Date: 2013-07-02T14:43:31+00:00

Actual source code: relax.h
petsc-3.4.2 2013-07-02

      2: /*
      3:     This is included by sbaij.c to generate unsigned short and regular versions of these two functions
      4: */
      6: #if defined(USESHORT)
      8: PetscErrorCode MatMult_SeqSBAIJ_1_Hermitian_ushort(Mat A,Vec xx,Vec zz)
      9: #else
     11: PetscErrorCode MatMult_SeqSBAIJ_1_Hermitian(Mat A,Vec xx,Vec zz)
     12: #endif
     13: {
     14:   Mat_SeqSBAIJ      *a = (Mat_SeqSBAIJ*)A->data;
     15:   const PetscScalar *x;
     16:   PetscScalar       *z,x1,sum;
     17:   const MatScalar   *v;
     18:   MatScalar         vj;
     19:   PetscErrorCode    ierr;
     20:   PetscInt          mbs=a->mbs,i,j,nz;
     21:   const PetscInt    *ai=a->i;
     22: #if defined(USESHORT)
     23:   const unsigned short *ib=a->jshort;
     24:   unsigned short       ibt;
     25: #else
     26:   const PetscInt *ib=a->j;
     27:   PetscInt       ibt;
     28: #endif
     29:   PetscInt nonzerorow = 0,jmin;

     32:   VecSet(zz,0.0);
     33:   VecGetArrayRead(xx,&x);
     34:   VecGetArray(zz,&z);

     36:   v = a->a;
     37:   for (i=0; i<mbs; i++) {
     38:     nz = ai[i+1] - ai[i];    /* length of i_th row of A */
     39:     if (!nz) continue; /* Move to the next row if the current row is empty */
     40:     nonzerorow++;
     41:     x1   = x[i];
     42:     sum  = 0.0;
     43:     jmin = 0;
     44:     if (ib[0] == i) {
     45:       sum = v[0]*x1;           /* diagonal term */
     46:       jmin++;
     47:     }
     48:     for (j=jmin; j<nz; j++) {
     49:       ibt     = ib[j];
     50:       vj      = v[j];
     51:       sum    += vj * x[ibt]; /* (strict upper triangular part of A)*x  */
     52:       z[ibt] += PetscConj(v[j]) * x1;    /* (strict lower triangular part of A)*x  */
     53:     }
     54:     z[i] += sum;
     55:     v    +=    nz;
     56:     ib   += nz;
     57:   }

     59:   VecRestoreArrayRead(xx,&x);
     60:   VecRestoreArray(zz,&z);
     61:   PetscLogFlops(2.0*(2.0*a->nz - nonzerorow) - nonzerorow);
     62:   return(0);
     63: }

     66: #if defined(USESHORT)
     68: PetscErrorCode MatMult_SeqSBAIJ_1_ushort(Mat A,Vec xx,Vec zz)
     69: #else
     71: PetscErrorCode MatMult_SeqSBAIJ_1(Mat A,Vec xx,Vec zz)
     72: #endif
     73: {
     74:   Mat_SeqSBAIJ      *a = (Mat_SeqSBAIJ*)A->data;
     75:   const PetscScalar *x;
     76:   PetscScalar       *z,x1,sum;
     77:   const MatScalar   *v;
     78:   MatScalar         vj;
     79:   PetscErrorCode    ierr;
     80:   PetscInt          mbs=a->mbs,i,j,nz;
     81:   const PetscInt    *ai=a->i;
     82: #if defined(USESHORT)
     83:   const unsigned short *ib=a->jshort;
     84:   unsigned short       ibt;
     85: #else
     86:   const PetscInt *ib=a->j;
     87:   PetscInt       ibt;
     88: #endif
     89:   PetscInt nonzerorow=0,jmin;

     92:   VecSet(zz,0.0);
     93:   VecGetArrayRead(xx,&x);
     94:   VecGetArray(zz,&z);

     96:   v = a->a;
     97:   for (i=0; i<mbs; i++) {
     98:     nz = ai[i+1] - ai[i];          /* length of i_th row of A */
     99:     if (!nz) continue; /* Move to the next row if the current row is empty */
    100:     nonzerorow++;
    101:     sum  = 0.0;
    102:     jmin = 0;
    103:     x1   = x[i];
    104:     if (ib[0] == i) {
    105:       sum = v[0]*x1;                 /* diagonal term */
    106:       jmin++;
    107:     }
    108:     PetscPrefetchBlock(ib+nz,nz,0,PETSC_PREFETCH_HINT_NTA); /* Indices for the next row (assumes same size as this one) */
    109:     PetscPrefetchBlock(v+nz,nz,0,PETSC_PREFETCH_HINT_NTA);  /* Entries for the next row */
    110:     for (j=jmin; j<nz; j++) {
    111:       ibt     = ib[j];
    112:       vj      = v[j];
    113:       z[ibt] += vj * x1;       /* (strict lower triangular part of A)*x  */
    114:       sum    += vj * x[ibt];   /* (strict upper triangular part of A)*x  */
    115:     }
    116:     z[i] += sum;
    117:     v    += nz;
    118:     ib   += nz;
    119:   }

