1: /*
  2:     Factorization code for BAIJ format.
  3: */
  4: #include <../src/mat/impls/baij/seq/baij.h>
  5: #include <petsc/private/kernels/blockinvert.h>

  7: PetscErrorCode MatLUFactorNumeric_SeqBAIJ_N_inplace(Mat C, Mat A, const MatFactorInfo *info)
  8: {
  9:   Mat_SeqBAIJ    *a = (Mat_SeqBAIJ *)A->data, *b = (Mat_SeqBAIJ *)C->data;
 10:   IS              isrow = b->row, isicol = b->icol;
 11:   const PetscInt *r, *ic;
 12:   PetscInt        i, j, n = a->mbs, *bi = b->i, *bj = b->j;
 13:   PetscInt       *ajtmpold, *ajtmp, nz, row, *ai = a->i, *aj = a->j, k, flg;
 14:   PetscInt       *diag_offset = b->diag, diag, bs = A->rmap->bs, bs2 = a->bs2, *pj, *v_pivots;
 15:   MatScalar      *ba = b->a, *aa = a->a, *pv, *v, *rtmp, *multiplier, *v_work, *pc, *w;
 16:   PetscBool       allowzeropivot, zeropivotdetected;

 18:   PetscFunctionBegin;
 19:   PetscCall(ISGetIndices(isrow, &r));
 20:   PetscCall(ISGetIndices(isicol, &ic));
 21:   allowzeropivot = PetscNot(A->erroriffailure);

 23:   PetscCall(PetscCalloc1(bs2 * (n + 1), &rtmp));
 24:   /* generate work space needed by dense LU factorization */
 25:   PetscCall(PetscMalloc3(bs, &v_work, bs2, &multiplier, bs, &v_pivots));

 27:   for (i = 0; i < n; i++) {
 28:     nz    = bi[i + 1] - bi[i];
 29:     ajtmp = bj + bi[i];
 30:     for (j = 0; j < nz; j++) PetscCall(PetscArrayzero(rtmp + bs2 * ajtmp[j], bs2));
 31:     /* load in initial (unfactored row) */
 32:     nz       = ai[r[i] + 1] - ai[r[i]];
 33:     ajtmpold = aj + ai[r[i]];
 34:     v        = aa + bs2 * ai[r[i]];
 35:     for (j = 0; j < nz; j++) PetscCall(PetscArraycpy(rtmp + bs2 * ic[ajtmpold[j]], v + bs2 * j, bs2));
 36:     row = *ajtmp++;
 37:     while (row < i) {
 38:       pc = rtmp + bs2 * row;
 39:       /*      if (*pc) { */
 40:       for (flg = 0, k = 0; k < bs2; k++) {
 41:         if (pc[k] != 0.0) {
 42:           flg = 1;
 43:           break;
 44:         }
 45:       }
 46:       if (flg) {
 47:         pv = ba + bs2 * diag_offset[row];
 48:         pj = bj + diag_offset[row] + 1;
 49:         PetscKernel_A_gets_A_times_B(bs, pc, pv, multiplier);
 50:         nz = bi[row + 1] - diag_offset[row] - 1;
 51:         pv += bs2;
 52:         for (j = 0; j < nz; j++) PetscKernel_A_gets_A_minus_B_times_C(bs, rtmp + bs2 * pj[j], pc, pv + bs2 * j);
 53:         PetscCall(PetscLogFlops(2.0 * bs * bs2 * (nz + 1.0) - bs));
 54:       }
 55:       row = *ajtmp++;
 56:     }
 57:     /* finished row so stick it into b->a */
 58:     pv = ba + bs2 * bi[i];
 59:     pj = bj + bi[i];
 60:     nz = bi[i + 1] - bi[i];
 61:     for (j = 0; j < nz; j++) PetscCall(PetscArraycpy(pv + bs2 * j, rtmp + bs2 * pj[j], bs2));
 62:     diag = diag_offset[i] - bi[i];
 63:     /* invert diagonal block */
 64:     w = pv + bs2 * diag;

 66:     PetscCall(PetscKernel_A_gets_inverse_A(bs, w, v_pivots, v_work, allowzeropivot, &zeropivotdetected));
 67:     if (zeropivotdetected) C->factorerrortype = MAT_FACTOR_NUMERIC_ZEROPIVOT;
 68:   }

 70:   PetscCall(PetscFree(rtmp));
 71:   PetscCall(PetscFree3(v_work, multiplier, v_pivots));
 72:   PetscCall(ISRestoreIndices(isicol, &ic));
 73:   PetscCall(ISRestoreIndices(isrow, &r));

 75:   C->ops->solve          = MatSolve_SeqBAIJ_N_inplace;
 76:   C->ops->solvetranspose = MatSolveTranspose_SeqBAIJ_N_inplace;
 77:   C->assembled           = PETSC_TRUE;

 79:   PetscCall(PetscLogFlops(1.333333333333 * bs * bs2 * b->mbs)); /* from inverting diagonal blocks */
 80:   PetscFunctionReturn(PETSC_SUCCESS);
 81: }