xref: /petsc/src/mat/impls/aij/mpi/mpiviennacl/mpiaijviennacl.cxx (revision d083f849a86f1f43e18d534ee43954e2786cb29a)
1aaa7dc30SBarry Smith #include <petscconf.h>
28f86e40fSKarl Rupp #include <../src/mat/impls/aij/mpi/mpiaij.h>   /*I "petscmat.h" I*/
365e3cb35SKarl Rupp #include <../src/mat/impls/aij/seq/seqviennacl/viennaclmatimpl.h>
48f86e40fSKarl Rupp 
58f86e40fSKarl Rupp PetscErrorCode  MatMPIAIJSetPreallocation_MPIAIJViennaCL(Mat B,PetscInt d_nz,const PetscInt d_nnz[],PetscInt o_nz,const PetscInt o_nnz[])
68f86e40fSKarl Rupp {
78f86e40fSKarl Rupp   Mat_MPIAIJ     *b = (Mat_MPIAIJ*)B->data;
88f86e40fSKarl Rupp   PetscErrorCode ierr;
98f86e40fSKarl Rupp 
108f86e40fSKarl Rupp   PetscFunctionBegin;
118f86e40fSKarl Rupp   ierr = PetscLayoutSetUp(B->rmap);CHKERRQ(ierr);
128f86e40fSKarl Rupp   ierr = PetscLayoutSetUp(B->cmap);CHKERRQ(ierr);
138f86e40fSKarl Rupp   if (!B->preallocated) {
148f86e40fSKarl Rupp     /* Explicitly create the two MATSEQAIJVIENNACL matrices. */
158f86e40fSKarl Rupp     ierr = MatCreate(PETSC_COMM_SELF,&b->A);CHKERRQ(ierr);
168f86e40fSKarl Rupp     ierr = MatSetSizes(b->A,B->rmap->n,B->cmap->n,B->rmap->n,B->cmap->n);CHKERRQ(ierr);
178f86e40fSKarl Rupp     ierr = MatSetType(b->A,MATSEQAIJVIENNACL);CHKERRQ(ierr);
18f7daeb2aSKarl Rupp     ierr = PetscLogObjectParent((PetscObject)B,(PetscObject)b->A);CHKERRQ(ierr);
198f86e40fSKarl Rupp     ierr = MatCreate(PETSC_COMM_SELF,&b->B);CHKERRQ(ierr);
208f86e40fSKarl Rupp     ierr = MatSetSizes(b->B,B->rmap->n,B->cmap->N,B->rmap->n,B->cmap->N);CHKERRQ(ierr);
218f86e40fSKarl Rupp     ierr = MatSetType(b->B,MATSEQAIJVIENNACL);CHKERRQ(ierr);
22f7daeb2aSKarl Rupp     ierr = PetscLogObjectParent((PetscObject)B,(PetscObject)b->B);CHKERRQ(ierr);
238f86e40fSKarl Rupp   }
248f86e40fSKarl Rupp   ierr = MatSeqAIJSetPreallocation(b->A,d_nz,d_nnz);CHKERRQ(ierr);
258f86e40fSKarl Rupp   ierr = MatSeqAIJSetPreallocation(b->B,o_nz,o_nnz);CHKERRQ(ierr);
268f86e40fSKarl Rupp   B->preallocated = PETSC_TRUE;
278f86e40fSKarl Rupp   PetscFunctionReturn(0);
288f86e40fSKarl Rupp }
298f86e40fSKarl Rupp 
3074fd8ad3SBarry Smith PetscErrorCode MatAssemblyEnd_MPIAIJViennaCL(Mat A,MatAssemblyType mode)
3174fd8ad3SBarry Smith {
3274fd8ad3SBarry Smith   Mat_MPIAIJ     *b = (Mat_MPIAIJ*)A->data;
3374fd8ad3SBarry Smith   PetscErrorCode ierr;
3474fd8ad3SBarry Smith   PetscBool      v;
3574fd8ad3SBarry Smith 
3674fd8ad3SBarry Smith   PetscFunctionBegin;
3774fd8ad3SBarry Smith   ierr = MatAssemblyEnd_MPIAIJ(A,mode);CHKERRQ(ierr);
3874fd8ad3SBarry Smith   ierr = PetscObjectTypeCompare((PetscObject)b->lvec,VECSEQVIENNACL,&v);CHKERRQ(ierr);
3974fd8ad3SBarry Smith   if (!v) {
4074fd8ad3SBarry Smith     PetscInt m;
4174fd8ad3SBarry Smith     ierr = VecGetSize(b->lvec,&m);CHKERRQ(ierr);
4274fd8ad3SBarry Smith     ierr = VecDestroy(&b->lvec);CHKERRQ(ierr);
4374fd8ad3SBarry Smith     ierr = VecCreateSeqViennaCL(PETSC_COMM_SELF,m,&b->lvec);CHKERRQ(ierr);
4474fd8ad3SBarry Smith   }
4574fd8ad3SBarry Smith   PetscFunctionReturn(0);
4674fd8ad3SBarry Smith }
478f86e40fSKarl Rupp 
488f86e40fSKarl Rupp PetscErrorCode MatDestroy_MPIAIJViennaCL(Mat A)
498f86e40fSKarl Rupp {
508f86e40fSKarl Rupp   PetscErrorCode ierr;
518f86e40fSKarl Rupp 
