double precision
[Sparse unfiled]

Functions

magma_int_t magma_djacobisetup_matrix (magma_d_sparse_matrix A, magma_d_sparse_matrix *M, magma_d_vector *d, magma_queue_t queue)
 Prepares the Matrix M for the Jacobi Iteration according to x^(k+1) = D^(-1) * b - D^(-1) * (L+U) * x^k x^(k+1) = c - M * x^k.
magma_int_t magma_djacobisetup_diagscal (magma_d_sparse_matrix A, magma_d_vector *d, magma_queue_t queue)
 It returns a vector d containing the inverse diagonal elements.
magma_int_t magma_djacobisetup_vector (magma_d_vector b, magma_d_vector d, magma_d_vector *c, magma_queue_t queue)
 Prepares the Jacobi Iteration according to x^(k+1) = D^(-1) * b - D^(-1) * (L+U) * x^k x^(k+1) = c - M * x^k.
magma_int_t magma_djacobisetup (magma_d_sparse_matrix A, magma_d_vector b, magma_d_sparse_matrix *M, magma_d_vector *c, magma_queue_t queue)
 Prepares the Jacobi Iteration according to x^(k+1) = D^(-1) * b - D^(-1) * (L+U) * x^k x^(k+1) = c - M * x^k.
magma_int_t magma_djacobiiter (magma_d_sparse_matrix M, magma_d_vector c, magma_d_vector *x, magma_d_solver_par *solver_par, magma_queue_t queue)
 Iterates the solution approximation according to x^(k+1) = D^(-1) * b - D^(-1) * (L+U) * x^k x^(k+1) = c - M * x^k.
magma_int_t magma_djacobiiter_precond (magma_d_sparse_matrix M, magma_d_vector *x, magma_d_solver_par *solver_par, magma_d_preconditioner *precond, magma_queue_t queue)
 Iterates the solution approximation according to x^(k+1) = D^(-1) * b - D^(-1) * (L+U) * x^k x^(k+1) = c - M * x^k.
void magma_dcompactActive (magma_int_t m, magma_int_t n, magmaDouble_ptr dA, magma_int_t ldda, magmaInt_ptr active, magma_queue_t queue)
 ZCOMPACTACTIVE takes a set of n vectors of size m (in dA) and an array of 1s and 0sindicating which vectors to compact (for 1s) and which to disregard (for 0s).
magma_int_t magma_dgeelltmv (magma_trans_t transA, magma_int_t m, magma_int_t n, magma_int_t nnz_per_row, double alpha, magmaDouble_ptr dval, magmaIndex_ptr dcolind, magmaDouble_ptr dx, double beta, magmaDouble_ptr dy, magma_queue_t queue)
 This routine computes y = alpha * A^t * x + beta * y on the GPU.
magma_int_t magma_djacobi_diagscal (int num_rows, magma_d_vector d, magma_d_vector b, magma_d_vector *c, magma_queue_t queue)
 Prepares the Jacobi Iteration according to x^(k+1) = D^(-1) * b - D^(-1) * (L+U) * x^k x^(k+1) = c - M * x^k.
magma_int_t magma_dgemvmdot (int n, int k, magmaDouble_ptr v, magmaDouble_ptr r, magmaDouble_ptr d1, magmaDouble_ptr d2, magmaDouble_ptr skp, magma_queue_t queue)
 This is an extension of the merged dot product above by chunking the set of vectors v_i such that the data always fits into cache.
magma_int_t magma_d_spmv (double alpha, magma_d_sparse_matrix A, magma_d_vector x, double beta, magma_d_vector y, magma_queue_t queue)
 For a given input matrix A and vectors x, y and scalars alpha, beta the wrapper determines the suitable SpMV computing y = alpha * A * x + beta * y.

Function Documentation

magma_int_t magma_d_spmv ( double  alpha,
magma_d_sparse_matrix  A,
magma_d_vector  x,
double  beta,
magma_d_vector  y,
magma_queue_t  queue 
)

For a given input matrix A and vectors x, y and scalars alpha, beta the wrapper determines the suitable SpMV computing y = alpha * A * x + beta * y.

