Solves a triangular matrix equation (forward or backward solve).
event trsm(queue &exec_queue, side left_right, uplo upper_lower, transpose transa, diag unit_diag, std::int64_t m, std::int64_t n, T alpha, const T* a, std::int64_t lda, T* b, std::int64_t ldb, const vector_class<event> &dependencies = {});
The USM version of trsm supports the following precisions and devices:
T | Devices Supported |
---|---|
float | Host, CPU, and GPU |
double | Host, CPU, and GPU |
std::complex<float> | Host, CPU, and GPU |
std::complex<double> | Host, CPU, and GPU |
The trsm routines solve one of the following matrix equations:
op(A)*X = alpha*B,
or
X*op(A) = alpha*B,
where:
op(A) is one of op(A) = A, or op(A) = AT, or op(A) = AH,
alpha is a scalar,
A is a triangular matrix, and
B and X are m x n general matrices.
A is either m x m or n x n, depending on whether it multiplies X on the left or right. On return, the matrix B is overwritten by the solution matrix X.
The queue where the routine should be executed.
Specifies whether A multiplies X on the left (side::left) or on the right (side::right). See Data Types for more details.
Specifies whether the matrix A is upper or lower triangular. See Data Types for more details.
Specifies op(A), the transposition operation applied to A. See Data Types for more details.
Specifies whether A is assumed to be unit triangular (all diagonal elements are 1). See Data Types for more details.
Specifies the number of rows of B. The value of m must be at least zero.
Specifies the number of columns of B. The value of n must be at least zero.
Scaling factor for the solution.
Pointer to input matrix A. Must have size at least lda*m if left_right = side::left, or lda*n if left_right = side::right. See Matrix and Vector Storage for more details.
Leading dimension of A. Must be at least m if left_right = side::left, and at least n if left_right = side::right. Must be positive.
Pointer to input/output matrix B. It must have size at least ldb*n if column major layout is used to store matrices or at least ldb*m if row major layout is used to store matrices. See Matrix and Vector Storage for more details.
Leading dimension of B. It must be positive and at least m if column major layout is used to store matrices or at least n if column major layout is used to store matrices.
List of events to wait for before starting computation, if any. If omitted, defaults to no dependencies.
Pointer to the output matrix. Overwritten by the solution matrix X.
If alpha = 0, matrix B is set to zero, and A and B do not need to be initialized at entry.
Output event to wait on to ensure computation is complete.