trtrs#
Solves a system of linear equations with a triangular coefficient matrix, with multiple right-hand sides.
Description
trtrs
supports the following precisions.
T
float
double
std::complex<float>
std::complex<double>
The routine solves for \(X\) the following systems of linear equations with a triangular matrix \(A\), with multiple right-hand sides stored in \(B\):
\(AX = B\)
if
transa
=transpose::nontrans
,\(A^TX = B\)
if
transa
=transpose::trans
,\(A^HX = B\)
if
transa
=transpose::conjtrans
(for complex matrices only).
trtrs (Buffer Version)#
Syntax
namespace oneapi::mkl::lapack {
void trtrs(cl::sycl::queue &queue, oneapi::mkl::uplo upper_lower, oneapi::mkl::transpose transa, oneapi::mkl::diag unit_diag, std::int64_t n, std::int64_t nrhs, cl::sycl::buffer<T,1> &a, std::int64_t lda, cl::sycl::buffer<T,1> &b, std::int64_t ldb, cl::sycl::buffer<T,1> &scratchpad, std::int64_t scratchpad_size)
}
Input Parameters
- queue
The queue where the routine should be executed.
- upper_lower
Indicates whether \(A\) is upper or lower triangular:
If upper_lower =
uplo::upper
, then \(A\) is upper triangular.If upper_lower =
uplo::lower
, then \(A\) is lower triangular.- transa
If transa =
transpose::nontrans
, then \(AX = B\) is solved for \(X\).If transa =
transpose::trans
, then \(A^{T}X = B\) is solved for \(X\).If transa =
transpose::conjtrans
, then \(A^{H}X = B\) is solved for \(X\).- unit_diag
If unit_diag =
diag::nonunit
, then \(A\) is not a unit triangular matrix.If unit_diag =
diag::unit
, then \(A\) is unit triangular: diagonal elements of \(A\) are assumed to be 1 and not referenced in the arraya
.- n
The order of \(A\); the number of rows in \(B\); \(n \ge 0\).
- nrhs
The number of right-hand sides; \(\text{nrhs} \ge 0\).
- a
Buffer containing the matrix \(A\). The second dimension of
a
must be at least \(\max(1,n)\).- lda
The leading dimension of
a
; \(\text{lda} \ge \max(1, n)\).- b
Buffer containing the matrix \(B\) whose columns are the right-hand sides for the systems of equations. The second dimension of
b
at least \(\max(1,\text{nrhs})\).- ldb
The leading dimension of
b
; \(\text{ldb} \ge \max(1, n)\).- scratchpad_size
Size of scratchpad memory as a number of floating point elements of type
T
. Size should not be less than the value returned by trtrs_scratchpad_size function.
Output Parameters
- b
Overwritten by the solution matrix \(X\).
- scratchpad
Buffer holding scratchpad memory to be used by routine for storing intermediate results.
Throws
This routine shall throw the following exceptions if the associated condition is detected. An implementation may throw additional implementation-specific exception(s) in case of error conditions not covered here.
oneapi::mkl::unsupported_device
oneapi::mkl::lapack::invalid_argument
oneapi::mkl::lapack::computation_error
Exception is thrown in case of problems during calculations. The
info
code of the problem can be obtained by info() method of exception object:If \(\text{info}=-i\), the \(i\)-th parameter had an illegal value.
If
info
equals to value passed as scratchpad size, and detail() returns non zero, then passed scratchpad is of insufficient size, and required size should not be less than value return by detail() method of exception object.
trtrs (USM Version)#
Syntax
namespace oneapi::mkl::lapack {
cl::sycl::event trtrs(cl::sycl::queue &queue, oneapi::mkl::uplo upper_lower, oneapi::mkl::transpose transa, oneapi::mkl::diag unit_diag, std::int64_t n, std::int64_t nrhs, const T *a, std::int64_t lda, T *b, std::int64_t ldb, T *scratchpad, std::int64_t scratchpad_size, const std::vector<cl::sycl::event> &events = {})
}
Input Parameters
- queue
The queue where the routine should be executed.
- upper_lower
Indicates whether \(A\) is upper or lower triangular:
If upper_lower =
uplo::upper
, then \(A\) is upper triangular.If upper_lower =
uplo::lower
, then \(A\) is lower triangular.- transa
If transa =
transpose::nontrans
, then \(AX = B\) is solved for \(X\).If transa =
transpose::trans
, then \(A^{T}X = B\) is solved for \(X\).If transa =
transpose::conjtrans
, then \(A^{H}X = B\) is solved for \(X\).- unit_diag
If unit_diag =
diag::nonunit
, then \(A\) is not a unit triangular matrix.If unit_diag =
diag::unit
, then \(A\) is unit triangular: diagonal elements of \(A\) are assumed to be 1 and not referenced in the arraya
.- n
The order of \(A\); the number of rows in \(B\); \(n \ge 0\).
- nrhs
The number of right-hand sides; \(\text{nrhs} \ge 0\).
- a
Array containing the matrix \(A\). The second dimension of
a
must be at least \(\max(1,n)\).- lda
The leading dimension of
a
; \(\text{lda} \ge \max(1, n)\).- b
Array containing the matrix \(B\) whose columns are the right-hand sides for the systems of equations. The second dimension of
b
at least \(\max(1,\text{nrhs})\).- ldb
The leading dimension of
b
; \(\text{ldb} \ge \max(1, n)\).- scratchpad_size
Size of scratchpad memory as a number of floating point elements of type
T
. Size should not be less than the value returned by trtrs_scratchpad_size function.- events
List of events to wait for before starting computation. Defaults to empty list.
Output Parameters
- b
Overwritten by the solution matrix \(X\).
- scratchpad
Pointer to scratchpad memory to be used by routine for storing intermediate results.
Throws
This routine shall throw the following exceptions if the associated condition is detected. An implementation may throw additional implementation-specific exception(s) in case of error conditions not covered here.
oneapi::mkl::unsupported_device
oneapi::mkl::lapack::invalid_argument
oneapi::mkl::lapack::computation_error
Exception is thrown in case of problems during calculations. The
info
code of the problem can be obtained by info() method of exception object:If \(\text{info}=-i\), the \(i\)-th parameter had an illegal value.
If
info
equals to value passed as scratchpad size, and detail() returns non zero, then passed scratchpad is of insufficient size, and required size should not be less than value return by detail() method of exception object.
Return Values
Output event to wait on to ensure computation is complete.
Parent topic: LAPACK Linear Equation Routines