MatCreateSeqAIJHIPSPARSE#
Creates a sparse matrix in MATAIJHIPSPARSE
(compressed row) format. This matrix will ultimately pushed down to AMD GPUs and use the HIPSPARSE library for calculations. For good matrix assembly performance the user should preallocate the matrix storage by setting the parameter nz
(or the array nnz
).
Synopsis#
#include "petscmat.h"
PetscErrorCode MatCreateSeqAIJHIPSPARSE(MPI_Comm comm, PetscInt m, PetscInt n, PetscInt nz, const PetscInt nnz[], Mat *A)
Collective
Input Parameters#
comm - MPI communicator, set to
PETSC_COMM_SELF
m - number of rows
n - number of columns
nz - number of nonzeros per row (same for all rows)
nnz - array containing the number of nonzeros in the various rows (possibly different for each row) or
NULL
Output Parameter#
A - the matrix
Notes#
It is recommended that one use the MatCreate()
, MatSetType()
and/or MatSetFromOptions()
,
MatXXXXSetPreallocation()
paradgm instead of this routine directly.
[MatXXXXSetPreallocation() is, for example, MatSeqAIJSetPreallocation
]
If nnz
is given then nz
is ignored
The AIJ format (compressed row storage), is fully compatible with standard Fortran storage. That is, the stored row and column indices can begin at either one (as in Fortran) or zero.
Specify the preallocated storage with either nz
or nnz
(not both).
Set nz
= PETSC_DEFAULT
and nnz
= NULL
for PETSc to control dynamic memory
allocation.
By default, this format uses inodes (identical nodes) when possible, to improve numerical efficiency of matrix-vector products and solves. We search for consecutive rows with the same nonzero structure, thereby reusing matrix information to achieve increased efficiency.
See Also#
Matrices, Mat
, MatCreate()
, MatCreateAIJ()
, MatSetValues()
, MatSeqAIJSetColumnIndices()
, MatCreateSeqAIJWithArrays()
, MatCreateAIJ()
, MATSEQAIJHIPSPARSE
, MATAIJHIPSPARSE
Level#
intermediate
Location#
src/mat/impls/aij/seq/seqhipsparse/aijhipsparse.hip.cpp
Index of all Mat routines
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