Parameters:
[in] alpha double scalar alpha
[in] A magma_d_sparse_matrix sparse matrix A
[in] x magma_d_vector input vector x
[in] beta double scalar beta
[out] y magma_d_vector output vector y
[in] queue magma_queue_t Queue to execute in.
void magma_dcompactActive ( magma_int_t  m,
magma_int_t  n,
magmaDouble_ptr  dA,
magma_int_t  ldda,
magmaInt_ptr  active,
magma_queue_t  queue 
)

ZCOMPACTACTIVE takes a set of n vectors of size m (in dA) and an array of 1s and 0sindicating which vectors to compact (for 1s) and which to disregard (for 0s).

Parameters:
[in] m INTEGER The number of rows of the matrix dA. M >= 0.
[in] n INTEGER The number of columns of the matrix dA. N >= 0.
[in] in,out] dA COMPLEX DOUBLE PRECISION array, dimension (LDDA,N) The m by n matrix dA.
[in] ldda INTEGER The leading dimension of the array dA. LDDA >= max(1,M).
[in] active INTEGER array, dimension N A mask of 1s and 0s showing if a vector remains or has been removed
[in] queue magma_queue_t Queue to execute in.
magma_int_t magma_dgeelltmv ( magma_trans_t  transA,
magma_int_t  m,
magma_int_t  n,
magma_int_t  nnz_per_row,
double  alpha,
magmaDouble_ptr  dval,
magmaIndex_ptr  dcolind,
magmaDouble_ptr  dx,
double  beta,
magmaDouble_ptr  dy,
magma_queue_t  queue 
)

This routine computes y = alpha * A^t * x + beta * y on the GPU.

Input format is ELL.

Parameters:
[in] transA magma_trans_t transposition parameter for A
[in] m magma_int_t number of rows in A
[in] n magma_int_t number of columns in A
[in] nnz_per_row magma_int_t number of elements in the longest row
[in] alpha double scalar multiplier
[in] dval magmaDouble_ptr array containing values of A in ELL
[in] dcolind magmaIndex_ptr columnindices of A in ELL
[in] dx magmaDouble_ptr input vector x
[in] beta double scalar multiplier
[out] dy magmaDouble_ptr input/output vector y
[in] queue magma_queue_t Queue to execute in.
magma_int_t magma_dgemvmdot ( int  n,
int  k,
magmaDouble_ptr  v,
magmaDouble_ptr  r,
magmaDouble_ptr  d1,
magmaDouble_ptr  d2,
magmaDouble_ptr  skp,
magma_queue_t  queue 
)

This is an extension of the merged dot product above by chunking the set of vectors v_i such that the data always fits into cache.

It is equivalent to a matrix vecor product Vr where V contains few rows and many columns. The computation is the same:

skp = ( <v_0,r>, <v_1,r>, .. )

Returns the vector skp.

Parameters:
[in] n int length of v_i and r
[in] k int # vectors v_i
[in] v magmaDouble_ptr v = (v_0 .. v_i.. v_k)
[in] r magmaDouble_ptr r
[in] d1 magmaDouble_ptr workspace
[in] d2 magmaDouble_ptr workspace
[out] skp magmaDouble_ptr vector[k] of scalar products (<v_i,r>...)
[in] queue magma_queue_t Queue to execute in.
magma_int_t magma_djacobi_diagscal ( int  num_rows,
magma_d_vector  d,
magma_d_vector  b,
magma_d_vector *  c,
magma_queue_t  queue 
)

Prepares the Jacobi Iteration according to x^(k+1) = D^(-1) * b - D^(-1) * (L+U) * x^k x^(k+1) = c - M * x^k.

