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docs: update changelog and readme

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Bobbin Threadbare 2024-01-05 16:38:32 -08:00 • committed by Bobbin Threadbare
parent 479fe5e649
commit 004a3bc7a8
9 changed files with 29 additions and 32 deletions
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2
CHANGELOG.md
View file

@ -4,7 +4,9 @@
* Updated Winterfell dependency to v0.7 (#200)
* Implemented RPX hash function (#201).
* Added `FeltRng` and `RpoRandomCoin` (#237).
* Accelerated RPO/RPX hash functions using AVX512 instructions (#234).
* Added `inner_nodes()` method to `PartialMmr` (#238).
* Improved `PartialMmr::apply_delta()` (#242).
## 0.7.1 (2023-10-10)

8
README.md
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@ -46,8 +46,14 @@ Both of these features imply the use of [alloc](https://doc.rust-lang.org/alloc/
To compile with `no_std`, disable default features via `--no-default-features` flag.
### AVX2 acceleration
On platforms with [AVX2](https://en.wikipedia.org/wiki/Advanced_Vector_Extensions) support, RPO and RPX hash function can be accelerated by using the vector processing unit. To enable AVX2 acceleration, the code needs to be compiled with the `avx2` target feature enabled. For example:
```shell
RUSTFLAGS="-C target-feature=+avx2" cargo build --release
```
### SVE acceleration
On platforms with [SVE](https://en.wikipedia.org/wiki/AArch64#Scalable_Vector_Extension_(SVE)) support, RPO hash function can be accelerated by using the vector processing unit. To enable SVE acceleration, the code needs to be compiled with the `sve` feature enabled. This feature has an effect only if the platform exposes `target-feature=sve` flag. On some platforms (e.g., Graviton 3), for this flag to be set, the compilation must be done in "native" mode. For example, to enable SVE acceleration on Graviton 3, we can execute the following:
On platforms with [SVE](https://en.wikipedia.org/wiki/AArch64#Scalable_Vector_Extension_(SVE)) support, RPO and RPX hash function can be accelerated by using the vector processing unit. To enable SVE acceleration, the code needs to be compiled with the `sve` feature enabled. This feature has an effect only if the platform exposes `target-feature=sve` flag. On some platforms (e.g., Graviton 3), for this flag to be set, the compilation must be done in "native" mode. For example, to enable SVE acceleration on Graviton 3, we can execute the following:
```shell
RUSTFLAGS="-C target-cpu=native" cargo build --release --features sve
```

3
benches/README.md
View file

@ -22,6 +22,7 @@ The second scenario is that of sequential hashing where we take a sequence of le
| Apple M2 Max | 71 ns | 233 ns | 1.3 µs | 7.9 µs | 4.6 µs | 2.4 µs |
| Amazon Graviton 3 | 108 ns | | | | 5.3 µs | 3.1 µs |
| AMD Ryzen 9 5950X | 64 ns | 273 ns | 1.2 µs | 9.1 µs | 5.5 µs | |
| AMD EPYC 9R14 | 83 ns | | | | 4.3 µs | 2.4 µs |
| Intel Core i5-8279U | 68 ns | 536 ns | 2.0 µs | 13.6 µs | 8.5 µs | 4.4 µs |
| Intel Xeon 8375C | 67 ns | | | | 8.2 µs | |
@ -33,11 +34,13 @@ The second scenario is that of sequential hashing where we take a sequence of le
| Apple M2 Max | 0.9 µs | 1.5 µs | 17.4 µs | 103 µs | 60 µs | 31 µs |
| Amazon Graviton 3 | 1.4 µs | | | | 69 µs | 41 µs |
| AMD Ryzen 9 5950X | 0.8 µs | 1.7 µs | 15.7 µs | 120 µs | 72 µs | |
| AMD EPYC 9R14 | 0.9 µs | | | | 56 µs | 32 µs |
| Intel Core i5-8279U | 0.9 µs | | | | 107 µs | 56 µs |
| Intel Xeon 8375C | 0.8 µs | | | | 110 µs | |
Notes:
- On Graviton 3, RPO256 and RPX256 are run with SVE acceleration enabled.
- On AMD EPYC 9R14, RPO256 and RPX256 are run with AVX2 acceleration enabled.
### Instructions
Before you can run the benchmarks, you'll need to make sure you have Rust [installed](https://www.rust-lang.org/tools/install). After that, to run the benchmarks for RPO and BLAKE3, clone the current repository, and from the root directory of the repo run the following:

6
benches/hash.rs
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@ -32,7 +32,6 @@ fn rpo256_2to1(c: &mut Criterion) {
fn rpo256_sequential(c: &mut Criterion) {
let v: [Felt; 100] = (0..100)
.into_iter()
.map(Felt::new)
.collect::<Vec<Felt>>()
.try_into()
@ -45,7 +44,6 @@ fn rpo256_sequential(c: &mut Criterion) {
bench.iter_batched(
|| {
let v: [Felt; 100] = (0..100)
.into_iter()
.map(|_| Felt::new(rand_value()))
.collect::<Vec<Felt>>()
.try_into()
@ -80,7 +78,6 @@ fn rpx256_2to1(c: &mut Criterion) {
fn rpx256_sequential(c: &mut Criterion) {
let v: [Felt; 100] = (0..100)
.into_iter()
.map(Felt::new)
.collect::<Vec<Felt>>()
.try_into()
@ -93,7 +90,6 @@ fn rpx256_sequential(c: &mut Criterion) {
bench.iter_batched(
|| {
let v: [Felt; 100] = (0..100)
.into_iter()
.map(|_| Felt::new(rand_value()))
.collect::<Vec<Felt>>()
.try_into()
@ -129,7 +125,6 @@ fn blake3_2to1(c: &mut Criterion) {
fn blake3_sequential(c: &mut Criterion) {
let v: [Felt; 100] = (0..100)
.into_iter()
.map(Felt::new)
.collect::<Vec<Felt>>()
.try_into()
@ -142,7 +137,6 @@ fn blake3_sequential(c: &mut Criterion) {
bench.iter_batched(
|| {
let v: [Felt; 100] = (0..100)
.into_iter()
.map(|_| Felt::new(rand_value()))
.collect::<Vec<Felt>>()
.try_into()

4
benches/smt.rs
View file

@ -27,7 +27,7 @@ fn smt_rpo(c: &mut Criterion) {
// benchmarks
let mut insert = c.benchmark_group(format!("smt update_leaf"));
let mut insert = c.benchmark_group("smt update_leaf".to_string());
for (tree, count) in trees.iter_mut() {
let depth = tree.depth();
@ -45,7 +45,7 @@ fn smt_rpo(c: &mut Criterion) {
insert.finish();
let mut path = c.benchmark_group(format!("smt get_leaf_path"));
let mut path = c.benchmark_group("smt get_leaf_path".to_string());
for (tree, count) in trees.iter_mut() {
let depth = tree.depth();

2
benches/store.rs
View file

@ -15,7 +15,7 @@ fn random_rpo_digest() -> RpoDigest {
/// Generates a random `Word`.
fn random_word() -> Word {
rand_array::<Felt, 4>().into()
rand_array::<Felt, 4>()
}
/// Generates an index at the specified depth in `0..range`.

4
src/merkle/partial_mt/tests.rs
View file

@ -209,7 +209,7 @@ fn get_paths() {
// Which have leaf nodes 20, 22, 23, 32 and 33. Hence overall we will have 5 paths -- one path
// for each leaf.
let leaves = vec![NODE20, NODE22, NODE23, NODE32, NODE33];
let leaves = [NODE20, NODE22, NODE23, NODE32, NODE33];
let expected_paths: Vec<(NodeIndex, ValuePath)> = leaves
.iter()
.map(|&leaf| {
@ -257,7 +257,7 @@ fn leaves() {
let value32 = mt.get_node(NODE32).unwrap();
let value33 = mt.get_node(NODE33).unwrap();
let leaves = vec![(NODE11, value11), (NODE20, value20), (NODE32, value32), (NODE33, value33)];
let leaves = [(NODE11, value11), (NODE20, value20), (NODE32, value32), (NODE33, value33)];
let expected_leaves = leaves.iter().copied();
assert!(expected_leaves.eq(pmt.leaves()));

