sbaij/seq/sbaijfact2.c

/*
    Factorization code for SBAIJ format.
*/

#include <../src/mat/impls/sbaij/seq/sbaij.h>
#include <../src/mat/impls/baij/seq/baij.h>
#include <petsc/private/kernels/blockinvert.h>

PetscErrorCode MatSolve_SeqSBAIJ_N_inplace(Mat A, Vec bb, Vec xx) {
  Mat_SeqSBAIJ      *a     = (Mat_SeqSBAIJ *)A->data;
  IS                 isrow = a->row;
  PetscInt           mbs = a->mbs, *ai = a->i, *aj = a->j;
  const PetscInt    *r;
  PetscInt           nz, *vj, k, idx, k1;
  PetscInt           bs = A->rmap->bs, bs2 = a->bs2;
  const MatScalar   *aa = a->a, *v, *diag;
  PetscScalar       *x, *xk, *xj, *xk_tmp, *t;
  const PetscScalar *b;

  PetscFunctionBegin;
  PetscCall(VecGetArrayRead(bb, &b));
  PetscCall(VecGetArray(xx, &x));
  t = a->solve_work;
  PetscCall(ISGetIndices(isrow, &r));
  PetscCall(PetscMalloc1(bs, &xk_tmp));

  /* solve U^T * D * y = b by forward substitution */
  xk = t;
  for (k = 0; k < mbs; k++) { /* t <- perm(b) */
    idx = bs * r[k];
    for (k1 = 0; k1 < bs; k1++) *xk++ = b[idx + k1];
  }
  for (k = 0; k < mbs; k++) {
    v  = aa + bs2 * ai[k];
    xk = t + k * bs;                          /* Dk*xk = k-th block of x */
    PetscCall(PetscArraycpy(xk_tmp, xk, bs)); /* xk_tmp <- xk */
    nz = ai[k + 1] - ai[k];
    vj = aj + ai[k];
    xj = t + (*vj) * bs; /* *vj-th block of x, *vj>k */
    while (nz--) {
      /* x(:) += U(k,:)^T*(Dk*xk) */
      PetscKernel_v_gets_v_plus_Atranspose_times_w(bs, xj, v, xk_tmp); /* xj <- xj + v^t * xk */
      vj++;
      xj = t + (*vj) * bs;
      v += bs2;
    }
    /* xk = inv(Dk)*(Dk*xk) */
    diag = aa + k * bs2;                                /* ptr to inv(Dk) */
    PetscKernel_w_gets_A_times_v(bs, xk_tmp, diag, xk); /* xk <- diag * xk */
  }

  /* solve U*x = y by back substitution */
  for (k = mbs - 1; k >= 0; k--) {
    v  = aa + bs2 * ai[k];
    xk = t + k * bs; /* xk */
    nz = ai[k + 1] - ai[k];
    vj = aj + ai[k];
    xj = t + (*vj) * bs;
    while (nz--) {
      /* xk += U(k,:)*x(:) */
      PetscKernel_v_gets_v_plus_A_times_w(bs, xk, v, xj); /* xk <- xk + v*xj */
      vj++;
      v += bs2;
      xj = t + (*vj) * bs;
    }
    idx = bs * r[k];
    for (k1 = 0; k1 < bs; k1++) x[idx + k1] = *xk++;
  }

  PetscCall(PetscFree(xk_tmp));
  PetscCall(ISRestoreIndices(isrow, &r));
  PetscCall(VecRestoreArrayRead(bb, &b));
  PetscCall(VecRestoreArray(xx, &x));
  PetscCall(PetscLogFlops(4.0 * bs2 * a->nz - (bs + 2.0 * bs2) * mbs));
  PetscFunctionReturn(0);
}

PetscErrorCode MatForwardSolve_SeqSBAIJ_N_inplace(Mat A, Vec bb, Vec xx) {
  PetscFunctionBegin;
  SETERRQ(PETSC_COMM_SELF, PETSC_ERR_SUP, "not implemented yet");
}

PetscErrorCode MatBackwardSolve_SeqSBAIJ_N_inplace(Mat A, Vec bb, Vec xx) {
  PetscFunctionBegin;
  SETERRQ(PETSC_COMM_SELF, PETSC_ERR_SUP, "Not yet implemented");
}

PetscErrorCode MatForwardSolve_SeqSBAIJ_N_NaturalOrdering(const PetscInt *ai, const PetscInt *aj, const MatScalar *aa, PetscInt mbs, PetscInt bs, PetscScalar *x) {
  PetscInt         nz, k;
  const PetscInt  *vj, bs2 = bs * bs;
  const MatScalar *v, *diag;
  PetscScalar     *xk, *xj, *xk_tmp;

  PetscFunctionBegin;
  PetscCall(PetscMalloc1(bs, &xk_tmp));
  for (k = 0; k < mbs; k++) {
    v  = aa + bs2 * ai[k];
    xk = x + k * bs;                          /* Dk*xk = k-th block of x */
    PetscCall(PetscArraycpy(xk_tmp, xk, bs)); /* xk_tmp <- xk */
    nz = ai[k + 1] - ai[k];
    vj = aj + ai[k];
    xj = x + (*vj) * bs; /* *vj-th block of x, *vj>k */
    while (nz--) {
      /* x(:) += U(k,:)^T*(Dk*xk) */
      PetscKernel_v_gets_v_plus_Atranspose_times_w(bs, xj, v, xk_tmp); /* xj <- xj + v^t * xk */
      vj++;
      xj = x + (*vj) * bs;
      v += bs2;
    }
    /* xk = inv(Dk)*(Dk*xk) */
    diag = aa + k * bs2;                                /* ptr to inv(Dk) */
    PetscKernel_w_gets_A_times_v(bs, xk_tmp, diag, xk); /* xk <- diag * xk */
  }
  PetscCall(PetscFree(xk_tmp));
  PetscFunctionReturn(0);
}

PetscErrorCode MatBackwardSolve_SeqSBAIJ_N_NaturalOrdering(const PetscInt *ai, const PetscInt *aj, const MatScalar *aa, PetscInt mbs, PetscInt bs, PetscScalar *x) {
  PetscInt         nz, k;
  const PetscInt  *vj, bs2 = bs * bs;
  const MatScalar *v;
  PetscScalar     *xk, *xj;

  PetscFunctionBegin;
  for (k = mbs - 1; k >= 0; k--) {
    v  = aa + bs2 * ai[k];
    xk = x + k * bs; /* xk */
    nz = ai[k + 1] - ai[k];
    vj = aj + ai[k];
    xj = x + (*vj) * bs;
    while (nz--) {
      /* xk += U(k,:)*x(:) */
      PetscKernel_v_gets_v_plus_A_times_w(bs, xk, v, xj); /* xk <- xk + v*xj */
      vj++;
      v += bs2;
      xj = x + (*vj) * bs;
    }
  }
  PetscFunctionReturn(0);
}

PetscErrorCode MatSolve_SeqSBAIJ_N_NaturalOrdering_inplace(Mat A, Vec bb, Vec xx) {
  Mat_SeqSBAIJ      *a   = (Mat_SeqSBAIJ *)A->data;
  const PetscInt     mbs = a->mbs, *ai = a->i, *aj = a->j;
  PetscInt           bs = A->rmap->bs;
  const MatScalar   *aa = a->a;
  PetscScalar       *x;
  const PetscScalar *b;

  PetscFunctionBegin;
  PetscCall(VecGetArrayRead(bb, &b));
  PetscCall(VecGetArray(xx, &x));

  /* solve U^T * D * y = b by forward substitution */
  PetscCall(PetscArraycpy(x, b, bs * mbs)); /* x <- b */
  PetscCall(MatForwardSolve_SeqSBAIJ_N_NaturalOrdering(ai, aj, aa, mbs, bs, x));

  /* solve U*x = y by back substitution */
  PetscCall(MatBackwardSolve_SeqSBAIJ_N_NaturalOrdering(ai, aj, aa, mbs, bs, x));

  PetscCall(VecRestoreArrayRead(bb, &b));
  PetscCall(VecRestoreArray(xx, &x));
  PetscCall(PetscLogFlops(4.0 * a->bs2 * a->nz - (bs + 2.0 * a->bs2) * mbs));
  PetscFunctionReturn(0);
}

PetscErrorCode MatForwardSolve_SeqSBAIJ_N_NaturalOrdering_inplace(Mat A, Vec bb, Vec xx) {
  Mat_SeqSBAIJ      *a   = (Mat_SeqSBAIJ *)A->data;
  const PetscInt     mbs = a->mbs, *ai = a->i, *aj = a->j;
  PetscInt           bs = A->rmap->bs;
  const MatScalar   *aa = a->a;
  const PetscScalar *b;
  PetscScalar       *x;

  PetscFunctionBegin;
  PetscCall(VecGetArrayRead(bb, &b));
  PetscCall(VecGetArray(xx, &x));
  PetscCall(PetscArraycpy(x, b, bs * mbs)); /* x <- b */
  PetscCall(MatForwardSolve_SeqSBAIJ_N_NaturalOrdering(ai, aj, aa, mbs, bs, x));
  PetscCall(VecRestoreArrayRead(bb, &b));
  PetscCall(VecRestoreArray(xx, &x));
  PetscCall(PetscLogFlops(2.0 * a->bs2 * a->nz - bs * mbs));
  PetscFunctionReturn(0);
}

PetscErrorCode MatBackwardSolve_SeqSBAIJ_N_NaturalOrdering_inplace(Mat A, Vec bb, Vec xx) {
  Mat_SeqSBAIJ      *a   = (Mat_SeqSBAIJ *)A->data;
  const PetscInt     mbs = a->mbs, *ai = a->i, *aj = a->j;
  PetscInt           bs = A->rmap->bs;
  const MatScalar   *aa = a->a;
  const PetscScalar *b;
  PetscScalar       *x;

  PetscFunctionBegin;
  PetscCall(VecGetArrayRead(bb, &b));
  PetscCall(VecGetArray(xx, &x));
  PetscCall(PetscArraycpy(x, b, bs * mbs));
  PetscCall(MatBackwardSolve_SeqSBAIJ_N_NaturalOrdering(ai, aj, aa, mbs, bs, x));
  PetscCall(VecRestoreArrayRead(bb, &b));
  PetscCall(VecRestoreArray(xx, &x));
  PetscCall(PetscLogFlops(2.0 * a->bs2 * (a->nz - mbs)));
  PetscFunctionReturn(0);
}

PetscErrorCode MatSolve_SeqSBAIJ_7_inplace(Mat A, Vec bb, Vec xx) {
  Mat_SeqSBAIJ      *a     = (Mat_SeqSBAIJ *)A->data;
  IS                 isrow = a->row;
  const PetscInt     mbs = a->mbs, *ai = a->i, *aj = a->j, *r, *vj;
  PetscInt           nz, k, idx;
  const MatScalar   *aa = a->a, *v, *d;
  PetscScalar       *x, x0, x1, x2, x3, x4, x5, x6, *t, *tp;
  const PetscScalar *b;

  PetscFunctionBegin;
  PetscCall(VecGetArrayRead(bb, &b));
  PetscCall(VecGetArray(xx, &x));
  t = a->solve_work;
  PetscCall(ISGetIndices(isrow, &r));

  /* solve U^T * D * y = b by forward substitution */
  tp = t;
  for (k = 0; k < mbs; k++) { /* t <- perm(b) */
    idx   = 7 * r[k];
    tp[0] = b[idx];
    tp[1] = b[idx + 1];
    tp[2] = b[idx + 2];
    tp[3] = b[idx + 3];
    tp[4] = b[idx + 4];
    tp[5] = b[idx + 5];
    tp[6] = b[idx + 6];
    tp += 7;
  }

  for (k = 0; k < mbs; k++) {
    v  = aa + 49 * ai[k];
    vj = aj + ai[k];
    tp = t + k * 7;
    x0 = tp[0];
    x1 = tp[1];
    x2 = tp[2];
    x3 = tp[3];
    x4 = tp[4];
    x5 = tp[5];
    x6 = tp[6];
    nz = ai[k + 1] - ai[k];
    tp = t + (*vj) * 7;
    while (nz--) {
      tp[0] += v[0] * x0 + v[1] * x1 + v[2] * x2 + v[3] * x3 + v[4] * x4 + v[5] * x5 + v[6] * x6;
      tp[1] += v[7] * x0 + v[8] * x1 + v[9] * x2 + v[10] * x3 + v[11] * x4 + v[12] * x5 + v[13] * x6;
      tp[2] += v[14] * x0 + v[15] * x1 + v[16] * x2 + v[17] * x3 + v[18] * x4 + v[19] * x5 + v[20] * x6;
      tp[3] += v[21] * x0 + v[22] * x1 + v[23] * x2 + v[24] * x3 + v[25] * x4 + v[26] * x5 + v[27] * x6;
      tp[4] += v[28] * x0 + v[29] * x1 + v[30] * x2 + v[31] * x3 + v[32] * x4 + v[33] * x5 + v[34] * x6;
      tp[5] += v[35] * x0 + v[36] * x1 + v[37] * x2 + v[38] * x3 + v[39] * x4 + v[40] * x5 + v[41] * x6;
      tp[6] += v[42] * x0 + v[43] * x1 + v[44] * x2 + v[45] * x3 + v[46] * x4 + v[47] * x5 + v[48] * x6;
      vj++;
      tp = t + (*vj) * 7;
      v += 49;
    }

    /* xk = inv(Dk)*(Dk*xk) */
    d     = aa + k * 49; /* ptr to inv(Dk) */
    tp    = t + k * 7;
    tp[0] = d[0] * x0 + d[7] * x1 + d[14] * x2 + d[21] * x3 + d[28] * x4 + d[35] * x5 + d[42] * x6;
    tp[1] = d[1] * x0 + d[8] * x1 + d[15] * x2 + d[22] * x3 + d[29] * x4 + d[36] * x5 + d[43] * x6;
    tp[2] = d[2] * x0 + d[9] * x1 + d[16] * x2 + d[23] * x3 + d[30] * x4 + d[37] * x5 + d[44] * x6;
    tp[3] = d[3] * x0 + d[10] * x1 + d[17] * x2 + d[24] * x3 + d[31] * x4 + d[38] * x5 + d[45] * x6;
    tp[4] = d[4] * x0 + d[11] * x1 + d[18] * x2 + d[25] * x3 + d[32] * x4 + d[39] * x5 + d[46] * x6;
    tp[5] = d[5] * x0 + d[12] * x1 + d[19] * x2 + d[26] * x3 + d[33] * x4 + d[40] * x5 + d[47] * x6;
    tp[6] = d[6] * x0 + d[13] * x1 + d[20] * x2 + d[27] * x3 + d[34] * x4 + d[41] * x5 + d[48] * x6;
  }

  /* solve U*x = y by back substitution */
  for (k = mbs - 1; k >= 0; k--) {
    v  = aa + 49 * ai[k];
    vj = aj + ai[k];
    tp = t + k * 7;
    x0 = tp[0];
    x1 = tp[1];
    x2 = tp[2];
    x3 = tp[3];
    x4 = tp[4];
    x5 = tp[5];
    x6 = tp[6]; /* xk */
    nz = ai[k + 1] - ai[k];

    tp = t + (*vj) * 7;
    while (nz--) {
      /* xk += U(k,:)*x(:) */
      x0 += v[0] * tp[0] + v[7] * tp[1] + v[14] * tp[2] + v[21] * tp[3] + v[28] * tp[4] + v[35] * tp[5] + v[42] * tp[6];
      x1 += v[1] * tp[0] + v[8] * tp[1] + v[15] * tp[2] + v[22] * tp[3] + v[29] * tp[4] + v[36] * tp[5] + v[43] * tp[6];
      x2 += v[2] * tp[0] + v[9] * tp[1] + v[16] * tp[2] + v[23] * tp[3] + v[30] * tp[4] + v[37] * tp[5] + v[44] * tp[6];
      x3 += v[3] * tp[0] + v[10] * tp[1] + v[17] * tp[2] + v[24] * tp[3] + v[31] * tp[4] + v[38] * tp[5] + v[45] * tp[6];
      x4 += v[4] * tp[0] + v[11] * tp[1] + v[18] * tp[2] + v[25] * tp[3] + v[32] * tp[4] + v[39] * tp[5] + v[46] * tp[6];
      x5 += v[5] * tp[0] + v[12] * tp[1] + v[19] * tp[2] + v[26] * tp[3] + v[33] * tp[4] + v[40] * tp[5] + v[47] * tp[6];
      x6 += v[6] * tp[0] + v[13] * tp[1] + v[20] * tp[2] + v[27] * tp[3] + v[34] * tp[4] + v[41] * tp[5] + v[48] * tp[6];
      vj++;
      tp = t + (*vj) * 7;
      v += 49;
    }
    tp         = t + k * 7;
    tp[0]      = x0;
    tp[1]      = x1;
    tp[2]      = x2;
    tp[3]      = x3;
    tp[4]      = x4;
    tp[5]      = x5;
    tp[6]      = x6;
    idx        = 7 * r[k];
    x[idx]     = x0;
    x[idx + 1] = x1;
    x[idx + 2] = x2;
    x[idx + 3] = x3;
    x[idx + 4] = x4;
    x[idx + 5] = x5;
    x[idx + 6] = x6;
  }

  PetscCall(ISRestoreIndices(isrow, &r));
  PetscCall(VecRestoreArrayRead(bb, &b));
  PetscCall(VecRestoreArray(xx, &x));
  PetscCall(PetscLogFlops(4.0 * a->bs2 * a->nz - (A->rmap->bs + 2.0 * a->bs2) * mbs));
  PetscFunctionReturn(0);
}

PetscErrorCode MatForwardSolve_SeqSBAIJ_7_NaturalOrdering(const PetscInt *ai, const PetscInt *aj, const MatScalar *aa, PetscInt mbs, PetscScalar *x) {
  const MatScalar *v, *d;
  PetscScalar     *xp, x0, x1, x2, x3, x4, x5, x6;
  PetscInt         nz, k;
  const PetscInt  *vj;

