/* Defines the basic matrix operations for the BAIJ (compressed row) matrix storage format. */ #include <../src/mat/impls/baij/seq/baij.h> /*I "petscmat.h" I*/ #include #include #include /* defines MatSetValues_Seq_Hash(), MatAssemblyEnd_Seq_Hash(), MatSetUp_Seq_Hash() */ #define TYPE BAIJ #define TYPE_BS #include "../src/mat/impls/aij/seq/seqhashmatsetvalues.h" #undef TYPE_BS #define TYPE_BS _BS #define TYPE_BS_ON #include "../src/mat/impls/aij/seq/seqhashmatsetvalues.h" #undef TYPE_BS #include "../src/mat/impls/aij/seq/seqhashmat.h" #undef TYPE #undef TYPE_BS_ON #if defined(PETSC_HAVE_HYPRE) PETSC_INTERN PetscErrorCode MatConvert_AIJ_HYPRE(Mat, MatType, MatReuse, Mat *); #endif #if defined(PETSC_HAVE_MKL_SPARSE_OPTIMIZE) PETSC_INTERN PetscErrorCode MatConvert_SeqBAIJ_SeqBAIJMKL(Mat, MatType, MatReuse, Mat *); #endif PETSC_INTERN PetscErrorCode MatConvert_XAIJ_IS(Mat, MatType, MatReuse, Mat *); MatGetDiagonalMarkers(SeqBAIJ, A->rmap->bs) static PetscErrorCode MatGetColumnReductions_SeqBAIJ(Mat A, PetscInt type, PetscReal *reductions) { Mat_SeqBAIJ *a_aij = (Mat_SeqBAIJ *)A->data; PetscInt m, n, ib, jb, bs = A->rmap->bs; MatScalar *a_val = a_aij->a; PetscFunctionBegin; PetscCall(MatGetSize(A, &m, &n)); PetscCall(PetscArrayzero(reductions, n)); if (type == NORM_2) { for (PetscInt i = a_aij->i[0]; i < a_aij->i[A->rmap->n / bs]; i++) { for (jb = 0; jb < bs; jb++) { for (ib = 0; ib < bs; ib++) { reductions[A->cmap->rstart + a_aij->j[i] * bs + jb] += PetscAbsScalar(*a_val * *a_val); a_val++; } } } } else if (type == NORM_1) { for (PetscInt i = a_aij->i[0]; i < a_aij->i[A->rmap->n / bs]; i++) { for (jb = 0; jb < bs; jb++) { for (ib = 0; ib < bs; ib++) { reductions[A->cmap->rstart + a_aij->j[i] * bs + jb] += PetscAbsScalar(*a_val); a_val++; } } } } else if (type == NORM_INFINITY) { for (PetscInt i = a_aij->i[0]; i < a_aij->i[A->rmap->n / bs]; i++) { for (jb = 0; jb < bs; jb++) { for (ib = 0; ib < bs; ib++) { PetscInt col = A->cmap->rstart + a_aij->j[i] * bs + jb; reductions[col] = PetscMax(PetscAbsScalar(*a_val), reductions[col]); a_val++; } } } } else if (type == REDUCTION_SUM_REALPART || type == REDUCTION_MEAN_REALPART) { for (PetscInt i = a_aij->i[0]; i < a_aij->i[A->rmap->n / bs]; i++) { for (jb = 0; jb < bs; jb++) { for (ib = 0; ib < bs; ib++) { reductions[A->cmap->rstart + a_aij->j[i] * bs + jb] += PetscRealPart(*a_val); a_val++; } } } } else if (type == REDUCTION_SUM_IMAGINARYPART || type == REDUCTION_MEAN_IMAGINARYPART) { for (PetscInt i = a_aij->i[0]; i < a_aij->i[A->rmap->n / bs]; i++) { for (jb = 0; jb < bs; jb++) { for (ib = 0; ib < bs; ib++) { reductions[A->cmap->rstart + a_aij->j[i] * bs + jb] += PetscImaginaryPart(*a_val); a_val++; } } } } else SETERRQ(PetscObjectComm((PetscObject)A), PETSC_ERR_ARG_WRONG, "Unknown reduction type"); if (type == NORM_2) { for (PetscInt i = 0; i < n; i++) reductions[i] = PetscSqrtReal(reductions[i]); } else if (type == REDUCTION_MEAN_REALPART || type == REDUCTION_MEAN_IMAGINARYPART) { for (PetscInt i = 0; i < n; i++) reductions[i] /= m; } PetscFunctionReturn(PETSC_SUCCESS); } static PetscErrorCode MatInvertBlockDiagonal_SeqBAIJ(Mat A, const PetscScalar **values) { Mat_SeqBAIJ *a = (Mat_SeqBAIJ *)A->data; PetscInt i, bs = A->rmap->bs, mbs = a->mbs, ipvt[5], bs2 = bs * bs, *v_pivots; MatScalar *v = a->a, *odiag, *diag, work[25], *v_work; PetscReal shift = 0.0; PetscBool allowzeropivot, zeropivotdetected = PETSC_FALSE; const PetscInt *adiag; PetscFunctionBegin; allowzeropivot = PetscNot(A->erroriffailure); if (a->idiagvalid) { if (values) *values = a->idiag; PetscFunctionReturn(PETSC_SUCCESS); } PetscCall(MatGetDiagonalMarkers_SeqBAIJ(A, &adiag, NULL)); if (!a->idiag) PetscCall(PetscMalloc1(bs2 * mbs, &a->idiag)); diag = a->idiag; if (values) *values = a->idiag; /* factor and invert each block */ switch (bs) { case 1: for (i = 0; i < mbs; i++) { odiag = v + 1 * adiag[i]; diag[0] = odiag[0]; if (PetscAbsScalar(diag[0] + shift) < PETSC_MACHINE_EPSILON) { PetscCheck(allowzeropivot, PETSC_COMM_SELF, PETSC_ERR_MAT_LU_ZRPVT, "Zero pivot, row %" PetscInt_FMT " pivot value %g tolerance %g", i, (double)PetscAbsScalar(diag[0]), (double)PETSC_MACHINE_EPSILON); A->factorerrortype = MAT_FACTOR_NUMERIC_ZEROPIVOT; A->factorerror_zeropivot_value = PetscAbsScalar(diag[0]); A->factorerror_zeropivot_row = i; PetscCall(PetscInfo(A, "Zero pivot, row %" PetscInt_FMT "\n", i)); } diag[0] = (PetscScalar)1.0 / (diag[0] + shift); diag += 1; } break; case 2: for (i = 0; i < mbs; i++) { odiag = v + 4 * adiag[i]; diag[0] = odiag[0]; diag[1] = odiag[1]; diag[2] = odiag[2]; diag[3] = odiag[3]; PetscCall(PetscKernel_A_gets_inverse_A_2(diag, shift, allowzeropivot, &zeropivotdetected)); if (zeropivotdetected) A->factorerrortype = MAT_FACTOR_NUMERIC_ZEROPIVOT; diag += 4; } break; case 3: for (i = 0; i < mbs; i++) { odiag = v + 9 * adiag[i]; diag[0] = odiag[0]; diag[1] = odiag[1]; diag[2] = odiag[2]; diag[3] = odiag[3]; diag[4] = odiag[4]; diag[5] = odiag[5]; diag[6] = odiag[6]; diag[7] = odiag[7]; diag[8] = odiag[8]; PetscCall(PetscKernel_A_gets_inverse_A_3(diag, shift, allowzeropivot, &zeropivotdetected)); if (zeropivotdetected) A->factorerrortype = MAT_FACTOR_NUMERIC_ZEROPIVOT; diag += 9; } break; case 4: for (i = 0; i < mbs; i++) { odiag = v + 16 * adiag[i]; PetscCall(PetscArraycpy(diag, odiag, 16)); PetscCall(PetscKernel_A_gets_inverse_A_4(diag, shift, allowzeropivot, &zeropivotdetected)); if (zeropivotdetected) A->factorerrortype = MAT_FACTOR_NUMERIC_ZEROPIVOT; diag += 16; } break; case 5: for (i = 0; i < mbs; i++) { odiag = v + 25 * adiag[i]; PetscCall(PetscArraycpy(diag, odiag, 25)); PetscCall(PetscKernel_A_gets_inverse_A_5(diag, ipvt, work, shift, allowzeropivot, &zeropivotdetected)); if (zeropivotdetected) A->factorerrortype = MAT_FACTOR_NUMERIC_ZEROPIVOT; diag += 25; } break; case 6: for (i = 0; i < mbs; i++) { odiag = v + 36 * adiag[i]; PetscCall(PetscArraycpy(diag, odiag, 36)); PetscCall(PetscKernel_A_gets_inverse_A_6(diag, shift, allowzeropivot, &zeropivotdetected)); if (zeropivotdetected) A->factorerrortype = MAT_FACTOR_NUMERIC_ZEROPIVOT; diag += 36; } break; case 7: for (i = 0; i < mbs; i++) { odiag = v + 49 * adiag[i]; PetscCall(PetscArraycpy(diag, odiag, 49)); PetscCall(PetscKernel_A_gets_inverse_A_7(diag, shift, allowzeropivot, &zeropivotdetected)); if (zeropivotdetected) A->factorerrortype = MAT_FACTOR_NUMERIC_ZEROPIVOT; diag += 49; } break; default: PetscCall(PetscMalloc2(bs, &v_work, bs, &v_pivots)); for (i = 0; i < mbs; i++) { odiag = v + bs2 * adiag[i]; PetscCall(PetscArraycpy(diag, odiag, bs2)); PetscCall(PetscKernel_A_gets_inverse_A(bs, diag, v_pivots, v_work, allowzeropivot, &zeropivotdetected)); if (zeropivotdetected) A->factorerrortype = MAT_FACTOR_NUMERIC_ZEROPIVOT; diag += bs2; } PetscCall(PetscFree2(v_work, v_pivots)); } a->idiagvalid = PETSC_TRUE; PetscFunctionReturn(PETSC_SUCCESS); } static PetscErrorCode MatSOR_SeqBAIJ(Mat A, Vec bb, PetscReal omega, MatSORType flag, PetscReal fshift, PetscInt its, PetscInt lits, Vec xx) { Mat_SeqBAIJ *a = (Mat_SeqBAIJ *)A->data; PetscScalar *x, *work, *w, *workt, *t; const MatScalar *v, *aa = a->a, *idiag; const PetscScalar *b, *xb; PetscScalar s[7], xw[7] = {0}; /* avoid some compilers thinking xw is uninitialized */ PetscInt m = a->mbs, i, i2, nz, bs = A->rmap->bs, bs2 = bs * bs, k, j, idx, it; const PetscInt *diag, *ai = a->i, *aj = a->j, *vi; PetscFunctionBegin; its = its * lits; PetscCheck(!(flag & SOR_EISENSTAT), PETSC_COMM_SELF, PETSC_ERR_SUP, "No support yet for Eisenstat"); PetscCheck(its > 0, PETSC_COMM_SELF, PETSC_ERR_ARG_WRONG, "Relaxation requires global its %" PetscInt_FMT " and local its %" PetscInt_FMT " both positive", its, lits); PetscCheck(!fshift, PETSC_COMM_SELF, PETSC_ERR_SUP, "No support for diagonal shift"); PetscCheck(omega == 1.0, PETSC_COMM_SELF, PETSC_ERR_SUP, "No support for non-trivial relaxation factor"); PetscCheck(!(flag & SOR_APPLY_UPPER) && !(flag & SOR_APPLY_LOWER), PETSC_COMM_SELF, PETSC_ERR_SUP, "No support for applying upper or lower triangular parts"); if (!a->idiagvalid) PetscCall(MatInvertBlockDiagonal(A, NULL)); if (!m) PetscFunctionReturn(PETSC_SUCCESS); diag = a->diag; idiag = a->idiag; k = PetscMax(A->rmap->n, A->cmap->n); if (!a->mult_work) PetscCall(PetscMalloc1(k + 1, &a->mult_work)); if (!a->sor_workt) PetscCall(PetscMalloc1(k, &a->sor_workt)); if (!a->sor_work) PetscCall(PetscMalloc1(bs, &a->sor_work)); work = a->mult_work; t = a->sor_workt; w = a->sor_work; PetscCall(VecGetArray(xx, &x)); PetscCall(VecGetArrayRead(bb, &b)); if (flag & SOR_ZERO_INITIAL_GUESS) { if (flag & SOR_FORWARD_SWEEP || flag & SOR_LOCAL_FORWARD_SWEEP) { switch (bs) { case 1: PetscKernel_v_gets_A_times_w_1(x, idiag, b); t[0] = b[0]; i2 = 1; idiag += 1; for (i = 1; i < m; i++) { v = aa + ai[i]; vi = aj + ai[i]; nz = diag[i] - ai[i]; s[0] = b[i2]; for (j = 0; j < nz; j++) { xw[0] = x[vi[j]]; PetscKernel_v_gets_v_minus_A_times_w_1(s, (v + j), xw); } t[i2] = s[0]; PetscKernel_v_gets_A_times_w_1(xw, idiag, s); x[i2] = xw[0]; idiag += 1; i2 += 1; } break; case 2: PetscKernel_v_gets_A_times_w_2(x, idiag, b); t[0] = b[0]; t[1] = b[1]; i2 = 2; idiag += 4; for (i = 1; i < m; i++) { v = aa + 4 * ai[i]; vi = aj + ai[i]; nz = diag[i] - ai[i]; s[0] = b[i2]; s[1] = b[i2 + 1]; for (j = 0; j < nz; j++) { idx = 2 * vi[j]; it = 4 * j; xw[0] = x[idx]; xw[1] = x[1 + idx]; PetscKernel_v_gets_v_minus_A_times_w_2(s, (v + it), xw); } t[i2] = s[0]; t[i2 + 1] = s[1]; PetscKernel_v_gets_A_times_w_2(xw, idiag, s); x[i2] = xw[0]; x[i2 + 1] = xw[1]; idiag += 4; i2 += 2; } break; case 3: PetscKernel_v_gets_A_times_w_3(x, idiag, b); t[0] = b[0]; t[1] = b[1]; t[2] = b[2]; i2 = 3; idiag += 9; for (i = 1; i < m; i++) { v = aa + 9 * ai[i]; vi = aj + ai[i]; nz = diag[i] - ai[i]; s[0] = b[i2]; s[1] = b[i2 + 1]; s[2] = b[i2 + 2]; while (nz--) { idx = 3 * (*vi++); xw[0] = x[idx]; xw[1] = x[1 + idx]; xw[2] = x[2 + idx]; PetscKernel_v_gets_v_minus_A_times_w_3(s, v, xw); v += 9; } t[i2] = s[0]; t[i2 + 1] = s[1]; t[i2 + 2] = s[2]; PetscKernel_v_gets_A_times_w_3(xw, idiag, s); x[i2] = xw[0]; x[i2 + 1] = xw[1]; x[i2 + 2] = xw[2]; idiag += 9; i2 += 3; } break; case 4: PetscKernel_v_gets_A_times_w_4(x, idiag, b); t[0] = b[0]; t[1] = b[1]; t[2] = b[2]; t[3] = b[3]; i2 = 4; idiag += 16; for (i = 1; i < m; i++) { v = aa + 16 * ai[i]; vi = aj + ai[i]; nz = diag[i] - ai[i]; s[0] = b[i2]; s[1] = b[i2 + 1]; s[2] = b[i2 + 2]; s[3] = b[i2 + 3]; while (nz--) { idx = 4 * (*vi++); xw[0] = x[idx]; xw[1] = x[1 + idx]; xw[2] = x[2 + idx]; xw[3] = x[3 + idx]; PetscKernel_v_gets_v_minus_A_times_w_4(s, v, xw); v += 16; } t[i2] = s[0]; t[i2 + 1] = s[1]; t[i2 + 2] = s[2]; t[i2 + 3] = s[3]; PetscKernel_v_gets_A_times_w_4(xw, idiag, s); x[i2] = xw[0]; x[i2 + 1] = xw[1]; x[i2 + 2] = xw[2]; x[i2 + 3] = xw[3]; idiag += 16; i2 += 4; } break; case 5: PetscKernel_v_gets_A_times_w_5(x, idiag, b); t[0] = b[0]; t[1] = b[1]; t[2] = b[2]; t[3] = b[3]; t[4] = b[4]; i2 = 5; idiag += 25; for (i = 1; i < m; i++) { v = aa + 25 * ai[i]; vi = aj + ai[i]; nz = diag[i] - ai[i]; s[0] = b[i2]; s[1] = b[i2 + 1]; s[2] = b[i2 + 2]; s[3] = b[i2 + 3]; s[4] = b[i2 + 4]; while (nz--) { idx = 5 * (*vi++); xw[0] = x[idx]; xw[1] = x[1 + idx]; xw[2] = x[2 + idx]; xw[3] = x[3 + idx]; xw[4] = x[4 + idx]; PetscKernel_v_gets_v_minus_A_times_w_5(s, v, xw); v += 25; } t[i2] = s[0]; t[i2 + 1] = s[1]; t[i2 + 2] = s[2]; t[i2 + 3] = s[3]; t[i2 + 4] = s[4]; PetscKernel_v_gets_A_times_w_5(xw, idiag, s); x[i2] = xw[0]; x[i2 + 1] = xw[1]; x[i2 + 2] = xw[2]; x[i2 + 3] = xw[3]; x[i2 + 4] = xw[4]; idiag += 25; i2 += 5; } break; case 6: PetscKernel_v_gets_A_times_w_6(x, idiag, b); t[0] = b[0]; t[1] = b[1]; t[2] = b[2]; t[3] = b[3]; t[4] = b[4]; t[5] = b[5]; i2 = 6; idiag += 36; for (i = 1; i < m; i++) { v = aa + 36 * ai[i]; vi = aj + ai[i]; nz = diag[i] - ai[i]; s[0] = b[i2]; s[1] = b[i2 + 1]; s[2] = b[i2 + 2]; s[3] = b[i2 + 3]; s[4] = b[i2 + 4]; s[5] = b[i2 + 5]; while (nz--) { idx = 6 * (*vi++); xw[0] = x[idx]; xw[1] = x[1 + idx]; xw[2] = x[2 + idx]; xw[3] = x[3 + idx]; xw[4] = x[4 + idx]; xw[5] = x[5 + idx]; PetscKernel_v_gets_v_minus_A_times_w_6(s, v, xw); v += 36; } t[i2] = s[0]; t[i2 + 1] = s[1]; t[i2 + 2] = s[2]; t[i2 + 3] = s[3]; t[i2 + 4] = s[4]; t[i2 + 5] = s[5]; PetscKernel_v_gets_A_times_w_6(xw, idiag, s); x[i2] = xw[0]; x[i2 + 1] = xw[1]; x[i2 + 2] = xw[2]; x[i2 + 3] = xw[3]; x[i2 + 4] = xw[4]; x[i2 + 5] = xw[5]; idiag += 36; i2 += 6; } break; case 7: PetscKernel_v_gets_A_times_w_7(x, idiag, b); t[0] = b[0]; t[1] = b[1]; t[2] = b[2]; t[3] = b[3]; t[4] = b[4]; t[5] = b[5]; t[6] = b[6]; i2 = 7; idiag += 49; for (i = 1; i < m; i++) { v = aa + 49 * ai[i]; vi = aj + ai[i]; nz = diag[i] - ai[i]; s[0] = b[i2]; s[1] = b[i2 + 1]; s[2] = b[i2 + 2]; s[3] = b[i2 + 3]; s[4] = b[i2 + 4]; s[5] = b[i2 + 5]; s[6] = b[i2 + 6]; while (nz--) { idx = 7 * (*vi++); xw[0] = x[idx]; xw[1] = x[1 + idx]; xw[2] = x[2 + idx]; xw[3] = x[3 + idx]; xw[4] = x[4 + idx]; xw[5] = x[5 + idx]; xw[6] = x[6 + idx]; PetscKernel_v_gets_v_minus_A_times_w_7(s, v, xw); v += 49; } t[i2] = s[0]; t[i2 + 1] = s[1]; t[i2 + 2] = s[2]; t[i2 + 3] = s[3]; t[i2 + 4] = s[4]; t[i2 + 5] = s[5]; t[i2 + 6] = s[6]; PetscKernel_v_gets_A_times_w_7(xw, idiag, s); x[i2] = xw[0]; x[i2 + 1] = xw[1]; x[i2 + 2] = xw[2]; x[i2 + 3] = xw[3]; x[i2 + 4] = xw[4]; x[i2 + 5] = xw[5]; x[i2 + 6] = xw[6]; idiag += 49; i2 += 7; } break; default: PetscKernel_w_gets_Ar_times_v(bs, bs, b, idiag, x); PetscCall(PetscArraycpy(t, b, bs)); i2 = bs; idiag += bs2; for (i = 1; i < m; i++) { v = aa + bs2 * ai[i]; vi = aj + ai[i]; nz = diag[i] - ai[i]; PetscCall(PetscArraycpy(w, b + i2, bs)); /* copy all rows of x that are needed into contiguous space */ workt = work; for (j = 0; j < nz; j++) { PetscCall(PetscArraycpy(workt, x + bs * (*vi++), bs)); workt += bs; } PetscKernel_w_gets_w_minus_Ar_times_v(bs, bs * nz, w, v, work); PetscCall(PetscArraycpy(t + i2, w, bs)); PetscKernel_w_gets_Ar_times_v(bs, bs, w, idiag, x + i2); idiag += bs2; i2 += bs; } break; } /* for logging purposes assume number of nonzero in lower half is 1/2 of total */ PetscCall(PetscLogFlops(1.0 * bs2 * a->nz)); xb = t; } else xb = b; if (flag & SOR_BACKWARD_SWEEP || flag & SOR_LOCAL_BACKWARD_SWEEP) { idiag = a->idiag + bs2 * (a->mbs - 1); i2 = bs * (m - 1); switch (bs) { case 1: s[0] = xb[i2]; PetscKernel_v_gets_A_times_w_1(xw, idiag, s); x[i2] = xw[0]; i2 -= 1; for (i = m - 2; i >= 0; i--) { v = aa + (diag[i] + 1); vi = aj + diag[i] + 1; nz = ai[i + 1] - diag[i] - 1; s[0] = xb[i2]; for (j = 0; j < nz; j++) { xw[0] = x[vi[j]]; PetscKernel_v_gets_v_minus_A_times_w_1(s, (v + j), xw); } PetscKernel_v_gets_A_times_w_1(xw, idiag, s); x[i2] = xw[0]; idiag -= 1; i2 -= 1; } break; case 