Implements concurrent Smt::compute_mutations

CHANGELOG.md

@@ -5,6 +5,7 @@
 ## 0.13.1 (2024-12-26)
 
 - Generate reverse mutations set on applying of mutations set, implemented serialization of `MutationsSet` (#355).
+- Added parallel implementation of `Smt::compute_mutations` with better performance (#365).
 
 ## 0.13.0 (2024-11-24)
 

src/main.rs

@@ -13,8 +13,14 @@ use rand_utils::rand_value;
 #[clap(name = "Benchmark", about = "SMT benchmark", version, rename_all = "kebab-case")]
 pub struct BenchmarkCmd {
     /// Size of the tree
-    #[clap(short = 's', long = "size")]
+    #[clap(short = 's', long = "size", default_value = "10000")]
     size: usize,
+    /// Number of insertions
+    #[clap(short = 'i', long = "insertions", default_value = "10000")]
+    insertions: usize,
+    /// Number of updates
+    #[clap(short = 'u', long = "updates", default_value = "10000")]
+    updates: usize,
 }
 
 fn main() {
@@ -25,7 +31,10 @@ fn main() {
 pub fn benchmark_smt() {
     let args = BenchmarkCmd::parse();
     let tree_size = args.size;
+    let insertions = args.insertions;
+    let updates = args.updates;
 
+    assert!(updates <= tree_size, "Cannot update more than `size`");
     // prepare the `leaves` vector for tree creation
     let mut entries = Vec::new();
     for i in 0..tree_size {
@@ -35,9 +44,9 @@ pub fn benchmark_smt() {
     }
 
     let mut tree = construction(entries.clone(), tree_size).unwrap();
-    insertion(&mut tree).unwrap();
-    batched_insertion(&mut tree).unwrap();
-    batched_update(&mut tree, entries).unwrap();
+    insertion(&mut tree.clone(), insertions).unwrap();
+    batched_insertion(&mut tree.clone(), insertions).unwrap();
+    batched_update(&mut tree.clone(), entries, updates).unwrap();
     proof_generation(&mut tree).unwrap();
 }
 
@@ -47,23 +56,20 @@ pub fn construction(entries: Vec<(RpoDigest, Word)>, size: usize) -> Result<Smt,
     let now = Instant::now();
     let tree = Smt::with_entries(entries)?;
     let elapsed = now.elapsed().as_secs_f32();
-
-    println!("Constructed a SMT with {size} key-value pairs in {elapsed:.1} seconds");
+    println!("Constructed an SMT with {size} key-value pairs in {elapsed:.1} seconds");
     println!("Number of leaf nodes: {}\n", tree.leaves().count());
 
     Ok(tree)
 }
 
 /// Runs the insertion benchmark for the [`Smt`].
-pub fn insertion(tree: &mut Smt) -> Result<(), MerkleError> {
-    const NUM_INSERTIONS: usize = 1_000;
-
+pub fn insertion(tree: &mut Smt, insertions: usize) -> Result<(), MerkleError> {
     println!("Running an insertion benchmark:");
 
     let size = tree.num_leaves();
     let mut insertion_times = Vec::new();
 
-    for i in 0..NUM_INSERTIONS {
+    for i in 0..insertions {
         let test_key = Rpo256::hash(&rand_value::<u64>().to_be_bytes());
         let test_value = [ONE, ONE, ONE, Felt::new((size + i) as u64)];
 
@@ -74,22 +80,20 @@ pub fn insertion(tree: &mut Smt) -> Result<(), MerkleError> {
     }
 
     println!(
-        "An average insertion time measured by {NUM_INSERTIONS} inserts into an SMT with {size} leaves is {:.0} μs\n",
+        "The average insertion time measured by {insertions} inserts into an SMT with {size} leaves is {:.0} μs\n",
         // calculate the average
-        insertion_times.iter().sum::<u128>() as f64 / (NUM_INSERTIONS as f64),
+        insertion_times.iter().sum::<u128>() as f64 / (insertions as f64),
     );
 
     Ok(())
 }
 
-pub fn batched_insertion(tree: &mut Smt) -> Result<(), MerkleError> {
-    const NUM_INSERTIONS: usize = 1_000;
-
+pub fn batched_insertion(tree: &mut Smt, insertions: usize) -> Result<(), MerkleError> {
     println!("Running a batched insertion benchmark:");
 
     let size = tree.num_leaves();
 
-    let new_pairs: Vec<(RpoDigest, Word)> = (0..NUM_INSERTIONS)
+    let new_pairs: Vec<(RpoDigest, Word)> = (0..insertions)
         .map(|i| {
             let key = Rpo256::hash(&rand_value::<u64>().to_be_bytes());
             let value = [ONE, ONE, ONE, Felt::new((size + i) as u64)];
@@ -101,24 +105,24 @@ pub fn batched_insertion(tree: &mut Smt) -> Result<(), MerkleError> {
     let mutations = tree.compute_mutations(new_pairs);
     let compute_elapsed = now.elapsed().as_secs_f64() * 1000_f64; // time in ms
 