  PetscFunctionBegin;
  for (k = 0; k < mbs; k++) {
    v  = aa + 49 * ai[k];
    xp = x + k * 7;
    x0 = xp[0];
    x1 = xp[1];
    x2 = xp[2];
    x3 = xp[3];
    x4 = xp[4];
    x5 = xp[5];
    x6 = xp[6]; /* Dk*xk = k-th block of x */
    nz = ai[k + 1] - ai[k];
    vj = aj + ai[k];
    PetscPrefetchBlock(vj + nz, nz, 0, PETSC_PREFETCH_HINT_NTA);          /* Indices for the next row (assumes same size as this one) */
    PetscPrefetchBlock(v + 49 * nz, 49 * nz, 0, PETSC_PREFETCH_HINT_NTA); /* Entries for the next row */
    while (nz--) {
      xp = x + (*vj) * 7;
      /* x(:) += U(k,:)^T*(Dk*xk) */
      xp[0] += v[0] * x0 + v[1] * x1 + v[2] * x2 + v[3] * x3 + v[4] * x4 + v[5] * x5 + v[6] * x6;
      xp[1] += v[7] * x0 + v[8] * x1 + v[9] * x2 + v[10] * x3 + v[11] * x4 + v[12] * x5 + v[13] * x6;
      xp[2] += v[14] * x0 + v[15] * x1 + v[16] * x2 + v[17] * x3 + v[18] * x4 + v[19] * x5 + v[20] * x6;
      xp[3] += v[21] * x0 + v[22] * x1 + v[23] * x2 + v[24] * x3 + v[25] * x4 + v[26] * x5 + v[27] * x6;
      xp[4] += v[28] * x0 + v[29] * x1 + v[30] * x2 + v[31] * x3 + v[32] * x4 + v[33] * x5 + v[34] * x6;
      xp[5] += v[35] * x0 + v[36] * x1 + v[37] * x2 + v[38] * x3 + v[39] * x4 + v[40] * x5 + v[41] * x6;
      xp[6] += v[42] * x0 + v[43] * x1 + v[44] * x2 + v[45] * x3 + v[46] * x4 + v[47] * x5 + v[48] * x6;
      vj++;
      v += 49;
    }
    /* xk = inv(Dk)*(Dk*xk) */
    d     = aa + k * 49; /* ptr to inv(Dk) */
    xp    = x + k * 7;
    xp[0] = d[0] * x0 + d[7] * x1 + d[14] * x2 + d[21] * x3 + d[28] * x4 + d[35] * x5 + d[42] * x6;
    xp[1] = d[1] * x0 + d[8] * x1 + d[15] * x2 + d[22] * x3 + d[29] * x4 + d[36] * x5 + d[43] * x6;
    xp[2] = d[2] * x0 + d[9] * x1 + d[16] * x2 + d[23] * x3 + d[30] * x4 + d[37] * x5 + d[44] * x6;
    xp[3] = d[3] * x0 + d[10] * x1 + d[17] * x2 + d[24] * x3 + d[31] * x4 + d[38] * x5 + d[45] * x6;
    xp[4] = d[4] * x0 + d[11] * x1 + d[18] * x2 + d[25] * x3 + d[32] * x4 + d[39] * x5 + d[46] * x6;
    xp[5] = d[5] * x0 + d[12] * x1 + d[19] * x2 + d[26] * x3 + d[33] * x4 + d[40] * x5 + d[47] * x6;
    xp[6] = d[6] * x0 + d[13] * x1 + d[20] * x2 + d[27] * x3 + d[34] * x4 + d[41] * x5 + d[48] * x6;
  }
  PetscFunctionReturn(0);
}

PetscErrorCode MatBackwardSolve_SeqSBAIJ_7_NaturalOrdering(const PetscInt *ai, const PetscInt *aj, const MatScalar *aa, PetscInt mbs, PetscScalar *x) {
  const MatScalar *v;
  PetscScalar     *xp, x0, x1, x2, x3, x4, x5, x6;
  PetscInt         nz, k;
  const PetscInt  *vj;

  PetscFunctionBegin;
  for (k = mbs - 1; k >= 0; k--) {
    v  = aa + 49 * ai[k];
    xp = x + k * 7;
    x0 = xp[0];
    x1 = xp[1];
    x2 = xp[2];
    x3 = xp[3];
    x4 = xp[4];
    x5 = xp[5];
    x6 = xp[6]; /* xk */
    nz = ai[k + 1] - ai[k];
    vj = aj + ai[k];
    PetscPrefetchBlock(vj - nz, nz, 0, PETSC_PREFETCH_HINT_NTA);          /* Indices for the next row (assumes same size as this one) */
    PetscPrefetchBlock(v - 49 * nz, 49 * nz, 0, PETSC_PREFETCH_HINT_NTA); /* Entries for the next row */
    while (nz--) {
      xp = x + (*vj) * 7;
      /* xk += U(k,:)*x(:) */
      x0 += v[0] * xp[0] + v[7] * xp[1] + v[14] * xp[2] + v[21] * xp[3] + v[28] * xp[4] + v[35] * xp[5] + v[42] * xp[6];
      x1 += v[1] * xp[0] + v[8] * xp[1] + v[15] * xp[2] + v[22] * xp[3] + v[29] * xp[4] + v[36] * xp[5] + v[43] * xp[6];
      x2 += v[2] * xp[0] + v[9] * xp[1] + v[16] * xp[2] + v[23] * xp[3] + v[30] * xp[4] + v[37] * xp[5] + v[44] * xp[6];
      x3 += v[3] * xp[0] + v[10] * xp[1] + v[17] * xp[2] + v[24] * xp[3] + v[31] * xp[4] + v[38] * xp[5] + v[45] * xp[6];
      x4 += v[4] * xp[0] + v[11] * xp[1] + v[18] * xp[2] + v[25] * xp[3] + v[32] * xp[4] + v[39] * xp[5] + v[46] * xp[6];
      x5 += v[5] * xp[0] + v[12] * xp[1] + v[19] * xp[2] + v[26] * xp[3] + v[33] * xp[4] + v[40] * xp[5] + v[47] * xp[6];
      x6 += v[6] * xp[0] + v[13] * xp[1] + v[20] * xp[2] + v[27] * xp[3] + v[34] * xp[4] + v[41] * xp[5] + v[48] * xp[6];
      vj++;
      v += 49;
    }
    xp    = x + k * 7;
    xp[0] = x0;
    xp[1] = x1;
    xp[2] = x2;
    xp[3] = x3;
    xp[4] = x4;
    xp[5] = x5;
    xp[6] = x6;
  }
  PetscFunctionReturn(0);
}

PetscErrorCode MatSolve_SeqSBAIJ_7_NaturalOrdering_inplace(Mat A, Vec bb, Vec xx) {
  Mat_SeqSBAIJ      *a   = (Mat_SeqSBAIJ *)A->data;
  const PetscInt     mbs = a->mbs, *ai = a->i, *aj = a->j;
  const MatScalar   *aa = a->a;
  PetscScalar       *x;
  const PetscScalar *b;

  PetscFunctionBegin;
  PetscCall(VecGetArrayRead(bb, &b));
  PetscCall(VecGetArray(xx, &x));

  /* solve U^T * D * y = b by forward substitution */
  PetscCall(PetscArraycpy(x, b, 7 * mbs)); /* x <- b */
  PetscCall(MatForwardSolve_SeqSBAIJ_7_NaturalOrdering(ai, aj, aa, mbs, x));

  /* solve U*x = y by back substitution */
  PetscCall(MatBackwardSolve_SeqSBAIJ_7_NaturalOrdering(ai, aj, aa, mbs, x));

  PetscCall(VecRestoreArrayRead(bb, &b));
  PetscCall(VecRestoreArray(xx, &x));
  PetscCall(PetscLogFlops(4.0 * a->bs2 * a->nz - (A->rmap->bs + 2.0 * a->bs2) * mbs));
  PetscFunctionReturn(0);
}

PetscErrorCode MatForwardSolve_SeqSBAIJ_7_NaturalOrdering_inplace(Mat A, Vec bb, Vec xx) {
  Mat_SeqSBAIJ      *a   = (Mat_SeqSBAIJ *)A->data;
  const PetscInt     mbs = a->mbs, *ai = a->i, *aj = a->j;
  const MatScalar   *aa = a->a;
  PetscScalar       *x;
  const PetscScalar *b;

  PetscFunctionBegin;
  PetscCall(VecGetArrayRead(bb, &b));
  PetscCall(VecGetArray(xx, &x));
  PetscCall(PetscArraycpy(x, b, 7 * mbs));
  PetscCall(MatForwardSolve_SeqSBAIJ_7_NaturalOrdering(ai, aj, aa, mbs, x));
  PetscCall(VecRestoreArrayRead(bb, &b));
  PetscCall(VecRestoreArray(xx, &x));
  PetscCall(PetscLogFlops(2.0 * a->bs2 * a->nz - A->rmap->bs * mbs));
  PetscFunctionReturn(0);
}

PetscErrorCode MatBackwardSolve_SeqSBAIJ_7_NaturalOrdering_inplace(Mat A, Vec bb, Vec xx) {
  Mat_SeqSBAIJ      *a   = (Mat_SeqSBAIJ *)A->data;
  const PetscInt     mbs = a->mbs, *ai = a->i, *aj = a->j;
  const MatScalar   *aa = a->a;
  PetscScalar       *x;
  const PetscScalar *b;

  PetscFunctionBegin;
  PetscCall(VecGetArrayRead(bb, &b));
  PetscCall(VecGetArray(xx, &x));
  PetscCall(PetscArraycpy(x, b, 7 * mbs));
  PetscCall(MatBackwardSolve_SeqSBAIJ_7_NaturalOrdering(ai, aj, aa, mbs, x));
  PetscCall(VecRestoreArrayRead(bb, &b));
  PetscCall(VecRestoreArray(xx, &x));
  PetscCall(PetscLogFlops(2.0 * a->bs2 * (a->nz - mbs)));
  PetscFunctionReturn(0);
}

PetscErrorCode MatSolve_SeqSBAIJ_6_inplace(Mat A, Vec bb, Vec xx) {
  Mat_SeqSBAIJ      *a     = (Mat_SeqSBAIJ *)A->data;
  IS                 isrow = a->row;
  const PetscInt     mbs = a->mbs, *ai = a->i, *aj = a->j, *r, *vj;
  PetscInt           nz, k, idx;
  const MatScalar   *aa = a->a, *v, *d;
  PetscScalar       *x, x0, x1, x2, x3, x4, x5, *t, *tp;
  const PetscScalar *b;

  PetscFunctionBegin;
  PetscCall(VecGetArrayRead(bb, &b));
  PetscCall(VecGetArray(xx, &x));
  t = a->solve_work;
  PetscCall(ISGetIndices(isrow, &r));

  /* solve U^T * D * y = b by forward substitution */
  tp = t;
  for (k = 0; k < mbs; k++) { /* t <- perm(b) */
    idx   = 6 * r[k];
    tp[0] = b[idx];
    tp[1] = b[idx + 1];
    tp[2] = b[idx + 2];
    tp[3] = b[idx + 3];
    tp[4] = b[idx + 4];
    tp[5] = b[idx + 5];
    tp += 6;
  }

  for (k = 0; k < mbs; k++) {
    v  = aa + 36 * ai[k];
    vj = aj + ai[k];
    tp = t + k * 6;
    x0 = tp[0];
    x1 = tp[1];
    x2 = tp[2];
    x3 = tp[3];
    x4 = tp[4];
    x5 = tp[5];
    nz = ai[k + 1] - ai[k];
    tp = t + (*vj) * 6;
    while (nz--) {
      tp[0] += v[0] * x0 + v[1] * x1 + v[2] * x2 + v[3] * x3 + v[4] * x4 + v[5] * x5;
      tp[1] += v[6] * x0 + v[7] * x1 + v[8] * x2 + v[9] * x3 + v[10] * x4 + v[11] * x5;
      tp[2] += v[12] * x0 + v[13] * x1 + v[14] * x2 + v[15] * x3 + v[16] * x4 + v[17] * x5;
      tp[3] += v[18] * x0 + v[19] * x1 + v[20] * x2 + v[21] * x3 + v[22] * x4 + v[23] * x5;
      tp[4] += v[24] * x0 + v[25] * x1 + v[26] * x2 + v[27] * x3 + v[28] * x4 + v[29] * x5;
      tp[5] += v[30] * x0 + v[31] * x1 + v[32] * x2 + v[33] * x3 + v[34] * x4 + v[35] * x5;
      vj++;
      tp = t + (*vj) * 6;
      v += 36;
    }

    /* xk = inv(Dk)*(Dk*xk) */
    d     = aa + k * 36; /* ptr to inv(Dk) */
    tp    = t + k * 6;
    tp[0] = d[0] * x0 + d[6] * x1 + d[12] * x2 + d[18] * x3 + d[24] * x4 + d[30] * x5;
    tp[1] = d[1] * x0 + d[7] * x1 + d[13] * x2 + d[19] * x3 + d[25] * x4 + d[31] * x5;
    tp[2] = d[2] * x0 + d[8] * x1 + d[14] * x2 + d[20] * x3 + d[26] * x4 + d[32] * x5;
    tp[3] = d[3] * x0 + d[9] * x1 + d[15] * x2 + d[21] * x3 + d[27] * x4 + d[33] * x5;
    tp[4] = d[4] * x0 + d[10] * x1 + d[16] * x2 + d[22] * x3 + d[28] * x4 + d[34] * x5;
    tp[5] = d[5] * x0 + d[11] * x1 + d[17] * x2 + d[23] * x3 + d[29] * x4 + d[35] * x5;
  }

  /* solve U*x = y by back substitution */
  for (k = mbs - 1; k >= 0; k--) {
    v  = aa + 36 * ai[k];
    vj = aj + ai[k];
    tp = t + k * 6;
    x0 = tp[0];
    x1 = tp[1];
    x2 = tp[2];
    x3 = tp[3];
    x4 = tp[4];
    x5 = tp[5]; /* xk */
    nz = ai[k + 1] - ai[k];

    tp = t + (*vj) * 6;
    while (nz--) {
      /* xk += U(k,:)*x(:) */
      x0 += v[0] * tp[0] + v[6] * tp[1] + v[12] * tp[2] + v[18] * tp[3] + v[24] * tp[4] + v[30] * tp[5];
      x1 += v[1] * tp[0] + v[7] * tp[1] + v[13] * tp[2] + v[19] * tp[3] + v[25] * tp[4] + v[31] * tp[5];
      x2 += v[2] * tp[0] + v[8] * tp[1] + v[14] * tp[2] + v[20] * tp[3] + v[26] * tp[4] + v[32] * tp[5];
      x3 += v[3] * tp[0] + v[9] * tp[1] + v[15] * tp[2] + v[21] * tp[3] + v[27] * tp[4] + v[33] * tp[5];
      x4 += v[4] * tp[0] + v[10] * tp[1] + v[16] * tp[2] + v[22] * tp[3] + v[28] * tp[4] + v[34] * tp[5];
      x5 += v[5] * tp[0] + v[11] * tp[1] + v[17] * tp[2] + v[23] * tp[3] + v[29] * tp[4] + v[35] * tp[5];
      vj++;
      tp = t + (*vj) * 6;
      v += 36;
    }
    tp         = t + k * 6;
    tp[0]      = x0;
    tp[1]      = x1;
    tp[2]      = x2;
    tp[3]      = x3;
    tp[4]      = x4;
    tp[5]      = x5;
    idx        = 6 * r[k];
    x[idx]     = x0;
    x[idx + 1] = x1;
    x[idx + 2] = x2;
    x[idx + 3] = x3;
    x[idx + 4] = x4;
    x[idx + 5] = x5;
  }

  PetscCall(ISRestoreIndices(isrow, &r));
  PetscCall(VecRestoreArrayRead(bb, &b));
  PetscCall(VecRestoreArray(xx, &x));
  PetscCall(PetscLogFlops(4.0 * a->bs2 * a->nz - (A->rmap->bs + 2.0 * a->bs2) * mbs));
  PetscFunctionReturn(0);
}

PetscErrorCode MatForwardSolve_SeqSBAIJ_6_NaturalOrdering(const PetscInt *ai, const PetscInt *aj, const MatScalar *aa, PetscInt mbs, PetscScalar *x) {
  const MatScalar *v, *d;
  PetscScalar     *xp, x0, x1, x2, x3, x4, x5;
  PetscInt         nz, k;
  const PetscInt  *vj;

  PetscFunctionBegin;
  for (k = 0; k < mbs; k++) {
    v  = aa + 36 * ai[k];
    xp = x + k * 6;
    x0 = xp[0];
    x1 = xp[1];
    x2 = xp[2];
    x3 = xp[3];
    x4 = xp[4];
    x5 = xp[5]; /* Dk*xk = k-th block of x */
    nz = ai[k + 1] - ai[k];
    vj = aj + ai[k];
    PetscPrefetchBlock(vj + nz, nz, 0, PETSC_PREFETCH_HINT_NTA);          /* Indices for the next row (assumes same size as this one) */
    PetscPrefetchBlock(v + 36 * nz, 36 * nz, 0, PETSC_PREFETCH_HINT_NTA); /* Entries for the next row */
    while (nz--) {
      xp = x + (*vj) * 6;
      /* x(:) += U(k,:)^T*(Dk*xk) */
      xp[0] += v[0] * x0 + v[1] * x1 + v[2] * x2 + v[3] * x3 + v[4] * x4 + v[5] * x5;
      xp[1] += v[6] * x0 + v[7] * x1 + v[8] * x2 + v[9] * x3 + v[10] * x4 + v[11] * x5;
      xp[2] += v[12] * x0 + v[13] * x1 + v[14] * x2 + v[15] * x3 + v[16] * x4 + v[17] * x5;
      xp[3] += v[18] * x0 + v[19] * x1 + v[20] * x2 + v[21] * x3 + v[22] * x4 + v[23] * x5;
      xp[4] += v[24] * x0 + v[25] * x1 + v[26] * x2 + v[27] * x3 + v[28] * x4 + v[29] * x5;
      xp[5] += v[30] * x0 + v[31] * x1 + v[32] * x2 + v[33] * x3 + v[34] * x4 + v[35] * x5;
      vj++;
      v += 36;
    }
    /* xk = inv(Dk)*(Dk*xk) */
    d     = aa + k * 36; /* ptr to inv(Dk) */
    xp    = x + k * 6;
    xp[0] = d[0] * x0 + d[6] * x1 + d[12] * x2 + d[18] * x3 + d[24] * x4 + d[30] * x5;
    xp[1] = d[1] * x0 + d[7] * x1 + d[13] * x2 + d[19] * x3 + d[25] * x4 + d[31] * x5;
    xp[2] = d[2] * x0 + d[8] * x1 + d[14] * x2 + d[20] * x3 + d[26] * x4 + d[32] * x5;
    xp[3] = d[3] * x0 + d[9] * x1 + d[15] * x2 + d[21] * x3 + d[27] * x4 + d[33] * x5;
    xp[4] = d[4] * x0 + d[10] * x1 + d[16] * x2 + d[22] * x3 + d[28] * x4 + d[34] * x5;
    xp[5] = d[5] * x0 + d[11] * x1 + d[17] * x2 + d[23] * x3 + d[29] * x4 + d[35] * x5;
  }
  PetscFunctionReturn(0);
}
PetscErrorCode MatBackwardSolve_SeqSBAIJ_6_NaturalOrdering(const PetscInt *ai, const PetscInt *aj, const MatScalar *aa, PetscInt mbs, PetscScalar *x) {
  const MatScalar *v;
  PetscScalar     *xp, x0, x1, x2, x3, x4, x5;
  PetscInt         nz, k;
  const PetscInt  *vj;

