# MatMPIBAIJSetPreallocation

Allocates memory for a sparse parallel matrix in block AIJ format (block compressed row). For good matrix assembly performance the user should preallocate the matrix storage by setting the parameters d_nz (or d_nnz) and o_nz (or o_nnz). By setting these parameters accurately, performance can be increased by more than a factor of 50.

### Synopsis

    #include "petscmat.h"
    PetscErrorCode PETSCMAT_DLLEXPORT MatMPIBAIJSetPreallocation(Mat B,PetscInt bs,PetscInt d_nz,const PetscInt d_nnz[],PetscInt o_nz,const PetscInt o_nnz[])

Collective on Mat

### Input Parameters

| A | - the matrix
| bs | - size of blockk
| d_nz | - number of block nonzeros per block row in diagonal portion of local submatrix (same for all local rows)
| d_nnz | - array containing the number of block nonzeros in the various block rows of the in diagonal portion of the local (possibly different for each block row) or PETSC_NULL. You must leave room for the diagonal entry even if it is zero.
| o_nz | - number of block nonzeros per block row in the off-diagonal portion of local submatrix (same for all local rows).
| o_nnz | - array containing the number of nonzeros in the various block rows of the off-diagonal portion of the local submatrix (possibly different for each block row) or PETSC_NULL.

If the *_nnz parameter is given then the *_nz parameter is ignored

### Options Database Keys

-mat_no_unroll -uses code that does not unroll the loops in the block calculations (much slower)
-mat_block_size -size of the blocks to use

### C++ variants

| MatMPIBAIJSetPreallocation(Mat A,PetscInt bs,const PetscInt nnz[],const PetscInt onz[]) |  | -> |  | MatMPIBAIJSetPreallocation(A,bs,0,nnz,0,onz)

### Notes

If PETSC_DECIDE or PETSC_DETERMINE is used for a particular argument on one processor than it must be used on all processors that share the object for that argument.

### Storage Information

For a square global matrix we define each processor's diagonal portion to be its local rows and the corresponding columns (a square submatrix); each processor's off-diagonal portion encompasses the remainder of the local matrix (a rectangular submatrix).

The user can specify preallocated storage for the diagonal part of the local submatrix with either d_nz or d_nnz (not both). Set d_nz=PETSC_DEFAULT and d_nnz=PETSC_NULL for PETSc to control dynamic memory allocation. Likewise, specify preallocated storage for the off-diagonal part of the local submatrix with o_nz or o_nnz (not both).

Consider a processor that owns rows 3, 4 and 5 of a parallel matrix. In the figure below we depict these three local rows and all columns (0-11).

               0 1 2 3 4 5 6 7 8 9 10 11
              -------------------
       row 3  |  o o o d d d o o o o o o
       row 4  |  o o o d d d o o o o o o
       row 5  |  o o o d d d o o o o o o
              -------------------

Thus, any entries in the d locations are stored in the d (diagonal) submatrix, and any entries in the o locations are stored in the o (off-diagonal) submatrix. Note that the d and the o submatrices are stored simply in the MATSEQBAIJ format for compressed row storage.

Now d_nz should indicate the number of block nonzeros per row in the d matrix, and o_nz should indicate the number of block nonzeros per row in the o matrix. In general, for PDE problems in which most nonzeros are near the diagonal, one expects d_nz >> o_nz. For large problems you MUST preallocate memory or you will get TERRIBLE performance; see the users' manual chapter on matrices.

### Keywords

matrix, block, aij, compressed row, sparse, parallel

### See Also

MatCreate(), MatCreateSeqBAIJ(), MatSetValues(), MatCreateMPIBAIJ(), MatMPIBAIJSetPreallocationCSR()

Level:intermediate
Location:src/mat/impls/baij/mpi/mpibaij.c
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