Actual source code: baij.c
petsc-3.10.5 2019-03-28
Report Typos and Errors

      2: /*
      3:     Defines the basic matrix operations for the BAIJ (compressed row)
      4:   matrix storage format.
      5: */
      6:  #include <../src/mat/impls/baij/seq/baij.h>
      7:  #include <petscblaslapack.h>
      8:  #include <petsc/private/kernels/blockinvert.h>
      9:  #include <petsc/private/kernels/blockmatmult.h>

     11: #if defined(PETSC_HAVE_HYPRE)
     12: PETSC_INTERN PetscErrorCode MatConvert_AIJ_HYPRE(Mat,MatType,MatReuse,Mat*);
     13: #endif

     15: #if defined(PETSC_HAVE_MKL_SPARSE_OPTIMIZE)
     16: PETSC_INTERN PetscErrorCode MatConvert_SeqBAIJ_SeqBAIJMKL(Mat,MatType,MatReuse,Mat*);
     17: #endif
     18: PETSC_INTERN PetscErrorCode MatConvert_XAIJ_IS(Mat,MatType,MatReuse,Mat*);
     19: PETSC_INTERN PetscErrorCode MatPtAP_IS_XAIJ(Mat,Mat,MatReuse,PetscReal,Mat*);

     21: PetscErrorCode MatInvertBlockDiagonal_SeqBAIJ(Mat A,const PetscScalar **values)
     22: {
     23:   Mat_SeqBAIJ    *a = (Mat_SeqBAIJ*) A->data;
     25:   PetscInt       *diag_offset,i,bs = A->rmap->bs,mbs = a->mbs,ipvt[5],bs2 = bs*bs,*v_pivots;
     26:   MatScalar      *v    = a->a,*odiag,*diag,work[25],*v_work;
     27:   PetscReal      shift = 0.0;
     28:   PetscBool      allowzeropivot,zeropivotdetected=PETSC_FALSE;

     31:   allowzeropivot = PetscNot(A->erroriffailure);

     33:   if (a->idiagvalid) {
     34:     if (values) *values = a->idiag;
     35:     return(0);
     36:   }
     37:   MatMarkDiagonal_SeqBAIJ(A);
     38:   diag_offset = a->diag;
     39:   if (!a->idiag) {
     40:     PetscMalloc1(bs2*mbs,&a->idiag);
     41:     PetscLogObjectMemory((PetscObject)A,bs2*mbs*sizeof(PetscScalar));
     42:   }
     43:   diag  = a->idiag;
     44:   if (values) *values = a->idiag;
     45:   /* factor and invert each block */
     46:   switch (bs) {
     47:   case 1:
     48:     for (i=0; i<mbs; i++) {
     49:       odiag    = v + 1*diag_offset[i];
     50:       diag[0]  = odiag[0];

     52:       if (PetscAbsScalar(diag[0] + shift) < PETSC_MACHINE_EPSILON) {
     53:         if (allowzeropivot) {
     54:           A->factorerrortype             = MAT_FACTOR_NUMERIC_ZEROPIVOT;
     55:           A->factorerror_zeropivot_value = PetscAbsScalar(diag[0]);
     56:           A->factorerror_zeropivot_row   = i;
     57:           PetscInfo1(A,"Zero pivot, row %D\n",i);
     58:         } else SETERRQ3(PETSC_COMM_SELF,PETSC_ERR_MAT_LU_ZRPVT,"Zero pivot, row %D pivot value %g tolerance %g",i,(double)PetscAbsScalar(diag[0]),(double)PETSC_MACHINE_EPSILON);
     59:       }

     61:       diag[0]  = (PetscScalar)1.0 / (diag[0] + shift);
     62:       diag    += 1;
     63:     }
     64:     break;
     65:   case 2:
     66:     for (i=0; i<mbs; i++) {
     67:       odiag    = v + 4*diag_offset[i];
     68:       diag[0]  = odiag[0]; diag[1] = odiag[1]; diag[2] = odiag[2]; diag[3] = odiag[3];
     69:       PetscKernel_A_gets_inverse_A_2(diag,shift,allowzeropivot,&zeropivotdetected);
     70:       if (zeropivotdetected) A->factorerrortype = MAT_FACTOR_NUMERIC_ZEROPIVOT;
     71:       diag    += 4;
     72:     }
     73:     break;
     74:   case 3:
     75:     for (i=0; i<mbs; i++) {
     76:       odiag    = v + 9*diag_offset[i];
     77:       diag[0]  = odiag[0]; diag[1] = odiag[1]; diag[2] = odiag[2]; diag[3] = odiag[3];
     78:       diag[4]  = odiag[4]; diag[5] = odiag[5]; diag[6] = odiag[6]; diag[7] = odiag[7];
     79:       diag[8]  = odiag[8];
     80:       PetscKernel_A_gets_inverse_A_3(diag,shift,allowzeropivot,&zeropivotdetected);
     81:       if (zeropivotdetected) A->factorerrortype = MAT_FACTOR_NUMERIC_ZEROPIVOT;
     82:       diag    += 9;
     83:     }
     84:     break;
     85:   case 4:
     86:     for (i=0; i<mbs; i++) {
     87:       odiag  = v + 16*diag_offset[i];
     88:       PetscMemcpy(diag,odiag,16*sizeof(PetscScalar));
     89:       PetscKernel_A_gets_inverse_A_4(diag,shift,allowzeropivot,&zeropivotdetected);
     90:       if (zeropivotdetected) A->factorerrortype = MAT_FACTOR_NUMERIC_ZEROPIVOT;
     91:       diag  += 16;
     92:     }
     93:     break;
     94:   case 5:
     95:     for (i=0; i<mbs; i++) {
     96:       odiag  = v + 25*diag_offset[i];
     97:       PetscMemcpy(diag,odiag,25*sizeof(PetscScalar));
     98:       PetscKernel_A_gets_inverse_A_5(diag,ipvt,work,shift,allowzeropivot,&zeropivotdetected);
     99:       if (zeropivotdetected) A->factorerrortype = MAT_FACTOR_NUMERIC_ZEROPIVOT;
    100:       diag  += 25;
    101:     }
    102:     break;
    103:   case 6:
    104:     for (i=0; i<mbs; i++) {
    105:       odiag  = v + 36*diag_offset[i];
    106:       PetscMemcpy(diag,odiag,36*sizeof(PetscScalar));
    107:       PetscKernel_A_gets_inverse_A_6(diag,shift,allowzeropivot,&zeropivotdetected);
    108:       if (zeropivotdetected) A->factorerrortype = MAT_FACTOR_NUMERIC_ZEROPIVOT;
    109:       diag  += 36;
    110:     }
    111:     break;
    112:   case 7:
    113:     for (i=0; i<mbs; i++) {
    114:       odiag  = v + 49*diag_offset[i];
    115:       PetscMemcpy(diag,odiag,49*sizeof(PetscScalar));
    116:       PetscKernel_A_gets_inverse_A_7(diag,shift,allowzeropivot,&zeropivotdetected);
    117:       if (zeropivotdetected) A->factorerrortype = MAT_FACTOR_NUMERIC_ZEROPIVOT;
    118:       diag  += 49;
    119:     }
    120:     break;
    121:   default:
    122:     PetscMalloc2(bs,&v_work,bs,&v_pivots);
    123:     for (i=0; i<mbs; i++) {
    124:       odiag  = v + bs2*diag_offset[i];
    125:       PetscMemcpy(diag,odiag,bs2*sizeof(PetscScalar));
    126:       PetscKernel_A_gets_inverse_A(bs,diag,v_pivots,v_work,allowzeropivot,&zeropivotdetected);
    127:       if (zeropivotdetected) A->factorerrortype = MAT_FACTOR_NUMERIC_ZEROPIVOT;
    128:       diag  += bs2;
    129:     }
    130:     PetscFree2(v_work,v_pivots);
    131:   }
    132:   a->idiagvalid = PETSC_TRUE;
    133:   return(0);
    134: }

    136: PetscErrorCode MatSOR_SeqBAIJ(Mat A,Vec bb,PetscReal omega,MatSORType flag,PetscReal fshift,PetscInt its,PetscInt lits,Vec xx)
    137: {
    138:   Mat_SeqBAIJ       *a = (Mat_SeqBAIJ*)A->data;
    139:   PetscScalar       *x,*work,*w,*workt,*t;
    140:   const MatScalar   *v,*aa = a->a, *idiag;
    141:   const PetscScalar *b,*xb;
    142:   PetscScalar       s[7], xw[7]={0}; /* avoid some compilers thinking xw is uninitialized */
    143:   PetscErrorCode    ierr;
    144:   PetscInt          m = a->mbs,i,i2,nz,bs = A->rmap->bs,bs2 = bs*bs,k,j,idx,it;
    145:   const PetscInt    *diag,*ai = a->i,*aj = a->j,*vi;

    148:   its = its*lits;
    149:   if (flag & SOR_EISENSTAT) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"No support yet for Eisenstat");
    150:   if (its <= 0) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONG,"Relaxation requires global its %D and local its %D both positive",its,lits);
    151:   if (fshift) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"Sorry, no support for diagonal shift");
    152:   if (omega != 1.0) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"Sorry, no support for non-trivial relaxation factor");
    153:   if ((flag & SOR_APPLY_UPPER) || (flag & SOR_APPLY_LOWER)) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"Sorry, no support for applying upper or lower triangular parts");

    155:   if (!a->idiagvalid) {MatInvertBlockDiagonal(A,NULL);}

    157:   if (!m) return(0);
    158:   diag  = a->diag;
    159:   idiag = a->idiag;
    160:   k    = PetscMax(A->rmap->n,A->cmap->n);
    161:   if (!a->mult_work) {
    162:     PetscMalloc1(k+1,&a->mult_work);
    163:   }
    164:   if (!a->sor_workt) {
    165:     PetscMalloc1(k,&a->sor_workt);
    166:   }
    167:   if (!a->sor_work) {
    168:     PetscMalloc1(bs,&a->sor_work);
    169:   }
    170:   work = a->mult_work;
    171:   t    = a->sor_workt;
    172:   w    = a->sor_work;

    174:   VecGetArray(xx,&x);
    175:   VecGetArrayRead(bb,&b);

