single precision
[Sparse unfiled]

Functions

magma_int_t magma_s_spmv (float alpha, magma_s_sparse_matrix A, magma_s_vector x, float beta, magma_s_vector y)
 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.
void magma_scompactActive (magma_int_t m, magma_int_t n, float *dA, magma_int_t ldda, magma_index_t *active)
 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_sgeelltmv (magma_trans_t transA, magma_int_t m, magma_int_t n, magma_int_t nnz_per_row, float alpha, float *d_val, magma_index_t *d_colind, float *d_x, float beta, float *d_y)
 This routine computes y = alpha * A^t * x + beta * y on the GPU.
magma_int_t magma_sjacobi_diagscal (int num_rows, float *b, float *d, float *c)
 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_sgemvmdot (int n, int k, float *v, float *r, float *d1, float *d2, float *skp)
 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.

Function Documentation

magma_int_t magma_s_spmv ( float  alpha,
magma_s_sparse_matrix  A,
magma_s_vector  x,
float  beta,
magma_s_vector  y 
)

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:
alpha float scalar alpha
A magma_s_sparse_matrix sparse matrix A
x magma_s_vector input vector x
beta float scalar beta
y magma_s_vector output vector y
void magma_scompactActive ( magma_int_t  m,
magma_int_t  n,
float *  dA,
magma_int_t  ldda,
magma_index_t *  active 
)

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,out] dA COMPLEX REAL 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
magma_int_t magma_sgeelltmv ( magma_trans_t  transA,
magma_int_t  m,
magma_int_t  n,
magma_int_t  nnz_per_row,
float  alpha,
float *  d_val,
magma_index_t *  d_colind,
float *  d_x,
float  beta,
float *  d_y 
)

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

Input format is ELL.

Parameters:
transA magma_trans_t transposition parameter for A
m magma_int_t number of rows in A
n magma_int_t number of columns in A
nnz_per_row magma_int_t number of elements in the longest row
alpha float scalar multiplier
d_val float* array containing values of A in ELL
d_colind magma_int_t* columnindices of A in ELL
d_x float* input vector x
beta float scalar multiplier
d_y float* input/output vector y
magma_int_t magma_sgemvmdot ( int  n,
int  k,
float *  v,
float *  r,
float *  d1,
float *  d2,
float *  skp 
)

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:
n int length of v_i and r
k int # vectors v_i
v float* v = (v_0 .. v_i.. v_k)
r float* r
d1 float* workspace
d2 float* workspace
skp float* vector[k] of scalar products (<v_i,r>...)
magma_int_t magma_sjacobi_diagscal ( int  num_rows,
float *  b,
float *  d,
float *  c 
)

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:
num_rows magma_int_t number of rows
b magma_s_vector RHS b
d magma_s_vector vector with diagonal entries
c magma_s_vector* c = D^(-1) * b

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