19
src/merkle/simple_smt/tests.rs
View file

@ -35,7 +35,7 @@ const ZERO_VALUES8: [Word; 8] = [int_to_leaf(0); 8];
fn build_empty_tree() {
// tree of depth 3
let smt = SimpleSmt::new(3).unwrap();
let mt = MerkleTree::new(ZERO_VALUES8.to_vec()).unwrap();
let mt = MerkleTree::new(ZERO_VALUES8).unwrap();
assert_eq!(mt.root(), smt.root());
}
@ -74,14 +74,12 @@ fn build_sparse_tree() {
/// Tests that [`SimpleSmt::with_contiguous_leaves`] works as expected
#[test]
fn build_contiguous_tree() {
let tree_with_leaves = SimpleSmt::with_leaves(
2,
[0, 1, 2, 3].into_iter().zip(digests_to_words(&VALUES4).into_iter()),
)
let tree_with_leaves =
SimpleSmt::with_leaves(2, [0, 1, 2, 3].into_iter().zip(digests_to_words(&VALUES4)))
.unwrap();
let tree_with_contiguous_leaves =
SimpleSmt::with_contiguous_leaves(2, digests_to_words(&VALUES4).into_iter()).unwrap();
SimpleSmt::with_contiguous_leaves(2, digests_to_words(&VALUES4)).unwrap();
assert_eq!(tree_with_leaves, tree_with_contiguous_leaves);
}
@ -89,8 +87,7 @@ fn build_contiguous_tree() {
#[test]
fn test_depth2_tree() {
let tree =
SimpleSmt::with_leaves(2, KEYS4.into_iter().zip(digests_to_words(&VALUES4).into_iter()))
.unwrap();
SimpleSmt::with_leaves(2, KEYS4.into_iter().zip(digests_to_words(&VALUES4))).unwrap();
// check internal structure
let (root, node2, node3) = compute_internal_nodes();
@ -118,8 +115,7 @@ fn test_depth2_tree() {
#[test]
fn test_inner_node_iterator() -> Result<(), MerkleError> {
let tree =
SimpleSmt::with_leaves(2, KEYS4.into_iter().zip(digests_to_words(&VALUES4).into_iter()))
.unwrap();
SimpleSmt::with_leaves(2, KEYS4.into_iter().zip(digests_to_words(&VALUES4))).unwrap();
// check depth 2
assert_eq!(VALUES4[0], tree.get_node(NodeIndex::make(2, 0)).unwrap());
@ -150,8 +146,7 @@ fn test_inner_node_iterator() -> Result<(), MerkleError> {
#[test]
fn update_leaf() {
let mut tree =
SimpleSmt::with_leaves(3, KEYS8.into_iter().zip(digests_to_words(&VALUES8).into_iter()))
.unwrap();
SimpleSmt::with_leaves(3, KEYS8.into_iter().zip(digests_to_words(&VALUES8))).unwrap();
// update one value
let key = 3;

11
src/merkle/store/tests.rs
View file

@ -210,7 +210,7 @@ fn test_get_invalid_node() {
fn test_add_sparse_merkle_tree_one_level() -> Result<(), MerkleError> {
let keys2: [u64; 2] = [0, 1];
let leaves2: [Word; 2] = [int_to_leaf(1), int_to_leaf(2)];
let smt = SimpleSmt::with_leaves(1, keys2.into_iter().zip(leaves2.into_iter())).unwrap();
let smt = SimpleSmt::with_leaves(1, keys2.into_iter().zip(leaves2)).unwrap();
let store = MerkleStore::from(&smt);
let idx = NodeIndex::make(1, 0);
@ -228,7 +228,7 @@ fn test_add_sparse_merkle_tree_one_level() -> Result<(), MerkleError> {
fn test_sparse_merkle_tree() -> Result<(), MerkleError> {
let smt = SimpleSmt::with_leaves(
SimpleSmt::MAX_DEPTH,
KEYS4.into_iter().zip(digests_to_words(&VALUES4).into_iter()),
KEYS4.into_iter().zip(digests_to_words(&VALUES4)),
)
.unwrap();
@ -553,11 +553,8 @@ fn test_constructors() -> Result<(), MerkleError> {
}
let depth = 32;
let smt = SimpleSmt::with_leaves(
depth,
KEYS4.into_iter().zip(digests_to_words(&VALUES4).into_iter()),
)
.unwrap();
let smt =
SimpleSmt::with_leaves(depth, KEYS4.into_iter().zip(digests_to_words(&VALUES4))).unwrap();
let store = MerkleStore::from(&smt);
let depth = smt.depth();