mat/utils/axpy.c

#include <petsc/private/matimpl.h> /*I   "petscmat.h"  I*/

static PetscErrorCode MatTransposeAXPY_Private(Mat Y, PetscScalar a, Mat X, MatStructure str, Mat T)
{
  Mat         A, F;
  PetscScalar vshift, vscale;
  PetscErrorCode (*f)(Mat, Mat *);

  PetscFunctionBegin;
  if (T == X) PetscCall(MatShellGetScalingShifts(T, &vshift, &vscale, (Vec *)MAT_SHELL_NOT_ALLOWED, (Vec *)MAT_SHELL_NOT_ALLOWED, (Vec *)MAT_SHELL_NOT_ALLOWED, (Mat *)MAT_SHELL_NOT_ALLOWED, (IS *)MAT_SHELL_NOT_ALLOWED, (IS *)MAT_SHELL_NOT_ALLOWED));
  else {
    vshift = 0.0;
    vscale = 1.0;
  }
  PetscCall(PetscObjectQueryFunction((PetscObject)T, "MatTransposeGetMat_C", &f));
  if (f) {
    PetscCall(MatTransposeGetMat(T, &A));
    if (T == X) {
      PetscCall(PetscInfo(NULL, "Explicitly transposing X of type MATTRANSPOSEVIRTUAL to perform MatAXPY()\n"));
      PetscCall(MatTranspose(A, MAT_INITIAL_MATRIX, &F));
      A = Y;
    } else {
      PetscCall(PetscInfo(NULL, "Transposing X because Y of type MATTRANSPOSEVIRTUAL to perform MatAXPY()\n"));
      PetscCall(MatTranspose(X, MAT_INITIAL_MATRIX, &F));
    }
  } else {
    PetscCall(MatHermitianTransposeGetMat(T, &A));
    if (T == X) {
      PetscCall(PetscInfo(NULL, "Explicitly Hermitian transposing X of type MATHERMITIANTRANSPOSEVIRTUAL to perform MatAXPY()\n"));
      PetscCall(MatHermitianTranspose(A, MAT_INITIAL_MATRIX, &F));
      A = Y;
    } else {
      PetscCall(PetscInfo(NULL, "Hermitian transposing X because Y of type MATHERMITIANTRANSPOSEVIRTUAL to perform MatAXPY()\n"));
      PetscCall(MatHermitianTranspose(X, MAT_INITIAL_MATRIX, &F));
    }
  }
  PetscCall(MatAXPY(A, a * vscale, F, str));
  PetscCall(MatShift(A, a * vshift));
  PetscCall(MatDestroy(&F));
  PetscFunctionReturn(PETSC_SUCCESS);
}

/*@
  MatAXPY - Computes Y = a*X + Y.

  Logically Collective

  Input Parameters:
+ a   - the scalar multiplier
. X   - the first matrix
. Y   - the second matrix
- str - either `SAME_NONZERO_PATTERN`, `DIFFERENT_NONZERO_PATTERN`, `UNKNOWN_NONZERO_PATTERN`, or `SUBSET_NONZERO_PATTERN` (nonzeros of `X` is a subset of `Y`'s)

  Level: intermediate

.seealso: [](ch_matrices), `Mat`, `MatAYPX()`
 @*/
PetscErrorCode MatAXPY(Mat Y, PetscScalar a, Mat X, MatStructure str)
{
  PetscInt  M1, M2, N1, N2;
  PetscInt  m1, m2, n1, n2;
  PetscBool sametype, transpose;

