-
Notifications
You must be signed in to change notification settings - Fork 116
Commit
This commit does not belong to any branch on this repository, and may belong to a fork outside of the repository.
synced docs+docsv3.2 for poseidon2, added theory part
- Loading branch information
Showing
4 changed files
with
243 additions
and
75 deletions.
There are no files selected for viewing
Loading
Sorry, something went wrong. Reload?
Sorry, we cannot display this file.
Sorry, this file is invalid so it cannot be displayed.
This file contains bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
Original file line number | Diff line number | Diff line change |
---|---|---|
@@ -1,91 +1,174 @@ | ||
# Poseidon2 | ||
|
||
TODO update for V3 | ||
[Poseidon2](https://eprint.iacr.org/2023/323) is a recently released optimized version of Poseidon. The two versions differ in two crucial points. First, Poseidon is a sponge hash function, while Poseidon2 can be either a sponge or a compression function depending on the use case. Secondly, Poseidon2 is instantiated by new and more efficient linear layers with respect to Poseidon. These changes decrease the number of multiplications in the linear layer by up to 90% and the number of constraints in Plonk circuits by up to 70%. This makes Poseidon2 currently the fastest arithmetization-oriented hash function without lookups. Since the compression mode is efficient it is ideal for use in Merkle trees as well. | ||
|
||
[Poseidon2](https://eprint.iacr.org/2023/323) is a recently released optimized version of Poseidon1. The two versions differ in two crucial points. First, Poseidon is a sponge hash function, while Poseidon2 can be either a sponge or a compression function depending on the use case. Secondly, Poseidon2 is instantiated by new and more efficient linear layers with respect to Poseidon. These changes decrease the number of multiplications in the linear layer by up to 90% and the number of constraints in Plonk circuits by up to 70%. This makes Poseidon2 currently the fastest arithmetization-oriented hash function without lookups. | ||
An overview of the Poseidon2 hash is provided in the diagram below | ||
![alt text](Poseidon2.png) | ||
|
||
## Description | ||
|
||
## Using Poseidon2 | ||
### Round constants | ||
|
||
ICICLE Poseidon2 is implemented for GPU and parallelization is performed for each state. | ||
We calculate multiple hash-sums over multiple pre-images in parallel, rather than going block by block over the input vector. | ||
* In the first full round and last full rounds Round constants are of the structure $[c_0,c_1,\ldots , c_{t-1}]$, where $c_i\in \mathbb{F}$ | ||
* In the partial rounds the round constants is only added to first element $[\tilde{c}_0,0,0,\ldots, 0_{t-1}]$, where $\tilde{c_0}\in \mathbb{F}$ | ||
|
||
For example, for Poseidon2 of width 16, input rate 8, output elements 8 and input of size 1024 * 8, we would expect 1024 * 8 elements of output. Which means each input block would be of size 8, resulting in 1024 Poseidon2 hashes being performed. | ||
Poseidon2 is also extremely customizable and using different constants will produce different hashes, security levels and performance results. | ||
|
||
