Actual source code: baijsolvtrannat5.c
1: #include <../src/mat/impls/baij/seq/baij.h>
3: PetscErrorCode MatSolveTranspose_SeqBAIJ_5_NaturalOrdering_inplace(Mat A,Vec bb,Vec xx)
4: {
5: Mat_SeqBAIJ *a=(Mat_SeqBAIJ*)A->data;
6: const PetscInt *diag=a->diag,n=a->mbs,*vi,*ai=a->i,*aj=a->j;
7: PetscInt i,nz,idx,idt,oidx;
8: const MatScalar *aa=a->a,*v;
9: PetscScalar s1,s2,s3,s4,s5,x1,x2,x3,x4,x5,*x;
11: VecCopy(bb,xx);
12: VecGetArray(xx,&x);
14: /* forward solve the U^T */
15: idx = 0;
16: for (i=0; i<n; i++) {
18: v = aa + 25*diag[i];
19: /* multiply by the inverse of the block diagonal */
20: x1 = x[idx]; x2 = x[1+idx]; x3 = x[2+idx]; x4 = x[3+idx]; x5 = x[4+idx];
21: s1 = v[0]*x1 + v[1]*x2 + v[2]*x3 + v[3]*x4 + v[4]*x5;
22: s2 = v[5]*x1 + v[6]*x2 + v[7]*x3 + v[8]*x4 + v[9]*x5;
23: s3 = v[10]*x1 + v[11]*x2 + v[12]*x3 + v[13]*x4 + v[14]*x5;
24: s4 = v[15]*x1 + v[16]*x2 + v[17]*x3 + v[18]*x4 + v[19]*x5;
25: s5 = v[20]*x1 + v[21]*x2 + v[22]*x3 + v[23]*x4 + v[24]*x5;
26: v += 25;
28: vi = aj + diag[i] + 1;
29: nz = ai[i+1] - diag[i] - 1;
30: while (nz--) {
31: oidx = 5*(*vi++);
32: x[oidx] -= v[0]*s1 + v[1]*s2 + v[2]*s3 + v[3]*s4 + v[4]*s5;
33: x[oidx+1] -= v[5]*s1 + v[6]*s2 + v[7]*s3 + v[8]*s4 + v[9]*s5;
34: x[oidx+2] -= v[10]*s1 + v[11]*s2 + v[12]*s3 + v[13]*s4 + v[14]*s5;
35: x[oidx+3] -= v[15]*s1 + v[16]*s2 + v[17]*s3 + v[18]*s4 + v[19]*s5;
36: x[oidx+4] -= v[20]*s1 + v[21]*s2 + v[22]*s3 + v[23]*s4 + v[24]*s5;
37: v += 25;
38: }
39: x[idx] = s1;x[1+idx] = s2; x[2+idx] = s3;x[3+idx] = s4; x[4+idx] = s5;
40: idx += 5;
41: }
42: /* backward solve the L^T */
43: for (i=n-1; i>=0; i--) {
44: v = aa + 25*diag[i] - 25;
45: vi = aj + diag[i] - 1;
46: nz = diag[i] - ai[i];
47: idt = 5*i;
48: s1 = x[idt]; s2 = x[1+idt]; s3 = x[2+idt];s4 = x[3+idt]; s5 = x[4+idt];
49: while (nz--) {
50: idx = 5*(*vi--);
51: x[idx] -= v[0]*s1 + v[1]*s2 + v[2]*s3 + v[3]*s4 + v[4]*s5;
52: x[idx+1] -= v[5]*s1 + v[6]*s2 + v[7]*s3 + v[8]*s4 + v[9]*s5;
53: x[idx+2] -= v[10]*s1 + v[11]*s2 + v[12]*s3 + v[13]*s4 + v[14]*s5;
54: x[idx+3] -= v[15]*s1 + v[16]*s2 + v[17]*s3 + v[18]*s4 + v[19]*s5;
55: x[idx+4] -= v[20]*s1 + v[21]*s2 + v[22]*s3 + v[23]*s4 + v[24]*s5;
56: v -= 25;
57: }
58: }
59: VecRestoreArray(xx,&x);
60: PetscLogFlops(2.0*25*(a->nz) - 5.0*A->cmap->n);
61: return 0;
62: }
