Struct Radix2DitParallel 

pub struct Radix2DitParallel<F> { /* private fields */ }

A parallel FFT algorithm which divides a butterfly network’s layers into two halves.

For the first half, we apply a butterfly network with smaller blocks in earlier layers, i.e. either DIT or Bowers G. Then we bit-reverse, and for the second half, we continue executing the same network but in bit-reversed order. This way we’re always working with small blocks, so within each half, we can have a certain amount of parallelism with no cross-thread communication.

Trait Implementations

impl<F: Clone> Clone for Radix2DitParallel<F>

fn clone(&self) -> Radix2DitParallel<F>

Returns a duplicate of the value.

fn clone_from(&mut self, source: &Self)

Performs copy-assignment from source.

impl<F: Debug> Debug for Radix2DitParallel<F>

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl<F: Default> Default for Radix2DitParallel<F>

fn default() -> Radix2DitParallel<F>

Returns the “default value” for a type.

impl<F: TwoAdicField + Ord> TwoAdicSubgroupDft<F> for Radix2DitParallel<F>

type Evaluations = RowIndexMappedView<BitReversalPerm, DenseMatrix<F>>

fn dft_batch(&self, mat: RowMajorMatrix<F>) -> Self::Evaluations

Compute the discrete Fourier transform (DFT) of each column in mat. This is the only method an implementer needs to define, all other methods can be derived from this one.

fn coset_lde_batch( &self, mat: RowMajorMatrix<F>, added_bits: usize, shift: F, ) -> Self::Evaluations

Compute the low-degree extension of each column in mat onto a coset of a larger subgroup.

fn dft(&self, vec: Vec<F>) -> Vec<F>

Compute the discrete Fourier transform (DFT) vec.

fn coset_dft(&self, vec: Vec<F>, shift: F) -> Vec<F>

Compute the “coset DFT” of vec. This can be viewed as interpolation onto a coset of a multiplicative subgroup, rather than the subgroup itself.

fn coset_dft_batch(&self, mat: RowMajorMatrix<F>, shift: F) -> Self::Evaluations

Compute the “coset DFT” of each column in mat. This can be viewed as interpolation onto a coset of a multiplicative subgroup, rather than the subgroup itself.

fn idft(&self, vec: Vec<F>) -> Vec<F>

Compute the inverse DFT of vec.

fn idft_batch(&self, mat: RowMajorMatrix<F>) -> RowMajorMatrix<F>

Compute the inverse DFT of each column in mat.

fn coset_idft(&self, vec: Vec<F>, shift: F) -> Vec<F>

Compute the “coset iDFT” of vec. This can be viewed as an inverse operation of “coset DFT”, that interpolates over a coset of a multiplicative subgroup, rather than subgroup itself.

fn coset_idft_batch( &self, mat: RowMajorMatrix<F>, shift: F, ) -> RowMajorMatrix<F>

Compute the “coset iDFT” of each column in mat. This can be viewed as an inverse operation of “coset DFT”, that interpolates over a coset of a multiplicative subgroup, rather than the subgroup itself.

fn lde(&self, vec: Vec<F>, added_bits: usize) -> Vec<F>

Compute the low-degree extension of vec onto a larger subgroup.

fn lde_batch( &self, mat: RowMajorMatrix<F>, added_bits: usize, ) -> Self::Evaluations

Compute the low-degree extension of each column in mat onto a larger subgroup.

fn coset_lde(&self, vec: Vec<F>, added_bits: usize, shift: F) -> Vec<F>

Compute the low-degree extension of each column in mat onto a coset of a larger subgroup.