/* Defines projective product routines where A is a SeqAIJ matrix C = P^T * A * P */ #include <../src/mat/impls/aij/seq/aij.h> /*I "petscmat.h" I*/ #include <../src/mat/utils/freespace.h> #include #include #if defined(PETSC_HAVE_HYPRE) PETSC_INTERN PetscErrorCode MatPtAPSymbolic_AIJ_AIJ_wHYPRE(Mat, Mat, PetscReal, Mat); #endif PetscErrorCode MatProductSymbolic_PtAP_SeqAIJ_SeqAIJ(Mat C) { Mat_Product *product = C->product; Mat A = product->A, P = product->B; MatProductAlgorithm alg = product->alg; PetscReal fill = product->fill; PetscBool flg; Mat Pt; PetscFunctionBegin; /* "scalable" */ PetscCall(PetscStrcmp(alg, "scalable", &flg)); if (flg) { PetscCall(MatPtAPSymbolic_SeqAIJ_SeqAIJ_SparseAxpy(A, P, fill, C)); C->ops->productnumeric = MatProductNumeric_PtAP; PetscFunctionReturn(PETSC_SUCCESS); } /* "rap" */ PetscCall(PetscStrcmp(alg, "rap", &flg)); if (flg) { MatProductCtx_MatTransMatMult *atb; PetscCall(PetscNew(&atb)); PetscCall(MatTranspose(P, MAT_INITIAL_MATRIX, &Pt)); PetscCall(MatMatMatMultSymbolic_SeqAIJ_SeqAIJ_SeqAIJ(Pt, A, P, fill, C)); atb->At = Pt; atb->data = C->product->data; atb->destroy = C->product->destroy; C->product->data = atb; C->product->destroy = MatProductCtxDestroy_SeqAIJ_MatTransMatMult; C->ops->ptapnumeric = MatPtAPNumeric_SeqAIJ_SeqAIJ; C->ops->productnumeric = MatProductNumeric_PtAP; PetscFunctionReturn(PETSC_SUCCESS); } /* hypre */ #if defined(PETSC_HAVE_HYPRE) PetscCall(PetscStrcmp(alg, "hypre", &flg)); if (flg) { PetscCall(MatPtAPSymbolic_AIJ_AIJ_wHYPRE(A, P, fill, C)); PetscFunctionReturn(PETSC_SUCCESS); } #endif SETERRQ(PETSC_COMM_SELF, PETSC_ERR_SUP, "MatProductType is not supported"); } PetscErrorCode MatPtAPSymbolic_SeqAIJ_SeqAIJ_SparseAxpy(Mat A, Mat P, PetscReal fill, Mat C) { PetscFreeSpaceList free_space = NULL, current_space = NULL; Mat_SeqAIJ *a = (Mat_SeqAIJ *)A->data, *p = (Mat_SeqAIJ *)P->data, *c; PetscInt *pti, *ptj, *ptJ, *ai = a->i, *aj = a->j, *ajj, *pi = p->i, *pj = p->j, *pjj; PetscInt *ci, *cj, *ptadenserow, *ptasparserow, *ptaj, nspacedouble = 0; PetscInt an = A->cmap->N, am = A->rmap->N, pn = P->cmap->N, pm = P->rmap->N; PetscInt i, j, k, ptnzi, arow, anzj, ptanzi, prow, pnzj, cnzi, nlnk, *lnk; MatScalar *ca; PetscBT lnkbt; PetscReal afill; PetscFunctionBegin; /* Get ij structure of P^T */ PetscCall(MatGetSymbolicTranspose_SeqAIJ(P, &pti, &ptj)); ptJ = ptj; /* Allocate ci array, arrays for fill computation and */ /* free space for accumulating nonzero column info */ PetscCall(PetscMalloc1(pn + 1, &ci)); ci[0] = 0; PetscCall(PetscCalloc1(2 * an + 1, &ptadenserow)); ptasparserow = ptadenserow + an; /* create and initialize a linked list */ nlnk = pn + 1; PetscCall(PetscLLCreate(pn, pn, nlnk, lnk, lnkbt)); /* Set initial free space to be fill*(nnz(A)+ nnz(P)) */ PetscCall(PetscFreeSpaceGet(PetscRealIntMultTruncate(fill, PetscIntSumTruncate(ai[am], pi[pm])), &free_space)); current_space = free_space; /* Determine symbolic info for each row of C: */ for (i = 0; i < pn; i++) { ptnzi = pti[i + 1] - pti[i]; ptanzi = 0; /* Determine symbolic row of PtA: */ for (j = 0; j < ptnzi; j++) { arow = *ptJ++; anzj = ai[arow + 1] - ai[arow]; ajj = aj + ai[arow]; for (k = 0; k < anzj; k++) { if (!ptadenserow[ajj[k]]) { ptadenserow[ajj[k]] = -1; ptasparserow[ptanzi++] = ajj[k]; } } } /* Using symbolic info for row of PtA, determine symbolic info for row of C: */ ptaj = ptasparserow; cnzi = 0; for (j = 0; j < ptanzi; j++) { prow = *ptaj++; pnzj = pi[prow + 1] - pi[prow]; pjj = pj + pi[prow]; /* add non-zero cols of P into the sorted linked list lnk */ PetscCall(PetscLLAddSorted(pnzj, pjj, pn, &nlnk, lnk, lnkbt)); cnzi += nlnk; } /* If free space is not available, make more free space */ /* Double the amount of total space in the list */ if (current_space->local_remaining < cnzi) { PetscCall(PetscFreeSpaceGet(PetscIntSumTruncate(cnzi, current_space->total_array_size), ¤t_space)); nspacedouble++; } /* Copy data into free space, and zero out denserows */ PetscCall(PetscLLClean(pn, pn, cnzi, lnk, current_space->array, lnkbt)); current_space->array += cnzi; current_space->local_used += cnzi; current_space->local_remaining -= cnzi; for (j = 0; j < ptanzi; j++) ptadenserow[ptasparserow[j]] = 0; /* Aside: Perhaps we should save the pta info for the numerical factorization. */ /* For now, we will recompute what is needed. */ ci[i + 1] = ci[i] + cnzi; } /* nnz is now stored in ci[ptm], column indices are in the list of free space */ /* Allocate space for cj, initialize cj, and */ /* destroy list of free space and other temporary array(s) */ PetscCall(PetscMalloc1(ci[pn], &cj)); PetscCall(PetscFreeSpaceContiguous(&free_space, cj)); PetscCall(PetscFree(ptadenserow)); PetscCall(PetscLLDestroy(lnk, lnkbt)); PetscCall(PetscCalloc1(ci[pn], &ca)); /* put together the new matrix */ PetscCall(MatSetSeqAIJWithArrays_private(PetscObjectComm((PetscObject)A), pn, pn, ci, cj, ca, ((PetscObject)A)->type_name, C)); PetscCall(MatSetBlockSizes(C, P->cmap->bs, P->cmap->bs)); /* MatCreateSeqAIJWithArrays flags matrix so PETSc doesn't free the user's arrays. */ /* Since these are PETSc arrays, change flags to free them as necessary. */ c = (Mat_SeqAIJ *)((C)->data); c->free_a = PETSC_TRUE; c->free_ij = PETSC_TRUE; c->nonew = 0; C->ops->ptapnumeric = MatPtAPNumeric_SeqAIJ_SeqAIJ_SparseAxpy; /* set MatInfo */ afill = (PetscReal)ci[pn] / (ai[am] + pi[pm] + 1.e-5); if (afill < 1.0) afill = 1.0; C->info.mallocs = nspacedouble; C->info.fill_ratio_given = fill; C->info.fill_ratio_needed = afill; /* Clean up. */ PetscCall(MatRestoreSymbolicTranspose_SeqAIJ(P, &pti, &ptj)); #if defined(PETSC_USE_INFO) if (ci[pn] != 0) { PetscCall(PetscInfo(C, "Reallocs %" PetscInt_FMT "; Fill ratio: given %g needed %g.\n", nspacedouble, (double)fill, (double)afill)); PetscCall(PetscInfo(C, "Use MatPtAP(A,P,MatReuse,%g,&C) for best performance.