|
|
@ -4,8 +4,9 @@ use clap::Parser; |
|
|
use miden_crypto::{
|
|
|
use miden_crypto::{
|
|
|
hash::rpo::{Rpo256, RpoDigest},
|
|
|
hash::rpo::{Rpo256, RpoDigest},
|
|
|
merkle::{MerkleError, Smt},
|
|
|
merkle::{MerkleError, Smt},
|
|
|
Felt, Word, ONE,
|
|
|
|
|
|
|
|
|
Felt, Word, EMPTY_WORD, ONE,
|
|
|
};
|
|
|
};
|
|
|
|
|
|
use rand::{prelude::IteratorRandom, thread_rng, Rng};
|
|
|
use rand_utils::rand_value;
|
|
|
use rand_utils::rand_value;
|
|
|
|
|
|
|
|
|
#[derive(Parser, Debug)]
|
|
|
#[derive(Parser, Debug)]
|
|
|
@ -13,7 +14,7 @@ use rand_utils::rand_value; |
|
|
pub struct BenchmarkCmd {
|
|
|
pub struct BenchmarkCmd {
|
|
|
/// Size of the tree
|
|
|
/// Size of the tree
|
|
|
#[clap(short = 's', long = "size")]
|
|
|
#[clap(short = 's', long = "size")]
|
|
|
size: u64,
|
|
|
|
|
|
|
|
|
size: usize,
|
|
|
}
|
|
|
}
|
|
|
|
|
|
|
|
|
fn main() {
|
|
|
fn main() {
|
|
|
@ -29,101 +30,152 @@ pub fn benchmark_smt() { |
|
|
let mut entries = Vec::new();
|
|
|
let mut entries = Vec::new();
|
|
|
for i in 0..tree_size {
|
|
|
for i in 0..tree_size {
|
|
|
let key = rand_value::<RpoDigest>();
|
|
|
let key = rand_value::<RpoDigest>();
|
|
|
let value = [ONE, ONE, ONE, Felt::new(i)];
|
|
|
|
|
|
|
|
|
let value = [ONE, ONE, ONE, Felt::new(i as u64)];
|
|
|
entries.push((key, value));
|
|
|
entries.push((key, value));
|
|
|
}
|
|
|
}
|
|
|
|
|
|
|
|
|
let mut tree = construction(entries, tree_size).unwrap();
|
|
|
|
|
|
insertion(&mut tree, tree_size).unwrap();
|
|
|
|
|
|
batched_insertion(&mut tree, tree_size).unwrap();
|
|
|
|
|
|
proof_generation(&mut tree, tree_size).unwrap();
|
|
|
|
|
|
|
|
|
let mut tree = construction(entries.clone(), tree_size).unwrap();
|
|
|
|
|
|
insertion(&mut tree).unwrap();
|
|
|
|
|
|
batched_insertion(&mut tree).unwrap();
|
|
|
|
|
|
batched_update(&mut tree, entries).unwrap();
|
|
|
|
|
|
proof_generation(&mut tree).unwrap();
|
|
|
}
|
|
|
}
|
|
|
|
|
|
|
|
|
/// Runs the construction benchmark for [`Smt`], returning the constructed tree.
|
|
|
/// Runs the construction benchmark for [`Smt`], returning the constructed tree.
|
|
|
pub fn construction(entries: Vec<(RpoDigest, Word)>, size: u64) -> Result<Smt, MerkleError> {
|
|
|
|
|
|
|
|
|
pub fn construction(entries: Vec<(RpoDigest, Word)>, size: usize) -> Result<Smt, MerkleError> {
|
|
|
println!("Running a construction benchmark:");
|
|
|
println!("Running a construction benchmark:");
|
|
|
let now = Instant::now();
|
|
|
let now = Instant::now();
|
|
|
let tree = Smt::with_entries(entries)?;
|
|
|
let tree = Smt::with_entries(entries)?;
|
|
|
let elapsed = now.elapsed();
|
|
|
|
|
|
println!(
|
|
|
|
|
|
"Constructed a SMT with {} key-value pairs in {:.1} seconds",
|
|
|
|
|
|
size,
|
|
|
|
|
|
elapsed.as_secs_f32(),
|
|
|
|
|
|
);
|
|
|
|
|
|
|
|
|
let elapsed = now.elapsed().as_secs_f32();
|
|
|
|
|
|
|
|
|
|
|
|
println!("Constructed a SMT with {size} key-value pairs in {elapsed:.1} seconds");
|
|
|
println!("Number of leaf nodes: {}\n", tree.leaves().count());
|
|
|
println!("Number of leaf nodes: {}\n", tree.leaves().count());
|
|
|
|
|
|
|
|
|
Ok(tree)
|
|
|
Ok(tree)
|
|
|
}
|
|
|
}
|
|
|
|
|
|
|
|
|
/// Runs the insertion benchmark for the [`Smt`].
