#include <../src/mat/impls/htool/htool.hpp> /*I "petscmat.h" I*/ #include #include const char *const MatHtoolCompressorTypes[] = { "sympartialACA", "fullACA", "SVD" }; const char *const MatHtoolClusteringTypes[] = { "PCARegular", "PCAGeometric", "BoundingBox1Regular", "BoundingBox1Geometric" }; const char HtoolCitation[] = "@article{marchand2020two,\n" " Author = {Marchand, Pierre and Claeys, Xavier and Jolivet, Pierre and Nataf, Fr\\'ed\\'eric and Tournier, Pierre-Henri},\n" " Title = {Two-level preconditioning for $h$-version boundary element approximation of hypersingular operator with {GenEO}},\n" " Year = {2020},\n" " Publisher = {Elsevier},\n" " Journal = {Numerische Mathematik},\n" " Volume = {146},\n" " Pages = {597--628},\n" " Url = {https://github.com/htool-ddm/htool}\n" "}\n"; static PetscBool HtoolCite = PETSC_FALSE; static PetscErrorCode MatGetDiagonal_Htool(Mat A,Vec v) { Mat_Htool *a = (Mat_Htool*)A->data; PetscScalar *x; PetscBool flg; PetscFunctionBegin; PetscCall(MatHasCongruentLayouts(A,&flg)); PetscCheck(flg,PetscObjectComm((PetscObject)A),PETSC_ERR_SUP,"Only congruent layouts supported"); PetscCall(VecGetArrayWrite(v,&x)); a->hmatrix->copy_local_diagonal(x); PetscCall(VecRestoreArrayWrite(v,&x)); PetscCall(VecScale(v,a->s)); PetscFunctionReturn(0); } static PetscErrorCode MatGetDiagonalBlock_Htool(Mat A,Mat *b) { Mat_Htool *a = (Mat_Htool*)A->data; Mat B; PetscScalar *ptr; PetscBool flg; PetscFunctionBegin; PetscCall(MatHasCongruentLayouts(A,&flg)); PetscCheck(flg,PetscObjectComm((PetscObject)A),PETSC_ERR_SUP,"Only congruent layouts supported"); PetscCall(PetscObjectQuery((PetscObject)A,"DiagonalBlock",(PetscObject*)&B)); /* same logic as in MatGetDiagonalBlock_MPIDense() */ if (!B) { PetscCall(MatCreateDense(PETSC_COMM_SELF,A->rmap->n,A->rmap->n,A->rmap->n,A->rmap->n,NULL,&B)); PetscCall(MatDenseGetArrayWrite(B,&ptr)); a->hmatrix->copy_local_diagonal_block(ptr); PetscCall(MatDenseRestoreArrayWrite(B,&ptr)); PetscCall(MatPropagateSymmetryOptions(A,B)); PetscCall(MatScale(B,a->s)); PetscCall(PetscObjectCompose((PetscObject)A,"DiagonalBlock",(PetscObject)B)); *b = B; PetscCall(MatDestroy(&B)); } else *b = B; PetscFunctionReturn(0); } static PetscErrorCode MatMult_Htool(Mat A,Vec x,Vec y) { Mat_Htool *a = (Mat_Htool*)A->data; const PetscScalar *in; PetscScalar *out; PetscFunctionBegin; PetscCall(VecGetArrayRead(x,&in)); PetscCall(VecGetArrayWrite(y,&out)); a->hmatrix->mvprod_local_to_local(in,out); PetscCall(VecRestoreArrayRead(x,&in)); PetscCall(VecRestoreArrayWrite(y,&out)); PetscCall(VecScale(y,a->s)); PetscFunctionReturn(0); } /* naive implementation of MatMultAdd() needed for FEM-BEM coupling via MATNEST */ static PetscErrorCode MatMultAdd_Htool(Mat A,Vec v1,Vec v2,Vec v3) { Mat_Htool *a = (Mat_Htool*)A->data; Vec tmp; const PetscScalar scale = a->s; PetscFunctionBegin; PetscCall(VecDuplicate(v2,&tmp)); PetscCall(VecCopy(v2,v3)); /* no-op in MatMultAdd(bA->m[i][j],bx[j],by[i],by[i]) since VecCopy() checks for x == y */ a->s = 1.0; /* set s to 1.0 since VecAXPY() may be used to scale the MatMult() output Vec */ PetscCall(MatMult_Htool(A,v1,tmp)); PetscCall(VecAXPY(v3,scale,tmp)); PetscCall(VecDestroy(&tmp)); a->s = scale; /* set s back to its original value */ PetscFunctionReturn(0); } static PetscErrorCode MatMultTranspose_Htool(Mat A,Vec x,Vec y) { Mat_Htool *a = (Mat_Htool*)A->data; const PetscScalar *in; PetscScalar *out; PetscFunctionBegin; PetscCall(VecGetArrayRead(x,&in)); PetscCall(VecGetArrayWrite(y,&out)); a->hmatrix->mvprod_transp_local_to_local(in,out); PetscCall(VecRestoreArrayRead(x,&in)); PetscCall(VecRestoreArrayWrite(y,&out)); PetscCall(VecScale(y,a->s)); PetscFunctionReturn(0); } static PetscErrorCode MatIncreaseOverlap_Htool(Mat A,PetscInt is_max,IS is[],PetscInt ov) { std::set set; const PetscInt *idx; PetscInt *oidx,size,bs[2]; PetscMPIInt csize; PetscFunctionBegin; PetscCall(MatGetBlockSizes(A,bs,bs+1)); if (bs[0] != bs[1]) bs[0] = 1; for (PetscInt i=0; i= 0) set.insert(idx[j] - k); /* do not insert negative indices */ if (idx[j] + k < A->rmap->N && idx[j] + k < A->cmap->N) set.insert(idx[j] + k); /* do not insert indices greater than the dimension of A */ } } PetscCall(ISRestoreIndices(is[i],&idx)); PetscCall(ISDestroy(is+i)); if (bs[0] > 1) { for (std::set::iterator it=set.cbegin(); it!