#define PETSCMAT_DLL /* -------------------------------------------------------------------- This file implements a subclass of the SeqAIJ matrix class that uses the SuperLU 3.0 sparse solver. You can use this as a starting point for implementing your own subclass of a PETSc matrix class. This demonstrates a way to make an implementation inheritence of a PETSc matrix type. This means constructing a new matrix type (SuperLU) by changing some of the methods of the previous type (SeqAIJ), adding additional data, and possibly additional method. (See any book on object oriented programming). */ /* Defines the data structure for the base matrix type (SeqAIJ) */ #include "src/mat/impls/aij/seq/aij.h" /* SuperLU include files */ EXTERN_C_BEGIN #if defined(PETSC_USE_COMPLEX) #include "slu_zdefs.h" #else #include "slu_ddefs.h" #endif #include "slu_util.h" EXTERN_C_END /* This is the data we are "ADDING" to the SeqAIJ matrix type to get the SuperLU matrix type */ typedef struct { SuperMatrix A,L,U,B,X; superlu_options_t options; PetscInt *perm_c; /* column permutation vector */ PetscInt *perm_r; /* row permutations from partial pivoting */ PetscInt *etree; PetscReal *R, *C; char equed[1]; PetscInt lwork; void *work; PetscReal rpg, rcond; mem_usage_t mem_usage; MatStructure flg; /* Flag to clean up (non-global) SuperLU objects during Destroy */ PetscTruth CleanUpSuperLU; } Mat_SuperLU; extern PetscErrorCode MatFactorInfo_SuperLU(Mat,PetscViewer); extern PetscErrorCode MatLUFactorNumeric_SuperLU(Mat,MatFactorInfo *,Mat *); extern PetscErrorCode MatDestroy_SuperLU(Mat); extern PetscErrorCode MatView_SuperLU(Mat,PetscViewer); extern PetscErrorCode MatAssemblyEnd_SuperLU(Mat,MatAssemblyType); extern PetscErrorCode MatSolve_SuperLU(Mat,Vec,Vec); extern PetscErrorCode MatSolveTranspose_SuperLU(Mat,Vec,Vec); extern PetscErrorCode MatLUFactorSymbolic_SuperLU(Mat,IS,IS,MatFactorInfo *,Mat *); extern PetscErrorCode MatDuplicate_SuperLU(Mat, MatDuplicateOption, Mat *); /* Utility function */ #undef __FUNCT__ #define __FUNCT__ "MatFactorInfo_SuperLU" PetscErrorCode MatFactorInfo_SuperLU(Mat A,PetscViewer viewer) { Mat_SuperLU *lu= (Mat_SuperLU*)A->spptr; PetscErrorCode ierr; superlu_options_t options; PetscFunctionBegin; /* check if matrix is superlu_dist type */ if (A->ops->solve != MatSolve_SuperLU) PetscFunctionReturn(0); options = lu->options; ierr = PetscViewerASCIIPrintf(viewer,"SuperLU run parameters:\n");CHKERRQ(ierr); ierr = PetscViewerASCIIPrintf(viewer," Equil: %s\n",(options.Equil != NO) ? "YES": "NO");CHKERRQ(ierr); ierr = PetscViewerASCIIPrintf(viewer," ColPerm: %D\n",options.ColPerm);CHKERRQ(ierr); ierr = PetscViewerASCIIPrintf(viewer," IterRefine: %D\n",options.IterRefine);CHKERRQ(ierr); ierr = PetscViewerASCIIPrintf(viewer," SymmetricMode: %s\n",(options.SymmetricMode != NO) ? "YES": "NO");CHKERRQ(ierr); ierr = PetscViewerASCIIPrintf(viewer," DiagPivotThresh: %g\n",options.DiagPivotThresh);CHKERRQ(ierr); ierr = PetscViewerASCIIPrintf(viewer," PivotGrowth: %s\n",(options.PivotGrowth != NO) ? "YES": "NO");CHKERRQ(ierr); ierr = PetscViewerASCIIPrintf(viewer," ConditionNumber: %s\n",(options.ConditionNumber != NO) ? "YES": "NO");CHKERRQ(ierr); ierr = PetscViewerASCIIPrintf(viewer," RowPerm: %D\n",options.RowPerm);CHKERRQ(ierr); ierr = PetscViewerASCIIPrintf(viewer," ReplaceTinyPivot: %s\n",(options.ReplaceTinyPivot != NO) ? "YES": "NO");CHKERRQ(ierr); ierr = PetscViewerASCIIPrintf(viewer," PrintStat: %s\n",(options.PrintStat != NO) ? "YES": "NO");CHKERRQ(ierr); ierr = PetscViewerASCIIPrintf(viewer," lwork: %D\n",lu->lwork);CHKERRQ(ierr); PetscFunctionReturn(0); } /* These are the methods provided to REPLACE the corresponding methods of the SeqAIJ matrix class. Other methods of SeqAIJ are not replaced */ #undef __FUNCT__ #define __FUNCT__ "MatLUFactorNumeric_SuperLU" PetscErrorCode MatLUFactorNumeric_SuperLU(Mat A,MatFactorInfo *info,Mat *F) { Mat_SeqAIJ *aa = (Mat_SeqAIJ*)(A)->data; Mat_SuperLU *lu = (Mat_SuperLU*)(*F)->spptr; PetscErrorCode ierr; PetscInt sinfo; SuperLUStat_t stat; PetscReal ferr, berr; NCformat *Ustore; SCformat *Lstore; PetscFunctionBegin; if (lu->flg == SAME_NONZERO_PATTERN){ /* successing numerical factorization */ lu->options.Fact = SamePattern; /* Ref: ~SuperLU_3.0/EXAMPLE/dlinsolx2.c */ Destroy_SuperMatrix_Store(&lu->A); if ( lu->lwork >= 0 ) { Destroy_SuperNode_Matrix(&lu->L); Destroy_CompCol_Matrix(&lu->U); lu->options.Fact = SamePattern; } } /* Create the SuperMatrix for lu->A=A^T: Since SuperLU likes column-oriented matrices,we pass it the transpose, and then solve A^T X = B in MatSolve(). */ #if defined(PETSC_USE_COMPLEX) zCreate_CompCol_Matrix(&lu->A,A->cmap.n,A->rmap.n,aa->nz,(doublecomplex*)aa->a,aa->j,aa->i, SLU_NC,SLU_Z,SLU_GE); #else dCreate_CompCol_Matrix(&lu->A,A->cmap.n,A->rmap.n,aa->nz,aa->a,aa->j,aa->i, SLU_NC,SLU_D,SLU_GE); #endif /* Initialize the statistics variables. */ StatInit(&stat); /* Numerical factorization */ lu->B.ncol = 0; /* Indicate not to solve the system */ #if defined(PETSC_USE_COMPLEX) zgssvx(&lu->options, &lu->A, lu->perm_c, lu->perm_r, lu->etree, lu->equed, lu->R, lu->C, &lu->L, &lu->U, lu->work, lu->lwork, &lu->B, &lu->X, &lu->rpg, &lu->rcond, &ferr, &berr, &lu->mem_usage, &stat, &sinfo); #else dgssvx(&lu->options, &lu->A, lu->perm_c, lu->perm_r, lu->etree, lu->equed, lu->R, lu->C, &lu->L, &lu->U, lu->work, lu->lwork, &lu->B, &lu->X, &lu->rpg, &lu->rcond, &ferr, &berr, &lu->mem_usage, &stat, &sinfo); #endif if ( !sinfo || sinfo == lu->A.ncol+1 ) { if ( lu->options.PivotGrowth ) ierr = PetscPrintf(PETSC_COMM_SELF," Recip. pivot growth = %e\n", lu->rpg); if ( lu->options.ConditionNumber ) ierr = PetscPrintf(PETSC_COMM_SELF," Recip. condition number = %e\n", lu->rcond); } else if ( sinfo > 0 ){ if ( lu->lwork == -1 ) { ierr = PetscPrintf(PETSC_COMM_SELF," ** Estimated memory: %D bytes\n", sinfo - lu->A.ncol); } else { ierr = PetscPrintf(PETSC_COMM_SELF," Warning: gssvx() returns info %D\n",sinfo); } } else { /* sinfo < 0 */ SETERRQ2(PETSC_ERR_LIB, "info = %D, the %D-th argument in gssvx() had an illegal value", sinfo,-sinfo); } if ( lu->options.PrintStat ) { ierr = PetscPrintf(PETSC_COMM_SELF,"MatLUFactorNumeric_SuperLU():\n"); StatPrint(&stat); Lstore = (SCformat *) lu->L.Store; Ustore = (NCformat *) lu->U.Store; ierr = PetscPrintf(PETSC_COMM_SELF," No of nonzeros in factor L = %D\n", Lstore->nnz); ierr = PetscPrintf(PETSC_COMM_SELF," No of nonzeros in factor U = %D\n", Ustore->nnz); ierr = PetscPrintf(PETSC_COMM_SELF," No of nonzeros in L+U = %D\n", Lstore->nnz + Ustore->nnz - lu->A.ncol); ierr = PetscPrintf(PETSC_COMM_SELF," L\\U MB %.3f\ttotal MB needed %.3f\texpansions %D\n", lu->mem_usage.for_lu/1e6, lu->mem_usage.total_needed/1e6, lu->mem_usage.expansions); } StatFree(&stat); lu->flg = SAME_NONZERO_PATTERN; PetscFunctionReturn(0); } #undef __FUNCT__ #define __FUNCT__ "MatDestroy_SuperLU" PetscErrorCode MatDestroy_SuperLU(Mat A) { PetscErrorCode ierr; Mat_SuperLU *lu=(Mat_SuperLU*)A->spptr; PetscFunctionBegin; if (lu->CleanUpSuperLU) { /* Free the SuperLU datastructures */ Destroy_SuperMatrix_Store(&lu->A); Destroy_SuperMatrix_Store(&lu->B); Destroy_SuperMatrix_Store(&lu->X); ierr = PetscFree(lu->etree);CHKERRQ(ierr); ierr = PetscFree(lu->perm_r);CHKERRQ(ierr); ierr = PetscFree(lu->perm_c);CHKERRQ(ierr); ierr = PetscFree(lu->R);CHKERRQ(ierr); ierr = PetscFree(lu->C);CHKERRQ(ierr); if ( lu->lwork >= 0 ) { Destroy_SuperNode_Matrix(&lu->L); Destroy_CompCol_Matrix(&lu->U); } } ierr = MatDestroy_SeqAIJ(A);CHKERRQ(ierr); PetscFunctionReturn(0); } #undef __FUNCT__ #define __FUNCT__ "MatView_SuperLU" PetscErrorCode MatView_SuperLU(Mat A,PetscViewer viewer) { PetscErrorCode ierr; PetscTruth iascii; PetscViewerFormat format; Mat_SuperLU *lu=(Mat_SuperLU*)(A->spptr); PetscFunctionBegin; ierr = MatView_SeqAIJ(A,viewer);CHKERRQ(ierr); ierr = PetscTypeCompare((PetscObject)viewer,PETSC_VIEWER_ASCII,&iascii);CHKERRQ(ierr); if (iascii) { ierr = PetscViewerGetFormat(viewer,&format);CHKERRQ(ierr); if (format == PETSC_VIEWER_ASCII_INFO) { ierr = MatFactorInfo_SuperLU(A,viewer);CHKERRQ(ierr); } } PetscFunctionReturn(0); } #undef __FUNCT__ #define __FUNCT__ "MatSolve_SuperLU_Private" PetscErrorCode MatSolve_SuperLU_Private(Mat A,Vec b,Vec x) { Mat_SuperLU *lu = (Mat_SuperLU*)A->spptr; PetscScalar *barray,*xarray; PetscErrorCode ierr; PetscInt info,i; SuperLUStat_t stat; PetscReal ferr,berr; PetscFunctionBegin; if ( lu->lwork == -1 ) { PetscFunctionReturn(0); } lu->B.ncol = 1; /* Set the number of right-hand side */ ierr = VecGetArray(b,&barray);CHKERRQ(ierr); ierr = VecGetArray(x,&xarray);CHKERRQ(ierr); #if