  PetscFunctionBegin;
  PetscValidHeaderSpecific(Y, MAT_CLASSID, 1);
  PetscValidLogicalCollectiveScalar(Y, a, 2);
  PetscValidHeaderSpecific(X, MAT_CLASSID, 3);
  PetscCheckSameComm(Y, 1, X, 3);
  PetscCall(MatGetSize(X, &M1, &N1));
  PetscCall(MatGetSize(Y, &M2, &N2));
  PetscCall(MatGetLocalSize(X, &m1, &n1));
  PetscCall(MatGetLocalSize(Y, &m2, &n2));
  PetscCheck(M1 == M2 && N1 == N2, PetscObjectComm((PetscObject)Y), PETSC_ERR_ARG_SIZ, "Non conforming matrix add: global sizes X %" PetscInt_FMT " x %" PetscInt_FMT ", Y %" PetscInt_FMT " x %" PetscInt_FMT, M1, N1, M2, N2);
  PetscCheck(m1 == m2 && n1 == n2, PETSC_COMM_SELF, PETSC_ERR_ARG_SIZ, "Non conforming matrix add: local sizes X %" PetscInt_FMT " x %" PetscInt_FMT ", Y %" PetscInt_FMT " x %" PetscInt_FMT, m1, n1, m2, n2);
  PetscCheck(Y->assembled, PetscObjectComm((PetscObject)Y), PETSC_ERR_ARG_WRONGSTATE, "Not for unassembled matrix (Y)");
  PetscCheck(X->assembled, PetscObjectComm((PetscObject)X), PETSC_ERR_ARG_WRONGSTATE, "Not for unassembled matrix (X)");
  if (a == (PetscScalar)0.0) PetscFunctionReturn(PETSC_SUCCESS);
  if (Y == X) {
    PetscCall(MatScale(Y, 1.0 + a));
    PetscFunctionReturn(PETSC_SUCCESS);
  }
  PetscCall(PetscObjectObjectTypeCompare((PetscObject)X, (PetscObject)Y, &sametype));
  PetscCall(PetscLogEventBegin(MAT_AXPY, Y, 0, 0, 0));
  if (Y->ops->axpy && (sametype || X->ops->axpy == Y->ops->axpy)) {
    PetscUseTypeMethod(Y, axpy, a, X, str);
  } else {
    PetscCall(PetscObjectTypeCompareAny((PetscObject)X, &transpose, MATTRANSPOSEVIRTUAL, MATHERMITIANTRANSPOSEVIRTUAL, ""));
    if (transpose) {
      PetscCall(MatTransposeAXPY_Private(Y, a, X, str, X));
    } else {
      PetscCall(PetscObjectTypeCompareAny((PetscObject)Y, &transpose, MATTRANSPOSEVIRTUAL, MATHERMITIANTRANSPOSEVIRTUAL, ""));
      if (transpose) {
        PetscCall(MatTransposeAXPY_Private(Y, a, X, str, Y));
      } else {
        PetscCall(MatAXPY_Basic(Y, a, X, str));
      }
    }
  }
  PetscCall(PetscLogEventEnd(MAT_AXPY, Y, 0, 0, 0));
  PetscFunctionReturn(PETSC_SUCCESS);
}

PetscErrorCode MatAXPY_Basic_Preallocate(Mat Y, Mat X, Mat *B)
{
  PetscErrorCode (*preall)(Mat, Mat, Mat *) = NULL;

  PetscFunctionBegin;
  /* look for any available faster alternative to the general preallocator */
  PetscCall(PetscObjectQueryFunction((PetscObject)Y, "MatAXPYGetPreallocation_C", &preall));
  if (preall) {
    PetscCall((*preall)(Y, X, B));
  } else { /* Use MatPrellocator, assumes same row-col distribution */
    Mat      preallocator;
    PetscInt r, rstart, rend;
    PetscInt m, n, M, N;

    PetscCall(MatGetRowUpperTriangular(Y));
    PetscCall(MatGetRowUpperTriangular(X));
    PetscCall(MatGetSize(Y, &M, &N));
    PetscCall(MatGetLocalSize(Y, &m, &n));
    PetscCall(MatCreate(PetscObjectComm((PetscObject)Y), &preallocator));
    PetscCall(MatSetType(preallocator, MATPREALLOCATOR));
    PetscCall(MatSetLayouts(preallocator, Y->rmap, Y->cmap));
    PetscCall(MatSetUp(preallocator));
    PetscCall(MatGetOwnershipRange(preallocator, &rstart, &rend));
    for (r = rstart; r < rend; ++r) {
      PetscInt           ncols;
      const PetscInt    *row;
      const PetscScalar *vals;