528f86e40fSKarl Rupp   PetscFunctionBegin;
538f86e40fSKarl Rupp   ierr = MatDestroy_MPIAIJ(A);CHKERRQ(ierr);
548f86e40fSKarl Rupp   PetscFunctionReturn(0);
558f86e40fSKarl Rupp }
568f86e40fSKarl Rupp 
578f86e40fSKarl Rupp PETSC_EXTERN PetscErrorCode MatCreate_MPIAIJViennaCL(Mat A)
588f86e40fSKarl Rupp {
598f86e40fSKarl Rupp   PetscErrorCode ierr;
608f86e40fSKarl Rupp 
618f86e40fSKarl Rupp   PetscFunctionBegin;
628f86e40fSKarl Rupp   ierr = MatCreate_MPIAIJ(A);CHKERRQ(ierr);
6334136279SStefano Zampini   ierr = PetscFree(A->defaultvectype);CHKERRQ(ierr);
6434136279SStefano Zampini   ierr = PetscStrallocpy(VECVIENNACL,&A->defaultvectype);CHKERRQ(ierr);
65ab6435e1SKarl Rupp   ierr = PetscObjectComposeFunction((PetscObject)A,"MatMPIAIJSetPreallocation_C",MatMPIAIJSetPreallocation_MPIAIJViennaCL);CHKERRQ(ierr);
6674fd8ad3SBarry Smith   A->ops->assemblyend = MatAssemblyEnd_MPIAIJViennaCL;
678f86e40fSKarl Rupp   ierr = PetscObjectChangeTypeName((PetscObject)A,MATMPIAIJVIENNACL);CHKERRQ(ierr);
688f86e40fSKarl Rupp   PetscFunctionReturn(0);
698f86e40fSKarl Rupp }
708f86e40fSKarl Rupp 
718f86e40fSKarl Rupp 
728f86e40fSKarl Rupp /*@
738f86e40fSKarl Rupp    MatCreateAIJViennaCL - Creates a sparse matrix in AIJ (compressed row) format
74023073b3SKarl Rupp    (the default parallel PETSc format).  This matrix will ultimately be pushed down
758f86e40fSKarl Rupp    to GPUs and use the ViennaCL library for calculations. For good matrix
768f86e40fSKarl Rupp    assembly performance the user should preallocate the matrix storage by setting
778f86e40fSKarl Rupp    the parameter nz (or the array nnz).  By setting these parameters accurately,
788f86e40fSKarl Rupp    performance during matrix assembly can be increased substantially.
798f86e40fSKarl Rupp 
808f86e40fSKarl Rupp 
81*d083f849SBarry Smith    Collective
828f86e40fSKarl Rupp 
838f86e40fSKarl Rupp    Input Parameters:
848f86e40fSKarl Rupp +  comm - MPI communicator, set to PETSC_COMM_SELF
858f86e40fSKarl Rupp .  m - number of rows
868f86e40fSKarl Rupp .  n - number of columns
878f86e40fSKarl Rupp .  nz - number of nonzeros per row (same for all rows)
888f86e40fSKarl Rupp -  nnz - array containing the number of nonzeros in the various rows
898f86e40fSKarl Rupp          (possibly different for each row) or NULL
908f86e40fSKarl Rupp 
918f86e40fSKarl Rupp    Output Parameter:
928f86e40fSKarl Rupp .  A - the matrix
938f86e40fSKarl Rupp 
948f86e40fSKarl Rupp    It is recommended that one use the MatCreate(), MatSetType() and/or MatSetFromOptions(),
958f86e40fSKarl Rupp    MatXXXXSetPreallocation() paradigm instead of this routine directly.
968f86e40fSKarl Rupp    [MatXXXXSetPreallocation() is, for example, MatSeqAIJSetPreallocation]
978f86e40fSKarl Rupp 
988f86e40fSKarl Rupp    Notes:
998f86e40fSKarl Rupp    If nnz is given then nz is ignored
1008f86e40fSKarl Rupp 
1018f86e40fSKarl Rupp    The AIJ format (also called the Yale sparse matrix format or
1028f86e40fSKarl Rupp    compressed row storage), is fully compatible with standard Fortran 77
1038f86e40fSKarl Rupp    storage.  That is, the stored row and column indices can begin at
1048f86e40fSKarl Rupp    either one (as in Fortran) or zero.  See the users' manual for details.