defined(PETSC_USE_COMPLEX) ((DNformat*)lu->B.Store)->nzval = (doublecomplex*)barray; ((DNformat*)lu->X.Store)->nzval = (doublecomplex*)xarray; #else ((DNformat*)lu->B.Store)->nzval = barray; ((DNformat*)lu->X.Store)->nzval = xarray; #endif /* Initialize the statistics variables. */ StatInit(&stat); lu->options.Fact = FACTORED; /* Indicate the factored form of A is supplied. */ #if defined(PETSC_USE_COMPLEX) zgssvx(&lu->options, &lu->A, lu->perm_c, lu->perm_r, lu->etree, lu->equed, lu->R, lu->C, &lu->L, &lu->U, lu->work, lu->lwork, &lu->B, &lu->X, &lu->rpg, &lu->rcond, &ferr, &berr, &lu->mem_usage, &stat, &info); #else dgssvx(&lu->options, &lu->A, lu->perm_c, lu->perm_r, lu->etree, lu->equed, lu->R, lu->C, &lu->L, &lu->U, lu->work, lu->lwork, &lu->B, &lu->X, &lu->rpg, &lu->rcond, &ferr, &berr, &lu->mem_usage, &stat, &info); #endif ierr = VecRestoreArray(b,&barray);CHKERRQ(ierr); ierr = VecRestoreArray(x,&xarray);CHKERRQ(ierr); if ( !info || info == lu->A.ncol+1 ) { if ( lu->options.IterRefine ) { ierr = PetscPrintf(PETSC_COMM_SELF,"Iterative Refinement:\n"); ierr = PetscPrintf(PETSC_COMM_SELF," %8s%8s%16s%16s\n", "rhs", "Steps", "FERR", "BERR"); for (i = 0; i < 1; ++i) ierr = PetscPrintf(PETSC_COMM_SELF," %8d%8d%16e%16e\n", i+1, stat.RefineSteps, ferr, berr); } } else if ( info > 0 ){ if ( lu->lwork == -1 ) { ierr = PetscPrintf(PETSC_COMM_SELF," ** Estimated memory: %D bytes\n", info - lu->A.ncol); } else { ierr = PetscPrintf(PETSC_COMM_SELF," Warning: gssvx() returns info %D\n",info); } } else if (info < 0){ SETERRQ2(PETSC_ERR_LIB, "info = %D, the %D-th argument in gssvx() had an illegal value", info,-info); } if ( lu->options.PrintStat ) { ierr = PetscPrintf(PETSC_COMM_SELF,"MatSolve__SuperLU():\n"); StatPrint(&stat); } StatFree(&stat); PetscFunctionReturn(0); } #undef __FUNCT__ #define __FUNCT__ "MatSolve_SuperLU" PetscErrorCode MatSolve_SuperLU(Mat A,Vec b,Vec x) { Mat_SuperLU *lu = (Mat_SuperLU*)A->spptr; PetscErrorCode ierr; PetscFunctionBegin; lu->options.Trans = TRANS; ierr = MatSolve_SuperLU_Private(A,b,x);CHKERRQ(ierr); PetscFunctionReturn(0); } #undef __FUNCT__ #define __FUNCT__ "MatSolveTranspose_SuperLU" PetscErrorCode MatSolveTranspose_SuperLU(Mat A,Vec b,Vec x) { Mat_SuperLU *lu = (Mat_SuperLU*)A->spptr; PetscErrorCode ierr; PetscFunctionBegin; lu->options.Trans = NOTRANS; ierr = MatSolve_SuperLU_Private(A,b,x);CHKERRQ(ierr); PetscFunctionReturn(0); } /* Note the r permutation is ignored */ #undef __FUNCT__ #define __FUNCT__ "MatLUFactorSymbolic_SuperLU" PetscErrorCode MatLUFactorSymbolic_SuperLU(Mat A,IS r,IS c,MatFactorInfo *info,Mat *F) { Mat_SuperLU *lu = (Mat_SuperLU*)((*F)->spptr); PetscErrorCode ierr; PetscInt m=A->rmap.n,n=A->cmap.n,indx; PetscFunctionBegin; /* Allocate spaces (notice sizes are for the transpose) */ ierr = PetscMalloc(m*sizeof(PetscInt),&lu->etree);CHKERRQ(ierr); ierr = PetscMalloc(n*sizeof(PetscInt),&lu->perm_r);CHKERRQ(ierr); ierr = PetscMalloc(m*sizeof(PetscInt),&lu->perm_c);CHKERRQ(ierr); ierr = PetscMalloc(n*sizeof(PetscInt),&lu->R);CHKERRQ(ierr); ierr = PetscMalloc(m*sizeof(PetscInt),&lu->C);CHKERRQ(ierr); /* create rhs and solution x without allocate space for .Store */ #if defined(PETSC_USE_COMPLEX) zCreate_Dense_Matrix(&lu->B, m, 1, PETSC_NULL, m, SLU_DN, SLU_Z, SLU_GE); zCreate_Dense_Matrix(&lu->X, m, 1, PETSC_NULL, m, SLU_DN, SLU_Z, SLU_GE); #else dCreate_Dense_Matrix(&lu->B, m, 1, PETSC_NULL, m, SLU_DN, SLU_D, SLU_GE); dCreate_Dense_Matrix(&lu->X, m, 1, PETSC_NULL, m, SLU_DN, SLU_D, SLU_GE); #endif lu->flg = DIFFERENT_NONZERO_PATTERN; lu->CleanUpSuperLU = PETSC_TRUE; PetscFunctionReturn(0); } /*MC MATSUPERLU - MATSUPERLU = "superlu" - A matrix type providing direct solvers (LU) for sequential matrices via the external package SuperLU. If SuperLU is installed (see the manual for instructions on how to declare the existence of external packages), a matrix type can be constructed which invokes SuperLU solvers. After calling MatCreate(...,A), simply call MatSetType(A,MATSUPERLU), then optionally call MatSeqAIJSetPreallocation() or MatMPIAIJSetPreallocation() DO NOT call MatCreateSeqAIJ/MPIAIJ() directly or the preallocation information will be LOST! This matrix inherits from MATSEQAIJ. As a result, MatSeqAIJSetPreallocation() is supported for this matrix type. One can also call MatConvert() for an inplace conversion to or from the MATSEQAIJ type AFTER the matrix values are set without data copy. Options Database Keys: + -mat_type superlu - sets the matrix type to "superlu" during a call to MatSetFromOptions() . -mat_superlu_ordering <0,1,2,3> - 0: natural ordering, 1: MMD applied to A'*A, 2: MMD applied to A'+A, 3: COLAMD, approximate minimum degree column ordering . -mat_superlu_iterrefine - have SuperLU do iterative refinement after the triangular solve choices: NOREFINE, SINGLE, DOUBLE, EXTRA; default is NOREFINE - -mat_superlu_printstat - print SuperLU statistics about the factorization Level: beginner .seealso: PCLU M*/ #undef __FUNCT__ #define __FUNCT__ "MatGetFactor_seqaij_superlu" PetscErrorCode MatGetFactor_seqaij_superlu(Mat A,Mat *F) { Mat B; Mat_SuperLU *lu; PetscErrorCode ierr; PetscInt m=A->rmap.n,n=A->cmap.n,indx; PetscTruth flg; const char *colperm[]={"NATURAL","MMD_ATA","MMD_AT_PLUS_A","COLAMD"}; /* MY_PERMC - not supported by the petsc interface yet */ const char *iterrefine[]={"NOREFINE", "SINGLE", "DOUBLE", "EXTRA"}; const char *rowperm[]={"NOROWPERM", "LargeDiag"}; /* MY_PERMC - not supported by the petsc interface yet */ PetscFunctionBegin; ierr = MatCreate(((PetscObject)A)->comm,&B);CHKERRQ(ierr); ierr = MatSetSizes(B,A->rmap.n,A->cmap.n,PETSC_DETERMINE,PETSC_DETERMINE);CHKERRQ(ierr); ierr = MatSetType(B,((PetscObject)A)->type_name);CHKERRQ(ierr); ierr = MatSeqAIJSetPreallocation(B,0,PETSC_NULL);CHKERRQ(ierr); B->ops->lufactornumeric = MatLUFactorNumeric_SuperLU; B->ops->lufactorsymbolic = MatLUFactorSymbolic_SuperLU; B->ops->solve = MatSolve_SuperLU; B->ops->solvetranspose = MatSolveTranspose_SuperLU; B->ops->destroy = MatDestroy_SuperLU; B->factor = FACTOR_LU; B->assembled = PETSC_TRUE; /* required by -ksp_view */ ierr = PetscNewLog(B,Mat_SuperLU,&lu);CHKERRQ(ierr); set_default_options(&lu->options); /* equilibration causes error in solve(), thus not supported here. See dgssvx.c for possible reason. */ lu->options.Equil = NO; lu->options.PrintStat = NO; lu->lwork = 0; /* allocate space internally by system malloc */ ierr = PetscOptionsBegin(((PetscObject)A)->comm,((PetscObject)A)->prefix,"SuperLU Options","Mat");CHKERRQ(ierr); ierr = PetscOptionsEList("-mat_superlu_colperm","ColPerm","None",colperm,4,colperm[3],&indx,&flg);CHKERRQ(ierr); if (flg) {lu->options.ColPerm = (colperm_t)indx;} ierr = PetscOptionsEList("-mat_superlu_iterrefine","IterRefine","None",iterrefine,4,iterrefine[0],&indx,&flg);CHKERRQ(ierr); if (flg) { lu->options.IterRefine = (IterRefine_t)indx;} ierr = PetscOptionsTruth("-mat_superlu_symmetricmode","SymmetricMode","None",PETSC_FALSE,&flg,0);CHKERRQ(ierr); if (flg) lu->options.SymmetricMode = YES; ierr = PetscOptionsReal("-mat_superlu_diagpivotthresh","DiagPivotThresh","None",lu->options.DiagPivotThresh,&lu->options.DiagPivotThresh,PETSC_NULL);CHKERRQ(ierr); ierr = PetscOptionsTruth("-mat_superlu_pivotgrowth","PivotGrowth","None",PETSC_FALSE,&flg,0);CHKERRQ(ierr); if (flg) lu->options.PivotGrowth = YES; ierr = PetscOptionsTruth("-mat_superlu_conditionnumber","ConditionNumber","None",PETSC_FALSE,&flg,0);CHKERRQ(ierr); if (flg) lu->options.ConditionNumber = YES; ierr = PetscOptionsEList("-mat_superlu_rowperm","rowperm","None",rowperm,2,rowperm[0],&indx,&flg);CHKERRQ(ierr); if (flg) {lu->options.RowPerm = (rowperm_t)indx;} ierr = PetscOptionsTruth("-mat_superlu_replacetinypivot","ReplaceTinyPivot","None",PETSC_FALSE,&flg,0);CHKERRQ(ierr); if (flg) lu->options.ReplaceTinyPivot = YES; ierr = PetscOptionsTruth("-mat_superlu_printstat","PrintStat","None",PETSC_FALSE,&flg,0);CHKERRQ(ierr); if (flg) lu->options.PrintStat = YES; ierr = PetscOptionsInt("-mat_superlu_lwork","size of work array in bytes used by factorization","None",lu->lwork,&lu->lwork,PETSC_NULL);CHKERRQ(ierr); if (lu->lwork > 0 ){ ierr = PetscMalloc(lu->lwork,&lu->work);CHKERRQ(ierr); } else if (lu->lwork != 0 && lu->lwork != -1){ ierr = PetscPrintf(PETSC_COMM_SELF," Warning: lwork %D is not supported by SUPERLU. The default lwork=0 is used.\n",lu->lwork); lu->lwork = 0; } PetscOptionsEnd(); #ifdef SUPERLU2 ierr = PetscObjectComposeFunctionDynamic((PetscObject)B,"MatCreateNull","MatCreateNull_SuperLU", (void(*)(void))MatCreateNull_SuperLU);CHKERRQ(ierr); #endif *F = B; PetscFunctionReturn(0); }