  PetscFunctionBegin;
  for (k = mbs - 1; k >= 0; k--) {
    v  = aa + 36 * ai[k];
    xp = x + k * 6;
    x0 = xp[0];
    x1 = xp[1];
    x2 = xp[2];
    x3 = xp[3];
    x4 = xp[4];
    x5 = xp[5]; /* xk */
    nz = ai[k + 1] - ai[k];
    vj = aj + ai[k];
    PetscPrefetchBlock(vj - nz, nz, 0, PETSC_PREFETCH_HINT_NTA);          /* Indices for the next row (assumes same size as this one) */
    PetscPrefetchBlock(v - 36 * nz, 36 * nz, 0, PETSC_PREFETCH_HINT_NTA); /* Entries for the next row */
    while (nz--) {
      xp = x + (*vj) * 6;
      /* xk += U(k,:)*x(:) */
      x0 += v[0] * xp[0] + v[6] * xp[1] + v[12] * xp[2] + v[18] * xp[3] + v[24] * xp[4] + v[30] * xp[5];
      x1 += v[1] * xp[0] + v[7] * xp[1] + v[13] * xp[2] + v[19] * xp[3] + v[25] * xp[4] + v[31] * xp[5];
      x2 += v[2] * xp[0] + v[8] * xp[1] + v[14] * xp[2] + v[20] * xp[3] + v[26] * xp[4] + v[32] * xp[5];
      x3 += v[3] * xp[0] + v[9] * xp[1] + v[15] * xp[2] + v[21] * xp[3] + v[27] * xp[4] + v[33] * xp[5];
      x4 += v[4] * xp[0] + v[10] * xp[1] + v[16] * xp[2] + v[22] * xp[3] + v[28] * xp[4] + v[34] * xp[5];
      x5 += v[5] * xp[0] + v[11] * xp[1] + v[17] * xp[2] + v[23] * xp[3] + v[29] * xp[4] + v[35] * xp[5];
      vj++;
      v += 36;
    }
    xp    = x + k * 6;
    xp[0] = x0;
    xp[1] = x1;
    xp[2] = x2;
    xp[3] = x3;
    xp[4] = x4;
    xp[5] = x5;
  }
  PetscFunctionReturn(0);
}

PetscErrorCode MatSolve_SeqSBAIJ_6_NaturalOrdering_inplace(Mat A, Vec bb, Vec xx) {
  Mat_SeqSBAIJ      *a   = (Mat_SeqSBAIJ *)A->data;
  const PetscInt     mbs = a->mbs, *ai = a->i, *aj = a->j;
  const MatScalar   *aa = a->a;
  PetscScalar       *x;
  const PetscScalar *b;

  PetscFunctionBegin;
  PetscCall(VecGetArrayRead(bb, &b));
  PetscCall(VecGetArray(xx, &x));

  /* solve U^T * D * y = b by forward substitution */
  PetscCall(PetscArraycpy(x, b, 6 * mbs)); /* x <- b */
  PetscCall(MatForwardSolve_SeqSBAIJ_6_NaturalOrdering(ai, aj, aa, mbs, x));

  /* solve U*x = y by back substitution */
  PetscCall(MatBackwardSolve_SeqSBAIJ_6_NaturalOrdering(ai, aj, aa, mbs, x));

  PetscCall(VecRestoreArrayRead(bb, &b));
  PetscCall(VecRestoreArray(xx, &x));
  PetscCall(PetscLogFlops(4.0 * a->bs2 * a->nz - (A->rmap->bs + 2.0 * a->bs2) * mbs));
  PetscFunctionReturn(0);
}

PetscErrorCode MatForwardSolve_SeqSBAIJ_6_NaturalOrdering_inplace(Mat A, Vec bb, Vec xx) {
  Mat_SeqSBAIJ      *a   = (Mat_SeqSBAIJ *)A->data;
  const PetscInt     mbs = a->mbs, *ai = a->i, *aj = a->j;
  const MatScalar   *aa = a->a;
  PetscScalar       *x;
  const PetscScalar *b;

  PetscFunctionBegin;
  PetscCall(VecGetArrayRead(bb, &b));
  PetscCall(VecGetArray(xx, &x));
  PetscCall(PetscArraycpy(x, b, 6 * mbs)); /* x <- b */
  PetscCall(MatForwardSolve_SeqSBAIJ_6_NaturalOrdering(ai, aj, aa, mbs, x));
  PetscCall(VecRestoreArrayRead(bb, &b));
  PetscCall(VecRestoreArray(xx, &x));
  PetscCall(PetscLogFlops(2.0 * a->bs2 * a->nz - A->rmap->bs * mbs));
  PetscFunctionReturn(0);
}

PetscErrorCode MatBackwardSolve_SeqSBAIJ_6_NaturalOrdering_inplace(Mat A, Vec bb, Vec xx) {
  Mat_SeqSBAIJ      *a   = (Mat_SeqSBAIJ *)A->data;
  const PetscInt     mbs = a->mbs, *ai = a->i, *aj = a->j;
  const MatScalar   *aa = a->a;
  PetscScalar       *x;
  const PetscScalar *b;

  PetscFunctionBegin;
  PetscCall(VecGetArrayRead(bb, &b));
  PetscCall(VecGetArray(xx, &x));
  PetscCall(PetscArraycpy(x, b, 6 * mbs)); /* x <- b */
  PetscCall(MatBackwardSolve_SeqSBAIJ_6_NaturalOrdering(ai, aj, aa, mbs, x));
  PetscCall(VecRestoreArrayRead(bb, &b));
  PetscCall(VecRestoreArray(xx, &x));
  PetscCall(PetscLogFlops(2.0 * a->bs2 * (a->nz - mbs)));
  PetscFunctionReturn(0);
}

PetscErrorCode MatSolve_SeqSBAIJ_5_inplace(Mat A, Vec bb, Vec xx) {
  Mat_SeqSBAIJ      *a     = (Mat_SeqSBAIJ *)A->data;
  IS                 isrow = a->row;
  const PetscInt     mbs = a->mbs, *ai = a->i, *aj = a->j;
  const PetscInt    *r, *vj;
  PetscInt           nz, k, idx;
  const MatScalar   *aa = a->a, *v, *diag;
  PetscScalar       *x, x0, x1, x2, x3, x4, *t, *tp;
  const PetscScalar *b;

  PetscFunctionBegin;
  PetscCall(VecGetArrayRead(bb, &b));
  PetscCall(VecGetArray(xx, &x));
  t = a->solve_work;
  PetscCall(ISGetIndices(isrow, &r));

  /* solve U^T * D * y = b by forward substitution */
  tp = t;
  for (k = 0; k < mbs; k++) { /* t <- perm(b) */
    idx   = 5 * r[k];
    tp[0] = b[idx];
    tp[1] = b[idx + 1];
    tp[2] = b[idx + 2];
    tp[3] = b[idx + 3];
    tp[4] = b[idx + 4];
    tp += 5;
  }

  for (k = 0; k < mbs; k++) {
    v  = aa + 25 * ai[k];
    vj = aj + ai[k];
    tp = t + k * 5;
    x0 = tp[0];
    x1 = tp[1];
    x2 = tp[2];
    x3 = tp[3];
    x4 = tp[4];
    nz = ai[k + 1] - ai[k];

    tp = t + (*vj) * 5;
    while (nz--) {
      tp[0] += v[0] * x0 + v[1] * x1 + v[2] * x2 + v[3] * x3 + v[4] * x4;
      tp[1] += v[5] * x0 + v[6] * x1 + v[7] * x2 + v[8] * x3 + v[9] * x4;
      tp[2] += v[10] * x0 + v[11] * x1 + v[12] * x2 + v[13] * x3 + v[14] * x4;
      tp[3] += v[15] * x0 + v[16] * x1 + v[17] * x2 + v[18] * x3 + v[19] * x4;
      tp[4] += v[20] * x0 + v[21] * x1 + v[22] * x2 + v[23] * x3 + v[24] * x4;
      vj++;
      tp = t + (*vj) * 5;
      v += 25;
    }

    /* xk = inv(Dk)*(Dk*xk) */
    diag  = aa + k * 25; /* ptr to inv(Dk) */
    tp    = t + k * 5;
    tp[0] = diag[0] * x0 + diag[5] * x1 + diag[10] * x2 + diag[15] * x3 + diag[20] * x4;
    tp[1] = diag[1] * x0 + diag[6] * x1 + diag[11] * x2 + diag[16] * x3 + diag[21] * x4;
    tp[2] = diag[2] * x0 + diag[7] * x1 + diag[12] * x2 + diag[17] * x3 + diag[22] * x4;
    tp[3] = diag[3] * x0 + diag[8] * x1 + diag[13] * x2 + diag[18] * x3 + diag[23] * x4;
    tp[4] = diag[4] * x0 + diag[9] * x1 + diag[14] * x2 + diag[19] * x3 + diag[24] * x4;
  }

  /* solve U*x = y by back substitution */
  for (k = mbs - 1; k >= 0; k--) {
    v  = aa + 25 * ai[k];
    vj = aj + ai[k];
    tp = t + k * 5;
    x0 = tp[0];
    x1 = tp[1];
    x2 = tp[2];
    x3 = tp[3];
    x4 = tp[4]; /* xk */
    nz = ai[k + 1] - ai[k];

    tp = t + (*vj) * 5;
    while (nz--) {
      /* xk += U(k,:)*x(:) */
      x0 += v[0] * tp[0] + v[5] * tp[1] + v[10] * tp[2] + v[15] * tp[3] + v[20] * tp[4];
      x1 += v[1] * tp[0] + v[6] * tp[1] + v[11] * tp[2] + v[16] * tp[3] + v[21] * tp[4];
      x2 += v[2] * tp[0] + v[7] * tp[1] + v[12] * tp[2] + v[17] * tp[3] + v[22] * tp[4];
      x3 += v[3] * tp[0] + v[8] * tp[1] + v[13] * tp[2] + v[18] * tp[3] + v[23] * tp[4];
      x4 += v[4] * tp[0] + v[9] * tp[1] + v[14] * tp[2] + v[19] * tp[3] + v[24] * tp[4];
      vj++;
      tp = t + (*vj) * 5;
      v += 25;
    }
    tp         = t + k * 5;
    tp[0]      = x0;
    tp[1]      = x1;
    tp[2]      = x2;
    tp[3]      = x3;
    tp[4]      = x4;
    idx        = 5 * r[k];
    x[idx]     = x0;
    x[idx + 1] = x1;
    x[idx + 2] = x2;
    x[idx + 3] = x3;
    x[idx + 4] = x4;
  }

  PetscCall(ISRestoreIndices(isrow, &r));
  PetscCall(VecRestoreArrayRead(bb, &b));
  PetscCall(VecRestoreArray(xx, &x));
  PetscCall(PetscLogFlops(4.0 * a->bs2 * a->nz - (A->rmap->bs + 2.0 * a->bs2) * mbs));
  PetscFunctionReturn(0);
}

PetscErrorCode MatForwardSolve_SeqSBAIJ_5_NaturalOrdering(const PetscInt *ai, const PetscInt *aj, const MatScalar *aa, PetscInt mbs, PetscScalar *x) {
  const MatScalar *v, *diag;
  PetscScalar     *xp, x0, x1, x2, x3, x4;
  PetscInt         nz, k;
  const PetscInt  *vj;

  PetscFunctionBegin;
  for (k = 0; k < mbs; k++) {
    v  = aa + 25 * ai[k];
    xp = x + k * 5;
    x0 = xp[0];
    x1 = xp[1];
    x2 = xp[2];
    x3 = xp[3];
    x4 = xp[4]; /* Dk*xk = k-th block of x */
    nz = ai[k + 1] - ai[k];
    vj = aj + ai[k];
    PetscPrefetchBlock(vj + nz, nz, 0, PETSC_PREFETCH_HINT_NTA);          /* Indices for the next row (assumes same size as this one) */
    PetscPrefetchBlock(v + 25 * nz, 25 * nz, 0, PETSC_PREFETCH_HINT_NTA); /* Entries for the next row */
    while (nz--) {
      xp = x + (*vj) * 5;
      /* x(:) += U(k,:)^T*(Dk*xk) */
      xp[0] += v[0] * x0 + v[1] * x1 + v[2] * x2 + v[3] * x3 + v[4] * x4;
      xp[1] += v[5] * x0 + v[6] * x1 + v[7] * x2 + v[8] * x3 + v[9] * x4;
      xp[2] += v[10] * x0 + v[11] * x1 + v[12] * x2 + v[13] * x3 + v[14] * x4;
      xp[3] += v[15] * x0 + v[16] * x1 + v[17] * x2 + v[18] * x3 + v[19] * x4;
      xp[4] += v[20] * x0 + v[21] * x1 + v[22] * x2 + v[23] * x3 + v[24] * x4;
      vj++;
      v += 25;
    }
    /* xk = inv(Dk)*(Dk*xk) */
    diag  = aa + k * 25; /* ptr to inv(Dk) */
    xp    = x + k * 5;
    xp[0] = diag[0] * x0 + diag[5] * x1 + diag[10] * x2 + diag[15] * x3 + diag[20] * x4;
    xp[1] = diag[1] * x0 + diag[6] * x1 + diag[11] * x2 + diag[16] * x3 + diag[21] * x4;
    xp[2] = diag[2] * x0 + diag[7] * x1 + diag[12] * x2 + diag[17] * x3 + diag[22] * x4;
    xp[3] = diag[3] * x0 + diag[8] * x1 + diag[13] * x2 + diag[18] * x3 + diag[23] * x4;
    xp[4] = diag[4] * x0 + diag[9] * x1 + diag[14] * x2 + diag[19] * x3 + diag[24] * x4;
  }
  PetscFunctionReturn(0);
}

PetscErrorCode MatBackwardSolve_SeqSBAIJ_5_NaturalOrdering(const PetscInt *ai, const PetscInt *aj, const MatScalar *aa, PetscInt mbs, PetscScalar *x) {
  const MatScalar *v;
  PetscScalar     *xp, x0, x1, x2, x3, x4;
  PetscInt         nz, k;
  const PetscInt  *vj;

  PetscFunctionBegin;
  for (k = mbs - 1; k >= 0; k--) {
    v  = aa + 25 * ai[k];
    xp = x + k * 5;
    x0 = xp[0];
    x1 = xp[1];
    x2 = xp[2];
    x3 = xp[3];
    x4 = xp[4]; /* xk */
    nz = ai[k + 1] - ai[k];
    vj = aj + ai[k];
    PetscPrefetchBlock(vj - nz, nz, 0, PETSC_PREFETCH_HINT_NTA);          /* Indices for the next row (assumes same size as this one) */
    PetscPrefetchBlock(v - 25 * nz, 25 * nz, 0, PETSC_PREFETCH_HINT_NTA); /* Entries for the next row */
    while (nz--) {
      xp = x + (*vj) * 5;
      /* xk += U(k,:)*x(:) */
      x0 += v[0] * xp[0] + v[5] * xp[1] + v[10] * xp[2] + v[15] * xp[3] + v[20] * xp[4];
      x1 += v[1] * xp[0] + v[6] * xp[1] + v[11] * xp[2] + v[16] * xp[3] + v[21] * xp[4];
      x2 += v[2] * xp[0] + v[7] * xp[1] + v[12] * xp[2] + v[17] * xp[3] + v[22] * xp[4];
      x3 += v[3] * xp[0] + v[8] * xp[1] + v[13] * xp[2] + v[18] * xp[3] + v[23] * xp[4];
      x4 += v[4] * xp[0] + v[9] * xp[1] + v[14] * xp[2] + v[19] * xp[3] + v[24] * xp[4];
      vj++;
      v += 25;
    }
    xp    = x + k * 5;
    xp[0] = x0;
    xp[1] = x1;
    xp[2] = x2;
    xp[3] = x3;
    xp[4] = x4;
  }
  PetscFunctionReturn(0);
}

PetscErrorCode MatSolve_SeqSBAIJ_5_NaturalOrdering_inplace(Mat A, Vec bb, Vec xx) {
  Mat_SeqSBAIJ      *a   = (Mat_SeqSBAIJ *)A->data;
  const PetscInt     mbs = a->mbs, *ai = a->i, *aj = a->j;
  const MatScalar   *aa = a->a;
  PetscScalar       *x;
  const PetscScalar *b;

  PetscFunctionBegin;
  PetscCall(VecGetArrayRead(bb, &b));
  PetscCall(VecGetArray(xx, &x));

  /* solve U^T * D * y = b by forward substitution */
  PetscCall(PetscArraycpy(x, b, 5 * mbs)); /* x <- b */
  PetscCall(MatForwardSolve_SeqSBAIJ_5_NaturalOrdering(ai, aj, aa, mbs, x));

  /* solve U*x = y by back substitution */
  PetscCall(MatBackwardSolve_SeqSBAIJ_5_NaturalOrdering(ai, aj, aa, mbs, x));

  PetscCall(VecRestoreArrayRead(bb, &b));
  PetscCall(VecRestoreArray(xx, &x));
  PetscCall(PetscLogFlops(4.0 * a->bs2 * a->nz - (A->rmap->bs + 2.0 * a->bs2) * mbs));
  PetscFunctionReturn(0);
}