    177:   if (flag & SOR_ZERO_INITIAL_GUESS) {
    178:     if (flag & SOR_FORWARD_SWEEP || flag & SOR_LOCAL_FORWARD_SWEEP) {
    179:       switch (bs) {
    180:       case 1:
    181:         PetscKernel_v_gets_A_times_w_1(x,idiag,b);
    182:         t[0] = b[0];
    183:         i2     = 1;
    184:         idiag += 1;
    185:         for (i=1; i<m; i++) {
    186:           v  = aa + ai[i];
    187:           vi = aj + ai[i];
    188:           nz = diag[i] - ai[i];
    189:           s[0] = b[i2];
    190:           for (j=0; j<nz; j++) {
    191:             xw[0] = x[vi[j]];
    192:             PetscKernel_v_gets_v_minus_A_times_w_1(s,(v+j),xw);
    193:           }
    194:           t[i2] = s[0];
    195:           PetscKernel_v_gets_A_times_w_1(xw,idiag,s);
    196:           x[i2]  = xw[0];
    197:           idiag += 1;
    198:           i2    += 1;
    199:         }
    200:         break;
    201:       case 2:
    202:         PetscKernel_v_gets_A_times_w_2(x,idiag,b);
    203:         t[0] = b[0]; t[1] = b[1];
    204:         i2     = 2;
    205:         idiag += 4;
    206:         for (i=1; i<m; i++) {
    207:           v  = aa + 4*ai[i];
    208:           vi = aj + ai[i];
    209:           nz = diag[i] - ai[i];
    210:           s[0] = b[i2]; s[1] = b[i2+1];
    211:           for (j=0; j<nz; j++) {
    212:             idx = 2*vi[j];
    213:             it  = 4*j;
    214:             xw[0] = x[idx]; xw[1] = x[1+idx];
    215:             PetscKernel_v_gets_v_minus_A_times_w_2(s,(v+it),xw);
    216:           }
    217:           t[i2] = s[0]; t[i2+1] = s[1];
    218:           PetscKernel_v_gets_A_times_w_2(xw,idiag,s);
    219:           x[i2]   = xw[0]; x[i2+1] = xw[1];
    220:           idiag  += 4;
    221:           i2     += 2;
    222:         }
    223:         break;
    224:       case 3:
    225:         PetscKernel_v_gets_A_times_w_3(x,idiag,b);
    226:         t[0] = b[0]; t[1] = b[1]; t[2] = b[2];
    227:         i2     = 3;
    228:         idiag += 9;
    229:         for (i=1; i<m; i++) {
    230:           v  = aa + 9*ai[i];
    231:           vi = aj + ai[i];
    232:           nz = diag[i] - ai[i];
    233:           s[0] = b[i2]; s[1] = b[i2+1]; s[2] = b[i2+2];
    234:           while (nz--) {
    235:             idx = 3*(*vi++);
    236:             xw[0] = x[idx]; xw[1] = x[1+idx]; xw[2] = x[2+idx];
    237:             PetscKernel_v_gets_v_minus_A_times_w_3(s,v,xw);
    238:             v  += 9;
    239:           }
    240:           t[i2] = s[0]; t[i2+1] = s[1]; t[i2+2] = s[2];
    241:           PetscKernel_v_gets_A_times_w_3(xw,idiag,s);
    242:           x[i2] = xw[0]; x[i2+1] = xw[1]; x[i2+2] = xw[2];
    243:           idiag  += 9;
    244:           i2     += 3;
    245:         }
    246:         break;
    247:       case 4:
    248:         PetscKernel_v_gets_A_times_w_4(x,idiag,b);
    249:         t[0] = b[0]; t[1] = b[1]; t[2] = b[2]; t[3] = b[3];
    250:         i2     = 4;
    251:         idiag += 16;
    252:         for (i=1; i<m; i++) {
    253:           v  = aa + 16*ai[i];
    254:           vi = aj + ai[i];
    255:           nz = diag[i] - ai[i];
    256:           s[0] = b[i2]; s[1] = b[i2+1]; s[2] = b[i2+2]; s[3] = b[i2+3];
    257:           while (nz--) {
    258:             idx = 4*(*vi++);
    259:             xw[0]  = x[idx]; xw[1] = x[1+idx]; xw[2] = x[2+idx]; xw[3] = x[3+idx];
    260:             PetscKernel_v_gets_v_minus_A_times_w_4(s,v,xw);
    261:             v  += 16;
    262:           }
    263:           t[i2] = s[0]; t[i2+1] = s[1]; t[i2+2] = s[2]; t[i2 + 3] = s[3];
    264:           PetscKernel_v_gets_A_times_w_4(xw,idiag,s);
    265:           x[i2] = xw[0]; x[i2+1] = xw[1]; x[i2+2] = xw[2]; x[i2+3] = xw[3];
    266:           idiag  += 16;
    267:           i2     += 4;
    268:         }
    269:         break;
    270:       case 5:
    271:         PetscKernel_v_gets_A_times_w_5(x,idiag,b);
    272:         t[0] = b[0]; t[1] = b[1]; t[2] = b[2]; t[3] = b[3]; t[4] = b[4];
    273:         i2     = 5;
    274:         idiag += 25;
    275:         for (i=1; i<m; i++) {
    276:           v  = aa + 25*ai[i];
    277:           vi = aj + ai[i];
    278:           nz = diag[i] - ai[i];
    279:           s[0] = b[i2]; s[1] = b[i2+1]; s[2] = b[i2+2]; s[3] = b[i2+3]; s[4] = b[i2+4];
    280:           while (nz--) {
    281:             idx = 5*(*vi++);
    282:             xw[0]  = x[idx]; xw[1] = x[1+idx]; xw[2] = x[2+idx]; xw[3] = x[3+idx]; xw[4] = x[4+idx];
    283:             PetscKernel_v_gets_v_minus_A_times_w_5(s,v,xw);
    284:             v  += 25;
    285:           }
    286:           t[i2] = s[0]; t[i2+1] = s[1]; t[i2+2] = s[2]; t[i2+3] = s[3]; t[i2+4] = s[4];
    287:           PetscKernel_v_gets_A_times_w_5(xw,idiag,s);
    288:           x[i2] = xw[0]; x[i2+1] = xw[1]; x[i2+2] = xw[2]; x[i2+3] = xw[3]; x[i2+4] = xw[4];
    289:           idiag  += 25;
    290:           i2     += 5;
    291:         }
    292:         break;
    293:       case 6:
    294:         PetscKernel_v_gets_A_times_w_6(x,idiag,b);
    295:         t[0] = b[0]; t[1] = b[1]; t[2] = b[2]; t[3] = b[3]; t[4] = b[4]; t[5] = b[5];
    296:         i2     = 6;
    297:         idiag += 36;
    298:         for (i=1; i<m; i++) {
    299:           v  = aa + 36*ai[i];
    300:           vi = aj + ai[i];
    301:           nz = diag[i] - ai[i];
    302:           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];
    303:           while (nz--) {
    304:             idx = 6*(*vi++);
    305:             xw[0] = x[idx];   xw[1] = x[1+idx]; xw[2] = x[2+idx];
    306:             xw[3] = x[3+idx]; xw[4] = x[4+idx]; xw[5] = x[5+idx];
    307:             PetscKernel_v_gets_v_minus_A_times_w_6(s,v,xw);
    308:             v  += 36;
    309:           }
    310:           t[i2]   = s[0]; t[i2+1] = s[1]; t[i2+2] = s[2];
    311:           t[i2+3] = s[3]; t[i2+4] = s[4]; t[i2+5] = s[5];
    312:           PetscKernel_v_gets_A_times_w_6(xw,idiag,s);
    313:           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];
    314:           idiag  += 36;
    315:           i2     += 6;
    316:         }
    317:         break;
    318:       case 7:
    319:         PetscKernel_v_gets_A_times_w_7(x,idiag,b);
    320:         t[0] = b[0]; t[1] = b[1]; t[2] = b[2];
    321:         t[3] = b[3]; t[4] = b[4]; t[5] = b[5]; t[6] = b[6];
    322:         i2     = 7;
    323:         idiag += 49;
    324:         for (i=1; i<m; i++) {
    325:           v  = aa + 49*ai[i];
    326:           vi = aj + ai[i];
    327:           nz = diag[i] - ai[i];
    328:           s[0] = b[i2];   s[1] = b[i2+1]; s[2] = b[i2+2];
    329:           s[3] = b[i2+3]; s[4] = b[i2+4]; s[5] = b[i2+5]; s[6] = b[i2+6];
    330:           while (nz--) {
    331:             idx = 7*(*vi++);
    332:             xw[0] = x[idx];   xw[1] = x[1+idx]; xw[2] = x[2+idx];
    333:             xw[3] = x[3+idx]; xw[4] = x[4+idx]; xw[5] = x[5+idx]; xw[6] = x[6+idx];
    334:             PetscKernel_v_gets_v_minus_A_times_w_7(s,v,xw);
    335:             v  += 49;
    336:           }
    337:           t[i2]   = s[0]; t[i2+1] = s[1]; t[i2+2] = s[2];
    338:           t[i2+3] = s[3]; t[i2+4] = s[4]; t[i2+5] = s[5]; t[i2+6] = s[6];
    339:           PetscKernel_v_gets_A_times_w_7(xw,idiag,s);
    340:           x[i2] =   xw[0]; x[i2+1] = xw[1]; x[i2+2] = xw[2];
    341:           x[i2+3] = xw[3]; x[i2+4] = xw[4]; x[i2+5] = xw[5]; x[i2+6] = xw[6];
    342:           idiag  += 49;
    343:           i2     += 7;
    344:         }
    345:         break;
    346:       default:
    347:         PetscKernel_w_gets_Ar_times_v(bs,bs,b,idiag,x);
    348:         PetscMemcpy(t,b,bs*sizeof(PetscScalar));
    349:         i2     = bs;
    350:         idiag += bs2;
    351:         for (i=1; i<m; i++) {
    352:           v  = aa + bs2*ai[i];
    353:           vi = aj + ai[i];
    354:           nz = diag[i] - ai[i];

