* merkle: add parent() helper function on NodeIndex * smt: add pairs_to_leaf() to trait * smt: add sorted_pairs_to_leaves() and test for it * smt: implement single subtree-8 hashing, w/ benchmarks & tests This will be composed into depth-8-subtree-based computation of entire sparse Merkle trees. * merkle: add a benchmark for constructing 256-balanced trees This is intended for comparison with the benchmarks from the previous commit. This benchmark represents the theoretical perfect-efficiency performance we could possibly (but impractically) get for computing depth-8 sparse Merkle subtrees. * smt: test that SparseMerkleTree::build_subtree() is composable * smt: test that subtree logic can correctly construct an entire tree This commit ensures that `SparseMerkleTree::build_subtree()` can correctly compose into building an entire sparse Merkle tree, without yet getting into potential complications concurrency introduces. * smt: implement test for basic parallelized subtree computation w/ rayon Building on the previous commit, this commit implements a test proving that `SparseMerkleTree::build_subtree()` can be composed into itself not just concurrently, but in parallel, without issue. * smt: add from_raw_parts() to trait interface This commit adds a new required method to the SparseMerkleTree trait, to allow generic construction from pre-computed parts. This will be used to add a generic version of `with_entries()` in a later commit. * smt: add parallel constructors to Smt and SimpleSmt What the previous few commits have been leading up to: SparseMerkleTree now has a function to construct the tree from existing data in parallel. This is significantly faster than the singlethreaded equivalent. Benchmarks incoming! --------- Co-authored-by: krushimir <krushimir@reilabs.co> Co-authored-by: krushimir <kresimir.grofelnik@reilabs.io>
142 lines
5.2 KiB
Rust
142 lines
5.2 KiB
Rust
use std::{fmt::Debug, hint, mem, time::Duration};
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use criterion::{criterion_group, criterion_main, BatchSize, BenchmarkId, Criterion};
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use miden_crypto::{
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hash::rpo::RpoDigest,
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merkle::{build_subtree_for_bench, NodeIndex, SmtLeaf, SubtreeLeaf, SMT_DEPTH},
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Felt, Word, ONE,
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};
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use rand_utils::prng_array;
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use winter_utils::Randomizable;
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const PAIR_COUNTS: [u64; 5] = [1, 64, 128, 192, 256];
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fn smt_subtree_even(c: &mut Criterion) {
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let mut seed = [0u8; 32];
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let mut group = c.benchmark_group("subtree8-even");
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for pair_count in PAIR_COUNTS {
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let bench_id = BenchmarkId::from_parameter(pair_count);
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group.bench_with_input(bench_id, &pair_count, |b, &pair_count| {
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b.iter_batched(
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|| {
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// Setup.
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let entries: Vec<(RpoDigest, Word)> = (0..pair_count)
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.map(|n| {
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// A single depth-8 subtree can have a maximum of 255 leaves.
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let leaf_index = ((n as f64 / pair_count as f64) * 255.0) as u64;
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let key = RpoDigest::new([
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generate_value(&mut seed),
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ONE,
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Felt::new(n),
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Felt::new(leaf_index),
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]);
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let value = generate_word(&mut seed);
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(key, value)
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})
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.collect();
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let mut leaves: Vec<_> = entries
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.iter()
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.map(|(key, value)| {
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let leaf = SmtLeaf::new_single(*key, *value);
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let col = NodeIndex::from(leaf.index()).value();
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let hash = leaf.hash();
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SubtreeLeaf { col, hash }
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})
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.collect();
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leaves.sort();
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leaves.dedup_by_key(|leaf| leaf.col);
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leaves
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},
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|leaves| {
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// Benchmarked function.
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let (subtree, _) = build_subtree_for_bench(
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hint::black_box(leaves),
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hint::black_box(SMT_DEPTH),
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hint::black_box(SMT_DEPTH),
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);
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assert!(!subtree.is_empty());
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},
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BatchSize::SmallInput,
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);
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});
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}
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}
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fn smt_subtree_random(c: &mut Criterion) {
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let mut seed = [0u8; 32];
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let mut group = c.benchmark_group("subtree8-rand");
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for pair_count in PAIR_COUNTS {
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let bench_id = BenchmarkId::from_parameter(pair_count);
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group.bench_with_input(bench_id, &pair_count, |b, &pair_count| {
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b.iter_batched(
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|| {
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// Setup.
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let entries: Vec<(RpoDigest, Word)> = (0..pair_count)
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.map(|i| {
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let leaf_index: u8 = generate_value(&mut seed);
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let key = RpoDigest::new([
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ONE,
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ONE,
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Felt::new(i),
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Felt::new(leaf_index as u64),
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]);
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let value = generate_word(&mut seed);
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(key, value)
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})
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.collect();
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let mut leaves: Vec<_> = entries
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.iter()
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.map(|(key, value)| {
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let leaf = SmtLeaf::new_single(*key, *value);
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let col = NodeIndex::from(leaf.index()).value();
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let hash = leaf.hash();
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SubtreeLeaf { col, hash }
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})
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.collect();
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leaves.sort();
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leaves
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},
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|leaves| {
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let (subtree, _) = build_subtree_for_bench(
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hint::black_box(leaves),
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hint::black_box(SMT_DEPTH),
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hint::black_box(SMT_DEPTH),
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);
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assert!(!subtree.is_empty());
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},
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BatchSize::SmallInput,
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);
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});
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}
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}
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criterion_group! {
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name = smt_subtree_group;
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config = Criterion::default()
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.measurement_time(Duration::from_secs(40))
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.sample_size(60)
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.configure_from_args();
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targets = smt_subtree_even, smt_subtree_random
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}
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criterion_main!(smt_subtree_group);
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// HELPER FUNCTIONS
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// --------------------------------------------------------------------------------------------
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fn generate_value<T: Copy + Debug + Randomizable>(seed: &mut [u8; 32]) -> T {
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mem::swap(seed, &mut prng_array(*seed));
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let value: [T; 1] = rand_utils::prng_array(*seed);
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value[0]
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}
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fn generate_word(seed: &mut [u8; 32]) -> Word {
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mem::swap(seed, &mut prng_array(*seed));
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let nums: [u64; 4] = prng_array(*seed);
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[Felt::new(nums[0]), Felt::new(nums[1]), Felt::new(nums[2]), Felt::new(nums[3])]
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}
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