PetscErrorCode MatForwardSolve_SeqSBAIJ_5_NaturalOrdering_inplace(Mat A, Vec bb, Vec xx) {
  Mat_SeqSBAIJ      *a   = (Mat_SeqSBAIJ *)A->data;
  const PetscInt     mbs = a->mbs, *ai = a->i, *aj = a->j;
  const MatScalar   *aa = a->a;
  PetscScalar       *x;
  const PetscScalar *b;

  PetscFunctionBegin;
  PetscCall(VecGetArrayRead(bb, &b));
  PetscCall(VecGetArray(xx, &x));
  PetscCall(PetscArraycpy(x, b, 5 * mbs)); /* x <- b */
  PetscCall(MatForwardSolve_SeqSBAIJ_5_NaturalOrdering(ai, aj, aa, mbs, x));
  PetscCall(VecRestoreArrayRead(bb, &b));
  PetscCall(VecRestoreArray(xx, &x));
  PetscCall(PetscLogFlops(2.0 * a->bs2 * a->nz - A->rmap->bs * mbs));
  PetscFunctionReturn(0);
}

PetscErrorCode MatBackwardSolve_SeqSBAIJ_5_NaturalOrdering_inplace(Mat A, Vec bb, Vec xx) {
  Mat_SeqSBAIJ      *a   = (Mat_SeqSBAIJ *)A->data;
  const PetscInt     mbs = a->mbs, *ai = a->i, *aj = a->j;
  const MatScalar   *aa = a->a;
  PetscScalar       *x;
  const PetscScalar *b;

  PetscFunctionBegin;
  PetscCall(VecGetArrayRead(bb, &b));
  PetscCall(VecGetArray(xx, &x));
  PetscCall(PetscArraycpy(x, b, 5 * mbs));
  PetscCall(MatBackwardSolve_SeqSBAIJ_5_NaturalOrdering(ai, aj, aa, mbs, x));
  PetscCall(VecRestoreArrayRead(bb, &b));
  PetscCall(VecRestoreArray(xx, &x));
  PetscCall(PetscLogFlops(2.0 * a->bs2 * (a->nz - mbs)));
  PetscFunctionReturn(0);
}

PetscErrorCode MatSolve_SeqSBAIJ_4_inplace(Mat A, Vec bb, Vec xx) {
  Mat_SeqSBAIJ      *a     = (Mat_SeqSBAIJ *)A->data;
  IS                 isrow = a->row;
  const PetscInt     mbs = a->mbs, *ai = a->i, *aj = a->j;
  const PetscInt    *r, *vj;
  PetscInt           nz, k, idx;
  const MatScalar   *aa = a->a, *v, *diag;
  PetscScalar       *x, x0, x1, x2, x3, *t, *tp;
  const PetscScalar *b;

  PetscFunctionBegin;
  PetscCall(VecGetArrayRead(bb, &b));
  PetscCall(VecGetArray(xx, &x));
  t = a->solve_work;
  PetscCall(ISGetIndices(isrow, &r));

  /* solve U^T * D * y = b by forward substitution */
  tp = t;
  for (k = 0; k < mbs; k++) { /* t <- perm(b) */
    idx   = 4 * r[k];
    tp[0] = b[idx];
    tp[1] = b[idx + 1];
    tp[2] = b[idx + 2];
    tp[3] = b[idx + 3];
    tp += 4;
  }

  for (k = 0; k < mbs; k++) {
    v  = aa + 16 * ai[k];
    vj = aj + ai[k];
    tp = t + k * 4;
    x0 = tp[0];
    x1 = tp[1];
    x2 = tp[2];
    x3 = tp[3];
    nz = ai[k + 1] - ai[k];

    tp = t + (*vj) * 4;
    while (nz--) {
      tp[0] += v[0] * x0 + v[1] * x1 + v[2] * x2 + v[3] * x3;
      tp[1] += v[4] * x0 + v[5] * x1 + v[6] * x2 + v[7] * x3;
      tp[2] += v[8] * x0 + v[9] * x1 + v[10] * x2 + v[11] * x3;
      tp[3] += v[12] * x0 + v[13] * x1 + v[14] * x2 + v[15] * x3;
      vj++;
      tp = t + (*vj) * 4;
      v += 16;
    }

    /* xk = inv(Dk)*(Dk*xk) */
    diag  = aa + k * 16; /* ptr to inv(Dk) */
    tp    = t + k * 4;
    tp[0] = diag[0] * x0 + diag[4] * x1 + diag[8] * x2 + diag[12] * x3;
    tp[1] = diag[1] * x0 + diag[5] * x1 + diag[9] * x2 + diag[13] * x3;
    tp[2] = diag[2] * x0 + diag[6] * x1 + diag[10] * x2 + diag[14] * x3;
    tp[3] = diag[3] * x0 + diag[7] * x1 + diag[11] * x2 + diag[15] * x3;
  }

  /* solve U*x = y by back substitution */
  for (k = mbs - 1; k >= 0; k--) {
    v  = aa + 16 * ai[k];
    vj = aj + ai[k];
    tp = t + k * 4;
    x0 = tp[0];
    x1 = tp[1];
    x2 = tp[2];
    x3 = tp[3]; /* xk */
    nz = ai[k + 1] - ai[k];

    tp = t + (*vj) * 4;
    while (nz--) {
      /* xk += U(k,:)*x(:) */
      x0 += v[0] * tp[0] + v[4] * tp[1] + v[8] * tp[2] + v[12] * tp[3];
      x1 += v[1] * tp[0] + v[5] * tp[1] + v[9] * tp[2] + v[13] * tp[3];
      x2 += v[2] * tp[0] + v[6] * tp[1] + v[10] * tp[2] + v[14] * tp[3];
      x3 += v[3] * tp[0] + v[7] * tp[1] + v[11] * tp[2] + v[15] * tp[3];
      vj++;
      tp = t + (*vj) * 4;
      v += 16;
    }
    tp         = t + k * 4;
    tp[0]      = x0;
    tp[1]      = x1;
    tp[2]      = x2;
    tp[3]      = x3;
    idx        = 4 * r[k];
    x[idx]     = x0;
    x[idx + 1] = x1;
    x[idx + 2] = x2;
    x[idx + 3] = x3;
  }

  PetscCall(ISRestoreIndices(isrow, &r));
  PetscCall(VecRestoreArrayRead(bb, &b));
  PetscCall(VecRestoreArray(xx, &x));
  PetscCall(PetscLogFlops(4.0 * a->bs2 * a->nz - (A->rmap->bs + 2.0 * a->bs2) * mbs));
  PetscFunctionReturn(0);
}

PetscErrorCode MatForwardSolve_SeqSBAIJ_4_NaturalOrdering(const PetscInt *ai, const PetscInt *aj, const MatScalar *aa, PetscInt mbs, PetscScalar *x) {
  const MatScalar *v, *diag;
  PetscScalar     *xp, x0, x1, x2, x3;
  PetscInt         nz, k;
  const PetscInt  *vj;

  PetscFunctionBegin;
  for (k = 0; k < mbs; k++) {
    v  = aa + 16 * ai[k];
    xp = x + k * 4;
    x0 = xp[0];
    x1 = xp[1];
    x2 = xp[2];
    x3 = xp[3]; /* Dk*xk = k-th block of x */
    nz = ai[k + 1] - ai[k];
    vj = aj + ai[k];
    PetscPrefetchBlock(vj + nz, nz, 0, PETSC_PREFETCH_HINT_NTA);          /* Indices for the next row (assumes same size as this one) */
    PetscPrefetchBlock(v + 16 * nz, 16 * nz, 0, PETSC_PREFETCH_HINT_NTA); /* Entries for the next row */
    while (nz--) {
      xp = x + (*vj) * 4;
      /* x(:) += U(k,:)^T*(Dk*xk) */
      xp[0] += v[0] * x0 + v[1] * x1 + v[2] * x2 + v[3] * x3;
      xp[1] += v[4] * x0 + v[5] * x1 + v[6] * x2 + v[7] * x3;
      xp[2] += v[8] * x0 + v[9] * x1 + v[10] * x2 + v[11] * x3;
      xp[3] += v[12] * x0 + v[13] * x1 + v[14] * x2 + v[15] * x3;
      vj++;
      v += 16;
    }
    /* xk = inv(Dk)*(Dk*xk) */
    diag  = aa + k * 16; /* ptr to inv(Dk) */
    xp    = x + k * 4;
    xp[0] = diag[0] * x0 + diag[4] * x1 + diag[8] * x2 + diag[12] * x3;
    xp[1] = diag[1] * x0 + diag[5] * x1 + diag[9] * x2 + diag[13] * x3;
    xp[2] = diag[2] * x0 + diag[6] * x1 + diag[10] * x2 + diag[14] * x3;
    xp[3] = diag[3] * x0 + diag[7] * x1 + diag[11] * x2 + diag[15] * x3;
  }
  PetscFunctionReturn(0);
}

PetscErrorCode MatBackwardSolve_SeqSBAIJ_4_NaturalOrdering(const PetscInt *ai, const PetscInt *aj, const MatScalar *aa, PetscInt mbs, PetscScalar *x) {
  const MatScalar *v;
  PetscScalar     *xp, x0, x1, x2, x3;
  PetscInt         nz, k;
  const PetscInt  *vj;

  PetscFunctionBegin;
  for (k = mbs - 1; k >= 0; k--) {
    v  = aa + 16 * ai[k];
    xp = x + k * 4;
    x0 = xp[0];
    x1 = xp[1];
    x2 = xp[2];
    x3 = xp[3]; /* xk */
    nz = ai[k + 1] - ai[k];
    vj = aj + ai[k];
    PetscPrefetchBlock(vj - nz, nz, 0, PETSC_PREFETCH_HINT_NTA);          /* Indices for the next row (assumes same size as this one) */
    PetscPrefetchBlock(v - 16 * nz, 16 * nz, 0, PETSC_PREFETCH_HINT_NTA); /* Entries for the next row */
    while (nz--) {
      xp = x + (*vj) * 4;
      /* xk += U(k,:)*x(:) */
      x0 += v[0] * xp[0] + v[4] * xp[1] + v[8] * xp[2] + v[12] * xp[3];
      x1 += v[1] * xp[0] + v[5] * xp[1] + v[9] * xp[2] + v[13] * xp[3];
      x2 += v[2] * xp[0] + v[6] * xp[1] + v[10] * xp[2] + v[14] * xp[3];
      x3 += v[3] * xp[0] + v[7] * xp[1] + v[11] * xp[2] + v[15] * xp[3];
      vj++;
      v += 16;
    }
    xp    = x + k * 4;
    xp[0] = x0;
    xp[1] = x1;
    xp[2] = x2;
    xp[3] = x3;
  }
  PetscFunctionReturn(0);
}

PetscErrorCode MatSolve_SeqSBAIJ_4_NaturalOrdering_inplace(Mat A, Vec bb, Vec xx) {
  Mat_SeqSBAIJ      *a   = (Mat_SeqSBAIJ *)A->data;
  const PetscInt     mbs = a->mbs, *ai = a->i, *aj = a->j;
  const MatScalar   *aa = a->a;
  PetscScalar       *x;
  const PetscScalar *b;

  PetscFunctionBegin;
  PetscCall(VecGetArrayRead(bb, &b));
  PetscCall(VecGetArray(xx, &x));

  /* solve U^T * D * y = b by forward substitution */
  PetscCall(PetscArraycpy(x, b, 4 * mbs)); /* x <- b */
  PetscCall(MatForwardSolve_SeqSBAIJ_4_NaturalOrdering(ai, aj, aa, mbs, x));

  /* solve U*x = y by back substitution */
  PetscCall(MatBackwardSolve_SeqSBAIJ_4_NaturalOrdering(ai, aj, aa, mbs, x));
  PetscCall(VecRestoreArrayRead(bb, &b));
  PetscCall(VecRestoreArray(xx, &x));
  PetscCall(PetscLogFlops(4.0 * a->bs2 * a->nz - (A->rmap->bs + 2.0 * a->bs2) * mbs));
  PetscFunctionReturn(0);
}

PetscErrorCode MatForwardSolve_SeqSBAIJ_4_NaturalOrdering_inplace(Mat A, Vec bb, Vec xx) {
  Mat_SeqSBAIJ      *a   = (Mat_SeqSBAIJ *)A->data;
  const PetscInt     mbs = a->mbs, *ai = a->i, *aj = a->j;
  const MatScalar   *aa = a->a;
  PetscScalar       *x;
  const PetscScalar *b;

  PetscFunctionBegin;
  PetscCall(VecGetArrayRead(bb, &b));
  PetscCall(VecGetArray(xx, &x));
  PetscCall(PetscArraycpy(x, b, 4 * mbs)); /* x <- b */
  PetscCall(MatForwardSolve_SeqSBAIJ_4_NaturalOrdering(ai, aj, aa, mbs, x));
  PetscCall(VecRestoreArrayRead(bb, &b));
  PetscCall(VecRestoreArray(xx, &x));
  PetscCall(PetscLogFlops(2.0 * a->bs2 * a->nz - A->rmap->bs * mbs));
  PetscFunctionReturn(0);
}

PetscErrorCode MatBackwardSolve_SeqSBAIJ_4_NaturalOrdering_inplace(Mat A, Vec bb, Vec xx) {
  Mat_SeqSBAIJ      *a   = (Mat_SeqSBAIJ *)A->data;
  const PetscInt     mbs = a->mbs, *ai = a->i, *aj = a->j;
  const MatScalar   *aa = a->a;
  PetscScalar       *x;
  const PetscScalar *b;

  PetscFunctionBegin;
  PetscCall(VecGetArrayRead(bb, &b));
  PetscCall(VecGetArray(xx, &x));
  PetscCall(PetscArraycpy(x, b, 4 * mbs));
  PetscCall(MatBackwardSolve_SeqSBAIJ_4_NaturalOrdering(ai, aj, aa, mbs, x));
  PetscCall(VecRestoreArrayRead(bb, &b));
  PetscCall(VecRestoreArray(xx, &x));
  PetscCall(PetscLogFlops(2.0 * a->bs2 * (a->nz - mbs)));
  PetscFunctionReturn(0);
}

PetscErrorCode MatSolve_SeqSBAIJ_3_inplace(Mat A, Vec bb, Vec xx) {
  Mat_SeqSBAIJ      *a     = (Mat_SeqSBAIJ *)A->data;
  IS                 isrow = a->row;
  const PetscInt     mbs = a->mbs, *ai = a->i, *aj = a->j;
  const PetscInt    *r;
  PetscInt           nz, k, idx;
  const PetscInt    *vj;
  const MatScalar   *aa = a->a, *v, *diag;
  PetscScalar       *x, x0, x1, x2, *t, *tp;
  const PetscScalar *b;

  PetscFunctionBegin;
  PetscCall(VecGetArrayRead(bb, &b));
  PetscCall(VecGetArray(xx, &x));
  t = a->solve_work;
  PetscCall(ISGetIndices(isrow, &r));

  /* solve U^T * D * y = b by forward substitution */
  tp = t;
  for (k = 0; k < mbs; k++) { /* t <- perm(b) */
    idx   = 3 * r[k];
    tp[0] = b[idx];
    tp[1] = b[idx + 1];
    tp[2] = b[idx + 2];
    tp += 3;
  }

  for (k = 0; k < mbs; k++) {
    v  = aa + 9 * ai[k];
    vj = aj + ai[k];
    tp = t + k * 3;
    x0 = tp[0];
    x1 = tp[1];
    x2 = tp[2];
    nz = ai[k + 1] - ai[k];

    tp = t + (*vj) * 3;
    while (nz--) {
      tp[0] += v[0] * x0 + v[1] * x1 + v[2] * x2;
      tp[1] += v[3] * x0 + v[4] * x1 + v[5] * x2;
      tp[2] += v[6] * x0 + v[7] * x1 + v[8] * x2;
      vj++;
      tp = t + (*vj) * 3;
      v += 9;
    }

    /* xk = inv(Dk)*(Dk*xk) */
    diag  = aa + k * 9; /* ptr to inv(Dk) */
    tp    = t + k * 3;
    tp[0] = diag[0] * x0 + diag[3] * x1 + diag[6] * x2;
    tp[1] = diag[1] * x0 + diag[4] * x1 + diag[7] * x2;
    tp[2] = diag[2] * x0 + diag[5] * x1 + diag[8] * x2;
  }

  /* solve U*x = y by back substitution */
  for (k = mbs - 1; k >= 0; k--) {
    v  = aa + 9 * ai[k];
    vj = aj + ai[k];
    tp = t + k * 3;
    x0 = tp[0];
    x1 = tp[1];
    x2 = tp[2]; /* xk */
    nz = ai[k + 1] - ai[k];

    tp = t + (*vj) * 3;
    while (nz--) {
      /* xk += U(k,:)*x(:) */
      x0 += v[0] * tp[0] + v[3] * tp[1] + v[6] * tp[2];
      x1 += v[1] * tp[0] + v[4] * tp[1] + v[7] * tp[2];
      x2 += v[2] * tp[0] + v[5] * tp[1] + v[8] * tp[2];
      vj++;
      tp = t + (*vj) * 3;
      v += 9;
    }
    tp         = t + k * 3;
    tp[0]      = x0;
    tp[1]      = x1;
    tp[2]      = x2;
    idx        = 3 * r[k];
    x[idx]     = x0;
    x[idx + 1] = x1;
    x[idx + 2] = x2;
  }

  PetscCall(ISRestoreIndices(isrow, &r));
  PetscCall(VecRestoreArrayRead(bb, &b));
  PetscCall(VecRestoreArray(xx, &x));
  PetscCall(PetscLogFlops(4.0 * a->bs2 * a->nz - (A->rmap->bs + 2.0 * a->bs2) * mbs));
  PetscFunctionReturn(0);
}

PetscErrorCode MatForwardSolve_SeqSBAIJ_3_NaturalOrdering(const PetscInt *ai, const PetscInt *aj, const MatScalar *aa, PetscInt mbs, PetscScalar *x) {
  const MatScalar *v, *diag;
  PetscScalar     *xp, x0, x1, x2;
  PetscInt         nz, k;
  const PetscInt  *vj;