    356:           PetscMemcpy(w,b+i2,bs*sizeof(PetscScalar));
    357:           /* copy all rows of x that are needed into contiguous space */
    358:           workt = work;
    359:           for (j=0; j<nz; j++) {
    360:             PetscMemcpy(workt,x + bs*(*vi++),bs*sizeof(PetscScalar));
    361:             workt += bs;
    362:           }
    363:           PetscKernel_w_gets_w_minus_Ar_times_v(bs,bs*nz,w,v,work);
    364:           PetscMemcpy(t+i2,w,bs*sizeof(PetscScalar));
    365:           PetscKernel_w_gets_Ar_times_v(bs,bs,w,idiag,x+i2);

    367:           idiag += bs2;
    368:           i2    += bs;
    369:         }
    370:         break;
    371:       }
    372:       /* for logging purposes assume number of nonzero in lower half is 1/2 of total */
    373:       PetscLogFlops(1.0*bs2*a->nz);
    374:       xb = t;
    375:     }
    376:     else xb = b;
    377:     if (flag & SOR_BACKWARD_SWEEP || flag & SOR_LOCAL_BACKWARD_SWEEP) {
    378:       idiag = a->idiag+bs2*(a->mbs-1);
    379:       i2 = bs * (m-1);
    380:       switch (bs) {
    381:       case 1:
    382:         s[0]  = xb[i2];
    383:         PetscKernel_v_gets_A_times_w_1(xw,idiag,s);
    384:         x[i2] = xw[0];
    385:         i2   -= 1;
    386:         for (i=m-2; i>=0; i--) {
    387:           v  = aa + (diag[i]+1);
    388:           vi = aj + diag[i] + 1;
    389:           nz = ai[i+1] - diag[i] - 1;
    390:           s[0] = xb[i2];
    391:           for (j=0; j<nz; j++) {
    392:             xw[0] = x[vi[j]];
    393:             PetscKernel_v_gets_v_minus_A_times_w_1(s,(v+j),xw);
    394:           }
    395:           PetscKernel_v_gets_A_times_w_1(xw,idiag,s);
    396:           x[i2]  = xw[0];
    397:           idiag -= 1;
    398:           i2    -= 1;
    399:         }
    400:         break;
    401:       case 2:
    402:         s[0]  = xb[i2]; s[1] = xb[i2+1];
    403:         PetscKernel_v_gets_A_times_w_2(xw,idiag,s);
    404:         x[i2] = xw[0]; x[i2+1] = xw[1];
    405:         i2    -= 2;
    406:         idiag -= 4;
    407:         for (i=m-2; i>=0; i--) {
    408:           v  = aa + 4*(diag[i] + 1);
    409:           vi = aj + diag[i] + 1;
    410:           nz = ai[i+1] - diag[i] - 1;
    411:           s[0] = xb[i2]; s[1] = xb[i2+1];
    412:           for (j=0; j<nz; j++) {
    413:             idx = 2*vi[j];
    414:             it  = 4*j;
    415:             xw[0] = x[idx]; xw[1] = x[1+idx];
    416:             PetscKernel_v_gets_v_minus_A_times_w_2(s,(v+it),xw);
    417:           }
    418:           PetscKernel_v_gets_A_times_w_2(xw,idiag,s);
    419:           x[i2]   = xw[0]; x[i2+1] = xw[1];
    420:           idiag  -= 4;
    421:           i2     -= 2;
    422:         }
    423:         break;
    424:       case 3:
    425:         s[0]  = xb[i2]; s[1] = xb[i2+1]; s[2] = xb[i2+2];
    426:         PetscKernel_v_gets_A_times_w_3(xw,idiag,s);
    427:         x[i2] = xw[0]; x[i2+1] = xw[1]; x[i2+2] = xw[2];
    428:         i2    -= 3;
    429:         idiag -= 9;
    430:         for (i=m-2; i>=0; i--) {
    431:           v  = aa + 9*(diag[i]+1);
    432:           vi = aj + diag[i] + 1;
    433:           nz = ai[i+1] - diag[i] - 1;
    434:           s[0] = xb[i2]; s[1] = xb[i2+1]; s[2] = xb[i2+2];
    435:           while (nz--) {
    436:             idx = 3*(*vi++);
    437:             xw[0] = x[idx]; xw[1] = x[1+idx]; xw[2] = x[2+idx];
    438:             PetscKernel_v_gets_v_minus_A_times_w_3(s,v,xw);
    439:             v  += 9;
    440:           }
    441:           PetscKernel_v_gets_A_times_w_3(xw,idiag,s);
    442:           x[i2] = xw[0]; x[i2+1] = xw[1]; x[i2+2] = xw[2];
    443:           idiag  -= 9;
    444:           i2     -= 3;
    445:         }
    446:         break;
    447:       case 4:
    448:         s[0]  = xb[i2]; s[1] = xb[i2+1]; s[2] = xb[i2+2]; s[3] = xb[i2+3];
    449:         PetscKernel_v_gets_A_times_w_4(xw,idiag,s);
    450:         x[i2] = xw[0]; x[i2+1] = xw[1]; x[i2+2] = xw[2]; x[i2+3] = xw[3];
    451:         i2    -= 4;
    452:         idiag -= 16;
    453:         for (i=m-2; i>=0; i--) {
    454:           v  = aa + 16*(diag[i]+1);
    455:           vi = aj + diag[i] + 1;
    456:           nz = ai[i+1] - diag[i] - 1;
    457:           s[0] = xb[i2]; s[1] = xb[i2+1]; s[2] = xb[i2+2]; s[3] = xb[i2+3];
    458:           while (nz--) {
    459:             idx = 4*(*vi++);
    460:             xw[0]  = x[idx]; xw[1] = x[1+idx]; xw[2] = x[2+idx]; xw[3] = x[3+idx];
    461:             PetscKernel_v_gets_v_minus_A_times_w_4(s,v,xw);
    462:             v  += 16;
    463:           }
    464:           PetscKernel_v_gets_A_times_w_4(xw,idiag,s);
    465:           x[i2] = xw[0]; x[i2+1] = xw[1]; x[i2+2] = xw[2]; x[i2+3] = xw[3];
    466:           idiag  -= 16;
    467:           i2     -= 4;
    468:         }
    469:         break;
    470:       case 5:
    471:         s[0]  = xb[i2]; s[1] = xb[i2+1]; s[2] = xb[i2+2]; s[3] = xb[i2+3]; s[4] = xb[i2+4];
    472:         PetscKernel_v_gets_A_times_w_5(xw,idiag,s);
    473:         x[i2] = xw[0]; x[i2+1] = xw[1]; x[i2+2] = xw[2]; x[i2+3] = xw[3]; x[i2+4] = xw[4];
    474:         i2    -= 5;
    475:         idiag -= 25;
    476:         for (i=m-2; i>=0; i--) {
    477:           v  = aa + 25*(diag[i]+1);
    478:           vi = aj + diag[i] + 1;
    479:           nz = ai[i+1] - diag[i] - 1;
    480:           s[0] = xb[i2]; s[1] = xb[i2+1]; s[2] = xb[i2+2]; s[3] = xb[i2+3]; s[4] = xb[i2+4];
    481:           while (nz--) {
    482:             idx = 5*(*vi++);
    483:             xw[0]  = x[idx]; xw[1] = x[1+idx]; xw[2] = x[2+idx]; xw[3] = x[3+idx]; xw[4] = x[4+idx];
    484:             PetscKernel_v_gets_v_minus_A_times_w_5(s,v,xw);
    485:             v  += 25;
    486:           }
    487:           PetscKernel_v_gets_A_times_w_5(xw,idiag,s);
    488:           x[i2] = xw[0]; x[i2+1] = xw[1]; x[i2+2] = xw[2]; x[i2+3] = xw[3]; x[i2+4] = xw[4];
    489:           idiag  -= 25;
    490:           i2     -= 5;
    491:         }
    492:         break;
    493:       case 6:
    494:         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];
    495:         PetscKernel_v_gets_A_times_w_6(xw,idiag,s);
    496:         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];
    497:         i2    -= 6;
    498:         idiag -= 36;
    499:         for (i=m-2; i>=0; i--) {
    500:           v  = aa + 36*(diag[i]+1);
    501:           vi = aj + diag[i] + 1;
    502:           nz = ai[i+1] - diag[i] - 1;
    503:           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];
    504:           while (nz--) {
    505:             idx = 6*(*vi++);
    506:             xw[0] = x[idx];   xw[1] = x[1+idx]; xw[2] = x[2+idx];
    507:             xw[3] = x[3+idx]; xw[4] = x[4+idx]; xw[5] = x[5+idx];
    508:             PetscKernel_v_gets_v_minus_A_times_w_6(s,v,xw);
    509:             v  += 36;
    510:           }
    511:           PetscKernel_v_gets_A_times_w_6(xw,idiag,s);
    512:           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];
    513:           idiag  -= 36;
    514:           i2     -= 6;
    515:         }
    516:         break;
    517:       case 7:
    518:         s[0] = xb[i2];   s[1] = xb[i2+1]; s[2] = xb[i2+2];
    519:         s[3] = xb[i2+3]; s[4] = xb[i2+4]; s[5] = xb[i2+5]; s[6] = xb[i2+6];
    520:         PetscKernel_v_gets_A_times_w_7(x,idiag,b);
    521:         x[i2]   = xw[0]; x[i2+1] = xw[1]; x[i2+2] = xw[2];
    522:         x[i2+3] = xw[3]; x[i2+4] = xw[4]; x[i2+5] = xw[5]; x[i2+6] = xw[6];
    523:         i2    -= 7;
    524:         idiag -= 49;
    525:         for (i=m-2; i>=0; i--) {
    526:           v  = aa + 49*(diag[i]+1);
    527:           vi = aj + diag[i] + 1;
    528:           nz = ai[i+1] - diag[i] - 1;
    529:           s[0] = xb[i2];   s[1] = xb[i2+1]; s[2] = xb[i2+2];
    530:           s[3] = xb[i2+3]; s[4] = xb[i2+4]; s[5] = xb[i2+5]; s[6] = xb[i2+6];
    531:           while (nz--) {
    532:             idx = 7*(*vi++);
    533:             xw[0] = x[idx];   xw[1] = x[1+idx]; xw[2] = x[2+idx];
    534:             xw[3] = x[3+idx]; xw[4] = x[4+idx]; xw[5] = x[5+idx]; xw[6] = x[6+idx];
    535:             PetscKernel_v_gets_v_minus_A_times_w_7(s,v,xw);
    536:             v  += 49;
    537:           }
    538:           PetscKernel_v_gets_A_times_w_7(xw,idiag,s);
    539:           x[i2] =   xw[0]; x[i2+1] = xw[1]; x[i2+2] = xw[2];
    540:           x[i2+3] = xw[3]; x[i2+4] = xw[4]; x[i2+5] = xw[5]; x[i2+6] = xw[6];
    541:           idiag  -= 49;
    542:           i2     -= 7;
    543:         }
    544:         break;
    545:       default:
    546:         PetscMemcpy(w,xb+i2,bs*sizeof(PetscScalar));
    547:         PetscKernel_w_gets_Ar_times_v(bs,bs,w,idiag,x+i2);
    548:         i2    -= bs;
    549:         idiag -= bs2;
    550:         for (i=m-2; i>=0; i--) {
    551:           v  = aa + bs2*(diag[i]+1);
    552:           vi = aj + diag[i] + 1;
    553:           nz = ai[i+1] - diag[i] - 1;

