
+  fn clone(&self) -> Self {
+    Self {
+      data: self.data.par_iter().cloned().collect(),
+      indices: self.indices.par_iter().cloned().collect(),
+      indptr: self.indptr.par_iter().cloned().collect(),
+      cols: self.cols,
+    }
+  }
+}
+
 impl<F: PrimeField> SparseMatrix<F> {
   /// 0x0 empty matrix
   pub fn empty() -> Self {