  PetscFunctionBegin;
  for (k = 0; k < mbs; k++) {
    v  = aa + 9 * ai[k];
    xp = x + k * 3;
    x0 = xp[0];
    x1 = xp[1];
    x2 = xp[2]; /* Dk*xk = k-th block of x */
    nz = ai[k + 1] - ai[k];
    vj = aj + ai[k];
    PetscPrefetchBlock(vj + nz, nz, 0, PETSC_PREFETCH_HINT_NTA);        /* Indices for the next row (assumes same size as this one) */
    PetscPrefetchBlock(v + 9 * nz, 9 * nz, 0, PETSC_PREFETCH_HINT_NTA); /* Entries for the next row */
    while (nz--) {
      xp = x + (*vj) * 3;
      /* x(:) += U(k,:)^T*(Dk*xk) */
      xp[0] += v[0] * x0 + v[1] * x1 + v[2] * x2;
      xp[1] += v[3] * x0 + v[4] * x1 + v[5] * x2;
      xp[2] += v[6] * x0 + v[7] * x1 + v[8] * x2;
      vj++;
      v += 9;
    }
    /* xk = inv(Dk)*(Dk*xk) */
    diag  = aa + k * 9; /* ptr to inv(Dk) */
    xp    = x + k * 3;
    xp[0] = diag[0] * x0 + diag[3] * x1 + diag[6] * x2;
    xp[1] = diag[1] * x0 + diag[4] * x1 + diag[7] * x2;
    xp[2] = diag[2] * x0 + diag[5] * x1 + diag[8] * x2;
  }
  PetscFunctionReturn(0);
}

PetscErrorCode MatBackwardSolve_SeqSBAIJ_3_NaturalOrdering(const PetscInt *ai, const PetscInt *aj, const MatScalar *aa, PetscInt mbs, PetscScalar *x) {
  const MatScalar *v;
  PetscScalar     *xp, x0, x1, x2;
  PetscInt         nz, k;
  const PetscInt  *vj;

  PetscFunctionBegin;
  for (k = mbs - 1; k >= 0; k--) {
    v  = aa + 9 * ai[k];
    xp = x + k * 3;
    x0 = xp[0];
    x1 = xp[1];
    x2 = xp[2]; /* xk */
    nz = ai[k + 1] - ai[k];
    vj = aj + ai[k];
    PetscPrefetchBlock(vj - nz, nz, 0, PETSC_PREFETCH_HINT_NTA);        /* Indices for the next row (assumes same size as this one) */
    PetscPrefetchBlock(v - 9 * nz, 9 * nz, 0, PETSC_PREFETCH_HINT_NTA); /* Entries for the next row */
    while (nz--) {
      xp = x + (*vj) * 3;
      /* xk += U(k,:)*x(:) */
      x0 += v[0] * xp[0] + v[3] * xp[1] + v[6] * xp[2];
      x1 += v[1] * xp[0] + v[4] * xp[1] + v[7] * xp[2];
      x2 += v[2] * xp[0] + v[5] * xp[1] + v[8] * xp[2];
      vj++;
      v += 9;
    }
    xp    = x + k * 3;
    xp[0] = x0;
    xp[1] = x1;
    xp[2] = x2;
  }
  PetscFunctionReturn(0);
}

PetscErrorCode MatSolve_SeqSBAIJ_3_NaturalOrdering_inplace(Mat A, Vec bb, Vec xx) {
  Mat_SeqSBAIJ      *a   = (Mat_SeqSBAIJ *)A->data;
  const PetscInt     mbs = a->mbs, *ai = a->i, *aj = a->j;
  const MatScalar   *aa = a->a;
  PetscScalar       *x;
  const PetscScalar *b;

  PetscFunctionBegin;
  PetscCall(VecGetArrayRead(bb, &b));
  PetscCall(VecGetArray(xx, &x));

  /* solve U^T * D * y = b by forward substitution */
  PetscCall(PetscArraycpy(x, b, 3 * mbs));
  PetscCall(MatForwardSolve_SeqSBAIJ_3_NaturalOrdering(ai, aj, aa, mbs, x));

  /* solve U*x = y by back substitution */
  PetscCall(MatBackwardSolve_SeqSBAIJ_3_NaturalOrdering(ai, aj, aa, mbs, x));

  PetscCall(VecRestoreArrayRead(bb, &b));
  PetscCall(VecRestoreArray(xx, &x));
  PetscCall(PetscLogFlops(4.0 * a->bs2 * a->nz - (A->rmap->bs + 2.0 * a->bs2) * mbs));
  PetscFunctionReturn(0);
}

PetscErrorCode MatForwardSolve_SeqSBAIJ_3_NaturalOrdering_inplace(Mat A, Vec bb, Vec xx) {
  Mat_SeqSBAIJ      *a   = (Mat_SeqSBAIJ *)A->data;
  const PetscInt     mbs = a->mbs, *ai = a->i, *aj = a->j;
  const MatScalar   *aa = a->a;
  PetscScalar       *x;
  const PetscScalar *b;

  PetscFunctionBegin;
  PetscCall(VecGetArrayRead(bb, &b));
  PetscCall(VecGetArray(xx, &x));
  PetscCall(PetscArraycpy(x, b, 3 * mbs));
  PetscCall(MatForwardSolve_SeqSBAIJ_3_NaturalOrdering(ai, aj, aa, mbs, x));
  PetscCall(VecRestoreArrayRead(bb, &b));
  PetscCall(VecRestoreArray(xx, &x));
  PetscCall(PetscLogFlops(2.0 * a->bs2 * a->nz - A->rmap->bs * mbs));
  PetscFunctionReturn(0);
}

PetscErrorCode MatBackwardSolve_SeqSBAIJ_3_NaturalOrdering_inplace(Mat A, Vec bb, Vec xx) {
  Mat_SeqSBAIJ      *a   = (Mat_SeqSBAIJ *)A->data;
  const PetscInt     mbs = a->mbs, *ai = a->i, *aj = a->j;
  const MatScalar   *aa = a->a;
  PetscScalar       *x;
  const PetscScalar *b;

  PetscFunctionBegin;
  PetscCall(VecGetArrayRead(bb, &b));
  PetscCall(VecGetArray(xx, &x));
  PetscCall(PetscArraycpy(x, b, 3 * mbs));
  PetscCall(MatBackwardSolve_SeqSBAIJ_3_NaturalOrdering(ai, aj, aa, mbs, x));
  PetscCall(VecRestoreArrayRead(bb, &b));
  PetscCall(VecRestoreArray(xx, &x));
  PetscCall(PetscLogFlops(2.0 * a->bs2 * (a->nz - mbs)));
  PetscFunctionReturn(0);
}

PetscErrorCode MatSolve_SeqSBAIJ_2_inplace(Mat A, Vec bb, Vec xx) {
  Mat_SeqSBAIJ      *a     = (Mat_SeqSBAIJ *)A->data;
  IS                 isrow = a->row;
  const PetscInt     mbs = a->mbs, *ai = a->i, *aj = a->j;
  const PetscInt    *r, *vj;
  PetscInt           nz, k, k2, idx;
  const MatScalar   *aa = a->a, *v, *diag;
  PetscScalar       *x, x0, x1, *t;
  const PetscScalar *b;

  PetscFunctionBegin;
  PetscCall(VecGetArrayRead(bb, &b));
  PetscCall(VecGetArray(xx, &x));
  t = a->solve_work;
  PetscCall(ISGetIndices(isrow, &r));

  /* solve U^T * D * y = perm(b) by forward substitution */
  for (k = 0; k < mbs; k++) { /* t <- perm(b) */
    idx          = 2 * r[k];
    t[k * 2]     = b[idx];
    t[k * 2 + 1] = b[idx + 1];
  }
  for (k = 0; k < mbs; k++) {
    v  = aa + 4 * ai[k];
    vj = aj + ai[k];
    k2 = k * 2;
    x0 = t[k2];
    x1 = t[k2 + 1];
    nz = ai[k + 1] - ai[k];
    while (nz--) {
      t[(*vj) * 2] += v[0] * x0 + v[1] * x1;
      t[(*vj) * 2 + 1] += v[2] * x0 + v[3] * x1;
      vj++;
      v += 4;
    }
    diag      = aa + k * 4; /* ptr to inv(Dk) */
    t[k2]     = diag[0] * x0 + diag[2] * x1;
    t[k2 + 1] = diag[1] * x0 + diag[3] * x1;
  }

  /* solve U*x = y by back substitution */
  for (k = mbs - 1; k >= 0; k--) {
    v  = aa + 4 * ai[k];
    vj = aj + ai[k];
    k2 = k * 2;
    x0 = t[k2];
    x1 = t[k2 + 1];
    nz = ai[k + 1] - ai[k];
    while (nz--) {
      x0 += v[0] * t[(*vj) * 2] + v[2] * t[(*vj) * 2 + 1];
      x1 += v[1] * t[(*vj) * 2] + v[3] * t[(*vj) * 2 + 1];
      vj++;
      v += 4;
    }
    t[k2]      = x0;
    t[k2 + 1]  = x1;
    idx        = 2 * r[k];
    x[idx]     = x0;
    x[idx + 1] = x1;
  }

  PetscCall(ISRestoreIndices(isrow, &r));
  PetscCall(VecRestoreArrayRead(bb, &b));
  PetscCall(VecRestoreArray(xx, &x));
  PetscCall(PetscLogFlops(4.0 * a->bs2 * a->nz - (A->rmap->bs + 2.0 * a->bs2) * mbs));
  PetscFunctionReturn(0);
}

PetscErrorCode MatForwardSolve_SeqSBAIJ_2_NaturalOrdering(const PetscInt *ai, const PetscInt *aj, const MatScalar *aa, PetscInt mbs, PetscScalar *x) {
  const MatScalar *v, *diag;
  PetscScalar      x0, x1;
  PetscInt         nz, k, k2;
  const PetscInt  *vj;

  PetscFunctionBegin;
  for (k = 0; k < mbs; k++) {
    v  = aa + 4 * ai[k];
    vj = aj + ai[k];
    k2 = k * 2;
    x0 = x[k2];
    x1 = x[k2 + 1]; /* Dk*xk = k-th block of x */
    nz = ai[k + 1] - ai[k];
    PetscPrefetchBlock(vj + nz, nz, 0, PETSC_PREFETCH_HINT_NTA);        /* Indices for the next row (assumes same size as this one) */
    PetscPrefetchBlock(v + 4 * nz, 4 * nz, 0, PETSC_PREFETCH_HINT_NTA); /* Entries for the next row */
    while (nz--) {
      /* x(:) += U(k,:)^T*(Dk*xk) */
      x[(*vj) * 2] += v[0] * x0 + v[1] * x1;
      x[(*vj) * 2 + 1] += v[2] * x0 + v[3] * x1;
      vj++;
      v += 4;
    }
    /* xk = inv(Dk)*(Dk*xk) */
    diag      = aa + k * 4; /* ptr to inv(Dk) */
    x[k2]     = diag[0] * x0 + diag[2] * x1;
    x[k2 + 1] = diag[1] * x0 + diag[3] * x1;
  }
  PetscFunctionReturn(0);
}

PetscErrorCode MatBackwardSolve_SeqSBAIJ_2_NaturalOrdering(const PetscInt *ai, const PetscInt *aj, const MatScalar *aa, PetscInt mbs, PetscScalar *x) {
  const MatScalar *v;
  PetscScalar      x0, x1;
  PetscInt         nz, k, k2;
  const PetscInt  *vj;

  PetscFunctionBegin;
  for (k = mbs - 1; k >= 0; k--) {
    v  = aa + 4 * ai[k];
    vj = aj + ai[k];
    k2 = k * 2;
    x0 = x[k2];
    x1 = x[k2 + 1]; /* xk */
    nz = ai[k + 1] - ai[k];
    PetscPrefetchBlock(vj - nz, nz, 0, PETSC_PREFETCH_HINT_NTA);        /* Indices for the next row (assumes same size as this one) */
    PetscPrefetchBlock(v - 4 * nz, 4 * nz, 0, PETSC_PREFETCH_HINT_NTA); /* Entries for the next row */
    while (nz--) {
      /* xk += U(k,:)*x(:) */
      x0 += v[0] * x[(*vj) * 2] + v[2] * x[(*vj) * 2 + 1];
      x1 += v[1] * x[(*vj) * 2] + v[3] * x[(*vj) * 2 + 1];
      vj++;
      v += 4;
    }
    x[k2]     = x0;
    x[k2 + 1] = x1;
  }
  PetscFunctionReturn(0);
}

PetscErrorCode MatSolve_SeqSBAIJ_2_NaturalOrdering_inplace(Mat A, Vec bb, Vec xx) {
  Mat_SeqSBAIJ      *a   = (Mat_SeqSBAIJ *)A->data;
  const PetscInt     mbs = a->mbs, *ai = a->i, *aj = a->j;
  const MatScalar   *aa = a->a;
  PetscScalar       *x;
  const PetscScalar *b;

  PetscFunctionBegin;
  PetscCall(VecGetArrayRead(bb, &b));
  PetscCall(VecGetArray(xx, &x));

  /* solve U^T * D * y = b by forward substitution */
  PetscCall(PetscArraycpy(x, b, 2 * mbs));
  PetscCall(MatForwardSolve_SeqSBAIJ_2_NaturalOrdering(ai, aj, aa, mbs, x));

  /* solve U*x = y by back substitution */
  PetscCall(MatBackwardSolve_SeqSBAIJ_2_NaturalOrdering(ai, aj, aa, mbs, x));

  PetscCall(VecRestoreArrayRead(bb, &b));
  PetscCall(VecRestoreArray(xx, &x));
  PetscCall(PetscLogFlops(4.0 * a->bs2 * a->nz - (A->rmap->bs + 2.0 * a->bs2) * mbs));
  PetscFunctionReturn(0);
}

PetscErrorCode MatForwardSolve_SeqSBAIJ_2_NaturalOrdering_inplace(Mat A, Vec bb, Vec xx) {
  Mat_SeqSBAIJ      *a   = (Mat_SeqSBAIJ *)A->data;
  const PetscInt     mbs = a->mbs, *ai = a->i, *aj = a->j;
  const MatScalar   *aa = a->a;
  PetscScalar       *x;
  const PetscScalar *b;

  PetscFunctionBegin;
  PetscCall(VecGetArrayRead(bb, &b));
  PetscCall(VecGetArray(xx, &x));
  PetscCall(PetscArraycpy(x, b, 2 * mbs));
  PetscCall(MatForwardSolve_SeqSBAIJ_2_NaturalOrdering(ai, aj, aa, mbs, x));
  PetscCall(VecRestoreArrayRead(bb, &b));
  PetscCall(VecRestoreArray(xx, &x));
  PetscCall(PetscLogFlops(2.0 * a->bs2 * a->nz - A->rmap->bs * mbs));
  PetscFunctionReturn(0);
}

PetscErrorCode MatBackwardSolve_SeqSBAIJ_2_NaturalOrdering_inplace(Mat A, Vec bb, Vec xx) {
  Mat_SeqSBAIJ      *a   = (Mat_SeqSBAIJ *)A->data;
  const PetscInt     mbs = a->mbs, *ai = a->i, *aj = a->j;
  const MatScalar   *aa = a->a;
  PetscScalar       *x;
  const PetscScalar *b;

  PetscFunctionBegin;
  PetscCall(VecGetArrayRead(bb, &b));
  PetscCall(VecGetArray(xx, &x));
  PetscCall(PetscArraycpy(x, b, 2 * mbs));
  PetscCall(MatBackwardSolve_SeqSBAIJ_2_NaturalOrdering(ai, aj, aa, mbs, x));
  PetscCall(VecRestoreArrayRead(bb, &b));
  PetscCall(VecRestoreArray(xx, &x));
  PetscCall(PetscLogFlops(2.0 * a->bs2 * (a->nz - mbs)));
  PetscFunctionReturn(0);
}

PetscErrorCode MatSolve_SeqSBAIJ_1(Mat A, Vec bb, Vec xx) {
  Mat_SeqSBAIJ      *a     = (Mat_SeqSBAIJ *)A->data;
  IS                 isrow = a->row;
  const PetscInt     mbs = a->mbs, *ai = a->i, *aj = a->j, *rp, *vj, *adiag = a->diag;
  const MatScalar   *aa = a->a, *v;
  const PetscScalar *b;
  PetscScalar       *x, xk, *t;
  PetscInt           nz, k, j;

  PetscFunctionBegin;
  PetscCall(VecGetArrayRead(bb, &b));
  PetscCall(VecGetArray(xx, &x));
  t = a->solve_work;
  PetscCall(ISGetIndices(isrow, &rp));

  /* solve U^T*D*y = perm(b) by forward substitution */
  for (k = 0; k < mbs; k++) t[k] = b[rp[k]];
  for (k = 0; k < mbs; k++) {
    v  = aa + ai[k];
    vj = aj + ai[k];
    xk = t[k];
    nz = ai[k + 1] - ai[k] - 1;
    for (j = 0; j < nz; j++) t[vj[j]] += v[j] * xk;
    t[k] = xk * v[nz]; /* v[nz] = 1/D(k) */
  }

  /* solve U*perm(x) = y by back substitution */
  for (k = mbs - 1; k >= 0; k--) {
    v  = aa + adiag[k] - 1;
    vj = aj + adiag[k] - 1;
    nz = ai[k + 1] - ai[k] - 1;
    for (j = 0; j < nz; j++) t[k] += v[-j] * t[vj[-j]];
    x[rp[k]] = t[k];
  }

  PetscCall(ISRestoreIndices(isrow, &rp));
  PetscCall(VecRestoreArrayRead(bb, &b));
  PetscCall(VecRestoreArray(xx, &x));
  PetscCall(PetscLogFlops(4.0 * a->nz - 3.0 * mbs));
  PetscFunctionReturn(0);
}

PetscErrorCode MatSolve_SeqSBAIJ_1_inplace(Mat A, Vec bb, Vec xx) {
  Mat_SeqSBAIJ      *a     = (Mat_SeqSBAIJ *)A->data;
  IS                 isrow = a->row;
  const PetscInt     mbs = a->mbs, *ai = a->i, *aj = a->j, *rp, *vj;
  const MatScalar   *aa = a->a, *v;
  PetscScalar       *x, xk, *t;
  const PetscScalar *b;
  PetscInt           nz, k;

  PetscFunctionBegin;
  PetscCall(VecGetArrayRead(bb, &b));
  PetscCall(VecGetArray(xx, &x));
  t = a->solve_work;
  PetscCall(ISGetIndices(isrow, &rp));

