potrs¶

Solves a system of linear equations with a Cholesky-factored symmetric (Hermitian) positive-definite coefficient matrix.

Description

potrs supports the following precisions.

T

float

double

std::complex<float>

std::complex<double>

The routine solves for $$X$$ the system of linear equations $$AX = B$$ with a symmetric positive-definite or, for complex data, Hermitian positive-definite matrix $$A$$, given the Cholesky factorization of $$A$$:

$$A = U^TU$$ for real data, $$A = U^HU$$ for complex data

if upper_lower=oneapi::mkl::uplo::upper

$$A = LL^T$$ for real data, $$A = LL^H$$ for complex data

if upper_lower=oneapi::mkl::uplo::lower

where $$L$$ is a lower triangular matrix and $$U$$ is upper triangular. The system is solved with multiple right-hand sides stored in the columns of the matrix $$B$$.

Before calling this routine, you must call potrf to compute the Cholesky factorization of $$A$$.

potrs (Buffer Version)¶

Syntax

namespace oneapi::mkl::lapack {
void potrs(sycl::queue &queue, oneapi::mkl::uplo upper_lower, std::int64_t n, std::int64_t nrhs, sycl::buffer<T,1> &a, std::int64_t lda, sycl::buffer<T,1> &b, std::int64_t ldb, sycl::buffer<T,1> &scratchpad, std::int64_t scratchpad_size)
}


Input Parameters

queue

The queue where the routine should be executed.

upper_lower

Indicates how the input matrix has been factored:

If upper_lower = oneapi::mkl::uplo::upper, the upper triangle $$U$$ of $$A$$ is stored, where $$A$$ = $$U^{T}U$$ for real data, $$A$$ = $$U^{H}U$$ for complex data.

If upper_lower = oneapi::mkl::uplo::lower, the lower triangle $$L$$ of $$A$$ is stored, where $$A$$ = $$LL^{T}$$ for real data, $$A$$ = $$LL^{H}$$ for complex data.

n

The order of matrix $$A$$ ($$0 \le n$$).

nrhs

The number of right-hand sides ($$0 \le \text{nrhs}$$).

a

Buffer containing the factorization of the matrix A, as returned by potrf. The second dimension of a must be at least $$\max(1, n)$$.

lda

The leading dimension of a.

b

The array b contains the matrix $$B$$ whose columns are the right-hand sides for the systems of equations. The second dimension of b must be at least $$\max(1,\text{nrhs})$$.

ldb

The leading dimension of b.

Size of scratchpad memory as a number of floating point elements of type T. Size should not be less than the value returned by potrs_scratchpad_size function.

Output Parameters

b

Overwritten by the solution matrix $$X$$.

Buffer holding scratchpad memory to be used by routine for storing intermediate results.

potrs (USM Version)¶

Syntax

namespace oneapi::mkl::lapack {
sycl::event potrs(sycl::queue &queue, oneapi::mkl::uplo upper_lower, std::int64_t n, std::int64_t nrhs, T *a, std::int64_t lda, T *b, std::int64_t ldb, T *scratchpad, std::int64_t scratchpad_size, const std::vector<sycl::event> &events = {})
}


Input Parameters

queue

The queue where the routine should be executed.

upper_lower

Indicates how the input matrix has been factored:

If upper_lower = oneapi::mkl::uplo::upper, the upper triangle $$U$$ of $$A$$ is stored, where $$A$$ = $$U^{T}U$$ for real data, $$A$$ = $$U^{H}U$$ for complex data.

If upper_lower = oneapi::mkl::uplo::lower, the lower triangle $$L$$ of $$A$$ is stored, where $$A$$ = $$LL^{T}$$ for real data, $$A$$ = $$LL^{H}$$ for complex data.

n

The order of matrix $$A$$ ($$0 \le n$$).

nrhs

The number of right-hand sides ($$0 \le \text{nrhs}$$).

a

Pointer to array containing the factorization of the matrix $$A$$, as returned by potrf. The second dimension of a must be at least $$\max(1, n)$$.

lda

The leading dimension of a.

b

The array b contains the matrix $$B$$ whose columns are the right-hand sides for the systems of equations. The second dimension of b must be at least $$\max(1,\text{nrhs})$$.

ldb

The leading dimension of b.

Size of scratchpad memory as a number of floating point elements of type T`. Size should not be less than the value returned by potrs_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 $$X$$.