=set.cend(); it++) { std::vector block(bs[0]); std::iota(block.begin(),block.end(),(*it/bs[0])*bs[0]); set.insert(block.cbegin(),block.cend()); } } size = set.size(); /* size with overlap */ PetscCall(PetscMalloc1(size,&oidx)); for (const PetscInt j : set) *oidx++ = j; oidx -= size; PetscCall(ISCreateGeneral(PETSC_COMM_SELF,size,oidx,PETSC_OWN_POINTER,is+i)); } PetscFunctionReturn(0); } static PetscErrorCode MatCreateSubMatrices_Htool(Mat A,PetscInt n,const IS irow[],const IS icol[],MatReuse scall,Mat *submat[]) { Mat_Htool *a = (Mat_Htool*)A->data; Mat D,B,BT; const PetscScalar *copy; PetscScalar *ptr; const PetscInt *idxr,*idxc,*it; PetscInt nrow,m,i; PetscBool flg; PetscFunctionBegin; if (scall != MAT_REUSE_MATRIX) { PetscCall(PetscCalloc1(n,submat)); } for (i=0; irmap->rstart); if (it != idxr+nrow && *it == A->rmap->rstart) { /* rmap->rstart in IS? */ if (std::distance(idxr,it) + A->rmap->n <= nrow) { /* long enough IS to store the local diagonal block? */ for (PetscInt j=0; jrmap->n && flg; ++j) if (PetscUnlikely(it[j] != A->rmap->rstart+j)) flg = PETSC_FALSE; if (flg) { /* complete local diagonal block in IS? */ /* fast extraction when the local diagonal block is part of the submatrix, e.g., for PCASM or PCHPDDM * [ B C E ] * A = [ B D E ] * [ B F E ] */ m = std::distance(idxr,it); /* shift of the coefficient (0,0) of block D from above */ PetscCall(MatGetDiagonalBlock_Htool(A,&D)); PetscCall(MatDenseGetArrayRead(D,©)); for (PetscInt k=0; krmap->n; ++k) { PetscCall(PetscArraycpy(ptr+(m+k)*nrow+m,copy+k*A->rmap->n,A->rmap->n)); /* block D from above */ } PetscCall(MatDenseRestoreArrayRead(D,©)); if (m) { a->wrapper->copy_submatrix(nrow,m,idxr,idxc,ptr); /* vertical block B from above */ /* entry-wise assembly may be costly, so transpose already-computed entries when possible */ if (A->symmetric == PETSC_BOOL3_TRUE || A->hermitian == PETSC_BOOL3_TRUE) { PetscCall(MatCreateDense(PETSC_COMM_SELF,A->rmap->n,m,A->rmap->n,m,ptr+m,&B)); PetscCall(MatDenseSetLDA(B,nrow)); PetscCall(MatCreateDense(PETSC_COMM_SELF,m,A->rmap->n,m,A->rmap->n,ptr+m*nrow,&BT)); PetscCall(MatDenseSetLDA(BT,nrow)); if (A->hermitian == PETSC_BOOL3_TRUE && PetscDefined(USE_COMPLEX)) { PetscCall(MatHermitianTranspose(B,MAT_REUSE_MATRIX,&BT)); } else { PetscCall(MatTranspose(B,MAT_REUSE_MATRIX,&BT)); } PetscCall(MatDestroy(&B)); PetscCall(MatDestroy(&BT)); } else { for (PetscInt k=0; krmap->n; ++k) { /* block C from above */ a->wrapper->copy_submatrix(m,1,idxr,idxc+m+k,ptr+(m+k)*nrow); } } } if (m+A->rmap->n != nrow) { a->wrapper->copy_submatrix(nrow,std::distance(it+A->rmap->n,idxr+nrow),idxr,idxc+m+A->rmap->n,ptr+(m+A->rmap->n)*nrow); /* vertical block E from above */ /* entry-wise assembly may be costly, so transpose already-computed entries when possible */ if (A->symmetric == PETSC_BOOL3_TRUE || A->hermitian == PETSC_BOOL3_TRUE) { PetscCall(MatCreateDense(PETSC_COMM_SELF,A->rmap->n,nrow-(m+A->rmap->n),A->rmap->n,nrow-(m+A->rmap->n),ptr+(m+A->rmap->n)*nrow+m,&B)); PetscCall(MatDenseSetLDA(B,nrow)); PetscCall(MatCreateDense(PETSC_COMM_SELF,nrow-(m+A->rmap->n),A->rmap->n,nrow-(m+A->rmap->n),A->rmap->n,ptr+m*nrow+m+A->rmap->n,&BT)); PetscCall(MatDenseSetLDA(BT,nrow)); if (A->hermitian == PETSC_BOOL3_TRUE && PetscDefined(USE_COMPLEX)) { PetscCall(MatHermitianTranspose(B,MAT_REUSE_MATRIX,&BT)); } else { PetscCall(MatTranspose(B,MAT_REUSE_MATRIX,&BT)); } PetscCall(MatDestroy(&B)); PetscCall(MatDestroy(&BT)); } else { for (PetscInt k=0; krmap->n; ++k) { /* block F from above */ a->wrapper->copy_submatrix(std::distance(it+A->rmap->n,idxr+nrow),1,it+A->rmap->n,idxc+m+k,ptr+(m+k)*nrow+m+A->rmap->n); } } } } /* complete local diagonal block not in IS */ } else flg = PETSC_FALSE; /* IS not long enough to store the local diagonal block */ } else flg = PETSC_FALSE; /* rmap->rstart not in IS */ } /* unsorted IS */ } } else flg = PETSC_FALSE; /* different row and column IS */ if (!flg) a->wrapper->copy_submatrix(nrow,m,idxr,idxc,ptr); /* reassemble everything */ PetscCall(ISRestoreIndices(irow[i],&idxr)); PetscCall(ISRestoreIndices(icol[i],&idxc)); PetscCall(MatDenseRestoreArrayWrite((*submat)[i],&ptr)); PetscCall(MatScale((*submat)[i],a->s)); } PetscFunctionReturn(0); } static PetscErrorCode MatDestroy_Htool(Mat A) { Mat_Htool *a = (Mat_Htool*)A->data; PetscContainer container; MatHtoolKernelTranspose *kernelt; PetscFunctionBegin; PetscCall(PetscObjectChangeTypeName((PetscObject)A,NULL)); PetscCall(PetscObjectComposeFunction((PetscObject)A,"MatProductSetFromOptions_htool_seqdense_C",NULL)); PetscCall(PetscObjectComposeFunction((PetscObject)A,"MatProductSetFromOptions_htool_mpidense_C",NULL)); PetscCall(PetscObjectComposeFunction((PetscObject)A,"MatConvert_htool_seqdense_C",NULL)); PetscCall(PetscObjectComposeFunction((PetscObject)A,"MatConvert_htool_mpidense_C",NULL)); PetscCall(PetscObjectComposeFunction((PetscObject)A,"MatHtoolGetHierarchicalMat_C",NULL)); PetscCall(PetscObjectComposeFunction((PetscObject)A,"MatHtoolSetKernel_C",NULL)); PetscCall(PetscObjectComposeFunction((PetscObject)A,"MatHtoolGetPermutationSource_C",NULL)); PetscCall(PetscObjectComposeFunction((PetscObject)A,"MatHtoolGetPermutationTarget_C",NULL)); PetscCall(PetscObjectComposeFunction((PetscObject)A,"MatHtoolUsePermutation_C",NULL)); PetscCall(PetscObjectQuery((PetscObject)A,"KernelTranspose",(PetscObject*)&container)); if (container) { /* created in MatTranspose_Htool() */ PetscCall(PetscContainerGetPointer(container,(void**)&kernelt)); PetscCall(MatDestroy(&kernelt->A)); PetscCall(PetscFree(kernelt)); PetscCall(PetscContainerDestroy(&container)); PetscCall(PetscObjectCompose((PetscObject)A,"KernelTranspose",NULL)); } if (a->gcoords_source != a->gcoords_target) { PetscCall(PetscFree(a->gcoords_source)); } PetscCall(PetscFree(a->gcoords_target)); PetscCall(PetscFree2(a->work_source,a->work_target)); delete a->wrapper; delete a->hmatrix; PetscCall(PetscFree(A->data)); PetscFunctionReturn(0); } static PetscErrorCode MatView_Htool(Mat A,PetscViewer pv) { Mat_Htool *a = (Mat_Htool*)A->data; PetscBool flg; PetscFunctionBegin; PetscCall(PetscObjectTypeCompare((PetscObject)pv,PETSCVIEWERASCII,&flg)); if (flg) { PetscCall(PetscViewerASCIIPrintf(pv,"symmetry: %c\n",a->hmatrix->get_symmetry_type())); if (PetscAbsScalar(a->s-1.0) > PETSC_MACHINE_EPSILON) { #if defined(PETSC_USE_COMPLEX) PetscCall(PetscViewerASCIIPrintf(pv,"scaling: %g+%gi\n",(double)PetscRealPart(a->s),(double)PetscImaginaryPart(a->s))); #else PetscCall(PetscViewerASCIIPrintf(pv,"scaling: %g\n",(double)a->s)); #endif } PetscCall(PetscViewerASCIIPrintf(pv,"minimum cluster size: %" PetscInt_FMT "\n",a->bs[0])); PetscCall(PetscViewerASCIIPrintf(pv,"maximum block size: %" PetscInt_FMT "\n",a->bs[1])); PetscCall(PetscViewerASCIIPrintf(pv,"epsilon: %g\n",(double)a->epsilon)); PetscCall(PetscViewerASCIIPrintf(pv,"eta: %g\n",(double)a->eta)); PetscCall(PetscViewerASCIIPrintf(pv,"minimum target depth: %" PetscInt_FMT "\n",a->depth[0])); PetscCall(PetscViewerASCIIPrintf(pv,"minimum source depth: %" PetscInt_FMT "\n",a->depth[1])); PetscCall(PetscViewerASCIIPrintf(pv,"compressor: %s\n",MatHtoolCompressorTypes[a->compressor])); PetscCall(PetscViewerASCIIPrintf(pv,"clustering: %s\n",MatHtoolClusteringTypes[a->clustering])); PetscCall(PetscViewerASCIIPrintf(pv,"compression ratio: %s\n",a->hmatrix->get_infos("Compression_ratio").c_str())); PetscCall(PetscViewerASCIIPrintf(pv,"space saving: %s\n",a->hmatrix->get_infos("Space_saving").c_str())); PetscCall(PetscViewerASCIIPrintf(pv,"number of dense (resp. low rank) matrices: %s (resp. %s)\n",a->hmatrix->get_infos("Number_of_dmat").c_str(),a->hmatrix->get_infos("Number_of_lrmat").c_str())); PetscCall(PetscViewerASCIIPrintf(pv,"(minimum, mean, maximum) dense block sizes: (%s, %s, %s)\n",a->hmatrix->get_infos("Dense_block_size_min").c_str(),a->hmatrix->get_infos("Dense_block_size_mean").c_str(),a->hmatrix->get_infos("Dense_block_size_max").c_str())); PetscCall(PetscViewerASCIIPrintf(pv,"(minimum, mean, maximum) low rank block sizes: (%s, %s, %s)\n",a->hmatrix->get_infos("Low_rank_block_size_min").c_str(),a->hmatrix->get_infos("Low_rank_block_size_mean").c_str(),a->hmatrix->get_infos("Low_rank_block_size_max").c_str())); PetscCall(PetscViewerASCIIPrintf(pv,"(minimum, mean, maximum) ranks: (%s, %s, %s)\n",a->hmatrix->get_infos("Rank_min").c_str(),a->hmatrix->get_infos("Rank_mean").c_str(),a->hmatrix->get_infos("Rank_max").c_str())); } PetscFunctionReturn(0); } static PetscErrorCode MatScale_Htool(Mat A,PetscScalar s) { Mat_Htool *a = (Mat_Htool*)A->data; PetscFunctionBegin; a->s *= s; PetscFunctionReturn(0); } /* naive implementation of MatGetRow() needed for MatConvert_Nest_AIJ() */ static PetscErrorCode MatGetRow_Htool(Mat