  /* solve U^T*D*y = perm(b) by forward substitution */
  for (k = 0; k < mbs; k++) t[k] = b[rp[k]];
  for (k = 0; k < mbs; k++) {
    v  = aa + ai[k] + 1;
    vj = aj + ai[k] + 1;
    xk = t[k];
    nz = ai[k + 1] - ai[k] - 1;
    while (nz--) t[*vj++] += (*v++) * xk;
    t[k] = xk * aa[ai[k]]; /* aa[k] = 1/D(k) */
  }

  /* solve U*perm(x) = y by back substitution */
  for (k = mbs - 1; k >= 0; k--) {
    v  = aa + ai[k] + 1;
    vj = aj + ai[k] + 1;
    nz = ai[k + 1] - ai[k] - 1;
    while (nz--) t[k] += (*v++) * t[*vj++];
    x[rp[k]] = t[k];
  }

  PetscCall(ISRestoreIndices(isrow, &rp));
  PetscCall(VecRestoreArrayRead(bb, &b));
  PetscCall(VecRestoreArray(xx, &x));
  PetscCall(PetscLogFlops(4.0 * a->nz - 3 * mbs));
  PetscFunctionReturn(0);
}

PetscErrorCode MatForwardSolve_SeqSBAIJ_1(Mat A, Vec bb, Vec xx) {
  Mat_SeqSBAIJ      *a     = (Mat_SeqSBAIJ *)A->data;
  IS                 isrow = a->row;
  const PetscInt     mbs = a->mbs, *ai = a->i, *aj = a->j, *rp, *vj, *adiag = a->diag;
  const MatScalar   *aa = a->a, *v;
  PetscReal          diagk;
  PetscScalar       *x, xk;
  const PetscScalar *b;
  PetscInt           nz, k;

  PetscFunctionBegin;
  /* solve U^T*D^(1/2)*x = perm(b) by forward substitution */
  PetscCall(VecGetArrayRead(bb, &b));
  PetscCall(VecGetArray(xx, &x));
  PetscCall(ISGetIndices(isrow, &rp));

  for (k = 0; k < mbs; k++) x[k] = b[rp[k]];
  for (k = 0; k < mbs; k++) {
    v  = aa + ai[k];
    vj = aj + ai[k];
    xk = x[k];
    nz = ai[k + 1] - ai[k] - 1;
    while (nz--) x[*vj++] += (*v++) * xk;

    diagk = PetscRealPart(aa[adiag[k]]); /* note: aa[diag[k]] = 1/D(k) */
    PetscCheck(!PetscImaginaryPart(aa[adiag[k]]) && diagk >= 0, PETSC_COMM_SELF, PETSC_ERR_SUP, "Diagonal must be real and nonnegative");
    x[k] = xk * PetscSqrtReal(diagk);
  }
  PetscCall(ISRestoreIndices(isrow, &rp));
  PetscCall(VecRestoreArrayRead(bb, &b));
  PetscCall(VecRestoreArray(xx, &x));
  PetscCall(PetscLogFlops(2.0 * a->nz - mbs));
  PetscFunctionReturn(0);
}

PetscErrorCode MatForwardSolve_SeqSBAIJ_1_inplace(Mat A, Vec bb, Vec xx) {
  Mat_SeqSBAIJ      *a     = (Mat_SeqSBAIJ *)A->data;
  IS                 isrow = a->row;
  const PetscInt     mbs = a->mbs, *ai = a->i, *aj = a->j, *rp, *vj;
  const MatScalar   *aa = a->a, *v;
  PetscReal          diagk;
  PetscScalar       *x, xk;
  const PetscScalar *b;
  PetscInt           nz, k;

  PetscFunctionBegin;
  /* solve U^T*D^(1/2)*x = perm(b) by forward substitution */
  PetscCall(VecGetArrayRead(bb, &b));
  PetscCall(VecGetArray(xx, &x));
  PetscCall(ISGetIndices(isrow, &rp));

  for (k = 0; k < mbs; k++) x[k] = b[rp[k]];
  for (k = 0; k < mbs; k++) {
    v  = aa + ai[k] + 1;
    vj = aj + ai[k] + 1;
    xk = x[k];
    nz = ai[k + 1] - ai[k] - 1;
    while (nz--) x[*vj++] += (*v++) * xk;

    diagk = PetscRealPart(aa[ai[k]]); /* note: aa[diag[k]] = 1/D(k) */
    PetscCheck(!PetscImaginaryPart(aa[ai[k]]) && diagk >= 0, PETSC_COMM_SELF, PETSC_ERR_SUP, "Diagonal must be real and nonnegative");
    x[k] = xk * PetscSqrtReal(diagk);
  }
  PetscCall(ISRestoreIndices(isrow, &rp));
  PetscCall(VecRestoreArrayRead(bb, &b));
  PetscCall(VecRestoreArray(xx, &x));
  PetscCall(PetscLogFlops(2.0 * a->nz - mbs));
  PetscFunctionReturn(0);
}

PetscErrorCode MatBackwardSolve_SeqSBAIJ_1(Mat A, Vec bb, Vec xx) {
  Mat_SeqSBAIJ      *a     = (Mat_SeqSBAIJ *)A->data;
  IS                 isrow = a->row;
  const PetscInt     mbs = a->mbs, *ai = a->i, *aj = a->j, *rp, *vj, *adiag = a->diag;
  const MatScalar   *aa = a->a, *v;
  PetscReal          diagk;
  PetscScalar       *x, *t;
  const PetscScalar *b;
  PetscInt           nz, k;

  PetscFunctionBegin;
  /* solve D^(1/2)*U*perm(x) = b by back substitution */
  PetscCall(VecGetArrayRead(bb, &b));
  PetscCall(VecGetArray(xx, &x));
  t = a->solve_work;
  PetscCall(ISGetIndices(isrow, &rp));

  for (k = mbs - 1; k >= 0; k--) {
    v     = aa + ai[k];
    vj    = aj + ai[k];
    diagk = PetscRealPart(aa[adiag[k]]);
    PetscCheck(!PetscImaginaryPart(aa[adiag[k]]) && diagk >= 0, PETSC_COMM_SELF, PETSC_ERR_SUP, "Diagonal must be real and nonnegative");
    t[k] = b[k] * PetscSqrtReal(diagk);
    nz   = ai[k + 1] - ai[k] - 1;
    while (nz--) t[k] += (*v++) * t[*vj++];
    x[rp[k]] = t[k];
  }
  PetscCall(ISRestoreIndices(isrow, &rp));
  PetscCall(VecRestoreArrayRead(bb, &b));
  PetscCall(VecRestoreArray(xx, &x));
  PetscCall(PetscLogFlops(2.0 * a->nz - mbs));
  PetscFunctionReturn(0);
}

PetscErrorCode MatBackwardSolve_SeqSBAIJ_1_inplace(Mat A, Vec bb, Vec xx) {
  Mat_SeqSBAIJ      *a     = (Mat_SeqSBAIJ *)A->data;
  IS                 isrow = a->row;
  const PetscInt     mbs = a->mbs, *ai = a->i, *aj = a->j, *rp, *vj;
  const MatScalar   *aa = a->a, *v;
  PetscReal          diagk;
  PetscScalar       *x, *t;
  const PetscScalar *b;
  PetscInt           nz, k;

  PetscFunctionBegin;
  /* solve D^(1/2)*U*perm(x) = b by back substitution */
  PetscCall(VecGetArrayRead(bb, &b));
  PetscCall(VecGetArray(xx, &x));
  t = a->solve_work;
  PetscCall(ISGetIndices(isrow, &rp));

  for (k = mbs - 1; k >= 0; k--) {
    v     = aa + ai[k] + 1;
    vj    = aj + ai[k] + 1;
    diagk = PetscRealPart(aa[ai[k]]);
    PetscCheck(!PetscImaginaryPart(aa[ai[k]]) && diagk >= 0, PETSC_COMM_SELF, PETSC_ERR_SUP, "Diagonal must be real and nonnegative");
    t[k] = b[k] * PetscSqrtReal(diagk);
    nz   = ai[k + 1] - ai[k] - 1;
    while (nz--) t[k] += (*v++) * t[*vj++];
    x[rp[k]] = t[k];
  }
  PetscCall(ISRestoreIndices(isrow, &rp));
  PetscCall(VecRestoreArrayRead(bb, &b));
  PetscCall(VecRestoreArray(xx, &x));
  PetscCall(PetscLogFlops(2.0 * a->nz - mbs));
  PetscFunctionReturn(0);
}

PetscErrorCode MatSolves_SeqSBAIJ_1(Mat A, Vecs bb, Vecs xx) {
  Mat_SeqSBAIJ *a = (Mat_SeqSBAIJ *)A->data;

  PetscFunctionBegin;
  if (A->rmap->bs == 1) {
    PetscCall(MatSolve_SeqSBAIJ_1(A, bb->v, xx->v));
  } else {
    IS                 isrow = a->row;
    const PetscInt    *vj, mbs = a->mbs, *ai = a->i, *aj = a->j, *rp;
    const MatScalar   *aa = a->a, *v;
    PetscScalar       *x, *t;
    const PetscScalar *b;
    PetscInt           nz, k, n, i, j;

    if (bb->n > a->solves_work_n) {
      PetscCall(PetscFree(a->solves_work));
      PetscCall(PetscMalloc1(bb->n * A->rmap->N, &a->solves_work));
      a->solves_work_n = bb->n;
    }
    n = bb->n;
    PetscCall(VecGetArrayRead(bb->v, &b));
    PetscCall(VecGetArray(xx->v, &x));
    t = a->solves_work;

    PetscCall(ISGetIndices(isrow, &rp));

    /* solve U^T*D*y = perm(b) by forward substitution */
    for (k = 0; k < mbs; k++) {
      for (i = 0; i < n; i++) t[n * k + i] = b[rp[k] + i * mbs]; /* values are stored interlaced in t */
    }
    for (k = 0; k < mbs; k++) {
      v  = aa + ai[k];
      vj = aj + ai[k];
      nz = ai[k + 1] - ai[k] - 1;
      for (j = 0; j < nz; j++) {
        for (i = 0; i < n; i++) t[n * (*vj) + i] += (*v) * t[n * k + i];
        v++;
        vj++;
      }
      for (i = 0; i < n; i++) t[n * k + i] *= aa[nz]; /* note: aa[nz] = 1/D(k) */
    }

    /* solve U*perm(x) = y by back substitution */
    for (k = mbs - 1; k >= 0; k--) {
      v  = aa + ai[k] - 1;
      vj = aj + ai[k] - 1;
      nz = ai[k + 1] - ai[k] - 1;
      for (j = 0; j < nz; j++) {
        for (i = 0; i < n; i++) t[n * k + i] += (*v) * t[n * (*vj) + i];
        v++;
        vj++;
      }
      for (i = 0; i < n; i++) x[rp[k] + i * mbs] = t[n * k + i];
    }

    PetscCall(ISRestoreIndices(isrow, &rp));
    PetscCall(VecRestoreArrayRead(bb->v, &b));
    PetscCall(VecRestoreArray(xx->v, &x));
    PetscCall(PetscLogFlops(bb->n * (4.0 * a->nz - 3.0 * mbs)));
  }
  PetscFunctionReturn(0);
}

PetscErrorCode MatSolves_SeqSBAIJ_1_inplace(Mat A, Vecs bb, Vecs xx) {
  Mat_SeqSBAIJ *a = (Mat_SeqSBAIJ *)A->data;

  PetscFunctionBegin;
  if (A->rmap->bs == 1) {
    PetscCall(MatSolve_SeqSBAIJ_1_inplace(A, bb->v, xx->v));
  } else {
    IS                 isrow = a->row;
    const PetscInt    *vj, mbs = a->mbs, *ai = a->i, *aj = a->j, *rp;
    const MatScalar   *aa = a->a, *v;
    PetscScalar       *x, *t;
    const PetscScalar *b;
    PetscInt           nz, k, n, i;

    if (bb->n > a->solves_work_n) {
      PetscCall(PetscFree(a->solves_work));
      PetscCall(PetscMalloc1(bb->n * A->rmap->N, &a->solves_work));
      a->solves_work_n = bb->n;
    }
    n = bb->n;
    PetscCall(VecGetArrayRead(bb->v, &b));
    PetscCall(VecGetArray(xx->v, &x));
    t = a->solves_work;

    PetscCall(ISGetIndices(isrow, &rp));

    /* solve U^T*D*y = perm(b) by forward substitution */
    for (k = 0; k < mbs; k++) {
      for (i = 0; i < n; i++) t[n * k + i] = b[rp[k] + i * mbs]; /* values are stored interlaced in t */
    }
    for (k = 0; k < mbs; k++) {
      v  = aa + ai[k];
      vj = aj + ai[k];
      nz = ai[k + 1] - ai[k];
      while (nz--) {
        for (i = 0; i < n; i++) t[n * (*vj) + i] += (*v) * t[n * k + i];
        v++;
        vj++;
      }
      for (i = 0; i < n; i++) t[n * k + i] *= aa[k]; /* note: aa[k] = 1/D(k) */
    }

    /* solve U*perm(x) = y by back substitution */
    for (k = mbs - 1; k >= 0; k--) {
      v  = aa + ai[k];
      vj = aj + ai[k];
      nz = ai[k + 1] - ai[k];
      while (nz--) {
        for (i = 0; i < n; i++) t[n * k + i] += (*v) * t[n * (*vj) + i];
        v++;
        vj++;
      }
      for (i = 0; i < n; i++) x[rp[k] + i * mbs] = t[n * k + i];
    }

    PetscCall(ISRestoreIndices(isrow, &rp));
    PetscCall(VecRestoreArrayRead(bb->v, &b));
    PetscCall(VecRestoreArray(xx->v, &x));
    PetscCall(PetscLogFlops(bb->n * (4.0 * a->nz - 3.0 * mbs)));
  }
  PetscFunctionReturn(0);
}

PetscErrorCode MatSolve_SeqSBAIJ_1_NaturalOrdering(Mat A, Vec bb, Vec xx) {
  Mat_SeqSBAIJ      *a   = (Mat_SeqSBAIJ *)A->data;
  const PetscInt     mbs = a->mbs, *ai = a->i, *aj = a->j, *vj, *adiag = a->diag;
  const MatScalar   *aa = a->a, *v;
  const PetscScalar *b;
  PetscScalar       *x, xi;
  PetscInt           nz, i, j;

  PetscFunctionBegin;
  PetscCall(VecGetArrayRead(bb, &b));
  PetscCall(VecGetArray(xx, &x));
  /* solve U^T*D*y = b by forward substitution */
  PetscCall(PetscArraycpy(x, b, mbs));
  for (i = 0; i < mbs; i++) {
    v  = aa + ai[i];
    vj = aj + ai[i];
    xi = x[i];
    nz = ai[i + 1] - ai[i] - 1; /* exclude diag[i] */
    for (j = 0; j < nz; j++) x[vj[j]] += v[j] * xi;
    x[i] = xi * v[nz]; /* v[nz] = aa[diag[i]] = 1/D(i) */
  }
  /* solve U*x = y by backward substitution */
  for (i = mbs - 2; i >= 0; i--) {
    xi = x[i];
    v  = aa + adiag[i] - 1; /* end of row i, excluding diag */
    vj = aj + adiag[i] - 1;
    nz = ai[i + 1] - ai[i] - 1;
    for (j = 0; j < nz; j++) xi += v[-j] * x[vj[-j]];
    x[i] = xi;
  }
  PetscCall(VecRestoreArrayRead(bb, &b));
  PetscCall(VecRestoreArray(xx, &x));
  PetscCall(PetscLogFlops(4.0 * a->nz - 3 * mbs));
  PetscFunctionReturn(0);
}

PetscErrorCode MatMatSolve_SeqSBAIJ_1_NaturalOrdering(Mat A, Mat B, Mat X) {
  Mat_SeqSBAIJ      *a   = (Mat_SeqSBAIJ *)A->data;
  const PetscInt     mbs = a->mbs, *ai = a->i, *aj = a->j, *vj, *adiag = a->diag;
  const MatScalar   *aa = a->a, *v;
  const PetscScalar *b;
  PetscScalar       *x, xi;
  PetscInt           nz, i, j, neq, ldb, ldx;
  PetscBool          isdense;

  PetscFunctionBegin;
  if (!mbs) PetscFunctionReturn(0);
  PetscCall(PetscObjectTypeCompare((PetscObject)B, MATSEQDENSE, &isdense));
  PetscCheck(isdense, PETSC_COMM_SELF, PETSC_ERR_ARG_INCOMP, "B matrix must be a SeqDense matrix");
  if (X != B) {
    PetscCall(PetscObjectTypeCompare((PetscObject)X, MATSEQDENSE, &isdense));
    PetscCheck(isdense, PETSC_COMM_SELF, PETSC_ERR_ARG_INCOMP, "X matrix must be a SeqDense matrix");
  }
  PetscCall(MatDenseGetArrayRead(B, &b));
  PetscCall(MatDenseGetLDA(B, &ldb));
  PetscCall(MatDenseGetArray(X, &x));
  PetscCall(MatDenseGetLDA(X, &ldx));
  for (neq = 0; neq < B->cmap->n; neq++) {
    /* solve U^T*D*y = b by forward substitution */
    PetscCall(PetscArraycpy(x, b, mbs));
    for (i = 0; i < mbs; i++) {
      v  = aa + ai[i];
      vj = aj + ai[i];
      xi = x[i];
      nz = ai[i + 1] - ai[i] - 1; /* exclude diag[i] */
      for (j = 0; j < nz; j++) x[vj[j]] += v[j] * xi;
      x[i] = xi * v[nz]; /* v[nz] = aa[diag[i]] = 1/D(i) */
    }
    /* solve U*x = y by backward substitution */
    for (i = mbs - 2; i >= 0; i--) {
      xi = x[i];
      v  = aa + adiag[i] - 1; /* end of row i, excluding diag */
      vj = aj + adiag[i] - 1;
      nz = ai[i + 1] - ai[i] - 1;
      for (j = 0; j < nz; j++) xi += v[-j] * x[vj[-j]];
      x[i] = xi;
    }
    b += ldb;
    x += ldx;
  }
  PetscCall(MatDenseRestoreArrayRead(B, &b));
  PetscCall(MatDenseRestoreArray(X, &x));
  PetscCall(PetscLogFlops(B->cmap->n * (4.0 * a->nz - 3 * mbs)));
  PetscFunctionReturn(0);
}