|
|
|
/// Runs the insertion benchmark for the [`Smt`].
|
|
|
pub fn insertion(tree: &mut Smt, size: u64) -> Result<(), MerkleError> {
|
|
|
|
|
|
|
|
|
pub fn insertion(tree: &mut Smt) -> Result<(), MerkleError> {
|
|
|
|
|
|
const NUM_INSERTIONS: usize = 1_000;
|
|
|
|
|
|
|
|
|
println!("Running an insertion benchmark:");
|
|
|
println!("Running an insertion benchmark:");
|
|
|
|
|
|
|
|
|
|
|
|
let size = tree.num_leaves();
|
|
|
let mut insertion_times = Vec::new();
|
|
|
let mut insertion_times = Vec::new();
|
|
|
|
|
|
|
|
|
const N: u64 = 100;
|
|
|
|
|
|
for i in 0..N {
|
|
|
|
|
|
|
|
|
for i in 0..NUM_INSERTIONS {
|
|
|
let test_key = Rpo256::hash(&rand_value::<u64>().to_be_bytes());
|
|
|
let test_key = Rpo256::hash(&rand_value::<u64>().to_be_bytes());
|
|
|
let test_value = [ONE, ONE, ONE, Felt::new(size + i)];
|
|
|
|
|
|
|
|
|
let test_value = [ONE, ONE, ONE, Felt::new((size + i) as u64)];
|
|
|
|
|
|
|
|
|
let now = Instant::now();
|
|
|
let now = Instant::now();
|
|
|
tree.insert(test_key, test_value);
|
|
|
tree.insert(test_key, test_value);
|
|
|
let elapsed = now.elapsed();
|
|
|
let elapsed = now.elapsed();
|
|
|
insertion_times.push(elapsed.as_secs_f32());
|
|
|
|
|
|
|
|
|
insertion_times.push(elapsed.as_micros());
|
|
|
}
|
|
|
}
|
|
|
|
|
|
|
|
|
println!(
|
|
|
println!(
|
|
|
"An average insertion time measured by {N} inserts into a SMT with {size} key-value pairs is {:.1} ms\n",
|
|
|
|
|
|
// calculate the average by dividing by 100 and convert to milliseconds by multiplying by
|
|
|
|
|
|
// 1000. As a result, we can only multiply by 10
|
|
|
|
|
|
insertion_times.iter().sum::<f32>() * 10_f32,
|
|
|
|
|
|
|
|
|
"An average insertion time measured by {NUM_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),
|
|
|
);
|
|
|
);
|
|
|
|
|
|
|
|
|
Ok(())
|
|
|
Ok(())
|
|
|
}
|
|
|
}
|
|
|
|
|
|
|
|
|
pub fn batched_insertion(tree: &mut Smt, size: u64) -> Result<(), MerkleError> {
|
|
|
|
|
|
|
|
|
pub fn batched_insertion(tree: &mut Smt) -> Result<(), MerkleError> {
|
|
|
|
|
|
const NUM_INSERTIONS: usize = 1_000;
|
|
|
|
|
|
|
|
|
println!("Running a batched insertion benchmark:");
|
|
|
println!("Running a batched insertion benchmark:");
|
|
|
|
|
|
|
|
|
let new_pairs: Vec<(RpoDigest, Word)> = (0..1000)
|
|
|
|
|
|
|
|
|
let size = tree.num_leaves();
|
|
|
|
|
|
|
|
|
|
|
|
let new_pairs: Vec<(RpoDigest, Word)> = (0..NUM_INSERTIONS)
|
|
|
.map(|i| {
|
|
|
.map(|i| {
|
|
|
let key = Rpo256::hash(&rand_value::<u64>().to_be_bytes());
|
|
|
let key = Rpo256::hash(&rand_value::<u64>().to_be_bytes());
|
|
|
let value = [ONE, ONE, ONE, Felt::new(size + i)];
|
|
|
|
|
|
|
|
|