-    let now = Instant::now();
-    tree.apply_mutations(mutations)?;
-    let apply_elapsed = now.elapsed().as_secs_f64() * 1000_f64; // time in ms
-
     println!(
-        "An average insert-batch computation time measured by a {NUM_INSERTIONS}-batch into an SMT with {size} leaves over {:.1} ms is {:.0} μs",
+        "The average insert-batch computation time measured by a {insertions}-batch into an SMT with {size} leaves over {:.1} ms is {:.0} μs",
         compute_elapsed,
-        compute_elapsed * 1000_f64 / NUM_INSERTIONS as f64, // time in μs
+        compute_elapsed * 1000_f64 / insertions as f64, // time in μs
     );
 
+    let now = Instant::now();
+    tree.apply_mutations(mutations)?;
+    let apply_elapsed = now.elapsed().as_secs_f64() * 1000_f64; // time in ms
+
     println!(
-        "An average insert-batch application time measured by a {NUM_INSERTIONS}-batch into an SMT with {size} leaves over {:.1} ms is {:.0} μs",
+        "The average insert-batch application time measured by a {insertions}-batch into an SMT with {size} leaves over {:.1} ms is {:.0} μs",
         apply_elapsed,
-        apply_elapsed * 1000_f64 / NUM_INSERTIONS as f64, // time in μs
+        apply_elapsed * 1000_f64 / insertions as f64, // time in μs
     );
 
     println!(
-        "An average batch insertion time measured by a 1k-batch into an SMT with {size} leaves totals to {:.1} ms",
+        "The average batch insertion time measured by a {insertions}-batch into an SMT with {size} leaves totals to {:.1} ms",
         (compute_elapsed + apply_elapsed),
     );
 
@@ -127,8 +131,11 @@ pub fn batched_insertion(tree: &mut Smt) -> Result<(), MerkleError> {
     Ok(())
 }
 
-pub fn batched_update(tree: &mut Smt, entries: Vec<(RpoDigest, Word)>) -> Result<(), MerkleError> {
-    const NUM_UPDATES: usize = 1_000;
+pub fn batched_update(
+    tree: &mut Smt,
+    entries: Vec<(RpoDigest, Word)>,
+    updates: usize,
+) -> Result<(), MerkleError> {
     const REMOVAL_PROBABILITY: f64 = 0.2;
 
     println!("Running a batched update benchmark:");
@@ -139,7 +146,7 @@ pub fn batched_update(tree: &mut Smt, entries: Vec<(RpoDigest, Word)>) -> Result
     let new_pairs =
         entries
             .into_iter()
-            .choose_multiple(&mut rng, NUM_UPDATES)
+            .choose_multiple(&mut rng, updates)
             .into_iter()
             .map(|(key, _)| {
                 let value = if rng.gen_bool(REMOVAL_PROBABILITY) {
@@ -151,7 +158,7 @@ pub fn batched_update(tree: &mut Smt, entries: Vec<(RpoDigest, Word)>) -> Result
                 (key, value)
             });
 
-    assert_eq!(new_pairs.len(), NUM_UPDATES);
+    assert_eq!(new_pairs.len(), updates);
 
     let now = Instant::now();
     let mutations = tree.compute_mutations(new_pairs);
@@ -162,19 +169,19 @@ pub fn batched_update(tree: &mut Smt, entries: Vec<(RpoDigest, Word)>) -> Result
     let apply_elapsed = now.elapsed().as_secs_f64() * 1000_f64; // time in ms
 
     println!(
-        "An average update-batch computation time measured by a {NUM_UPDATES}-batch into an SMT with {size} leaves over {:.1} ms is {:.0} μs",
+        "The average update-batch computation time measured by a {updates}-batch into an SMT with {size} leaves over {:.1} ms is {:.0} μs",
         compute_elapsed,
-        compute_elapsed * 1000_f64 / NUM_UPDATES as f64, // time in μs
+        compute_elapsed * 1000_f64 / updates as f64, // time in μs
     );
 
     println!(
-        "An average update-batch application time measured by a {NUM_UPDATES}-batch into an SMT with {size} leaves over {:.1} ms is {:.0} μs",
+        "The average update-batch application time measured by a {updates}-batch into an SMT with {size} leaves over {:.1} ms is {:.0} μs",
         apply_elapsed,
-        apply_elapsed * 1000_f64 / NUM_UPDATES as f64, // time in μs
+        apply_elapsed * 1000_f64 / updates as f64, // time in μs
     );
 
     println!(
-        "An average batch update time measured by a 1k-batch into an SMT with {size} leaves totals to {:.1} ms",
+        "The average batch update time measured by a {updates}-batch into an SMT with {size} leaves totals to {:.1} ms",
         (compute_elapsed + apply_elapsed),
     );
 
@@ -203,7 +210,7 @@ pub fn proof_generation(tree: &mut Smt) -> Result<(), MerkleError> {
     }
 
     println!(
-        "An average proving time measured by {NUM_PROOFS} value proofs in an SMT with {size} leaves in {:.0} μs",
+        "The average proving time measured by {NUM_PROOFS} value proofs in an SMT with {size} leaves in {:.0} μs",
         // calculate the average
         insertion_times.iter().sum::<u128>() as f64 / (NUM_PROOFS as f64),
     );