### Supported Bindings | ||
We support pre-calculated constants for each of the [supported curves](../libraries#supported-curves-and-operations). The constants can be found [here](https://github.com/ingonyama-zk/icicle/tree/main/icicle/include/poseidon2/constants) and are labeled clearly per curve `<curve_name>_poseidon2.h`. | ||
|
||
[`Rust`](https://github.com/ingonyama-zk/icicle/tree/main/wrappers/rust/icicle-core/src/poseidon2) | ||
You can also use your own set of constants as shown [here](https://github.com/ingonyama-zk/icicle/blob/main/wrappers/rust/icicle-fields/icicle-babybear/src/poseidon2/mod.rs#L290) | ||
|
||
### Constants | ||
### S box | ||
|
||
Poseidon2 is also extremely customizable and using different constants will produce different hashes, security levels and performance results. | ||
Allowed values of $\alpha$ for a given prime is the smallest integer such that $gcd(\alpha,p-1)=1$ | ||
|
||
We support pre-calculated constants for each of the [supported curves](../libraries#supported-curves-and-operations). The constants can be found [here](https://github.com/ingonyama-zk/icicle/tree/main/icicle/include/poseidon2/constants) and are labeled clearly per curve `<curve_name>_poseidon2.h`. | ||
For ICICLE supported curves/fields | ||
|
||
You can also use your own set of constants as shown [here](https://github.com/ingonyama-zk/icicle/blob/main/wrappers/rust/icicle-fields/icicle-babybear/src/poseidon2/mod.rs#L290) | ||
* Mersene $\alpha = 5$ | ||
* Goldilocks $\alpha =7$ | ||
* Babybear $\alpha=7$ | ||
* Bls12-377 $\alpha =11$ | ||
* Bls12-381 $\alpha=5$ | ||
* BN254 $\alpha = 5$ | ||
* Grumpkin $\alpha = 5$ | ||
* Stark252 $\alpha=3$ | ||
|
||
### Rust API | ||
### MDS matrix structure | ||
|
||
This is the most basic way to use the Poseidon2 API. | ||
There are only two matrices: There is one type of matrix for full round and another for partial round. There are two cases available one for state size $t'=4\cdot t$ and another for $t=2,3$. | ||
|
||
```rust | ||
let test_size = 1 << 10; | ||
let width = 16; | ||
let rate = 8; | ||
let ctx = get_default_device_context(); | ||
let poseidon = Poseidon2::load(width, rate, MdsType::Default, DiffusionStrategy::Default, &ctx).unwrap(); | ||
let config = HashConfig::default(); | ||
#### $t=4\cdot t'$ where $t'$ is an integer | ||
|
||
let inputs = vec![F::one(); test_size * rate as usize]; | ||
let outputs = vec![F::zero(); test_size]; | ||
let mut input_slice = HostOrDeviceSlice::on_host(inputs); | ||
let mut output_slice = HostOrDeviceSlice::on_host(outputs); | ||
|
||
poseidon.hash_many::<F>( | ||
&mut input_slice, | ||
&mut output_slice, | ||
test_size as u32, | ||
rate as u32, | ||
8, // Output length | ||
&config, | ||
) | ||
.unwrap(); | ||
``` | ||
**Full Matrix** $M_{full}$ (Referred in paper as $M_{\mathcal{E}}$). These are hard coded (same for all primes $p>2^{30}$) for any fixed state size $t=4\cdot t'$ where $t'$ is an integer. | ||
|
||
$$ | ||
M_{4} = \begin{pmatrix} | ||
5 & 7 & 1 & 3 \\ | ||
4& 6 & 1 & 1 \\ | ||
1 & 3 & 5 & 7\\ | ||
1 & 1 & 4 & 6\\ | ||
\end{pmatrix} $$ | ||
|
||
As per the [paper](https://eprint.iacr.org/2023/323.pdf) this structure is always maintained and is always MDS for any prime $p>2^{30}$. | ||
|
||
eg for $t=8$ the matrix looks like | ||
|
||
$$ | ||
M_{full}^{8\times 8} = \begin{pmatrix} | ||
2\cdot M_4 & M_4 \\ | ||
M_4 & 2\cdot M_4 \\ | ||