Returns the vector c. It calls a GPU kernel

Parameters:
[in] num_rows magma_int_t number of rows
[in] b magma_d_vector RHS b
[in] d magma_d_vector vector with diagonal entries
[out] c magma_d_vector* c = D^(-1) * b
[in] queue magma_queue_t Queue to execute in.
magma_int_t magma_djacobiiter ( magma_d_sparse_matrix  M,
magma_d_vector  c,
magma_d_vector *  x,
magma_d_solver_par *  solver_par,
magma_queue_t  queue 
)

Iterates the solution approximation according to x^(k+1) = D^(-1) * b - D^(-1) * (L+U) * x^k x^(k+1) = c - M * x^k.

Parameters:
[in] M magma_d_sparse_matrix input matrix M = D^(-1) * (L+U)
[in] c magma_d_vector c = D^(-1) * b
[in,out] x magma_d_vector* iteration vector x
[in,out] solver_par magma_d_solver_par* solver parameters
[in] queue magma_queue_t Queue to execute in.
magma_int_t magma_djacobiiter_precond ( magma_d_sparse_matrix  M,
magma_d_vector *  x,
magma_d_solver_par *  solver_par,
magma_d_preconditioner *  precond,
magma_queue_t  queue 
)

Iterates the solution approximation according to x^(k+1) = D^(-1) * b - D^(-1) * (L+U) * x^k x^(k+1) = c - M * x^k.

Parameters:
[in] M magma_d_sparse_matrix input matrix M = D^(-1) * (L+U)
[in] c magma_d_vector c = D^(-1) * b
[in,out] x magma_d_vector* iteration vector x
[in,out] solver_par magma_d_solver_par* solver parameters
[in] solver_par magma_d_precond_par* precond parameters
[in] queue magma_queue_t Queue to execute in.
magma_int_t magma_djacobisetup ( magma_d_sparse_matrix  A,
magma_d_vector  b,
magma_d_sparse_matrix *  M,
magma_d_vector *  c,
magma_queue_t  queue 
)

Prepares the Jacobi Iteration according to x^(k+1) = D^(-1) * b - D^(-1) * (L+U) * x^k x^(k+1) = c - M * x^k.

Parameters:
[in] A magma_d_sparse_matrix input matrix A
[in] b magma_d_vector RHS b
[in] M magma_d_sparse_matrix* M = D^(-1) * (L+U)
[in] c magma_d_vector* c = D^(-1) * b
[in] queue magma_queue_t Queue to execute in.
magma_int_t magma_djacobisetup_diagscal ( magma_d_sparse_matrix  A,
magma_d_vector *  d,
magma_queue_t  queue 
)

It returns a vector d containing the inverse diagonal elements.

Parameters:
[in] A magma_d_sparse_matrix input matrix A
[in,out] d magma_d_vector* vector with diagonal elements
[in] queue magma_queue_t Queue to execute in.
magma_int_t magma_djacobisetup_matrix ( magma_d_sparse_matrix  A,
magma_d_sparse_matrix *  M,
magma_d_vector *  d,
magma_queue_t  queue 
)

Prepares the Matrix M for the Jacobi Iteration according to x^(k+1) = D^(-1) * b - D^(-1) * (L+U) * x^k x^(k+1) = c - M * x^k.

It returns the preconditioner Matrix M and a vector d containing the diagonal elements.

Parameters:
[in] A magma_d_sparse_matrix input matrix A
[in] M magma_d_sparse_matrix* M = D^(-1) * (L+U)
[in,out] d magma_d_vector* vector with diagonal elements of A
[in] queue magma_queue_t Queue to execute in.
magma_int_t magma_djacobisetup_vector ( magma_d_vector  b,
magma_d_vector  d,
magma_d_vector *  c,
magma_queue_t  queue 
)

Prepares the Jacobi Iteration according to x^(k+1) = D^(-1) * b - D^(-1) * (L+U) * x^k x^(k+1) = c - M * x^k.

Returns the vector c

Parameters:
[in] b magma_d_vector RHS b
[in] d magma_d_vector vector with diagonal entries
[in] c magma_d_vector* c = D^(-1) * b
[in] queue magma_queue_t Queue to execute in.

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