kernels.hpp File Reference

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Namespaces
namespace	mfem
namespace	mfem::kernels

Functions
template<int dim>
MFEM_HOST_DEVICE real_t	mfem::kernels::DistanceSquared (const real_t *x, const real_t *y)
	Compute the square of the Euclidean distance to another vector.
template<int dim>
MFEM_HOST_DEVICE void	mfem::kernels::Diag (const real_t c, real_t *data)
	Creates n x n diagonal matrix with diagonal elements c.
template<int dim>
MFEM_HOST_DEVICE void	mfem::kernels::Subtract (const real_t a, const real_t *x, const real_t *y, real_t *z)
	Vector subtraction operation: z = a * (x - y)
template<int dim>
MFEM_HOST_DEVICE void	mfem::kernels::AddMultVWt (const real_t *v, const real_t *w, real_t *VWt)
	Dense matrix operation: VWt += v w^t.
template<int H, int W, typename T >
MFEM_HOST_DEVICE void	mfem::kernels::FNorm (real_t &scale_factor, real_t &scaled_fnorm2, const T *data)
template<int H, int W, typename T >
MFEM_HOST_DEVICE real_t	mfem::kernels::FNorm (const T *data)
	Compute the Frobenius norm of the matrix.
template<int H, int W, typename T >
MFEM_HOST_DEVICE real_t	mfem::kernels::FNorm2 (const T *data)
	Compute the square of the Frobenius norm of the matrix.
template<typename T >
MFEM_HOST_DEVICE real_t	mfem::kernels::Norml2 (const int size, const T *data)
	Returns the l2 norm of the Vector with given size and data.
template<typename TA , typename TX , typename TY >
MFEM_HOST_DEVICE void	mfem::kernels::Mult (const int height, const int width, const TA *data, const TX *x, TY *y)
	Matrix vector multiplication: y = A x, where the matrix A is of size height x width with given data, while x and y specify the data of the input and output vectors.
template<typename TA , typename TX , typename TY >
MFEM_HOST_DEVICE void	mfem::kernels::MultTranspose (const int height, const int width, const TA *data, const TX *x, TY *y)
	Matrix transpose vector multiplication: y = At x, where the matrix A is of size height x width with given data, while x and y specify the data of the input and output vectors.
template<typename T >
MFEM_HOST_DEVICE void	mfem::kernels::Symmetrize (const int size, T *data)
	Symmetrize a square matrix with given size and data: A -> (A+A^T)/2.
template<int dim, typename T >
MFEM_HOST_DEVICE T	mfem::kernels::Det (const T *data)
	Compute the determinant of a square matrix of size dim with given data.
template<int dim, typename T >
MFEM_HOST_DEVICE void	mfem::kernels::CalcInverse (const T *data, T *inv_data)
	Return the inverse of a matrix with given size and data into the matrix with data inv_data.
template<int dim, typename T >
MFEM_HOST_DEVICE void	mfem::kernels::CalcAdjugate (const T *data, T *adj_data)
	Return the adjugate of a matrix.
template<typename TALPHA , typename TA , typename TB , typename TC >
MFEM_HOST_DEVICE void	mfem::kernels::Add (const int height, const int width, const TALPHA alpha, const TA *Adata, const TB *Bdata, TC *Cdata)
	Compute C = A + alpha*B, where the matrices A, B and C are of size height x width with data Adata, Bdata and Cdata.
template<typename TALPHA , typename TBETA , typename TA , typename TB , typename TC >
MFEM_HOST_DEVICE void	mfem::kernels::Add (const int height, const int width, const TALPHA alpha, const TA *Adata, const TBETA beta, const TB *Bdata, TC *Cdata)
	Compute C = alpha*A + beta*B, where the matrices A, B and C are of size height x width with data Adata, Bdata and Cdata.
template<typename TA , typename TB >
MFEM_HOST_DEVICE void	mfem::kernels::Add (const int height, const int width, const TA *Adata, TB *Bdata)
	Compute B += A, where the matrices A and B are of size height x width with data Adata and Bdata.
template<typename TA , typename TB >
MFEM_HOST_DEVICE void	mfem::kernels::Add (const int height, const int width, const real_t alpha, const TA *Adata, TB *Bdata)
	Compute B +=alpha*A, where the matrices A and B are of size height x width with data Adata and Bdata.
template<typename TA , typename TB >
MFEM_HOST_DEVICE void	mfem::kernels::Set (const int height, const int width, const real_t alpha, const TA *Adata, TB *Bdata)
	Compute B = alpha*A, where the matrices A and B are of size height x width with data Adata and Bdata.
template<typename TA , typename TB , typename TC >
MFEM_HOST_DEVICE void	mfem::kernels::AddMult (const int Aheight, const int Awidth, const int Bwidth, const TB *Bdata, const TC *Cdata, TA *Adata, const TB alpha, const TA beta)
	Matrix-matrix multiplication: A = alpha * B * C + beta * A, where the matrices A, B and C are of sizes Aheight x Awidth, Aheight x Bwidth and Bwidth x Awidth, respectively.
