int main(int argc,char **argv) {
Mat A,B,As;
PetscInt i,j,k,nz,n,*ai,*aj,asi[]={0,2,3,4,6,7};
PetscInt asj[]={0,4,1,2,3,4,4};
PetscScalar asa[7],*aa;
PetscRandom rctx;
PetscErrorCode ierr;
PetscMPIInt size;
PetscBool flg;
PetscInitialize(&argc,&argv,(char *)0,help);
ierr = MPI_Comm_size(PETSC_COMM_WORLD,&size);CHKERRQ(ierr);
if (size != 1) SETERRQ(PETSC_COMM_WORLD,PETSC_ERR_SUP,"This is a uniprocessor example only!");
/* Create a aij matrix for checking */
ierr = MatCreateSeqAIJ(PETSC_COMM_SELF,5,5,2,PETSC_NULL,&A);CHKERRQ(ierr);
ierr = PetscRandomCreate(PETSC_COMM_WORLD,&rctx);CHKERRQ(ierr);
ierr = PetscRandomSetFromOptions(rctx);CHKERRQ(ierr);
k = 0;
for (i=0; i<5; i++) {
nz = asi[i+1] - asi[i]; /* length of i_th row of A */
for (j=0; j<nz; j++){
ierr = PetscRandomGetValue(rctx,&asa[k]);CHKERRQ(ierr);
ierr = MatSetValues(A,1,&i,1,&asj[k],&asa[k],INSERT_VALUES);CHKERRQ(ierr);
ierr = MatSetValues(A,1,&i,1,&asj[k],&asa[k],INSERT_VALUES);CHKERRQ(ierr);
if (i != asj[k]){ /* insert symmetric entry */
ierr = MatSetValues(A,1,&asj[k],1,&i,&asa[k],INSERT_VALUES);CHKERRQ(ierr);
}
k++;
}
}
ierr = MatAssemblyBegin(A,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr);
ierr = MatAssemblyEnd(A,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr);
/* Create a baij matrix using MatCreateSeqBAIJWithArrays() */
ierr = MatGetRowIJ(A,0,PETSC_FALSE,PETSC_FALSE,&n,&ai,&aj,&flg);CHKERRQ(ierr);
ierr = MatGetArray(A,&aa);CHKERRQ(ierr);
ierr = MatCreateSeqBAIJWithArrays(PETSC_COMM_SELF,1,5,5,ai,aj,aa,&B);CHKERRQ(ierr);
ierr = MatRestoreArray(A,&aa);CHKERRQ(ierr);
ierr = MatRestoreRowIJ(A,0,PETSC_FALSE,PETSC_FALSE,&n,&ai,&aj,&flg);CHKERRQ(ierr);
ierr = MatMultEqual(A,B,10,&flg);CHKERRQ(ierr);
if (!flg) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_NOTSAMETYPE,"MatMult(A,B) are NOT equal");
/* Create a sbaij matrix using MatCreateSeqSBAIJWithArrays() */
ierr = MatCreateSeqSBAIJWithArrays(PETSC_COMM_SELF,1,5,5,asi,asj,asa,&As);CHKERRQ(ierr);
ierr = MatMultEqual(A,As,10,&flg);CHKERRQ(ierr);
if (!flg) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_NOTSAMETYPE,"MatMult(A,As) are NOT equal");
/* Free spaces */
ierr = PetscRandomDestroy(&rctx);CHKERRQ(ierr);
ierr = MatDestroy(&A);CHKERRQ(ierr);
ierr = MatDestroy(&B);CHKERRQ(ierr);
ierr = MatDestroy(&As);CHKERRQ(ierr);
ierr = PetscFinalize();
return(0);
}
void
destroy() {
if (valid) {
//clean up the local array structures I allocated.
