Actual source code: baijsolvnat5.c

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

  4: PetscErrorCode MatSolve_SeqBAIJ_5_NaturalOrdering_inplace(Mat A, Vec bb, Vec xx)
  5: {
  6:   Mat_SeqBAIJ       *a    = (Mat_SeqBAIJ *)A->data;
  7:   const PetscInt    *diag = a->diag, n = a->mbs, *vi, *ai = a->i, *aj = a->j;
  8:   PetscInt           i, nz, idx, idt, jdx;
  9:   const MatScalar   *aa = a->a, *v;
 10:   PetscScalar       *x, s1, s2, s3, s4, s5, x1, x2, x3, x4, x5;
 11:   const PetscScalar *b;

 13:   VecGetArrayRead(bb, &b);
 14:   VecGetArray(xx, &x);
 15:   /* forward solve the lower triangular */
 16:   idx  = 0;
 17:   x[0] = b[idx];
 18:   x[1] = b[1 + idx];
 19:   x[2] = b[2 + idx];
 20:   x[3] = b[3 + idx];
 21:   x[4] = b[4 + idx];
 22:   for (i = 1; i < n; i++) {
 23:     v   = aa + 25 * ai[i];
 24:     vi  = aj + ai[i];
 25:     nz  = diag[i] - ai[i];
 26:     idx = 5 * i;
 27:     s1  = b[idx];
 28:     s2  = b[1 + idx];
 29:     s3  = b[2 + idx];
 30:     s4  = b[3 + idx];
 31:     s5  = b[4 + idx];
 32:     while (nz--) {
 33:       jdx = 5 * (*vi++);
 34:       x1  = x[jdx];
 35:       x2  = x[1 + jdx];
 36:       x3  = x[2 + jdx];
 37:       x4  = x[3 + jdx];
 38:       x5  = x[4 + jdx];
 39:       s1 -= v[0] * x1 + v[5] * x2 + v[10] * x3 + v[15] * x4 + v[20] * x5;
 40:       s2 -= v[1] * x1 + v[6] * x2 + v[11] * x3 + v[16] * x4 + v[21] * x5;
 41:       s3 -= v[2] * x1 + v[7] * x2 + v[12] * x3 + v[17] * x4 + v[22] * x5;
 42:       s4 -= v[3] * x1 + v[8] * x2 + v[13] * x3 + v[18] * x4 + v[23] * x5;
 43:       s5 -= v[4] * x1 + v[9] * x2 + v[14] * x3 + v[19] * x4 + v[24] * x5;
 44:       v += 25;
 45:     }
 46:     x[idx]     = s1;
 47:     x[1 + idx] = s2;
 48:     x[2 + idx] = s3;
 49:     x[3 + idx] = s4;
 50:     x[4 + idx] = s5;
 51:   }
 52:   /* backward solve the upper triangular */
 53:   for (i = n - 1; i >= 0; i--) {
 54:     v   = aa + 25 * diag[i] + 25;
 55:     vi  = aj + diag[i] + 1;
 56:     nz  = ai[i + 1] - diag[i] - 1;
 57:     idt = 5 * i;
 58:     s1  = x[idt];
 59:     s2  = x[1 + idt];
 60:     s3  = x[2 + idt];
 61:     s4  = x[3 + idt];
 62:     s5  = x[4 + idt];
 63:     while (nz--) {
 64:       idx = 5 * (*vi++);
 65:       x1  = x[idx];
 66:       x2  = x[1 + idx];
 67:       x3  = x[2 + idx];
 68:       x4  = x[3 + idx];
 69:       x5  = x[4 + idx];
 70:       s1 -= v[0] * x1 + v[5] * x2 + v[10] * x3 + v[15] * x4 + v[20] * x5;
 71:       s2 -= v[1] * x1 + v[6] * x2 + v[11] * x3 + v[16] * x4 + v[21] * x5;
 72:       s3 -= v[2] * x1 + v[7] * x2 + v[12] * x3 + v[17] * x4 + v[22] * x5;
 73:       s4 -= v[3] * x1 + v[8] * x2 + v[13] * x3 + v[18] * x4 + v[23] * x5;
 74:       s5 -= v[4] * x1 + v[9] * x2 + v[14] * x3 + v[19] * x4 + v[24] * x5;
 75:       v += 25;
 76:     }
 77:     v          = aa + 25 * diag[i];
 78:     x[idt]     = v[0] * s1 + v[5] * s2 + v[10] * s3 + v[15] * s4 + v[20] * s5;
 79:     x[1 + idt] = v[1] * s1 + v[6] * s2 + v[11] * s3 + v[16] * s4 + v[21] * s5;
 80:     x[2 + idt] = v[2] * s1 + v[7] * s2 + v[12] * s3 + v[17] * s4 + v[22] * s5;
 81:     x[3 + idt] = v[3] * s1 + v[8] * s2 + v[13] * s3 + v[18] * s4 + v[23] * s5;
 82:     x[4 + idt] = v[4] * s1 + v[9] * s2 + v[14] * s3 + v[19] * s4 + v[24] * s5;
 83:   }

 85:   VecRestoreArrayRead(bb, &b);
 86:   VecRestoreArray(xx, &x);
 87:   PetscLogFlops(2.0 * 25 * (a->nz) - 5.0 * A->cmap->n);
 88:   return 0;
 89: }