      PetscCall(MatGetRow(Y, r, &ncols, &row, &vals));
      PetscCall(MatSetValues(preallocator, 1, &r, ncols, row, vals, INSERT_VALUES));
      PetscCall(MatRestoreRow(Y, r, &ncols, &row, &vals));
      PetscCall(MatGetRow(X, r, &ncols, &row, &vals));
      PetscCall(MatSetValues(preallocator, 1, &r, ncols, row, vals, INSERT_VALUES));
      PetscCall(MatRestoreRow(X, r, &ncols, &row, &vals));
    }
    PetscCall(MatSetOption(preallocator, MAT_NO_OFF_PROC_ENTRIES, PETSC_TRUE));
    PetscCall(MatAssemblyBegin(preallocator, MAT_FINAL_ASSEMBLY));
    PetscCall(MatAssemblyEnd(preallocator, MAT_FINAL_ASSEMBLY));
    PetscCall(MatRestoreRowUpperTriangular(Y));
    PetscCall(MatRestoreRowUpperTriangular(X));

    PetscCall(MatCreate(PetscObjectComm((PetscObject)Y), B));
    PetscCall(MatSetType(*B, ((PetscObject)Y)->type_name));
    PetscCall(MatSetLayouts(*B, Y->rmap, Y->cmap));
    PetscCall(MatPreallocatorPreallocate(preallocator, PETSC_FALSE, *B));
    PetscCall(MatDestroy(&preallocator));
  }
  PetscFunctionReturn(PETSC_SUCCESS);
}

PetscErrorCode MatAXPY_Basic(Mat Y, PetscScalar a, Mat X, MatStructure str)
{
  PetscBool isshell, isdense, isnest;

  PetscFunctionBegin;
  PetscCall(MatIsShell(Y, &isshell));
  if (isshell) { /* MatShell has special support for AXPY */
    PetscErrorCode (*f)(Mat, PetscScalar, Mat, MatStructure);

    PetscCall(MatGetOperation(Y, MATOP_AXPY, (void (**)(void)) & f));
    if (f) {
      PetscCall((*f)(Y, a, X, str));
      PetscFunctionReturn(PETSC_SUCCESS);
    }
  }
  /* no need to preallocate if Y is dense */
  PetscCall(PetscObjectBaseTypeCompareAny((PetscObject)Y, &isdense, MATSEQDENSE, MATMPIDENSE, ""));
  if (isdense) {
    PetscCall(PetscObjectTypeCompare((PetscObject)X, MATNEST, &isnest));
    if (isnest) {
      PetscCall(MatAXPY_Dense_Nest(Y, a, X));
      PetscFunctionReturn(PETSC_SUCCESS);
    }
    if (str == DIFFERENT_NONZERO_PATTERN || str == UNKNOWN_NONZERO_PATTERN) str = SUBSET_NONZERO_PATTERN;
  }
  if (str != DIFFERENT_NONZERO_PATTERN && str != UNKNOWN_NONZERO_PATTERN) {
    PetscInt           i, start, end, j, ncols, m, n;
    const PetscInt    *row;
    PetscScalar       *val;
    const PetscScalar *vals;

    PetscCall(MatGetSize(X, &m, &n));
    PetscCall(MatGetOwnershipRange(X, &start, &end));
    PetscCall(MatGetRowUpperTriangular(X));
    if (a == 1.0) {
      for (i = start; i < end; i++) {
        PetscCall(MatGetRow(X, i, &ncols, &row, &vals));
        PetscCall(MatSetValues(Y, 1, &i, ncols, row, vals, ADD_VALUES));
        PetscCall(MatRestoreRow(X, i, &ncols, &row, &vals));
      }
    } else {
      PetscInt vs = 100;
      /* realloc if needed, as this function may be used in parallel */
      PetscCall(PetscMalloc1(vs, &val));
      for (i = start; i < end; i++) {
        PetscCall(MatGetRow(X, i, &ncols, &row, &vals));
        if (vs < ncols) {
          vs = PetscMin(2 * ncols, n);
          PetscCall(PetscRealloc(vs * sizeof(*val), &val));
        }
        for (j = 0; j < ncols; j++) val[j] = a * vals[j];
        PetscCall(MatSetValues(Y, 1, &i, ncols, row, val, ADD_VALUES));
        PetscCall(MatRestoreRow(X, i, &ncols, &row, &vals));
      }
      PetscCall(PetscFree(val));
    }
    PetscCall(MatRestoreRowUpperTriangular(X));
    PetscCall(MatAssemblyBegin(Y, MAT_FINAL_ASSEMBLY));
    PetscCall(MatAssemblyEnd(Y, MAT_FINAL_ASSEMBLY));
  } else {
    Mat B;