let value = [ONE, ONE, ONE, Felt::new((size + i) as u64)];
|
|
|
(key, value)
|
|
|
(key, value)
|
|
|
})
|
|
|
})
|
|
|
.collect();
|
|
|
.collect();
|
|
|
|
|
|
|
|
|
let now = Instant::now();
|
|
|
let now = Instant::now();
|
|
|
let mutations = tree.compute_mutations(new_pairs);
|
|
|
let mutations = tree.compute_mutations(new_pairs);
|
|
|
let compute_elapsed = now.elapsed();
|
|
|
|
|
|
|
|
|
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",
|
|
|
|
|
|
compute_elapsed,
|
|
|
|
|
|
compute_elapsed * 1000_f64 / NUM_INSERTIONS as f64, // time in μs
|
|
|
|
|
|
);
|
|
|
|
|
|
|
|
|
|
|
|
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",
|
|
|
|
|
|
apply_elapsed,
|
|
|
|
|
|
apply_elapsed * 1000_f64 / NUM_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",
|
|
|
|
|
|
(compute_elapsed + apply_elapsed),
|
|
|
|
|
|
);
|
|
|
|
|
|
|
|
|
|
|
|
println!();
|
|
|
|
|
|
|
|
|
|
|
|
Ok(())
|
|
|
|
|
|
}
|
|
|
|
|
|
|
|
|
|
|
|
pub fn batched_update(tree: &mut Smt, entries: Vec<(RpoDigest, Word)>) -> Result<(), MerkleError> {
|
|
|
|
|
|
const NUM_UPDATES: usize = 1_000;
|
|
|
|
|
|
const REMOVAL_PROBABILITY: f64 = 0.2;
|
|
|
|
|
|
|
|
|
|
|
|
println!("Running a batched update benchmark:");
|
|
|
|
|
|
|
|
|
|
|
|
let size = tree.num_leaves();
|
|
|
|
|
|
let mut rng = thread_rng();
|
|
|
|
|
|
|
|
|
|
|
|
let new_pairs =
|
|
|
|
|
|
entries
|
|
|
|
|
|
.into_iter()
|
|
|
|
|
|
.choose_multiple(&mut rng, NUM_UPDATES)
|
|
|
|
|
|
.into_iter()
|
|
|
|
|
|
.map(|(key, _)| {
|
|
|
|
|
|
let value = if rng.gen_bool(REMOVAL_PROBABILITY) {
|
|
|
|
|
|
EMPTY_WORD
|
|
|
|
|
|
} else {
|
|
|
|
|
|
[ONE, ONE, ONE, Felt::new(rng.gen())]
|
|
|
|
|
|
};
|
|
|
|
|
|
|
|
|
|
|
|
(key, value)
|
|
|
|
|
|
});
|
|
|
|
|
|
|
|
|
|
|
|
assert_eq!(new_pairs.len(), NUM_UPDATES);
|
|
|
|
|
|
|
|
|
|
|
|
let now = Instant::now();
|
|
|
|
|
|
let mutations = tree.compute_mutations(new_pairs);
|
|
|
|
|
|
let compute_elapsed = now.elapsed().as_secs_f64() * 1000_f64; // time in ms
|
|
|
|
|
|
|
|
|
let now = Instant::now();
|
|
|
let now = Instant::now();
|
|
|
tree.apply_mutations(mutations).unwrap();
|
|
|
|
|
|
let apply_elapsed = now.elapsed();
|
|
|
|
|
|
|
|
|
tree.apply_mutations(mutations)?;
|
|
|
|
|
|
let apply_elapsed = now.elapsed().as_secs_f64() * 1000_f64; // time in ms
|
|
|
|
|
|
|
|
|
println!(
|
|
|
println!(
|
|
|
"An average batch computation time measured by a 1k-batch into an SMT with {} key-value pairs over {:.1} ms is {:.3} ms",
|
|
|
|
|
|
size,
|
|
|
|
|
|
compute_elapsed.as_secs_f32() * 1000f32,
|
|
|
|
|
|
// Dividing by the number of iterations, 1000, and then multiplying by 1000 to get
|
|
|
|
|
|
// milliseconds, cancels out.