2: s[0] = xb[i2]; s[1] = xb[i2 + 1]; PetscKernel_v_gets_A_times_w_2(xw, idiag, s); x[i2] = xw[0]; x[i2 + 1] = xw[1]; i2 -= 2; idiag -= 4; for (i = m - 2; i >= 0; i--) { v = aa + 4 * (diag[i] + 1); vi = aj + diag[i] + 1; nz = ai[i + 1] - diag[i] - 1; s[0] = xb[i2]; s[1] = xb[i2 + 1]; for (j = 0; j < nz; j++) { idx = 2 * vi[j]; it = 4 * j; xw[0] = x[idx]; xw[1] = x[1 + idx]; PetscKernel_v_gets_v_minus_A_times_w_2(s, (v + it), xw); } PetscKernel_v_gets_A_times_w_2(xw, idiag, s); x[i2] = xw[0]; x[i2 + 1] = xw[1]; idiag -= 4; i2 -= 2; } break; case 3: s[0] = xb[i2]; s[1] = xb[i2 + 1]; s[2] = xb[i2 + 2]; PetscKernel_v_gets_A_times_w_3(xw, idiag, s); x[i2] = xw[0]; x[i2 + 1] = xw[1]; x[i2 + 2] = xw[2]; i2 -= 3; idiag -= 9; for (i = m - 2; i >= 0; i--) { v = aa + 9 * (diag[i] + 1); vi = aj + diag[i] + 1; nz = ai[i + 1] - diag[i] - 1; s[0] = xb[i2]; s[1] = xb[i2 + 1]; s[2] = xb[i2 + 2]; while (nz--) { idx = 3 * (*vi++); xw[0] = x[idx]; xw[1] = x[1 + idx]; xw[2] = x[2 + idx]; PetscKernel_v_gets_v_minus_A_times_w_3(s, v, xw); v += 9; } PetscKernel_v_gets_A_times_w_3(xw, idiag, s); x[i2] = xw[0]; x[i2 + 1] = xw[1]; x[i2 + 2] = xw[2]; idiag -= 9; i2 -= 3; } break; case 4: s[0] = xb[i2]; s[1] = xb[i2 + 1]; s[2] = xb[i2 + 2]; s[3] = xb[i2 + 3]; PetscKernel_v_gets_A_times_w_4(xw, idiag, s); x[i2] = xw[0]; x[i2 + 1] = xw[1]; x[i2 + 2] = xw[2]; x[i2 + 3] = xw[3]; i2 -= 4; idiag -= 16; for (i = m - 2; i >= 0; i--) { v = aa + 16 * (diag[i] + 1); vi = aj + diag[i] + 1; nz = ai[i + 1] - diag[i] - 1; s[0] = xb[i2]; s[1] = xb[i2 + 1]; s[2] = xb[i2 + 2]; s[3] = xb[i2 + 3]; while (nz--) { idx = 4 * (*vi++); xw[0] = x[idx]; xw[1] = x[1 + idx]; xw[2] = x[2 + idx]; xw[3] = x[3 + idx]; PetscKernel_v_gets_v_minus_A_times_w_4(s, v, xw); v += 16; } PetscKernel_v_gets_A_times_w_4(xw, idiag, s); x[i2] = xw[0]; x[i2 + 1] = xw[1]; x[i2 + 2] = xw[2]; x[i2 + 3] = xw[3]; idiag -= 16; i2 -= 4; } break; case 5: s[0] = xb[i2]; s[1] = xb[i2 + 1]; s[2] = xb[i2 + 2]; s[3] = xb[i2 + 3]; s[4] = xb[i2 + 4]; PetscKernel_v_gets_A_times_w_5(xw, idiag, s); x[i2] = xw[0]; x[i2 + 1] = xw[1]; x[i2 + 2] = xw[2]; x[i2 + 3] = xw[3]; x[i2 + 4] = xw[4]; i2 -= 5; idiag -= 25; for (i = m - 2; i >= 0; i--) { v = aa + 25 * (diag[i] + 1); vi = aj + diag[i] + 1; nz = ai[i + 1] - diag[i] - 1; s[0] = xb[i2]; s[1] = xb[i2 + 1]; s[2] = xb[i2 + 2]; s[3] = xb[i2 + 3]; s[4] = xb[i2 + 4]; while (nz--) { idx = 5 * (*vi++); xw[0] = x[idx]; xw[1] = x[1 + idx]; xw[2] = x[2 + idx]; xw[3] = x[3 + idx]; xw[4] = x[4 + idx]; PetscKernel_v_gets_v_minus_A_times_w_5(s, v, xw); v += 25; } PetscKernel_v_gets_A_times_w_5(xw, idiag, s); x[i2] = xw[0]; x[i2 + 1] = xw[1]; x[i2 + 2] = xw[2]; x[i2 + 3] = xw[3]; x[i2 + 4] = xw[4]; idiag -= 25; i2 -= 5; } break; case 6: s[0] = xb[i2]; s[1] = xb[i2 + 1]; s[2] = xb[i2 + 2]; s[3] = xb[i2 + 3]; s[4] = xb[i2 + 4]; s[5] = xb[i2 + 5]; PetscKernel_v_gets_A_times_w_6(xw, idiag, s); x[i2] = xw[0]; x[i2 + 1] = xw[1]; x[i2 + 2] = xw[2]; x[i2 + 3] = xw[3]; x[i2 + 4] = xw[4]; x[i2 + 5] = xw[5]; i2 -= 6; idiag -= 36; for (i = m - 2; i >= 0; i--) { v = aa + 36 * (diag[i] + 1); vi = aj + diag[i] + 1; nz = ai[i + 1] - diag[i] - 1; s[0] = xb[i2]; s[1] = xb[i2 + 1]; s[2] = xb[i2 + 2]; s[3] = xb[i2 + 3]; s[4] = xb[i2 + 4]; s[5] = xb[i2 + 5]; while (nz--) { idx = 6 * (*vi++); xw[0] = x[idx]; xw[1] = x[1 + idx]; xw[2] = x[2 + idx]; xw[3] = x[3 + idx]; xw[4] = x[4 + idx]; xw[5] = x[5 + idx]; PetscKernel_v_gets_v_minus_A_times_w_6(s, v, xw); v += 36; } PetscKernel_v_gets_A_times_w_6(xw, idiag, s); x[i2] = xw[0]; x[i2 + 1] = xw[1]; x[i2 + 2] = xw[2]; x[i2 + 3] = xw[3]; x[i2 + 4] = xw[4]; x[i2 + 5] = xw[5]; idiag -= 36; i2 -= 6; } break; case 7: s[0] = xb[i2]; s[1] = xb[i2 + 1]; s[2] = xb[i2 + 2]; s[3] = xb[i2 + 3]; s[4] = xb[i2 + 4]; s[5] = xb[i2 + 5]; s[6] = xb[i2 + 6]; PetscKernel_v_gets_A_times_w_7(x, idiag, b); x[i2] = xw[0]; x[i2 + 1] = xw[1]; x[i2 + 2] = xw[2]; x[i2 + 3] = xw[3]; x[i2 + 4] = xw[4]; x[i2 + 5] = xw[5]; x[i2 + 6] = xw[6]; i2 -= 7; idiag -= 49; for (i = m - 2; i >= 0; i--) { v = aa + 49 * (diag[i] + 1); vi = aj + diag[i] + 1; nz = ai[i + 1] - diag[i] - 1; s[0] = xb[i2]; s[1] = xb[i2 + 1]; s[2] = xb[i2 + 2]; s[3] = xb[i2 + 3]; s[4] = xb[i2 + 4]; s[5] = xb[i2 + 5]; s[6] = xb[i2 + 6]; while (nz--) { idx = 7 * (*vi++); xw[0] = x[idx]; xw[1] = x[1 + idx]; xw[2] = x[2 + idx]; xw[3] = x[3 + idx]; xw[4] = x[4 + idx]; xw[5] = x[5 + idx]; xw[6] = x[6 + idx]; PetscKernel_v_gets_v_minus_A_times_w_7(s, v, xw); v += 49; } PetscKernel_v_gets_A_times_w_7(xw, idiag, s); x[i2] = xw[0]; x[i2 + 1] = xw[1]; x[i2 + 2] = xw[2]; x[i2 + 3] = xw[3]; x[i2 + 4] = xw[4]; x[i2 + 5] = xw[5]; x[i2 + 6] = xw[6]; idiag -= 49; i2 -= 7; } break; default: PetscCall(PetscArraycpy(w, xb + i2, bs)); PetscKernel_w_gets_Ar_times_v(bs, bs, w, idiag, x + i2); i2 -= bs; idiag -= bs2; for (i = m - 2; i >= 0; i--) { v = aa + bs2 * (diag[i] + 1); vi = aj + diag[i] + 1; nz = ai[i + 1] - diag[i] - 1; PetscCall(PetscArraycpy(w, xb + i2, bs)); /* copy all rows of x that are needed into contiguous space */ workt = work; for (j = 0; j < nz; j++) { PetscCall(PetscArraycpy(workt, x + bs * (*vi++), bs)); workt += bs; } PetscKernel_w_gets_w_minus_Ar_times_v(bs, bs * nz, w, v, work); PetscKernel_w_gets_Ar_times_v(bs, bs, w, idiag, x + i2); idiag -= bs2; i2 -= bs; } break; } PetscCall(PetscLogFlops(1.0 * bs2 * (a->nz))); } its--; } while (its--) { if (flag & SOR_FORWARD_SWEEP || flag & SOR_LOCAL_FORWARD_SWEEP) { idiag = a->idiag; i2 = 0; switch (bs) { case 1: for (i = 0; i < m; i++) { v = aa + ai[i]; vi = aj + ai[i]; nz = ai[i + 1] - ai[i]; s[0] = b[i2]; for (j = 0; j < nz; j++) { xw[0] = x[vi[j]]; PetscKernel_v_gets_v_minus_A_times_w_1(s, (v + j), xw); } PetscKernel_v_gets_A_times_w_1(xw, idiag, s); x[i2] += xw[0]; idiag += 1; i2 += 1; } break; case 2: for (i = 0; i < m; i++) { v = aa + 4 * ai[i]; vi = aj + ai[i]; nz = ai[i + 1] - ai[i]; s[0] = b[i2]; s[1] = b[i2 + 1]; for (j = 0; j < nz; j++) { idx = 2 * vi[j]; it = 4 * j; xw[0] = x[idx]; xw[1] = x[1 + idx]; PetscKernel_v_gets_v_minus_A_times_w_2(s, (v + it), xw); } PetscKernel_v_gets_A_times_w_2(xw, idiag, s); x[i2] += xw[0]; x[i2 + 1] += xw[1]; idiag += 4; i2 += 2; } break; case 3: for (i = 0; i < m; i++) { v = aa + 9 * ai[i]; vi = aj + ai[i]; nz = ai[i + 1] - ai[i]; s[0] = b[i2]; s[1] = b[i2 + 1]; s[2] = b[i2 + 2]; while (nz--) { idx = 3 * (*vi++); xw[0] = x[idx]; xw[1] = x[1 + idx]; xw[2] = x[2 + idx]; PetscKernel_v_gets_v_minus_A_times_w_3(s, v, xw); v += 9; } PetscKernel_v_gets_A_times_w_3(xw, idiag, s); x[i2] += xw[0]; x[i2 + 1] += xw[1]; x[i2 + 2] += xw[2]; idiag += 9; i2 += 3; } break; case 4: for (i = 0; i < m; i++) { v = aa + 16 * ai[i]; vi = aj + ai[i]; nz = ai[i + 1] - ai[i]; s[0] = b[i2]; s[1] = b[i2 + 1]; s[2] = b[i2 + 2]; s[3] = b[i2 + 3]; while (nz--) { idx = 4 * (*vi++); xw[0] = x[idx]; xw[1] = x[1 + idx]; xw[2] = x[2 + idx]; xw[3] = x[3 + idx]; PetscKernel_v_gets_v_minus_A_times_w_4(s, v, xw); v += 16; } PetscKernel_v_gets_A_times_w_4(xw, idiag, s); x[i2] += xw[0]; x[i2 + 1] += xw[1]; x[i2 + 2] += xw[2]; x[i2 + 3] += xw[3]; idiag += 16; i2 += 4; } break; case 5: for (i = 0; i < m; i++) { v = aa + 25 * ai[i]; vi = aj + ai[i]; nz = ai[i + 1] - ai[i]; s[0] = b[i2]; s[1] = b[i2 + 1]; s[2] = b[i2 + 2]; s[3] = b[i2 + 3]; s[4] = b[i2 + 4]; while (nz--) { idx = 5 * (*vi++); xw[0] = x[idx]; xw[1] = x[1 + idx]; xw[2] = x[2 + idx]; xw[3] = x[3 + idx]; xw[4] = x[4 + idx]; PetscKernel_v_gets_v_minus_A_times_w_5(s, v, xw); v += 25; } PetscKernel_v_gets_A_times_w_5(xw, idiag, s); x[i2] += xw[0]; x[i2 + 1] += xw[1]; x[i2 + 2] += xw[2]; x[i2 + 3] += xw[3]; x[i2 + 4] += xw[4]; idiag += 25; i2 += 5; } break; case 6: for (i = 0; i < m; i++) { v = aa + 36 * ai[i]; vi = aj + ai[i]; nz = ai[i + 1] - ai[i]; s[0] = b[i2]; s[1] = b[i2 + 1]; s[2] = b[i2 + 2]; s[3] = b[i2 + 3]; s[4] = b[i2 + 4]; s[5] = b[i2 + 5]; while (nz--) { idx = 6 * (*vi++); xw[0] = x[idx]; xw[1] = x[1 + idx]; xw[2] = x[2 + idx]; xw[3] = x[3 + idx]; xw[4] = x[4 + idx]; xw[5] = x[5 + idx]; PetscKernel_v_gets_v_minus_A_times_w_6(s, v, xw); v += 36; } PetscKernel_v_gets_A_times_w_6(xw, idiag, s); x[i2] += xw[0]; x[i2 + 1] += xw[1]; x[i2 + 2] += xw[2]; x[i2 + 3] += xw[3]; x[i2 + 4] += xw[4]; x[i2 + 5] += xw[5]; idiag += 36; i2 += 6; } break; case 7: for (i = 0; i < m; i++) { v = aa + 49 * ai[i]; vi = aj + ai[i]; nz = ai[i + 1] - ai[i]; s[0] = b[i2]; s[1] = b[i2 + 1]; s[2] = b[i2 + 2]; s[3] = b[i2 + 3]; s[4] = b[i2 + 4]; s[5] = b[i2 + 5]; s[6] = b[i2 + 6]; while (nz--) { idx = 7 * (*vi++); xw[0] = x[idx]; xw[1] = x[1 + idx]; xw[2] = x[2 + idx]; xw[3] = x[3 + idx]; xw[4] = x[4 + idx]; xw[5] = x[5 + idx]; xw[6] = x[6 + idx]; PetscKernel_v_gets_v_minus_A_times_w_7(s, v, xw); v += 49; } PetscKernel_v_gets_A_times_w_7(xw, idiag, s); x[i2] += xw[0]; x[i2 + 1] += xw[1]; x[i2 + 2] += xw[2]; x[i2 + 3] += xw[3]; x[i2 + 4] += xw[4]; x[i2 + 5] += xw[5]; x[i2 + 6] += xw[6]; idiag += 49; i2 += 7; } break; default: for (i = 0; i < m; i++) { v = aa + bs2 * ai[i]; vi = aj + ai[i]; nz = ai[i + 1] - ai[i]; PetscCall(PetscArraycpy(w, b + i2, bs)); /* copy all rows of x that are needed into contiguous space */ workt = work; for (j = 0; j < nz; j++) { PetscCall(PetscArraycpy(workt, x + bs * (*vi++), bs)); workt += bs; } PetscKernel_w_gets_w_minus_Ar_times_v(bs, bs * nz, w, v, work); PetscKernel_w_gets_w_plus_Ar_times_v(bs, bs, w, idiag, x + i2); idiag += bs2; i2 += bs; } break; } PetscCall(PetscLogFlops(2.0 * bs2 * a->nz)); } if (flag & SOR_BACKWARD_SWEEP || flag & SOR_LOCAL_BACKWARD_SWEEP) { idiag = a->idiag + bs2 * (a->mbs - 1); i2 = bs * (m - 1); switch (bs) { case 1: for (i = m - 1; i >= 0; i--) { v = aa + ai[i]; vi = aj + ai[i]; nz = ai[i + 1] - ai[i]; s[0] = b[i2]; for (j = 0; j < nz; j++) { xw[0] = x[vi[j]]; PetscKernel_v_gets_v_minus_A_times_w_1(s, (v + j), xw); } PetscKernel_v_gets_A_times_w_1(xw, idiag, s); x[i2] += xw[0]; idiag -= 1; i2 -= 1; } break; case 2: for (i = m - 1; i >= 0; i--) { v = aa + 4 * ai[i]; vi = aj + ai[i]; nz = ai[i + 1] - ai[i]; s[0] = b[i2]; s[1] = b[i2 + 1]; for (j = 0; j < nz; j++) { idx = 2 * vi[j]; it = 4 * j; xw[0] = x[idx]; xw[1] = x[1 + idx]; PetscKernel_v_gets_v_minus_A_times_w_2(s, (v + it), xw); } PetscKernel_v_gets_A_times_w_2(xw, idiag, s); x[i2] += xw[0]; x[i2 + 1] += xw[1]; idiag -= 4; i2 -= 2; } break; case 3: for (i = m - 1; i >= 0; i--) { v = aa + 9 * ai[i]; vi = aj + ai[i]; nz = ai[i + 1] - ai[i]; s[0] = b[i2]; s[1] = b[i2 + 1]; s[2] = b[i2 + 2]; while (nz--) { idx = 3 * (*vi++); xw[0] = x[idx]; xw[1] = x[1 + idx]; xw[2] = x[2 + idx]; PetscKernel_v_gets_v_minus_A_times_w_3(s, v, xw); v += 9; } PetscKernel_v_gets_A_times_w_3(xw, idiag, s); x[i2] += xw[0]; x[i2 + 1] += xw[1]; x[i2 + 2] += xw[2]; idiag -= 9; i2 -= 3; } break; case 4: for (i = m - 1; i >= 0; i--) { v = aa + 16 * ai[i]; vi = aj + ai[i]; nz = ai[i + 1] - ai[i]; s[0] = b[i2]; s[1] = b[i2 + 1]; s[2] = b[i2 + 2]; s[3] = b[i2 + 3]; while (nz--) { idx = 4 * (*vi++); xw[0] = x[idx]; xw[1] = x[1 + idx]; xw[2] = x[2 + idx]; xw[3] = x[3 + idx]; PetscKernel_v_gets_v_minus_A_times_w_4(s, v, xw); v += 16; } PetscKernel_v_gets_A_times_w_4(xw, idiag, s); x[i2] += xw[0]; x[i2 + 1] += xw[1]; x[i2 + 2] += xw[2]; x[i2 + 3] += xw[3]; idiag -= 16; i2 -= 4; } break; case 5: for (i = m - 1; i >= 0; i--) { v = aa + 25 * ai[i]; vi = aj + ai[i]; nz = ai[i + 1] - ai[i]; s[0] = b[i2]; s[1] = b[i2 + 1]; s[2] = b[i2 + 2]; s[3] = b[i2 + 3]; s[4] = b[i2 + 4]; while (nz--) { idx = 5 * (*vi++); xw[0] = x[idx]; xw[1] = x[1 + idx]; xw[2] = x[2 + idx]; xw[3] = x[3 + idx]; xw[4] = x[4 + idx]; PetscKernel_v_gets_v_minus_A_times_w_5(s, v, xw); v += 25; } PetscKernel_v_gets_A_times_w_5(xw, idiag, s); x[i2] += xw[0]; x[i2 + 1] += xw[1]; x[i2 + 2] += xw[2]; x[i2 + 3] += xw[3]; x[i2 + 4] += xw[4]; idiag -= 25; i2 -= 5; } break; case 6: for (i = m - 1; i >= 0; i--) { v = aa + 36 * ai[i]; vi = aj + ai[i]; nz = ai[i + 1] - ai[i]; s[0] = b[i2]; s[1] = b[i2 + 1]; s[2] = b[i2 + 2]; s[3] = b[i2 + 3]; s[4] = b[i2 + 4]; s[5] = b[i2 + 5]; while (nz--) { idx = 6 * (*vi++); xw[0] = x[idx]; xw[1] = x[1 + idx]; xw[2] = x[2 + idx]; xw[3] = x[3 + idx]; xw[4] = x[4 + idx]; xw[5] = x[5 + idx]; PetscKernel_v_gets_v_minus_A_times_w_6(s, v, xw); v += 36; } PetscKernel_v_gets_A_times_w_6(xw, idiag, s); x[i2] += xw[0]; x[i2 + 1] += xw[1]; x[i2 + 2] += xw[2]; x[i2 + 3] += xw[3]; x[i2 + 4] += xw[4]; x[i2 + 5] += xw[5]; idiag -= 36; i2 -= 6; } break; case 7: for (i = m - 1; i >= 0; i--) { v = aa + 49 * ai[i]; vi = aj + ai[i]; nz = ai[i + 1] - ai[i]; s[0] = b[i2]; s[1] = b[i2 + 1]; s[2] = b[i2 + 2]; s[3] = b[i2 + 3]; s[4] = b[i2 + 4]; s[5] = b[i2 + 5]; s[6] = b[i2 + 6]; while (nz--) { idx = 7 * (*vi++); xw[0] = x[idx]; xw[1] = x[1 + idx]; xw[2] = x[2 + idx]; xw[3] = x[3 + idx]; xw[4] = x[4 + idx]; xw[5] = x[5 + idx]; xw[6] = x[6 + idx]; PetscKernel_v_gets_v_minus_A_times_w_7(s, v, xw); v += 49; } PetscKernel_v_gets_A_times_w_7(xw, idiag, s); x[i2] += xw[0]; x[i2 + 1] += xw[1]; x[i2 + 2] += xw[2]; x[i2 + 3] += xw[3]; x[i2 + 4] += xw[4]; x[i2 + 5] += xw[5]; x[i2 + 6] += xw[6]; idiag -= 49; i2 -= 7; } break; default: for (i = m - 1; i >= 0; i--) { v = aa + bs2 * ai[i]; vi = aj + ai[i]; nz = ai[i + 1] - ai[i]; PetscCall(PetscArraycpy(w, b + i2, bs)); /* copy all rows of x that are needed into contiguous space */ workt = work; for (j = 0; j < nz; j++) { PetscCall(PetscArraycpy(workt, x + bs * (*vi++), bs)); workt += bs; } PetscKernel_w_gets_w_minus_Ar_times_v(bs, bs * nz, w, v, work); PetscKernel_w_gets_w_plus_Ar_times_v(bs, bs, w, idiag, x + i2); idiag -= bs2; i2 -= bs; } break; } PetscCall(PetscLogFlops(2.0 * bs2 * (a->nz))); } } PetscCall(VecRestoreArray(xx, &x)); PetscCall(VecRestoreArrayRead(bb, &b)); PetscFunctionReturn(PETSC_SUCCESS); } /* Special version for direct calls from Fortran (Used in PETSc-fun3d) */ #if defined(PETSC_HAVE_FORTRAN_CAPS) #define matsetvaluesblocked4_ MATSETVALUESBLOCKED4 #elif !defined(PETSC_HAVE_FORTRAN_UNDERSCORE) #define matsetvaluesblocked4_ matsetvaluesblocked4 #endif PETSC_EXTERN void matsetvaluesblocked4_(Mat *AA, PetscInt *mm, const PetscInt im[], PetscInt *nn, const PetscInt in[], const PetscScalar v[]) { Mat A = *AA; Mat_SeqBAIJ *a = (Mat_SeqBAIJ *)A->data; PetscInt *rp, k, low, high, t, ii, jj, row, nrow, i, col, l, N, m = *mm, n = *nn; PetscInt *ai = a->i, *ailen = a->ilen; PetscInt *aj = a->j, stepval, lastcol = -1; const PetscScalar *value = v; MatScalar *ap, *aa = a->a, *bap; PetscFunctionBegin; if (A->rmap->bs != 4) SETERRABORT(PetscObjectComm((PetscObject)A), PETSC_ERR_ARG_WRONG, "Can only be called with a block size of 4"); stepval = (n - 1) * 4; for (k = 0; k < m; k++) { /* loop over added rows */ row = im[k]; rp = aj + ai[row]; ap = aa + 16 * ai[row]; nrow = ailen[row]; low = 0; high = nrow; for (l = 0; l < n; l++) { /* loop over added columns */ col = in[l]; if (col <= lastcol) low = 0; else high = nrow; lastcol = col; value = v + k * (stepval + 4 + l) * 4; while (high - low > 7) { t = (low + high) / 2; if (rp[t] > col) high = t; else low = t; } for (i = low; i < high; i++) { if (rp[i] > col) break; if (rp[i] == col) { bap = ap + 16 * i; for (ii = 0; ii < 4; ii++, value += stepval) { for (jj = ii; jj < 16; jj += 4) bap[jj] += *value++; } goto noinsert2; } } N = nrow++ - 1; high++; /* added new column index thus must search to one higher than before */ /* shift up all the later entries in this row */ for (ii = N; ii >= i; ii--) { rp[ii + 1] = rp[ii]; PetscCallVoid(PetscArraycpy(ap + 16 * (ii + 1), ap + 16 * (ii), 16)); } if (N >= i) PetscCallVoid(PetscArrayzero(ap + 16 * i, 16)); rp[i] = col; bap = ap + 16 * i; for (ii = 0; ii < 4; ii++, value += stepval) { for (jj = ii; jj < 16; jj += 4) bap[jj] = *value++; } noinsert2:; low = i; } ailen[row] = nrow; } PetscFunctionReturnVoid(); } #if defined(PETSC_HAVE_FORTRAN_CAPS) #define matsetvalues4_ MATSETVALUES4 #elif !defined(PETSC_HAVE_FORTRAN_UNDERSCORE) #define matsetvalues4_ matsetvalues4 #endif PETSC_EXTERN void matsetvalues4_(Mat *AA, PetscInt *mm, PetscInt *im, PetscInt *nn, PetscInt *in, PetscScalar *v) { Mat A = *AA; Mat_SeqBAIJ *a = (Mat_SeqBAIJ *)A->data; PetscInt *rp, k, low, high, t, row, nrow, i, col, l, N, n = *nn, m = *mm; PetscInt *ai = a->i, *ailen = a->ilen; PetscInt *aj = a->j, brow, bcol; PetscInt ridx, cidx, lastcol = -1; MatScalar *ap, value, *aa = a->a, *bap; PetscFunctionBegin; for (k = 0; k < m; k++) { /* loop over added rows */ row = im[k]; brow = row / 4; rp = aj + ai[brow]; ap = aa + 16 * ai[brow]; nrow = ailen[brow]; low = 0; high = nrow; for (l = 0; l < n; l++) { /* loop over added columns */ col = in[l]; bcol = col / 4; ridx = row % 4; cidx = col % 4; value = v[l + k * n]; if (col <= lastcol) low = 0; else high = nrow; lastcol = col; while (high - low > 7) { t = (low + high) / 2; if (rp[t] > bcol) high = t; else low = t; } for (i = low; i < high; i++) { if (rp[i] > bcol) break; if (rp[i] == bcol) { bap = ap + 16 * i + 4 * cidx + ridx; *bap += value; goto noinsert1; } } N = nrow++ - 1; high++; /* added new column thus must search to one higher than before */ /* shift up all the later entries in this row */ PetscCallVoid(PetscArraymove(rp + i + 1, rp + i, N - i + 1)); PetscCallVoid(PetscArraymove(ap + 16 * i + 16, ap + 16 * i, 16 * (N - i + 1))); PetscCallVoid(PetscArrayzero(ap + 16 * i, 16)); rp[i] = bcol; ap[16 * i + 4 * cidx + ridx] = value; noinsert1:; low = i; } ailen[brow] = nrow; } PetscFunctionReturnVoid(); } static PetscErrorCode MatGetRowIJ_SeqBAIJ(Mat A, PetscInt oshift, PetscBool symmetric, PetscBool blockcompressed, PetscInt *nn, const PetscInt *inia[], const PetscInt *inja[], PetscBool *done) { Mat_SeqBAIJ *a = (Mat_SeqBAIJ *)A->data; PetscInt i, j, n = a->mbs, nz = a->i[n], *tia, *tja, bs = A->rmap->bs, k, l, cnt; PetscInt **ia = (PetscInt **)inia, **ja = (PetscInt **)inja; PetscFunctionBegin; *nn = n; if (!ia) PetscFunctionReturn(PETSC_SUCCESS); if (symmetric) { PetscCall(MatToSymmetricIJ_SeqAIJ(n, a->i, a->j, PETSC_TRUE, 0, 0, &tia, &tja)); nz = tia[n]; } else { tia = a->i; tja = a->j; } if (!blockcompressed && bs > 1) { (*nn) *= bs; /* malloc & create the natural set of indices */ PetscCall(PetscMalloc1((n + 1) * bs, ia)); if (n) { (*ia)[0] = oshift; for (j = 1; j < bs; j++) (*ia)[j] = (tia[1] - tia[0]) * bs + (*ia)[j - 1]; } for (i = 1; i < n; i++) { (*ia)[i * bs] = (tia[i] - tia[i - 1]) * bs + (*ia)[i * bs - 1]; for (j = 1; j < bs; j++) (*ia)[i * bs + j] = (tia[i + 1] - tia[i]) * bs + (*ia)[i * bs + j - 1]; } if (n) (*ia)[n * bs] = (tia[n] - tia[n - 1]) * bs + (*ia)[n * bs - 1]; if (inja) { PetscCall(PetscMalloc1(nz * bs * bs, ja)); cnt = 0; for (i = 0; i < n; i++) { for (j = 0; j < bs; j++) { for (k = tia[i]; k < tia[i + 1]; k++) { for (l = 0; l < bs; l++) (*ja)[cnt++] = bs * tja[k] + l; } } } } if (symmetric) { /* deallocate memory allocated in MatToSymmetricIJ_SeqAIJ() */ PetscCall(PetscFree(tia)); PetscCall(PetscFree(tja)); } } else if (oshift == 1) { if (symmetric) { nz = tia[A->rmap->n / bs]; /* add 1 to i and j indices */ for (i = 0; i < A->rmap->n / bs + 1; i++) tia[i] = tia[i] + 1; *ia = tia; if (ja) { for (i = 0; i < nz; i++) tja[i] = tja[i] + 1; *ja = tja; } } else { nz = a->i[A->rmap->n / bs]; /* malloc space and add 1 to i and j indices */ PetscCall(PetscMalloc1(A->rmap->n / bs + 1, ia)); for (i = 0; i < A->rmap->n / bs + 1; i++) (*ia)[i] = a->i[i] + 1; if (ja) { PetscCall(PetscMalloc1(nz, ja)); for (i = 0; i < nz; i++) (*ja)[i] = a->j[i] + 1; } } } else { *ia = tia; if (ja) *ja = tja; } PetscFunctionReturn(PETSC_SUCCESS); } static PetscErrorCode MatRestoreRowIJ_SeqBAIJ(Mat A, PetscInt oshift, PetscBool symmetric, PetscBool blockcompressed, PetscInt *nn, const PetscInt *ia[], const PetscInt *ja[], PetscBool *done) { PetscFunctionBegin; if (!ia) PetscFunctionReturn(PETSC_SUCCESS); if ((!blockcompressed && A->rmap->bs > 1) || (symmetric || oshift == 1)) { PetscCall(PetscFree(*ia)); if (ja) PetscCall(PetscFree(*ja)); } PetscFunctionReturn(PETSC_SUCCESS); } PetscErrorCode MatDestroy_SeqBAIJ(Mat A) { Mat_SeqBAIJ *a = (Mat_SeqBAIJ *)A->data; PetscFunctionBegin; if (A->hash_active) { PetscInt bs; A->ops[0] = a->cops; PetscCall(PetscHMapIJVDestroy(&a->ht)); PetscCall(MatGetBlockSize(A, &bs)); if (bs > 1) PetscCall(PetscHSetIJDestroy(&a->bht)); PetscCall(PetscFree(a->dnz)); PetscCall(PetscFree(a->bdnz)); A->hash_active = PETSC_FALSE; } PetscCall(PetscLogObjectState((PetscObject)A, "Rows=%" PetscInt_FMT ", Cols=%" PetscInt_FMT ", NZ=%" PetscInt_FMT, A->rmap->N, A->cmap->n, a->nz)); PetscCall(MatSeqXAIJFreeAIJ(A, &a->a, &a->j, &a->i)); PetscCall(ISDestroy(&a->row)); PetscCall(ISDestroy(&a->col)); PetscCall(PetscFree(a->diag)); PetscCall(PetscFree(a->idiag)); if (a->free_imax_ilen) PetscCall(PetscFree2(a->imax, a->ilen)); PetscCall(PetscFree(a->solve_work)); PetscCall(PetscFree(a->mult_work)); PetscCall(PetscFree(a->sor_workt)); PetscCall(PetscFree(a->sor_work)); PetscCall(ISDestroy(&a->icol)); PetscCall(PetscFree(a->saved_values)); PetscCall(PetscFree2(a->compressedrow.i, a->compressedrow.rindex)); PetscCall(MatDestroy(&a->sbaijMat)); PetscCall(MatDestroy(&a->parent)); PetscCall(PetscFree(A->data)); PetscCall(PetscObjectChangeTypeName((PetscObject)A, NULL)); PetscCall(PetscObjectComposeFunction((PetscObject)A, "MatSeqBAIJGetArray_C", NULL)); PetscCall(PetscObjectComposeFunction((PetscObject)A, "MatSeqBAIJRestoreArray_C", NULL)); PetscCall(PetscObjectComposeFunction((PetscObject)A, "MatStoreValues_C", NULL)); PetscCall(PetscObjectComposeFunction((PetscObject)A, "MatRetrieveValues_C", NULL)); PetscCall(PetscObjectComposeFunction((PetscObject)A, "MatSeqBAIJSetColumnIndices_C", NULL)); PetscCall(PetscObjectComposeFunction((PetscObject)A, "MatConvert_seqbaij_seqaij_C", NULL)); PetscCall(PetscObjectComposeFunction((PetscObject)A, "MatConvert_seqbaij_seqsbaij_C", NULL)); PetscCall(PetscObjectComposeFunction((PetscObject)A, "MatSeqBAIJSetPreallocation_C", NULL)); PetscCall(PetscObjectComposeFunction((PetscObject)A, "MatSeqBAIJSetPreallocationCSR_C", NULL)); PetscCall(PetscObjectComposeFunction((PetscObject)A, "MatConvert_seqbaij_seqbstrm_C", NULL)); PetscCall(PetscObjectComposeFunction((PetscObject)A, "MatIsTranspose_C", NULL)); #if defined(PETSC_HAVE_HYPRE) PetscCall(PetscObjectComposeFunction((PetscObject)A, "MatConvert_seqbaij_hypre_C", NULL)); #endif PetscCall(PetscObjectComposeFunction((PetscObject)A, "MatConvert_seqbaij_is_C", NULL)); PetscCall(PetscObjectComposeFunction((PetscObject)A, "MatFactorGetSolverType_C", NULL)); PetscFunctionReturn(PETSC_SUCCESS); } static PetscErrorCode MatSetOption_SeqBAIJ(Mat A, MatOption op, PetscBool flg) { Mat_SeqBAIJ *a = (Mat_SeqBAIJ *)A->data; PetscFunctionBegin; switch (op) { case MAT_ROW_ORIENTED: a->roworiented = flg; break; case MAT_KEEP_NONZERO_PATTERN: a->keepnonzeropattern = flg; break; case MAT_NEW_NONZERO_LOCATIONS: a->nonew = (flg ? 0 : 1); break; case MAT_NEW_NONZERO_LOCATION_ERR: a->nonew = (flg ? -1 : 0); break; case MAT_NEW_NONZERO_ALLOCATION_ERR: a->nonew = (flg ? -2 : 0); break; case MAT_UNUSED_NONZERO_LOCATION_ERR: a->nounused = (flg ? -1 : 0); break; default: break; } PetscFunctionReturn(PETSC_SUCCESS); } /* used for both SeqBAIJ and SeqSBAIJ matrices */ PetscErrorCode MatGetRow_SeqBAIJ_private(Mat A, PetscInt row, PetscInt *nz, PetscInt **idx, PetscScalar **v, PetscInt *ai, PetscInt *aj, PetscScalar *aa) { PetscInt itmp, i, j, k, M, bn, bp, *idx_i, bs, bs2; MatScalar *aa_i; PetscScalar *v_i; PetscFunctionBegin; bs = A->rmap->bs; bs2 = bs * bs; PetscCheck(row >= 0 && row < A->rmap->N, PETSC_COMM_SELF, PETSC_ERR_ARG_OUTOFRANGE, "Row %" PetscInt_FMT " out of range", row); bn = row / bs; /* Block number */ bp = row % bs; /* Block Position */ M = ai[bn + 1] - ai[bn]; *nz = bs * M; if (v) { *v = NULL; if (*nz) { PetscCall(PetscMalloc1(*nz, v)); for (i = 0; i < M; i++) { /* for each block in the block row */ v_i = *v + i * bs; aa_i = aa + bs2 * (ai[bn] + i); for (j = bp, k = 0; j < bs2; j += bs, k++) v_i[k] = aa_i[j]; } } } if (idx) { *idx = NULL; if (*nz) { PetscCall(PetscMalloc1(*nz, idx)); for (i = 0; i < M; i++) { /* for each block in the block row */ idx_i = *idx + i * bs; itmp = bs * aj[ai[bn] + i]; for (j = 0; j < bs; j++) idx_i[j] = itmp++; } } } PetscFunctionReturn(PETSC_SUCCESS); } PetscErrorCode MatGetRow_SeqBAIJ(Mat A, PetscInt row, PetscInt *nz, PetscInt **idx, PetscScalar **v) { Mat_SeqBAIJ *a = (Mat_SeqBAIJ *)A->data; PetscFunctionBegin; PetscCall(MatGetRow_SeqBAIJ_private(A, row, nz, idx, v, a->i, a->j, a->a)); PetscFunctionReturn(PETSC_SUCCESS); } PetscErrorCode MatRestoreRow_SeqBAIJ(Mat A, PetscInt row, PetscInt *nz, PetscInt **idx, PetscScalar **v) { PetscFunctionBegin; if (idx) PetscCall(PetscFree(*idx)); if (v) PetscCall(PetscFree(*v)); PetscFunctionReturn(PETSC_SUCCESS); } static PetscErrorCode MatTranspose_SeqBAIJ(Mat A, MatReuse reuse, Mat *B) { Mat_SeqBAIJ *a = (Mat_SeqBAIJ *)A->data, *at; Mat C; PetscInt i, j, k, *aj = a->j, *ai = a->i, bs = A->rmap->bs, mbs = a->mbs, nbs = a->nbs, *atfill; PetscInt bs2 = a->bs2, *ati, *atj, anzj, kr; MatScalar *ata, *aa = a->a; PetscFunctionBegin; if (reuse == MAT_REUSE_MATRIX) PetscCall(MatTransposeCheckNonzeroState_Private(A, *B)); PetscCall(PetscCalloc1(1 + nbs, &atfill)); if (reuse == MAT_INITIAL_MATRIX || reuse == MAT_INPLACE_MATRIX) { for (i = 0; i < ai[mbs]; i++) atfill[aj[i]] += 1; /* count num of non-zeros in row aj[i] */ PetscCall(MatCreate(PetscObjectComm((PetscObject)A), &C)); PetscCall(MatSetSizes(C, A->cmap->n, A->rmap->N, A->cmap->n, A->rmap->N)); PetscCall(MatSetType(C, ((PetscObject)A)->type_name)); PetscCall(MatSeqBAIJSetPreallocation(C, bs, 0, atfill)); at = (Mat_SeqBAIJ *)C->data; ati = at->i; for (i = 0; i < nbs; i++) at->ilen[i] = at->imax[i] = ati[i + 1] - ati[i]; } else { C = *B; at = (Mat_SeqBAIJ *)C->data; ati = at->i; } atj = at->j; ata = at->a; /* Copy ati into atfill so we have locations of the next free space in atj */ PetscCall(PetscArraycpy(atfill, ati, nbs)); /* Walk through A row-wise and mark nonzero entries of A^T. */ for (i = 0; i < mbs; i++) { anzj = ai[i + 1] - ai[i]; for (j = 0; j < anzj; j++) { atj[atfill[*aj]] = i; for (kr = 0; kr < bs; kr++) { for (k = 0; k < bs; k++) ata[bs2 * atfill[*aj] + k * bs + kr] = *aa++; } atfill[*aj++] += 1; } } PetscCall(MatAssemblyBegin(C, MAT_FINAL_ASSEMBLY)); PetscCall(MatAssemblyEnd(C, MAT_FINAL_ASSEMBLY)); /* Clean up temporary space and complete requests. */ PetscCall(PetscFree(atfill)); if (reuse == MAT_INITIAL_MATRIX || reuse == MAT_REUSE_MATRIX) { PetscCall(MatSetBlockSizes(C, A->cmap->bs, A->rmap->bs)); *B = C; } else { PetscCall(MatHeaderMerge(A, &C)); } PetscFunctionReturn(PETSC_SUCCESS); } static PetscErrorCode MatCompare_SeqBAIJ_Private(Mat A, Mat B, PetscReal tol, PetscBool *flg) { Mat_SeqBAIJ *a = (Mat_SeqBAIJ *)A->data, *b = (Mat_SeqBAIJ *)B->data; PetscFunctionBegin; /* If the matrix/block dimensions are not equal, or no of nonzeros or shift */ if (A->rmap->N != B->rmap->N || A->cmap->n != B->cmap->n || A->rmap->bs != B->rmap->bs || a->nz != b->nz) { *flg = PETSC_FALSE; PetscFunctionReturn(PETSC_SUCCESS); } /* if the a->i are the same */ PetscCall(PetscArraycmp(a->i, b->i, a->mbs + 1, flg)); if (!*flg) PetscFunctionReturn(PETSC_SUCCESS); /* if a->j are the same */ PetscCall(PetscArraycmp(a->j, b->j, a->nz, flg)); if (!