PetscErrorCode MatSolve_SeqSBAIJ_1_NaturalOrdering_inplace(Mat A, Vec bb, Vec xx) {
  Mat_SeqSBAIJ      *a   = (Mat_SeqSBAIJ *)A->data;
  const PetscInt     mbs = a->mbs, *ai = a->i, *aj = a->j, *vj;
  const MatScalar   *aa = a->a, *v;
  PetscScalar       *x, xk;
  const PetscScalar *b;
  PetscInt           nz, k;

  PetscFunctionBegin;
  PetscCall(VecGetArrayRead(bb, &b));
  PetscCall(VecGetArray(xx, &x));

  /* solve U^T*D*y = b by forward substitution */
  PetscCall(PetscArraycpy(x, b, mbs));
  for (k = 0; k < mbs; k++) {
    v  = aa + ai[k] + 1;
    vj = aj + ai[k] + 1;
    xk = x[k];
    nz = ai[k + 1] - ai[k] - 1; /* exclude diag[k] */
    while (nz--) x[*vj++] += (*v++) * xk;
    x[k] = xk * aa[ai[k]]; /* note: aa[diag[k]] = 1/D(k) */
  }

  /* solve U*x = y by back substitution */
  for (k = mbs - 2; k >= 0; k--) {
    v  = aa + ai[k] + 1;
    vj = aj + ai[k] + 1;
    xk = x[k];
    nz = ai[k + 1] - ai[k] - 1;
    while (nz--) { xk += (*v++) * x[*vj++]; }
    x[k] = xk;
  }

  PetscCall(VecRestoreArrayRead(bb, &b));
  PetscCall(VecRestoreArray(xx, &x));
  PetscCall(PetscLogFlops(4.0 * a->nz - 3 * mbs));
  PetscFunctionReturn(0);
}

PetscErrorCode MatForwardSolve_SeqSBAIJ_1_NaturalOrdering(Mat A, Vec bb, Vec xx) {
  Mat_SeqSBAIJ      *a   = (Mat_SeqSBAIJ *)A->data;
  const PetscInt     mbs = a->mbs, *ai = a->i, *aj = a->j, *adiag = a->diag, *vj;
  const MatScalar   *aa = a->a, *v;
  PetscReal          diagk;
  PetscScalar       *x;
  const PetscScalar *b;
  PetscInt           nz, k;

  PetscFunctionBegin;
  /* solve U^T*D^(1/2)*x = b by forward substitution */
  PetscCall(VecGetArrayRead(bb, &b));
  PetscCall(VecGetArray(xx, &x));
  PetscCall(PetscArraycpy(x, b, mbs));
  for (k = 0; k < mbs; k++) {
    v  = aa + ai[k];
    vj = aj + ai[k];
    nz = ai[k + 1] - ai[k] - 1; /* exclude diag[k] */
    while (nz--) x[*vj++] += (*v++) * x[k];
    diagk = PetscRealPart(aa[adiag[k]]); /* note: aa[adiag[k]] = 1/D(k) */
    PetscCheck(!PetscImaginaryPart(aa[adiag[k]]) && diagk >= 0, PETSC_COMM_SELF, PETSC_ERR_SUP, "Diagonal (%g,%g) must be real and nonnegative", (double)PetscRealPart(aa[adiag[k]]), (double)PetscImaginaryPart(aa[adiag[k]]));
    x[k] *= PetscSqrtReal(diagk);
  }
  PetscCall(VecRestoreArrayRead(bb, &b));
  PetscCall(VecRestoreArray(xx, &x));
  PetscCall(PetscLogFlops(2.0 * a->nz - mbs));
  PetscFunctionReturn(0);
}

PetscErrorCode MatForwardSolve_SeqSBAIJ_1_NaturalOrdering_inplace(Mat A, Vec bb, Vec xx) {
  Mat_SeqSBAIJ      *a   = (Mat_SeqSBAIJ *)A->data;
  const PetscInt     mbs = a->mbs, *ai = a->i, *aj = a->j, *vj;
  const MatScalar   *aa = a->a, *v;
  PetscReal          diagk;
  PetscScalar       *x;
  const PetscScalar *b;
  PetscInt           nz, k;

  PetscFunctionBegin;
  /* solve U^T*D^(1/2)*x = b by forward substitution */
  PetscCall(VecGetArrayRead(bb, &b));
  PetscCall(VecGetArray(xx, &x));
  PetscCall(PetscArraycpy(x, b, mbs));
  for (k = 0; k < mbs; k++) {
    v  = aa + ai[k] + 1;
    vj = aj + ai[k] + 1;
    nz = ai[k + 1] - ai[k] - 1; /* exclude diag[k] */
    while (nz--) x[*vj++] += (*v++) * x[k];
    diagk = PetscRealPart(aa[ai[k]]); /* note: aa[diag[k]] = 1/D(k) */
    PetscCheck(!PetscImaginaryPart(aa[ai[k]]) && diagk >= 0, PETSC_COMM_SELF, PETSC_ERR_SUP, "Diagonal (%g,%g) must be real and nonnegative", (double)PetscRealPart(aa[ai[k]]), (double)PetscImaginaryPart(aa[ai[k]]));
    x[k] *= PetscSqrtReal(diagk);
  }
  PetscCall(VecRestoreArrayRead(bb, &b));
  PetscCall(VecRestoreArray(xx, &x));
  PetscCall(PetscLogFlops(2.0 * a->nz - mbs));
  PetscFunctionReturn(0);
}

PetscErrorCode MatBackwardSolve_SeqSBAIJ_1_NaturalOrdering(Mat A, Vec bb, Vec xx) {
  Mat_SeqSBAIJ      *a   = (Mat_SeqSBAIJ *)A->data;
  const PetscInt     mbs = a->mbs, *ai = a->i, *aj = a->j, *adiag = a->diag, *vj;
  const MatScalar   *aa = a->a, *v;
  PetscReal          diagk;
  PetscScalar       *x;
  const PetscScalar *b;
  PetscInt           nz, k;

  PetscFunctionBegin;
  /* solve D^(1/2)*U*x = b by back substitution */
  PetscCall(VecGetArrayRead(bb, &b));
  PetscCall(VecGetArray(xx, &x));

  for (k = mbs - 1; k >= 0; k--) {
    v     = aa + ai[k];
    vj    = aj + ai[k];
    diagk = PetscRealPart(aa[adiag[k]]); /* note: aa[diag[k]] = 1/D(k) */
    PetscCheck(!PetscImaginaryPart(aa[adiag[k]]) && diagk >= 0, PETSC_COMM_SELF, PETSC_ERR_SUP, "Diagonal must be real and nonnegative");
    x[k] = PetscSqrtReal(diagk) * b[k];
    nz   = ai[k + 1] - ai[k] - 1;
    while (nz--) x[k] += (*v++) * x[*vj++];
  }
  PetscCall(VecRestoreArrayRead(bb, &b));
  PetscCall(VecRestoreArray(xx, &x));
  PetscCall(PetscLogFlops(2.0 * a->nz - mbs));
  PetscFunctionReturn(0);
}

PetscErrorCode MatBackwardSolve_SeqSBAIJ_1_NaturalOrdering_inplace(Mat A, Vec bb, Vec xx) {
  Mat_SeqSBAIJ      *a   = (Mat_SeqSBAIJ *)A->data;
  const PetscInt     mbs = a->mbs, *ai = a->i, *aj = a->j, *vj;
  const MatScalar   *aa = a->a, *v;
  PetscReal          diagk;
  PetscScalar       *x;
  const PetscScalar *b;
  PetscInt           nz, k;

  PetscFunctionBegin;
  /* solve D^(1/2)*U*x = b by back substitution */
  PetscCall(VecGetArrayRead(bb, &b));
  PetscCall(VecGetArray(xx, &x));

  for (k = mbs - 1; k >= 0; k--) {
    v     = aa + ai[k] + 1;
    vj    = aj + ai[k] + 1;
    diagk = PetscRealPart(aa[ai[k]]); /* note: aa[diag[k]] = 1/D(k) */
    PetscCheck(!PetscImaginaryPart(aa[ai[k]]) && diagk >= 0, PETSC_COMM_SELF, PETSC_ERR_SUP, "Diagonal must be real and nonnegative");
    x[k] = PetscSqrtReal(diagk) * b[k];
    nz   = ai[k + 1] - ai[k] - 1;
    while (nz--) x[k] += (*v++) * x[*vj++];
  }
  PetscCall(VecRestoreArrayRead(bb, &b));
  PetscCall(VecRestoreArray(xx, &x));
  PetscCall(PetscLogFlops(2.0 * a->nz - mbs));
  PetscFunctionReturn(0);
}

/* Use Modified Sparse Row storage for u and ju, see Saad pp.85 */
PetscErrorCode MatICCFactorSymbolic_SeqSBAIJ_MSR(Mat B, Mat A, IS perm, const MatFactorInfo *info) {
  Mat_SeqSBAIJ   *a = (Mat_SeqSBAIJ *)A->data, *b;
  const PetscInt *rip, mbs    = a->mbs, *ai, *aj;
  PetscInt       *jutmp, bs   = A->rmap->bs, i;
  PetscInt        m, reallocs = 0, *levtmp;
  PetscInt       *prowl, *q, jmin, jmax, juidx, nzk, qm, *iu, *ju, k, j, vj, umax, maxadd;
  PetscInt        incrlev, *lev, shift, prow, nz;
  PetscReal       f = info->fill, levels = info->levels;
  PetscBool       perm_identity;

  PetscFunctionBegin;
  /* check whether perm is the identity mapping */
  PetscCall(ISIdentity(perm, &perm_identity));

  if (perm_identity) {
    a->permute = PETSC_FALSE;
    ai         = a->i;
    aj         = a->j;
  } else { /*  non-trivial permutation */
    SETERRQ(PETSC_COMM_SELF, PETSC_ERR_SUP, "Matrix reordering is not supported for sbaij matrix. Use aij format");
  }

  /* initialization */
  PetscCall(ISGetIndices(perm, &rip));
  umax = (PetscInt)(f * ai[mbs] + 1);
  PetscCall(PetscMalloc1(umax, &lev));
  umax += mbs + 1;
  shift = mbs + 1;
  PetscCall(PetscMalloc1(mbs + 1, &iu));
  PetscCall(PetscMalloc1(umax, &ju));
  iu[0] = mbs + 1;
  juidx = mbs + 1;
  /* prowl: linked list for pivot row */
  PetscCall(PetscMalloc3(mbs, &prowl, mbs, &q, mbs, &levtmp));
  /* q: linked list for col index */

  for (i = 0; i < mbs; i++) {
    prowl[i] = mbs;
    q[i]     = 0;
  }

  /* for each row k */
  for (k = 0; k < mbs; k++) {
    nzk  = 0;
    q[k] = mbs;
    /* copy current row into linked list */
    nz   = ai[rip[k] + 1] - ai[rip[k]];
    j    = ai[rip[k]];
    while (nz--) {
      vj = rip[aj[j++]];
      if (vj > k) {
        qm = k;
        do {
          m  = qm;
          qm = q[m];
        } while (qm < vj);
        PetscCheck(qm != vj, PETSC_COMM_SELF, PETSC_ERR_PLIB, "Duplicate entry in A");
        nzk++;
        q[m]       = vj;
        q[vj]      = qm;
        levtmp[vj] = 0; /* initialize lev for nonzero element */
      }
    }

    /* modify nonzero structure of k-th row by computing fill-in
       for each row prow to be merged in */
    prow = k;
    prow = prowl[prow]; /* next pivot row (== 0 for symbolic factorization) */

    while (prow < k) {
      /* merge row prow into k-th row */
      jmin = iu[prow] + 1;
      jmax = iu[prow + 1];
      qm   = k;
      for (j = jmin; j < jmax; j++) {
        incrlev = lev[j - shift] + 1;
        if (incrlev > levels) continue;
        vj = ju[j];
        do {
          m  = qm;
          qm = q[m];
        } while (qm < vj);
        if (qm != vj) { /* a fill */
          nzk++;
          q[m]       = vj;
          q[vj]      = qm;
          qm         = vj;
          levtmp[vj] = incrlev;
        } else if (levtmp[vj] > incrlev) levtmp[vj] = incrlev;
      }
      prow = prowl[prow]; /* next pivot row */
    }

    /* add k to row list for first nonzero element in k-th row */
    if (nzk > 1) {
      i        = q[k]; /* col value of first nonzero element in k_th row of U */
      prowl[k] = prowl[i];
      prowl[i] = k;
    }
    iu[k + 1] = iu[k] + nzk;

    /* allocate more space to ju and lev if needed */
    if (iu[k + 1] > umax) {
      /* estimate how much additional space we will need */
      /* use the strategy suggested by David Hysom <hysom@perch-t.icase.edu> */
      /* just double the memory each time */
      maxadd = umax;
      if (maxadd < nzk) maxadd = (mbs - k) * (nzk + 1) / 2;
      umax += maxadd;

      /* allocate a longer ju */
      PetscCall(PetscMalloc1(umax, &jutmp));
      PetscCall(PetscArraycpy(jutmp, ju, iu[k]));
      PetscCall(PetscFree(ju));
      ju = jutmp;

      PetscCall(PetscMalloc1(umax, &jutmp));
      PetscCall(PetscArraycpy(jutmp, lev, iu[k] - shift));
      PetscCall(PetscFree(lev));
      lev = jutmp;
      reallocs += 2; /* count how many times we realloc */
    }

    /* save nonzero structure of k-th row in ju */
    i = k;
    while (nzk--) {
      i                  = q[i];
      ju[juidx]          = i;
      lev[juidx - shift] = levtmp[i];
      juidx++;
    }
  }

#if defined(PETSC_USE_INFO)
  if (ai[mbs] != 0) {
    PetscReal af = ((PetscReal)iu[mbs]) / ((PetscReal)ai[mbs]);
    PetscCall(PetscInfo(A, "Reallocs %" PetscInt_FMT " Fill ratio:given %g needed %g\n", reallocs, (double)f, (double)af));
    PetscCall(PetscInfo(A, "Run with -pc_factor_fill %g or use \n", (double)af));
    PetscCall(PetscInfo(A, "PCFactorSetFill(pc,%g);\n", (double)af));
    PetscCall(PetscInfo(A, "for best performance.\n"));
  } else {
    PetscCall(PetscInfo(A, "Empty matrix\n"));
  }
#endif

  PetscCall(ISRestoreIndices(perm, &rip));
  PetscCall(PetscFree3(prowl, q, levtmp));
  PetscCall(PetscFree(lev));

  /* put together the new matrix */
  PetscCall(MatSeqSBAIJSetPreallocation(B, bs, 0, NULL));

  /* PetscCall(PetscLogObjectParent((PetscObject)B,(PetscObject)iperm)); */
  b = (Mat_SeqSBAIJ *)(B)->data;
  PetscCall(PetscFree2(b->imax, b->ilen));

  b->singlemalloc = PETSC_FALSE;
  b->free_a       = PETSC_TRUE;
  b->free_ij      = PETSC_TRUE;
  /* the next line frees the default space generated by the Create() */
  PetscCall(PetscFree3(b->a, b->j, b->i));
  PetscCall(PetscMalloc1((iu[mbs] + 1) * a->bs2, &b->a));
  b->j    = ju;
  b->i    = iu;
  b->diag = NULL;
  b->ilen = NULL;
  b->imax = NULL;

  PetscCall(ISDestroy(&b->row));
  PetscCall(ISDestroy(&b->icol));
  b->row  = perm;
  b->icol = perm;
  PetscCall(PetscObjectReference((PetscObject)perm));
  PetscCall(PetscObjectReference((PetscObject)perm));
  PetscCall(PetscMalloc1(bs * mbs + bs, &b->solve_work));
  /* In b structure:  Free imax, ilen, old a, old j.
     Allocate idnew, solve_work, new a, new j */
  PetscCall(PetscLogObjectMemory((PetscObject)B, (iu[mbs] - mbs) * (sizeof(PetscInt) + sizeof(MatScalar))));
  b->maxnz = b->nz = iu[mbs];

  (B)->info.factor_mallocs   = reallocs;
  (B)->info.fill_ratio_given = f;
  if (ai[mbs] != 0) {
    (B)->info.fill_ratio_needed = ((PetscReal)iu[mbs]) / ((PetscReal)ai[mbs]);
  } else {
    (B)->info.fill_ratio_needed = 0.0;
  }
  PetscCall(MatSeqSBAIJSetNumericFactorization_inplace(B, perm_identity));
  PetscFunctionReturn(0);
}

/*
  See MatICCFactorSymbolic_SeqAIJ() for description of its data structure
*/
#include <petscbt.h>
#include <../src/mat/utils/freespace.h>
PetscErrorCode MatICCFactorSymbolic_SeqSBAIJ(Mat fact, Mat A, IS perm, const MatFactorInfo *info) {
  Mat_SeqSBAIJ      *a = (Mat_SeqSBAIJ *)A->data, *b;
  PetscBool          perm_identity, free_ij = PETSC_TRUE, missing;
  PetscInt           bs = A->rmap->bs, am = a->mbs, d, *ai = a->i, *aj = a->j;
  const PetscInt    *rip;
  PetscInt           reallocs = 0, i, *ui, *udiag, *cols;
  PetscInt           jmin, jmax, nzk, k, j, *jl, prow, *il, nextprow;
  PetscInt           nlnk, *lnk, *lnk_lvl = NULL, ncols, *uj, **uj_ptr, **uj_lvl_ptr;
  PetscReal          fill = info->fill, levels = info->levels;
  PetscFreeSpaceList free_space = NULL, current_space = NULL;
  PetscFreeSpaceList free_space_lvl = NULL, current_space_lvl = NULL;
  PetscBT            lnkbt;

  PetscFunctionBegin;
  PetscCheck(A->rmap->n == A->cmap->n, PETSC_COMM_SELF, PETSC_ERR_ARG_WRONG, "Must be square matrix, rows %" PetscInt_FMT " columns %" PetscInt_FMT, A->rmap->n, A->cmap->n);
  PetscCall(MatMissingDiagonal(A, &missing, &d));
  PetscCheck(!missing, PETSC_COMM_SELF, PETSC_ERR_ARG_WRONGSTATE, "Matrix is missing diagonal entry %" PetscInt_FMT, d);
  if (bs > 1) {
    PetscCall(MatICCFactorSymbolic_SeqSBAIJ_inplace(fact, A, perm, info));
    PetscFunctionReturn(0);
  }