|
|
|
|
|
|
compute_elapsed.as_secs_f32(),
|
|
|
|
|
|
|
|
|
"An average update-batch computation time measured by a {NUM_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
|
|
|
);
|
|
|
);
|
|
|
|
|
|
|
|
|
println!(
|
|
|
println!(
|
|
|
"An average batch application time measured by a 1k-batch into an SMT with {} key-value pairs over {:.1} ms is {:.3} ms",
|
|
|
|
|
|
size,
|
|
|
|
|
|
apply_elapsed.as_secs_f32() * 1000f32,
|
|
|
|
|
|
// Dividing by the number of iterations, 1000, and then multiplying by 1000 to get
|
|
|
|
|
|
// milliseconds, cancels out.
|
|
|
|
|
|
apply_elapsed.as_secs_f32(),
|
|
|
|
|
|
|
|
|
"An average update-batch application time measured by a {NUM_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
|
|
|
);
|
|
|
);
|
|
|
|
|
|
|
|
|
println!(
|
|
|
println!(
|
|
|
"An average batch insertion time measured by a 1k-batch into an SMT with {} key-value pairs totals to {:.1} ms",
|
|
|
|
|
|
size,
|
|
|
|
|
|
(compute_elapsed + apply_elapsed).as_secs_f32() * 1000f32,
|
|
|
|
|
|
|
|
|
"An average batch update time measured by a 1k-batch into an SMT with {size} leaves totals to {:.1} ms",
|
|
|
|
|
|
(compute_elapsed + apply_elapsed),
|
|
|
);
|
|
|
);
|
|
|
|
|
|
|
|
|
println!();
|
|
|
println!();
|
|
|
@ -132,28 +184,28 @@ pub fn batched_insertion(tree: &mut Smt, size: u64) -> Result<(), MerkleError> { |
|
|
}
|
|
|
}
|
|
|
|
|
|
|
|
|
/// Runs the proof generation benchmark for the [`Smt`].
|
|
|
/// Runs the proof generation benchmark for the [`Smt`].
|
|
|
pub fn proof_generation(tree: &mut Smt, size: u64) -> Result<(), MerkleError> {
|
|
|
|
|
|
|
|
|
pub fn proof_generation(tree: &mut Smt) -> Result<(), MerkleError> {
|
|
|
|
|
|
const NUM_PROOFS: usize = 100;
|
|
|
|
|
|
|
|
|
println!("Running a proof generation benchmark:");
|
|
|
println!("Running a proof generation benchmark:");
|
|
|
|
|
|
|
|
|
let mut insertion_times = Vec::new();
|
|
|
let mut insertion_times = Vec::new();
|
|
|
|
|
|
let size = tree.num_leaves();
|
|
|
|
|
|
|
|
|
const N: u64 = 100;
|
|
|
|
|
|
for i in 0..N {
|
|
|
|
|
|
|
|
|
for i in 0..NUM_PROOFS {
|
|
|
let test_key = Rpo256::hash(&rand_value::<u64>().to_be_bytes());
|
|
|
let test_key = Rpo256::hash(&rand_value::<u64>().to_be_bytes());
|
|
|
let test_value = [ONE, ONE, ONE, Felt::new(size + i)];
|
|
|
|
|
|
|
|
|
let test_value = [ONE, ONE, ONE, Felt::new((size + i) as u64)];
|
|
|
tree.insert(test_key, test_value);
|
|
|
tree.insert(test_key, test_value);
|
|
|
|
|
|
|
|
|
let now = Instant::now();
|
|
|
let now = Instant::now();
|
|
|
let _proof = tree.open(&test_key);
|
|
|
let _proof = tree.open(&test_key);
|
|
|
let elapsed = now.elapsed();
|
|
|
|
|
|
insertion_times.push(elapsed.as_secs_f32());
|
|
|
|
|
|
|
|
|
insertion_times.push(now.elapsed().as_micros());
|
|
|
}
|
|
|
}
|
|
|
|
|
|
|
|
|
println!(
|
|
|
println!(
|
|
|
"An average proving time measured by {N} value proofs in a SMT with {size} key-value pairs is {:.1} μs",
|
|
|
|
|
|
// calculate the average by dividing by 100 and convert to microseconds by multiplying by
|
|
|
|
|
|
// 1000000. As a result, we can only multiply by 10000
|
|
|
|
|
|
insertion_times.iter().sum::<f32>() * 10000_f32,
|
|
|
|
|
|
|
|
|
"An 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),
|
|
|
);
|
|
|
);
|
|
|
|
|
|
|
|
|
Ok(())
|
|
|
Ok(())
|
|
|
|
Bobbin Threadbare
3 months ago
GitHub