MatRestoreArray(mat, &data);
PetscTruth done = PETSC_FALSE;
MatRestoreRowIJ(mat, 0, PETSC_FALSE, PETSC_FALSE, &nrows, &ia, &ja, &done);
assert(done == PETSC_TRUE || "Unexpected error: can't return csr structure to matrix");
}
valid = false;
}
int main(int argc,char **argv)
{
Mat A,B,C,D;
PetscInt i,j,k,M=10,N=5;
PetscScalar *array,*a;
PetscErrorCode ierr;
PetscRandom r;
PetscTruth equal=PETSC_FALSE;
PetscReal fill = 1.0;
PetscInt rstart,rend,nza,col,am,an,bm,bn;
PetscInitialize(&argc,&argv,(char *)0,help);
ierr = PetscOptionsGetInt(PETSC_NULL,"-M",&M,PETSC_NULL);CHKERRQ(ierr);
ierr = PetscOptionsGetInt(PETSC_NULL,"-N",&N,PETSC_NULL);CHKERRQ(ierr);
ierr = PetscOptionsGetReal(PETSC_NULL,"-fill",&fill,PETSC_NULL);CHKERRQ(ierr);
ierr = PetscRandomCreate(PETSC_COMM_WORLD,&r);CHKERRQ(ierr);
ierr = PetscRandomSetFromOptions(r);CHKERRQ(ierr);
/* create a aij matrix A */
ierr = MatCreate(PETSC_COMM_WORLD,&A);CHKERRQ(ierr);
ierr = MatSetSizes(A,PETSC_DECIDE,PETSC_DECIDE,N,M);CHKERRQ(ierr);
ierr = MatSetType(A,MATAIJ);CHKERRQ(ierr);
nza = (PetscInt)(.3*M); /* num of nozeros in each row of A */
ierr = MatSeqAIJSetPreallocation(A,nza,PETSC_NULL);CHKERRQ(ierr);
ierr = MatMPIAIJSetPreallocation(A,nza,PETSC_NULL,nza,PETSC_NULL);CHKERRQ(ierr);
ierr = MatGetOwnershipRange(A,&rstart,&rend);CHKERRQ(ierr);
ierr = PetscMalloc((nza+1)*sizeof(PetscScalar),&a);CHKERRQ(ierr);
for (i=rstart; i<rend; i++) {
for (j=0; j<nza; j++) {
ierr = PetscRandomGetValue(r,&a[j]);CHKERRQ(ierr);
col = (PetscInt)(M*PetscRealPart(a[j]));
ierr = MatSetValues(A,1,&i,1,&col,&a[j],ADD_VALUES);CHKERRQ(ierr);
}
}
ierr = MatAssemblyBegin(A,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr);
ierr = MatAssemblyEnd(A,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr);
/* create a dense matrix B */
ierr = MatGetLocalSize(A,&am,&an);CHKERRQ(ierr);
ierr = MatCreate(PETSC_COMM_WORLD,&B);CHKERRQ(ierr);
ierr = MatSetSizes(B,PETSC_DECIDE,am,N,PETSC_DECIDE);CHKERRQ(ierr);
ierr = MatSetType(B,MATDENSE);CHKERRQ(ierr);
ierr = MatSeqDenseSetPreallocation(B,PETSC_NULL);CHKERRQ(ierr);
ierr = MatMPIDenseSetPreallocation(B,PETSC_NULL);CHKERRQ(ierr);
ierr = MatGetLocalSize(B,&bm,&bn);CHKERRQ(ierr);
ierr = MatGetArray(B,&array);CHKERRQ(ierr);
k = 0;
for (j=0; j<N; j++){ /* local column-wise entries */
for (i=0; i<bm; i++){
ierr = PetscRandomGetValue(r,&array[k++]);CHKERRQ(ierr);
}
}
ierr = MatRestoreArray(B,&array);CHKERRQ(ierr);