    PetscCall(MatAXPY_Basic_Preallocate(Y, X, &B));
    PetscCall(MatAXPY_BasicWithPreallocation(B, Y, a, X, str));
    PetscCall(MatHeaderMerge(Y, &B));
  }
  PetscFunctionReturn(PETSC_SUCCESS);
}

PetscErrorCode MatAXPY_BasicWithPreallocation(Mat B, Mat Y, PetscScalar a, Mat X, MatStructure str)
{
  PetscInt           i, start, end, j, ncols, m, n;
  const PetscInt    *row;
  PetscScalar       *val;
  const PetscScalar *vals;

  PetscFunctionBegin;
  PetscCall(MatGetSize(X, &m, &n));
  PetscCall(MatGetOwnershipRange(X, &start, &end));
  PetscCall(MatGetRowUpperTriangular(Y));
  PetscCall(MatGetRowUpperTriangular(X));
  if (a == 1.0) {
    for (i = start; i < end; i++) {
      PetscCall(MatGetRow(Y, i, &ncols, &row, &vals));
      PetscCall(MatSetValues(B, 1, &i, ncols, row, vals, ADD_VALUES));
      PetscCall(MatRestoreRow(Y, i, &ncols, &row, &vals));

      PetscCall(MatGetRow(X, i, &ncols, &row, &vals));
      PetscCall(MatSetValues(B, 1, &i, ncols, row, vals, ADD_VALUES));
      PetscCall(MatRestoreRow(X, i, &ncols, &row, &vals));
    }
  } else {
    PetscInt vs = 100;
    /* realloc if needed, as this function may be used in parallel */
    PetscCall(PetscMalloc1(vs, &val));
    for (i = start; i < end; i++) {
      PetscCall(MatGetRow(Y, i, &ncols, &row, &vals));
      PetscCall(MatSetValues(B, 1, &i, ncols, row, vals, ADD_VALUES));
      PetscCall(MatRestoreRow(Y, i, &ncols, &row, &vals));

      PetscCall(MatGetRow(X, i, &ncols, &row, &vals));
      if (vs < ncols) {
        vs = PetscMin(2 * ncols, n);
        PetscCall(PetscRealloc(vs * sizeof(*val), &val));
      }
      for (j = 0; j < ncols; j++) val[j] = a * vals[j];
      PetscCall(MatSetValues(B, 1, &i, ncols, row, val, ADD_VALUES));
      PetscCall(MatRestoreRow(X, i, &ncols, &row, &vals));
    }
    PetscCall(PetscFree(val));
  }
  PetscCall(MatRestoreRowUpperTriangular(Y));
  PetscCall(MatRestoreRowUpperTriangular(X));
  PetscCall(MatAssemblyBegin(B, MAT_FINAL_ASSEMBLY));
  PetscCall(MatAssemblyEnd(B, MAT_FINAL_ASSEMBLY));
  PetscFunctionReturn(PETSC_SUCCESS);
}

/*@
  MatShift - Computes `Y =  Y + a I`, where `a` is a `PetscScalar`

  Neighbor-wise Collective

  Input Parameters:
+ Y - the matrix
- a - the `PetscScalar`

  Level: intermediate

  Notes:
  If `Y` is a rectangular matrix, the shift is done on the main diagonal of the matrix (https://en.wikipedia.org/wiki/Main_diagonal)

  If the matrix `Y` is missing some diagonal entries this routine can be very slow. To make it fast one should initially
  fill the matrix so that all diagonal entries have a value (with a value of zero for those locations that would not have an
  entry). No operation is performed when a is zero.

