/* Defines the basic matrix operations for the SBAIJ (compressed row) matrix storage format. */ #include "src/mat/impls/baij/seq/baij.h" /*I "petscmat.h" I*/ #include "src/inline/spops.h" #include "src/mat/impls/sbaij/seq/sbaij.h" #define CHUNKSIZE 10 /* Checks for missing diagonals */ #undef __FUNCT__ #define __FUNCT__ "MatMissingDiagonal_SeqSBAIJ" PetscErrorCode MatMissingDiagonal_SeqSBAIJ(Mat A) { Mat_SeqSBAIJ *a = (Mat_SeqSBAIJ*)A->data; PetscErrorCode ierr; int *diag,*jj = a->j,i; PetscFunctionBegin; ierr = MatMarkDiagonal_SeqSBAIJ(A);CHKERRQ(ierr); diag = a->diag; for (i=0; imbs; i++) { if (jj[diag[i]] != i) SETERRQ1(1,"Matrix is missing diagonal number %d",i); } PetscFunctionReturn(0); } #undef __FUNCT__ #define __FUNCT__ "MatMarkDiagonal_SeqSBAIJ" PetscErrorCode MatMarkDiagonal_SeqSBAIJ(Mat A) { Mat_SeqSBAIJ *a = (Mat_SeqSBAIJ*)A->data; PetscErrorCode ierr; int i,mbs = a->mbs; PetscFunctionBegin; if (a->diag) PetscFunctionReturn(0); ierr = PetscMalloc((mbs+1)*sizeof(int),&a->diag);CHKERRQ(ierr); PetscLogObjectMemory(A,(mbs+1)*sizeof(int)); for (i=0; idiag[i] = a->i[i]; PetscFunctionReturn(0); } #undef __FUNCT__ #define __FUNCT__ "MatGetRowIJ_SeqSBAIJ" static PetscErrorCode MatGetRowIJ_SeqSBAIJ(Mat A,int oshift,PetscTruth symmetric,int *nn,int *ia[],int *ja[],PetscTruth *done) { Mat_SeqSBAIJ *a = (Mat_SeqSBAIJ*)A->data; int n = a->mbs,i; PetscFunctionBegin; *nn = n; if (!ia) PetscFunctionReturn(0); if (oshift == 1) { /* temporarily add 1 to i and j indices */ int nz = a->i[n]; for (i=0; ij[i]++; for (i=0; ii[i]++; *ia = a->i; *ja = a->j; } else { *ia = a->i; *ja = a->j; } PetscFunctionReturn(0); } #undef __FUNCT__ #define __FUNCT__ "MatRestoreRowIJ_SeqSBAIJ" static PetscErrorCode MatRestoreRowIJ_SeqSBAIJ(Mat A,int oshift,PetscTruth symmetric,int *nn,int *ia[],int *ja[],PetscTruth *done) { Mat_SeqSBAIJ *a = (Mat_SeqSBAIJ*)A->data; int i,n = a->mbs; PetscFunctionBegin; if (!ia) PetscFunctionReturn(0); if (oshift == 1) { int nz = a->i[n]-1; for (i=0; ij[i]--; for (i=0; ii[i]--; } PetscFunctionReturn(0); } #undef __FUNCT__ #define __FUNCT__ "MatGetBlockSize_SeqSBAIJ" PetscErrorCode MatGetBlockSize_SeqSBAIJ(Mat mat,int *bs) { Mat_SeqSBAIJ *sbaij = (Mat_SeqSBAIJ*)mat->data; PetscFunctionBegin; *bs = sbaij->bs; PetscFunctionReturn(0); } #undef __FUNCT__ #define __FUNCT__ "MatDestroy_SeqSBAIJ" PetscErrorCode MatDestroy_SeqSBAIJ(Mat A) { Mat_SeqSBAIJ *a = (Mat_SeqSBAIJ*)A->data; PetscErrorCode ierr; PetscFunctionBegin; #if defined(PETSC_USE_LOG) PetscLogObjectState((PetscObject)A,"Rows=%d, NZ=%d",A->m,a->nz); #endif ierr = PetscFree(a->a);CHKERRQ(ierr); if (!a->singlemalloc) { ierr = PetscFree(a->i);CHKERRQ(ierr); ierr = PetscFree(a->j);CHKERRQ(ierr); } if (a->row) { ierr = ISDestroy(a->row);CHKERRQ(ierr); } if (a->diag) {ierr = PetscFree(a->diag);CHKERRQ(ierr);} if (a->ilen) {ierr = PetscFree(a->ilen);CHKERRQ(ierr);} if (a->imax) {ierr = PetscFree(a->imax);CHKERRQ(ierr);} if (a->icol) {ierr = ISDestroy(a->icol);CHKERRQ(ierr);} if (a->solve_work) {ierr = PetscFree(a->solve_work);CHKERRQ(ierr);} if (a->solves_work) {ierr = PetscFree(a->solves_work);CHKERRQ(ierr);} if (a->mult_work) {ierr = PetscFree(a->mult_work);CHKERRQ(ierr);} if (a->saved_values) {ierr = PetscFree(a->saved_values);CHKERRQ(ierr);} if (a->xtoy) {ierr = PetscFree(a->xtoy);CHKERRQ(ierr);} if (a->inew){ ierr = PetscFree(a->inew);CHKERRQ(ierr); a->inew = 0; } ierr = PetscFree(a);CHKERRQ(ierr); PetscFunctionReturn(0); } #undef __FUNCT__ #define __FUNCT__ "MatSetOption_SeqSBAIJ" PetscErrorCode MatSetOption_SeqSBAIJ(Mat A,MatOption op) { Mat_SeqSBAIJ *a = (Mat_SeqSBAIJ*)A->data; PetscFunctionBegin; switch (op) { case MAT_ROW_ORIENTED: a->roworiented = PETSC_TRUE; break; case MAT_COLUMN_ORIENTED: a->roworiented = PETSC_FALSE; break; case MAT_COLUMNS_SORTED: a->sorted = PETSC_TRUE; break; case MAT_COLUMNS_UNSORTED: a->sorted = PETSC_FALSE; break; case MAT_KEEP_ZEROED_ROWS: a->keepzeroedrows = PETSC_TRUE; break; case MAT_NO_NEW_NONZERO_LOCATIONS: a->nonew = 1; break; case MAT_NEW_NONZERO_LOCATION_ERR: a->nonew = -1; break; case MAT_NEW_NONZERO_ALLOCATION_ERR: a->nonew = -2; break; case MAT_YES_NEW_NONZERO_LOCATIONS: a->nonew = 0; break; case MAT_ROWS_SORTED: case MAT_ROWS_UNSORTED: case MAT_YES_NEW_DIAGONALS: case MAT_IGNORE_OFF_PROC_ENTRIES: case MAT_USE_HASH_TABLE: PetscLogInfo(A,"MatSetOption_SeqSBAIJ:Option ignored\n"); break; case MAT_NO_NEW_DIAGONALS: SETERRQ(PETSC_ERR_SUP,"MAT_NO_NEW_DIAGONALS"); case MAT_NOT_SYMMETRIC: case MAT_NOT_STRUCTURALLY_SYMMETRIC: case MAT_HERMITIAN: SETERRQ(PETSC_ERR_SUP,"Matrix must be symmetric"); case MAT_SYMMETRIC: case MAT_STRUCTURALLY_SYMMETRIC: case MAT_NOT_HERMITIAN: case MAT_SYMMETRY_ETERNAL: case MAT_NOT_SYMMETRY_ETERNAL: break; default: SETERRQ(PETSC_ERR_SUP,"unknown option"); } PetscFunctionReturn(0); } #undef __FUNCT__ #define __FUNCT__ "MatGetRow_SeqSBAIJ" PetscErrorCode MatGetRow_SeqSBAIJ(Mat A,int row,int *ncols,int **cols,PetscScalar **v) { Mat_SeqSBAIJ *a = (Mat_SeqSBAIJ*)A->data; PetscErrorCode ierr; int itmp,i,j,k,M,*ai,*aj,bs,bn,bp,*cols_i,bs2; MatScalar *aa,*aa_i; PetscScalar *v_i; PetscFunctionBegin; bs = a->bs; ai = a->i; aj = a->j; aa = a->a; bs2 = a->bs2; if (row < 0 || row >= A->m) SETERRQ1(PETSC_ERR_ARG_OUTOFRANGE, "Row %d out of range", row); bn = row/bs; /* Block number */ bp = row % bs; /* Block position */ M = ai[bn+1] - ai[bn]; *ncols = bs*M; if (v) { *v = 0; if (*ncols) { ierr = PetscMalloc((*ncols+row)*sizeof(PetscScalar),v);CHKERRQ(ierr); for (i=0; idata; PetscErrorCode ierr; int i,j,bs = a->bs,k,l,bs2=a->bs2; char *name; PetscViewerFormat format; PetscFunctionBegin; ierr = PetscObjectGetName((PetscObject)A,&name);CHKERRQ(ierr); ierr = PetscViewerGetFormat(viewer,&format);CHKERRQ(ierr); if (format == PETSC_VIEWER_ASCII_INFO || format == PETSC_VIEWER_ASCII_INFO_DETAIL) { ierr = PetscViewerASCIIPrintf(viewer," block size is %d\n",bs);CHKERRQ(ierr); } else if (format == PETSC_VIEWER_ASCII_MATLAB) { SETERRQ(PETSC_ERR_SUP,"Matlab format not supported"); } else if (format == PETSC_VIEWER_ASCII_COMMON) { ierr = PetscViewerASCIIUseTabs(viewer,PETSC_NO);CHKERRQ(ierr); for (i=0; imbs; i++) { for (j=0; ji[i]; ki[i+1]; k++) { for (l=0; la[bs2*k + l*bs + j]) > 0.0 && PetscRealPart(a->a[bs2*k + l*bs + j]) != 0.0) { ierr = PetscViewerASCIIPrintf(viewer," (%d, %g + %g i) ",bs*a->j[k]+l, PetscRealPart(a->a[bs2*k + l*bs + j]),PetscImaginaryPart(a->a[bs2*k + l*bs + j]));CHKERRQ(ierr); } else if (PetscImaginaryPart(a->a[bs2*k + l*bs + j]) < 0.0 && PetscRealPart(a->a[bs2*k + l*bs + j]) != 0.0) { ierr = PetscViewerASCIIPrintf(viewer," (%d, %g - %g i) ",bs*a->j[k]+l, PetscRealPart(a->a[bs2*k + l*bs + j]),-PetscImaginaryPart(a->a[bs2*k + l*bs + j]));CHKERRQ(ierr); } else if (PetscRealPart(a->a[bs2*k + l*bs + j]) != 0.0) { ierr = PetscViewerASCIIPrintf(viewer," (%d, %g) ",bs*a->j[k]+l,PetscRealPart(a->a[bs2*k + l*bs + j]));CHKERRQ(ierr); } #else if (a->a[bs2*k + l*bs + j] != 0.0) { ierr = PetscViewerASCIIPrintf(viewer," (%d, %g) ",bs*a->j[k]+l,a->a[bs2*k + l*bs + j]);CHKERRQ(ierr); } #endif } } ierr = PetscViewerASCIIPrintf(viewer,"\n");CHKERRQ(ierr); } } ierr = PetscViewerASCIIUseTabs(viewer,PETSC_YES);CHKERRQ(ierr); } else { ierr = PetscViewerASCIIUseTabs(viewer,PETSC_NO);CHKERRQ(ierr); for (i=0; imbs; i++) { for (j=0; ji[i]; ki[i+1]; k++) { for (l=0; la[bs2*k + l*bs + j]) > 0.0) { ierr = PetscViewerASCIIPrintf(viewer," (%d, %g + %g i) ",bs*a->j[k]+l, PetscRealPart(a->a[bs2*k + l*bs + j]),PetscImaginaryPart(a->a[bs2*k + l*bs + j]));CHKERRQ(ierr); } else if (PetscImaginaryPart(a->a[bs2*k + l*bs + j]) < 0.0) { ierr = PetscViewerASCIIPrintf(viewer," (%d, %g - %g i) ",bs*a->j[k]+l, PetscRealPart(a->a[bs2*k + l*bs + j]),-PetscImaginaryPart(a->a[bs2*k + l*bs + j]));CHKERRQ(ierr); } else { ierr = PetscViewerASCIIPrintf(viewer," (%d, %g) ",bs*a->j[k]+l,PetscRealPart(a->a[bs2*k + l*bs + j]));CHKERRQ(ierr); } #else ierr = PetscViewerASCIIPrintf(viewer," %d %g ",bs*a->j[k]+l,a->a[bs2*k + l*bs + j]);CHKERRQ(ierr); #endif } } ierr = PetscViewerASCIIPrintf(viewer,"\n");CHKERRQ(ierr); } } ierr = PetscViewerASCIIUseTabs(viewer,PETSC_YES);CHKERRQ(ierr); } ierr = PetscViewerFlush(viewer);CHKERRQ(ierr); PetscFunctionReturn(0); } #undef __FUNCT__ #define __FUNCT__ "MatView_SeqSBAIJ_Draw_Zoom" static PetscErrorCode MatView_SeqSBAIJ_Draw_Zoom(PetscDraw draw,void *Aa) { Mat A = (Mat) Aa; Mat_SeqSBAIJ *a=(Mat_SeqSBAIJ*)A->data; PetscErrorCode ierr; int row,i,j,k,l,mbs=a->mbs,color,bs=a->bs,bs2=a->bs2,rank; PetscReal xl,yl,xr,yr,x_l,x_r,y_l,y_r; MatScalar *aa; MPI_Comm comm; PetscViewer viewer; PetscFunctionBegin; /* This is nasty. If this is called from an originally parallel matrix then all processes call this,but only the first has the matrix so the rest should return immediately. */ ierr = PetscObjectGetComm((PetscObject)draw,&comm);CHKERRQ(ierr); ierr = MPI_Comm_rank(comm,&rank);CHKERRQ(ierr); if (rank) PetscFunctionReturn(0); ierr = PetscObjectQuery((PetscObject)A,"Zoomviewer",(PetscObject*)&viewer);CHKERRQ(ierr); ierr = PetscDrawGetCoordinates(draw,&xl,&yl,&xr,&yr);CHKERRQ(ierr); PetscDrawString(draw, .3*(xl+xr), .3*(yl+yr), PETSC_DRAW_BLACK, "symmetric"); /* loop over matrix elements drawing boxes */ color = PETSC_DRAW_BLUE; for (i=0,row=0; ii[i]; ji[i+1]; j++) { y_l = A->m - row - 1.0; y_r = y_l + 1.0; x_l = a->j[j]*bs; x_r = x_l + 1.0; aa = a->a + j*bs2; for (k=0; k= 0.) continue; ierr = PetscDrawRectangle(draw,x_l+k,y_l-l,x_r+k,y_r-l,color,color,color,color);CHKERRQ(ierr); } } } } color = PETSC_DRAW_CYAN; for (i=0,row=0; ii[i]; ji[i+1]; j++) { y_l = A->m - row - 1.0; y_r = y_l + 1.0; x_l = a->j[j]*bs; x_r = x_l + 1.0; aa = a->a + j*bs2; for (k=0; ki[i]; ji[i+1]; j++) { y_l = A->m - row - 1.0; y_r = y_l + 1.0; x_l = a->j[j]*bs; x_r = x_l + 1.0; aa = a->a + j*bs2; for (k=0; km; yr = A->m; h = yr/10.0; w = xr/10.0; xr += w; yr += h; xl = -w; yl = -h; ierr = PetscDrawSetCoordinates(draw,xl,yl,xr,yr);CHKERRQ(ierr); ierr = PetscDrawZoom(draw,MatView_SeqSBAIJ_Draw_Zoom,A);CHKERRQ(ierr); ierr = PetscObjectCompose((PetscObject)A,"Zoomviewer",PETSC_NULL);CHKERRQ(ierr); PetscFunctionReturn(0); } #undef __FUNCT__ #define __FUNCT__ "MatView_SeqSBAIJ" PetscErrorCode MatView_SeqSBAIJ(Mat A,PetscViewer viewer) { PetscErrorCode ierr; PetscTruth iascii,isdraw; PetscFunctionBegin; ierr = PetscTypeCompare((PetscObject)viewer,PETSC_VIEWER_ASCII,&iascii);CHKERRQ(ierr); ierr = PetscTypeCompare((PetscObject)viewer,PETSC_VIEWER_DRAW,&isdraw);CHKERRQ(ierr); if (iascii){ ierr = MatView_SeqSBAIJ_ASCII(A,viewer);CHKERRQ(ierr); } else if (isdraw) { ierr = MatView_SeqSBAIJ_Draw(A,viewer);CHKERRQ(ierr); } else { Mat B; ierr = MatConvert(A,MATSEQAIJ,&B);CHKERRQ(ierr); ierr = MatView(B,viewer);CHKERRQ(ierr); ierr = MatDestroy(B);CHKERRQ(ierr); } PetscFunctionReturn(0); } #undef __FUNCT__ #define __FUNCT__ "MatGetValues_SeqSBAIJ" PetscErrorCode MatGetValues_SeqSBAIJ(Mat A,int m,const int im[],int n,const int in[],PetscScalar v[]) { Mat_SeqSBAIJ *a = (Mat_SeqSBAIJ*)A->data; int *rp,k,low,high,t,row,nrow,i,col,l,*aj = a->j; int *ai = a->i,*ailen = a->ilen; int brow,bcol,ridx,cidx,bs=a->bs,bs2=a->bs2; MatScalar *ap,*aa = a->a,zero = 0.0; PetscFunctionBegin; for (k=0; k= A->m) SETERRQ2(PETSC_ERR_ARG_OUTOFRANGE,"Row too large: row %d max %d",row,A->m-1); rp = aj + ai[brow] ; ap = aa + bs2*ai[brow] ; nrow = ailen[brow]; for (l=0; l= A->n) SETERRQ2(PETSC_ERR_ARG_OUTOFRANGE,"Column too large: col %d max %d",in[l],A->n-1); col = in[l] ; bcol = col/bs; cidx = col%bs; ridx = row%bs; high = nrow; low = 0; /* assume unsorted */ while (high-low > 5) { t = (low+high)/2; if (rp[t] > bcol) high = t; else low = t; } for (i=low; i bcol) break; if (rp[i] == bcol) { *v++ = ap[bs2*i+bs*cidx+ridx]; goto finished; } } *v++ = zero; finished:; } } PetscFunctionReturn(0); } #undef __FUNCT__ #define __FUNCT__ "MatSetValuesBlocked_SeqSBAIJ" PetscErrorCode MatSetValuesBlocked_SeqSBAIJ(Mat A,int m,const int im[],int n,const int in[],const PetscScalar v[],InsertMode is) { Mat_SeqSBAIJ *a = (Mat_SeqSBAIJ*)A->data; PetscErrorCode ierr; int *rp,k,low,high,t,ii,jj,row,nrow,i,col,l,rmax,N,sorted=a->sorted; int *imax=a->imax,*ai=a->i,*ailen=a->ilen; int *aj=a->j,nonew=a->nonew,bs2=a->bs2,bs=a->bs,stepval; PetscTruth roworiented=a->roworiented; const MatScalar *value = v; MatScalar *ap,*aa = a->a,*bap; PetscFunctionBegin; if (roworiented) { stepval = (n-1)*bs; } else { stepval = (m-1)*bs; } for (k=0; k= a->mbs) SETERRQ2(PETSC_ERR_ARG_OUTOFRANGE,"Row too large: row %d max %d",row,a->mbs-1); #endif rp = aj + ai[row]; ap = aa + bs2*ai[row]; rmax = imax[row]; nrow = ailen[row]; low = 0; for (l=0; l= a->nbs) SETERRQ2(PETSC_ERR_ARG_OUTOFRANGE,"Column too large: col %d max %d",col,a->nbs-1); #endif if (col < row) continue; /* ignore lower triangular block */ if (roworiented) { value = v + k*(stepval+bs)*bs + l*bs; } else { value = v + l*(stepval+bs)*bs + k*bs; } if (!sorted) low = 0; high = nrow; while (high-low > 7) { t = (low+high)/2; if (rp[t] > col) high = t; else low = t; } for (i=low; i col) break; if (rp[i] == col) { bap = ap + bs2*i; if (roworiented) { if (is == ADD_VALUES) { for (ii=0; ii= rmax) { /* there is no extra room in row, therefore