 91: PetscErrorCode MatSolve_SeqBAIJ_5_NaturalOrdering(Mat A, Vec bb, Vec xx)
 92: {
 93:   Mat_SeqBAIJ       *a = (Mat_SeqBAIJ *)A->data;
 94:   const PetscInt     n = a->mbs, *vi, *ai = a->i, *aj = a->j, *adiag = a->diag;
 95:   PetscInt           i, k, nz, idx, idt, jdx;
 96:   const MatScalar   *aa = a->a, *v;
 97:   PetscScalar       *x, s1, s2, s3, s4, s5, x1, x2, x3, x4, x5;
 98:   const PetscScalar *b;

100:   VecGetArrayRead(bb, &b);
101:   VecGetArray(xx, &x);
102:   /* forward solve the lower triangular */
103:   idx  = 0;
104:   x[0] = b[idx];
105:   x[1] = b[1 + idx];
106:   x[2] = b[2 + idx];
107:   x[3] = b[3 + idx];
108:   x[4] = b[4 + idx];
109:   for (i = 1; i < n; i++) {
110:     v   = aa + 25 * ai[i];
111:     vi  = aj + ai[i];
112:     nz  = ai[i + 1] - ai[i];
113:     idx = 5 * i;
114:     s1  = b[idx];
115:     s2  = b[1 + idx];
116:     s3  = b[2 + idx];
117:     s4  = b[3 + idx];
118:     s5  = b[4 + idx];
119:     for (k = 0; k < nz; k++) {
120:       jdx = 5 * vi[k];
121:       x1  = x[jdx];
122:       x2  = x[1 + jdx];
123:       x3  = x[2 + jdx];
124:       x4  = x[3 + jdx];
125:       x5  = x[4 + jdx];
126:       s1 -= v[0] * x1 + v[5] * x2 + v[10] * x3 + v[15] * x4 + v[20] * x5;
127:       s2 -= v[1] * x1 + v[6] * x2 + v[11] * x3 + v[16] * x4 + v[21] * x5;
128:       s3 -= v[2] * x1 + v[7] * x2 + v[12] * x3 + v[17] * x4 + v[22] * x5;
129:       s4 -= v[3] * x1 + v[8] * x2 + v[13] * x3 + v[18] * x4 + v[23] * x5;
130:       s5 -= v[4] * x1 + v[9] * x2 + v[14] * x3 + v[19] * x4 + v[24] * x5;
131:       v += 25;
132:     }
133:     x[idx]     = s1;
134:     x[1 + idx] = s2;
135:     x[2 + idx] = s3;
136:     x[3 + idx] = s4;
137:     x[4 + idx] = s5;
138:   }

140:   /* backward solve the upper triangular */
141:   for (i = n - 1; i >= 0; i--) {
142:     v   = aa + 25 * (adiag[i + 1] + 1);
143:     vi  = aj + adiag[i + 1] + 1;
144:     nz  = adiag[i] - adiag[i + 1] - 1;
145:     idt = 5 * i;
146:     s1  = x[idt];
147:     s2  = x[1 + idt];
148:     s3  = x[2 + idt];
149:     s4  = x[3 + idt];
150:     s5  = x[4 + idt];
151:     for (k = 0; k < nz; k++) {
152:       idx = 5 * vi[k];
153:       x1  = x[idx];
154:       x2  = x[1 + idx];
155:       x3  = x[2 + idx];
156:       x4  = x[3 + idx];
157:       x5  = x[4 + idx];
158:       s1 -= v[0] * x1 + v[5] * x2 + v[10] * x3 + v[15] * x4 + v[20] * x5;
159:       s2 -= v[1] * x1 + v[6] * x2 + v[11] * x3 + v[16] * x4 + v[21] * x5;
160:       s3 -= v[2] * x1 + v[7] * x2 + v[12] * x3 + v[17] * x4 + v[22] * x5;
161:       s4 -= v[3] * x1 + v[8] * x2 + v[13] * x3 + v[18] * x4 + v[23] * x5;
162:       s5 -= v[4] * x1 + v[9] * x2 + v[14] * x3 + v[19] * x4 + v[24] * x5;
163:       v += 25;
164:     }
165:     /* x = inv_diagonal*x */
166:     x[idt]     = v[0] * s1 + v[5] * s2 + v[10] * s3 + v[15] * s4 + v[20] * s5;
167:     x[1 + idt] = v[1] * s1 + v[6] * s2 + v[11] * s3 + v[16] * s4 + v[21] * s5;
168:     x[2 + idt] = v[2] * s1 + v[7] * s2 + v[12] * s3 + v[17] * s4 + v[22] * s5;
169:     x[3 + idt] = v[3] * s1 + v[8] * s2 + v[13] * s3 + v[18] * s4 + v[23] * s5;
170:     x[4 + idt] = v[4] * s1 + v[9] * s2 + v[14] * s3 + v[19] * s4 + v[24] * s5;
171:   }

173:   VecRestoreArrayRead(bb, &b);
174:   VecRestoreArray(xx, &x);
175:   PetscLogFlops(2.0 * 25 * (a->nz) - 5.0 * A->cmap->n);
176:   return 0;
177: }