    555:           PetscMemcpy(w,xb+i2,bs*sizeof(PetscScalar));
    556:           /* copy all rows of x that are needed into contiguous space */
    557:           workt = work;
    558:           for (j=0; j<nz; j++) {
    559:             PetscMemcpy(workt,x + bs*(*vi++),bs*sizeof(PetscScalar));
    560:             workt += bs;
    561:           }
    562:           PetscKernel_w_gets_w_minus_Ar_times_v(bs,bs*nz,w,v,work);
    563:           PetscKernel_w_gets_Ar_times_v(bs,bs,w,idiag,x+i2);

    565:           idiag -= bs2;
    566:           i2    -= bs;
    567:         }
    568:         break;
    569:       }
    570:       PetscLogFlops(1.0*bs2*(a->nz));
    571:     }
    572:     its--;
    573:   }
    574:   while (its--) {
    575:     if (flag & SOR_FORWARD_SWEEP || flag & SOR_LOCAL_FORWARD_SWEEP) {
    576:       idiag = a->idiag;
    577:       i2 = 0;
    578:       switch (bs) {
    579:       case 1:
    580:         for (i=0; i<m; i++) {
    581:           v  = aa + ai[i];
    582:           vi = aj + ai[i];
    583:           nz = ai[i+1] - ai[i];
    584:           s[0] = b[i2];
    585:           for (j=0; j<nz; j++) {
    586:             xw[0] = x[vi[j]];
    587:             PetscKernel_v_gets_v_minus_A_times_w_1(s,(v+j),xw);
    588:           }
    589:           PetscKernel_v_gets_A_times_w_1(xw,idiag,s);
    590:           x[i2] += xw[0];
    591:           idiag += 1;
    592:           i2    += 1;
    593:         }
    594:         break;
    595:       case 2:
    596:         for (i=0; i<m; i++) {
    597:           v  = aa + 4*ai[i];
    598:           vi = aj + ai[i];
    599:           nz = ai[i+1] - ai[i];
    600:           s[0] = b[i2]; s[1] = b[i2+1];
    601:           for (j=0; j<nz; j++) {
    602:             idx = 2*vi[j];
    603:             it  = 4*j;
    604:             xw[0] = x[idx]; xw[1] = x[1+idx];
    605:             PetscKernel_v_gets_v_minus_A_times_w_2(s,(v+it),xw);
    606:           }
    607:           PetscKernel_v_gets_A_times_w_2(xw,idiag,s);
    608:           x[i2]  += xw[0]; x[i2+1] += xw[1];
    609:           idiag  += 4;
    610:           i2     += 2;
    611:         }
    612:         break;
    613:       case 3:
    614:         for (i=0; i<m; i++) {
    615:           v  = aa + 9*ai[i];
    616:           vi = aj + ai[i];
    617:           nz = ai[i+1] - ai[i];
    618:           s[0] = b[i2]; s[1] = b[i2+1]; s[2] = b[i2+2];
    619:           while (nz--) {
    620:             idx = 3*(*vi++);
    621:             xw[0] = x[idx]; xw[1] = x[1+idx]; xw[2] = x[2+idx];
    622:             PetscKernel_v_gets_v_minus_A_times_w_3(s,v,xw);
    623:             v  += 9;
    624:           }
    625:           PetscKernel_v_gets_A_times_w_3(xw,idiag,s);
    626:           x[i2] += xw[0]; x[i2+1] += xw[1]; x[i2+2] += xw[2];
    627:           idiag  += 9;
    628:           i2     += 3;
    629:         }
    630:         break;
    631:       case 4:
    632:         for (i=0; i<m; i++) {
    633:           v  = aa + 16*ai[i];
    634:           vi = aj + ai[i];
    635:           nz = ai[i+1] - ai[i];
    636:           s[0] = b[i2]; s[1] = b[i2+1]; s[2] = b[i2+2]; s[3] = b[i2+3];
    637:           while (nz--) {
    638:             idx = 4*(*vi++);
    639:             xw[0]  = x[idx]; xw[1] = x[1+idx]; xw[2] = x[2+idx]; xw[3] = x[3+idx];
    640:             PetscKernel_v_gets_v_minus_A_times_w_4(s,v,xw);
    641:             v  += 16;
    642:           }
    643:           PetscKernel_v_gets_A_times_w_4(xw,idiag,s);
    644:           x[i2] += xw[0]; x[i2+1] += xw[1]; x[i2+2] += xw[2]; x[i2+3] += xw[3];
    645:           idiag  += 16;
    646:           i2     += 4;
    647:         }
    648:         break;
    649:       case 5:
    650:         for (i=0; i<m; i++) {
    651:           v  = aa + 25*ai[i];
    652:           vi = aj + ai[i];
    653:           nz = ai[i+1] - ai[i];
    654:           s[0] = b[i2]; s[1] = b[i2+1]; s[2] = b[i2+2]; s[3] = b[i2+3]; s[4] = b[i2+4];
    655:           while (nz--) {
    656:             idx = 5*(*vi++);
    657:             xw[0]  = x[idx]; xw[1] = x[1+idx]; xw[2] = x[2+idx]; xw[3] = x[3+idx]; xw[4] = x[4+idx];
    658:             PetscKernel_v_gets_v_minus_A_times_w_5(s,v,xw);
    659:             v  += 25;
    660:           }
    661:           PetscKernel_v_gets_A_times_w_5(xw,idiag,s);
    662:           x[i2] += xw[0]; x[i2+1] += xw[1]; x[i2+2] += xw[2]; x[i2+3] += xw[3]; x[i2+4] += xw[4];
    663:           idiag  += 25;
    664:           i2     += 5;
    665:         }
    666:         break;
    667:       case 6:
    668:         for (i=0; i<m; i++) {
    669:           v  = aa + 36*ai[i];
    670:           vi = aj + ai[i];
    671:           nz = ai[i+1] - ai[i];
    672:           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];
    673:           while (nz--) {
    674:             idx = 6*(*vi++);
    675:             xw[0] = x[idx];   xw[1] = x[1+idx]; xw[2] = x[2+idx];
    676:             xw[3] = x[3+idx]; xw[4] = x[4+idx]; xw[5] = x[5+idx];
    677:             PetscKernel_v_gets_v_minus_A_times_w_6(s,v,xw);
    678:             v  += 36;
    679:           }
    680:           PetscKernel_v_gets_A_times_w_6(xw,idiag,s);
    681:           x[i2] += xw[0]; x[i2+1] += xw[1]; x[i2+2] += xw[2];
    682:           x[i2+3] += xw[3]; x[i2+4] += xw[4]; x[i2+5] += xw[5];
    683:           idiag  += 36;
    684:           i2     += 6;
    685:         }
    686:         break;
    687:       case 7:
    688:         for (i=0; i<m; i++) {
    689:           v  = aa + 49*ai[i];
    690:           vi = aj + ai[i];
    691:           nz = ai[i+1] - ai[i];
    692:           s[0] = b[i2];   s[1] = b[i2+1]; s[2] = b[i2+2];
    693:           s[3] = b[i2+3]; s[4] = b[i2+4]; s[5] = b[i2+5]; s[6] = b[i2+6];
    694:           while (nz--) {
    695:             idx = 7*(*vi++);
    696:             xw[0] = x[idx];   xw[1] = x[1+idx]; xw[2] = x[2+idx];
    697:             xw[3] = x[3+idx]; xw[4] = x[4+idx]; xw[5] = x[5+idx]; xw[6] = x[6+idx];
    698:             PetscKernel_v_gets_v_minus_A_times_w_7(s,v,xw);
    699:             v  += 49;
    700:           }
    701:           PetscKernel_v_gets_A_times_w_7(xw,idiag,s);
    702:           x[i2]   += xw[0]; x[i2+1] += xw[1]; x[i2+2] += xw[2];
    703:           x[i2+3] += xw[3]; x[i2+4] += xw[4]; x[i2+5] += xw[5]; x[i2+6] += xw[6];
    704:           idiag  += 49;
    705:           i2     += 7;
    706:         }
    707:         break;
    708:       default:
    709:         for (i=0; i<m; i++) {
    710:           v  = aa + bs2*ai[i];
    711:           vi = aj + ai[i];
    712:           nz = ai[i+1] - ai[i];

    714:           PetscMemcpy(w,b+i2,bs*sizeof(PetscScalar));
    715:           /* copy all rows of x that are needed into contiguous space */
    716:           workt = work;
    717:           for (j=0; j<nz; j++) {
    718:             PetscMemcpy(workt,x + bs*(*vi++),bs*sizeof(PetscScalar));
    719:             workt += bs;
    720:           }
    721:           PetscKernel_w_gets_w_minus_Ar_times_v(bs,bs*nz,w,v,work);
    722:           PetscKernel_w_gets_w_plus_Ar_times_v(bs,bs,w,idiag,x+i2);