ierr = PetscRandomDestroy(r);CHKERRQ(ierr);
ierr = MatAssemblyBegin(B,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr);
ierr = MatAssemblyEnd(B,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr);
/* Test MatMatMult() */
ierr = MatMatMult(B,A,MAT_INITIAL_MATRIX,fill,&C);CHKERRQ(ierr);
/*
ierr = PetscViewerSetFormat(PETSC_VIEWER_STDOUT_WORLD,PETSC_VIEWER_ASCII_MATLAB);
ierr = MatView(C,0);CHKERRQ(ierr);
ierr = MatView(B,0);CHKERRQ(ierr);
ierr = MatView(A,0);CHKERRQ(ierr);
*/
ierr = MatMatMultSymbolic(B,A,fill,&D);CHKERRQ(ierr);
for (i=0; i<2; i++){
ierr = MatMatMultNumeric(B,A,D);CHKERRQ(ierr);
}
ierr = MatEqual(C,D,&equal);CHKERRQ(ierr);
if (!equal) SETERRQ(PETSC_ERR_ARG_WRONGSTATE,"C != D");
ierr = MatDestroy(D);CHKERRQ(ierr);
ierr = MatDestroy(C);CHKERRQ(ierr);
ierr = MatDestroy(B);CHKERRQ(ierr);
ierr = MatDestroy(A);CHKERRQ(ierr);
ierr = PetscFree(a);CHKERRQ(ierr);
PetscFinalize();
return(0);
}
int main(int argc,char **args)
{
Mat C,C1,F;
Vec u,x,b;
PetscErrorCode ierr;
PetscMPIInt rank,nproc;
PetscInt i,M = 10,m,n,nfact,nsolve;
PetscScalar *array,rval;
PetscReal norm,tol=1.e-12;
IS perm,iperm;
MatFactorInfo info;
PetscRandom rand;
PetscTruth flg;
PetscInitialize(&argc,&args,(char *)0,help);
ierr = MPI_Comm_rank(PETSC_COMM_WORLD, &rank);CHKERRQ(ierr);
ierr = MPI_Comm_size(PETSC_COMM_WORLD, &nproc);CHKERRQ(ierr);
/* Create matrix and vectors */
ierr = PetscOptionsGetInt(PETSC_NULL,"-M",&M,PETSC_NULL);CHKERRQ(ierr);
ierr = MatCreate(PETSC_COMM_WORLD,&C);CHKERRQ(ierr);
ierr = MatSetSizes(C,PETSC_DECIDE,PETSC_DECIDE,M,M);CHKERRQ(ierr);
ierr = MatSetType(C,MATDENSE);CHKERRQ(ierr);
ierr = MatSetFromOptions(C);CHKERRQ(ierr);
ierr = MatGetLocalSize(C,&m,&n);CHKERRQ(ierr);
if (m != n) SETERRQ2(PETSC_ERR_ARG_WRONG,"Matrix local size m %d must equal n %d",m,n);
ierr = VecCreate(PETSC_COMM_WORLD,&x);CHKERRQ(ierr);
ierr = VecSetSizes(x,n,PETSC_DECIDE);CHKERRQ(ierr);
ierr = VecSetFromOptions(x);CHKERRQ(ierr);
ierr = VecDuplicate(x,&b);CHKERRQ(ierr);
ierr = VecDuplicate(x,&u);CHKERRQ(ierr); /* save the true solution */
/* Assembly */
ierr = PetscRandomCreate(PETSC_COMM_WORLD,&rand);CHKERRQ(ierr);
ierr = PetscRandomSetFromOptions(rand);CHKERRQ(ierr);
ierr = MatGetArray(C,&array);CHKERRQ(ierr);
for (i=0; i<m*M; i++){
ierr = PetscRandomGetValue(rand,&rval);CHKERRQ(ierr);
array[i] = rval;
}
ierr = MatRestoreArray(C,&array);CHKERRQ(ierr);