A,PetscInt row,PetscInt *nz,PetscInt **idx,PetscScalar **v) { Mat_Htool *a = (Mat_Htool*)A->data; PetscInt *idxc; PetscBLASInt one = 1,bn; PetscFunctionBegin; if (nz) *nz = A->cmap->N; if (idx || v) { /* even if !idx, need to set idxc for htool::copy_submatrix() */ PetscCall(PetscMalloc1(A->cmap->N,&idxc)); for (PetscInt i=0; icmap->N; ++i) idxc[i] = i; } if (idx) *idx = idxc; if (v) { PetscCall(PetscMalloc1(A->cmap->N,v)); if (a->wrapper) a->wrapper->copy_submatrix(1,A->cmap->N,&row,idxc,*v); else reinterpret_cast*>(a->kernelctx)->copy_submatrix(1,A->cmap->N,&row,idxc,*v); PetscCall(PetscBLASIntCast(A->cmap->N,&bn)); PetscStackCallBLAS("BLASscal",BLASscal_(&bn,&a->s,*v,&one)); } if (!idx) { PetscCall(PetscFree(idxc)); } PetscFunctionReturn(0); } static PetscErrorCode MatRestoreRow_Htool(Mat A,PetscInt row,PetscInt *nz,PetscInt **idx,PetscScalar **v) { PetscFunctionBegin; if (nz) *nz = 0; if (idx) { PetscCall(PetscFree(*idx)); } if (v) { PetscCall(PetscFree(*v)); } PetscFunctionReturn(0); } static PetscErrorCode MatSetFromOptions_Htool(PetscOptionItems *PetscOptionsObject,Mat A) { Mat_Htool *a = (Mat_Htool*)A->data; PetscInt n; PetscBool flg; PetscFunctionBegin; PetscOptionsHeadBegin(PetscOptionsObject,"Htool options"); PetscCall(PetscOptionsInt("-mat_htool_min_cluster_size","Minimal leaf size in cluster tree",NULL,a->bs[0],a->bs,NULL)); PetscCall(PetscOptionsInt("-mat_htool_max_block_size","Maximal number of coefficients in a dense block",NULL,a->bs[1],a->bs + 1,NULL)); PetscCall(PetscOptionsReal("-mat_htool_epsilon","Relative error in Frobenius norm when approximating a block",NULL,a->epsilon,&a->epsilon,NULL)); PetscCall(PetscOptionsReal("-mat_htool_eta","Admissibility condition tolerance",NULL,a->eta,&a->eta,NULL)); PetscCall(PetscOptionsInt("-mat_htool_min_target_depth","Minimal cluster tree depth associated with the rows",NULL,a->depth[0],a->depth,NULL)); PetscCall(PetscOptionsInt("-mat_htool_min_source_depth","Minimal cluster tree depth associated with the columns",NULL,a->depth[1],a->depth + 1,NULL)); n = 0; PetscCall(PetscOptionsEList("-mat_htool_compressor","Type of compression","MatHtoolCompressorType",MatHtoolCompressorTypes,PETSC_STATIC_ARRAY_LENGTH(MatHtoolCompressorTypes),MatHtoolCompressorTypes[MAT_HTOOL_COMPRESSOR_SYMPARTIAL_ACA],&n,&flg)); if (flg) a->compressor = MatHtoolCompressorType(n); n = 0; PetscCall(PetscOptionsEList("-mat_htool_clustering","Type of clustering","MatHtoolClusteringType",MatHtoolClusteringTypes,PETSC_STATIC_ARRAY_LENGTH(MatHtoolClusteringTypes),MatHtoolClusteringTypes[MAT_HTOOL_CLUSTERING_PCA_REGULAR],&n,&flg)); if (flg) a->clustering = MatHtoolClusteringType(n); PetscOptionsHeadEnd(); PetscFunctionReturn(0); } static PetscErrorCode MatAssemblyEnd_Htool(Mat A,MatAssemblyType type) { Mat_Htool *a = (Mat_Htool*)A->data; const PetscInt *ranges; PetscInt *offset; PetscMPIInt size; char S = PetscDefined(USE_COMPLEX) && A->hermitian == PETSC_BOOL3_TRUE ? 'H' : (A->symmetric == PETSC_BOOL3_TRUE ? 'S' : 'N'),uplo = S == 'N' ? 'N' : 'U'; htool::VirtualGenerator *generator = nullptr; std::shared_ptr t,s = nullptr; std::shared_ptr> compressor = nullptr; PetscFunctionBegin; PetscCall(PetscCitationsRegister(HtoolCitation,&HtoolCite)); delete a->wrapper; delete a->hmatrix; PetscCallMPI(MPI_Comm_size(PetscObjectComm((PetscObject)A),&size)); PetscCall(PetscMalloc1(2*size,&offset)); PetscCall(MatGetOwnershipRanges(A,&ranges)); for (PetscInt i=0; iclustering) { case MAT_HTOOL_CLUSTERING_PCA_GEOMETRIC: t = std::make_shared>>(a->dim); break; case MAT_HTOOL_CLUSTERING_BOUNDING_BOX_1_GEOMETRIC: t = std::make_shared>>(a->dim); break; case MAT_HTOOL_CLUSTERING_BOUNDING_BOX_1_REGULAR: t = std::make_shared>>(a->dim); break; default: t = std::make_shared>>(a->dim); } t->set_minclustersize(a->bs[0]); t->build(A->rmap->N,a->gcoords_target,offset); if (a->kernel) a->wrapper = new WrapperHtool(A->rmap->N,A->cmap->N,a->dim,a->kernel,a->kernelctx); else { a->wrapper = NULL; generator = reinterpret_cast*>(a->kernelctx); } if (a->gcoords_target != a->gcoords_source) { PetscCall(MatGetOwnershipRangesColumn(A,&ranges)); for (PetscInt i=0; iclustering) { case MAT_HTOOL_CLUSTERING_PCA_GEOMETRIC: s = std::make_shared>>(a->dim); break; case MAT_HTOOL_CLUSTERING_BOUNDING_BOX_1_GEOMETRIC: s = std::make_shared>>(a->dim); break; case