    724:           idiag += bs2;
    725:           i2    += bs;
    726:         }
    727:         break;
    728:       }
    729:       PetscLogFlops(2.0*bs2*a->nz);
    730:     }
    731:     if (flag & SOR_BACKWARD_SWEEP || flag & SOR_LOCAL_BACKWARD_SWEEP) {
    732:       idiag = a->idiag+bs2*(a->mbs-1);
    733:       i2 = bs * (m-1);
    734:       switch (bs) {
    735:       case 1:
    736:         for (i=m-1; i>=0; i--) {
    737:           v  = aa + ai[i];
    738:           vi = aj + ai[i];
    739:           nz = ai[i+1] - ai[i];
    740:           s[0] = b[i2];
    741:           for (j=0; j<nz; j++) {
    742:             xw[0] = x[vi[j]];
    743:             PetscKernel_v_gets_v_minus_A_times_w_1(s,(v+j),xw);
    744:           }
    745:           PetscKernel_v_gets_A_times_w_1(xw,idiag,s);
    746:           x[i2] += xw[0];
    747:           idiag -= 1;
    748:           i2    -= 1;
    749:         }
    750:         break;
    751:       case 2:
    752:         for (i=m-1; i>=0; i--) {
    753:           v  = aa + 4*ai[i];
    754:           vi = aj + ai[i];
    755:           nz = ai[i+1] - ai[i];
    756:           s[0] = b[i2]; s[1] = b[i2+1];
    757:           for (j=0; j<nz; j++) {
    758:             idx = 2*vi[j];
    759:             it  = 4*j;
    760:             xw[0] = x[idx]; xw[1] = x[1+idx];
    761:             PetscKernel_v_gets_v_minus_A_times_w_2(s,(v+it),xw);
    762:           }
    763:           PetscKernel_v_gets_A_times_w_2(xw,idiag,s);
    764:           x[i2]  += xw[0]; x[i2+1] += xw[1];
    765:           idiag  -= 4;
    766:           i2     -= 2;
    767:         }
    768:         break;
    769:       case 3:
    770:         for (i=m-1; i>=0; i--) {
    771:           v  = aa + 9*ai[i];
    772:           vi = aj + ai[i];
    773:           nz = ai[i+1] - ai[i];
    774:           s[0] = b[i2]; s[1] = b[i2+1]; s[2] = b[i2+2];
    775:           while (nz--) {
    776:             idx = 3*(*vi++);
    777:             xw[0] = x[idx]; xw[1] = x[1+idx]; xw[2] = x[2+idx];
    778:             PetscKernel_v_gets_v_minus_A_times_w_3(s,v,xw);
    779:             v  += 9;
    780:           }
    781:           PetscKernel_v_gets_A_times_w_3(xw,idiag,s);
    782:           x[i2] += xw[0]; x[i2+1] += xw[1]; x[i2+2] += xw[2];
    783:           idiag  -= 9;
    784:           i2     -= 3;
    785:         }
    786:         break;
    787:       case 4:
    788:         for (i=m-1; i>=0; i--) {
    789:           v  = aa + 16*ai[i];
    790:           vi = aj + ai[i];
    791:           nz = ai[i+1] - ai[i];
    792:           s[0] = b[i2]; s[1] = b[i2+1]; s[2] = b[i2+2]; s[3] = b[i2+3];
    793:           while (nz--) {
    794:             idx = 4*(*vi++);
    795:             xw[0]  = x[idx]; xw[1] = x[1+idx]; xw[2] = x[2+idx]; xw[3] = x[3+idx];
    796:             PetscKernel_v_gets_v_minus_A_times_w_4(s,v,xw);
    797:             v  += 16;
    798:           }
    799:           PetscKernel_v_gets_A_times_w_4(xw,idiag,s);
    800:           x[i2] += xw[0]; x[i2+1] += xw[1]; x[i2+2] += xw[2]; x[i2+3] += xw[3];
    801:           idiag  -= 16;
    802:           i2     -= 4;
    803:         }
    804:         break;
    805:       case 5:
    806:         for (i=m-1; i>=0; i--) {
    807:           v  = aa + 25*ai[i];
    808:           vi = aj + ai[i];
    809:           nz = ai[i+1] - ai[i];
    810:           s[0] = b[i2]; s[1] = b[i2+1]; s[2] = b[i2+2]; s[3] = b[i2+3]; s[4] = b[i2+4];
    811:           while (nz--) {
    812:             idx = 5*(*vi++);
    813:             xw[0]  = x[idx]; xw[1] = x[1+idx]; xw[2] = x[2+idx]; xw[3] = x[3+idx]; xw[4] = x[4+idx];
    814:             PetscKernel_v_gets_v_minus_A_times_w_5(s,v,xw);
    815:             v  += 25;
    816:           }
    817:           PetscKernel_v_gets_A_times_w_5(xw,idiag,s);
    818:           x[i2] += xw[0]; x[i2+1] += xw[1]; x[i2+2] += xw[2]; x[i2+3] += xw[3]; x[i2+4] += xw[4];
    819:           idiag  -= 25;
    820:           i2     -= 5;
    821:         }
    822:         break;
    823:       case 6:
    824:         for (i=m-1; i>=0; i--) {
    825:           v  = aa + 36*ai[i];
    826:           vi = aj + ai[i];
    827:           nz = ai[i+1] - ai[i];
    828:           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];
    829:           while (nz--) {
    830:             idx = 6*(*vi++);
    831:             xw[0] = x[idx];   xw[1] = x[1+idx]; xw[2] = x[2+idx];
    832:             xw[3] = x[3+idx]; xw[4] = x[4+idx]; xw[5] = x[5+idx];
    833:             PetscKernel_v_gets_v_minus_A_times_w_6(s,v,xw);
    834:             v  += 36;
    835:           }
    836:           PetscKernel_v_gets_A_times_w_6(xw,idiag,s);
    837:           x[i2] += xw[0]; x[i2+1] += xw[1]; x[i2+2] += xw[2];
    838:           x[i2+3] += xw[3]; x[i2+4] += xw[4]; x[i2+5] += xw[5];
    839:           idiag  -= 36;
    840:           i2     -= 6;
    841:         }
    842:         break;
    843:       case 7:
    844:         for (i=m-1; i>=0; i--) {
    845:           v  = aa + 49*ai[i];
    846:           vi = aj + ai[i];
    847:           nz = ai[i+1] - ai[i];
    848:           s[0] = b[i2];   s[1] = b[i2+1]; s[2] = b[i2+2];
    849:           s[3] = b[i2+3]; s[4] = b[i2+4]; s[5] = b[i2+5]; s[6] = b[i2+6];
    850:           while (nz--) {
    851:             idx = 7*(*vi++);
    852:             xw[0] = x[idx];   xw[1] = x[1+idx]; xw[2] = x[2+idx];
    853:             xw[3] = x[3+idx]; xw[4] = x[4+idx]; xw[5] = x[5+idx]; xw[6] = x[6+idx];
    854:             PetscKernel_v_gets_v_minus_A_times_w_7(s,v,xw);
    855:             v  += 49;
    856:           }
    857:           PetscKernel_v_gets_A_times_w_7(xw,idiag,s);
    858:           x[i2] +=   xw[0]; x[i2+1] += xw[1]; x[i2+2] += xw[2];
    859:           x[i2+3] += xw[3]; x[i2+4] += xw[4]; x[i2+5] += xw[5]; x[i2+6] += xw[6];
    860:           idiag  -= 49;
    861:           i2     -= 7;
    862:         }
    863:         break;
    864:       default:
    865:         for (i=m-1; i>=0; i--) {
    866:           v  = aa + bs2*ai[i];
    867:           vi = aj + ai[i];
    868:           nz = ai[i+1] - ai[i];

    870:           PetscMemcpy(w,b+i2,bs*sizeof(PetscScalar));
    871:           /* copy all rows of x that are needed into contiguous space */
    872:           workt = work;
    873:           for (j=0; j<nz; j++) {
    874:             PetscMemcpy(workt,x + bs*(*vi++),bs*sizeof(PetscScalar));
    875:             workt += bs;
    876:           }
    877:           PetscKernel_w_gets_w_minus_Ar_times_v(bs,bs*nz,w,v,work);
    878:           PetscKernel_w_gets_w_plus_Ar_times_v(bs,bs,w,idiag,x+i2);

    880:           idiag -= bs2;
    881:           i2    -= bs;
    882:         }
    883:         break;
    884:       }
    885:       PetscLogFlops(2.0*bs2*(a->nz));
    886:     }
    887:   }
    888:   VecRestoreArray(xx,&x);
    889:   VecRestoreArrayRead(bb,&b);
    890:   return(0);
    891: }

    894: /*
    895:     Special version for direct calls from Fortran (Used in PETSc-fun3d)
    896: */
    897: #if defined(PETSC_HAVE_FORTRAN_CAPS)
    898: #define matsetvaluesblocked4_ MATSETVALUESBLOCKED4
    899: #elif !defined(PETSC_HAVE_FORTRAN_UNDERSCORE)
    900: #define matsetvaluesblocked4_ matsetvaluesblocked4
    901: #endif

    903: PETSC_EXTERN void matsetvaluesblocked4_(Mat *AA,PetscInt *mm,const PetscInt im[],PetscInt *nn,const PetscInt in[],const PetscScalar v[])
    904: {
    905:   Mat               A  = *AA;
    906:   Mat_SeqBAIJ       *a = (Mat_SeqBAIJ*)A->data;
    907:   PetscInt          *rp,k,low,high,t,ii,jj,row,nrow,i,col,l,N,m = *mm,n = *nn;
    908:   PetscInt          *ai    =a->i,*ailen=a->ilen;
    909:   PetscInt          *aj    =a->j,stepval,lastcol = -1;
    910:   const PetscScalar *value = v;
    911:   MatScalar         *ap,*aa = a->a,*bap;