*flg) PetscFunctionReturn(PETSC_SUCCESS); if (tol == 0.0) PetscCall(PetscArraycmp(a->a, b->a, a->nz * A->rmap->bs * A->rmap->bs, flg)); /* if a->a are the same */ else { *flg = PETSC_TRUE; for (PetscInt i = 0; (i < a->nz * A->rmap->bs * A->rmap->bs) && *flg; ++i) if (PetscAbsScalar(a->a[i] - b->a[i]) > tol) *flg = PETSC_FALSE; } PetscFunctionReturn(PETSC_SUCCESS); } static PetscErrorCode MatIsTranspose_SeqBAIJ(Mat A, Mat B, PetscReal tol, PetscBool *f) { Mat Btrans; PetscFunctionBegin; PetscCall(MatTranspose(A, MAT_INITIAL_MATRIX, &Btrans)); PetscCall(MatCompare_SeqBAIJ_Private(A, Btrans, tol, f)); PetscCall(MatDestroy(&Btrans)); PetscFunctionReturn(PETSC_SUCCESS); } static PetscErrorCode MatEqual_SeqBAIJ(Mat A, Mat B, PetscBool *flg) { PetscFunctionBegin; PetscCall(MatCompare_SeqBAIJ_Private(A, B, 0.0, flg)); PetscFunctionReturn(PETSC_SUCCESS); } /* Used for both SeqBAIJ and SeqSBAIJ matrices */ PetscErrorCode MatView_SeqBAIJ_Binary(Mat mat, PetscViewer viewer) { Mat_SeqBAIJ *A = (Mat_SeqBAIJ *)mat->data; PetscInt header[4], M, N, m, bs, nz, cnt, i, j, k, l; PetscInt *rowlens, *colidxs; PetscScalar *matvals; PetscFunctionBegin; PetscCall(PetscViewerSetUp(viewer)); M = mat->rmap->N; N = mat->cmap->N; m = mat->rmap->n; bs = mat->rmap->bs; nz = bs * bs * A->nz; /* write matrix header */ header[0] = MAT_FILE_CLASSID; header[1] = M; header[2] = N; header[3] = nz; PetscCall(PetscViewerBinaryWrite(viewer, header, 4, PETSC_INT)); /* store row lengths */ PetscCall(PetscMalloc1(m, &rowlens)); for (cnt = 0, i = 0; i < A->mbs; i++) for (j = 0; j < bs; j++) rowlens[cnt++] = bs * (A->i[i + 1] - A->i[i]); PetscCall(PetscViewerBinaryWrite(viewer, rowlens, m, PETSC_INT)); PetscCall(PetscFree(rowlens)); /* store column indices */ PetscCall(PetscMalloc1(nz, &colidxs)); for (cnt = 0, i = 0; i < A->mbs; i++) for (k = 0; k < bs; k++) for (j = A->i[i]; j < A->i[i + 1]; j++) for (l = 0; l < bs; l++) colidxs[cnt++] = bs * A->j[j] + l; PetscCheck(cnt == nz, PETSC_COMM_SELF, PETSC_ERR_LIB, "Internal PETSc error: cnt = %" PetscInt_FMT " nz = %" PetscInt_FMT, cnt, nz); PetscCall(PetscViewerBinaryWrite(viewer, colidxs, nz, PETSC_INT)); PetscCall(PetscFree(colidxs)); /* store nonzero values */ PetscCall(PetscMalloc1(nz, &matvals)); for (cnt = 0, i = 0; i < A->mbs; i++) for (k = 0; k < bs; k++) for (j = A->i[i]; j < A->i[i + 1]; j++) for (l = 0; l < bs; l++) matvals[cnt++] = A->a[bs * (bs * j + l) + k]; PetscCheck(cnt == nz, PETSC_COMM_SELF, PETSC_ERR_LIB, "Internal PETSc error: cnt = %" PetscInt_FMT " nz = %" PetscInt_FMT, cnt, nz); PetscCall(PetscViewerBinaryWrite(viewer, matvals, nz, PETSC_SCALAR)); PetscCall(PetscFree(matvals)); /* write block size option to the viewer's .info file */ PetscCall(MatView_Binary_BlockSizes(mat, viewer)); PetscFunctionReturn(PETSC_SUCCESS); } static PetscErrorCode MatView_SeqBAIJ_ASCII_structonly(Mat A, PetscViewer viewer) { Mat_SeqBAIJ *a = (Mat_SeqBAIJ *)A->data; PetscInt i, bs = A->rmap->bs, k; PetscFunctionBegin; PetscCall(PetscViewerASCIIUseTabs(viewer, PETSC_FALSE)); for (i = 0; i < a->mbs; i++) { PetscCall(PetscViewerASCIIPrintf(viewer, "row %" PetscInt_FMT "-%" PetscInt_FMT ":", i * bs, i * bs + bs - 1)); for (k = a->i[i]; k < a->i[i + 1]; k++) PetscCall(PetscViewerASCIIPrintf(viewer, " (%" PetscInt_FMT "-%" PetscInt_FMT ") ", bs * a->j[k], bs * a->j[k] + bs - 1)); PetscCall(PetscViewerASCIIPrintf(viewer, "\n")); } PetscCall(PetscViewerASCIIUseTabs(viewer, PETSC_TRUE)); PetscFunctionReturn(PETSC_SUCCESS); } static PetscErrorCode MatView_SeqBAIJ_ASCII(Mat A, PetscViewer viewer) { Mat_SeqBAIJ *a = (Mat_SeqBAIJ *)A->data; PetscInt i, j, bs = A->rmap->bs, k, l, bs2 = a->bs2; PetscViewerFormat format; PetscFunctionBegin; if (A->structure_only) { PetscCall(MatView_SeqBAIJ_ASCII_structonly(A, viewer)); PetscFunctionReturn(PETSC_SUCCESS); } PetscCall(PetscViewerGetFormat(viewer, &format)); if (format == PETSC_VIEWER_ASCII_INFO || format == PETSC_VIEWER_ASCII_INFO_DETAIL) { } else if (format == PETSC_VIEWER_ASCII_MATLAB) { const char *matname; Mat aij; PetscCall(MatConvert(A, MATSEQAIJ, MAT_INITIAL_MATRIX, &aij)); PetscCall(PetscObjectGetName((PetscObject)A, &matname)); PetscCall(PetscObjectSetName((PetscObject)aij, matname)); PetscCall(MatView(aij, viewer)); PetscCall(MatDestroy(&aij)); } else if (format == PETSC_VIEWER_ASCII_FACTOR_INFO) { PetscFunctionReturn(PETSC_SUCCESS); } else if (format == PETSC_VIEWER_ASCII_COMMON) { PetscCall(PetscViewerASCIIUseTabs(viewer, PETSC_FALSE)); for (i = 0; i < a->mbs; i++) { for (j = 0; j < bs; j++) { PetscCall(PetscViewerASCIIPrintf(viewer, "row %" PetscInt_FMT ":", i * bs + j)); for (k = a->i[i]; k < a->i[i + 1]; k++) { for (l = 0; l < bs; l++) { #if defined(PETSC_USE_COMPLEX) if (PetscImaginaryPart(a->a[bs2 * k + l * bs + j]) > 0.0 && PetscRealPart(a->a[bs2 * k + l * bs + j]) != 0.0) { PetscCall(PetscViewerASCIIPrintf(viewer, " (%" PetscInt_FMT ", %g + %gi) ", bs * a->j[k] + l, (double)PetscRealPart(a->a[bs2 * k + l * bs + j]), (double)PetscImaginaryPart(a->a[bs2 * k + l * bs + j]))); } else if (PetscImaginaryPart(a->a[bs2 * k + l * bs + j]) < 0.0 && PetscRealPart(a->a[bs2 * k + l * bs + j]) != 0.0) { PetscCall(PetscViewerASCIIPrintf(viewer, " (%" PetscInt_FMT ", %g - %gi) ", bs * a->j[k] + l, (double)PetscRealPart(a->a[bs2 * k + l * bs + j]), -(double)PetscImaginaryPart(a->a[bs2 * k + l * bs + j]))); } else if (PetscRealPart(a->a[bs2 * k + l * bs + j]) != 0.0) { PetscCall(PetscViewerASCIIPrintf(viewer, " (%" PetscInt_FMT ", %g) ", bs * a->j[k] + l, (double)PetscRealPart(a->a[bs2 * k + l * bs + j]))); } #else if (a->a[bs2 * k + l * bs + j] != 0.0) PetscCall(PetscViewerASCIIPrintf(viewer, " (%" PetscInt_FMT ", %g) ", bs * a->j[k] + l, (double)a->a[bs2 * k + l * bs + j])); #endif } } PetscCall(PetscViewerASCIIPrintf(viewer, "\n")); } } PetscCall(PetscViewerASCIIUseTabs(viewer, PETSC_TRUE)); } else { PetscCall(PetscViewerASCIIUseTabs(viewer, PETSC_FALSE)); for (i = 0; i < a->mbs; i++) { for (j = 0; j < bs; j++) { PetscCall(PetscViewerASCIIPrintf(viewer, "row %" PetscInt_FMT ":", i * bs + j)); for (k = a->i[i]; k < a->i[i + 1]; k++) { for (l = 0; l < bs; l++) { #if defined(PETSC_USE_COMPLEX) if (PetscImaginaryPart(a->a[bs2 * k + l * bs + j]) > 0.0) { PetscCall(PetscViewerASCIIPrintf(viewer, " (%" PetscInt_FMT ", %g + %g i) ", bs * a->j[k] + l, (double)PetscRealPart(a->a[bs2 * k + l * bs + j]), (double)PetscImaginaryPart(a->a[bs2 * k + l * bs + j]))); } else if (PetscImaginaryPart(a->a[bs2 * k + l * bs + j]) < 0.0) { PetscCall(PetscViewerASCIIPrintf(viewer, " (%" PetscInt_FMT ", %g - %g i) ", bs * a->j[k] + l, (double)PetscRealPart(a->a[bs2 * k + l * bs + j]), -(double)PetscImaginaryPart(a->a[bs2 * k + l * bs + j]))); } else { PetscCall(PetscViewerASCIIPrintf(viewer, " (%" PetscInt_FMT ", %g) ", bs * a->j[k] + l, (double)PetscRealPart(a->a[bs2 * k + l * bs + j]))); } #else PetscCall(PetscViewerASCIIPrintf(viewer, " (%" PetscInt_FMT ", %g) ", bs * a->j[k] + l, (double)a->a[bs2 * k + l * bs + j])); #endif } } PetscCall(PetscViewerASCIIPrintf(viewer, "\n")); } } PetscCall(PetscViewerASCIIUseTabs(viewer, PETSC_TRUE)); } PetscCall(PetscViewerFlush(viewer)); PetscFunctionReturn(PETSC_SUCCESS); } #include static PetscErrorCode MatView_SeqBAIJ_Draw_Zoom(PetscDraw draw, void *Aa) { Mat A = (Mat)Aa; Mat_SeqBAIJ *a = (Mat_SeqBAIJ *)A->data; PetscInt row, i, j, k, l, mbs = a->mbs, bs = A->rmap->bs, bs2 = a->bs2; PetscReal xl, yl, xr, yr, x_l, x_r, y_l, y_r; MatScalar *aa; PetscViewer viewer; PetscViewerFormat format; int color; PetscFunctionBegin; PetscCall(PetscObjectQuery((PetscObject)A, "Zoomviewer", (PetscObject *)&viewer)); PetscCall(PetscViewerGetFormat(viewer, &format)); PetscCall(PetscDrawGetCoordinates(draw, &xl, &yl, &xr, &yr)); /* loop over matrix elements drawing boxes */ if (format != PETSC_VIEWER_DRAW_CONTOUR) { PetscDrawCollectiveBegin(draw); /* Blue for negative, Cyan for zero and Red for positive */ color = PETSC_DRAW_BLUE; for (i = 0, row = 0; i < mbs; i++, row += bs) { for (j = a->i[i]; j < a->i[i + 1]; j++) { y_l = A->rmap->N - row - 1.0; y_r = y_l + 1.0; x_l = a->j[j] * bs; x_r = x_l + 1.0; aa = a->a + j * bs2; for (k = 0; k < bs; k++) { for (l = 0; l < bs; l++) { if (PetscRealPart(*aa++) >= 0.) continue; PetscCall(PetscDrawRectangle(draw, x_l + k, y_l - l, x_r + k, y_r - l, color, color, color, color)); } } } } color = PETSC_DRAW_CYAN; for (i = 0, row = 0; i < mbs; i++, row += bs) { for (j = a->i[i]; j < a->i[i + 1]; j++) { y_l = A->rmap->N - row - 1.0; y_r = y_l + 1.0; x_l = a->j[j] * bs; x_r = x_l + 1.0; aa = a->a + j * bs2; for (k = 0; k < bs; k++) { for (l = 0; l < bs; l++) { if (PetscRealPart(*aa++) != 0.) continue; PetscCall(PetscDrawRectangle(draw, x_l + k, y_l - l, x_r + k, y_r - l, color, color, color, color)); } } } } color = PETSC_DRAW_RED; for (i = 0, row = 0; i < mbs; i++, row += bs) { for (j = a->i[i]; j < a->i[i + 1]; j++) { y_l = A->rmap->N - row - 1.0; y_r = y_l + 1.0; x_l = a->j[j] * bs; x_r = x_l + 1.0; aa = a->a + j * bs2; for (k = 0; k < bs; k++) { for (l = 0; l < bs; l++) { if (PetscRealPart(*aa++) <= 0.) continue; PetscCall(PetscDrawRectangle(draw, x_l + k, y_l - l, x_r + k, y_r - l, color, color, color, color)); } } } } PetscDrawCollectiveEnd(draw); } else { /* use contour shading to indicate magnitude of values */ /* first determine max of all nonzero values */ PetscReal minv = 0.0, maxv = 0.0; PetscDraw popup; for (i = 0; i < a->nz * a->bs2; i++) { if (PetscAbsScalar(a->a[i]) > maxv) maxv = PetscAbsScalar(a->a[i]); } if (minv >= maxv) maxv = minv + PETSC_SMALL; PetscCall(PetscDrawGetPopup(draw, &popup)); PetscCall(PetscDrawScalePopup(popup, 0.0, maxv)); PetscDrawCollectiveBegin(draw); for (i = 0, row = 0; i < mbs; i++, row += bs) { for (j = a->i[i]; j < a->i[i + 1]; j++) { y_l = A->rmap->N - row - 1.0; y_r = y_l + 1.0; x_l = a->j[j] * bs; x_r = x_l + 1.0; aa = a->a + j * bs2; for (k = 0; k < bs; k++) { for (l = 0; l < bs; l++) { MatScalar v = *aa++; color = PetscDrawRealToColor(PetscAbsScalar(v), minv, maxv); PetscCall(PetscDrawRectangle(draw, x_l + k, y_l - l, x_r + k, y_r - l, color, color, color, color)); } } } } PetscDrawCollectiveEnd(draw); } PetscFunctionReturn(PETSC_SUCCESS); } static PetscErrorCode MatView_SeqBAIJ_Draw(Mat A, PetscViewer viewer) { PetscReal xl, yl, xr, yr, w, h; PetscDraw draw; PetscBool isnull; PetscFunctionBegin; PetscCall(PetscViewerDrawGetDraw(viewer, 0, &draw)); PetscCall(PetscDrawIsNull(draw, &isnull)); if (isnull) PetscFunctionReturn(PETSC_SUCCESS); xr = A->cmap->n; yr = A->rmap->N; h = yr / 10.0; w = xr / 10.0; xr += w; yr += h; xl = -w; yl = -h; PetscCall(PetscDrawSetCoordinates(draw, xl, yl, xr, yr)); PetscCall(PetscObjectCompose((PetscObject)A, "Zoomviewer", (PetscObject)viewer)); PetscCall(PetscDrawZoom(draw, MatView_SeqBAIJ_Draw_Zoom, A)); PetscCall(PetscObjectCompose((PetscObject)A, "Zoomviewer", NULL)); PetscCall(PetscDrawSave(draw)); PetscFunctionReturn(PETSC_SUCCESS); } PetscErrorCode MatView_SeqBAIJ(Mat A, PetscViewer viewer) { PetscBool isascii, isbinary, isdraw; PetscFunctionBegin; PetscCall(PetscObjectTypeCompare((PetscObject)viewer, PETSCVIEWERASCII, &isascii)); PetscCall(PetscObjectTypeCompare((PetscObject)viewer, PETSCVIEWERBINARY, &isbinary)); PetscCall(PetscObjectTypeCompare((PetscObject)viewer, PETSCVIEWERDRAW, &isdraw)); if (isascii) { PetscCall(MatView_SeqBAIJ_ASCII(A, viewer)); } else if (isbinary) { PetscCall(MatView_SeqBAIJ_Binary(A, viewer)); } else if (isdraw) { PetscCall(MatView_SeqBAIJ_Draw(A, viewer)); } else { Mat B; PetscCall(MatConvert(A, MATSEQAIJ, MAT_INITIAL_MATRIX, &B)); PetscCall(MatView(B, viewer)); PetscCall(MatDestroy(&B)); } PetscFunctionReturn(PETSC_SUCCESS); } PetscErrorCode MatGetValues_SeqBAIJ(Mat A, PetscInt m, const PetscInt im[], PetscInt n, const PetscInt in[], PetscScalar v[]) { Mat_SeqBAIJ *a = (Mat_SeqBAIJ *)A->data; PetscInt *rp, k, low, high, t, row, nrow, i, col, l, *aj = a->j; PetscInt *ai = a->i, *ailen = a->ilen; PetscInt brow, bcol, ridx, cidx, bs = A->rmap->bs, bs2 = a->bs2; MatScalar *ap, *aa = a->a; PetscFunctionBegin; for (k = 0; k < m; k++) { /* loop over rows */ row = im[k]; brow = row / bs; if (row < 0) { v += n; continue; } /* negative row */ PetscCheck(row < A->rmap->N, PETSC_COMM_SELF, PETSC_ERR_ARG_OUTOFRANGE, "Row %" PetscInt_FMT " too large", row); rp = PetscSafePointerPlusOffset(aj, ai[brow]); ap = PetscSafePointerPlusOffset(aa, bs2 * ai[brow]); nrow = ailen[brow]; for (l = 0; l < n; l++) { /* loop over columns */ if (in[l] < 0) { v++; continue; } /* negative column */ PetscCheck(in[l] < A->cmap->n, PETSC_COMM_SELF, PETSC_ERR_ARG_OUTOFRANGE, "Column %" PetscInt_FMT " too large", in[l]); col = in[l]; bcol = col / bs; cidx = col % bs; ridx = row % bs; high = nrow; low = 0; /* assume unsorted */ while (high - low > 5) { t = (low + high) / 2; if (rp[t] > bcol) high = t; else low = t; } for (i = low; i < high; i++) { if (rp[i] > bcol) break; if (rp[i] == bcol) { *v++ = ap[bs2 * i + bs * cidx + ridx]; goto finished; } } *v++ = 0.0; finished:; } } PetscFunctionReturn(PETSC_SUCCESS); } PetscErrorCode MatSetValuesBlocked_SeqBAIJ(Mat A, PetscInt m, const PetscInt im[], PetscInt n, const PetscInt in[], const PetscScalar v[], InsertMode is) { Mat_SeqBAIJ *a = (Mat_SeqBAIJ *)A->data; PetscInt *rp, k, low, high, t, ii, jj, row, nrow, i, col, l, rmax, N, lastcol = -1; PetscInt *imax = a->imax, *ai = a->i, *ailen = a->ilen; PetscInt *aj = a->j, nonew = a->nonew, bs2 = a->bs2, bs = A->rmap->bs, stepval; PetscBool roworiented = a->roworiented; const PetscScalar *value = v; MatScalar *ap = NULL, *aa = a->a, *bap; PetscFunctionBegin; if (roworiented) { stepval = (n - 1) * bs; } else { stepval = (m - 1) * bs; } for (k = 0; k < m; k++) { /* loop over added rows */ row = im[k]; if (row < 0) continue; PetscCheck(row < a->mbs, PETSC_COMM_SELF, PETSC_ERR_ARG_OUTOFRANGE, "Block row index too large %" PetscInt_FMT " max %" PetscInt_FMT, row, a->mbs - 1); rp = aj + ai[row]; if (!A->structure_only) ap = aa + bs2 * ai[row]; rmax = imax[row]; nrow = ailen[row]; low = 0; high = nrow; for (l = 0; l < n; l++) { /* loop over added columns */ if (in[l] < 0) continue; PetscCheck(in[l] < a->nbs, PETSC_COMM_SELF, PETSC_ERR_ARG_OUTOFRANGE, "Block column index too large %" PetscInt_FMT " max %" PetscInt_FMT, in[l], a->nbs - 1); col = in[l]; if (!A->structure_only) { if (roworiented) { value = v + (k * (stepval + bs) + l) * bs; } else { value = v + (l * (stepval + bs) + k) * bs; } } if (col <= lastcol) low = 0; else high = nrow; lastcol = col; while (high - low > 7) { t = (low + high) / 2; if (rp[t] > col) high = t; else low = t; } for (i = low; i < high; i++) { if (rp[i] > col) break; if (rp[i] == col) { if (A->structure_only) goto noinsert2; bap = ap + bs2 * i; if (roworiented) { if (is == ADD_VALUES) { for (ii = 0; ii < bs; ii++, value += stepval) { for (jj = ii; jj < bs2; jj += bs) bap[jj] += *value++; } } else { for (ii = 0; ii < bs; ii++, value += stepval) { for (jj = ii; jj < bs2; jj += bs) bap[jj] = *value++; } } } else { if (is == ADD_VALUES) { for (ii = 0; ii < bs; ii++, value += bs + stepval) { for (jj = 0; jj < bs; jj++) bap[jj] += value[jj]; bap += bs; } } else { for (ii = 0; ii < bs; ii++, value += bs + stepval) { for (jj = 0; jj < bs; jj++) bap[jj] = value[jj]; bap += bs; } } } goto noinsert2; } } if (nonew == 1) goto noinsert2; PetscCheck(nonew != -1, PETSC_COMM_SELF, PETSC_ERR_ARG_OUTOFRANGE, "Inserting a new blocked index new nonzero block (%" PetscInt_FMT ", %" PetscInt_FMT ") in the matrix", row, col); if (A->structure_only) { MatSeqXAIJReallocateAIJ_structure_only(A, a->mbs, bs2, nrow, row, col, rmax, ai, aj, rp, imax, nonew, MatScalar); } else { MatSeqXAIJReallocateAIJ(A, a->mbs, bs2, nrow, row, col, rmax, aa, ai, aj, rp, ap, imax, nonew, MatScalar); } N = nrow++ - 1; high++; /* shift up all the later entries in this row */ PetscCall(PetscArraymove(rp + i + 1, rp + i, N - i + 1)); rp[i] = col; if (!A->structure_only) { PetscCall(PetscArraymove(ap + bs2 * (i + 1), ap + bs2 * i, bs2 * (N - i + 1))); bap = ap + bs2 * i; if (roworiented) { for (ii = 0; ii < bs; ii++, value += stepval) { for (jj = ii; jj < bs2; jj += bs) bap[jj] = *value++; } } else { for (ii = 0; ii < bs; ii++, value += stepval) { for (jj = 0; jj < bs; jj++) *bap++ = *value++; } } } noinsert2:; low = i; } ailen[row] = nrow; } PetscFunctionReturn(PETSC_SUCCESS); } PetscErrorCode MatAssemblyEnd_SeqBAIJ(Mat A, MatAssemblyType mode) { Mat_SeqBAIJ *a = (Mat_SeqBAIJ *)A->data; PetscInt fshift = 0, i, *ai = a->i, *aj = a->j, *imax = a->imax; PetscInt m = A->rmap->N, *ip, N, *ailen = a->ilen; PetscInt mbs = a->mbs, bs2 = a->bs2, rmax = 0; MatScalar *aa = a->a, *ap; PetscReal ratio = 0.6; PetscFunctionBegin; if (mode == MAT_FLUSH_ASSEMBLY || (A->was_assembled && A->ass_nonzerostate == A->nonzerostate)) PetscFunctionReturn(PETSC_SUCCESS); if (m) rmax = ailen[0]; for (i = 1; i < mbs; i++) { /* move each row back by the amount of empty slots (fshift) before it*/ fshift += imax[i - 1] - ailen[i - 1]; rmax = PetscMax(rmax, ailen[i]); if (fshift) { ip = aj + ai[i]; ap = aa + bs2 * ai[i]; N = ailen[i]; PetscCall(PetscArraymove(ip - fshift, ip, N)); if (!A->structure_only) PetscCall(PetscArraymove(ap - bs2 * fshift, ap, bs2 * N)); } ai[i] = ai[i - 1] + ailen[i - 1]; } if (mbs) { fshift += imax[mbs - 1] - ailen[mbs - 1]; ai[mbs] = ai[mbs - 1] + ailen[mbs - 1]; } /* reset ilen and imax for each row */ a->nonzerorowcnt = 0; if (A->structure_only) { PetscCall(PetscFree2(a->imax, a->ilen)); } else { /* !A->structure_only */ for (i = 0; i < mbs; i++) { ailen[i] = imax[i] = ai[i + 1] - ai[i]; a->nonzerorowcnt += ((ai[i + 1] - ai[i]) > 0); } } a->nz = ai[mbs]; /* diagonals may have moved, so kill the diagonal pointers */ a->idiagvalid = PETSC_FALSE; if (fshift) PetscCheck(a->nounused != -1, PETSC_COMM_SELF, PETSC_ERR_PLIB, "Unused space detected in matrix: %" PetscInt_FMT " X %" PetscInt_FMT " block size %" PetscInt_FMT ", %" PetscInt_FMT " unneeded", m, A->cmap->n, A->rmap->bs, fshift * bs2); PetscCall(PetscInfo(A, "Matrix size: %" PetscInt_FMT " X %" PetscInt_FMT ", block size %" PetscInt_FMT "; storage space: %" PetscInt_FMT " unneeded, %" PetscInt_FMT " used\n", m, A->cmap->n, A->rmap->bs, fshift * bs2, a->nz * bs2)); PetscCall(PetscInfo(A, "Number of mallocs during MatSetValues is %" PetscInt_FMT "\n", a->reallocs)); PetscCall(PetscInfo(A, "Most nonzeros blocks in any row is %" PetscInt_FMT "\n", rmax)); A->info.mallocs += a->reallocs; a->reallocs = 0; A->info.nz_unneeded = (PetscReal)fshift * bs2; a->rmax = rmax; if (!A->structure_only) PetscCall(MatCheckCompressedRow(A, a->nonzerorowcnt, &a->compressedrow, a->i, mbs, ratio)); PetscFunctionReturn(PETSC_SUCCESS); } /* This function returns an array of flags which indicate the locations of contiguous blocks that should be zeroed. for eg: if bs = 3 and is = [0,1,2,3,5,6,7,8,9] then the resulting sizes = [3,1,1,3,1] corresponding to sets [(0,1,2),(3),(5),(6,7,8),(9)] Assume: sizes should be long enough to hold all the values. */ static PetscErrorCode MatZeroRows_SeqBAIJ_Check_Blocks(PetscInt idx[], PetscInt n, PetscInt bs, PetscInt sizes[], PetscInt *bs_max) { PetscInt j = 0; PetscFunctionBegin; for (PetscInt i = 0; i < n; j++) { PetscInt row = idx[i]; if (row % bs != 0) { /* Not the beginning of a block */ sizes[j] = 1; i++; } else if (i + bs > n) { /* complete block doesn't exist (at idx end) */ sizes[j] = 1; /* Also makes sure at least 'bs' values exist for next else */ i++; } else { /* Beginning of the block, so check if the complete block exists */ PetscBool flg = PETSC_TRUE; for (PetscInt k = 1; k < bs; k++) { if (row + k != idx[i + k]) { /* break in the block */ flg = PETSC_FALSE; break; } } if (flg) { /* No break in the bs */ sizes[j] = bs; i += bs; } else { sizes[j] = 1; i++; } } } *bs_max = j; PetscFunctionReturn(PETSC_SUCCESS); } PetscErrorCode MatZeroRows_SeqBAIJ(Mat A, PetscInt is_n, const PetscInt is_idx[], PetscScalar diag, Vec x, Vec b) { Mat_SeqBAIJ *baij = (Mat_SeqBAIJ *)A->data; PetscInt i, j, k, count, *rows; PetscInt bs = A->rmap->bs, bs2 = baij->bs2, *sizes, row, bs_max; PetscScalar zero = 0.0; MatScalar *aa; const PetscScalar *xx; PetscScalar *bb; PetscFunctionBegin; /* fix right-hand side if needed */ if (x && b) { PetscCall(VecGetArrayRead(x, &xx)); PetscCall(VecGetArray(b, &bb)); for (i = 0; i < is_n; i++) bb[is_idx[i]] = diag * xx[is_idx[i]]; PetscCall(VecRestoreArrayRead(x, &xx)); PetscCall(VecRestoreArray(b, &bb)); } /* Make a copy of the IS and sort it */ /* allocate memory for rows,sizes */ PetscCall(PetscMalloc2(is_n, &rows, 2 * is_n, &sizes)); /* copy IS values to rows, and sort them */ for (i = 0; i < is_n; i++) rows[i] = is_idx[i]; PetscCall(PetscSortInt(is_n, rows)); if (baij->keepnonzeropattern) { for (i = 0; i < is_n; i++) sizes[i] = 1; bs_max = is_n; } else { PetscCall(MatZeroRows_SeqBAIJ_Check_Blocks(rows, is_n, bs, sizes, &bs_max)); A->nonzerostate++; } for (i = 0, j = 0; i < bs_max; j += sizes[i], i++) { row = rows[j]; PetscCheck(row >= 0 && row <= A->rmap->N, PETSC_COMM_SELF, PETSC_ERR_ARG_OUTOFRANGE, "row %" PetscInt_FMT " out of range", row); count = (baij->i[row / bs + 1] - baij->i[row / bs]) * bs; aa = baij->a + baij->i[row / bs] * bs2 + (row % bs); if (sizes[i] == bs && !baij->keepnonzeropattern) { if (diag != (PetscScalar)0.0) { if (baij->ilen[row / bs] > 0) { baij->ilen[row / bs] = 1; baij->j[baij->i[row / bs]] = row / bs; PetscCall(PetscArrayzero(aa, count * bs)); } /* Now insert all the diagonal values for this bs */ for (k = 0; k < bs; k++) PetscUseTypeMethod(A, setvalues, 1, rows + j + k, 1, rows + j + k, &diag, INSERT_VALUES); } else { /* (diag == 0.0) */ baij->ilen[row / bs] = 0; } /* end (diag == 0.0) */ } else { /* (sizes[i] != bs) */ PetscAssert(sizes[i] == 1, PETSC_COMM_SELF, PETSC_ERR_PLIB, "Internal Error. Value should be 1"); for (k = 0; k < count; k++) { aa[0] = zero; aa += bs; } if (diag != (PetscScalar)0.0) PetscUseTypeMethod(A, setvalues, 1, rows + j, 1, rows + j, &diag, INSERT_VALUES); } } PetscCall(PetscFree2(rows, sizes)); PetscCall(MatAssemblyEnd_SeqBAIJ(A, MAT_FINAL_ASSEMBLY)); PetscFunctionReturn(PETSC_SUCCESS); } static PetscErrorCode MatZeroRowsColumns_SeqBAIJ(Mat A, PetscInt is_n, const PetscInt is_idx[], PetscScalar diag, Vec x, Vec b) { Mat_SeqBAIJ *baij = (Mat_SeqBAIJ *)A->data; PetscInt i, j, k, count; PetscInt bs = A->rmap->bs, bs2 = baij->bs2, row, col; PetscScalar zero = 0.0; MatScalar *aa; const PetscScalar *xx; PetscScalar *bb; PetscBool *zeroed, vecs = PETSC_FALSE; PetscFunctionBegin; /* fix right-hand side if needed */ if (x && b) { PetscCall(VecGetArrayRead(x, &xx)); PetscCall(VecGetArray(b, &bb)); vecs = PETSC_TRUE; } /* zero the columns */ PetscCall(PetscCalloc1(A->rmap->n, &zeroed)); for (i = 0; i < is_n; i++) { PetscCheck(is_idx[i] >= 0 && is_idx[i] < A->rmap->N, PETSC_COMM_SELF, PETSC_ERR_ARG_OUTOFRANGE, "row %" PetscInt_FMT " out of range", is_idx[i]); zeroed[is_idx[i]] = PETSC_TRUE; } for (i = 0; i < A->rmap->N; i++) { if (!zeroed[i]) { row = i / bs; for (j = baij->i[row]; j < baij->i[row + 1]; j++) { for (k = 0; k < bs; k++) { col = bs * baij->j[j] + k; if (zeroed[col]) { aa = baij->a + j * bs2 + (i % bs) + bs * k; if (vecs) bb[i] -= aa[0] * xx[col]; aa[0] = 0.0; } } } } else if (vecs) bb[i] = diag * xx[i]; } PetscCall(PetscFree(zeroed)); if (vecs) { PetscCall(VecRestoreArrayRead(x, &xx)); PetscCall(VecRestoreArray(b, &bb)); } /* zero the rows */ for (i = 0; i < is_n; i++) { row = is_idx[i]; count = (baij->i[row / bs + 1] - baij->i[row / bs]) * bs; aa = baij->a + baij->i[row / bs] * bs2 + (row % bs); for (k = 0; k < count; k++) { aa[0] = zero; aa += bs; } if (diag != (PetscScalar)0.0) PetscUseTypeMethod(A, setvalues, 1, &row, 1, &row, &diag, INSERT_VALUES); } PetscCall(MatAssemblyEnd_SeqBAIJ(A, MAT_FINAL_ASSEMBLY)); PetscFunctionReturn(PETSC_SUCCESS); } PetscErrorCode MatSetValues_SeqBAIJ(Mat A, PetscInt m, const PetscInt im[], PetscInt n, const PetscInt in[], const PetscScalar v[], InsertMode is) { Mat_SeqBAIJ *a = (Mat_SeqBAIJ *)A->data; PetscInt *rp, k, low, high, t, ii, row, nrow, i, col, l, rmax, N, lastcol = -1; PetscInt *imax = a->imax, *ai = a->i, *ailen = a->ilen; PetscInt *aj = a->j, nonew = a->nonew, bs = A->rmap->bs, brow, bcol; PetscInt ridx, cidx, bs2 = a->bs2; PetscBool roworiented = a->roworiented; MatScalar *ap = NULL, value = 0.0, *aa = a->a, *bap; PetscFunctionBegin; for (k = 0; k < m; k++) { /* loop over added rows */ row = im[k]; brow = row / bs; if (row < 0) continue; PetscCheck(row < A->rmap->N, PETSC_COMM_SELF, PETSC_ERR_ARG_OUTOFRANGE, "Row too large: row %" PetscInt_FMT " max %" PetscInt_FMT, row, A->rmap->N - 1); rp = PetscSafePointerPlusOffset(aj, ai[brow]); if (!A->structure_only) ap = PetscSafePointerPlusOffset(aa, bs2 * ai[brow]); rmax = imax[brow]; nrow = ailen[brow]; low = 0; high = nrow; for (l = 0; l < n; l++) { /* loop over added columns */ if (in[l] < 0) continue; PetscCheck(in[l] < A->cmap->n, PETSC_COMM_SELF, PETSC_ERR_ARG_OUTOFRANGE, "Column too large: col %" PetscInt_FMT " max %" PetscInt_FMT, in[l], A->cmap->n - 1); col = in[l]; bcol = col / bs; ridx = row % bs; cidx = col % bs; if (!A->structure_only) { if (roworiented) { value = v[l + k * n]; } else { value = v[k + l * m]; } } if (col <= lastcol) low = 0; else high = nrow; lastcol = col; while (high - low > 7) { t = (low + high) / 2; if (rp[t] > bcol) high = t; else low = t; } for (i = low; i < high; i++) { if (rp[i] > bcol) break; if (rp[i] == bcol) { bap = PetscSafePointerPlusOffset(ap, bs2 * i + bs * cidx + ridx); if (!A->structure_only) { if (is == ADD_VALUES) *bap += value; else *bap = value; } goto noinsert1; } } if (nonew == 1) goto noinsert1; PetscCheck(nonew != -1, PETSC_COMM_SELF, PETSC_ERR_ARG_OUTOFRANGE, "Inserting a new nonzero (%" PetscInt_FMT ", %" PetscInt_FMT ") in the matrix", row, col); if (A->structure_only) { MatSeqXAIJReallocateAIJ_structure_only(A, a->mbs, bs2, nrow, brow, bcol, rmax, ai, aj, rp, imax, nonew, MatScalar); } else { MatSeqXAIJReallocateAIJ(A, a->mbs, bs2, nrow, brow, bcol, rmax, aa, ai, aj, rp, ap, imax, nonew, MatScalar); } N = nrow++ - 1; high++; /* shift up all the later entries in this row */ PetscCall(PetscArraymove(rp + i + 1, rp + i, N - i + 1)); rp[i] = bcol; if (!A->structure_only) { PetscCall(PetscArraymove(ap + bs2 * (i + 1), ap + bs2 * i, bs2 * (N - i + 1))); PetscCall(PetscArrayzero(ap + bs2 * i, bs2)); ap[bs2 * i + bs * cidx + ridx] = value; } a->nz++; noinsert1:; low = i; } ailen[brow] = nrow; } PetscFunctionReturn(PETSC_SUCCESS); } static PetscErrorCode MatILUFactor_SeqBAIJ(Mat inA, IS row, IS col, const MatFactorInfo *info) { Mat_SeqBAIJ *a = (Mat_SeqBAIJ *)inA->data; Mat outA; PetscBool row_identity, col_identity; PetscFunctionBegin; PetscCheck(info->levels == 0, PETSC_COMM_SELF, PETSC_ERR_SUP, "Only levels = 0 supported for in-place ILU"); PetscCall(ISIdentity(row, &row_identity)); PetscCall(ISIdentity(col, &col_identity)); PetscCheck(row_identity && col_identity, PETSC_COMM_SELF, PETSC_ERR_ARG_WRONG, "Row and column permutations must be identity for in-place ILU"); outA = inA; inA->factortype = MAT_FACTOR_LU; PetscCall(PetscFree(inA->solvertype)); PetscCall(PetscStrallocpy(MATSOLVERPETSC, &inA->solvertype)); PetscCall(PetscObjectReference((PetscObject)row)); PetscCall(ISDestroy(&a->row)); a->row = row; PetscCall(PetscObjectReference((PetscObject)col)); PetscCall(ISDestroy(&a->col)); a->col = col; /* Create the invert permutation so that it can be used in MatLUFactorNumeric() */ PetscCall(ISDestroy(&a->icol)); PetscCall(ISInvertPermutation(col, PETSC_DECIDE, &a->icol)); PetscCall(MatSeqBAIJSetNumericFactorization_inplace(inA, (PetscBool)(row_identity && col_identity))); if (!a->solve_work) PetscCall(PetscMalloc1(inA->rmap->N + inA->rmap->bs, &a->solve_work)); PetscCall(MatLUFactorNumeric(outA, inA, info)); PetscFunctionReturn(PETSC_SUCCESS); } static PetscErrorCode MatSeqBAIJSetColumnIndices_SeqBAIJ(Mat mat, const PetscInt *indices) { Mat_SeqBAIJ *baij = (Mat_SeqBAIJ *)mat->data; PetscFunctionBegin; baij->nz = baij->maxnz; PetscCall(PetscArraycpy(baij->j, indices, baij->nz)); PetscCall(PetscArraycpy(baij->ilen, baij->imax, baij->mbs)); PetscFunctionReturn(PETSC_SUCCESS); } /*@ MatSeqBAIJSetColumnIndices - Set the column indices for all the block rows in the matrix. Input Parameters: + mat - the `MATSEQBAIJ` matrix - indices - the block column indices Level: advanced Notes: This can be called if you have precomputed the nonzero structure of the matrix and want to provide it to the matrix object to improve the performance of the `MatSetValues()` operation. You MUST have set the correct numbers of nonzeros per row in the call to `MatCreateSeqBAIJ()`, and the columns indices MUST be sorted. MUST be called before any calls to `MatSetValues()` .seealso: [](ch_matrices), `Mat`, `MATSEQBAIJ`, `MatSetValues()` @*/ PetscErrorCode MatSeqBAIJSetColumnIndices(Mat mat, PetscInt *indices) { PetscFunctionBegin; PetscValidHeaderSpecific(mat, MAT_CLASSID, 1); PetscAssertPointer(indices, 2); PetscUseMethod(mat, "MatSeqBAIJSetColumnIndices_C", (Mat, const PetscInt *), (mat, (const PetscInt *)indices)); PetscFunctionReturn(PETSC_SUCCESS); } static PetscErrorCode MatGetRowMaxAbs_SeqBAIJ(Mat A, Vec v, PetscInt idx[]) { Mat_SeqBAIJ *a = (Mat_SeqBAIJ *)A->data; PetscInt i, j, n, row, bs, *ai, *aj, mbs; PetscReal atmp; PetscScalar *x, zero = 0.0; MatScalar *aa; PetscInt ncols, brow, krow, kcol; PetscFunctionBegin; PetscCheck(!A->factortype, PETSC_COMM_SELF, PETSC_ERR_ARG_WRONGSTATE, "Not for factored matrix"); bs = A->rmap->bs; aa = a->a; ai = a->i; aj = a->j; mbs = a->mbs; PetscCall(VecSet(v, zero)); PetscCall(VecGetArray(v, &x)); PetscCall(VecGetLocalSize(v, &n)); PetscCheck(n == A->rmap->N, PETSC_COMM_SELF, PETSC_ERR_ARG_SIZ, "Nonconforming matrix and vector"); for (i = 0; i < mbs; i++) { ncols = ai[1] - ai[0]; ai++; brow = bs * i; for (j = 0; j < ncols; j++) { for (kcol = 0; kcol < bs; kcol++) { for (krow = 0; krow < bs; krow++) { atmp = PetscAbsScalar(*aa); aa++; row = brow + krow; /* row index */ if (PetscAbsScalar(x[row]) < atmp) { x[row] = atmp; if (idx) idx[row] = bs * (*aj) + kcol; } } } aj++; } } PetscCall(VecRestoreArray(v, &x)); PetscFunctionReturn(PETSC_SUCCESS); } static PetscErrorCode MatGetRowSumAbs_SeqBAIJ(Mat A, Vec v) { Mat_SeqBAIJ *a = (Mat_SeqBAIJ *)A->data; PetscInt i, j, n, row, bs, *ai, mbs; PetscReal atmp; PetscScalar *x, zero = 0.0; MatScalar *aa; PetscInt ncols, brow, krow, kcol; PetscFunctionBegin; PetscCheck(!A->factortype, PETSC_COMM_SELF, PETSC_ERR_ARG_WRONGSTATE, "Not for factored matrix"); bs = A->rmap->bs; aa = a->a; ai = a->i; mbs = a->mbs; PetscCall(VecSet(v, zero)); PetscCall(VecGetArrayWrite(v, &x)); PetscCall(VecGetLocalSize(v, &n)); PetscCheck(n == A->rmap->N, PETSC_COMM_SELF, PETSC_ERR_ARG_SIZ, "Nonconforming matrix and vector"); for (i = 0; i < mbs; i++) { ncols = ai[1] - ai[0]; ai++; brow = bs * i; for (j = 0; j < ncols; j++) { for (kcol = 0; kcol < bs; kcol++) { for (krow = 0; krow < bs; krow++) { atmp = PetscAbsScalar(*aa); aa++; row = brow + krow; /* row index */ x[row] += atmp; } } } } PetscCall(VecRestoreArrayWrite(v, &x)); PetscFunctionReturn(PETSC_SUCCESS); } static PetscErrorCode MatCopy_SeqBAIJ(Mat A, Mat B, MatStructure str) { PetscFunctionBegin; /* If the two matrices have the same copy implementation, use fast copy. */ if (str == SAME_NONZERO_PATTERN && (A->ops->copy == B->ops->copy)) { Mat_SeqBAIJ *a = (Mat_SeqBAIJ *)A->data; Mat_SeqBAIJ *b = (Mat_SeqBAIJ *)B->data; PetscInt ambs = a->mbs, bmbs = b->mbs, abs = A->rmap->bs, bbs = B->rmap->bs, bs2 = abs * abs; PetscCheck(a->i[ambs] == b->i[bmbs], PETSC_COMM_SELF, PETSC_ERR_ARG_INCOMP, "Number of nonzero blocks in matrices A %" PetscInt_FMT " and B %" PetscInt_FMT " are different", a->i[ambs], b->i[bmbs]); PetscCheck(abs == bbs, PETSC_COMM_SELF, PETSC_ERR_ARG_INCOMP, "Block size A %" PetscInt_FMT " and B %" PetscInt_FMT " are different", abs, bbs); PetscCall(PetscArraycpy(b->a, a->a, bs2 * a->i[ambs])); PetscCall(PetscObjectStateIncrease((PetscObject)B)); } else { PetscCall(MatCopy_Basic(A, B, str)); } PetscFunctionReturn(PETSC_SUCCESS); } static PetscErrorCode MatSeqBAIJGetArray_SeqBAIJ(Mat A, PetscScalar *array[]) { Mat_SeqBAIJ *a = (Mat_SeqBAIJ *)A->data; PetscFunctionBegin; *array = a->a; PetscFunctionReturn(PETSC_SUCCESS); } static PetscErrorCode MatSeqBAIJRestoreArray_SeqBAIJ(Mat A, PetscScalar *array[]) { PetscFunctionBegin; *array = NULL; PetscFunctionReturn(PETSC_SUCCESS); } PetscErrorCode MatAXPYGetPreallocation_SeqBAIJ(Mat Y, Mat X, PetscInt *nnz) { PetscInt bs = Y->rmap->bs, mbs = Y->rmap->N / bs; Mat_SeqBAIJ *x = (Mat_SeqBAIJ *)X->data; Mat_SeqBAIJ *y = (Mat_SeqBAIJ *)Y->data; PetscFunctionBegin; /* Set the number of nonzeros in the new matrix */ PetscCall(MatAXPYGetPreallocation_SeqX_private(mbs, x->i, x->j, y->i, y->j, nnz)); PetscFunctionReturn(PETSC_SUCCESS); } PetscErrorCode MatAXPY_SeqBAIJ(Mat Y, PetscScalar a, Mat X, MatStructure str) { Mat_SeqBAIJ *x = (Mat_SeqBAIJ *)X->data, *y = (Mat_SeqBAIJ *)Y->data; PetscInt bs = Y->rmap->bs, bs2 = bs * bs; PetscBLASInt one = 1; PetscFunctionBegin; if (str == UNKNOWN_NONZERO_PATTERN || (PetscDefined(USE_DEBUG) && str == SAME_NONZERO_PATTERN)) { PetscBool e = x->nz == y->nz && x->mbs == y->mbs && bs == X->rmap->bs ? PETSC_TRUE : PETSC_FALSE; if (e) { PetscCall(PetscArraycmp(x->i, y->i, x->mbs + 1, &e)); if (e) { PetscCall(PetscArraycmp(x->j, y->j, x->i[x->mbs], &e)); if (e) str = SAME_NONZERO_PATTERN; } } if (!e) PetscCheck(str != SAME_NONZERO_PATTERN, PETSC_COMM_SELF, PETSC_ERR_ARG_WRONG, "MatStructure is not SAME_NONZERO_PATTERN"); } if (str == SAME_NONZERO_PATTERN) { PetscScalar alpha = a; PetscBLASInt bnz; PetscCall(PetscBLASIntCast(x->nz * bs2, &bnz)); PetscCallBLAS("BLASaxpy", BLASaxpy_(&bnz, &alpha, x->a, &one, y->a, &one)); PetscCall(PetscObjectStateIncrease((PetscObject)Y)); } else if (str == SUBSET_NONZERO_PATTERN) { /* nonzeros of X is a subset of Y's */ PetscCall(MatAXPY_Basic(Y, a, X, str)); } else { Mat B; PetscInt *nnz; PetscCheck(bs == X->rmap->bs, PETSC_COMM_SELF, PETSC_ERR_ARG_SIZ, "Matrices must have same block size"); PetscCall(PetscMalloc1(Y->rmap->N, &nnz)); PetscCall(MatCreate(PetscObjectComm((PetscObject)Y), &B)); PetscCall(PetscObjectSetName((PetscObject)B, ((PetscObject)Y)->name)); PetscCall(MatSetSizes(B, Y->rmap->n, Y->cmap->n, Y->rmap->N, Y->cmap->N)); PetscCall(MatSetBlockSizesFromMats(B, Y, Y)); PetscCall(MatSetType(B, (MatType)((PetscObject)Y)->type_name)); PetscCall(MatAXPYGetPreallocation_SeqBAIJ(Y, X, nnz)); PetscCall(MatSeqBAIJSetPreallocation(B, bs, 0, nnz)); PetscCall(MatAXPY_BasicWithPreallocation(B, Y, a, X, str)); PetscCall(MatHeaderMerge(Y, &B)); PetscCall(PetscFree(nnz)); } PetscFunctionReturn(PETSC_SUCCESS); } PETSC_INTERN PetscErrorCode MatConjugate_SeqBAIJ(Mat A) { Mat_SeqBAIJ *a = (Mat_SeqBAIJ *)A->data; PetscInt i, nz = a->bs2 * a->i[a->mbs]; MatScalar *aa = a->a; PetscFunctionBegin; for (i = 0; i < nz; i++) aa[i] = PetscConj(aa[i]); PetscFunctionReturn(PETSC_SUCCESS); } static PetscErrorCode MatRealPart_SeqBAIJ(Mat A) { #if PetscDefined(USE_COMPLEX) Mat_SeqBAIJ *a = (Mat_SeqBAIJ *)A->data; PetscInt i, nz = a->bs2 * a->i[a->mbs]; MatScalar *aa = a->a; PetscFunctionBegin; for (i = 0; i < nz; i++) aa[i] = PetscRealPart(aa[i]); PetscFunctionReturn(PETSC_SUCCESS); #else (void)A; return PETSC_SUCCESS; #endif } static PetscErrorCode MatImaginaryPart_SeqBAIJ(Mat A) { #if PetscDefined(USE_COMPLEX) Mat_SeqBAIJ *a = (Mat_SeqBAIJ *)A->data; PetscInt i, nz = a->bs2 * a->i[a->mbs]; MatScalar *aa = a->a; PetscFunctionBegin; for (i = 0; i < nz; i++) aa[i] = PetscImaginaryPart(aa[i]); PetscFunctionReturn(PETSC_SUCCESS); #else (void)A; return PETSC_SUCCESS; #endif } /* Code almost identical to MatGetColumnIJ_SeqAIJ() should share common code */ static PetscErrorCode MatGetColumnIJ_SeqBAIJ(Mat A, PetscInt oshift, PetscBool symmetric, PetscBool inodecompressed, PetscInt *nn, const PetscInt *ia[], const PetscInt *ja[], PetscBool *done) { Mat_SeqBAIJ *a = (Mat_SeqBAIJ *)A->data; PetscInt bs = A->rmap->bs, i, *collengths, *cia, *cja, n = A->cmap->n / bs, m = A->rmap->n / bs; PetscInt nz = a->i[m], row, *jj, mr, col; PetscFunctionBegin; *nn = n; if (!ia) PetscFunctionReturn(PETSC_SUCCESS); PetscCheck(!symmetric, PETSC_COMM_SELF, PETSC_ERR_SUP, "Not for BAIJ matrices"); PetscCall(PetscCalloc1(n, &collengths)); PetscCall(PetscMalloc1(n + 1, &cia)); PetscCall(PetscMalloc1(nz, &cja)); jj = a->j; for (i = 0; i < nz; i++) collengths[jj[i]]++; cia[0] = oshift; for (i = 0; i < n; i++) cia[i + 1] = cia[i] + collengths[i]; PetscCall(PetscArrayzero(collengths, n)); jj = a->j; for (row = 0; row < m; row++) { mr = a->i[row + 1] - a->i[row]; for (i = 0; i < mr; i++) { col = *jj++; cja[cia[col] + collengths[col]++ - oshift] = row + oshift; } } PetscCall(PetscFree(collengths)); *ia = cia; *ja = cja; PetscFunctionReturn(PETSC_SUCCESS); } static PetscErrorCode MatRestoreColumnIJ_SeqBAIJ(Mat A, PetscInt oshift, PetscBool symmetric, PetscBool inodecompressed, PetscInt *n, const PetscInt *ia[], const PetscInt *ja[], PetscBool *done) { PetscFunctionBegin; if (!ia) PetscFunctionReturn(PETSC_SUCCESS); PetscCall(PetscFree(*ia)); PetscCall(PetscFree(*ja)); PetscFunctionReturn(PETSC_SUCCESS); } /* MatGetColumnIJ_SeqBAIJ_Color() and MatRestoreColumnIJ_SeqBAIJ_Color() are customized from MatGetColumnIJ_SeqBAIJ() and MatRestoreColumnIJ_SeqBAIJ() by adding an output spidx[], index of a->a, to be used in MatTransposeColoringCreate() and MatFDColoringCreate() */ PetscErrorCode MatGetColumnIJ_SeqBAIJ_Color(Mat A, PetscInt oshift, PetscBool symmetric, PetscBool inodecompressed, PetscInt *nn, const PetscInt *ia[], const PetscInt *ja[], PetscInt *spidx[], PetscBool *done) { Mat_SeqBAIJ *a = (Mat_SeqBAIJ *)A->data; PetscInt i, *collengths, *cia, *cja, n = a->nbs, m = a->mbs; PetscInt nz = a->i[m], row, *jj, mr, col; PetscInt *cspidx; PetscFunctionBegin; *nn = n; if (!ia) PetscFunctionReturn(PETSC_SUCCESS); PetscCall(PetscCalloc1(n, &collengths)); PetscCall(PetscMalloc1(n + 1, &cia)); PetscCall(PetscMalloc1(nz, &cja)); PetscCall(PetscMalloc1(nz, &cspidx)); jj = a->j; for (i = 0; i < nz; i++) collengths[jj[i]]++; cia[0] = oshift; for (i = 0; i < n; i++) cia[i + 1] = cia[i] + collengths[i]; PetscCall(PetscArrayzero(collengths, n)); jj = a->j; for (row = 0; row < m; row++) { mr = a->i[row + 1] - a->i[row]; for (i = 0; i < mr; i++) { col = *jj++; cspidx[cia[col] + collengths[col] - oshift] = a->i[row] + i; /* index of a->j */ cja[cia[col] + collengths[col]++ - oshift] = row + oshift; } } PetscCall(PetscFree(collengths)); *ia = cia; *ja = cja; *spidx = cspidx; PetscFunctionReturn(PETSC_SUCCESS); } PetscErrorCode MatRestoreColumnIJ_SeqBAIJ_Color(Mat A, PetscInt oshift, PetscBool symmetric, PetscBool inodecompressed, PetscInt *n, const PetscInt *ia[], const PetscInt *ja[], PetscInt *spidx[], PetscBool *done) { PetscFunctionBegin; PetscCall(MatRestoreColumnIJ_SeqBAIJ(A, oshift, symmetric, inodecompressed, n, ia, ja, done)); PetscCall(PetscFree(*spidx)); PetscFunctionReturn(PETSC_SUCCESS); } static PetscErrorCode MatShift_SeqBAIJ(Mat Y, PetscScalar a) { Mat_SeqBAIJ *aij = (Mat_SeqBAIJ *)Y->data; PetscFunctionBegin; if (!Y->preallocated || !aij->nz) PetscCall(MatSeqBAIJSetPreallocation(Y, Y->rmap->bs, 1, NULL)); PetscCall(MatShift_Basic(Y, a)); PetscFunctionReturn(PETSC_SUCCESS); } PetscErrorCode MatEliminateZeros_SeqBAIJ(Mat A, PetscBool keep) { Mat_SeqBAIJ *a = (Mat_SeqBAIJ *)A->data; PetscInt fshift = 0, fshift_prev = 0, i, *ai = a->i, *aj = a->j, *imax = a->imax, j, k; PetscInt m = A->rmap->N, *ailen = a->ilen; PetscInt mbs = a->mbs, bs2 = a->bs2, rmax = 0; MatScalar *aa = a->a, *ap; PetscBool zero; PetscFunctionBegin; PetscCheck(A->assembled, PETSC_COMM_SELF, PETSC_ERR_ARG_WRONGSTATE, "Cannot eliminate zeros for unassembled matrix"); if (m) rmax = ailen[0]; for (i = 1; i <= mbs; i++) { for (k = ai[i - 1]; k < ai[i]; k++) { zero = PETSC_TRUE; ap = aa + bs2 * k; for (j = 0; j < bs2 && zero; j++) { if (ap[j] != 0.0) zero = PETSC_FALSE; } if (zero && (aj[k] != i - 1 || !keep)) fshift++; else { if (zero && aj[k] == i - 1) PetscCall(PetscInfo(A, "Keep the diagonal block at row %" PetscInt_FMT "\n", i - 1)); aj[k - fshift] = aj[k]; PetscCall(PetscArraymove(ap - bs2 * fshift, ap, bs2)); } } ai[i - 1] -= fshift_prev; fshift_prev = fshift; ailen[i - 1] = imax[i - 1] = ai[i] - fshift - ai[i - 1]; a->nonzerorowcnt += ((ai[i] - fshift - ai[i - 1]) > 0); rmax = PetscMax(rmax, ailen[i - 1]); } if (fshift) { if (mbs) { ai[mbs] -= fshift; a->nz = ai[mbs]; } PetscCall(PetscInfo(A, "Matrix size: %" PetscInt_FMT " X %" PetscInt_FMT "; zeros eliminated: %" PetscInt_FMT "; nonzeros left: %" PetscInt_FMT "\n", m, A->cmap->n, fshift, a->nz)); A->nonzerostate++; A->info.nz_unneeded += (PetscReal)fshift; a->rmax = rmax; PetscCall(MatAssemblyBegin(A, MAT_FINAL_ASSEMBLY)); PetscCall(MatAssemblyEnd(A, MAT_FINAL_ASSEMBLY)); } PetscFunctionReturn(PETSC_SUCCESS); } static struct _MatOps MatOps_Values = {MatSetValues_SeqBAIJ, MatGetRow_SeqBAIJ, MatRestoreRow_SeqBAIJ, MatMult_SeqBAIJ_N, /* 4*/ MatMultAdd_SeqBAIJ_N, MatMultTranspose_SeqBAIJ, MatMultTransposeAdd_SeqBAIJ, NULL, NULL, NULL, /* 10*/ NULL, MatLUFactor_SeqBAIJ, NULL, NULL, MatTranspose_SeqBAIJ, /* 15*/ MatGetInfo_SeqBAIJ, MatEqual_SeqBAIJ, MatGetDiagonal_SeqBAIJ, MatDiagonalScale_SeqBAIJ, MatNorm_SeqBAIJ, /* 20*/ NULL, MatAssemblyEnd_SeqBAIJ, MatSetOption_SeqBAIJ, MatZeroEntries_SeqBAIJ, /* 24*/ MatZeroRows_SeqBAIJ, NULL, NULL, NULL, NULL, /* 29*/ MatSetUp_Seq_Hash, NULL, NULL, NULL, NULL, /* 34*/ MatDuplicate_SeqBAIJ, NULL, NULL, MatILUFactor_SeqBAIJ, NULL, /* 39*/ MatAXPY_SeqBAIJ, MatCreateSubMatrices_SeqBAIJ, MatIncreaseOverlap_SeqBAIJ, MatGetValues_SeqBAIJ, MatCopy_SeqBAIJ, /* 44*/ NULL, MatScale_SeqBAIJ, MatShift_SeqBAIJ, NULL, MatZeroRowsColumns_SeqBAIJ, /* 49*/ NULL, MatGetRowIJ_SeqBAIJ, MatRestoreRowIJ_SeqBAIJ, MatGetColumnIJ_SeqBAIJ, MatRestoreColumnIJ_SeqBAIJ, /* 54*/ MatFDColoringCreate_SeqXAIJ, NULL, NULL, NULL, MatSetValuesBlocked_SeqBAIJ, /* 59*/ MatCreateSubMatrix_SeqBAIJ, MatDestroy_SeqBAIJ, MatView_SeqBAIJ, NULL, NULL, /* 64*/ NULL, NULL, NULL, NULL, MatGetRowMaxAbs_SeqBAIJ, /* 69*/ NULL, MatConvert_Basic, NULL, MatFDColoringApply_BAIJ, NULL, /* 74*/ NULL, NULL, NULL, NULL, MatLoad_SeqBAIJ, /* 79*/ NULL, NULL, NULL, NULL, NULL, /* 84*/ NULL, NULL, NULL, NULL, NULL, /* 89*/ NULL, NULL, NULL, NULL, MatConjugate_SeqBAIJ, /* 94*/ NULL, NULL, MatRealPart_SeqBAIJ, MatImaginaryPart_SeqBAIJ, NULL, /* 99*/ NULL, NULL, NULL, NULL, NULL, /*104*/ NULL, NULL, NULL, NULL, NULL, /*109*/ NULL, NULL, MatMultHermitianTranspose_SeqBAIJ, MatMultHermitianTransposeAdd_SeqBAIJ, NULL, /*114*/ NULL, MatGetColumnReductions_SeqBAIJ, MatInvertBlockDiagonal_SeqBAIJ, NULL, NULL, /*119*/ NULL, NULL, NULL, NULL, NULL, /*124*/ NULL, NULL, MatSetBlockSizes_Default, NULL, MatFDColoringSetUp_SeqXAIJ, /*129*/ NULL, MatCreateMPIMatConcatenateSeqMat_SeqBAIJ, MatDestroySubMatrices_SeqBAIJ, NULL, NULL, /*134*/ NULL, NULL, MatEliminateZeros_SeqBAIJ, MatGetRowSumAbs_SeqBAIJ, NULL, /*139*/ NULL, NULL, MatCopyHashToXAIJ_Seq_Hash, NULL, NULL}; static PetscErrorCode MatStoreValues_SeqBAIJ(Mat mat) { Mat_SeqBAIJ *aij = (Mat_SeqBAIJ *)mat->data; PetscInt nz = aij->i[aij->mbs] * aij->bs2; PetscFunctionBegin; PetscCheck(aij->nonew == 1, PETSC_COMM_SELF, PETSC_ERR_ORDER, "Must call MatSetOption(A,MAT_NEW_NONZERO_LOCATIONS,PETSC_FALSE);first"); /* allocate space for values if not already there */ if (!aij->saved_values) PetscCall(PetscMalloc1(nz + 1, &aij->saved_values)); /* copy values over */ PetscCall(PetscArraycpy(aij->saved_values, aij->a, nz)); PetscFunctionReturn(PETSC_SUCCESS); } static PetscErrorCode MatRetrieveValues_SeqBAIJ(Mat mat) { Mat_SeqBAIJ *aij = (Mat_SeqBAIJ *)mat->data; PetscInt nz = aij->i[aij->mbs] * aij->bs2; PetscFunctionBegin; PetscCheck(aij->nonew == 1, PETSC_COMM_SELF, PETSC_ERR_ORDER, "Must call MatSetOption(A,MAT_NEW_NONZERO_LOCATIONS,PETSC_FALSE);first"); PetscCheck(aij->saved_values, PETSC_COMM_SELF, PETSC_ERR_ORDER, "Must call MatStoreValues(A);first"); /* copy values over */ PetscCall(PetscArraycpy(aij->a, aij->saved_values, nz)); PetscFunctionReturn(PETSC_SUCCESS); } PETSC_INTERN PetscErrorCode MatConvert_SeqBAIJ_SeqAIJ(Mat, MatType, MatReuse, Mat *); PETSC_INTERN PetscErrorCode MatConvert_SeqBAIJ_SeqSBAIJ(Mat, MatType, MatReuse, Mat *); PetscErrorCode MatSeqBAIJSetPreallocation_SeqBAIJ(Mat B, PetscInt bs, PetscInt nz, const PetscInt nnz[]) { Mat_SeqBAIJ *b = (Mat_SeqBAIJ *)B->data; PetscInt i, mbs, nbs, bs2; PetscBool flg = PETSC_FALSE, skipallocation = PETSC_FALSE, realalloc = PETSC_FALSE; PetscFunctionBegin; if (B->hash_active) { PetscInt bs; B->ops[0] = b->cops; PetscCall(PetscHMapIJVDestroy(&b->ht)); PetscCall(MatGetBlockSize(B, &bs)); if (bs > 1) PetscCall(PetscHSetIJDestroy(&b->bht)); PetscCall(PetscFree(b->dnz)); PetscCall(PetscFree(b->bdnz)); B->hash_active = PETSC_FALSE; } if (nz >= 0 || nnz) realalloc = PETSC_TRUE; if (nz == MAT_SKIP_ALLOCATION) { skipallocation = PETSC_TRUE; nz = 0; } PetscCall(MatSetBlockSize(B, bs)); PetscCall(PetscLayoutSetUp(B->rmap)); PetscCall(PetscLayoutSetUp(B->cmap)); PetscCall(PetscLayoutGetBlockSize(B->rmap, &bs)); B->preallocated = PETSC_TRUE; mbs = B->rmap->n / bs; nbs = B->cmap->n / bs; bs2 = bs * bs; PetscCheck(mbs * bs == B->rmap->n && nbs * bs == B->cmap->n, PETSC_COMM_SELF, PETSC_ERR_ARG_SIZ, "Number rows %" PetscInt_FMT ", cols %" PetscInt_FMT " must be divisible by blocksize %" PetscInt_FMT, B->rmap->N, B->cmap->n, bs); if (nz == PETSC_DEFAULT || nz == PETSC_DECIDE) nz = 5; PetscCheck(nz >= 0, PETSC_COMM_SELF, PETSC_ERR_ARG_OUTOFRANGE, "nz cannot be less than 0: value %" PetscInt_FMT, nz); if (nnz) { for (i = 0; i < mbs; i++) { PetscCheck(nnz[i] >= 0, PETSC_COMM_SELF, PETSC_ERR_ARG_OUTOFRANGE, "nnz cannot be less than 0: local row %" PetscInt_FMT " value %" PetscInt_FMT, i, nnz[i]); PetscCheck(nnz[i] <= nbs, PETSC_COMM_SELF, PETSC_ERR_ARG_OUTOFRANGE, "nnz cannot be greater than block row length: local row %" PetscInt_FMT " value %" PetscInt_FMT " rowlength %" PetscInt_FMT, i, nnz[i], nbs); } } PetscOptionsBegin(PetscObjectComm((PetscObject)B), NULL, "Optimize