    121:   VecRestoreArrayRead(xx,&x);
    122:   VecRestoreArray(zz,&z);
    123:   PetscLogFlops(2.0*(2.0*a->nz - nonzerorow) - nonzerorow);
    124:   return(0);
    125: }

    128: #if defined(USESHORT)
    130: PetscErrorCode MatSOR_SeqSBAIJ_ushort(Mat A,Vec bb,PetscReal omega,MatSORType flag,PetscReal fshift,PetscInt its,PetscInt lits,Vec xx)
    131: #else
    133: PetscErrorCode MatSOR_SeqSBAIJ(Mat A,Vec bb,PetscReal omega,MatSORType flag,PetscReal fshift,PetscInt its,PetscInt lits,Vec xx)
    134: #endif
    135: {
    136:   Mat_SeqSBAIJ      *a = (Mat_SeqSBAIJ*)A->data;
    137:   const MatScalar   *aa=a->a,*v,*v1,*aidiag;
    138:   PetscScalar       *x,*t,sum;
    139:   const PetscScalar *b;
    140:   MatScalar         tmp;
    141:   PetscErrorCode    ierr;
    142:   PetscInt          m  =a->mbs,bs=A->rmap->bs,j;
    143:   const PetscInt    *ai=a->i;
    144: #if defined(USESHORT)
    145:   const unsigned short *aj=a->jshort,*vj,*vj1;
    146: #else
    147:   const PetscInt *aj=a->j,*vj,*vj1;
    148: #endif
    149:   PetscInt nz,nz1,i;

    152:   if (flag & SOR_EISENSTAT) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"No support yet for Eisenstat");

    154:   its = its*lits;
    155:   if (its <= 0) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONG,"Relaxation requires global its %D and local its %D both positive",its,lits);

    157:   if (bs > 1) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"SSOR for block size > 1 is not yet implemented");

    159:   VecGetArray(xx,&x);
    160:   VecGetArrayRead(bb,&b);

    162:   if (!a->idiagvalid) {
    163:     if (!a->idiag) {
    164:       PetscMalloc(m*sizeof(PetscScalar),&a->idiag);
    165:     }
    166:     for (i=0; i<a->mbs; i++) a->idiag[i] = 1.0/a->a[a->i[i]];
    167:     a->idiagvalid = PETSC_TRUE;
    168:   }

    170:   if (!a->sor_work) {
    171:     PetscMalloc(m*sizeof(PetscScalar),&a->sor_work);
    172:   }
    173:   t = a->sor_work;

    175:   aidiag = a->idiag;

    177:   if (flag == SOR_APPLY_UPPER) {
    178:     /* apply (U + D/omega) to the vector */
    179:     PetscScalar d;
    180:     for (i=0; i<m; i++) {
    181:       d   = fshift + aa[ai[i]];
    182:       nz  = ai[i+1] - ai[i] - 1;
    183:       vj  = aj + ai[i] + 1;
    184:       v   = aa + ai[i] + 1;
    185:       sum = b[i]*d/omega;
    186:       PetscSparseDensePlusDot(sum,b,v,vj,nz);
    187:       x[i] = sum;
    188:     }
    189:     PetscLogFlops(a->nz);
    190:   }

    192:   if (flag & SOR_ZERO_INITIAL_GUESS) {
    193:     if (flag & SOR_FORWARD_SWEEP || flag & SOR_LOCAL_FORWARD_SWEEP) {
    194:       PetscMemcpy(t,b,m*sizeof(PetscScalar));

    196:       v  = aa + 1;
    197:       vj = aj + 1;
    198:       for (i=0; i<m; i++) {
    199:         nz  = ai[i+1] - ai[i] - 1;
    200:         tmp = -(x[i] = omega*t[i]*aidiag[i]);
    201:         for (j=0; j<nz; j++) t[vj[j]] += tmp*v[j];
    202:         v  += nz + 1;
    203:         vj += nz + 1;
    204:       }
    205:       PetscLogFlops(2*a->nz);
    206:     }