  /* check whether perm is the identity mapping */
  PetscCall(ISIdentity(perm, &perm_identity));
  PetscCheck(perm_identity, PETSC_COMM_SELF, PETSC_ERR_SUP, "Matrix reordering is not supported for sbaij matrix. Use aij format");
  a->permute = PETSC_FALSE;

  PetscCall(PetscMalloc1(am + 1, &ui));
  PetscCall(PetscMalloc1(am + 1, &udiag));
  ui[0] = 0;

  /* ICC(0) without matrix ordering: simply rearrange column indices */
  if (!levels) {
    /* reuse the column pointers and row offsets for memory savings */
    for (i = 0; i < am; i++) {
      ncols     = ai[i + 1] - ai[i];
      ui[i + 1] = ui[i] + ncols;
      udiag[i]  = ui[i + 1] - 1; /* points to the last entry of U(i,:) */
    }
    PetscCall(PetscMalloc1(ui[am] + 1, &uj));
    cols = uj;
    for (i = 0; i < am; i++) {
      aj    = a->j + ai[i] + 1; /* 1st entry of U(i,:) without diagonal */
      ncols = ai[i + 1] - ai[i] - 1;
      for (j = 0; j < ncols; j++) *cols++ = aj[j];
      *cols++ = i; /* diagonal is located as the last entry of U(i,:) */
    }
  } else { /* case: levels>0 */
    PetscCall(ISGetIndices(perm, &rip));

    /* initialization */
    /* jl: linked list for storing indices of the pivot rows
       il: il[i] points to the 1st nonzero entry of U(i,k:am-1) */
    PetscCall(PetscMalloc4(am, &uj_ptr, am, &uj_lvl_ptr, am, &il, am, &jl));
    for (i = 0; i < am; i++) {
      jl[i] = am;
      il[i] = 0;
    }

    /* create and initialize a linked list for storing column indices of the active row k */
    nlnk = am + 1;
    PetscCall(PetscIncompleteLLCreate(am, am, nlnk, lnk, lnk_lvl, lnkbt));

    /* initial FreeSpace size is fill*(ai[am]+1) */
    PetscCall(PetscFreeSpaceGet(PetscRealIntMultTruncate(fill, ai[am] + 1), &free_space));

    current_space = free_space;

    PetscCall(PetscFreeSpaceGet(PetscRealIntMultTruncate(fill, ai[am] + 1), &free_space_lvl));

    current_space_lvl = free_space_lvl;

    for (k = 0; k < am; k++) { /* for each active row k */
      /* initialize lnk by the column indices of row k */
      nzk   = 0;
      ncols = ai[k + 1] - ai[k];
      PetscCheck(ncols, PETSC_COMM_SELF, PETSC_ERR_MAT_CH_ZRPVT, "Empty row %" PetscInt_FMT " in matrix ", k);
      cols = aj + ai[k];
      PetscCall(PetscIncompleteLLInit(ncols, cols, am, rip, &nlnk, lnk, lnk_lvl, lnkbt));
      nzk += nlnk;

      /* update lnk by computing fill-in for each pivot row to be merged in */
      prow = jl[k]; /* 1st pivot row */

      while (prow < k) {
        nextprow = jl[prow];

        /* merge prow into k-th row */
        jmin  = il[prow] + 1; /* index of the 2nd nzero entry in U(prow,k:am-1) */
        jmax  = ui[prow + 1];
        ncols = jmax - jmin;
        i     = jmin - ui[prow];

        cols = uj_ptr[prow] + i;     /* points to the 2nd nzero entry in U(prow,k:am-1) */
        uj   = uj_lvl_ptr[prow] + i; /* levels of cols */
        j    = *(uj - 1);
        PetscCall(PetscICCLLAddSorted(ncols, cols, levels, uj, am, &nlnk, lnk, lnk_lvl, lnkbt, j));
        nzk += nlnk;

        /* update il and jl for prow */
        if (jmin < jmax) {
          il[prow] = jmin;

          j        = *cols;
          jl[prow] = jl[j];
          jl[j]    = prow;
        }
        prow = nextprow;
      }

      /* if free space is not available, make more free space */
      if (current_space->local_remaining < nzk) {
        i = am - k + 1;                                    /* num of unfactored rows */
        i = PetscIntMultTruncate(i, PetscMin(nzk, i - 1)); /* i*nzk, i*(i-1): estimated and max additional space needed */
        PetscCall(PetscFreeSpaceGet(i, &current_space));
        PetscCall(PetscFreeSpaceGet(i, &current_space_lvl));
        reallocs++;
      }

      /* copy data into free_space and free_space_lvl, then initialize lnk */
      PetscCheck(nzk != 0, PETSC_COMM_SELF, PETSC_ERR_ARG_WRONG, "Empty row %" PetscInt_FMT " in ICC matrix factor", k);
      PetscCall(PetscIncompleteLLClean(am, am, nzk, lnk, lnk_lvl, current_space->array, current_space_lvl->array, lnkbt));

      /* add the k-th row into il and jl */
      if (nzk > 1) {
        i     = current_space->array[1]; /* col value of the first nonzero element in U(k, k+1:am-1) */
        jl[k] = jl[i];
        jl[i] = k;
        il[k] = ui[k] + 1;
      }
      uj_ptr[k]     = current_space->array;
      uj_lvl_ptr[k] = current_space_lvl->array;

      current_space->array += nzk;
      current_space->local_used += nzk;
      current_space->local_remaining -= nzk;
      current_space_lvl->array += nzk;
      current_space_lvl->local_used += nzk;
      current_space_lvl->local_remaining -= nzk;

      ui[k + 1] = ui[k] + nzk;
    }

    PetscCall(ISRestoreIndices(perm, &rip));
    PetscCall(PetscFree4(uj_ptr, uj_lvl_ptr, il, jl));

    /* destroy list of free space and other temporary array(s) */
    PetscCall(PetscMalloc1(ui[am] + 1, &uj));
    PetscCall(PetscFreeSpaceContiguous_Cholesky(&free_space, uj, am, ui, udiag)); /* store matrix factor  */
    PetscCall(PetscIncompleteLLDestroy(lnk, lnkbt));
    PetscCall(PetscFreeSpaceDestroy(free_space_lvl));

  } /* end of case: levels>0 || (levels=0 && !perm_identity) */

  /* put together the new matrix in MATSEQSBAIJ format */
  PetscCall(MatSeqSBAIJSetPreallocation(fact, bs, MAT_SKIP_ALLOCATION, NULL));

  b = (Mat_SeqSBAIJ *)(fact)->data;
  PetscCall(PetscFree2(b->imax, b->ilen));

  b->singlemalloc = PETSC_FALSE;
  b->free_a       = PETSC_TRUE;
  b->free_ij      = free_ij;

  PetscCall(PetscMalloc1(ui[am] + 1, &b->a));

  b->j         = uj;
  b->i         = ui;
  b->diag      = udiag;
  b->free_diag = PETSC_TRUE;
  b->ilen      = NULL;
  b->imax      = NULL;
  b->row       = perm;
  b->col       = perm;

  PetscCall(PetscObjectReference((PetscObject)perm));
  PetscCall(PetscObjectReference((PetscObject)perm));

  b->pivotinblocks = PETSC_FALSE; /* need to get from MatFactorInfo */

  PetscCall(PetscMalloc1(am + 1, &b->solve_work));
  PetscCall(PetscLogObjectMemory((PetscObject)fact, ui[am] * (sizeof(PetscInt) + sizeof(MatScalar))));

  b->maxnz = b->nz = ui[am];

  fact->info.factor_mallocs   = reallocs;
  fact->info.fill_ratio_given = fill;
  if (ai[am] != 0) {
    fact->info.fill_ratio_needed = ((PetscReal)ui[am]) / ai[am];
  } else {
    fact->info.fill_ratio_needed = 0.0;
  }
#if defined(PETSC_USE_INFO)
  if (ai[am] != 0) {
    PetscReal af = fact->info.fill_ratio_needed;
    PetscCall(PetscInfo(A, "Reallocs %" PetscInt_FMT " Fill ratio:given %g needed %g\n", reallocs, (double)fill, (double)af));
    PetscCall(PetscInfo(A, "Run with -pc_factor_fill %g or use \n", (double)af));
    PetscCall(PetscInfo(A, "PCFactorSetFill(pc,%g) for best performance.\n", (double)af));
  } else {
    PetscCall(PetscInfo(A, "Empty matrix\n"));
  }
#endif
  fact->ops->choleskyfactornumeric = MatCholeskyFactorNumeric_SeqSBAIJ_1_NaturalOrdering;
  PetscFunctionReturn(0);
}

PetscErrorCode MatICCFactorSymbolic_SeqSBAIJ_inplace(Mat fact, Mat A, IS perm, const MatFactorInfo *info) {
  Mat_SeqSBAIJ      *a = (Mat_SeqSBAIJ *)A->data;
  Mat_SeqSBAIJ      *b;
  PetscBool          perm_identity, free_ij = PETSC_TRUE;
  PetscInt           bs = A->rmap->bs, am = a->mbs;
  const PetscInt    *cols, *rip, *ai = a->i, *aj = a->j;
  PetscInt           reallocs = 0, i, *ui;
  PetscInt           jmin, jmax, nzk, k, j, *jl, prow, *il, nextprow;
  PetscInt           nlnk, *lnk, *lnk_lvl = NULL, ncols, *cols_lvl, *uj, **uj_ptr, **uj_lvl_ptr;
  PetscReal          fill = info->fill, levels = info->levels, ratio_needed;
  PetscFreeSpaceList free_space = NULL, current_space = NULL;
  PetscFreeSpaceList free_space_lvl = NULL, current_space_lvl = NULL;
  PetscBT            lnkbt;

  PetscFunctionBegin;
  /*
   This code originally uses Modified Sparse Row (MSR) storage
   (see page 85, "Iterative Methods ..." by Saad) for the output matrix B - bad choice!
   Then it is rewritten so the factor B takes seqsbaij format. However the associated
   MatCholeskyFactorNumeric_() have not been modified for the cases of bs>1,
   thus the original code in MSR format is still used for these cases.
   The code below should replace MatICCFactorSymbolic_SeqSBAIJ_MSR() whenever
   MatCholeskyFactorNumeric_() is modified for using sbaij symbolic factor.
  */
  if (bs > 1) {
    PetscCall(MatICCFactorSymbolic_SeqSBAIJ_MSR(fact, A, perm, info));
    PetscFunctionReturn(0);
  }

  /* check whether perm is the identity mapping */
  PetscCall(ISIdentity(perm, &perm_identity));
  PetscCheck(perm_identity, PETSC_COMM_SELF, PETSC_ERR_SUP, "Matrix reordering is not supported for sbaij matrix. Use aij format");
  a->permute = PETSC_FALSE;

  /* special case that simply copies fill pattern */
  if (!levels) {
    /* reuse the column pointers and row offsets for memory savings */
    ui           = a->i;
    uj           = a->j;
    free_ij      = PETSC_FALSE;
    ratio_needed = 1.0;
  } else { /* case: levels>0 */
    PetscCall(ISGetIndices(perm, &rip));

    /* initialization */
    PetscCall(PetscMalloc1(am + 1, &ui));
    ui[0] = 0;

    /* jl: linked list for storing indices of the pivot rows
       il: il[i] points to the 1st nonzero entry of U(i,k:am-1) */
    PetscCall(PetscMalloc4(am, &uj_ptr, am, &uj_lvl_ptr, am, &il, am, &jl));
    for (i = 0; i < am; i++) {
      jl[i] = am;
      il[i] = 0;
    }

    /* create and initialize a linked list for storing column indices of the active row k */
    nlnk = am + 1;
    PetscCall(PetscIncompleteLLCreate(am, am, nlnk, lnk, lnk_lvl, lnkbt));

    /* initial FreeSpace size is fill*(ai[am]+1) */
    PetscCall(PetscFreeSpaceGet(PetscRealIntMultTruncate(fill, ai[am] + 1), &free_space));

    current_space = free_space;

    PetscCall(PetscFreeSpaceGet(PetscRealIntMultTruncate(fill, ai[am] + 1), &free_space_lvl));

    current_space_lvl = free_space_lvl;

    for (k = 0; k < am; k++) { /* for each active row k */
      /* initialize lnk by the column indices of row rip[k] */
      nzk   = 0;
      ncols = ai[rip[k] + 1] - ai[rip[k]];
      cols  = aj + ai[rip[k]];
      PetscCall(PetscIncompleteLLInit(ncols, cols, am, rip, &nlnk, lnk, lnk_lvl, lnkbt));
      nzk += nlnk;

      /* update lnk by computing fill-in for each pivot row to be merged in */
      prow = jl[k]; /* 1st pivot row */

      while (prow < k) {
        nextprow = jl[prow];

        /* merge prow into k-th row */
        jmin     = il[prow] + 1; /* index of the 2nd nzero entry in U(prow,k:am-1) */
        jmax     = ui[prow + 1];
        ncols    = jmax - jmin;
        i        = jmin - ui[prow];
        cols     = uj_ptr[prow] + i; /* points to the 2nd nzero entry in U(prow,k:am-1) */
        j        = *(uj_lvl_ptr[prow] + i - 1);
        cols_lvl = uj_lvl_ptr[prow] + i;
        PetscCall(PetscICCLLAddSorted(ncols, cols, levels, cols_lvl, am, &nlnk, lnk, lnk_lvl, lnkbt, j));
        nzk += nlnk;

        /* update il and jl for prow */
        if (jmin < jmax) {
          il[prow] = jmin;
          j        = *cols;
          jl[prow] = jl[j];
          jl[j]    = prow;
        }
        prow = nextprow;
      }

      /* if free space is not available, make more free space */
      if (current_space->local_remaining < nzk) {
        i = am - k + 1;                                                             /* num of unfactored rows */
        i = PetscMin(PetscIntMultTruncate(i, nzk), PetscIntMultTruncate(i, i - 1)); /* i*nzk, i*(i-1): estimated and max additional space needed */
        PetscCall(PetscFreeSpaceGet(i, &current_space));
        PetscCall(PetscFreeSpaceGet(i, &current_space_lvl));
        reallocs++;
      }

      /* copy data into free_space and free_space_lvl, then initialize lnk */
      PetscCall(PetscIncompleteLLClean(am, am, nzk, lnk, lnk_lvl, current_space->array, current_space_lvl->array, lnkbt));

      /* add the k-th row into il and jl */
      if (nzk - 1 > 0) {
        i     = current_space->array[1]; /* col value of the first nonzero element in U(k, k+1:am-1) */
        jl[k] = jl[i];
        jl[i] = k;
        il[k] = ui[k] + 1;
      }
      uj_ptr[k]     = current_space->array;
      uj_lvl_ptr[k] = current_space_lvl->array;

      current_space->array += nzk;
      current_space->local_used += nzk;
      current_space->local_remaining -= nzk;
      current_space_lvl->array += nzk;
      current_space_lvl->local_used += nzk;
      current_space_lvl->local_remaining -= nzk;

      ui[k + 1] = ui[k] + nzk;
    }

    PetscCall(ISRestoreIndices(perm, &rip));
    PetscCall(PetscFree4(uj_ptr, uj_lvl_ptr, il, jl));

    /* destroy list of free space and other temporary array(s) */
    PetscCall(PetscMalloc1(ui[am] + 1, &uj));
    PetscCall(PetscFreeSpaceContiguous(&free_space, uj));
    PetscCall(PetscIncompleteLLDestroy(lnk, lnkbt));
    PetscCall(PetscFreeSpaceDestroy(free_space_lvl));
    if (ai[am] != 0) {
      ratio_needed = ((PetscReal)ui[am]) / ((PetscReal)ai[am]);
    } else {
      ratio_needed = 0.0;
    }
  } /* end of case: levels>0 || (levels=0 && !perm_identity) */

  /* put together the new matrix in MATSEQSBAIJ format */
  PetscCall(MatSeqSBAIJSetPreallocation(fact, bs, MAT_SKIP_ALLOCATION, NULL));

  b = (Mat_SeqSBAIJ *)(fact)->data;

  PetscCall(PetscFree2(b->imax, b->ilen));

  b->singlemalloc = PETSC_FALSE;
  b->free_a       = PETSC_TRUE;
  b->free_ij      = free_ij;

  PetscCall(PetscMalloc1(ui[am] + 1, &b->a));

  b->j             = uj;
  b->i             = ui;
  b->diag          = NULL;
  b->ilen          = NULL;
  b->imax          = NULL;
  b->row           = perm;
  b->pivotinblocks = PETSC_FALSE; /* need to get from MatFactorInfo */

  PetscCall(PetscObjectReference((PetscObject)perm));
  b->icol = perm;
  PetscCall(PetscObjectReference((PetscObject)perm));
  PetscCall(PetscMalloc1(am + 1, &b->solve_work));

  b->maxnz = b->nz = ui[am];

  fact->info.factor_mallocs    = reallocs;
  fact->info.fill_ratio_given  = fill;
  fact->info.fill_ratio_needed = ratio_needed;
#if defined(PETSC_USE_INFO)
  if (ai[am] != 0) {
    PetscReal af = fact->info.fill_ratio_needed;
    PetscCall(PetscInfo(A, "Reallocs %" PetscInt_FMT " Fill ratio:given %g needed %g\n", reallocs, (double)fill, (double)af));
    PetscCall(PetscInfo(A, "Run with -pc_factor_fill %g or use \n", (double)af));
    PetscCall(PetscInfo(A, "PCFactorSetFill(pc,%g) for best performance.\n", (double)af));
  } else {
    PetscCall(PetscInfo(A, "Empty matrix\n"));
  }
#endif
  if (perm_identity) {
    fact->ops->choleskyfactornumeric = MatCholeskyFactorNumeric_SeqSBAIJ_1_NaturalOrdering_inplace;
  } else {
    fact->ops->choleskyfactornumeric = MatCholeskyFactorNumeric_SeqSBAIJ_1_inplace;
  }
  PetscFunctionReturn(0);
}