    914:   if (A->rmap->bs != 4) SETERRABORT(PetscObjectComm((PetscObject)A),PETSC_ERR_ARG_WRONG,"Can only be called with a block size of 4");
    915:   stepval = (n-1)*4;
    916:   for (k=0; k<m; k++) { /* loop over added rows */
    917:     row  = im[k];
    918:     rp   = aj + ai[row];
    919:     ap   = aa + 16*ai[row];
    920:     nrow = ailen[row];
    921:     low  = 0;
    922:     high = nrow;
    923:     for (l=0; l<n; l++) { /* loop over added columns */
    924:       col = in[l];
    925:       if (col <= lastcol)  low = 0;
    926:       else                high = nrow;
    927:       lastcol = col;
    928:       value   = v + k*(stepval+4 + l)*4;
    929:       while (high-low > 7) {
    930:         t = (low+high)/2;
    931:         if (rp[t] > col) high = t;
    932:         else             low  = t;
    933:       }
    934:       for (i=low; i<high; i++) {
    935:         if (rp[i] > col) break;
    936:         if (rp[i] == col) {
    937:           bap = ap +  16*i;
    938:           for (ii=0; ii<4; ii++,value+=stepval) {
    939:             for (jj=ii; jj<16; jj+=4) {
    940:               bap[jj] += *value++;
    941:             }
    942:           }
    943:           goto noinsert2;
    944:         }
    945:       }
    946:       N = nrow++ - 1;
    947:       high++; /* added new column index thus must search to one higher than before */
    948:       /* shift up all the later entries in this row */
    949:       for (ii=N; ii>=i; ii--) {
    950:         rp[ii+1] = rp[ii];
    951:         PetscMemcpy(ap+16*(ii+1),ap+16*(ii),16*sizeof(MatScalar));
    952:       }
    953:       if (N >= i) {
    954:         PetscMemzero(ap+16*i,16*sizeof(MatScalar));
    955:       }
    956:       rp[i] = col;
    957:       bap   = ap +  16*i;
    958:       for (ii=0; ii<4; ii++,value+=stepval) {
    959:         for (jj=ii; jj<16; jj+=4) {
    960:           bap[jj] = *value++;
    961:         }
    962:       }
    963:       noinsert2:;
    964:       low = i;
    965:     }
    966:     ailen[row] = nrow;
    967:   }
    968:   PetscFunctionReturnVoid();
    969: }

    971: #if defined(PETSC_HAVE_FORTRAN_CAPS)
    972: #define matsetvalues4_ MATSETVALUES4
    973: #elif !defined(PETSC_HAVE_FORTRAN_UNDERSCORE)
    974: #define matsetvalues4_ matsetvalues4
    975: #endif

    977: PETSC_EXTERN void matsetvalues4_(Mat *AA,PetscInt *mm,PetscInt *im,PetscInt *nn,PetscInt *in,PetscScalar *v)
    978: {
    979:   Mat         A  = *AA;
    980:   Mat_SeqBAIJ *a = (Mat_SeqBAIJ*)A->data;
    981:   PetscInt    *rp,k,low,high,t,ii,row,nrow,i,col,l,N,n = *nn,m = *mm;
    982:   PetscInt    *ai=a->i,*ailen=a->ilen;
    983:   PetscInt    *aj=a->j,brow,bcol;
    984:   PetscInt    ridx,cidx,lastcol = -1;
    985:   MatScalar   *ap,value,*aa=a->a,*bap;

    988:   for (k=0; k<m; k++) { /* loop over added rows */
    989:     row  = im[k]; brow = row/4;
    990:     rp   = aj + ai[brow];
    991:     ap   = aa + 16*ai[brow];
    992:     nrow = ailen[brow];
    993:     low  = 0;
    994:     high = nrow;
    995:     for (l=0; l<n; l++) { /* loop over added columns */
    996:       col   = in[l]; bcol = col/4;
    997:       ridx  = row % 4; cidx = col % 4;
    998:       value = v[l + k*n];
    999:       if (col <= lastcol)  low = 0;
    1000:       else                high = nrow;
    1001:       lastcol = col;
    1002:       while (high-low > 7) {
    1003:         t = (low+high)/2;
    1004:         if (rp[t] > bcol) high = t;
    1005:         else              low  = t;
    1006:       }
    1007:       for (i=low; i<high; i++) {
    1008:         if (rp[i] > bcol) break;
    1009:         if (rp[i] == bcol) {
    1010:           bap   = ap +  16*i + 4*cidx + ridx;
    1011:           *bap += value;
    1012:           goto noinsert1;
    1013:         }
    1014:       }
    1015:       N = nrow++ - 1;
    1016:       high++; /* added new column thus must search to one higher than before */
    1017:       /* shift up all the later entries in this row */
    1018:       for (ii=N; ii>=i; ii--) {
    1019:         rp[ii+1] = rp[ii];
    1020:         PetscMemcpy(ap+16*(ii+1),ap+16*(ii),16*sizeof(MatScalar));
    1021:       }
    1022:       if (N>=i) {
    1023:         PetscMemzero(ap+16*i,16*sizeof(MatScalar));
    1024:       }
    1025:       rp[i]                    = bcol;
    1026:       ap[16*i + 4*cidx + ridx] = value;
    1027: noinsert1:;
    1028:       low = i;
    1029:     }
    1030:     ailen[brow] = nrow;
    1031:   }
    1032:   PetscFunctionReturnVoid();
    1033: }

    1035: /*
    1036:      Checks for missing diagonals
    1037: */
    1038: PetscErrorCode MatMissingDiagonal_SeqBAIJ(Mat A,PetscBool  *missing,PetscInt *d)
    1039: {
    1040:   Mat_SeqBAIJ    *a = (Mat_SeqBAIJ*)A->data;
    1042:   PetscInt       *diag,*ii = a->i,i;

    1045:   MatMarkDiagonal_SeqBAIJ(A);
    1046:   *missing = PETSC_FALSE;
    1047:   if (A->rmap->n > 0 && !ii) {
    1048:     *missing = PETSC_TRUE;
    1049:     if (d) *d = 0;
    1050:     PetscInfo(A,"Matrix has no entries therefore is missing diagonal\n");
    1051:   } else {
    1052:     diag = a->diag;
    1053:     for (i=0; i<a->mbs; i++) {
    1054:       if (diag[i] >= ii[i+1]) {
    1055:         *missing = PETSC_TRUE;
    1056:         if (d) *d = i;
    1057:         PetscInfo1(A,"Matrix is missing block diagonal number %D\n",i);
    1058:         break;
    1059:       }
    1060:     }
    1061:   }
    1062:   return(0);
    1063: }

    1065: PetscErrorCode MatMarkDiagonal_SeqBAIJ(Mat A)
    1066: {
    1067:   Mat_SeqBAIJ    *a = (Mat_SeqBAIJ*)A->data;
    1069:   PetscInt       i,j,m = a->mbs;

    1072:   if (!a->diag) {
    1073:     PetscMalloc1(m,&a->diag);
    1074:     PetscLogObjectMemory((PetscObject)A,m*sizeof(PetscInt));
    1075:     a->free_diag = PETSC_TRUE;
    1076:   }
    1077:   for (i=0; i<m; i++) {
    1078:     a->diag[i] = a->i[i+1];
    1079:     for (j=a->i[i]; j<a->i[i+1]; j++) {
    1080:       if (a->j[j] == i) {
    1081:         a->diag[i] = j;
    1082:         break;
    1083:       }
    1084:     }
    1085:   }
    1086:   return(0);
    1087: }

    1090: static PetscErrorCode MatGetRowIJ_SeqBAIJ(Mat A,PetscInt oshift,PetscBool symmetric,PetscBool blockcompressed,PetscInt *nn,const PetscInt *inia[],const PetscInt *inja[],PetscBool  *done)
    1091: {
    1092:   Mat_SeqBAIJ    *a = (Mat_SeqBAIJ*)A->data;
    1094:   PetscInt       i,j,n = a->mbs,nz = a->i[n],*tia,*tja,bs = A->rmap->bs,k,l,cnt;
    1095:   PetscInt       **ia = (PetscInt**)inia,**ja = (PetscInt**)inja;

    1098:   *nn = n;
    1099:   if (!ia) return(0);
    1100:   if (symmetric) {
    1101:     MatToSymmetricIJ_SeqAIJ(n,a->i,a->j,PETSC_TRUE,0,0,&tia,&tja);
    1102:     nz   = tia[n];
    1103:   } else {
    1104:     tia = a->i; tja = a->j;
    1105:   }

    1107:   if (!blockcompressed && bs > 1) {
    1108:     (*nn) *= bs;
    1109:     /* malloc & create the natural set of indices */
    1110:     PetscMalloc1((n+1)*bs,ia);
    1111:     if (n) {
    1112:       (*ia)[0] = oshift;
    1113:       for (j=1; j<bs; j++) {
    1114:         (*ia)[j] = (tia[1]-tia[0])*bs+(*ia)[j-1];
    1115:       }
    1116:     }

    1118:     for (i=1; i<n; i++) {
    1119:       (*ia)[i*bs] = (tia[i]-tia[i-1])*bs + (*ia)[i*bs-1];
    1120:       for (j=1; j<bs; j++) {
    1121:         (*ia)[i*bs+j] = (tia[i+1]-tia[i])*bs + (*ia)[i*bs+j-1];
    1122:       }
    1123:     }
    1124:     if (n) {
    1125:       (*ia)[n*bs] = (tia[n]-tia[n-1])*bs + (*ia)[n*bs-1];
    1126:     }

    1128:     if (inja) {
    1129:       PetscMalloc1(nz*bs*bs,ja);
    1130:       cnt = 0;
    1131:       for (i=0; i<n; i++) {
    1132:         for (j=0; j<bs; j++) {
    1133:           for (k=tia[i]; k<tia[i+1]; k++) {
    1134:             for (l=0; l<bs; l++) {
    1135:               (*ja)[cnt++] = bs*tja[k] + l;
    1136:             }
    1137:           }
    1138:         }
    1139:       }
    1140:     }

    1142:     if (symmetric) { /* deallocate memory allocated in MatToSymmetricIJ_SeqAIJ() */
    1143:       PetscFree(tia);
    1144:       PetscFree(tja);
    1145:     }
    1146:   } else if (oshift == 1) {
    1147:     if (symmetric) {
    1148:       nz = tia[A->rmap->n/bs];
    1149:       /*  add 1 to i and j indices */
    1150:       for (i=0; i<A->rmap->n/bs+1; i++) tia[i] = tia[i] + 1;
    1151:       *ia = tia;
    1152:       if (ja) {
    1153:         for (i=0; i<nz; i++) tja[i] = tja[i] + 1;
    1154:         *ja = tja;
    1155:       }
    1156:     } else {
    1157:       nz = a->i[A->rmap->n/bs];
    1158:       /* malloc space and  add 1 to i and j indices */
    1159:       PetscMalloc1(A->rmap->n/bs+1,ia);
    1160:       for (i=0; i<A->rmap->n/bs+1; i++) (*ia)[i] = a->i[i] + 1;
    1161:       if (ja) {
    1162:         PetscMalloc1(nz,ja);
    1163:         for (i=0; i<nz; i++) (*ja)[i] = a->j[i] + 1;
    1164:       }
    1165:     }
    1166:   } else {
    1167:     *ia = tia;
    1168:     if (ja) *ja = tja;
    1169:   }
    1170:   return(0);
    1171: }

    1173: static PetscErrorCode MatRestoreRowIJ_SeqBAIJ(Mat A,PetscInt oshift,PetscBool symmetric,PetscBool blockcompressed,PetscInt *nn,const PetscInt *ia[],const PetscInt *ja[],PetscBool  *done)
    1174: {

    1178:   if (!ia) return(0);
    1179:   if ((!blockcompressed && A->rmap->bs > 1) || (symmetric || oshift == 1)) {
    1180:     PetscFree(*ia);
    1181:     if (ja) {PetscFree(*ja);}
    1182:   }
    1183:   return(0);
    1184: }

    1186: PetscErrorCode MatDestroy_SeqBAIJ(Mat A)
    1187: {
    1188:   Mat_SeqBAIJ    *a = (Mat_SeqBAIJ*)A->data;

    1192: #if defined(PETSC_USE_LOG)
    1193:   PetscLogObjectState((PetscObject)A,"Rows=%D, Cols=%D, NZ=%D",A->rmap->N,A->cmap->n,a->nz);
    1194: #endif
    1195:   MatSeqXAIJFreeAIJ(A,&a->a,&a->j,&a->i);
    1196:   ISDestroy(&a->row);
    1197:   ISDestroy(&a->col);
    1198:   if (a->free_diag) {PetscFree(a->diag);}
    1199:   PetscFree(a->idiag);
    1200:   if (a->free_imax_ilen) {PetscFree2(a->imax,a->ilen);}
    1201:   PetscFree(a->solve_work);
    1202:   PetscFree(a->mult_work);
    1203:   PetscFree(a->sor_workt);
    1204:   PetscFree(a->sor_work);
    1205:   ISDestroy(&a->icol);
    1206:   PetscFree(a->saved_values);
    1207:   PetscFree2(a->compressedrow.i,a->compressedrow.rindex);

    1209:   MatDestroy(&a->sbaijMat);
    1210:   MatDestroy(&a->parent);
    1211:   PetscFree(A->data);

    1213:   PetscObjectChangeTypeName((PetscObject)A,0);
    1214:   PetscObjectComposeFunction((PetscObject)A,"MatInvertBlockDiagonal_C",NULL);
    1215:   PetscObjectComposeFunction((PetscObject)A,"MatStoreValues_C",NULL);
    1216:   PetscObjectComposeFunction((PetscObject)A,"MatRetrieveValues_C",NULL);
    1217:   PetscObjectComposeFunction((PetscObject)A,"MatSeqBAIJSetColumnIndices_C",NULL);
    1218:   PetscObjectComposeFunction((PetscObject)A,"MatConvert_seqbaij_seqaij_C",NULL);
    1219:   PetscObjectComposeFunction((PetscObject)A,"MatConvert_seqbaij_seqsbaij_C",NULL);
    1220:   PetscObjectComposeFunction((PetscObject)A,"MatSeqBAIJSetPreallocation_C",NULL);
    1221:   PetscObjectComposeFunction((PetscObject)A,"MatSeqBAIJSetPreallocationCSR_C",NULL);
    1222:   PetscObjectComposeFunction((PetscObject)A,"MatConvert_seqbaij_seqbstrm_C",NULL);
    1223:   PetscObjectComposeFunction((PetscObject)A,"MatIsTranspose_C",NULL);
    1224: #if defined(PETSC_HAVE_HYPRE)
    1225:   PetscObjectComposeFunction((PetscObject)A,"MatConvert_seqbaij_hypre_C",NULL);
    1226: #endif
    1227:   PetscObjectComposeFunction((PetscObject)A,"MatConvert_seqbaij_is_C",NULL);
    1228:   PetscObjectComposeFunction((PetscObject)A,"MatPtAP_is_seqaij_C",NULL);
    1229:   return(0);
    1230: }

    1232: PetscErrorCode MatSetOption_SeqBAIJ(Mat A,MatOption op,PetscBool flg)
    1233: {
    1234:   Mat_SeqBAIJ    *a = (Mat_SeqBAIJ*)A->data;

    1238:   switch (op) {
    1239:   case MAT_ROW_ORIENTED:
    1240:     a->roworiented = flg;
    1241:     break;
    1242:   case MAT_KEEP_NONZERO_PATTERN:
    1243:     a->keepnonzeropattern = flg;
    1244:     break;
    1245:   case MAT_NEW_NONZERO_LOCATIONS:
    1246:     a->nonew = (flg ? 0 : 1);
    1247:     break;
    1248:   case MAT_NEW_NONZERO_LOCATION_ERR:
    1249:     a->nonew = (flg ? -1 : 0);
    1250:     break;
    1251:   case MAT_NEW_NONZERO_ALLOCATION_ERR:
    1252:     a->nonew = (flg ? -2 : 0);
    1253:     break;
    1254:   case MAT_UNUSED_NONZERO_LOCATION_ERR:
    1255:     a->nounused = (flg ? -1 : 0);
    1256:     break;
    1257:   case MAT_NEW_DIAGONALS:
    1258:   case MAT_IGNORE_OFF_PROC_ENTRIES:
    1259:   case MAT_USE_HASH_TABLE:
    1260:     PetscInfo1(A,"Option %s ignored\n",MatOptions[op]);
    1261:     break;
    1262:   case MAT_SPD:
    1263:   case MAT_SYMMETRIC:
    1264:   case MAT_STRUCTURALLY_SYMMETRIC:
    1265:   case MAT_HERMITIAN:
    1266:   case MAT_SYMMETRY_ETERNAL:
    1267:   case MAT_SUBMAT_SINGLEIS:
    1268:   case MAT_STRUCTURE_ONLY:
    1269:     /* These options are handled directly by MatSetOption() */
    1270:     break;
    1271:   default:
    1272:     SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_SUP,"unknown option %d",op);
    1273:   }
    1274:   return(0);
    1275: }

    1277: /* used for both SeqBAIJ and SeqSBAIJ matrices */
    1278: PetscErrorCode MatGetRow_SeqBAIJ_private(Mat A,PetscInt row,PetscInt *nz,PetscInt **idx,PetscScalar **v,PetscInt *ai,PetscInt *aj,PetscScalar *aa)
    1279: {
    1281:   PetscInt       itmp,i,j,k,M,bn,bp,*idx_i,bs,bs2;
    1282:   MatScalar      *aa_i;
    1283:   PetscScalar    *v_i;

    1286:   bs  = A->rmap->bs;
    1287:   bs2 = bs*bs;
    1288:   if (row < 0 || row >= A->rmap->N) SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Row %D out of range", row);

    1290:   bn  = row/bs;   /* Block number */
    1291:   bp  = row % bs; /* Block Position */
    1292:   M   = ai[bn+1] - ai[bn];
    1293:   *nz = bs*M;

    1295:   if (v) {
    1296:     *v = 0;
    1297:     if (*nz) {
    1298:       PetscMalloc1(*nz,v);
    1299:       for (i=0; i<M; i++) { /* for each block in the block row */
    1300:         v_i  = *v + i*bs;
    1301:         aa_i = aa + bs2*(ai[bn] + i);
    1302:         for (j=bp,k=0; j<bs2; j+=bs,k++) v_i[k] = aa_i[j];
    1303:       }
    1304:     }
    1305:   }

    1307:   if (idx) {
    1308:     *idx = 0;
    1309:     if (*nz) {
    1310:       PetscMalloc1(*nz,idx);
    1311:       for (i=0; i<M; i++) { /* for each block in the block row */
    1312:         idx_i = *idx + i*bs;
    1313:         itmp  = bs*aj[ai[bn] + i];
    1314:         for (j=0; j<bs; j++) idx_i[j] = itmp++;
    1315:       }
    1316:     }
    1317:   }
    1318:   return(0);
    1319: }

    1321: PetscErrorCode MatGetRow_SeqBAIJ(Mat A,PetscInt row,PetscInt *nz,PetscInt **idx,PetscScalar **v)
    1322: {
    1323:   Mat_SeqBAIJ    *a = (Mat_SeqBAIJ*)A->data;

    1327:   MatGetRow_SeqBAIJ_private(A,row,nz,idx,v,a->i,a->j,a->a);
    1328:   return(0);
    1329: }

    1331: PetscErrorCode MatRestoreRow_SeqBAIJ(Mat A,PetscInt row,PetscInt *nz,PetscInt **idx,PetscScalar **v)
    1332: {

    1336:   if (idx) {PetscFree(*idx);}
    1337:   if (v)   {PetscFree(*v);}
    1338:   return(0);
    1339: }

    1341: PetscErrorCode MatTranspose_SeqBAIJ(Mat A,MatReuse reuse,Mat *B)
    1342: {
    1343:   Mat_SeqBAIJ    *a=(Mat_SeqBAIJ*)A->data;
    1344:   Mat            C;
    1346:   PetscInt       i,j,k,*aj=a->j,*ai=a->i,bs=A->rmap->bs,mbs=a->mbs,nbs=a->nbs,len,*col;
    1347:   PetscInt       *rows,*cols,bs2=a->bs2;
    1348:   MatScalar      *array;

    1351:   if (reuse == MAT_INITIAL_MATRIX || reuse == MAT_INPLACE_MATRIX) {
    1352:     PetscCalloc1(1+nbs,&col);

