Module ops_inplace

Provides scalar, vector, vector-vector, vector-matrix and matrix-matrix operations.

Most of the operations are optimized using the underlying BLAS implementation. For each function it is explicitly documented whether or not BLAS is used.

Examples

The following example adds two vectors using BLAS and stores the result in the first vector.

use rustml::*;

let mut a = [1.0, 2.0, 3.0, 4.0, 5.0, 6.0];
let b = [3.0, 6.0, 2.0, 3.0, 6.0, 9.0];
a.iadd(&b);
assert_eq!(a, [4.0, 8.0, 5.0, 7.0, 11.0, 15.0]);

Traits

FunctionsInPlace

Trait for common mathematical functions for scalars, vectors and matrices.

MatrixMatrixOpsInPlace

Trait for matrix-matrix operations.

MatrixScalarOpsInPlace

Trait for matrix-scalar operations.

VectorVectorOpsInPlace

Trait for inplace vector-vector operations.

Functions

d_axpy

Computes alpha * x + y and stores the result in y. (optimized via BLAS)

d_gemm

Computes alpha * op(A) * op(B) + beta * C and stores the result in C. (optimized via BLAS)

d_gemv

Computes alpha * A * x + beta * y or alpha * A^T * x + beta * y and stores the result in y. (optimized via BLAS)

d_nrm2

Computes the L2 norm (euclidean norm) of a vector. (optimized via BLAS)

s_axpy

Computes alpha * x + y and stores the result in y. (optimized via BLAS)

s_gemm

Computes alpha * op(A) * op(B) + beta * C and stores the result in C. (optimized via BLAS)

s_gemv

Computes alpha * A * x + beta * y or alpha * A^T * x + beta * y and stores the result in y. (optimized via BLAS)

s_nrm2

Computes the L2 norm (euclidean norm) of a vector. (optimized via BLAS)