MAT_HTOOL_CLUSTERING_BOUNDING_BOX_1_REGULAR: s = std::make_shared>>(a->dim); break; default: s = std::make_shared>>(a->dim); } s->set_minclustersize(a->bs[0]); s->build(A->cmap->N,a->gcoords_source,offset); S = uplo = 'N'; } PetscCall(PetscFree(offset)); switch (a->compressor) { case MAT_HTOOL_COMPRESSOR_FULL_ACA: compressor = std::make_shared>(); break; case MAT_HTOOL_COMPRESSOR_SVD: compressor = std::make_shared>(); break; default: compressor = std::make_shared>(); } a->hmatrix = dynamic_cast*>(new htool::HMatrix(t,s ? s : t,a->epsilon,a->eta,S,uplo)); a->hmatrix->set_compression(compressor); a->hmatrix->set_maxblocksize(a->bs[1]); a->hmatrix->set_mintargetdepth(a->depth[0]); a->hmatrix->set_minsourcedepth(a->depth[1]); if (s) a->hmatrix->build(a->wrapper ? *a->wrapper : *generator,a->gcoords_target,a->gcoords_source); else a->hmatrix->build(a->wrapper ? *a->wrapper : *generator,a->gcoords_target); PetscFunctionReturn(0); } static PetscErrorCode MatProductNumeric_Htool(Mat C) { Mat_Product *product = C->product; Mat_Htool *a = (Mat_Htool*)product->A->data; const PetscScalar *in; PetscScalar *out; PetscInt N,lda; PetscFunctionBegin; MatCheckProduct(C,1); PetscCall(MatGetSize(C,NULL,&N)); PetscCall(MatDenseGetLDA(C,&lda)); PetscCheck(lda == C->rmap->n,PETSC_COMM_SELF,PETSC_ERR_SUP,"Unsupported leading dimension (%" PetscInt_FMT " != %" PetscInt_FMT ")",lda,C->rmap->n); PetscCall(MatDenseGetArrayRead(product->B,&in)); PetscCall(MatDenseGetArrayWrite(C,&out)); switch (product->type) { case MATPRODUCT_AB: a->hmatrix->mvprod_local_to_local(in,out,N); break; case MATPRODUCT_AtB: a->hmatrix->mvprod_transp_local_to_local(in,out,N); break; default: SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"MatProductType %s is not supported",MatProductTypes[product->type]); } PetscCall(MatDenseRestoreArrayWrite(C,&out)); PetscCall(MatDenseRestoreArrayRead(product->B,&in)); PetscCall(MatScale(C,a->s)); PetscFunctionReturn(0); } static PetscErrorCode MatProductSymbolic_Htool(Mat C) { Mat_Product *product = C->product; Mat A,B; PetscBool flg; PetscFunctionBegin; MatCheckProduct(C,1); A = product->A; B = product->B; PetscCall(PetscObjectTypeCompareAny((PetscObject)B,&flg,MATSEQDENSE,MATMPIDENSE,"")); PetscCheck(flg,PetscObjectComm((PetscObject)B),PETSC_ERR_SUP,"MatProduct_AB not supported for %s",((PetscObject)product->B)->type_name); switch (product->type) { case MATPRODUCT_AB: if (C->rmap->n == PETSC_DECIDE || C->cmap->n == PETSC_DECIDE || C->rmap->N == PETSC_DECIDE || C->cmap->N == PETSC_DECIDE) { PetscCall(MatSetSizes(C,A->rmap->n,B->cmap->n,A->rmap->N,B->cmap->N)); } break; case MATPRODUCT_AtB: if (C->rmap->n == PETSC_DECIDE || C->cmap->n == PETSC_DECIDE || C->rmap->N == PETSC_DECIDE || C->cmap->N == PETSC_DECIDE) { PetscCall(MatSetSizes(C,A->cmap->n,B->cmap->n,A->cmap->N,B->cmap->N)); } break; default: SETERRQ(PetscObjectComm((PetscObject)B),PETSC_ERR_SUP,"ProductType %s is not supported",MatProductTypes[product->type]); } PetscCall(MatSetType(C,MATDENSE)); PetscCall(MatSetUp(C)); PetscCall(MatSetOption(C,MAT_NO_OFF_PROC_ENTRIES,PETSC_TRUE)); PetscCall(MatAssemblyBegin(C,MAT_FINAL_ASSEMBLY)); PetscCall(MatAssemblyEnd(C,MAT_FINAL_ASSEMBLY)); C->ops->productsymbolic = NULL; C->ops->productnumeric = MatProductNumeric_Htool; PetscFunctionReturn(0); } static PetscErrorCode MatProductSetFromOptions_Htool(Mat C) { PetscFunctionBegin; MatCheckProduct(C,1); if (C->product->type == MATPRODUCT_AB || C->product->type == MATPRODUCT_AtB) C->ops->productsymbolic = MatProductSymbolic_Htool; PetscFunctionReturn(0); } static PetscErrorCode MatHtoolGetHierarchicalMat_Htool(Mat A,const htool::VirtualHMatrix **hmatrix) { Mat_Htool *a = (Mat_Htool*)A->data; PetscFunctionBegin; *hmatrix = a->hmatrix; PetscFunctionReturn(0); } /*@C MatHtoolGetHierarchicalMat - Retrieves the opaque pointer to a Htool virtual matrix stored in a MATHTOOL. Input Parameter: . A - hierarchical matrix Output Parameter: . hmatrix - opaque pointer to a Htool virtual matrix Level: advanced .seealso: `MATHTOOL` @*/ PETSC_EXTERN PetscErrorCode MatHtoolGetHierarchicalMat(Mat A,const htool::VirtualHMatrix **hmatrix) { PetscFunctionBegin; PetscValidHeaderSpecific(A,MAT_CLASSID,1); PetscValidPointer(hmatrix,2); PetscTryMethod(A,"MatHtoolGetHierarchicalMat_C",(Mat,const htool::VirtualHMatrix**),(A,hmatrix)); PetscFunctionReturn(0); } static