  To form Y = Y + diag(V) use `MatDiagonalSet()`

.seealso: [](ch_matrices), `Mat`, `MatDiagonalSet()`, `MatScale()`, `MatDiagonalScale()`
 @*/
PetscErrorCode MatShift(Mat Y, PetscScalar a)
{
  PetscFunctionBegin;
  PetscValidHeaderSpecific(Y, MAT_CLASSID, 1);
  PetscCheck(Y->assembled, PetscObjectComm((PetscObject)Y), PETSC_ERR_ARG_WRONGSTATE, "Not for unassembled matrix");
  PetscCheck(!Y->factortype, PetscObjectComm((PetscObject)Y), PETSC_ERR_ARG_WRONGSTATE, "Not for factored matrix");
  MatCheckPreallocated(Y, 1);
  if (a == 0.0) PetscFunctionReturn(PETSC_SUCCESS);

  if (Y->ops->shift) PetscUseTypeMethod(Y, shift, a);
  else PetscCall(MatShift_Basic(Y, a));

  PetscCall(PetscObjectStateIncrease((PetscObject)Y));
  PetscFunctionReturn(PETSC_SUCCESS);
}

PetscErrorCode MatDiagonalSet_Default(Mat Y, Vec D, InsertMode is)
{
  PetscInt           i, start, end;
  const PetscScalar *v;

  PetscFunctionBegin;
  PetscCall(MatGetOwnershipRange(Y, &start, &end));
  PetscCall(VecGetArrayRead(D, &v));
  for (i = start; i < end; i++) PetscCall(MatSetValues(Y, 1, &i, 1, &i, v + i - start, is));
  PetscCall(VecRestoreArrayRead(D, &v));
  PetscCall(MatAssemblyBegin(Y, MAT_FINAL_ASSEMBLY));
  PetscCall(MatAssemblyEnd(Y, MAT_FINAL_ASSEMBLY));
  PetscFunctionReturn(PETSC_SUCCESS);
}

/*@
  MatDiagonalSet - Computes `Y` = `Y` + `D`, where `D` is a diagonal matrix
  that is represented as a vector. Or Y[i,i] = D[i] if `InsertMode` is
  `INSERT_VALUES`.

  Neighbor-wise Collective

  Input Parameters:
+ Y  - the input matrix
. D  - the diagonal matrix, represented as a vector
- is - `INSERT_VALUES` or `ADD_VALUES`

  Level: intermediate

  Note:
  If the matrix `Y` is missing some diagonal entries this routine can be very slow. To make it fast one should initially
  fill the matrix so that all diagonal entries have a value (with a value of zero for those locations that would not have an
  entry).

.seealso: [](ch_matrices), `Mat`, `MatShift()`, `MatScale()`, `MatDiagonalScale()`
@*/
PetscErrorCode MatDiagonalSet(Mat Y, Vec D, InsertMode is)
{
  PetscInt matlocal, veclocal;

  PetscFunctionBegin;
  PetscValidHeaderSpecific(Y, MAT_CLASSID, 1);
  PetscValidHeaderSpecific(D, VEC_CLASSID, 2);
  MatCheckPreallocated(Y, 1);
  PetscCall(MatGetLocalSize(Y, &matlocal, NULL));
  PetscCall(VecGetLocalSize(D, &veclocal));
  PetscCheck(matlocal == veclocal, PETSC_COMM_SELF, PETSC_ERR_ARG_INCOMP, "Number local rows of matrix %" PetscInt_FMT " does not match that of vector for diagonal %" PetscInt_FMT, matlocal, veclocal);
  if (Y->ops->diagonalset) PetscUseTypeMethod(Y, diagonalset, D, is);
  else PetscCall(MatDiagonalSet_Default(Y, D, is));
  PetscCall(PetscObjectStateIncrease((PetscObject)Y));
  PetscFunctionReturn(PETSC_SUCCESS);
}

/*@
  MatAYPX - Computes Y = a*Y + X.