    208:     if (flag & SOR_BACKWARD_SWEEP || flag & SOR_LOCAL_BACKWARD_SWEEP) {
    209:       int nz2;
    210:       if (!(flag & SOR_FORWARD_SWEEP || flag & SOR_LOCAL_FORWARD_SWEEP)) {
    211: #if defined(PETSC_USE_BACKWARD_LOOP)
    212:         v  = aa + ai[m] - 1;
    213:         vj = aj + ai[m] - 1;
    214:         for (i=m-1; i>=0; i--) {
    215:           sum = b[i];
    216:           nz  = ai[i+1] - ai[i] - 1;
    217:           {PetscInt __i;for (__i=0; __i<nz; __i++) sum -= v[-__i] * x[vj[-__i]];}
    218: #else
    219:         v  = aa + ai[m-1] + 1;
    220:         vj = aj + ai[m-1] + 1;
    221:         nz = 0;
    222:         for (i=m-1; i>=0; i--) {
    223:           sum = b[i];
    224:           nz2 = ai[i] - ai[i-1] - 1;
    225:           PETSC_Prefetch(v-nz2-1,0,PETSC_PREFETCH_HINT_NTA);
    226:           PETSC_Prefetch(vj-nz2-1,0,PETSC_PREFETCH_HINT_NTA);
    227:           PetscSparseDenseMinusDot(sum,x,v,vj,nz);
    228:           nz = nz2;
    229: #endif
    230:           x[i] = omega*sum*aidiag[i];
    231:           v   -= nz + 1;
    232:           vj  -= nz + 1;
    233:         }
    234:         PetscLogFlops(2*a->nz);
    235:       } else {
    236:         v  = aa + ai[m-1] + 1;
    237:         vj = aj + ai[m-1] + 1;
    238:         nz = 0;
    239:         for (i=m-1; i>=0; i--) {
    240:           sum = t[i];
    241:           nz2 = ai[i] - ai[i-1] - 1;
    242:           PETSC_Prefetch(v-nz2-1,0,PETSC_PREFETCH_HINT_NTA);
    243:           PETSC_Prefetch(vj-nz2-1,0,PETSC_PREFETCH_HINT_NTA);
    244:           PetscSparseDenseMinusDot(sum,x,v,vj,nz);
    245:           x[i] = (1-omega)*x[i] + omega*sum*aidiag[i];
    246:           nz   = nz2;
    247:           v   -= nz + 1;
    248:           vj  -= nz + 1;
    249:         }
    250:         PetscLogFlops(2*a->nz);
    251:       }
    252:     }
    253:     its--;
    254:   }

    256:   while (its--) {
    257:     /*
    258:        forward sweep:
    259:        for i=0,...,m-1:
    260:          sum[i] = (b[i] - U(i,:)x)/d[i];
    261:          x[i]   = (1-omega)x[i] + omega*sum[i];
    262:          b      = b - x[i]*U^T(i,:);

    264:     */
    265:     if (flag & SOR_FORWARD_SWEEP || flag & SOR_LOCAL_FORWARD_SWEEP) {
    266:       PetscMemcpy(t,b,m*sizeof(PetscScalar));

    268:       for (i=0; i<m; i++) {
    269:         v    = aa + ai[i] + 1; v1=v;
    270:         vj   = aj + ai[i] + 1; vj1=vj;
    271:         nz   = ai[i+1] - ai[i] - 1; nz1=nz;
    272:         sum  = t[i];
    273:         PetscLogFlops(4.0*nz-2);
    274:         while (nz1--) sum -= (*v1++)*x[*vj1++];
    275:         x[i] = (1-omega)*x[i] + omega*sum*aidiag[i];
    276:         while (nz--) t[*vj++] -= x[i]*(*v++);
    277:       }
    278:     }

    280:     if (flag & SOR_BACKWARD_SWEEP || flag & SOR_LOCAL_BACKWARD_SWEEP) {
    281:       /*
    282:        backward sweep:
    283:        b = b - x[i]*U^T(i,:), i=0,...,n-2
    284:        for i=m-1,...,0:
    285:          sum[i] = (b[i] - U(i,:)x)/d[i];
    286:          x[i]   = (1-omega)x[i] + omega*sum[i];
    287:       */
    288:       /* if there was a forward sweep done above then I thing the next two for loops are not needed */
    289:       PetscMemcpy(t,b,m*sizeof(PetscScalar));

    291:       for (i=0; i<m-1; i++) {  /* update rhs */
    292:         v    = aa + ai[i] + 1;
    293:         vj   = aj + ai[i] + 1;
    294:         nz   = ai[i+1] - ai[i] - 1;
    295:         PetscLogFlops(2.0*nz-1);
    296:         while (nz--) t[*vj++] -= x[i]*(*v++);
    297:       }
    298:       for (i=m-1; i>=0; i--) {
    299:         v    = aa + ai[i] + 1;
    300:         vj   = aj + ai[i] + 1;
    301:         nz   = ai[i+1] - ai[i] - 1;
    302:         PetscLogFlops(2.0*nz-1);
    303:         sum  = t[i];
    304:         while (nz--) sum -= x[*vj++]*(*v++);
    305:         x[i] =   (1-omega)*x[i] + omega*sum*aidiag[i];
    306:       }
    307:     }
    308:   }

    310:   VecRestoreArray(xx,&x);
    311:   VecRestoreArrayRead(bb,&b);
    312:   return(0);
    313: }