64: PetscErrorCode MatSolveTranspose_SeqBAIJ_5_NaturalOrdering(Mat A,Vec bb,Vec xx)
65: {
66: Mat_SeqBAIJ *a=(Mat_SeqBAIJ*)A->data;
67: const PetscInt n=a->mbs,*vi,*ai=a->i,*aj=a->j,*diag=a->diag;
68: PetscInt nz,idx,idt,j,i,oidx;
69: const PetscInt bs =A->rmap->bs,bs2=a->bs2;
70: const MatScalar *aa=a->a,*v;
71: PetscScalar s1,s2,s3,s4,s5,x1,x2,x3,x4,x5,*x;
73: VecCopy(bb,xx);
74: VecGetArray(xx,&x);
76: /* forward solve the U^T */
77: idx = 0;
78: for (i=0; i<n; i++) {
79: v = aa + bs2*diag[i];
80: /* multiply by the inverse of the block diagonal */
81: x1 = x[idx]; x2 = x[1+idx]; x3 = x[2+idx]; x4 = x[3+idx];
82: x5 = x[4+idx];
83: s1 = v[0]*x1 + v[1]*x2 + v[2]*x3 + v[3]*x4 + v[4]*x5;
84: s2 = v[5]*x1 + v[6]*x2 + v[7]*x3 + v[8]*x4 + v[9]*x5;
85: s3 = v[10]*x1 + v[11]*x2 + v[12]*x3 + v[13]*x4 + v[14]*x5;
86: s4 = v[15]*x1 + v[16]*x2 + v[17]*x3 + v[18]*x4 + v[19]*x5;
87: s5 = v[20]*x1 + v[21]*x2 + v[22]*x3 + v[23]*x4 + v[24]*x5;
88: v -= bs2;
90: vi = aj + diag[i] - 1;
91: nz = diag[i] - diag[i+1] - 1;
92: for (j=0; j>-nz; j--) {
93: oidx = bs*vi[j];
94: x[oidx] -= v[0]*s1 + v[1]*s2 + v[2]*s3 + v[3]*s4 + v[4]*s5;
95: x[oidx+1] -= v[5]*s1 + v[6]*s2 + v[7]*s3 + v[8]*s4 + v[9]*s5;
96: x[oidx+2] -= v[10]*s1 + v[11]*s2 + v[12]*s3 + v[13]*s4 + v[14]*s5;
97: x[oidx+3] -= v[15]*s1 + v[16]*s2 + v[17]*s3 + v[18]*s4 + v[19]*s5;
98: x[oidx+4] -= v[20]*s1 + v[21]*s2 + v[22]*s3 + v[23]*s4 + v[24]*s5;
99: v -= bs2;
100: }
101: x[idx] = s1;x[1+idx] = s2; x[2+idx] = s3; x[3+idx] = s4; x[4+idx] = s5;
102: idx += bs;
103: }
104: /* backward solve the L^T */
105: for (i=n-1; i>=0; i--) {
106: v = aa + bs2*ai[i];
107: vi = aj + ai[i];
108: nz = ai[i+1] - ai[i];
109: idt = bs*i;
110: s1 = x[idt]; s2 = x[1+idt]; s3 = x[2+idt]; s4 = x[3+idt]; s5 = x[4+idt];
111: for (j=0; j<nz; j++) {
112: idx = bs*vi[j];
113: x[idx] -= v[0]*s1 + v[1]*s2 + v[2]*s3 + v[3]*s4 + v[4]*s5;
114: x[idx+1] -= v[5]*s1 + v[6]*s2 + v[7]*s3 + v[8]*s4 + v[9]*s5;
115: x[idx+2] -= v[10]*s1 + v[11]*s2 + v[12]*s3 + v[13]*s4 + v[14]*s5;
116: x[idx+3] -= v[15]*s1 + v[16]*s2 + v[17]*s3 + v[18]*s4 + v[19]*s5;
117: x[idx+4] -= v[20]*s1 + v[21]*s2 + v[22]*s3 + v[23]*s4 + v[24]*s5;
118: v += bs2;
119: }
120: }
121: VecRestoreArray(xx,&x);
122: PetscLogFlops(2.0*bs2*(a->nz) - bs*A->cmap->n);
123: return 0;
124: }