PetscErrorCode MatHtoolSetKernel_Htool(Mat A,MatHtoolKernel kernel,void *kernelctx) { Mat_Htool *a = (Mat_Htool*)A->data; PetscFunctionBegin; a->kernel = kernel; a->kernelctx = kernelctx; delete a->wrapper; if (a->kernel) a->wrapper = new WrapperHtool(A->rmap->N,A->cmap->N,a->dim,a->kernel,a->kernelctx); PetscFunctionReturn(0); } /*@C MatHtoolSetKernel - Sets the kernel and context used for the assembly of a MATHTOOL. Input Parameters: + A - hierarchical matrix . kernel - computational kernel (or NULL) - kernelctx - kernel context (if kernel is NULL, the pointer must be of type htool::VirtualGenerator*) Level: advanced .seealso: `MATHTOOL`, `MatCreateHtoolFromKernel()` @*/ PETSC_EXTERN PetscErrorCode MatHtoolSetKernel(Mat A,MatHtoolKernel kernel,void *kernelctx) { PetscFunctionBegin; PetscValidHeaderSpecific(A,MAT_CLASSID,1); if (!kernelctx) PetscValidFunction(kernel,2); if (!kernel) PetscValidPointer(kernelctx,3); PetscTryMethod(A,"MatHtoolSetKernel_C",(Mat,MatHtoolKernel,void*),(A,kernel,kernelctx)); PetscFunctionReturn(0); } static PetscErrorCode MatHtoolGetPermutationSource_Htool(Mat A,IS* is) { Mat_Htool *a = (Mat_Htool*)A->data; std::vector source; PetscFunctionBegin; source = a->hmatrix->get_source_cluster()->get_local_perm(); PetscCall(ISCreateGeneral(PetscObjectComm((PetscObject)A),source.size(),source.data(),PETSC_COPY_VALUES,is)); PetscCall(ISSetPermutation(*is)); PetscFunctionReturn(0); } /*@C MatHtoolGetPermutationSource - Gets the permutation associated to the source cluster. Input Parameter: . A - hierarchical matrix Output Parameter: . is - permutation Level: advanced .seealso: `MATHTOOL`, `MatHtoolGetPermutationTarget()`, `MatHtoolUsePermutation()` @*/ PETSC_EXTERN PetscErrorCode MatHtoolGetPermutationSource(Mat A,IS* is) { PetscFunctionBegin; PetscValidHeaderSpecific(A,MAT_CLASSID,1); if (!is) PetscValidPointer(is,2); PetscTryMethod(A,"MatHtoolGetPermutationSource_C",(Mat,IS*),(A,is)); PetscFunctionReturn(0); } static PetscErrorCode MatHtoolGetPermutationTarget_Htool(Mat A,IS* is) { Mat_Htool *a = (Mat_Htool*)A->data; std::vector target; PetscFunctionBegin; target = a->hmatrix->get_target_cluster()->get_local_perm(); PetscCall(ISCreateGeneral(PetscObjectComm((PetscObject)A),target.size(),target.data(),PETSC_COPY_VALUES,is)); PetscCall(ISSetPermutation(*is)); PetscFunctionReturn(0); } /*@C MatHtoolGetPermutationTarget - Gets the permutation associated to the target cluster. Input Parameter: . A - hierarchical matrix Output Parameter: . is - permutation Level: advanced .seealso: `MATHTOOL`, `MatHtoolGetPermutationSource()`, `MatHtoolUsePermutation()` @*/ PETSC_EXTERN PetscErrorCode MatHtoolGetPermutationTarget(Mat A,IS* is) { PetscFunctionBegin; PetscValidHeaderSpecific(A,MAT_CLASSID,1); if (!is) PetscValidPointer(is,2); PetscTryMethod(A,"MatHtoolGetPermutationTarget_C",(Mat,IS*),(A,is)); PetscFunctionReturn(0); } static PetscErrorCode MatHtoolUsePermutation_Htool(Mat A,PetscBool use) { Mat_Htool *a = (Mat_Htool*)A->data; PetscFunctionBegin; a->hmatrix->set_use_permutation(use); PetscFunctionReturn(0); } /*@C MatHtoolUsePermutation - Sets whether MATHTOOL should permute input (resp. output) vectors following its internal source (resp. target) permutation. Input Parameters: + A - hierarchical matrix - use - Boolean value Level: advanced .seealso: `MATHTOOL`, `MatHtoolGetPermutationSource()`, `MatHtoolGetPermutationTarget()` @*/ PETSC_EXTERN PetscErrorCode MatHtoolUsePermutation(Mat A,PetscBool use) { PetscFunctionBegin; PetscValidHeaderSpecific(A,MAT_CLASSID,1); PetscValidLogicalCollectiveBool(A,use,2); PetscTryMethod(A,"MatHtoolUsePermutation_C",(Mat,PetscBool),(A,use)); PetscFunctionReturn(0); } static PetscErrorCode MatConvert_Htool_Dense(Mat A,MatType newtype,MatReuse reuse,Mat *B) { Mat C; Mat_Htool *a = (Mat_Htool*)A->data; PetscInt lda; PetscScalar *array; PetscFunctionBegin; if (reuse == MAT_REUSE_MATRIX) { C = *B; PetscCheck(C->rmap->n == A->rmap->n && C->cmap->N == A->cmap->N,PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"Incompatible dimensions"); PetscCall(MatDenseGetLDA(C,&lda)); PetscCheck(lda == C->rmap->n,PETSC_COMM_SELF,PETSC_ERR_SUP,"Unsupported leading dimension (%" PetscInt_FMT " != %" PetscInt_FMT ")",lda,C->rmap->n); } else { PetscCall(MatCreate(PetscObjectComm((PetscObject)A),&C)); PetscCall(MatSetSizes(C,A->rmap->n,A->cmap->n,A->rmap->N,A->cmap->N)); PetscCall(MatSetType(C,MATDENSE)); PetscCall(MatSetUp(C)); PetscCall(MatSetOption(C,MAT_NO_OFF_PROC_ENTRIES,PETSC_TRUE)); } PetscCall(MatAssemblyBegin(C,MAT_FINAL_ASSEMBLY)); PetscCall(MatAssemblyEnd(C,MAT_FINAL_ASSEMBLY)); PetscCall(MatDenseGetArrayWrite(C,&array)); a->hmatrix->copy_local_dense_perm(array); PetscCall(MatDenseRestoreArrayWrite(C,&array)); PetscCall(MatScale(C,a->s)); if (reuse == MAT_INPLACE_MATRIX) { PetscCall(MatHeaderReplace(A,&C)); } else *B = C; PetscFunctionReturn(0); } static PetscErrorCode GenEntriesTranspose(PetscInt sdim,PetscInt M,PetscInt N,const PetscInt *rows,const PetscInt *cols,PetscScalar *ptr,void *ctx) { MatHtoolKernelTranspose *generator = (MatHtoolKernelTranspose*)ctx; PetscScalar *tmp; PetscFunctionBegin; generator->kernel(sdim,N,M,cols,rows,ptr,generator->kernelctx); PetscCall(PetscMalloc1(M*N,&tmp)); PetscCall(PetscArraycpy(tmp,ptr,M*N)); for (PetscInt i=0; idata,*c; PetscInt M = A->rmap->N,N = A->cmap->N,m = A->rmap->n,n = A->cmap->n; PetscContainer container; MatHtoolKernelTranspose *kernelt; PetscFunctionBegin; PetscCheck(reuse != MAT_INPLACE_MATRIX,PetscObjectComm((PetscObject)A),PETSC_ERR_SUP,"MatTranspose() with MAT_INPLACE_MATRIX not supported"); if (reuse == MAT_INITIAL_MATRIX) { PetscCall(MatCreate(PetscObjectComm((PetscObject)A),&C)); PetscCall(MatSetSizes(C,n,m,N,M)); PetscCall(MatSetType(C,((PetscObject)A)->type_name)); PetscCall(MatSetUp(C)); PetscCall(PetscContainerCreate(PetscObjectComm((PetscObject)C),&container)); PetscCall(PetscNew(&kernelt)); PetscCall(PetscContainerSetPointer(container,kernelt)); PetscCall(PetscObjectCompose((PetscObject)C,"KernelTranspose",(PetscObject)container)); } else { C = *B; PetscCall(PetscObjectQuery((PetscObject)C,"KernelTranspose",(PetscObject*)&container)); PetscCheck(container,PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Must call MatTranspose() with MAT_INITIAL_MATRIX first"); PetscCall(PetscContainerGetPointer(container,(void**)&kernelt)); } c = (Mat_Htool*)C->data; c->dim = a->dim; c->s = a->s; c->kernel = GenEntriesTranspose; if (kernelt->A != A) { PetscCall(MatDestroy(&kernelt->A)); kernelt->A = A; PetscCall(PetscObjectReference((PetscObject)A)); } kernelt->kernel = a->kernel; kernelt->kernelctx = a->kernelctx; c->kernelctx = kernelt; if (reuse == MAT_INITIAL_MATRIX) { PetscCall(PetscMalloc1(N*c->dim,&c->gcoords_target)); PetscCall(PetscArraycpy(c->gcoords_target,a->gcoords_source,N*c->dim)); if (a->gcoords_target != a->gcoords_source) { PetscCall(PetscMalloc1(M*c->dim,&c->gcoords_source)); PetscCall(PetscArraycpy(c->gcoords_source,a->gcoords_target,M*c->dim)); } else c->gcoords_source = c->gcoords_target; PetscCall(PetscCalloc2(M,&c->work_source,N,&c->work_target)); } PetscCall(MatAssemblyBegin(C,MAT_FINAL_ASSEMBLY)); PetscCall(MatAssemblyEnd(C,MAT_FINAL_ASSEMBLY)); if (reuse == MAT_INITIAL_MATRIX) *B = C; PetscFunctionReturn(0); } /*@C MatCreateHtoolFromKernel - Creates a MATHTOOL from a user-supplied kernel. Input Parameters: + comm - MPI communicator . m - number of local rows (or PETSC_DECIDE to have calculated if M is given) . n - number of local columns (or PETSC_DECIDE to have calculated if N is given) . M - number of global rows (or PETSC_DETERMINE to have calculated if m is given) . N - number of global columns (or PETSC_DETERMINE to have calculated if n is given) . spacedim - dimension of the space coordinates . coords_target - coordinates of the target . coords_source - coordinates of the source . kernel - computational kernel (or NULL) - kernelctx - kernel context (if kernel is NULL, the pointer must be of type htool::VirtualGenerator*) Output Parameter: . B - matrix Options Database Keys: + -mat_htool_min_cluster_size - minimal leaf size in cluster tree . -mat_htool_max_block_size - maximal number of coefficients in a dense block . -mat_htool_epsilon - relative error in Frobenius norm when approximating a block . -mat_htool_eta - admissibility condition tolerance . -mat_htool_min_target_depth - minimal cluster tree depth associated with the rows . -mat_htool_min_source_depth - minimal cluster tree depth associated with the columns . -mat_htool_compressor - type of compression - -mat_htool_clustering - type of clustering Level: intermediate .seealso: `MatCreate()`, `MATHTOOL`, `PCSetCoordinates()`, `MatHtoolSetKernel()`, `MatHtoolCompressorType`, `MATH2OPUS`, `MatCreateH2OpusFromKernel()` @*/ PetscErrorCode MatCreateHtoolFromKernel(MPI_Comm comm,PetscInt m,PetscInt n,PetscInt M,PetscInt N,PetscInt spacedim,const PetscReal coords_target[],const PetscReal coords_source[],MatHtoolKernel kernel,void *kernelctx,Mat *B) { Mat A; Mat_Htool *a; PetscFunctionBegin; PetscCall(MatCreate(comm,&A)); PetscValidLogicalCollectiveInt(A,spacedim,6); PetscValidRealPointer(coords_target,7); PetscValidRealPointer(coords_source,8); if (!kernelctx) PetscValidFunction(kernel,9); if (!kernel) PetscValidPointer(kernelctx,10); PetscCall(MatSetSizes(A,m,n,M,N)); PetscCall(MatSetType(A,MATHTOOL)); PetscCall(MatSetUp(A)); a = (Mat_Htool*)A->data; a->dim = spacedim; a->s = 1.0; a->kernel = kernel; a->kernelctx = kernelctx; PetscCall(PetscCalloc1(A->rmap->N*spacedim,&a->gcoords_target)); PetscCall(PetscArraycpy(a->gcoords_target+A->rmap->rstart*spacedim,coords_target,A->rmap->n*spacedim)); PetscCall(MPIU_Allreduce(MPI_IN_PLACE,a->gcoords_target,A->rmap->N*spacedim,MPIU_REAL,MPI_SUM,PetscObjectComm((PetscObject)A))); /* global target coordinates */ if (coords_target != coords_source) { PetscCall(PetscCalloc1(A->cmap->N*spacedim,&a->gcoords_source)); PetscCall(PetscArraycpy(a->gcoords_source+A->cmap->rstart*spacedim,coords_source,A->cmap->n*spacedim)); PetscCall(MPIU_Allreduce(MPI_IN_PLACE,a->gcoords_source,A->cmap->N*spacedim,MPIU_REAL,MPI_SUM,PetscObjectComm((PetscObject)A))); /* global source coordinates */ } else a->gcoords_source = a->gcoords_target; PetscCall(PetscCalloc2(A->cmap->N,&a->work_source,A->rmap->N,&a->work_target)); *B = A; PetscFunctionReturn(0); } /*MC MATHTOOL = "htool" - A matrix type for hierarchical matrices using the Htool package. Use ./configure --download-htool to install PETSc to use Htool. Options Database Keys: . -mat_type htool - matrix type to "htool" during a call to MatSetFromOptions() Level: beginner .seealso: `MATH2OPUS`, `MATDENSE`, `MatCreateHtoolFromKernel()`, `MatHtoolSetKernel()` M*/ PETSC_EXTERN PetscErrorCode MatCreate_Htool(Mat A) { Mat_Htool *a; PetscFunctionBegin; PetscCall(PetscNewLog(A,&a)); A->data = (void*)a; PetscCall(PetscObjectChangeTypeName((PetscObject)A,MATHTOOL)); PetscCall(PetscMemzero(A->ops,sizeof(struct _MatOps))); A->ops->getdiagonal = MatGetDiagonal_Htool; A->ops->getdiagonalblock = MatGetDiagonalBlock_Htool; A->ops->mult = MatMult_Htool; A->ops->multadd = MatMultAdd_Htool; A->ops->multtranspose = MatMultTranspose_Htool; if (!PetscDefined(USE_COMPLEX)) A->ops->multhermitiantranspose = MatMultTranspose_Htool; A->ops->increaseoverlap = MatIncreaseOverlap_Htool; A->ops->createsubmatrices = MatCreateSubMatrices_Htool; A->ops->transpose = MatTranspose_Htool; A->ops->destroy = MatDestroy_Htool; A->ops->view = MatView_Htool; A->ops->setfromoptions = MatSetFromOptions_Htool; A->ops->scale = MatScale_Htool; A->ops->getrow = MatGetRow_Htool; A->ops->restorerow = MatRestoreRow_Htool; A->ops->assemblyend = MatAssemblyEnd_Htool; a->dim = 0; a->gcoords_target = NULL; a->gcoords_source = NULL; a->s = 1.0; a->bs[0] = 10; a->bs[1] = 1000000; a->epsilon = PetscSqrtReal(PETSC_SMALL); a->eta = 10.0; a->depth[0] = 0; a->depth[1] = 0; a->compressor = MAT_HTOOL_COMPRESSOR_SYMPARTIAL_ACA; PetscCall(PetscObjectComposeFunction((PetscObject)A,"MatProductSetFromOptions_htool_seqdense_C",MatProductSetFromOptions_Htool)); PetscCall(PetscObjectComposeFunction((PetscObject)A,"MatProductSetFromOptions_htool_mpidense_C",MatProductSetFromOptions_Htool)); PetscCall(PetscObjectComposeFunction((PetscObject)A,"MatConvert_htool_seqdense_C",MatConvert_Htool_Dense)); PetscCall(PetscObjectComposeFunction((PetscObject)A,"MatConvert_htool_mpidense_C",MatConvert_Htool_Dense)); PetscCall(PetscObjectComposeFunction((PetscObject)A,"MatHtoolGetHierarchicalMat_C",MatHtoolGetHierarchicalMat_Htool)); PetscCall(PetscObjectComposeFunction((PetscObject)A,"MatHtoolSetKernel_C",MatHtoolSetKernel_Htool)); PetscCall(PetscObjectComposeFunction((PetscObject)A,"MatHtoolGetPermutationSource_C",MatHtoolGetPermutationSource_Htool)); PetscCall(PetscObjectComposeFunction((PetscObject)A,"MatHtoolGetPermutationTarget_C",MatHtoolGetPermutationTarget_Htool)); PetscCall(PetscObjectComposeFunction((PetscObject)A,"MatHtoolUsePermutation_C",MatHtoolUsePermutation_Htool)); PetscFunctionReturn(0); }