MatCreateAIJCUSPARSE#
Creates a sparse matrix in MATAIJCUSPARSE (compressed row) format (the default parallel PETSc format). This matrix will ultimately pushed down to NVIDIA GPUs and use the CuSPARSE library for calculations.
Synopsis#
Collective
Input Parameters#
comm - MPI communicator, set to
PETSC_COMM_SELFm - number of local rows (or
PETSC_DECIDEto have calculated ifMis given) This value should be the same as the local size used in creating the y vector for the matrix-vector product y = Ax.n - This value should be the same as the local size used in creating the x vector for the matrix-vector product y = Ax. (or PETSC_DECIDE to have calculated if
Nis given) For square matricesnis almost alwaysm.M - number of global rows (or
PETSC_DETERMINEto have calculated ifmis given)N - number of global columns (or
PETSC_DETERMINEto have calculated ifnis given)d_nz - number of nonzeros per row in DIAGONAL portion of local submatrix (same value is used for all local rows)
d_nnz - array containing the number of nonzeros in the various rows of the DIAGONAL portion of the local submatrix (possibly different for each row) or
NULL, ifd_nzis used to specify the nonzero structure. The size of this array is equal to the number of local rows, i.em. For matrices you plan to factor you must leave room for the diagonal entry and put in the entry even if it is zero.o_nz - number of nonzeros per row in the OFF-DIAGONAL portion of local submatrix (same value is used for all local rows).
o_nnz - array containing the number of nonzeros in the various rows of the OFF-DIAGONAL portion of the local submatrix (possibly different for each row) or
NULL, ifo_nzis used to specify the nonzero structure. The size of this array is equal to the number of local rows, i.em.
Output Parameter#
A - the matrix
Notes#
It is recommended that one use the MatCreate(), MatSetType() and/or MatSetFromOptions(),
MatXXXXSetPreallocation() paradigm instead of this routine directly.
[MatXXXXSetPreallocation() is, for example, MatSeqAIJSetPreallocation()]
The AIJ format, also called the 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.
See Also#
Matrices, Mat, MATAIJCUSPARSE, MatCreate(), MatCreateAIJ(), MatSetValues(), MatSeqAIJSetColumnIndices(), MatCreateSeqAIJWithArrays(), MATMPIAIJCUSPARSE
Level#
intermediate
Location#
src/mat/impls/aij/mpi/mpicusparse/mpiaijcusparse.cu
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