\end{pmatrix} $$ | ||
|
||
**Partial Matrix** $M_{partial}$(referred in paper as $M_{\mathcal{I}}$) - There is only ONE partial matrix for all the partial rounds and has non zero diagonal entries along the diagonal and $1$ everywhere else. | ||
|
||
$$ | ||
M_{Partial}^{t\times t} = \begin{pmatrix} | ||
\mu_0 &1 & \ldots & 1 \\ | ||
1 &\mu_1 & \ldots & 1 \\ | ||
\vdots & \vdots & \ddots & \vdots \\ | ||
1 & 1 &\ldots & \mu_{t-1}\\ | ||
\end{pmatrix} $$ | ||
|
||
In the example above `Poseidon2::load(width, rate, MdsType::Default, DiffusionStrategy::Default, &ctx).unwrap();` is used to load the correct constants based on width and curve. Here, the default MDS matrices and diffusion are used. If you want to get a Plonky3 compliant version, set them to `MdsType::Plonky` and `DiffusionStrategy::Montgomery` respectively. | ||
where $\mu_i \in \mathbb{F}$. In general this matrix is different for each prime since one has to find values that satisfy some inequalities in a field. However unlike Poseidon there is only one $M_{partial}$ for all partial rounds. | ||
|
||
## The Tree Builder | ||
#### $t=2,3$ | ||
|
||
Similar to Poseidon1, you can use Poseidon2 in a tree builder. | ||
These are special state sizes. In all ICICLE supported curves/fields the matrices for $t=3$ are | ||
|
||
$$M_{full} = \begin{pmatrix} | ||
2 & 1 & 1 \\ | ||
1 & 2 & 1 \\ | ||
1 & 1 & 2 \\ | ||
\end{pmatrix} \ , \ M_{Partial} = \begin{pmatrix} | ||
2 & 1 & 1 \\ | ||
1 & 2 & 1 \\ | ||
1 & 1 & 3 \\ | ||
\end{pmatrix}$$ | ||
|
||
and the matrices for $t=2$ are | ||
|
||
$$M_{full} = \begin{pmatrix} | ||
2 & 1 \\ | ||
1 & 2 \\ | ||
\end{pmatrix} \ , \ M_{Partial} = \begin{pmatrix} | ||
2 & 1 \\ | ||
1 & 3 \\ | ||
\end{pmatrix}$$ | ||
|
||
# Supported Bindings | ||
|
||
[`Rust`](https://github.com/ingonyama-zk/icicle/tree/main/wrappers/rust/icicle-core/src/poseidon2) | ||
|
||
# Rust API | ||
|
||
This is the most basic way to use the Poseidon2 API. See the [examples/poseidon2](https://github.com/ingonyama-zk/icicle/tree/b12d83e6bcb8ee598409de78015bd118458a55d0/examples/rust/poseidon2) folder for the relevant code | ||
|
||
```rust | ||
use icicle_bn254::tree::Bn254TreeBuilder; | ||
use icicle_bn254::poseidon2::Poseidon2; | ||
|
||
let mut config = TreeBuilderConfig::default(); | ||
let arity = 2; | ||
config.arity = arity as u32; | ||
let input_block_len = arity; | ||
let leaves = vec![F::one(); (1 << height) * arity]; | ||
let mut digests = vec![F::zero(); merkle_tree_digests_len((height + 1) as u32, arity as u32, 1)]; | ||
|
||
let leaves_slice = HostSlice::from_slice(&leaves); | ||
let digests_slice = HostSlice::from_mut_slice(&mut digests); | ||
|
||
let ctx = device_context::DeviceContext::default(); | ||
let hash = Poseidon2::load(arity, arity, MdsType::Default, DiffusionStrategy::Default, &ctx).unwrap(); | ||
|
||
let mut config = TreeBuilderConfig::default(); | ||
config.keep_rows = 5; | ||
Bn254TreeBuilder::build_merkle_tree( | ||
leaves_slice, | ||
digests_slice, | ||
height, | ||
input_block_len, | ||
&hash, | ||
&hash, | ||
&config, | ||
) | ||
.unwrap(); | ||
let test_size = 4; | ||
let poseidon = Poseidon2::new::<F>(test_size,None).unwrap(); | ||
let config = HashConfig::default(); | ||
let inputs = vec![F::one(); test_size]; | ||
let input_slice = HostSlice::from_slice(&inputs); | ||
