| blas_amax | Determines the smallest index of the element with the maximum
magnitude of the specified input vector, using the cuBLAS/BLAS library.
|
| blas_amin | Determines the smallest index of the element with the minimum
magnitude of the specified input vector using the cuBLAS/BLAS library.
|
| blas_asum | Calculates the sum of the absolute values of the input matrix,
using the cuBLAS/BLAS library
|
| blas_axpy | Calculates the matrix scaling and addition operation using the
cuBLAS/BLAS library:
: Y = alpha * X + Y
|
| blas_chol | Calculates the Cholesky decomposition of the Hermitian
positive definite matrix A, using the cuSolver library:
:A = L^H * L
|
| blas_cholsolve | Solves a linear system of equations using a previous Cholesky decomposition
obtained using , using the cuSolver library:
:A * X = B
where X and B are vectors/matrices (corresponding to multiple right-handed sides)
|
| blas_dot | Calculates the dot-product of two vectors or matrices using the
cuBLAS/BLAS library:
: y = sum(A.*conj(B))
|
| blas_geam | Calculates the following matrix-matrix addition/transposition using the
cuBLAS/BLAS library:
:C = alpha*op(A) + beta*op(B)
where
: op(A) = At ? transpose(A) : A
: op(B) = Bt ? transpose(B) : B
|
| blas_gemm | Efficiently calculates the matrix-matrix multiplication and addition
using the cuBLAS/BLAS library:
|
| blas_gemv | Efficiently calculates the matrix-vector multiplication using the
cuBLAS/BLAS library:
|
| blas_gesvd | Calculates the singular value decomposition of the matrix A, using the
cuSolver library:
: A = U * S * VH
|
| blas_hermtranspose | Calculates the Hermitian transpose of the matrix X using the cuBLAS/BLAS library.
|
| blas_lu | Performs an LU decomposition of the matrix A using the library cuSolver.
The result of the operation is stored in the matrices A and P. The LU
decomposition is defined as follows:
:perm(P) * A = L * U
where perm(P) is a permutation matrix (the vector P specifies the
permutations to be applied in sequence to the rows of an identity matrix,
the i-th permutation is given by [i,P[i]]).
|
| blas_lubatched | Performs an LU decomposition of a stack of K matrices A_i using the library cuSolver.
The result of the operation is stored in the matrices A_i and P_i. The LU
decomposition is defined as follows:
:perm(P_i) * A_i = L_i * U_i, i = 0, ..., K-1
where perm(P_i) is a permutation matrix (the vector P_i specifies the
permutations to be applied in sequence to the rows of an identity matrix,
the i-th permutation is given by [i,P[i]]).
|
| blas_lumatinvbatched | Calculates the matrix inverse of a stacked set of input matrices, using
a LU factorization previously performed with the function .
|
| blas_lusolve | Solves a linear system of multiple right-hand sides using the cuSolver library:
: op(A)*X = B
where
: op(A) = At ? transpose(A) : A
|
| blas_lusolvebatched | Solves multiple linear systems with multiple right-hand sides using the cuSolver library:
: op(A_i)*X_i = B_i, i = 0, ..., K-1
where
: op(A) = At ? transpose(A) : A
|
| blas_matinvbatched | Calculates the matrix inverse of a stacked set of input matrices, using the
cuBLAS library.
|
| blas_nrm2 | Calculates the Euclidean norm of the vector (or matrix) A, using the
cuBLAS/BLAS library:
: y = sqrt(sum(abs(A).^2))
In case of a matrix, the Euclidean norm is calculated over all elements of the
matrix.
|
| blas_q | Calculates the Q factor of a QR matrix obtained using the function .
|
| blas_qr | Calculates the QR factorization of an m x n matrix A using the cuSolver library:
:A = Q * R
|
| blas_scal | Scales the matrix X using the cuBLAS/BLAS library:
: X = X * alpha
|
| blas_transpose | Calculates the transpose of the matrix X using the cuBLAS/BLAS library.
The function is identical to the function, but may have different
performance characteristics.
|
| blas_trsv | Solves a triangular system of equations with a single right-hand side
using the cuBLAS / BLAS library:
: op(A)X = B
where
: op(A) = At ? transpose(A) : A
|
| blas_version | Returns the version of the currently installed cuBLAS library.
|