Struct DefaultSparseOps 

pub struct DefaultSparseOps { /* private fields */ }

Default sparse operations implementation

Implementations

impl DefaultSparseOps

pub fn new(device: Device) -> Self

Create new sparse operations instance

pub fn with_hints(self, hints: SparseOptimizationHints) -> Self

Set optimization hints

Trait Implementations

impl Debug for DefaultSparseOps

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

Formats the value using the given formatter.

impl SparseOps<f32> for DefaultSparseOps

fn spmv( &self, matrix: &SparseMatrix<f32>, x: &[f32], y: &mut [f32], ) -> BackendResult<()>

Sparse matrix-vector multiplication: y = A * x

fn spmm( &self, a: &SparseMatrix<f32>, b: &SparseMatrix<f32>, ) -> BackendResult<SparseMatrix<f32>>

Sparse matrix-matrix multiplication: C = A * B

fn sparse_add( &self, a: &SparseMatrix<f32>, b: &SparseMatrix<f32>, ) -> BackendResult<SparseMatrix<f32>>

Sparse matrix addition: C = A + B

fn to_dense(&self, matrix: &SparseMatrix<f32>) -> BackendResult<Vec<f32>>

Convert sparse matrix to dense format

fn from_dense( &self, dense: &[f32], rows: usize, cols: usize, threshold: f32, ) -> BackendResult<SparseMatrix<f32>>

Create sparse matrix from dense format

fn transpose( &self, matrix: &SparseMatrix<f32>, ) -> BackendResult<SparseMatrix<f32>>

Transpose sparse matrix