options for SEQBAIJ matrix 2 ", "Mat"); PetscCall(PetscOptionsBool("-mat_no_unroll", "Do not optimize for block size (slow)", NULL, flg, &flg, NULL)); PetscOptionsEnd(); if (!flg) { switch (bs) { case 1: B->ops->mult = MatMult_SeqBAIJ_1; B->ops->multadd = MatMultAdd_SeqBAIJ_1; break; case 2: B->ops->mult = MatMult_SeqBAIJ_2; B->ops->multadd = MatMultAdd_SeqBAIJ_2; break; case 3: B->ops->mult = MatMult_SeqBAIJ_3; B->ops->multadd = MatMultAdd_SeqBAIJ_3; break; case 4: B->ops->mult = MatMult_SeqBAIJ_4; B->ops->multadd = MatMultAdd_SeqBAIJ_4; break; case 5: B->ops->mult = MatMult_SeqBAIJ_5; B->ops->multadd = MatMultAdd_SeqBAIJ_5; break; case 6: B->ops->mult = MatMult_SeqBAIJ_6; B->ops->multadd = MatMultAdd_SeqBAIJ_6; break; case 7: B->ops->mult = MatMult_SeqBAIJ_7; B->ops->multadd = MatMultAdd_SeqBAIJ_7; break; case 9: { PetscInt version = 1; PetscCall(PetscOptionsGetInt(NULL, ((PetscObject)B)->prefix, "-mat_baij_mult_version", &version, NULL)); switch (version) { #if defined(PETSC_HAVE_IMMINTRIN_H) && defined(__AVX2__) && defined(__FMA__) && defined(PETSC_USE_REAL_DOUBLE) && !defined(PETSC_USE_COMPLEX) && !defined(PETSC_USE_64BIT_INDICES) case 1: B->ops->mult = MatMult_SeqBAIJ_9_AVX2; B->ops->multadd = MatMultAdd_SeqBAIJ_9_AVX2; PetscCall(PetscInfo(B, "Using AVX2 for MatMult for BAIJ for blocksize %" PetscInt_FMT "\n", bs)); break; #endif default: B->ops->mult = MatMult_SeqBAIJ_N; B->ops->multadd = MatMultAdd_SeqBAIJ_N; PetscCall(PetscInfo(B, "Using BLAS for MatMult for BAIJ for blocksize %" PetscInt_FMT "\n", bs)); break; } break; } case 11: B->ops->mult = MatMult_SeqBAIJ_11; B->ops->multadd = MatMultAdd_SeqBAIJ_11; break; case 12: { PetscInt version = 1; PetscCall(PetscOptionsGetInt(NULL, ((PetscObject)B)->prefix, "-mat_baij_mult_version", &version, NULL)); switch (version) { case 1: B->ops->mult = MatMult_SeqBAIJ_12_ver1; B->ops->multadd = MatMultAdd_SeqBAIJ_12_ver1; PetscCall(PetscInfo(B, "Using version %" PetscInt_FMT " of MatMult for BAIJ for blocksize %" PetscInt_FMT "\n", version, bs)); break; case 2: B->ops->mult = MatMult_SeqBAIJ_12_ver2; B->ops->multadd = MatMultAdd_SeqBAIJ_12_ver2; PetscCall(PetscInfo(B, "Using version %" PetscInt_FMT " of MatMult for BAIJ for blocksize %" PetscInt_FMT "\n", version, bs)); break; #if defined(PETSC_HAVE_IMMINTRIN_H) && defined(__AVX2__) && defined(__FMA__) && defined(PETSC_USE_REAL_DOUBLE) && !defined(PETSC_USE_COMPLEX) && !defined(PETSC_USE_64BIT_INDICES) case 3: B->ops->mult = MatMult_SeqBAIJ_12_AVX2; B->ops->multadd = MatMultAdd_SeqBAIJ_12_ver1; PetscCall(PetscInfo(B, "Using AVX2 for MatMult for BAIJ for blocksize %" PetscInt_FMT "\n", bs)); break; #endif default: B->ops->mult = MatMult_SeqBAIJ_N; B->ops->multadd = MatMultAdd_SeqBAIJ_N; PetscCall(PetscInfo(B, "Using BLAS for MatMult for BAIJ for blocksize %" PetscInt_FMT "\n", bs)); break; } break; } case 15: { PetscInt version = 1; PetscCall(PetscOptionsGetInt(NULL, ((PetscObject)B)->prefix, "-mat_baij_mult_version", &version, NULL)); switch (version) { case 1: B->ops->mult = MatMult_SeqBAIJ_15_ver1; PetscCall(PetscInfo(B, "Using version %" PetscInt_FMT " of MatMult for BAIJ for blocksize %" PetscInt_FMT "\n", version, bs)); break; case 2: B->ops->mult = MatMult_SeqBAIJ_15_ver2; PetscCall(PetscInfo(B, "Using version %" PetscInt_FMT " of MatMult for BAIJ for blocksize %" PetscInt_FMT "\n", version, bs)); break; case 3: B->ops->mult = MatMult_SeqBAIJ_15_ver3; PetscCall(PetscInfo(B, "Using version %" PetscInt_FMT " of MatMult for BAIJ for blocksize %" PetscInt_FMT "\n", version, bs)); break; case 4: B->ops->mult = MatMult_SeqBAIJ_15_ver4; PetscCall(PetscInfo(B, "Using version %" PetscInt_FMT " of MatMult for BAIJ for blocksize %" PetscInt_FMT "\n", version, bs)); break; default: B->ops->mult = MatMult_SeqBAIJ_N; PetscCall(PetscInfo(B, "Using BLAS for MatMult for BAIJ for blocksize %" PetscInt_FMT "\n", bs)); break; } B->ops->multadd = MatMultAdd_SeqBAIJ_N; break; } default: B->ops->mult = MatMult_SeqBAIJ_N; B->ops->multadd = MatMultAdd_SeqBAIJ_N; PetscCall(PetscInfo(B, "Using BLAS for MatMult for BAIJ for blocksize %" PetscInt_FMT "\n", bs)); break; } } B->ops->sor = MatSOR_SeqBAIJ; b->mbs = mbs; b->nbs = nbs; if (!skipallocation) { if (!b->imax) { PetscCall(PetscMalloc2(mbs, &b->imax, mbs, &b->ilen)); b->free_imax_ilen = PETSC_TRUE; } /* b->ilen will count nonzeros in each block row so far. */ for (i = 0; i < mbs; i++) b->ilen[i] = 0; if (!nnz) { if (nz == PETSC_DEFAULT || nz == PETSC_DECIDE) nz = 5; else if (nz < 0) nz = 1; nz = PetscMin(nz, nbs); for (i = 0; i < mbs; i++) b->imax[i] = nz; PetscCall(PetscIntMultError(nz, mbs, &nz)); } else { PetscInt64 nz64 = 0; for (i = 0; i < mbs; i++) { b->imax[i] = nnz[i]; nz64 += nnz[i]; } PetscCall(PetscIntCast(nz64, &nz)); } /* allocate the matrix space */ PetscCall(MatSeqXAIJFreeAIJ(B, &b->a, &b->j, &b->i)); PetscCall(PetscShmgetAllocateArray(nz, sizeof(PetscInt), (void **)&b->j)); PetscCall(PetscShmgetAllocateArray(B->rmap->N + 1, sizeof(PetscInt), (void **)&b->i)); if (B->structure_only) { b->free_a = PETSC_FALSE; } else { PetscInt nzbs2 = 0; PetscCall(PetscIntMultError(nz, bs2, &nzbs2)); PetscCall(PetscShmgetAllocateArray(nzbs2, sizeof(PetscScalar), (void **)&b->a)); b->free_a = PETSC_TRUE; PetscCall(PetscArrayzero(b->a, nzbs2)); } b->free_ij = PETSC_TRUE; PetscCall(PetscArrayzero(b->j, nz)); b->i[0] = 0; for (i = 1; i < mbs + 1; i++) b->i[i] = b->i[i - 1] + b->imax[i - 1]; } else { b->free_a = PETSC_FALSE; b->free_ij = PETSC_FALSE; } b->bs2 = bs2; b->mbs = mbs; b->nz = 0; b->maxnz = nz; B->info.nz_unneeded = (PetscReal)b->maxnz * bs2; B->was_assembled = PETSC_FALSE; B->assembled = PETSC_FALSE; if (realalloc) PetscCall(MatSetOption(B, MAT_NEW_NONZERO_ALLOCATION_ERR, PETSC_TRUE)); PetscFunctionReturn(PETSC_SUCCESS); } static PetscErrorCode MatSeqBAIJSetPreallocationCSR_SeqBAIJ(Mat B, PetscInt bs, const PetscInt ii[], const PetscInt jj[], const PetscScalar V[]) { PetscInt i, m, nz, nz_max = 0, *nnz; PetscScalar *values = NULL; PetscBool roworiented = ((Mat_SeqBAIJ *)B->data)->roworiented; PetscFunctionBegin; PetscCheck(bs >= 1, PETSC_COMM_SELF, PETSC_ERR_ARG_OUTOFRANGE, "Invalid block size specified, must be positive but it is %" PetscInt_FMT, bs); PetscCall(PetscLayoutSetBlockSize(B->rmap, bs)); PetscCall(PetscLayoutSetBlockSize(B->cmap, bs)); PetscCall(PetscLayoutSetUp(B->rmap)); PetscCall(PetscLayoutSetUp(B->cmap)); PetscCall(PetscLayoutGetBlockSize(B->rmap, &bs)); m = B->rmap->n / bs; PetscCheck(ii[0] == 0, PETSC_COMM_SELF, PETSC_ERR_ARG_OUTOFRANGE, "ii[0] must be 0 but it is %" PetscInt_FMT, ii[0]); PetscCall(PetscMalloc1(m + 1, &nnz)); for (i = 0; i < m; i++) { nz = ii[i + 1] - ii[i]; PetscCheck(nz >= 0, PETSC_COMM_SELF, PETSC_ERR_ARG_OUTOFRANGE, "Local row %" PetscInt_FMT " has a negative number of columns %" PetscInt_FMT, i, nz); nz_max = PetscMax(nz_max, nz); nnz[i] = nz; } PetscCall(MatSeqBAIJSetPreallocation(B, bs, 0, nnz)); PetscCall(PetscFree(nnz)); values = (PetscScalar *)V; if (!values) PetscCall(PetscCalloc1(bs * bs * (nz_max + 1), &values)); for (i = 0; i < m; i++) { PetscInt ncols = ii[i + 1] - ii[i]; const PetscInt *icols = jj + ii[i]; if (bs == 1 || !roworiented) { const PetscScalar *svals = values + (V ? (bs * bs * ii[i]) : 0); PetscCall(MatSetValuesBlocked_SeqBAIJ(B, 1, &i, ncols, icols, svals, INSERT_VALUES)); } else { PetscInt j; for (j = 0; j < ncols; j++) { const PetscScalar *svals = values + (V ? (bs * bs * (ii[i] + j)) : 0); PetscCall(MatSetValuesBlocked_SeqBAIJ(B, 1, &i, 1, &icols[j], svals, INSERT_VALUES)); } } } if (!V) PetscCall(PetscFree(values)); PetscCall(MatAssemblyBegin(B, MAT_FINAL_ASSEMBLY)); PetscCall(MatAssemblyEnd(B, MAT_FINAL_ASSEMBLY)); PetscCall(MatSetOption(B, MAT_NEW_NONZERO_LOCATION_ERR, PETSC_TRUE)); PetscFunctionReturn(PETSC_SUCCESS); } /*@C MatSeqBAIJGetArray - gives read/write access to the array where the data for a `MATSEQBAIJ` matrix is stored Not Collective Input Parameter: . A - a `MATSEQBAIJ` matrix Output Parameter: . array - pointer to the data Level: intermediate .seealso: [](ch_matrices), `Mat`, `MATSEQBAIJ`, `MatSeqBAIJRestoreArray()`, `MatSeqAIJGetArray()`, `MatSeqAIJRestoreArray()` @*/ PetscErrorCode MatSeqBAIJGetArray(Mat A, PetscScalar *array[]) { PetscFunctionBegin; PetscUseMethod(A, "MatSeqBAIJGetArray_C", (Mat, PetscScalar **), (A, array)); PetscFunctionReturn(PETSC_SUCCESS); } /*@C MatSeqBAIJRestoreArray - returns access to the array where the data for a `MATSEQBAIJ` matrix is stored obtained by `MatSeqBAIJGetArray()` Not Collective Input Parameters: + A - a `MATSEQBAIJ` matrix - array - pointer to the data Level: intermediate .seealso: [](ch_matrices), `Mat`, `MatSeqBAIJGetArray()`, `MatSeqAIJGetArray()`, `MatSeqAIJRestoreArray()` @*/ PetscErrorCode MatSeqBAIJRestoreArray(Mat A, PetscScalar *array[]) { PetscFunctionBegin; PetscUseMethod(A, "MatSeqBAIJRestoreArray_C", (Mat, PetscScalar **), (A, array)); PetscFunctionReturn(PETSC_SUCCESS); } /*MC MATSEQBAIJ - MATSEQBAIJ = "seqbaij" - A matrix type to be used for sequential block sparse matrices, based on block sparse compressed row format. Options Database Keys: + -mat_type seqbaij - sets the matrix type to `MATSEQBAIJ` during a call to `MatSetFromOptions()` - -mat_baij_mult_version version - indicate the version of the matrix-vector product to use (0 often indicates using BLAS) Level: beginner Notes: `MatSetOptions`(,`MAT_STRUCTURE_ONLY`,`PETSC_TRUE`) may be called for this matrix type. In this no space is allocated for the nonzero entries and any entries passed with `MatSetValues()` are ignored Run with `-info` to see what version of the matrix-vector product is being used .seealso: [](ch_matrices), `Mat`, `MatCreateSeqBAIJ()` M*/ PETSC_INTERN PetscErrorCode MatConvert_SeqBAIJ_SeqBSTRM(Mat, MatType, MatReuse, Mat *); PETSC_EXTERN PetscErrorCode MatCreate_SeqBAIJ(Mat B) { PetscMPIInt size; Mat_SeqBAIJ *b; PetscFunctionBegin; PetscCallMPI(MPI_Comm_size(PetscObjectComm((PetscObject)B), &size)); PetscCheck(size == 1, PETSC_COMM_SELF, PETSC_ERR_ARG_WRONG, "Comm must be of size 1"); PetscCall(PetscNew(&b)); B->data = (void *)b; B->ops[0] = MatOps_Values; b->row = NULL; b->col = NULL; b->icol = NULL; b->reallocs = 0; b->saved_values = NULL; b->roworiented = PETSC_TRUE; b->nonew = 0; b->diag = NULL; B->spptr = NULL; B->info.nz_unneeded = (PetscReal)b->maxnz * b->bs2; b->keepnonzeropattern = PETSC_FALSE; PetscCall(PetscObjectComposeFunction((PetscObject)B, "MatSeqBAIJGetArray_C", MatSeqBAIJGetArray_SeqBAIJ)); PetscCall(PetscObjectComposeFunction((PetscObject)B, "MatSeqBAIJRestoreArray_C", MatSeqBAIJRestoreArray_SeqBAIJ)); PetscCall(PetscObjectComposeFunction((PetscObject)B, "MatStoreValues_C", MatStoreValues_SeqBAIJ)); PetscCall(PetscObjectComposeFunction((PetscObject)B, "MatRetrieveValues_C", MatRetrieveValues_SeqBAIJ)); PetscCall(PetscObjectComposeFunction((PetscObject)B, "MatSeqBAIJSetColumnIndices_C", MatSeqBAIJSetColumnIndices_SeqBAIJ)); PetscCall(PetscObjectComposeFunction((PetscObject)B, "MatConvert_seqbaij_seqaij_C", MatConvert_SeqBAIJ_SeqAIJ)); PetscCall(PetscObjectComposeFunction((PetscObject)B, "MatConvert_seqbaij_seqsbaij_C", MatConvert_SeqBAIJ_SeqSBAIJ)); PetscCall(PetscObjectComposeFunction((PetscObject)B, "MatSeqBAIJSetPreallocation_C", MatSeqBAIJSetPreallocation_SeqBAIJ)); PetscCall(PetscObjectComposeFunction((PetscObject)B, "MatSeqBAIJSetPreallocationCSR_C", MatSeqBAIJSetPreallocationCSR_SeqBAIJ)); PetscCall(PetscObjectComposeFunction((PetscObject)B, "MatIsTranspose_C", MatIsTranspose_SeqBAIJ)); #if defined(PETSC_HAVE_HYPRE) PetscCall(PetscObjectComposeFunction((PetscObject)B, "MatConvert_seqbaij_hypre_C", MatConvert_AIJ_HYPRE)); #endif PetscCall(PetscObjectComposeFunction((PetscObject)B, "MatConvert_seqbaij_is_C", MatConvert_XAIJ_IS)); PetscCall(PetscObjectChangeTypeName((PetscObject)B, MATSEQBAIJ)); PetscFunctionReturn(PETSC_SUCCESS); } PETSC_INTERN PetscErrorCode MatDuplicateNoCreate_SeqBAIJ(Mat C, Mat A, MatDuplicateOption cpvalues, PetscBool mallocmatspace) { Mat_SeqBAIJ *c = (Mat_SeqBAIJ *)C->data, *a = (Mat_SeqBAIJ *)A->data; PetscInt i, mbs = a->mbs, nz = a->nz, bs2 = a->bs2; PetscFunctionBegin; PetscCheck(A->assembled, PetscObjectComm((PetscObject)A), PETSC_ERR_ARG_WRONGSTATE, "Cannot duplicate unassembled matrix"); PetscCheck(a->i[mbs] == nz, PETSC_COMM_SELF, PETSC_ERR_PLIB, "Corrupt matrix"); if (cpvalues == MAT_SHARE_NONZERO_PATTERN) { c->imax = a->imax; c->ilen = a->ilen; c->free_imax_ilen = PETSC_FALSE; } else { PetscCall(PetscMalloc2(mbs, &c->imax, mbs, &c->ilen)); for (i = 0; i < mbs; i++) { c->imax[i] = a->imax[i]; c->ilen[i] = a->ilen[i]; } c->free_imax_ilen = PETSC_TRUE; } /* allocate the matrix space */ if (mallocmatspace) { if (cpvalues == MAT_SHARE_NONZERO_PATTERN) { PetscCall(PetscShmgetAllocateArray(bs2 * nz, sizeof(PetscScalar), (void **)&c->a)); PetscCall(PetscArrayzero(c->a, bs2 * nz)); c->free_a = PETSC_TRUE; c->i = a->i; c->j = a->j; c->free_ij = PETSC_FALSE; c->parent = A; C->preallocated = PETSC_TRUE; C->assembled = PETSC_TRUE; PetscCall(PetscObjectReference((PetscObject)A)); PetscCall(MatSetOption(A, MAT_NEW_NONZERO_LOCATION_ERR, PETSC_TRUE)); PetscCall(MatSetOption(C, MAT_NEW_NONZERO_LOCATION_ERR, PETSC_TRUE)); } else { PetscCall(PetscShmgetAllocateArray(bs2 * nz, sizeof(PetscScalar), (void **)&c->a)); PetscCall(PetscShmgetAllocateArray(nz, sizeof(PetscInt), (void **)&c->j)); PetscCall(PetscShmgetAllocateArray(mbs + 1, sizeof(PetscInt), (void **)&c->i)); c->free_a = PETSC_TRUE; c->free_ij = PETSC_TRUE; PetscCall(PetscArraycpy(c->i, a->i, mbs + 1)); if (mbs > 0) { PetscCall(PetscArraycpy(c->j, a->j, nz)); if (cpvalues == MAT_COPY_VALUES) { PetscCall(PetscArraycpy(c->a, a->a, bs2 * nz)); } else { PetscCall(PetscArrayzero(c->a, bs2 * nz)); } } C->preallocated = PETSC_TRUE; C->assembled = PETSC_TRUE; } } c->roworiented = a->roworiented; c->nonew = a->nonew; PetscCall(PetscLayoutReference(A->rmap, &C->rmap)); PetscCall(PetscLayoutReference(A->cmap, &C->cmap)); c->bs2 = a->bs2; c->mbs = a->mbs; c->nbs = a->nbs; c->nz = a->nz; c->maxnz = a->nz; /* Since we allocate exactly the right amount */ c->solve_work = NULL; c->mult_work = NULL; c->sor_workt = NULL; c->sor_work = NULL; c->compressedrow.use = a->compressedrow.use; c->compressedrow.nrows = a->compressedrow.nrows; if (a->compressedrow.use) { i = a->compressedrow.nrows; PetscCall(PetscMalloc2(i + 1, &c->compressedrow.i, i + 1, &c->compressedrow.rindex)); PetscCall(PetscArraycpy(c->compressedrow.i, a->compressedrow.i, i + 1)); PetscCall(PetscArraycpy(c->compressedrow.rindex, a->compressedrow.rindex, i)); } else { c->compressedrow.use = PETSC_FALSE; c->compressedrow.i = NULL; c->compressedrow.rindex = NULL; } c->nonzerorowcnt = a->nonzerorowcnt; C->nonzerostate = A->nonzerostate; PetscCall(PetscFunctionListDuplicate(((PetscObject)A)->qlist, &((PetscObject)C)->qlist)); PetscFunctionReturn(PETSC_SUCCESS); } PetscErrorCode MatDuplicate_SeqBAIJ(Mat A, MatDuplicateOption cpvalues, Mat *B) { PetscFunctionBegin; PetscCall(MatCreate(PetscObjectComm((PetscObject)A), B)); PetscCall(MatSetSizes(*B, A->rmap->N, A->cmap->n, A->rmap->N, A->cmap->n)); PetscCall(MatSetType(*B, MATSEQBAIJ)); PetscCall(MatDuplicateNoCreate_SeqBAIJ(*B, A, cpvalues, PETSC_TRUE)); PetscFunctionReturn(PETSC_SUCCESS); } /* Used for both SeqBAIJ and SeqSBAIJ matrices */ PetscErrorCode MatLoad_SeqBAIJ_Binary(Mat mat, PetscViewer viewer) { PetscInt header[4], M, N, nz, bs, m, n, mbs, nbs, rows, cols, sum, i, j, k; PetscInt *rowidxs, *colidxs; PetscScalar *matvals; PetscFunctionBegin; PetscCall(PetscViewerSetUp(viewer)); /* read matrix header */ PetscCall(PetscViewerBinaryRead(viewer, header, 4, NULL, PETSC_INT)); PetscCheck(header[0] == MAT_FILE_CLASSID, PETSC_COMM_SELF, PETSC_ERR_FILE_UNEXPECTED, "Not a matrix object in file"); M = header[1]; N = header[2]; nz = header[3]; PetscCheck(M >= 0, PetscObjectComm((PetscObject)viewer), PETSC_ERR_FILE_UNEXPECTED, "Matrix row size (%" PetscInt_FMT ") in file is negative", M); PetscCheck(N >= 0, PetscObjectComm((PetscObject)viewer), PETSC_ERR_FILE_UNEXPECTED, "Matrix column size (%" PetscInt_FMT ") in file is negative", N); PetscCheck(nz >= 0, PETSC_COMM_SELF, PETSC_ERR_FILE_UNEXPECTED, "Matrix stored in special format on disk, cannot load as SeqBAIJ"); /* set block sizes from the viewer's .info file */ PetscCall(MatLoad_Binary_BlockSizes(mat, viewer)); /* set local and global sizes if not set already */ if (mat->rmap->n < 0) mat->rmap->n = M; if (mat->cmap->n < 0) mat->cmap->n = N; if (mat->rmap->N < 0) mat->rmap->N = M; if (mat->cmap->N < 0) mat->cmap->N = N; PetscCall(PetscLayoutSetUp(mat->rmap)); PetscCall(PetscLayoutSetUp(mat->cmap)); /* check if the matrix sizes are correct */ PetscCall(MatGetSize(mat, &rows, &cols)); PetscCheck(M == rows && N == cols, PETSC_COMM_SELF, PETSC_ERR_FILE_UNEXPECTED, "Matrix in file of different sizes (%" PetscInt_FMT ", %" PetscInt_FMT ") than the input matrix (%" PetscInt_FMT ", %" PetscInt_FMT ")", M, N, rows, cols); PetscCall(MatGetBlockSize(mat, &bs)); PetscCall(MatGetLocalSize(mat, &m, &n)); mbs = m / bs; nbs = n / bs; /* read in row lengths, column indices and nonzero values */ PetscCall(PetscMalloc1(m + 1, &rowidxs)); PetscCall(PetscViewerBinaryRead(viewer, rowidxs + 1, m, NULL, PETSC_INT)); rowidxs[0] = 0; for (i = 0; i < m; i++) rowidxs[i + 1] += rowidxs[i]; sum = rowidxs[m]; PetscCheck(sum == nz, PETSC_COMM_SELF, PETSC_ERR_FILE_UNEXPECTED, "Inconsistent matrix data in file: nonzeros = %" PetscInt_FMT ", sum-row-lengths = %" PetscInt_FMT, nz, sum); /* read in column indices and nonzero values */ PetscCall(PetscMalloc2(rowidxs[m], &colidxs, nz, &matvals)); PetscCall(PetscViewerBinaryRead(viewer, colidxs, rowidxs[m], NULL, PETSC_INT)); PetscCall(PetscViewerBinaryRead(viewer, matvals, rowidxs[m], NULL, PETSC_SCALAR)); { /* preallocate matrix storage */ PetscBT bt; /* helper bit set to count nonzeros */ PetscInt *nnz; PetscBool sbaij; PetscCall(PetscBTCreate(nbs, &bt)); PetscCall(PetscCalloc1(mbs, &nnz)); PetscCall(PetscObjectTypeCompare((PetscObject)mat, MATSEQSBAIJ, &sbaij)); for (i = 0; i < mbs; i++) { PetscCall(PetscBTMemzero(nbs, bt)); for (k = 0; k < bs; k++) { PetscInt row = bs * i + k; for (j = rowidxs[row]; j < rowidxs[row + 1]; j++) { PetscInt col = colidxs[j]; if (!sbaij || col >= row) if (!PetscBTLookupSet(bt, col / bs)) nnz[i]++; } } } PetscCall(PetscBTDestroy(&bt)); PetscCall(MatSeqBAIJSetPreallocation(mat, bs, 0, nnz)); PetscCall(MatSeqSBAIJSetPreallocation(mat, bs, 0, nnz)); PetscCall(PetscFree(nnz)); } /* store matrix values */ for (i = 0; i < m; i++) { PetscInt row = i, s = rowidxs[i], e = rowidxs[i + 1]; PetscUseTypeMethod(mat, setvalues, 1, &row, e - s, colidxs + s, matvals + s, INSERT_VALUES); } PetscCall(PetscFree(rowidxs)); PetscCall(PetscFree2(colidxs, matvals)); PetscCall(MatAssemblyBegin(mat, MAT_FINAL_ASSEMBLY)); PetscCall(MatAssemblyEnd(mat, MAT_FINAL_ASSEMBLY)); PetscFunctionReturn(PETSC_SUCCESS); } PetscErrorCode MatLoad_SeqBAIJ(Mat mat, PetscViewer viewer) { PetscBool isbinary; PetscFunctionBegin; PetscCall(PetscObjectTypeCompare((PetscObject)viewer, PETSCVIEWERBINARY, &isbinary)); PetscCheck(isbinary, PetscObjectComm((PetscObject)viewer), PETSC_ERR_SUP, "Viewer type %s not yet supported for reading %s matrices", ((PetscObject)viewer)->type_name, ((PetscObject)mat)->type_name); PetscCall(MatLoad_SeqBAIJ_Binary(mat, viewer)); PetscFunctionReturn(PETSC_SUCCESS); } /*@ MatCreateSeqBAIJ - Creates a sparse matrix in `MATSEQAIJ` (block compressed row) format. For good matrix assembly performance the user should preallocate the matrix storage by setting the parameter `nz` (or the array `nnz`). Collective Input Parameters: + comm - MPI communicator, set to `PETSC_COMM_SELF` . bs - size of block, the blocks are ALWAYS square. One can use `MatSetBlockSizes()` to set a different row and column blocksize but the row blocksize always defines the size of the blocks. The column blocksize sets the blocksize of the vectors obtained with `MatCreateVecs()` . m - number of rows . n - number of columns . nz - number of nonzero blocks per block row (same for all rows) - nnz - array containing the number of nonzero blocks in the various block rows (possibly different for each block row) or `NULL` Output Parameter: . A - the matrix Options Database Keys: + -mat_no_unroll - uses code that does not unroll the loops in the block calculations (much slower) - -mat_block_size - size of the blocks to use Level: intermediate Notes: It is recommended that one use `MatCreateFromOptions()` or the `MatCreate()`, `MatSetType()` and/or `MatSetFromOptions()`, MatXXXXSetPreallocation() paradigm instead of this routine directly. [MatXXXXSetPreallocation() is, for example, `MatSeqAIJSetPreallocation()`] The number of rows and columns must be divisible by blocksize. If the `nnz` parameter is given then the `nz` parameter is ignored A nonzero block is any block that as 1 or more nonzeros in it The `MATSEQBAIJ` format is fully compatible with standard Fortran storage. That is, the stored row and column indices can begin at either one (as in Fortran) or zero. Specify the preallocated storage with either `nz` or `nnz` (not both). Set `nz` = `PETSC_DEFAULT` and `nnz` = `NULL` for PETSc to control dynamic memory allocation. See [Sparse Matrices](sec_matsparse) for details. matrices. .seealso: [](ch_matrices), `Mat`, [Sparse Matrices](sec_matsparse), `MatCreate()`, `MatCreateSeqAIJ()`, `MatSetValues()`, `MatCreateBAIJ()` @*/ PetscErrorCode MatCreateSeqBAIJ(MPI_Comm comm, PetscInt bs, PetscInt m, PetscInt n, PetscInt nz, const PetscInt nnz[], Mat *A) { PetscFunctionBegin; PetscCall(MatCreate(comm, A)); PetscCall(MatSetSizes(*A, m, n, m, n)); PetscCall(MatSetType(*A, MATSEQBAIJ)); PetscCall(MatSeqBAIJSetPreallocation(*A, bs, nz, (PetscInt *)nnz)); PetscFunctionReturn(PETSC_SUCCESS); } /*@ MatSeqBAIJSetPreallocation - Sets the block size and expected nonzeros per row in the matrix. For good matrix assembly performance the user should preallocate the matrix storage by setting the parameter `nz` (or the array `nnz`). Collective Input Parameters: + B - the matrix . bs - size of block, the blocks are ALWAYS square. One can use `MatSetBlockSizes()` to set a different row and column blocksize but the row blocksize always defines the size of the blocks. The column blocksize sets the blocksize of the vectors obtained with `MatCreateVecs()` . nz - number of block nonzeros per block row (same for all rows) - nnz - array containing the number of block nonzeros in the various block rows (possibly different for each block row) or `NULL` Options Database Keys: + -mat_no_unroll - uses code that does not unroll the loops in the block calculations (much slower) - -mat_block_size - size of the blocks to use Level: intermediate Notes: If the `nnz` parameter is given then the `nz` parameter is ignored You can call `MatGetInfo()` to get information on how effective the preallocation was; for example the fields mallocs,nz_allocated,nz_used,nz_unneeded; You can also run with the option `-info` and look for messages with the string malloc in them to see if additional memory allocation was needed. The `MATSEQBAIJ` format is fully compatible with standard Fortran storage. That is, the stored row and column indices can begin at either one (as in Fortran) or zero. Specify the preallocated storage with either `nz` or `nnz` (not both). Set `nz` = `PETSC_DEFAULT` and `nnz` = `NULL` for PETSc to control dynamic memory allocation. See [Sparse Matrices](sec_matsparse) for details. .seealso: [](ch_matrices), `Mat`, [Sparse Matrices](sec_matsparse), `MatCreate()`, `MatCreateSeqAIJ()`, `MatSetValues()`, `MatCreateBAIJ()`, `MatGetInfo()` @*/ PetscErrorCode MatSeqBAIJSetPreallocation(Mat B, PetscInt bs, PetscInt nz, const PetscInt nnz[]) { PetscFunctionBegin; PetscValidHeaderSpecific(B, MAT_CLASSID, 1); PetscValidType(B, 1); PetscValidLogicalCollectiveInt(B, bs, 2); PetscTryMethod(B, "MatSeqBAIJSetPreallocation_C", (Mat, PetscInt, PetscInt, const PetscInt[]), (B, bs, nz, nnz)); PetscFunctionReturn(PETSC_SUCCESS); } /*@C MatSeqBAIJSetPreallocationCSR - Creates a sparse sequential matrix in `MATSEQBAIJ` format using the given nonzero structure and (optional) numerical values Collective Input Parameters: + B - the matrix . bs - the blocksize . i - the indices into `j` for the start of each local row (indices start with zero) . j - the column indices for each local row (indices start with zero) these must be sorted for each row - v - optional values in the matrix, use `NULL` if not provided Level: advanced Notes: The `i`,`j`,`v` values are COPIED with this routine; to avoid the copy use `MatCreateSeqBAIJWithArrays()` The order of the entries in values is specified by the `MatOption` `MAT_ROW_ORIENTED`. For example, C programs may want to use the default `MAT_ROW_ORIENTED` of `PETSC_TRUE` and use an array v[nnz][bs][bs] where the second index is over rows within a block and the last index is over columns within a block row. Fortran programs will likely set `MAT_ROW_ORIENTED` of `PETSC_FALSE` and use a Fortran array v(bs,bs,nnz) in which the first index is over rows within a block column and the second index is over columns within a block. Though this routine has Preallocation() in the name it also sets the exact nonzero locations of the matrix entries and usually the numerical values as well .seealso: [](ch_matrices), `Mat`, `MatCreate()`, `MatCreateSeqBAIJ()`, `MatSetValues()`, `MatSeqBAIJSetPreallocation()`, `MATSEQBAIJ` @*/ PetscErrorCode MatSeqBAIJSetPreallocationCSR(Mat B, PetscInt bs, const PetscInt i[], const PetscInt j[], const PetscScalar v[]) { PetscFunctionBegin; PetscValidHeaderSpecific(B, MAT_CLASSID, 1); PetscValidType(B, 1); PetscValidLogicalCollectiveInt(B, bs, 2); PetscTryMethod(B, "MatSeqBAIJSetPreallocationCSR_C", (Mat, PetscInt, const PetscInt[], const PetscInt[], const PetscScalar[]), (B, bs, i, j, v)); PetscFunctionReturn(PETSC_SUCCESS); } /*@ MatCreateSeqBAIJWithArrays - Creates a `MATSEQBAIJ` matrix using matrix elements provided by the user. Collective Input Parameters: + comm - must be an MPI communicator of size 1 . bs - size of block . m - number of rows . n - number of columns . i - row indices; that is i[0] = 0, i[row] = i[row-1] + number of elements in that row block row of the matrix . j - column indices - a - matrix values Output Parameter: . mat - the matrix Level: advanced Notes: The `i`, `j`, and `a` arrays are not copied by this routine, the user must free these arrays once the matrix is destroyed You cannot set new nonzero locations into this matrix, that will generate an error. The `i` and `j` indices are 0 based When block size is greater than 1 the matrix values must be stored using the `MATSEQBAIJ` storage format The order of the entries in values is the same as the block compressed sparse row storage format; that is, it is the same as a three dimensional array in Fortran values(bs,bs,nnz) that contains the first column of the first block, followed by the second column of the first block etc etc. That is, the blocks are contiguous in memory with column-major ordering within blocks. .seealso: [](ch_matrices), `Mat`, `MatCreate()`, `MatCreateBAIJ()`, `MatCreateSeqBAIJ()` @*/ PetscErrorCode MatCreateSeqBAIJWithArrays(MPI_Comm comm, PetscInt bs, PetscInt m, PetscInt n, PetscInt i[], PetscInt j[], PetscScalar a[], Mat *mat) { Mat_SeqBAIJ *baij; PetscFunctionBegin; PetscCheck(bs == 1, PETSC_COMM_SELF, PETSC_ERR_SUP, "block size %" PetscInt_FMT " > 1 is not supported yet", bs); if (m > 0) PetscCheck(i[0] == 0, PETSC_COMM_SELF, PETSC_ERR_ARG_OUTOFRANGE, "i (row indices) must start with 0"); PetscCall(MatCreate(comm, mat)); PetscCall(MatSetSizes(*mat, m, n, m, n)); PetscCall(MatSetType(*mat, MATSEQBAIJ)); PetscCall(MatSeqBAIJSetPreallocation(*mat, bs, MAT_SKIP_ALLOCATION, NULL)); baij = (Mat_SeqBAIJ *)(*mat)->data; PetscCall(PetscMalloc2(m, &baij->imax, m, &baij->ilen)); baij->i = i; baij->j = j; baij->a = a; baij->nonew = -1; /*this indicates that inserting a new value in the matrix that generates a new nonzero is an error*/ baij->free_a = PETSC_FALSE; baij->free_ij = PETSC_FALSE; baij->free_imax_ilen = PETSC_TRUE; for (PetscInt ii = 0; ii < m; ii++) { const PetscInt row_len = i[ii + 1] - i[ii]; baij->ilen[ii] = baij->imax[ii] = row_len; PetscCheck(row_len >= 0, PETSC_COMM_SELF, PETSC_ERR_ARG_OUTOFRANGE, "Negative row length in i (row indices) row = %" PetscInt_FMT " length = %" PetscInt_FMT, ii, row_len); } if (PetscDefined(USE_DEBUG)) { for (PetscInt ii = 0; ii < baij->i[m]; ii++) { PetscCheck(j[ii] >= 0, PETSC_COMM_SELF, PETSC_ERR_ARG_OUTOFRANGE, "Negative column index at location = %" PetscInt_FMT " index = %" PetscInt_FMT, ii, j[ii]); PetscCheck(j[ii] <= n - 1, PETSC_COMM_SELF, PETSC_ERR_ARG_OUTOFRANGE, "Column index to large at location = %" PetscInt_FMT " index = %" PetscInt_FMT, ii, j[ii]); } } PetscCall(MatAssemblyBegin(*mat, MAT_FINAL_ASSEMBLY)); PetscCall(MatAssemblyEnd(*mat, MAT_FINAL_ASSEMBLY)); PetscFunctionReturn(PETSC_SUCCESS); } PetscErrorCode MatCreateMPIMatConcatenateSeqMat_SeqBAIJ(MPI_Comm comm, Mat inmat, PetscInt n, MatReuse scall, Mat *outmat) { PetscFunctionBegin; PetscCall(MatCreateMPIMatConcatenateSeqMat_MPIBAIJ(comm, inmat, n, scall, outmat)); PetscFunctionReturn(PETSC_SUCCESS); }