template<typename TA , typename TB , typename TC >
MFEM_HOST_DEVICE void	mfem::kernels::Mult (const int Aheight, const int Awidth, const int Bwidth, const TB *Bdata, const TC *Cdata, TA *Adata)
	Matrix-matrix multiplication: A = B * C, where the matrices A, B and C are of sizes Aheight x Awidth, Aheight x Bwidth and Bwidth x Awidth, respectively.
template<typename TA , typename TB , typename TC >
MFEM_HOST_DEVICE void	mfem::kernels::MultABt (const int Aheight, const int Awidth, const int Bheight, const TA *Adata, const TB *Bdata, TC *ABtdata)
	Multiply a matrix of size Aheight x Awidth and data Adata with the transpose of a matrix of size Bheight x Awidth and data Bdata: A * Bt. Return the result in a matrix with data ABtdata.
template<typename TA , typename TB , typename TC >
MFEM_HOST_DEVICE void	mfem::kernels::AddMultAtB (const int Aheight, const int Awidth, const int Bwidth, const TA *Adata, const TB *Bdata, TC *Cdata, const TB alpha, const TA beta)
	Compute C = alpha*At*B + beta*C.
template<typename TA , typename TB , typename TC >
MFEM_HOST_DEVICE void	mfem::kernels::MultAtB (const int Aheight, const int Awidth, const int Bwidth, const TA *Adata, const TB *Bdata, TC *AtBdata)
	Multiply the transpose of a matrix of size Aheight x Awidth and data Adata with a matrix of size Aheight x Bwidth and data Bdata: At * B. Return the result in a matrix with data AtBdata.
template<typename TA , typename TB , typename TC >
MFEM_HOST_DEVICE void	mfem::kernels::AddMultAtB (const int Aheight, const int Awidth, const int Bwidth, const TA *Adata, const TB *Bdata, TC *AtBdata)
	Multiply the transpose of a matrix of size Aheight x Awidth and data Adata with a matrix of size Aheight x Bwidth and data Bdata: At * B. Add the result to the matrix with data AtBdata.
template<int HEIGHT, int WIDTH>
MFEM_HOST_DEVICE void	mfem::kernels::CalcLeftInverse (const real_t *data, real_t *left_inv)
	Given a matrix of size 2x1, 3x1, or 3x2, compute the left inverse.
template<int dim>
MFEM_HOST_DEVICE void	mfem::kernels::CalcEigenvalues (const real_t *data, real_t *lambda, real_t *vec)
template<int dim>
MFEM_HOST_DEVICE real_t	mfem::kernels::CalcSingularvalue (const real_t *data, const int i)
	Return the i'th singular value of the matrix of size dim with given data.
template<>
MFEM_HOST_DEVICE void	mfem::kernels::CalcLeftInverse< 2, 1 > (const real_t *d, real_t *left_inv)
template<>
MFEM_HOST_DEVICE void	mfem::kernels::CalcLeftInverse< 3, 1 > (const real_t *d, real_t *left_inv)
template<>
MFEM_HOST_DEVICE void	mfem::kernels::CalcLeftInverse< 3, 2 > (const real_t *d, real_t *left_inv)
template<>
MFEM_HOST_DEVICE void	mfem::kernels::CalcEigenvalues< 2 > (const real_t *data, real_t *lambda, real_t *vec)
template<>
MFEM_HOST_DEVICE void	mfem::kernels::CalcEigenvalues< 3 > (const real_t *data, real_t *lambda, real_t *vec)
template<>
MFEM_HOST_DEVICE real_t	mfem::kernels::CalcSingularvalue< 2 > (const real_t *data, const int i)
	Return the i'th singular value of the matrix of size 2 with given data.
template<>
MFEM_HOST_DEVICE real_t	mfem::kernels::CalcSingularvalue< 3 > (const real_t *data, const int i)
	Return the i'th singular value of the matrix of size 3 with given data.
MFEM_HOST_DEVICE void	mfem::kernels::LSolve (const real_t *data, const int m, const int *ipiv, real_t *x)
	Assuming L.U = P.A factored matrix of size (m x m), compute X <- L^{-1} P X, for a vector X of length m.
MFEM_HOST_DEVICE void	mfem::kernels::USolve (const real_t *data, const int m, real_t *x)
	Assuming L.U = P.A factored matrix of size (m x m), compute X <- U^{-1} X, for a vector X of length m.
MFEM_HOST_DEVICE void	mfem::kernels::LUSolve (const real_t *data, const int m, const int *ipiv, real_t *x)
	Assuming L.U = P.A for a factored matrix (m x m),.
MFEM_HOST_DEVICE void	mfem::kernels::SubMult (const int m, const int n, const int r, const real_t *A21, const real_t *X1, real_t *X2)
	Given an (n x m) matrix A21, compute X2 <- X2 - A21 X1, for matrices X1, and X2 of size (m x r) and (n x r), respectively.
MFEM_HOST_DEVICE void	mfem::kernels::BlockFactor (const real_t *data, int m, const int *ipiv, int n, real_t *A12, real_t *A21, real_t *A22)
MFEM_HOST_DEVICE bool	mfem::kernels::LUFactor (real_t *A, const int m, int *ipiv, const real_t tol=0.0)
	Compute the LU factorization of the m x m matrix A.