cblas_?gemm3m_batch

Developer Reference for Intel® oneAPI Math Kernel Library for C

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ID 766684

Date 3/22/2024

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cblas_?gemm3m_batch_strided

Computes groups of matrix-matrix product with general matrices.

Syntax

void cblas_cgemm3m_batch_strided (const CBLAS_LAYOUT layout, const CBLAS_TRANSPOSE transa, const CBLAS_TRANSPOSE transb, const MKL_INT m, const MKL_INT n, const MKL_INT k, const void *alpha, const void *a, const MKL_INT lda, const MKL_INT stridea, const void *b, const MKL_INT ldb, const MKL_INT strideb, const void *beta, void *c, const MKL_INT ldc, const MKL_INT stridec, const MKL_INT batch_size);

void cblas_zgemm3m_batch_strided (const CBLAS_LAYOUT layout, const CBLAS_TRANSPOSE transa, const CBLAS_TRANSPOSE transb, const MKL_INT m, const MKL_INT n, const MKL_INT k, const void *alpha, const void *a, const MKL_INT lda, const MKL_INT stridea, const void *b, const MKL_INT ldb, const MKL_INT strideb, const void *beta, void *c, const MKL_INT ldc, const MKL_INT stridec, const MKL_INT batch_size);

Include Files

mkl.h

Description

The cblas_?gemm3m_batch_strided routines perform a series of matrix-matrix operations with general matrices. They are similar to the cblas_?gemm routine counterparts, but the cblas_?gemm3m_batch_strided routines perform matrix-matrix operations with groups of matrices. The groups contain matrices with the same parameters.

All matrix a (respectively, b or c) have the same parameters (size, leading dimension, transpose operation, alpha, beta scaling) and are stored at constant stridea (respectively, strideb or stridec) from each other. The operation is defined as

For i = 0 … batch_size – 1
    Ai, Bi and Ci are matrices at offset i * stridea, i * strideb and i * stridec in a, b and c
    Ci = alpha * Ai * Bi +  beta * Ci
end for

The cblas_?gemm3m_batch_strided routines use fewer matrix multiplications than the cblas_?gemm routines, as described in the Application Notes below.

Input Parameters

layout

Specifies whether two-dimensional array storage is row-major (CblasRowMajor) or column-major (CblasColMajor).

transa

Specifies op(A) the transposition operation applied to the matrices A.

if transa = CblasNoTrans, then op(A) = A;

if transa = CblasTrans, then op(A) = A^T;

if transa = CblasConjTrans, then op(A) = A^H.

transb

Specifies op(B) the transposition operation applied to the matrices B.

if transb = CblasNoTrans, then op(B) = B;

if transb = CblasTrans, then op(B) = B^T;

if transb = CblasConjTrans, then op(B) = B^H.

m

Number of rows of the op(A) and C matrices. Must be at least 0.

n

Number of columns of the op(B) and C matrices. Must be at least 0.

k

Number of columns of the op(A) matrix and number of rows of the op(B) matrix. Must be at least 0.

alpha

Specifies the scalar alpha.

a

Array of size at least stridea*batch_size holding the a matrices.

	transa=CblasNoTrans	transa=CblasTrans or CblasConjTrans
layout = CblasColMajor	Before entry, the leading `m`-by-`k` part of the array a + i * `stridea` must contain the matrix A_i.	Before entry, the leading `k`-by-`m` part of the array a + i * `stridea` must contain the matrix A_i.
layout = CblasRowMajor	Before entry, the leading `k`-by-`m` part of the array a + i * `stridea` must contain the matrix A_i.	Before entry, the leading `m`-by-`k` part of the array a + i * `stridea` must contain the matrix A_i.

lda

Specifies the leading dimension of the a matrices.

	transa=CblasNoTrans	transa=CblasTrans or CblasConjTrans
layout = CblasColMajor	`lda` must be at least max(1,`m`).	`lda` must be at least max(1,`k`).
layout = CblasRowMajor	`lda` must be at least max(1,`k`).	`lda` must be at least max(1,`m`).

stridea

Stride between two consecutive a matrices.

	transa=CblasNoTrans	transa=CblasTrans or CblasConjTrans
layout = CblasColMajor	Must be at least `lda`*`k`.	Must be at least `lda`*`m`.
layout = CblasRowMajor	Must be at least `lda`*`m`.	Must be at least `lda`*`k`.

b

Array of size at least strideb*batch_size holding the b matrices.

	transb=CblasNoTrans	transb=CblasTrans or CblasConjTrans
layout = CblasColMajor	Before entry, the leading `k`-by-`n` part of the array b + i * `strideb` must contain the matrix B_i.	Before entry, the leading `n`-by-`k` part of the array b + i * `strideb` must contain the matrix B_i.
layout = CblasRowMajor	Before entry, the leading `n`-by-`k` part of the array b + i * `strideb` must contain the matrix B_i.	Before entry, the leading `k`-by-`n` part of the array b + i * `strideb` must contain the matrix B_i.

ldb

Specifies the leading dimension of the b matrices.

	transab=CblasNoTrans	transb=CblasTrans or CblasConjTrans
layout = CblasColMajor	`ldb` must be at least max(1,`k`).	`ldb` must be at least max(1,`n`).
layout = CblasRowMajor	`ldb` must be at least max(1,`n`).	`ldb` must be at least max(1,`k`).

strideb

Stride between two consecutive b matrices.

	transa=CblasNoTrans	transa=CblasTrans or CblasConjTrans
layout = CblasColMajor	Must be at least `ldb`*`n`.	Must be at least `ldb`*`k`.
layout = CblasRowMajor	Must be at least `ldb`*`k`.	Must be at least `ldb`*`n`.

beta

Specifies the scalar beta.

c

Array of size at least stridec*batch_size holding the c matrices.

If layout=CblasColMajor, before entry, the leading m-by-n part of the array c + i * stridec must contain the matrix C_i.

If layout=CblasRowMajor, before entry, the leading n-by-m part of the array c + i * stridec must contain the matrix C_i.

ldc

Specifies the leading dimension of the c matrices.

Must be at least max(1,m) if layout=CblasColMajor or max(1,n) if layout=CblasRowMajor.

stridec

Specifies the stride between two consecutive c matrices.

Must be at least ldc*nif layout=CblasColMajor or ldc*m if layout=CblasRowMajor.

batch_size

Number of gemm computations to perform and a, b and c matrices. Must be at least 0.

Output Parameters

c: Array holding the batch_size updated c matrices.

Application Notes

These routines perform a complex matrix multiplication by forming the real and imaginary parts of the input matrices. This uses three real matrix multiplications and five real matrix additions instead of the conventional four real matrix multiplications and two real matrix additions. The use of three real matrix multiplications reduces the time spent in matrix operations by 25%, resulting in significant savings in compute time for large matrices.

If the errors in the floating point calculations satisfy the following conditions:

fl(x op y)=(x op y)(1+δ),|δ|≤u, op=×,/, fl(x±y)=x(1+α)±y(1+β), |α|,|β|≤u

then for an n-by-n matrix Ĉ=fl(C1+iC2)=fl((A1+iA2)(B1+iB2))=Ĉ1+iĈ2, the following bounds are satisfied:

║Ĉ1-C1║≤ 2(n+1)u║A║∞║B║∞+O(u2),
║Ĉ2-C2║≤ 4(n+4)u║A║∞║B║∞+O(u2),

where ║A║∞=max(║A1║∞,║A2║∞), and ║B║∞=max(║B1║∞,║B2║∞).

Thus the corresponding matrix multiplications are stable.

Parent topic: BLAS-like Extensions

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