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remove spmv_coo

This commit is contained in:
Andreas Longva 2020-12-14 11:18:16 +01:00
parent 41941e62c8
commit c4285d9fb3
3 changed files with 2 additions and 102 deletions
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72
nalgebra-sparse/src/ops/serial/coo.rs
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@ -1,72 +0,0 @@
//! Matrix operations involving sparse matrices.
use crate::coo::CooMatrix;
use nalgebra::base::storage::{Storage, StorageMut};
use nalgebra::{ClosedAdd, ClosedMul, Dim, Scalar, Vector};
use num_traits::{One, Zero};
/// Sparse matrix-vector multiplication `y = beta * y + alpha * A * x`.
///
/// Computes a matrix-vector product with the COO matrix "A" and the vector `x`, storing the
/// result in `y`.
///
/// If `beta == 0`, the elements in `y` are never read.
///
/// TODO: Rethink this function
///
/// Panics
/// ------
///
/// Panics if `y`, `a` and `x` do not have compatible dimensions.
pub fn spmv_coo<T, Y, X, YDim, XDim>(
beta: T,
y: &mut Vector<T, YDim, Y>,
alpha: T,
a: &CooMatrix<T>,
x: &Vector<T, XDim, X>,
) where
T: Scalar + ClosedAdd + ClosedMul + Zero + One,
YDim: Dim,
XDim: Dim,
Y: StorageMut<T, YDim>,
X: Storage<T, XDim>,
{
assert_eq!(
y.len(),
a.nrows(),
"y and a must be dimensionally compatible"
);
assert_eq!(
a.ncols(),
x.len(),
"a and x must be dimensionally compatible"
);
if beta == T::zero() {
// If `y` is constructed through `new_uninitialized()`, we must make sure to not read
// any of the elements in order to avoid UB, so we special case beta == 0
// in order to ensure that we only write, not read, the elements in y.
for y_i in y.iter_mut() {
*y_i = T::zero();
}
} else if beta != T::one() {
// Since the COO triplets have no particular structure, we cannot combine initialization
// of y with the triplet loop below, and instead have to do it in a pre-pass.
for y_i in y.iter_mut() {
*y_i *= beta.inlined_clone();
}
}
for (i, j, v) in a.triplet_iter() {
// TODO: We could skip bounds checks with unsafe here, since COO ensures that all indices
// are in bounds and we assert on dimensions up-front.
// The compiler will not be able to elide the checks, since we're doing
// random/unpredictable access to elements in `x` and `y`.
let (alpha, v, x_j) = (
alpha.inlined_clone(),
v.inlined_clone(),
x[j].inlined_clone(),
);
y[i] += alpha * v * x_j;
}
}

2
nalgebra-sparse/src/ops/serial/mod.rs
View File

@ -30,11 +30,9 @@ macro_rules! assert_compatible_spmm_dims {
}
}
mod coo;
mod csr;
mod pattern;
pub use coo::*;
pub use csr::*;
pub use pattern::*;

30
nalgebra-sparse/tests/unit_tests/ops.rs
View File

@ -1,11 +1,10 @@
use nalgebra_sparse::coo::CooMatrix;
use nalgebra_sparse::ops::serial::{spmv_coo, spmm_csr_dense, spadd_build_pattern, spadd_csr};
use nalgebra_sparse::ops::serial::{spmm_csr_dense, spadd_build_pattern, spadd_csr};
use nalgebra_sparse::ops::{Transpose};
use nalgebra_sparse::csr::CsrMatrix;
use nalgebra_sparse::proptest::{csr, sparsity_pattern};
use nalgebra_sparse::pattern::SparsityPattern;
use nalgebra::{DVector, DMatrix, Scalar, DMatrixSliceMut, DMatrixSlice};
use nalgebra::{DMatrix, Scalar, DMatrixSliceMut, DMatrixSlice};
use nalgebra::proptest::matrix;
use proptest::prelude::*;
@ -24,31 +23,6 @@ fn dense_csr_pattern(pattern: &SparsityPattern) -> DMatrix<i32> {
DMatrix::from(&boolean_csr)
}
#[test]
fn spmv_coo_agrees_with_dense_gemv() {
let x = DVector::from_column_slice(&[2, 3, 4, 5]);
let i = vec![0, 0, 1, 1, 2, 2];
let j = vec![0, 3, 0, 1, 1, 3];
let v = vec![3, 2, 1, 2, 3, 1];
let a = CooMatrix::try_from_triplets(3, 4, i, j, v).unwrap();
let betas = [0, 1, 2];
let alphas = [0, 1, 2];
for &beta in &betas {
for &alpha in &alphas {
let mut y = DVector::from_column_slice(&[2, 5, 3]);
let mut y_dense = y.clone();
spmv_coo(beta, &mut y, alpha, &a, &x);
y_dense.gemv(alpha, &DMatrix::from(&a), &x, beta);
assert_eq!(y, y_dense);
}
}
}
#[derive(Debug)]
struct SpmmCsrDenseArgs<T: Scalar> {
c: DMatrix<T>,