ierr = MatAssemblyBegin(C,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr);
ierr = MatAssemblyEnd(C,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr);
/*if (!rank) {printf("main, C: \n");}
ierr = MatView(C,PETSC_VIEWER_STDOUT_WORLD);CHKERRQ(ierr); */
/* Test MatDuplicate() */
ierr = MatDuplicate(C,MAT_COPY_VALUES,&C1);CHKERRQ(ierr);
ierr = MatEqual(C,C1,&flg);CHKERRQ(ierr);
if (!flg){
SETERRQ(PETSC_ERR_ARG_WRONG,"Duplicate C1 != C");
}
/* Test LU Factorization */
ierr = MatGetOrdering(C1,MATORDERING_NATURAL,&perm,&iperm);CHKERRQ(ierr);
if (nproc == 1){
ierr = MatGetFactor(C1,MAT_SOLVER_PETSC,MAT_FACTOR_LU,&F);CHKERRQ(ierr);
} else {
ierr = MatGetFactor(C1,MAT_SOLVER_PLAPACK,MAT_FACTOR_LU,&F);CHKERRQ(ierr);
}
ierr = MatLUFactorSymbolic(F,C1,perm,iperm,&info);CHKERRQ(ierr);
for (nfact = 0; nfact < 2; nfact++){
if (!rank) printf(" LU nfact %d\n",nfact);
ierr = MatLUFactorNumeric(F,C1,&info);CHKERRQ(ierr);
/* Test MatSolve() */
for (nsolve = 0; nsolve < 5; nsolve++){
ierr = VecGetArray(x,&array);CHKERRQ(ierr);
for (i=0; i<m; i++){
ierr = PetscRandomGetValue(rand,&rval);CHKERRQ(ierr);
array[i] = rval;
}
ierr = VecRestoreArray(x,&array);CHKERRQ(ierr);
ierr = VecCopy(x,u);CHKERRQ(ierr);
ierr = MatMult(C,x,b);CHKERRQ(ierr);
ierr = MatSolve(F,b,x);CHKERRQ(ierr);
/* Check the error */
ierr = VecAXPY(u,-1.0,x);CHKERRQ(ierr); /* u <- (-1.0)x + u */
ierr = VecNorm(u,NORM_2,&norm);CHKERRQ(ierr);
if (norm > tol){
if (!rank){
ierr = PetscPrintf(PETSC_COMM_SELF,"Error: Norm of error %g, LU nfact %d\n",norm,nfact);CHKERRQ(ierr);
}
}
}
}
ierr = MatDestroy(C1);CHKERRQ(ierr);
ierr = MatDestroy(F);CHKERRQ(ierr);
/* Test Cholesky Factorization */
ierr = MatTranspose(C,MAT_INITIAL_MATRIX,&C1);CHKERRQ(ierr); /* C1 = C^T */
ierr = MatAXPY(C,1.0,C1,SAME_NONZERO_PATTERN);CHKERRQ(ierr); /* make C symmetric: C <- C + C^T */
ierr = MatShift(C,M);CHKERRQ(ierr); /* make C positive definite */
ierr = MatDestroy(C1);CHKERRQ(ierr);
ierr = MatSetOption(C,MAT_SYMMETRIC,PETSC_TRUE);CHKERRQ(ierr);
ierr = MatSetOption(C,MAT_SYMMETRY_ETERNAL,PETSC_TRUE);CHKERRQ(ierr);
if (nproc == 1){
ierr = MatGetFactor(C,MAT_SOLVER_PETSC,MAT_FACTOR_CHOLESKY,&F);CHKERRQ(ierr);
} else {
ierr = MatGetFactor(C,MAT_SOLVER_PLAPACK,MAT_FACTOR_CHOLESKY,&F);CHKERRQ(ierr);
}
ierr = MatCholeskyFactorSymbolic(F,C,perm,&info);CHKERRQ(ierr);
for (nfact = 0; nfact < 2; nfact++){
if (!rank) printf(" Cholesky nfact %d\n",nfact);
ierr = MatCholeskyFactorNumeric(F,C,&info);CHKERRQ(ierr);
/* Test MatSolve() */
for (nsolve = 0; nsolve < 5; nsolve++){
ierr = VecGetArray(x,&array);CHKERRQ(ierr);
for (i=0; i<m; i++){
ierr = PetscRandomGetValue(rand,&rval);CHKERRQ(ierr);
array[i] = rval;
}
ierr = VecRestoreArray(x,&array);CHKERRQ(ierr);
ierr = VecCopy(x,u);CHKERRQ(ierr);
ierr = MatMult(C,x,b);CHKERRQ(ierr);
ierr = MatSolve(F,b,x);CHKERRQ(ierr);
/* Check the error */
ierr = VecAXPY(u,-1.0,x);CHKERRQ(ierr); /* u <- (-1.0)x + u */
ierr = VecNorm(u,NORM_2,&norm);CHKERRQ(ierr);
if (norm > tol){
if (!rank){
ierr = PetscPrintf(PETSC_COMM_SELF,"Error: Norm of error %g, Cholesky nfact %d\n",norm,nfact);CHKERRQ(ierr);
}
}
}
}
ierr = MatDestroy(F);CHKERRQ(ierr);
/* Free data structures */
ierr = PetscRandomDestroy(rand);CHKERRQ(ierr);
ierr = ISDestroy(perm);CHKERRQ(ierr);
ierr = ISDestroy(iperm);CHKERRQ(ierr);
ierr = VecDestroy(x);CHKERRQ(ierr);
ierr = VecDestroy(b);CHKERRQ(ierr);
ierr = VecDestroy(u);CHKERRQ(ierr);
ierr = MatDestroy(C);CHKERRQ(ierr);
ierr = PetscFinalize();CHKERRQ(ierr);
return 0;
}
PetscErrorCode MatMatSolve_SuperLU_DIST(Mat A,Mat B_mpi,Mat X)
{
Mat_SuperLU_DIST *lu = (Mat_SuperLU_DIST*)A->spptr;
PetscErrorCode ierr;
PetscMPIInt size;
PetscInt M=A->rmap->N,m=A->rmap->n,nrhs;
SuperLUStat_t stat;
double berr[1];
PetscScalar *bptr;
int info; /* SuperLU_Dist info code is ALWAYS an int, even with long long indices */
PetscBool flg;
PetscFunctionBegin;
if (lu->options.Fact != FACTORED) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONG,"SuperLU_DIST options.Fact mush equal FACTORED");
ierr = PetscObjectTypeCompareAny((PetscObject)B_mpi,&flg,MATSEQDENSE,MATMPIDENSE,PETSC_NULL);CHKERRQ(ierr);
if (!flg) SETERRQ(((PetscObject)A)->comm,PETSC_ERR_ARG_WRONG,"Matrix B must be MATDENSE matrix");
ierr = PetscObjectTypeCompareAny((PetscObject)X,&flg,MATSEQDENSE,MATMPIDENSE,PETSC_NULL);CHKERRQ(ierr);
if (!flg) SETERRQ(((PetscObject)A)->comm,PETSC_ERR_ARG_WRONG,"Matrix X must be MATDENSE matrix");
ierr = MPI_Comm_size(((PetscObject)A)->comm,&size);CHKERRQ(ierr);
if (size > 1 && lu->MatInputMode == GLOBAL) SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_SUP,"MatInputMode=GLOBAL for nproc %d>1 is not supported",size);
/* size==1 or distributed mat input */
if (lu->options.SolveInitialized && !lu->matmatsolve_iscalled){
/* communication pattern of SOLVEstruct is unlikely created for matmatsolve,
thus destroy it and create a new SOLVEstruct.
Otherwise it may result in memory corruption or incorrect solution
See src/mat/examples/tests/ex125.c */
#if defined(PETSC_USE_COMPLEX)
zSolveFinalize(&lu->options, &lu->SOLVEstruct);
#else
dSolveFinalize(&lu->options, &lu->SOLVEstruct);
#endif
lu->options.SolveInitialized = NO;
}
ierr = MatCopy(B_mpi,X,SAME_NONZERO_PATTERN);CHKERRQ(ierr);
ierr = MatGetSize(B_mpi,PETSC_NULL,&nrhs);CHKERRQ(ierr);
PStatInit(&stat); /* Initialize the statistics variables. */
ierr = MatGetArray(X,&bptr);CHKERRQ(ierr);
if (lu->MatInputMode == GLOBAL) { /* size == 1 */
#if defined(PETSC_USE_COMPLEX)
pzgssvx_ABglobal(&lu->options, &lu->A_sup, &lu->ScalePermstruct,(doublecomplex*)bptr, M, nrhs,
&lu->grid, &lu->LUstruct, berr, &stat, &info);
#else
pdgssvx_ABglobal(&lu->options, &lu->A_sup, &lu->ScalePermstruct,bptr, M, nrhs,
&lu->grid, &lu->LUstruct, berr, &stat, &info);
#endif
} else { /* distributed mat input */
#if defined(PETSC_USE_COMPLEX)
pzgssvx(&lu->options,&lu->A_sup,&lu->ScalePermstruct,(doublecomplex*)bptr,m,nrhs,&lu->grid,
&lu->LUstruct,&lu->SOLVEstruct,berr,&stat,&info);
#else
pdgssvx(&lu->options,&lu->A_sup,&lu->ScalePermstruct,bptr,m,nrhs,&lu->grid,
&lu->LUstruct,&lu->SOLVEstruct,berr,&stat,&info);
#endif
}
if (info) SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_LIB,"pdgssvx fails, info: %d\n",info);
ierr = MatRestoreArray(X,&bptr);CHKERRQ(ierr);
if (lu->options.PrintStat) {
PStatPrint(&lu->options, &stat, &lu->grid); /* Print the statistics. */
}
PStatFree(&stat);
lu->matsolve_iscalled = PETSC_FALSE;
lu->matmatsolve_iscalled = PETSC_TRUE;
PetscFunctionReturn(0);
}
nrecvs = from->n;
while (nrecvs) {
ierr = MPI_Waitany(from->n,rwaits,&imdex,&status);CHKERRQ(ierr);
nrecvs--;
/* unpack a message at a time */
CHKMEMQ;
for (j=0; j<rstarts[imdex+1]-rstarts[imdex]; j++){
for (k=0; k<ncols; k++) {
w[rindices[rstarts[imdex]+j] + nrows*k] = rvalues[ncols*(rstarts[imdex] + j) + k];
}
}
CHKMEMQ;
}
if (to->n) {ierr = MPI_Waitall(to->n,swaits,to->sstatus);CHKERRQ(ierr)}
ierr = MatRestoreArray(B,&b);CHKERRQ(ierr);
ierr = MatRestoreArray(workB,&w);CHKERRQ(ierr);
ierr = MatAssemblyBegin(workB,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr);
ierr = MatAssemblyEnd(workB,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr);
PetscFunctionReturn(0);
}
extern PetscErrorCode MatMatMultNumericAdd_SeqAIJ_SeqDense(Mat,Mat,Mat);
#undef __FUNCT__
#define __FUNCT__ "MatMatMultNumeric_MPIAIJ_MPIDense"
PetscErrorCode MatMatMultNumeric_MPIAIJ_MPIDense(Mat A,Mat B,Mat C)
{
PetscErrorCode ierr;
Mat_MPIAIJ *aij = (Mat_MPIAIJ*)A->data;
Mat_MPIDense *bdense = (Mat_MPIDense*)B->data;
Mat_MPIDense *cdense = (Mat_MPIDense*)C->data;