enlarge */ int new_nz = ai[a->mbs] + CHUNKSIZE,len,*new_i,*new_j; MatScalar *new_a; if (nonew == -2) SETERRQ2(PETSC_ERR_ARG_OUTOFRANGE,"Inserting a new nonzero (%d, %d) in the matrix", row, col); /* malloc new storage space */ len = new_nz*(sizeof(int)+bs2*sizeof(MatScalar))+(a->mbs+1)*sizeof(int); ierr = PetscMalloc(len,&new_a);CHKERRQ(ierr); new_j = (int*)(new_a + bs2*new_nz); new_i = new_j + new_nz; /* copy over old data into new slots */ for (ii=0; iimbs+1; ii++) {new_i[ii] = ai[ii]+CHUNKSIZE;} ierr = PetscMemcpy(new_j,aj,(ai[row]+nrow)*sizeof(int));CHKERRQ(ierr); len = (new_nz - CHUNKSIZE - ai[row] - nrow); ierr = PetscMemcpy(new_j+ai[row]+nrow+CHUNKSIZE,aj+ai[row]+nrow,len*sizeof(int));CHKERRQ(ierr); ierr = PetscMemcpy(new_a,aa,(ai[row]+nrow)*bs2*sizeof(MatScalar));CHKERRQ(ierr); ierr = PetscMemzero(new_a+bs2*(ai[row]+nrow),bs2*CHUNKSIZE*sizeof(MatScalar));CHKERRQ(ierr); ierr = PetscMemcpy(new_a+bs2*(ai[row]+nrow+CHUNKSIZE),aa+bs2*(ai[row]+nrow),bs2*len*sizeof(MatScalar));CHKERRQ(ierr); /* free up old matrix storage */ ierr = PetscFree(a->a);CHKERRQ(ierr); if (!a->singlemalloc) { ierr = PetscFree(a->i);CHKERRQ(ierr); ierr = PetscFree(a->j);CHKERRQ(ierr); } aa = a->a = new_a; ai = a->i = new_i; aj = a->j = new_j; a->singlemalloc = PETSC_TRUE; rp = aj + ai[row]; ap = aa + bs2*ai[row]; rmax = imax[row] = imax[row] + CHUNKSIZE; PetscLogObjectMemory(A,CHUNKSIZE*(sizeof(int) + bs2*sizeof(MatScalar))); a->maxnz += bs2*CHUNKSIZE; a->reallocs++; a->nz++; } N = nrow++ - 1; /* shift up all the later entries in this row */ for (ii=N; ii>=i; ii--) { rp[ii+1] = rp[ii]; ierr = PetscMemcpy(ap+bs2*(ii+1),ap+bs2*(ii),bs2*sizeof(MatScalar));CHKERRQ(ierr); } if (N >= i) { ierr = PetscMemzero(ap+bs2*i,bs2*sizeof(MatScalar));CHKERRQ(ierr); } rp[i] = col; bap = ap + bs2*i; if (roworiented) { for (ii=0; iidata; PetscErrorCode ierr; int fshift = 0,i,j,*ai = a->i,*aj = a->j,*imax = a->imax; int m = A->m,*ip,N,*ailen = a->ilen; int mbs = a->mbs,bs2 = a->bs2,rmax = 0; MatScalar *aa = a->a,*ap; PetscFunctionBegin; if (mode == MAT_FLUSH_ASSEMBLY) PetscFunctionReturn(0); if (m) rmax = ailen[0]; for (i=1; inz = ai[mbs]; /* diagonals may have moved, reset it */ if (a->diag) { ierr = PetscMemcpy(a->diag,ai,(mbs+1)*sizeof(int));CHKERRQ(ierr); } PetscLogInfo(A,"MatAssemblyEnd_SeqSBAIJ:Matrix size: %d X %d, block size %d; storage space: %d unneeded, %d used\n", m,A->m,a->bs,fshift*bs2,a->nz*bs2); PetscLogInfo(A,"MatAssemblyEnd_SeqSBAIJ:Number of mallocs during MatSetValues is %d\n", a->reallocs); PetscLogInfo(A,"MatAssemblyEnd_SeqSBAIJ:Most nonzeros blocks in any row is %d\n",rmax); a->reallocs = 0; A->info.nz_unneeded = (PetscReal)fshift*bs2; PetscFunctionReturn(0); } /* This function returns an array of flags which indicate the locations of contiguous blocks that should be zeroed. for eg: if bs = 3 and is = [0,1,2,3,5,6,7,8,9] then the resulting sizes = [3,1,1,3,1] correspondig to sets [(0,1,2),(3),(5),(6,7,8),(9)] Assume: sizes should be long enough to hold all the values. */ #undef __FUNCT__ #define __FUNCT__ "MatZeroRows_SeqSBAIJ_Check_Blocks" PetscErrorCode MatZeroRows_SeqSBAIJ_Check_Blocks(int idx[],int n,int bs,int sizes[], int *bs_max) { int i,j,k,row; PetscTruth flg; PetscFunctionBegin; for (i=0,j=0; i n) { /* Beginning of a block, but complete block doesn't exist (at idx end) */ sizes[j] = 1; /* Also makes sure atleast 'bs' values exist for next else */ i++; } else { /* Begining of the block, so check if the complete block exists */ flg = PETSC_TRUE; for (k=1; kj input by user is ingored. */ #undef __FUNCT__ #define __FUNCT__ "MatSetValues_SeqSBAIJ" PetscErrorCode MatSetValues_SeqSBAIJ(Mat A,int m,const int im[],int n,const int in[],const PetscScalar v[],InsertMode is) { Mat_SeqSBAIJ *a = (Mat_SeqSBAIJ*)A->data; PetscErrorCode ierr; int *rp,k,low,high,t,ii,row,nrow,i,col,l,rmax,N,sorted=a->sorted; int *imax=a->imax,*ai=a->i,*ailen=a->ilen,roworiented=a->roworiented; int *aj=a->j,nonew=a->nonew,bs=a->bs,brow,bcol; int ridx,cidx,bs2=a->bs2; MatScalar *ap,value,*aa=a->a,*bap; PetscFunctionBegin; for (k=0; k= A->m) SETERRQ2(PETSC_ERR_ARG_OUTOFRANGE,"Row too large: row %d max %d",row,A->m-1); #endif rp = aj + ai[brow]; /*ptr to beginning of column value of the row block*/ ap = aa + bs2*ai[brow]; /*ptr to beginning of element value of the row block*/ rmax = imax[brow]; /* maximum space allocated for this row */ nrow = ailen[brow]; /* actual length of this row */ low = 0; for (l=0; l= A->m) SETERRQ2(PETSC_ERR_ARG_OUTOFRANGE,"Column too large: col %d max %d",in[l],A->m-1); #endif col = in[l]; bcol = col/bs; /* block col number */ if (brow <= bcol){ ridx = row % bs; cidx = col % bs; /*row and col index inside the block */ if ((brow==bcol && ridx<=cidx) || (brow 7) { t = (low+high)/2; if (rp[t] > bcol) high = t; else low = t; } for (i=low; i bcol) break; if (rp[i] == bcol) { bap = ap + bs2*i + bs*cidx + ridx; if (is == ADD_VALUES) *bap += value; else *bap = value; /* for diag block, add/insert its symmetric element a(cidx,ridx) */ if (brow == bcol && ridx < cidx){ bap = ap + bs2*i + bs*ridx + cidx; if (is == ADD_VALUES) *bap += value; else *bap = value; } goto noinsert1; } } if (nonew == 1) goto noinsert1; else if (nonew == -1) SETERRQ2(PETSC_ERR_ARG_OUTOFRANGE,"Inserting a new nonzero (%d, %d) in the matrix", row, col); if (nrow >= rmax) { /* there is no extra room in row, therefore enlarge */ int new_nz = ai[a->mbs] + CHUNKSIZE,len,*new_i,*new_j; MatScalar *new_a; if (nonew == -2) SETERRQ2(PETSC_ERR_ARG_OUTOFRANGE,"Inserting a new nonzero (%d, %d) in the matrix", row, col); /* Malloc new storage space */ len = new_nz*(sizeof(int)+bs2*sizeof(MatScalar))+(a->mbs+1)*sizeof(int); ierr = PetscMalloc(len,&new_a);CHKERRQ(ierr); new_j = (int*)(new_a + bs2*new_nz); new_i = new_j + new_nz; /* copy over old data into new slots */ for (ii=0; iimbs+1; ii++) {new_i[ii] = ai[ii]+CHUNKSIZE;} ierr = PetscMemcpy(new_j,aj,(ai[brow]+nrow)*sizeof(int));CHKERRQ(ierr); len = (new_nz - CHUNKSIZE - ai[brow] - nrow); ierr = PetscMemcpy(new_j+ai[brow]+nrow+CHUNKSIZE,aj+ai[brow]+nrow,len*sizeof(int));CHKERRQ(ierr); ierr = PetscMemcpy(new_a,aa,(ai[brow]+nrow)*bs2*sizeof(MatScalar));CHKERRQ(ierr); ierr = PetscMemzero(new_a+bs2*(ai[brow]+nrow),bs2*CHUNKSIZE*sizeof(MatScalar));CHKERRQ(ierr); ierr = PetscMemcpy(new_a+bs2*(ai[brow]+nrow+CHUNKSIZE),aa+bs2*(ai[brow]+nrow),bs2*len*sizeof(MatScalar));CHKERRQ(ierr); /* free up old matrix storage */ ierr = PetscFree(a->a);CHKERRQ(ierr); if (!a->singlemalloc) { ierr = PetscFree(a->i);CHKERRQ(ierr); ierr = PetscFree(a->j);CHKERRQ(ierr); } aa = a->a = new_a; ai = a->i = new_i; aj = a->j = new_j; a->singlemalloc = PETSC_TRUE; rp = aj + ai[brow]; ap = aa + bs2*ai[brow]; rmax = imax[brow] = imax[brow] + CHUNKSIZE; PetscLogObjectMemory(A,CHUNKSIZE*(sizeof(int) + bs2*sizeof(MatScalar))); a->maxnz += bs2*CHUNKSIZE; a->reallocs++; a->nz++; } N = nrow++ - 1; /* shift up all the later entries in this row */ for (ii=N; ii>=i; ii--) { rp[ii+1] = rp[ii]; ierr = PetscMemcpy(ap+bs2*(ii+1),ap+bs2*(ii),bs2*sizeof(MatScalar));CHKERRQ(ierr); } if (N>=i) { ierr = PetscMemzero(ap+bs2*i,bs2*sizeof(MatScalar));CHKERRQ(ierr); } rp[i] = bcol; ap[bs2*i + bs*cidx + ridx] = value; noinsert1:; low = i; /* } */ } } /* end of if .. if.. */ } /* end of loop over added columns */ ailen[brow] = nrow; } /* end of loop over added rows */ PetscFunctionReturn(0); } EXTERN PetscErrorCode MatCholeskyFactorSymbolic_SeqSBAIJ(Mat,IS,MatFactorInfo*,Mat*); EXTERN PetscErrorCode MatCholeskyFactor_SeqSBAIJ(Mat,IS,MatFactorInfo*); EXTERN PetscErrorCode MatIncreaseOverlap_SeqSBAIJ(Mat,int,IS[],int); EXTERN PetscErrorCode MatGetSubMatrix_SeqSBAIJ(Mat,IS,IS,int,MatReuse,Mat*); EXTERN PetscErrorCode MatGetSubMatrices_SeqSBAIJ(Mat,int,const IS[],const IS[],MatReuse,Mat*[]); EXTERN PetscErrorCode MatMultTranspose_SeqSBAIJ(Mat,Vec,Vec); EXTERN PetscErrorCode MatMultTransposeAdd_SeqSBAIJ(Mat,Vec,Vec,Vec); EXTERN PetscErrorCode MatScale_SeqSBAIJ(const PetscScalar*,Mat); EXTERN PetscErrorCode MatNorm_SeqSBAIJ(Mat,NormType,PetscReal *); EXTERN PetscErrorCode MatEqual_SeqSBAIJ(Mat,Mat,PetscTruth*); EXTERN PetscErrorCode MatGetDiagonal_SeqSBAIJ(Mat,Vec); EXTERN PetscErrorCode MatDiagonalScale_SeqSBAIJ(Mat,Vec,Vec); EXTERN PetscErrorCode MatGetInfo_SeqSBAIJ(Mat,MatInfoType,MatInfo *); EXTERN PetscErrorCode MatZeroEntries_SeqSBAIJ(Mat); EXTERN PetscErrorCode MatGetRowMax_SeqSBAIJ(Mat,Vec); EXTERN PetscErrorCode MatSolve_SeqSBAIJ_N(Mat,Vec,Vec); EXTERN PetscErrorCode MatSolve_SeqSBAIJ_1(Mat,Vec,Vec); EXTERN PetscErrorCode MatSolve_SeqSBAIJ_2(Mat,Vec,Vec); EXTERN PetscErrorCode MatSolve_SeqSBAIJ_3(Mat,Vec,Vec); EXTERN PetscErrorCode MatSolve_SeqSBAIJ_4(Mat,Vec,Vec); EXTERN PetscErrorCode MatSolve_SeqSBAIJ_5(Mat,Vec,Vec); EXTERN PetscErrorCode MatSolve_SeqSBAIJ_6(Mat,Vec,Vec); EXTERN PetscErrorCode MatSolve_SeqSBAIJ_7(Mat,Vec,Vec); EXTERN PetscErrorCode MatSolveTranspose_SeqSBAIJ_7(Mat,Vec,Vec); EXTERN PetscErrorCode MatSolveTranspose_SeqSBAIJ_6(Mat,Vec,Vec); EXTERN PetscErrorCode MatSolveTranspose_SeqSBAIJ_5(Mat,Vec,Vec); EXTERN PetscErrorCode MatSolveTranspose_SeqSBAIJ_4(Mat,Vec,Vec); EXTERN PetscErrorCode MatSolveTranspose_SeqSBAIJ_3(Mat,Vec,Vec); EXTERN PetscErrorCode MatSolveTranspose_SeqSBAIJ_2(Mat,Vec,Vec); EXTERN PetscErrorCode MatSolveTranspose_SeqSBAIJ_1(Mat,Vec,Vec); EXTERN PetscErrorCode MatSolves_SeqSBAIJ_1(Mat,Vecs,Vecs); EXTERN PetscErrorCode MatSolve_SeqSBAIJ_1_NaturalOrdering(Mat,Vec,Vec); EXTERN PetscErrorCode MatSolve_SeqSBAIJ_2_NaturalOrdering(Mat,Vec,Vec); EXTERN PetscErrorCode MatSolve_SeqSBAIJ_3_NaturalOrdering(Mat,Vec,Vec); EXTERN PetscErrorCode MatSolve_SeqSBAIJ_4_NaturalOrdering(Mat,Vec,Vec); EXTERN PetscErrorCode MatSolve_SeqSBAIJ_5_NaturalOrdering(Mat,Vec,Vec); EXTERN PetscErrorCode MatSolve_SeqSBAIJ_6_NaturalOrdering(Mat,Vec,Vec); EXTERN PetscErrorCode MatSolve_SeqSBAIJ_7_NaturalOrdering(Mat,Vec,Vec); EXTERN PetscErrorCode MatSolve_SeqSBAIJ_N_NaturalOrdering(Mat,Vec,Vec); EXTERN PetscErrorCode MatCholeskyFactorNumeric_SeqSBAIJ_N(Mat,Mat*); EXTERN PetscErrorCode MatCholeskyFactorNumeric_SeqSBAIJ_1(Mat,Mat*); EXTERN PetscErrorCode MatCholeskyFactorNumeric_SeqSBAIJ_2(Mat,Mat*); EXTERN PetscErrorCode MatCholeskyFactorNumeric_SeqSBAIJ_3(Mat,Mat*); EXTERN PetscErrorCode MatCholeskyFactorNumeric_SeqSBAIJ_4(Mat,Mat*); EXTERN PetscErrorCode MatCholeskyFactorNumeric_SeqSBAIJ_5(Mat,Mat*); EXTERN PetscErrorCode MatCholeskyFactorNumeric_SeqSBAIJ_6(Mat,Mat*); EXTERN PetscErrorCode MatCholeskyFactorNumeric_SeqSBAIJ_7(Mat,Mat*); EXTERN PetscErrorCode MatGetInertia_SeqSBAIJ(Mat,int*,int*,int*); EXTERN PetscErrorCode MatMult_SeqSBAIJ_1(Mat,Vec,Vec); EXTERN PetscErrorCode MatMult_SeqSBAIJ_2(Mat,Vec,Vec); EXTERN PetscErrorCode MatMult_SeqSBAIJ_3(Mat,Vec,Vec); EXTERN PetscErrorCode MatMult_SeqSBAIJ_4(Mat,Vec,Vec); EXTERN PetscErrorCode MatMult_SeqSBAIJ_5(Mat,Vec,Vec); EXTERN PetscErrorCode MatMult_SeqSBAIJ_6(Mat,Vec,Vec); EXTERN PetscErrorCode MatMult_SeqSBAIJ_7(Mat,Vec,Vec); EXTERN PetscErrorCode MatMult_SeqSBAIJ_N(Mat,Vec,Vec); EXTERN PetscErrorCode MatMultAdd_SeqSBAIJ_1(Mat,Vec,Vec,Vec); EXTERN PetscErrorCode MatMultAdd_SeqSBAIJ_2(Mat,Vec,Vec,Vec); EXTERN PetscErrorCode MatMultAdd_SeqSBAIJ_3(Mat,Vec,Vec,Vec); EXTERN PetscErrorCode MatMultAdd_SeqSBAIJ_4(Mat,Vec,Vec,Vec); EXTERN PetscErrorCode MatMultAdd_SeqSBAIJ_5(Mat,Vec,Vec,Vec); EXTERN PetscErrorCode MatMultAdd_SeqSBAIJ_6(Mat,Vec,Vec,Vec); EXTERN PetscErrorCode MatMultAdd_SeqSBAIJ_7(Mat,Vec,Vec,Vec); EXTERN PetscErrorCode MatMultAdd_SeqSBAIJ_N(Mat,Vec,Vec,Vec); #ifdef HAVE_MatICCFactor /* modified from MatILUFactor_SeqSBAIJ, needs further work! */ #undef __FUNCT__ #define __FUNCT__ "MatICCFactor_SeqSBAIJ" PetscErrorCode MatICCFactor_SeqSBAIJ(Mat inA,IS row,MatFactorInfo *info) { Mat_SeqSBAIJ *a = (Mat_SeqSBAIJ*)inA->data; Mat outA; PetscErrorCode ierr; PetscTruth row_identity,col_identity; PetscFunctionBegin; /* if (level != 0) SETERRQ(PETSC_ERR_SUP,"Only levels = 0 supported for in-place ILU"); ierr = ISIdentity(row,&row_identity);CHKERRQ(ierr); ierr = ISIdentity(col,&col_identity);CHKERRQ(ierr); if (!row_identity || !col_identity) { SETERRQ(1,"Row and column permutations must be identity for in-place ICC"); } */ outA = inA; inA->factor = FACTOR_CHOLESKY; if (!a->diag) { ierr = MatMarkDiagonal_SeqSBAIJ(inA);CHKERRQ(ierr); } /* Blocksize 2, 3, 4, 5, 6 and 7 have a special faster factorization/solver for ILU(0) factorization with natural ordering */ switch (a->bs) { case 1: inA->ops->solve = MatSolve_SeqSBAIJ_1_NaturalOrdering; inA->ops->solvetranspose = MatSolve_SeqSBAIJ_1_NaturalOrdering; inA->ops->solves = MatSolves_SeqSBAIJ_1; PetscLoginfo(inA,"MatICCFactor_SeqSBAIJ:Using special in-place natural ordering solvetrans BS=1\n"); case 2: inA->ops->lufactornumeric = MatCholeskyFactorNumeric_SeqSBAIJ_2_NaturalOrdering; inA->ops->solve = MatSolve_SeqSBAIJ_2_NaturalOrdering; inA->ops->solvetranspose = MatSolve_SeqSBAIJ_2_NaturalOrdering; PetscLogInfo(inA,"MatICCFactor_SeqSBAIJ:Using special in-place natural ordering factor and solve BS=2\n"); break; case 3: inA->ops->lufactornumeric = MatCholeskyFactorNumeric_SeqSBAIJ_3_NaturalOrdering; inA->ops->solve = MatSolve_SeqSBAIJ_3_NaturalOrdering; inA->ops->solvetranspose = MatSolve_SeqSBAIJ_3_NaturalOrdering; PetscLogInfo(inA,"MatICCFactor_SeqSBAIJ:Using special in-place natural ordering factor and solve BS=3\n"); break; case 4: inA->ops->lufactornumeric = MatCholeskyFactorNumeric_SeqSBAIJ_4_NaturalOrdering; inA->ops->solve = MatSolve_SeqSBAIJ_4_NaturalOrdering; inA->ops->solvetranspose = MatSolve_SeqSBAIJ_4_NaturalOrdering; PetscLogInfo(inA,"MatICCFactor_SeqSBAIJ:Using special in-place natural ordering factor and solve BS=4\n"); break; case 5: inA->ops->lufactornumeric = MatCholeskyFactorNumeric_SeqSBAIJ_5_NaturalOrdering; inA->ops->solve = MatSolve_SeqSBAIJ_5_NaturalOrdering; inA->ops->solvetranspose = MatSolve_SeqSBAIJ_5_NaturalOrdering; PetscLogInfo(inA,"MatICCFactor_SeqSBAIJ:Using special in-place natural ordering factor and solve BS=5\n"); break; case 6: inA->ops->lufactornumeric = MatCholeskyFactorNumeric_SeqSBAIJ_6_NaturalOrdering; inA->ops->solve = MatSolve_SeqSBAIJ_6_NaturalOrdering; inA->ops->solvetranspose = MatSolve_SeqSBAIJ_6_NaturalOrdering; PetscLogInfo(inA,"MatICCFactor_SeqSBAIJ:Using special in-place natural ordering factor and solve BS=6\n"); break; case 7: inA->ops->lufactornumeric = MatCholeskyFactorNumeric_SeqSBAIJ_7_NaturalOrdering; inA->ops->solvetranspose = MatSolve_SeqSBAIJ_7_NaturalOrdering; inA->ops->solve = MatSolve_SeqSBAIJ_7_NaturalOrdering; PetscLogInfo(inA,"MatICCFactor_SeqSBAIJ:Using special in-place natural ordering factor and solve BS=7\n"); break; default: a->row = row; a->icol = col; ierr = PetscObjectReference((PetscObject)row);CHKERRQ(ierr); ierr = PetscObjectReference((PetscObject)col);CHKERRQ(ierr); /* Create the invert permutation so that it can be used in MatLUFactorNumeric() */ ierr = ISInvertPermutation(col,PETSC_DECIDE, &(a->icol));CHKERRQ(ierr); PetscLogObjectParent(inA,a->icol); if (!a->solve_work) { ierr = PetscMalloc((A->m+a->bs)*sizeof(PetscScalar),&a->solve_work);CHKERRQ(ierr); PetscLogObjectMemory(inA,(A->m+a->bs)*sizeof(PetscScalar)); } } ierr = MatCholeskyFactorNumeric(inA,&outA);CHKERRQ(ierr); PetscFunctionReturn(0); } #endif #undef __FUNCT__ #define __FUNCT__ "MatPrintHelp_SeqSBAIJ" PetscErrorCode MatPrintHelp_SeqSBAIJ(Mat A) { static PetscTruth called = PETSC_FALSE; MPI_Comm comm = A->comm; PetscErrorCode ierr; PetscFunctionBegin; if (called) {PetscFunctionReturn(0);} else called = PETSC_TRUE; ierr = (*PetscHelpPrintf)(comm," Options for MATSEQSBAIJ and MATMPISBAIJ matrix formats (the defaults):\n");CHKERRQ(ierr); ierr = (*PetscHelpPrintf)(comm," -mat_block_size \n");CHKERRQ(ierr); PetscFunctionReturn(0); } EXTERN_C_BEGIN #undef __FUNCT__ #define __FUNCT__ "MatSeqSBAIJSetColumnIndices_SeqSBAIJ" PetscErrorCode MatSeqSBAIJSetColumnIndices_SeqSBAIJ(Mat mat,int *indices) { Mat_SeqSBAIJ *baij = (Mat_SeqSBAIJ *)mat->data; int i,nz,n; PetscFunctionBegin; nz = baij->maxnz; n = mat->n; for (i=0; ij[i] = indices[i]; } baij->nz = nz; for (i=0; iilen[i] = baij->imax[i]; } PetscFunctionReturn(0); } EXTERN_C_END #undef __FUNCT__ #define __FUNCT__ "MatSeqSBAIJSetColumnIndices" /*@ MatSeqSBAIJSetColumnIndices - Set the column indices for all the rows in the matrix. Input Parameters: + mat - the SeqSBAIJ matrix - indices - the column indices Level: advanced Notes: This can be called if you have precomputed the nonzero structure of the matrix and want to provide it to the matrix object to improve the performance of the MatSetValues() operation. You MUST have set the correct numbers of nonzeros per row in the call to MatCreateSeqSBAIJ(). MUST be called before any calls to MatSetValues() .seealso: MatCreateSeqSBAIJ @*/ PetscErrorCode MatSeqSBAIJSetColumnIndices(Mat mat,int *indices) { PetscErrorCode ierr,(*f)(Mat,int *); PetscFunctionBegin; PetscValidHeaderSpecific(mat,MAT_COOKIE,1); PetscValidPointer(indices,2); ierr = PetscObjectQueryFunction((PetscObject)mat,"MatSeqSBAIJSetColumnIndices_C",(void (**)(void))&f);CHKERRQ(ierr); if (f) { ierr = (*f)(mat,indices);CHKERRQ(ierr); } else { SETERRQ(1,"Wrong type of matrix to set column indices"); } PetscFunctionReturn(0); } #undef __FUNCT__ #define __FUNCT__ "MatSetUpPreallocation_SeqSBAIJ" PetscErrorCode MatSetUpPreallocation_SeqSBAIJ(Mat A) { PetscErrorCode ierr; PetscFunctionBegin; ierr = MatSeqSBAIJSetPreallocation(A,1,PETSC_DEFAULT,0);CHKERRQ(ierr); PetscFunctionReturn(0); } #undef __FUNCT__ #define __FUNCT__ "MatGetArray_SeqSBAIJ" PetscErrorCode MatGetArray_SeqSBAIJ(Mat A,PetscScalar *array[]) { Mat_SeqSBAIJ *a = (Mat_SeqSBAIJ*)A->data; PetscFunctionBegin; *array = a->a; PetscFunctionReturn(0); } #undef __FUNCT__ #define __FUNCT__ "MatRestoreArray_SeqSBAIJ" PetscErrorCode MatRestoreArray_SeqSBAIJ(Mat A,PetscScalar *array[]) { PetscFunctionBegin; PetscFunctionReturn(0); } #include "petscblaslapack.h" #undef __FUNCT__ #define __FUNCT__ "MatAXPY_SeqSBAIJ" PetscErrorCode MatAXPY_SeqSBAIJ(const PetscScalar *a,Mat X,Mat Y,MatStructure str) { Mat_SeqSBAIJ *x=(Mat_SeqSBAIJ *)X->data, *y=(Mat_SeqSBAIJ *)Y->data; PetscErrorCode ierr; int one=1,i,bs=y->bs,bs2,j; PetscFunctionBegin; if (str == SAME_NONZERO_PATTERN) { BLaxpy_(&x->nz,(PetscScalar*)a,x->a,&one,y->a,&one); } else if (str == SUBSET_NONZERO_PATTERN) { /* nonzeros of X is a subset of Y's */ if (y->xtoy && y->XtoY != X) { ierr = PetscFree(y->xtoy);CHKERRQ(ierr); ierr = MatDestroy(y->XtoY);CHKERRQ(ierr); } if (!y->xtoy) { /* get xtoy */ ierr = MatAXPYGetxtoy_Private(x->mbs,x->i,x->j,PETSC_NULL, y->i,y->j,PETSC_NULL, &y->xtoy);CHKERRQ(ierr); y->XtoY = X; } bs2 = bs*bs; for (i=0; inz; i++) { j = 0; while (j < bs2){ y->a[bs2*y->xtoy[i]+j] += (*a)*(x->a[bs2*i+j]); j++; } } PetscLogInfo(0,"MatAXPY_SeqSBAIJ: ratio of nnz_s(X)/nnz_s(Y): %d/%d = %g\n",bs2*x->nz,bs2*y->nz,(PetscReal)(bs2*x->nz)/(bs2*y->nz)); } else { ierr = MatAXPY_Basic(a,X,Y,str);CHKERRQ(ierr); } PetscFunctionReturn(0); } #undef __FUNCT__ #define __FUNCT__ "MatIsSymmetric_SeqSBAIJ" PetscErrorCode MatIsSymmetric_SeqSBAIJ(Mat A,PetscReal tol,PetscTruth *flg) { PetscFunctionBegin; *flg = PETSC_TRUE; PetscFunctionReturn(0); } #undef __FUNCT__ #define __FUNCT__ "MatIsStructurallySymmetric_SeqSBAIJ" PetscErrorCode MatIsStructurallySymmetric_SeqSBAIJ(Mat A,PetscTruth *flg) { PetscFunctionBegin; *flg = PETSC_TRUE; PetscFunctionReturn(0); } #undef __FUNCT__ #define __FUNCT__ "MatIsHermitian_SeqSBAIJ" PetscErrorCode MatIsHermitian_SeqSBAIJ(Mat A,PetscTruth *flg) { PetscFunctionBegin; *flg = PETSC_FALSE; PetscFunctionReturn(0); } /* -------------------------------------------------------------------*/ static struct _MatOps MatOps_Values = {MatSetValues_SeqSBAIJ, MatGetRow_SeqSBAIJ, MatRestoreRow_SeqSBAIJ, MatMult_SeqSBAIJ_N, /* 4*/ MatMultAdd_SeqSBAIJ_N, MatMultTranspose_SeqSBAIJ, MatMultTransposeAdd_SeqSBAIJ, MatSolve_SeqSBAIJ_N, 0, 0, /*10*/ 0, 0, MatCholeskyFactor_SeqSBAIJ, MatRelax_SeqSBAIJ, MatTranspose_SeqSBAIJ, /*15*/ MatGetInfo_SeqSBAIJ, MatEqual_SeqSBAIJ, MatGetDiagonal_SeqSBAIJ, MatDiagonalScale_SeqSBAIJ, MatNorm_SeqSBAIJ, /*20*/ 0, MatAssemblyEnd_SeqSBAIJ, 0, MatSetOption_SeqSBAIJ, MatZeroEntries_SeqSBAIJ, /*25*/ MatZeroRows_SeqSBAIJ, 0, 0, MatCholeskyFactorSymbolic_SeqSBAIJ, MatCholeskyFactorNumeric_SeqSBAIJ_N, /*30*/ MatSetUpPreallocation_SeqSBAIJ, 0, MatICCFactorSymbolic_SeqSBAIJ, MatGetArray_SeqSBAIJ, MatRestoreArray_SeqSBAIJ, /*35*/ MatDuplicate_SeqSBAIJ, 0, 0, 0, 0, /*40*/ MatAXPY_SeqSBAIJ, MatGetSubMatrices_SeqSBAIJ, MatIncreaseOverlap_SeqSBAIJ, MatGetValues_SeqSBAIJ, 0, /*45*/ MatPrintHelp_SeqSBAIJ, MatScale_SeqSBAIJ, 0, 0, 0, /*50*/ MatGetBlockSize_SeqSBAIJ, MatGetRowIJ_SeqSBAIJ, MatRestoreRowIJ_SeqSBAIJ, 0, 0, /*55*/ 0, 0, 0, 0, MatSetValuesBlocked_SeqSBAIJ, /*60*/ MatGetSubMatrix_SeqSBAIJ, 0, 0, MatGetPetscMaps_Petsc, 0, /*65*/ 0, 0, 0, 0, 0, /*70*/ MatGetRowMax_SeqSBAIJ, 0, 0, 0, 0, /*75*/ 0, 0, 0, 0, 0, /*80*/ 0, 0, 0, #if !defined(PETSC_USE_COMPLEX) MatGetInertia_SeqSBAIJ, #else 0, #endif /*85*/ MatLoad_SeqSBAIJ, MatIsSymmetric_SeqSBAIJ, MatIsStructurallySymmetric_SeqSBAIJ, MatIsHermitian_SeqSBAIJ }; EXTERN_C_BEGIN #undef __FUNCT__ #define __FUNCT__ "MatStoreValues_SeqSBAIJ" PetscErrorCode MatStoreValues_SeqSBAIJ(Mat mat) { Mat_SeqSBAIJ *aij = (Mat_SeqSBAIJ *)mat->data; int nz = aij->i[mat->m]*aij->bs*aij->bs2; PetscErrorCode ierr; PetscFunctionBegin; if (aij->nonew != 1) { SETERRQ(1,"Must call MatSetOption(A,MAT_NO_NEW_NONZERO_LOCATIONS);first"); } /* allocate space for values if not already there */ if (!aij->saved_values) { ierr = PetscMalloc((nz+1)*sizeof(PetscScalar),&aij->saved_values);CHKERRQ(ierr); } /* copy values over */ ierr = PetscMemcpy(aij->saved_values,aij->a,nz*sizeof(PetscScalar));CHKERRQ(ierr); PetscFunctionReturn(0); } EXTERN_C_END EXTERN_C_BEGIN #undef __FUNCT__ #define __FUNCT__ "MatRetrieveValues_SeqSBAIJ" PetscErrorCode MatRetrieveValues_SeqSBAIJ(Mat mat) { Mat_SeqSBAIJ *aij = (Mat_SeqSBAIJ *)mat->data; PetscErrorCode ierr; int nz = aij->i[mat->m]*aij->bs*aij->bs2; PetscFunctionBegin; if (aij->nonew != 1) { SETERRQ(1,"Must call MatSetOption(A,MAT_NO_NEW_NONZERO_LOCATIONS);first"); } if (!aij->saved_values) { SETERRQ(1,"Must call MatStoreValues(A);first"); } /* copy values over */ ierr = PetscMemcpy(aij->a,aij->saved_values,nz*sizeof(PetscScalar));CHKERRQ(ierr); PetscFunctionReturn(0); } EXTERN_C_END EXTERN_C_BEGIN #undef __FUNCT__ #define __FUNCT__ "MatSeqSBAIJSetPreallocation_SeqSBAIJ" PetscErrorCode MatSeqSBAIJSetPreallocation_SeqSBAIJ(Mat B,int bs,int nz,int *nnz) { Mat_SeqSBAIJ *b = (Mat_SeqSBAIJ*)B->data; PetscErrorCode ierr; int i,len,mbs,bs2; PetscTruth flg; PetscFunctionBegin; B->preallocated = PETSC_TRUE; ierr = PetscOptionsGetInt(B->prefix,"-mat_block_size",&bs,PETSC_NULL);CHKERRQ(ierr); mbs = B->m/bs; bs2 = bs*bs; if (mbs*bs != B->m) { SETERRQ(PETSC_ERR_ARG_SIZ,"Number rows, cols must be divisible by blocksize"); } if (nz == PETSC_DEFAULT || nz == PETSC_DECIDE) nz = 3; if (nz < 0) SETERRQ1(PETSC_ERR_ARG_OUTOFRANGE,"nz cannot be less than 0: value %d",nz); if (nnz) { for (i=0; i mbs) SETERRQ3(PETSC_ERR_ARG_OUTOFRANGE,"nnz cannot be greater than block row length: local row %d value %d rowlength %d",i,nnz[i],mbs); } } ierr = PetscOptionsHasName(B->prefix,"-mat_no_unroll",&flg);CHKERRQ(ierr); if (!flg) { switch (bs) { case 1: B->ops->choleskyfactornumeric = MatCholeskyFactorNumeric_SeqSBAIJ_1; B->ops->solve = MatSolve_SeqSBAIJ_1; B->ops->solves = MatSolves_SeqSBAIJ_1; B->ops->solvetranspose = MatSolveTranspose_SeqSBAIJ_1; B->ops->mult = MatMult_SeqSBAIJ_1; B->ops->multadd = MatMultAdd_SeqSBAIJ_1; break; case 2: B->ops->choleskyfactornumeric = MatCholeskyFactorNumeric_SeqSBAIJ_2; B->ops->solve = MatSolve_SeqSBAIJ_2; B->ops->solvetranspose = MatSolveTranspose_SeqSBAIJ_2; B->ops->mult = MatMult_SeqSBAIJ_2; B->ops->multadd = MatMultAdd_SeqSBAIJ_2; break; case 3: B->ops->choleskyfactornumeric = MatCholeskyFactorNumeric_SeqSBAIJ_3; B->ops->solve = MatSolve_SeqSBAIJ_3; B->ops->solvetranspose = MatSolveTranspose_SeqSBAIJ_3; B->ops->mult = MatMult_SeqSBAIJ_3; B->ops->multadd = MatMultAdd_SeqSBAIJ_3; break; case 4: B->ops->choleskyfactornumeric = MatCholeskyFactorNumeric_SeqSBAIJ_4; B->ops->solve = MatSolve_SeqSBAIJ_4; B->ops->solvetranspose = MatSolveTranspose_SeqSBAIJ_4; B->ops->mult = MatMult_SeqSBAIJ_4; B->ops->multadd = MatMultAdd_SeqSBAIJ_4; break; case 5: B->ops->choleskyfactornumeric = MatCholeskyFactorNumeric_SeqSBAIJ_5; B->ops->solve = MatSolve_SeqSBAIJ_5; B->ops->solvetranspose = MatSolveTranspose_SeqSBAIJ_5; B->ops->mult = MatMult_SeqSBAIJ_5; B->ops->multadd = MatMultAdd_SeqSBAIJ_5; break; case 6: B->ops->choleskyfactornumeric = MatCholeskyFactorNumeric_SeqSBAIJ_6; B->ops->solve = MatSolve_SeqSBAIJ_6; B->ops->solvetranspose = MatSolveTranspose_SeqSBAIJ_6; B->ops->mult = MatMult_SeqSBAIJ_6; B->ops->multadd = MatMultAdd_SeqSBAIJ_6; break; case 7: B->ops->choleskyfactornumeric = MatCholeskyFactorNumeric_SeqSBAIJ_7; B->ops->solve = MatSolve_SeqSBAIJ_7; B->ops->solvetranspose = MatSolveTranspose_SeqSBAIJ_7; B->ops->mult = MatMult_SeqSBAIJ_7; B->ops->multadd = MatMultAdd_SeqSBAIJ_7; break; } } b->mbs = mbs; b->nbs = mbs; ierr = PetscMalloc((mbs+1)*sizeof(int),&b->imax);CHKERRQ(ierr); if (!nnz) { if (nz == PETSC_DEFAULT || nz == PETSC_DECIDE) nz = 5; else if (nz <= 0) nz = 1; for (i=0; iimax[i] = nz; } nz = nz*mbs; /* total nz */ } else { nz = 0; for (i=0; iimax[i] = nnz[i]; nz += nnz[i];} } /* nz=(nz+mbs)/2; */ /* total diagonal and superdiagonal nonzero blocks */ /* allocate the matrix space */ len = nz*sizeof(int) + nz*bs2*sizeof(MatScalar) + (B->m+1)*sizeof(int); ierr = PetscMalloc(len,&b->a);CHKERRQ(ierr); ierr = PetscMemzero(b->a,nz*bs2*sizeof(MatScalar));CHKERRQ(ierr); b->j = (int*)(b->a + nz*bs2); ierr = PetscMemzero(b->j,nz*sizeof(int));CHKERRQ(ierr); b->i = b->j + nz; b->singlemalloc = PETSC_TRUE; /* pointer to beginning of each row */ b->i[0] = 0; for (i=1; ii[i] = b->i[i-1] + b->imax[i-1]; } /* b->ilen will count nonzeros in each block row so far. */ ierr = PetscMalloc((mbs+1)*sizeof(int),&b->ilen);CHKERRQ(ierr); PetscLogObjectMemory(B,len+2*(mbs+1)*sizeof(int)+sizeof(struct _p_Mat)+sizeof(Mat_SeqSBAIJ)); for (i=0; iilen[i] = 0;} b->bs = bs; b->bs2 = bs2; b->nz = 0; b->maxnz = nz*bs2; b->inew = 0; b->jnew = 0; b->anew = 0; b->a2anew = 0; b->permute = PETSC_FALSE; PetscFunctionReturn(0); } EXTERN_C_END EXTERN_C_BEGIN EXTERN PetscErrorCode MatConvert_SeqSBAIJ_SeqAIJ(Mat,const MatType,Mat*); EXTERN PetscErrorCode MatConvert_SeqSBAIJ_SeqBAIJ(Mat,const MatType,Mat*); EXTERN_C_END /*MC MATSEQSBAIJ - MATSEQSBAIJ = "seqsbaij" - A matrix type to be used for sequential symmetric block sparse matrices, based on block compressed sparse row format. Only the upper triangular portion of the matrix is stored. Options Database Keys: . -mat_type seqsbaij - sets the matrix type to "seqsbaij" during a call to MatSetFromOptions() Level: beginner .seealso: MatCreateSeqSBAIJ M*/ EXTERN_C_BEGIN #undef __FUNCT__ #define __FUNCT__ "MatCreate_SeqSBAIJ" PetscErrorCode MatCreate_SeqSBAIJ(Mat B) { Mat_SeqSBAIJ *b; PetscErrorCode ierr; int size; PetscFunctionBegin; ierr = MPI_Comm_size(B->comm,&size);CHKERRQ(ierr); if (size > 1) SETERRQ(PETSC_ERR_ARG_WRONG,"Comm must be of size 1"); B->m = B->M = PetscMax(B->m,B->M); B->n = B->N = PetscMax(B->n,B->N); ierr = PetscNew(Mat_SeqSBAIJ,&b);CHKERRQ(ierr); B->data = (void*)b; ierr = PetscMemzero(b,sizeof(Mat_SeqSBAIJ));CHKERRQ(ierr); ierr = PetscMemcpy(B->ops,&MatOps_Values,sizeof(struct _MatOps));CHKERRQ(ierr); B->ops->destroy = MatDestroy_SeqSBAIJ; B->ops->view = MatView_SeqSBAIJ; B->factor = 0; B->lupivotthreshold = 1.0; B->mapping = 0; b->row = 0; b->icol = 0; b->reallocs = 0; b->saved_values = 0; ierr = PetscMapCreateMPI(B->comm,B->m,B->M,&B->rmap);CHKERRQ(ierr); ierr = PetscMapCreateMPI(B->comm,B->n,B->N,&B->cmap);CHKERRQ(ierr); b->sorted = PETSC_FALSE; b->roworiented = PETSC_TRUE; b->nonew = 0; b->diag = 0; b->solve_work = 0; b->mult_work = 0; B->spptr = 0; b->keepzeroedrows = PETSC_FALSE; b->xtoy = 0; b->XtoY = 0; b->inew = 0; b->jnew = 0; b->anew = 0; b->a2anew = 0; b->permute = PETSC_FALSE; ierr = PetscObjectComposeFunctionDynamic((PetscObject)B,"MatStoreValues_C", "MatStoreValues_SeqSBAIJ", MatStoreValues_SeqSBAIJ);CHKERRQ(ierr); ierr = PetscObjectComposeFunctionDynamic((PetscObject)B,"MatRetrieveValues_C", "MatRetrieveValues_SeqSBAIJ", (void*)MatRetrieveValues_SeqSBAIJ);CHKERRQ(ierr); ierr = PetscObjectComposeFunctionDynamic((PetscObject)B,"MatSeqSBAIJSetColumnIndices_C", "MatSeqSBAIJSetColumnIndices_SeqSBAIJ", MatSeqSBAIJSetColumnIndices_SeqSBAIJ);CHKERRQ(ierr); ierr = PetscObjectComposeFunctionDynamic((PetscObject)B,"MatConvert_seqsbaij_seqaij_C", "MatConvert_SeqSBAIJ_SeqAIJ", MatConvert_SeqSBAIJ_SeqAIJ);CHKERRQ(ierr); ierr = PetscObjectComposeFunctionDynamic((PetscObject)B,"MatConvert_seqsbaij_seqbaij_C", "MatConvert_SeqSBAIJ_SeqBAIJ", MatConvert_SeqSBAIJ_SeqBAIJ);CHKERRQ(ierr); ierr = PetscObjectComposeFunctionDynamic((PetscObject)B,"MatSeqSBAIJSetPreallocation_C", "MatSeqSBAIJSetPreallocation_SeqSBAIJ", MatSeqSBAIJSetPreallocation_SeqSBAIJ);CHKERRQ(ierr); B->symmetric = PETSC_TRUE; B->structurally_symmetric = PETSC_TRUE; B->symmetric_set = PETSC_TRUE; B->structurally_symmetric_set = PETSC_TRUE; PetscFunctionReturn(0); } EXTERN_C_END #undef __FUNCT__ #define __FUNCT__ "MatSeqSBAIJSetPreallocation" /*@C MatSeqSBAIJSetPreallocation - Creates a sparse symmetric matrix in block AIJ (block compressed row) format. For good matrix assembly performance the user should preallocate the matrix storage by setting the parameter nz (or the array nnz). By setting these parameters accurately, performance during matrix assembly can be increased by more than a factor of 50. Collective on Mat Input Parameters: + A - the symmetric matrix . bs - size of block . nz - number of block nonzeros per block row (same for all rows) - nnz - array containing the number of block nonzeros in the upper triangular plus diagonal portion of each block (possibly different for each block row) or PETSC_NULL Options Database Keys: . -mat_no_unroll - uses code that does not unroll the loops in the block calculations (much slower) . -mat_block_size - size of the blocks to use Level: intermediate Notes: Specify the preallocated storage with either nz or nnz (not both). Set nz=PETSC_DEFAULT and nnz=PETSC_NULL for PETSc to control dynamic memory allocation. For additional details, see the users manual chapter on matrices. .seealso: MatCreate(), MatCreateSeqAIJ(), MatSetValues(), MatCreateMPISBAIJ() @*/ PetscErrorCode MatSeqSBAIJSetPreallocation(Mat B,int bs,int nz,const int nnz[]) { PetscErrorCode ierr,(*f)(Mat,int,int,const int[]); PetscFunctionBegin; ierr = PetscObjectQueryFunction((PetscObject)B,"MatSeqSBAIJSetPreallocation_C",(void (**)(void))&f);CHKERRQ(ierr); if (f) { ierr = (*f)(B,bs,nz,nnz);CHKERRQ(ierr); } PetscFunctionReturn(0); } #undef __FUNCT__ #define __FUNCT__ "MatCreateSeqSBAIJ" /*@C MatCreateSeqSBAIJ - Creates a sparse symmetric matrix in block AIJ (block compressed row) format. For good matrix assembly performance the user should preallocate the matrix storage by setting the parameter nz (or the array nnz). By setting these parameters accurately, performance during matrix assembly can be increased by more than a factor of 50. Collective on MPI_Comm Input Parameters: + comm - MPI communicator, set to PETSC_COMM_SELF . bs - size of block . m - number of rows, or number of columns . nz - number of block nonzeros per block row (same for all rows) - nnz - array containing the number of block nonzeros in the upper triangular plus diagonal portion of each block (possibly different for each block row) or PETSC_NULL Output Parameter: . A - the symmetric matrix Options Database Keys: . -mat_no_unroll - uses code that does not unroll the loops in the block calculations (much slower) . -mat_block_size - size of the blocks to use Level: intermediate Notes: Specify the preallocated storage with either nz or nnz (not both). Set nz=PETSC_DEFAULT and nnz=PETSC_NULL for PETSc to control dynamic memory allocation. For additional details, see the users manual chapter on matrices. .seealso: MatCreate(), MatCreateSeqAIJ(), MatSetValues(), MatCreateMPISBAIJ() @*/ PetscErrorCode MatCreateSeqSBAIJ(MPI_Comm comm,int bs,int m,int n,int nz,const int nnz[],Mat *A) { PetscErrorCode ierr; PetscFunctionBegin; ierr = MatCreate(comm,m,n,m,n,A);CHKERRQ(ierr); ierr = MatSetType(*A,MATSEQSBAIJ);CHKERRQ(ierr); ierr = MatSeqSBAIJSetPreallocation(*A,bs,nz,nnz);CHKERRQ(ierr); PetscFunctionReturn(0); } #undef __FUNCT__ #define __FUNCT__ "MatDuplicate_SeqSBAIJ" PetscErrorCode MatDuplicate_SeqSBAIJ(Mat A,MatDuplicateOption cpvalues,Mat *B) { Mat C; Mat_SeqSBAIJ *c,*a = (Mat_SeqSBAIJ*)A->data; PetscErrorCode ierr; int i,len,mbs = a->mbs,nz = a->nz,bs2 =a->bs2; PetscFunctionBegin; if (a->i[mbs] != nz) SETERRQ(PETSC_ERR_PLIB,"Corrupt