\n", (double)afill)); } else { PetscCall(PetscInfo(C, "Empty matrix product\n")); } #endif PetscFunctionReturn(PETSC_SUCCESS); } PetscErrorCode MatPtAPNumeric_SeqAIJ_SeqAIJ_SparseAxpy(Mat A, Mat P, Mat C) { Mat_SeqAIJ *a = (Mat_SeqAIJ *)A->data; Mat_SeqAIJ *p = (Mat_SeqAIJ *)P->data; Mat_SeqAIJ *c = (Mat_SeqAIJ *)C->data; PetscInt *ai = a->i, *aj = a->j, *apj, *apjdense, *pi = p->i, *pj = p->j, *pJ = p->j, *pjj; PetscInt *ci = c->i, *cj = c->j, *cjj; PetscInt am = A->rmap->N, cn = C->cmap->N, cm = C->rmap->N; PetscInt i, j, k, anzi, pnzi, apnzj, nextap, pnzj, prow, crow; MatScalar *aa, *apa, *pa, *pA, *paj, *ca, *caj; PetscFunctionBegin; /* Allocate temporary array for storage of one row of A*P (cn: non-scalable) */ PetscCall(PetscCalloc2(cn, &apa, cn, &apjdense)); PetscCall(PetscMalloc1(cn, &apj)); /* trigger CPU copies if needed and flag CPU mask for C */ #if defined(PETSC_HAVE_DEVICE) { const PetscScalar *unused; PetscCall(MatSeqAIJGetArrayRead(A, &unused)); PetscCall(MatSeqAIJRestoreArrayRead(A, &unused)); PetscCall(MatSeqAIJGetArrayRead(P, &unused)); PetscCall(MatSeqAIJRestoreArrayRead(P, &unused)); if (C->offloadmask != PETSC_OFFLOAD_UNALLOCATED) C->offloadmask = PETSC_OFFLOAD_CPU; } #endif aa = a->a; pa = p->a; pA = p->a; ca = c->a; /* Clear old values in C */ PetscCall(PetscArrayzero(ca, ci[cm])); for (i = 0; i < am; i++) { /* Form sparse row of A*P */ anzi = ai[i + 1] - ai[i]; apnzj = 0; for (j = 0; j < anzi; j++) { prow = *aj++; pnzj = pi[prow + 1] - pi[prow]; pjj = pj + pi[prow]; paj = pa + pi[prow]; for (k = 0; k < pnzj; k++) { if (!apjdense[pjj[k]]) { apjdense[pjj[k]] = -1; apj[apnzj++] = pjj[k]; } apa[pjj[k]] += (*aa) * paj[k]; } PetscCall(PetscLogFlops(2.0 * pnzj)); aa++; } /* Sort the j index array for quick sparse axpy. */ /* Note: a array does not need sorting as it is in dense storage locations. */ PetscCall(PetscSortInt(apnzj, apj)); /* Compute P^T*A*P using outer product (P^T)[:,j]*(A*P)[j,:]. */ pnzi = pi[i + 1] - pi[i]; for (j = 0; j < pnzi; j++) { nextap = 0; crow = *pJ++; cjj = cj + ci[crow]; caj = ca + ci[crow]; /* Perform sparse axpy operation. Note cjj includes apj. */ for (k = 0; nextap < apnzj; k++) { PetscAssert(k < ci[crow + 1] - ci[crow], PETSC_COMM_SELF, PETSC_ERR_PLIB, "k too large k %" PetscInt_FMT ", crow %" PetscInt_FMT, k, crow); if (cjj[k] == apj[nextap]) caj[k] += (*pA) * apa[apj[nextap++]]; } PetscCall(PetscLogFlops(2.0 * apnzj)); pA++; } /* Zero the current row info for A*P */ for (j = 0; j < apnzj; j++) { apa[apj[j]] = 0.; apjdense[apj[j]] = 0; } } /* Assemble the final matrix and clean up */ PetscCall(MatAssemblyBegin(C, MAT_FINAL_ASSEMBLY)); PetscCall(MatAssemblyEnd(C, MAT_FINAL_ASSEMBLY)); PetscCall(PetscFree2(apa, apjdense)); PetscCall(PetscFree(apj)); PetscFunctionReturn(PETSC_SUCCESS); } PetscErrorCode MatPtAPNumeric_SeqAIJ_SeqAIJ(Mat A, Mat P, Mat C) { MatProductCtx_MatTransMatMult *atb; PetscFunctionBegin; MatCheckProduct(C, 3); atb = (MatProductCtx_MatTransMatMult *)C->product->data; PetscCheck(atb, PetscObjectComm((PetscObject)C), PETSC_ERR_PLIB, "Missing data structure"); PetscCall(MatTranspose(P, MAT_REUSE_MATRIX, &atb->At)); PetscCheck(C->ops->matmultnumeric, PetscObjectComm((PetscObject)C), PETSC_ERR_PLIB, "Missing numeric operation"); /* when using rap, MatMatMatMultSymbolic used a different data */ if (atb->data) C->product->data = atb->data; PetscCall((*C->ops->matmatmultnumeric)(atb->At, A, P, C)); C->product->data = atb; PetscFunctionReturn(PETSC_SUCCESS); }