//digest is a single element | ||
let out_init:F = F::zero(); | ||
let mut binding = [out_init]; | ||
let out_init_slice = HostSlice::from_mut_slice(&mut binding); | ||
|
||
poseidon.hash(input_slice, &config, out_init_slice).unwrap(); | ||
println!("computed digest: {:?} ",out_init_slice.as_slice().to_vec()[0]); | ||
|
||
``` | ||
|
||
# Merkle Tree Builder | ||
|
||
Similar to Poseidon1, you can use Poseidon2 in a tree builder. See the [examples/poseidon2](https://github.com/ingonyama-zk/icicle/tree/b12d83e6bcb8ee598409de78015bd118458a55d0/examples/rust/poseidon2) folder for the relevant code. | ||
|
||
```rust | ||
pub fn compute_binary_tree<F:FieldImpl>( | ||
mut test_vec: Vec<F>, | ||
leaf_size: u64, | ||
hasher: Hasher, | ||
compress: Hasher, | ||
mut tree_config: MerkleTreeConfig, | ||
) -> MerkleTree | ||
{ | ||
let tree_height: usize = test_vec.len().ilog2() as usize; | ||
//just to be safe | ||
tree_config.padding_policy = PaddingPolicy::ZeroPadding; | ||
let layer_hashes: Vec<&Hasher> = std::iter::once(&hasher) | ||
.chain(std::iter::repeat(&compress).take(tree_height)) | ||
.collect(); | ||
let vec_slice: &mut HostSlice<F> = HostSlice::from_mut_slice(&mut test_vec[..]); | ||
let merkle_tree: MerkleTree = MerkleTree::new(&layer_hashes, leaf_size, 0).unwrap(); | ||
|
||
let _ = merkle_tree | ||
.build(vec_slice,&tree_config); | ||
merkle_tree | ||
} | ||
|
||
//poseidon2 supports t=2,3,4,8,12,16,20,24. In this example we build a binary tree with Poseidon2 t=2. | ||
let poseidon_state_size = 2; | ||
let leaf_size:u64 = 4;// each leaf is a 32 bit element 32/8 = 4 bytes | ||
|
||
let mut test_vec = vec![F::from_u32(random::<u32>()); 1024* (poseidon_state_size as usize)]; | ||
println!("Generated random vector of size {:?}", 1024* (poseidon_state_size as usize)); | ||
//to use later for merkle proof | ||
let mut binding = test_vec.clone(); | ||
let test_vec_slice = HostSlice::from_mut_slice(&mut binding); | ||
//define hash and compression functions (You can use different hashes here) | ||
//note:"None" does not work with generics, use F= Fm31, Fbabybear etc | ||
let hasher :Hasher = Poseidon2::new::<F>(poseidon_state_size.try_into().unwrap(),None).unwrap(); | ||
let compress: Hasher = Poseidon2::new::<F>((hasher.output_size()*2).try_into().unwrap(),None).unwrap(); | ||
//tree config | ||
let tree_config = MerkleTreeConfig::default(); | ||
let merk_tree = compute_binary_tree(test_vec.clone(), leaf_size, hasher, compress,tree_config.clone()); | ||
println!("computed Merkle root {:?}", merk_tree.get_root::<F>().unwrap()); | ||
|
||
let random_test_index = rand::thread_rng().gen_range(0..1024*(poseidon_state_size as usize)); | ||
print!("Generating proof for element {:?} at random test index {:?} ",test_vec[random_test_index], random_test_index); | ||
let merkle_proof = merk_tree.get_proof::<F>(test_vec_slice, random_test_index.try_into().unwrap(), false, &tree_config).unwrap(); | ||
|
||
//actually should construct verifier tree :) | ||
assert!(merk_tree.verify(&merkle_proof).unwrap()); | ||
println!("\n Merkle proof verified successfully!"); | ||
``` |
Loading
Sorry, something went wrong. Reload?
Sorry, we cannot display this file.
Sorry, this file is invalid so it cannot be displayed.
This file contains bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters