sgemm

Usage

var sgemm = require( '@stdlib/blas/base/sgemm' );

sgemm( ord, ta, tb, M, N, K, α, A, lda, B, ldb, β, C, ldc )

Performs the matrix-matrix operation C = α*op(A)*op(B) + β*C where op(X) is either op(X) = X or op(X) = X^T, α and β are scalars, A, B, and C are matrices, with op(A) an M by K matrix, op(B) a K by N matrix, and C an M by N matrix.

var Float32Array = require( '@stdlib/array/float32' );

var A = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );
var B = new Float32Array( [ 1.0, 1.0, 0.0, 1.0 ] );
var C = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );

sgemm( 'row-major', 'no-transpose', 'no-transpose', 2, 2, 2, 1.0, A, 2, B, 2, 1.0, C, 2 );
// C => <Float32Array>[ 2.0, 5.0, 6.0, 11.0 ]

The function has the following parameters:

• ord: storage layout.
• ta: specifies whether A should be transposed, conjugate-transposed, or not transposed.
• tb: specifies whether B should be transposed, conjugate-transposed, or not transposed.
• M: number of rows in the matrix op(A) and in the matrix C.
• N: number of columns in the matrix op(B) and in the matrix C.
• K: number of columns in the matrix op(A) and number of rows in the matrix op(B).
• α: scalar constant.
• A: first input matrix stored in linear memory as a Float32Array.
• lda: stride of the first dimension of A (leading dimension of A).
• B: second input matrix stored in linear memory as a Float32Array.
• ldb: stride of the first dimension of B (leading dimension of B).
• β: scalar constant.
• C: third input matrix stored in linear memory as a Float32Array.
• ldc: stride of the first dimension of C (leading dimension of C).

The stride parameters determine how elements in the input arrays are accessed at runtime. For example, to perform matrix multiplication of two subarrays

var Float32Array = require( '@stdlib/array/float32' );

var A = new Float32Array( [ 1.0, 2.0, 0.0, 0.0, 3.0, 4.0, 0.0, 0.0 ] );
var B = new Float32Array( [ 1.0, 1.0, 0.0, 0.0, 0.0, 1.0, 0.0, 0.0 ] );
var C = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );

sgemm( 'row-major', 'no-transpose', 'no-transpose', 2, 2, 2, 1.0, A, 4, B, 4, 1.0, C, 2 );
// C => <Float32Array>[ 2.0, 5.0, 6.0, 11.0 ]

sgemm.ndarray( ta, tb, M, N, K, α, A, sa1, sa2, oa, B, sb1, sb2, ob, β, C, sc1, sc2, oc )

Performs the matrix-matrix operation C = α*op(A)*op(B) + β*C, using alternative indexing semantics and where op(X) is either op(X) = X or op(X) = X^T, α and β are scalars, A, B, and C are matrices, with op(A) an M by K matrix, op(B) a K by N matrix, and C an M by N matrix.

var Float32Array = require( '@stdlib/array/float32' );

var A = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );
var B = new Float32Array( [ 1.0, 1.0, 0.0, 1.0 ] );
var C = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );

sgemm.ndarray( 'no-transpose', 'no-transpose', 2, 2, 2, 1.0, A, 2, 1, 0, B, 2, 1, 0, 1.0, C, 2, 1, 0 );
// C => <Float32Array>[ 2.0, 5.0, 6.0, 11.0 ]

The function has the following additional parameters:

• sa1: stride of the first dimension of A.
• sa2: stride of the second dimension of A.
• oa: starting index for A.
• sb1: stride of the first dimension of B.
• sb2: stride of the second dimension of B.
• ob: starting index for B.
• sc1: stride of the first dimension of C.
• sc2: stride of the second dimension of C.
• oc: starting index for C.

While typed array views mandate a view offset based on the underlying buffer, the offset parameters support indexing semantics based on starting indices. For example,

var Float32Array = require( '@stdlib/array/float32' );

var A = new Float32Array( [ 0.0, 0.0, 1.0, 3.0, 2.0, 4.0 ] );
var B = new Float32Array( [ 0.0, 1.0, 0.0, 1.0, 1.0 ] );
var C = new Float32Array( [ 0.0, 0.0, 0.0, 1.0, 3.0, 2.0, 4.0 ] );

sgemm.ndarray( 'no-transpose', 'no-transpose', 2, 2, 2, 1.0, A, 1, 2, 2, B, 1, 2, 1, 1.0, C, 1, 2, 3 );
// C => <Float32Array>[ 0.0, 0.0, 0.0, 2.0, 6.0, 5.0, 11.0 ]