matrix"); *B = 0; ierr = MatCreate(A->comm,A->m,A->n,A->m,A->n,&C);CHKERRQ(ierr); ierr = MatSetType(C,A->type_name);CHKERRQ(ierr); ierr = PetscMemcpy(C->ops,A->ops,sizeof(struct _MatOps));CHKERRQ(ierr); c = (Mat_SeqSBAIJ*)C->data; C->preallocated = PETSC_TRUE; C->factor = A->factor; c->row = 0; c->icol = 0; c->saved_values = 0; c->keepzeroedrows = a->keepzeroedrows; C->assembled = PETSC_TRUE; C->M = A->M; C->N = A->N; c->bs = a->bs; c->bs2 = a->bs2; c->mbs = a->mbs; c->nbs = a->nbs; ierr = PetscMalloc((mbs+1)*sizeof(int),&c->imax);CHKERRQ(ierr); ierr = PetscMalloc((mbs+1)*sizeof(int),&c->ilen);CHKERRQ(ierr); for (i=0; iimax[i] = a->imax[i]; c->ilen[i] = a->ilen[i]; } /* allocate the matrix space */ c->singlemalloc = PETSC_TRUE; len = (mbs+1)*sizeof(int) + nz*(bs2*sizeof(MatScalar) + sizeof(int)); ierr = PetscMalloc(len,&c->a);CHKERRQ(ierr); c->j = (int*)(c->a + nz*bs2); c->i = c->j + nz; ierr = PetscMemcpy(c->i,a->i,(mbs+1)*sizeof(int));CHKERRQ(ierr); if (mbs > 0) { ierr = PetscMemcpy(c->j,a->j,nz*sizeof(int));CHKERRQ(ierr); if (cpvalues == MAT_COPY_VALUES) { ierr = PetscMemcpy(c->a,a->a,bs2*nz*sizeof(MatScalar));CHKERRQ(ierr); } else { ierr = PetscMemzero(c->a,bs2*nz*sizeof(MatScalar));CHKERRQ(ierr); } } PetscLogObjectMemory(C,len+2*(mbs+1)*sizeof(int)+sizeof(struct _p_Mat)+sizeof(Mat_SeqSBAIJ)); c->sorted = a->sorted; c->roworiented = a->roworiented; c->nonew = a->nonew; if (a->diag) { ierr = PetscMalloc((mbs+1)*sizeof(int),&c->diag);CHKERRQ(ierr); PetscLogObjectMemory(C,(mbs+1)*sizeof(int)); for (i=0; idiag[i] = a->diag[i]; } } else c->diag = 0; c->nz = a->nz; c->maxnz = a->maxnz; c->solve_work = 0; c->mult_work = 0; *B = C; ierr = PetscFListDuplicate(A->qlist,&C->qlist);CHKERRQ(ierr); PetscFunctionReturn(0); } #undef __FUNCT__ #define __FUNCT__ "MatLoad_SeqSBAIJ" PetscErrorCode MatLoad_SeqSBAIJ(PetscViewer viewer,const MatType type,Mat *A) { Mat_SeqSBAIJ *a; Mat B; PetscErrorCode ierr; int i,nz,fd,header[4],size,*rowlengths=0,M,N,bs=1; int *mask,mbs,*jj,j,rowcount,nzcount,k,*s_browlengths,maskcount; int kmax,jcount,block,idx,point,nzcountb,extra_rows; int *masked,nmask,tmp,bs2,ishift; PetscScalar *aa; MPI_Comm comm = ((PetscObject)viewer)->comm; PetscFunctionBegin; ierr = PetscOptionsGetInt(PETSC_NULL,"-matload_block_size",&bs,PETSC_NULL);CHKERRQ(ierr); bs2 = bs*bs; ierr = MPI_Comm_size(comm,&size);CHKERRQ(ierr); if (size > 1) SETERRQ(PETSC_ERR_ARG_WRONG,"view must have one processor"); ierr = PetscViewerBinaryGetDescriptor(viewer,&fd);CHKERRQ(ierr); ierr = PetscBinaryRead(fd,header,4,PETSC_INT);CHKERRQ(ierr); if (header[0] != MAT_FILE_COOKIE) SETERRQ(PETSC_ERR_FILE_UNEXPECTED,"not Mat object"); M = header[1]; N = header[2]; nz = header[3]; if (header[3] < 0) { SETERRQ(PETSC_ERR_FILE_UNEXPECTED,"Matrix stored in special format, cannot load as SeqSBAIJ"); } if (M != N) SETERRQ(PETSC_ERR_SUP,"Can only do square matrices"); /* This code adds extra rows to make sure the number of rows is divisible by the blocksize */ mbs = M/bs; extra_rows = bs - M + bs*(mbs); if (extra_rows == bs) extra_rows = 0; else mbs++; if (extra_rows) { PetscLogInfo(0,"MatLoad_SeqSBAIJ:Padding loaded matrix to match blocksize\n"); } /* read in row lengths */ ierr = PetscMalloc((M+extra_rows)*sizeof(int),&rowlengths);CHKERRQ(ierr); ierr = PetscBinaryRead(fd,rowlengths,M,PETSC_INT);CHKERRQ(ierr); for (i=0; i= i) {masked[nmask++] = tmp; mask[tmp] = 1;} } rowcount++; } s_browlengths[i] += nmask; /* zero out the mask elements we set */ for (j=0; jdata; /* set matrix "i" values */ a->i[0] = 0; for (i=1; i<= mbs; i++) { a->i[i] = a->i[i-1] + s_browlengths[i-1]; a->ilen[i-1] = s_browlengths[i-1]; } a->nz = a->i[mbs]; /* read in nonzero values */ ierr = PetscMalloc((nz+extra_rows)*sizeof(PetscScalar),&aa);CHKERRQ(ierr); ierr = PetscBinaryRead(fd,aa,nz,PETSC_SCALAR);CHKERRQ(ierr); for (i=0; i= i) { masked[nmask++] = tmp; mask[tmp] = 1;} } } /* sort the masked values */ ierr = PetscSortInt(nmask,masked);CHKERRQ(ierr); /* set "j" values into matrix */ maskcount = 1; for (j=0; jj[jcount++] = masked[j]; mask[masked[j]] = maskcount++; } /* set "a" values into matrix */ ishift = bs2*a->i[i]; for (j=0; j= i){ block = mask[tmp] - 1; point = jj[nzcountb] - bs*tmp; idx = ishift + bs2*block + j + bs*point; a->a[idx] = aa[nzcountb]; } nzcountb++; } } /* zero out the mask elements we set */ for (j=0; jnz) SETERRQ(PETSC_ERR_FILE_UNEXPECTED,"Bad binary matrix"); ierr = PetscFree(rowlengths);CHKERRQ(ierr); ierr = PetscFree(s_browlengths);CHKERRQ(ierr); ierr = PetscFree(aa);CHKERRQ(ierr); ierr = PetscFree(jj);CHKERRQ(ierr); ierr = PetscFree(mask);CHKERRQ(ierr); ierr = MatAssemblyBegin(B,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); ierr = MatAssemblyEnd(B,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); ierr = MatView_Private(B);CHKERRQ(ierr); *A = B; PetscFunctionReturn(0); } #undef __FUNCT__ #define __FUNCT__ "MatRelax_SeqSBAIJ" PetscErrorCode MatRelax_SeqSBAIJ(Mat A,Vec bb,PetscReal omega,MatSORType flag,PetscReal fshift,int its,int lits,Vec xx) { Mat_SeqSBAIJ *a = (Mat_SeqSBAIJ*)A->data; MatScalar *aa=a->a,*v,*v1; PetscScalar *x,*b,*t,sum,d; PetscErrorCode ierr; int m=a->mbs,bs=a->bs,*ai=a->i,*aj=a->j; int nz,nz1,*vj,*vj1,i; PetscFunctionBegin; its = its*lits; if (its <= 0) SETERRQ2(PETSC_ERR_ARG_WRONG,"Relaxation requires global its %d and local its %d both positive",its,lits); if (bs > 1) SETERRQ(PETSC_ERR_SUP,"SSOR for block size > 1 is not yet implemented"); ierr = VecGetArray(xx,&x);CHKERRQ(ierr); if (xx != bb) { ierr = VecGetArray(bb,&b);CHKERRQ(ierr); } else { b = x; } ierr = PetscMalloc(m*sizeof(PetscScalar),&t);CHKERRQ(ierr); if (flag & SOR_ZERO_INITIAL_GUESS) { if (flag & SOR_FORWARD_SWEEP || flag & SOR_LOCAL_FORWARD_SWEEP){ for (i=0; i=0; i--){ d = *(aa + ai[i]); v = aa + ai[i] + 1; vj = aj + ai[i] + 1; nz = ai[i+1] - ai[i] - 1; sum = t[i]; while (nz--) sum -= x[*vj++]*(*v++); PetscLogFlops(2*nz-1); x[i] = (1-omega)*x[i] + omega*sum/d; } } its--; } while (its--) { /* forward sweep: for i=0,...,m-1: sum[i] = (b[i] - U(i,:)x )/d[i]; x[i] = (1-omega)x[i] + omega*sum[i]; b = b - x[i]*U^T(i,:); */ if (flag & SOR_FORWARD_SWEEP || flag & SOR_LOCAL_FORWARD_SWEEP){ for (i=0; i=0; i--){ d = *(aa + ai[i]); v = aa + ai[i] + 1; vj = aj + ai[i] + 1; nz = ai[i+1] - ai[i] - 1; sum = t[i]; while (nz--) sum -= x[*vj++]*(*v++); PetscLogFlops(2*nz-1); x[i] = (1-omega)*x[i] + omega*sum/d; } } } ierr = PetscFree(t);CHKERRQ(ierr); ierr = VecRestoreArray(xx,&x);CHKERRQ(ierr); if (bb != xx) { ierr = VecRestoreArray(bb,&b);CHKERRQ(ierr); } PetscFunctionReturn(0); }