  Logically Collective

  Input Parameters:
+ a   - the `PetscScalar` multiplier
. Y   - the first matrix
. X   - the second matrix
- str - either `SAME_NONZERO_PATTERN`, `DIFFERENT_NONZERO_PATTERN`, `UNKNOWN_NONZERO_PATTERN`, or `SUBSET_NONZERO_PATTERN` (nonzeros of `X` is a subset of `Y`'s)

  Level: intermediate

.seealso: [](ch_matrices), `Mat`, `MatAXPY()`
 @*/
PetscErrorCode MatAYPX(Mat Y, PetscScalar a, Mat X, MatStructure str)
{
  PetscFunctionBegin;
  PetscCall(MatScale(Y, a));
  PetscCall(MatAXPY(Y, 1.0, X, str));
  PetscFunctionReturn(PETSC_SUCCESS);
}

/*@C
  MatComputeOperator - Computes the explicit matrix

  Collective

  Input Parameters:
+ inmat   - the matrix
- mattype - the matrix type for the explicit operator

  Output Parameter:
. mat - the explicit  operator

  Level: advanced

  Note:
  This computation is done by applying the operator to columns of the identity matrix.
  This routine is costly in general, and is recommended for use only with relatively small systems.
  Currently, this routine uses a dense matrix format if `mattype` == `NULL`.

.seealso: [](ch_matrices), `Mat`, `MatConvert()`, `MatMult()`, `MatComputeOperatorTranspose()`
@*/
PetscErrorCode MatComputeOperator(Mat inmat, MatType mattype, Mat *mat)
{
  PetscFunctionBegin;
  PetscValidHeaderSpecific(inmat, MAT_CLASSID, 1);
  PetscAssertPointer(mat, 3);
  PetscCall(MatConvert_Shell(inmat, mattype ? mattype : MATDENSE, MAT_INITIAL_MATRIX, mat));
  PetscFunctionReturn(PETSC_SUCCESS);
}

/*@C
  MatComputeOperatorTranspose - Computes the explicit matrix representation of
  a give matrix that can apply `MatMultTranspose()`

  Collective

  Input Parameters:
+ inmat   - the matrix
- mattype - the matrix type for the explicit operator

  Output Parameter:
. mat - the explicit  operator transposed

  Level: advanced

  Note:
  This computation is done by applying the transpose of the operator to columns of the identity matrix.
  This routine is costly in general, and is recommended for use only with relatively small systems.
  Currently, this routine uses a dense matrix format if `mattype` == `NULL`.

.seealso: [](ch_matrices), `Mat`, `MatConvert()`, `MatMult()`, `MatComputeOperator()`
@*/
PetscErrorCode MatComputeOperatorTranspose(Mat inmat, MatType mattype, Mat *mat)
{
  Mat A;

  PetscFunctionBegin;
  PetscValidHeaderSpecific(inmat, MAT_CLASSID, 1);
  PetscAssertPointer(mat, 3);
  PetscCall(MatCreateTranspose(inmat, &A));
  PetscCall(MatConvert_Shell(A, mattype ? mattype : MATDENSE, MAT_INITIAL_MATRIX, mat));
  PetscCall(MatDestroy(&A));
  PetscFunctionReturn(PETSC_SUCCESS);
}

/*@
  MatFilter - Set all values in the matrix with an absolute value less than or equal to the tolerance to zero, and optionally compress the underlying storage

  Input Parameters:
+ A        - The matrix
. tol      - The zero tolerance
. compress - Whether the storage from the input matrix `A` should be compressed once values less than or equal to `tol` are set to zero
- keep     - If `compress` is true and for a given row of `A`, the diagonal coefficient is less than or equal to `tol`, indicates whether it should be left in the structure or eliminated as well

  Level: intermediate

.seealso: [](ch_matrices), `Mat`, `MatCreate()`, `MatZeroEntries()`, `MatEliminateZeros()`, `VecFilter()`
 @*/
PetscErrorCode MatFilter(Mat A, PetscReal tol, PetscBool compress, PetscBool keep)
{
  Mat          a;
  PetscScalar *newVals;
  PetscInt    *newCols, rStart, rEnd, maxRows, r, colMax = 0, nnz0 = 0, nnz1 = 0;
  PetscBool    flg;