1058f86e40fSKarl Rupp 
1068f86e40fSKarl Rupp    Specify the preallocated storage with either nz or nnz (not both).
1078f86e40fSKarl Rupp    Set nz=PETSC_DEFAULT and nnz=NULL for PETSc to control dynamic memory
1088f86e40fSKarl Rupp    allocation.  For large problems you MUST preallocate memory or you
1098f86e40fSKarl Rupp    will get TERRIBLE performance, see the users' manual chapter on matrices.
1108f86e40fSKarl Rupp 
1118f86e40fSKarl Rupp    Level: intermediate
1128f86e40fSKarl Rupp 
113e9e886b6SKarl Rupp .seealso: MatCreate(), MatCreateAIJ(), MatCreateAIJCUSPARSE(), MatSetValues(), MatSeqAIJSetColumnIndices(), MatCreateSeqAIJWithArrays(), MatCreateAIJ(), MATMPIAIJVIENNACL, MATAIJVIENNACL
1148f86e40fSKarl Rupp @*/
1158f86e40fSKarl Rupp PetscErrorCode  MatCreateAIJViennaCL(MPI_Comm comm,PetscInt m,PetscInt n,PetscInt M,PetscInt N,PetscInt d_nz,const PetscInt d_nnz[],PetscInt o_nz,const PetscInt o_nnz[],Mat *A)
1168f86e40fSKarl Rupp {
1178f86e40fSKarl Rupp   PetscErrorCode ierr;
1188f86e40fSKarl Rupp   PetscMPIInt    size;
1198f86e40fSKarl Rupp 
1208f86e40fSKarl Rupp   PetscFunctionBegin;
1218f86e40fSKarl Rupp   ierr = MatCreate(comm,A);CHKERRQ(ierr);
1228f86e40fSKarl Rupp   ierr = MatSetSizes(*A,m,n,M,N);CHKERRQ(ierr);
1238f86e40fSKarl Rupp   ierr = MPI_Comm_size(comm,&size);CHKERRQ(ierr);
1248f86e40fSKarl Rupp   if (size > 1) {
1258f86e40fSKarl Rupp     ierr = MatSetType(*A,MATMPIAIJVIENNACL);CHKERRQ(ierr);
1268f86e40fSKarl Rupp     ierr = MatMPIAIJSetPreallocation(*A,d_nz,d_nnz,o_nz,o_nnz);CHKERRQ(ierr);
1278f86e40fSKarl Rupp   } else {
1288f86e40fSKarl Rupp     ierr = MatSetType(*A,MATSEQAIJVIENNACL);CHKERRQ(ierr);
1298f86e40fSKarl Rupp     ierr = MatSeqAIJSetPreallocation(*A,d_nz,d_nnz);CHKERRQ(ierr);
1308f86e40fSKarl Rupp   }
1318f86e40fSKarl Rupp   PetscFunctionReturn(0);
1328f86e40fSKarl Rupp }
1338f86e40fSKarl Rupp 
1343ca39a21SBarry Smith /*MC
1358f86e40fSKarl Rupp    MATAIJVIENNACL - MATMPIAIJVIENNACL= "aijviennacl" = "mpiaijviennacl" - A matrix type to be used for sparse matrices.
1368f86e40fSKarl Rupp 
1378f86e40fSKarl Rupp    A matrix type (CSR format) whose data resides on GPUs.
1388f86e40fSKarl Rupp    All matrix calculations are performed using the ViennaCL library.
1398f86e40fSKarl Rupp 
1408f86e40fSKarl Rupp    This matrix type is identical to MATSEQAIJVIENNACL when constructed with a single process communicator,
1418f86e40fSKarl Rupp    and MATMPIAIJVIENNACL otherwise.  As a result, for single process communicators,
1428f86e40fSKarl Rupp    MatSeqAIJSetPreallocation is supported, and similarly MatMPIAIJSetPreallocation is supported
1438f86e40fSKarl Rupp    for communicators controlling multiple processes.  It is recommended that you call both of
1448f86e40fSKarl Rupp    the above preallocation routines for simplicity.
1458f86e40fSKarl Rupp 
1468f86e40fSKarl Rupp    Options Database Keys:
1478f86e40fSKarl Rupp +  -mat_type mpiaijviennacl - sets the matrix type to "mpiaijviennacl" during a call to MatSetFromOptions()
1488f86e40fSKarl Rupp 
1498f86e40fSKarl Rupp   Level: beginner
1508f86e40fSKarl Rupp 
1518f86e40fSKarl Rupp  .seealso: MatCreateAIJViennaCL(), MATSEQAIJVIENNACL, MatCreateSeqAIJVIENNACL()
1528f86e40fSKarl Rupp M*/
153