  PetscFunctionBegin;
  PetscCall(PetscObjectBaseTypeCompareAny((PetscObject)A, &flg, MATSEQDENSE, MATMPIDENSE, ""));
  if (flg) {
    PetscCall(MatDenseGetLocalMatrix(A, &a));
    PetscCall(MatDenseGetLDA(a, &r));
    PetscCall(MatGetSize(a, &rStart, &rEnd));
    PetscCall(MatDenseGetArray(a, &newVals));
    for (; colMax < rEnd; ++colMax) {
      for (maxRows = 0; maxRows < rStart; ++maxRows) newVals[maxRows + colMax * r] = PetscAbsScalar(newVals[maxRows + colMax * r]) <= tol ? 0.0 : newVals[maxRows + colMax * r];
    }
    PetscCall(MatDenseRestoreArray(a, &newVals));
  } else {
    const PetscInt *ranges;
    PetscMPIInt     rank, size;

    PetscCallMPI(MPI_Comm_rank(PetscObjectComm((PetscObject)A), &rank));
    PetscCallMPI(MPI_Comm_size(PetscObjectComm((PetscObject)A), &size));
    PetscCall(MatGetOwnershipRanges(A, &ranges));
    rStart = ranges[rank];
    rEnd   = ranges[rank + 1];
    PetscCall(MatGetRowUpperTriangular(A));
    for (r = rStart; r < rEnd; ++r) {
      PetscInt ncols;

      PetscCall(MatGetRow(A, r, &ncols, NULL, NULL));
      colMax = PetscMax(colMax, ncols);
      PetscCall(MatRestoreRow(A, r, &ncols, NULL, NULL));
    }
    maxRows = 0;
    for (r = 0; r < size; ++r) maxRows = PetscMax(maxRows, ranges[r + 1] - ranges[r]);
    PetscCall(PetscCalloc2(colMax, &newCols, colMax, &newVals));
    PetscCall(MatGetOption(A, MAT_NO_OFF_PROC_ENTRIES, &flg)); /* cache user-defined value */
    PetscCall(MatSetOption(A, MAT_NO_OFF_PROC_ENTRIES, PETSC_TRUE));
    /* short-circuit code in MatAssemblyBegin() and MatAssemblyEnd()             */
    /* that are potentially called many times depending on the distribution of A */
    for (r = rStart; r < rStart + maxRows; ++r) {
      if (r < rEnd) {
        const PetscScalar *vals;
        const PetscInt    *cols;
        PetscInt           ncols, newcols = 0, c;

        PetscCall(MatGetRow(A, r, &ncols, &cols, &vals));
        nnz0 += ncols - 1;
        for (c = 0; c < ncols; ++c) {
          if (PetscUnlikely(PetscAbsScalar(vals[c]) <= tol)) newCols[newcols++] = cols[c];
        }
        nnz1 += ncols - newcols - 1;
        PetscCall(MatRestoreRow(A, r, &ncols, &cols, &vals));
        PetscCall(MatSetValues(A, 1, &r, newcols, newCols, newVals, INSERT_VALUES));
      }
      PetscCall(MatAssemblyBegin(A, MAT_FINAL_ASSEMBLY));
      PetscCall(MatAssemblyEnd(A, MAT_FINAL_ASSEMBLY));
    }
    PetscCall(MatRestoreRowUpperTriangular(A));
    PetscCall(PetscFree2(newCols, newVals));
    PetscCall(MatSetOption(A, MAT_NO_OFF_PROC_ENTRIES, flg)); /* reset option to its user-defined value */
    if (nnz0 > 0) PetscCall(PetscInfo(NULL, "Filtering left %g%% edges in graph\n", 100 * (double)nnz1 / (double)nnz0));
    else PetscCall(PetscInfo(NULL, "Warning: %" PetscInt_FMT " edges to filter with %" PetscInt_FMT " rows\n", nnz0, maxRows));
  }
  if (compress && A->ops->eliminatezeros) {
    Mat       B;
    PetscBool flg;

    PetscCall(PetscObjectTypeCompareAny((PetscObject)A, &flg, MATSEQAIJHIPSPARSE, MATMPIAIJHIPSPARSE, ""));
    if (!flg) {
      PetscCall(MatEliminateZeros(A, keep));
      PetscCall(MatDuplicate(A, MAT_COPY_VALUES, &B));
      PetscCall(MatHeaderReplace(A, &B));
    }
  }
  PetscFunctionReturn(PETSC_SUCCESS);
}