    1354:     for (i=0; i<ai[mbs]; i++) col[aj[i]] += 1;
    1355:     MatCreate(PetscObjectComm((PetscObject)A),&C);
    1356:     MatSetSizes(C,A->cmap->n,A->rmap->N,A->cmap->n,A->rmap->N);
    1357:     MatSetType(C,((PetscObject)A)->type_name);
    1358:     MatSeqBAIJSetPreallocation(C,bs,0,col);
    1359:     PetscFree(col);
    1360:   } else {
    1361:     C = *B;
    1362:   }

    1364:   array = a->a;
    1365:   PetscMalloc2(bs,&rows,bs,&cols);
    1366:   for (i=0; i<mbs; i++) {
    1367:     cols[0] = i*bs;
    1368:     for (k=1; k<bs; k++) cols[k] = cols[k-1] + 1;
    1369:     len = ai[i+1] - ai[i];
    1370:     for (j=0; j<len; j++) {
    1371:       rows[0] = (*aj++)*bs;
    1372:       for (k=1; k<bs; k++) rows[k] = rows[k-1] + 1;
    1373:       MatSetValues_SeqBAIJ(C,bs,rows,bs,cols,array,INSERT_VALUES);
    1374:       array += bs2;
    1375:     }
    1376:   }
    1377:   PetscFree2(rows,cols);

    1379:   MatAssemblyBegin(C,MAT_FINAL_ASSEMBLY);
    1380:   MatAssemblyEnd(C,MAT_FINAL_ASSEMBLY);

    1382:   if (reuse == MAT_INITIAL_MATRIX || reuse == MAT_REUSE_MATRIX) {
    1383:     *B = C;
    1384:   } else {
    1385:     MatHeaderMerge(A,&C);
    1386:   }
    1387:   return(0);
    1388: }

    1390: PetscErrorCode MatIsTranspose_SeqBAIJ(Mat A,Mat B,PetscReal tol,PetscBool  *f)
    1391: {
    1393:   Mat            Btrans;

    1396:   *f   = PETSC_FALSE;
    1397:   MatTranspose_SeqBAIJ(A,MAT_INITIAL_MATRIX,&Btrans);
    1398:   MatEqual_SeqBAIJ(B,Btrans,f);
    1399:   MatDestroy(&Btrans);
    1400:   return(0);
    1401: }

    1403: static PetscErrorCode MatView_SeqBAIJ_Binary(Mat A,PetscViewer viewer)
    1404: {
    1405:   Mat_SeqBAIJ    *a = (Mat_SeqBAIJ*)A->data;
    1407:   PetscInt       i,*col_lens,bs = A->rmap->bs,count,*jj,j,k,l,bs2=a->bs2;
    1408:   int            fd;
    1409:   PetscScalar    *aa;
    1410:   FILE           *file;

    1413:   PetscViewerBinaryGetDescriptor(viewer,&fd);
    1414:   PetscMalloc1(4+A->rmap->N,&col_lens);
    1415:   col_lens[0] = MAT_FILE_CLASSID;

    1417:   col_lens[1] = A->rmap->N;
    1418:   col_lens[2] = A->cmap->n;
    1419:   col_lens[3] = a->nz*bs2;

    1421:   /* store lengths of each row and write (including header) to file */
    1422:   count = 0;
    1423:   for (i=0; i<a->mbs; i++) {
    1424:     for (j=0; j<bs; j++) {
    1425:       col_lens[4+count++] = bs*(a->i[i+1] - a->i[i]);
    1426:     }
    1427:   }
    1428:   PetscBinaryWrite(fd,col_lens,4+A->rmap->N,PETSC_INT,PETSC_TRUE);
    1429:   PetscFree(col_lens);

    1431:   /* store column indices (zero start index) */
    1432:   PetscMalloc1((a->nz+1)*bs2,&jj);
    1433:   count = 0;
    1434:   for (i=0; i<a->mbs; i++) {
    1435:     for (j=0; j<bs; j++) {
    1436:       for (k=a->i[i]; k<a->i[i+1]; k++) {
    1437:         for (l=0; l<bs; l++) {
    1438:           jj[count++] = bs*a->j[k] + l;
    1439:         }
    1440:       }
    1441:     }
    1442:   }
    1443:   PetscBinaryWrite(fd,jj,bs2*a->nz,PETSC_INT,PETSC_FALSE);
    1444:   PetscFree(jj);

    1446:   /* store nonzero values */
    1447:   PetscMalloc1((a->nz+1)*bs2,&aa);
    1448:   count = 0;
    1449:   for (i=0; i<a->mbs; i++) {
    1450:     for (j=0; j<bs; j++) {
    1451:       for (k=a->i[i]; k<a->i[i+1]; k++) {
    1452:         for (l=0; l<bs; l++) {
    1453:           aa[count++] = a->a[bs2*k + l*bs + j];
    1454:         }
    1455:       }
    1456:     }
    1457:   }
    1458:   PetscBinaryWrite(fd,aa,bs2*a->nz,PETSC_SCALAR,PETSC_FALSE);
    1459:   PetscFree(aa);

    1461:   PetscViewerBinaryGetInfoPointer(viewer,&file);
    1462:   if (file) {
    1463:     fprintf(file,"-matload_block_size %d\n",(int)A->rmap->bs);
    1464:   }
    1465:   return(0);
    1466: }

    1468: static PetscErrorCode MatView_SeqBAIJ_ASCII_structonly(Mat A,PetscViewer viewer)
    1469: {
    1471:   Mat_SeqBAIJ    *a = (Mat_SeqBAIJ*)A->data;
    1472:   PetscInt       i,bs = A->rmap->bs,k;

    1475:   PetscViewerASCIIUseTabs(viewer,PETSC_FALSE);
    1476:   for (i=0; i<a->mbs; i++) {
    1477:     PetscViewerASCIIPrintf(viewer,"row %D-%D:",i*bs,i*bs+bs-1);
    1478:     for (k=a->i[i]; k<a->i[i+1]; k++) {
    1479:       PetscViewerASCIIPrintf(viewer," (%D-%D) ",bs*a->j[k],bs*a->j[k]+bs-1);
    1480:     }
    1481:     PetscViewerASCIIPrintf(viewer,"\n");
    1482:   }
    1483:   PetscViewerASCIIUseTabs(viewer,PETSC_TRUE);
    1484:   return(0);
    1485: }

    1487: static PetscErrorCode MatView_SeqBAIJ_ASCII(Mat A,PetscViewer viewer)
    1488: {
    1489:   Mat_SeqBAIJ       *a = (Mat_SeqBAIJ*)A->data;
    1490:   PetscErrorCode    ierr;
    1491:   PetscInt          i,j,bs = A->rmap->bs,k,l,bs2=a->bs2;
    1492:   PetscViewerFormat format;

    1495:   if (A->structure_only) {
    1496:     MatView_SeqBAIJ_ASCII_structonly(A,viewer);
    1497:     return(0);
    1498:   }

    1500:   PetscViewerGetFormat(viewer,&format);
    1501:   if (format == PETSC_VIEWER_ASCII_INFO || format == PETSC_VIEWER_ASCII_INFO_DETAIL) {
    1502:     PetscViewerASCIIPrintf(viewer,"  block size is %D\n",bs);
    1503:   } else if (format == PETSC_VIEWER_ASCII_MATLAB) {
    1504:     const char *matname;
    1505:     Mat        aij;
    1506:     MatConvert(A,MATSEQAIJ,MAT_INITIAL_MATRIX,&aij);
    1507:     PetscObjectGetName((PetscObject)A,&matname);
    1508:     PetscObjectSetName((PetscObject)aij,matname);
    1509:     MatView(aij,viewer);
    1510:     MatDestroy(&aij);
    1511:   } else if (format == PETSC_VIEWER_ASCII_FACTOR_INFO) {
    1512:       return(0);
    1513:   } else if (format == PETSC_VIEWER_ASCII_COMMON) {
    1514:     PetscViewerASCIIUseTabs(viewer,PETSC_FALSE);
    1515:     for (i=0; i<a->mbs; i++) {
    1516:       for (j=0; j<bs; j++) {
    1517:         PetscViewerASCIIPrintf(viewer,"row %D:",i*bs+j);
    1518:         for (k=a->i[i]; k<a->i[i+1]; k++) {
    1519:           for (l=0; l<bs; l++) {
    1520: #if defined(PETSC_USE_COMPLEX)
    1521:             if (PetscImaginaryPart(a->a[bs2*k + l*bs + j]) > 0.0 && PetscRealPart(a->a[bs2*k + l*bs + j]) != 0.0) {
    1522:               PetscViewerASCIIPrintf(viewer," (%D, %g + %gi) ",bs*a->j[k]+l,
    1523:                                             (double)PetscRealPart(a->a[bs2*k + l*bs + j]),(double)PetscImaginaryPart(a->a[bs2*k + l*bs + j]));
    1524:             } else if (PetscImaginaryPart(a->a[bs2*k + l*bs + j]) < 0.0 && PetscRealPart(a->a[bs2*k + l*bs + j]) != 0.0) {
    1525:               PetscViewerASCIIPrintf(viewer," (%D, %g - %gi) ",bs*a->j[k]+l,
    1526:                                             (double)PetscRealPart(a->a[bs2*k + l*bs + j]),-(double)PetscImaginaryPart(a->a[bs2*k + l*bs + j]));
    1527:             } else if (PetscRealPart(a->a[bs2*k + l*bs + j]) != 0.0) {
    1528:               PetscViewerASCIIPrintf(viewer," (%D, %g) ",bs*a->j[k]+l,(double)PetscRealPart(a->a[bs2*k + l*bs + j]));
    1529:             }
    1530: #else
    1531:             if (a->a[bs2*k + l*bs + j] != 0.0) {
    1532:               PetscViewerASCIIPrintf(viewer," (%D, %g) ",bs*a->j[k]+l,(double)a->a[bs2*k + l*bs + j]);
    1533:             }
    1534: #endif
    1535:           }
    1536:         }
    1537:         PetscViewerASCIIPrintf(viewer,"\n");
    1538:       }
    1539:     }
    1540:     PetscViewerASCIIUseTabs(viewer,PETSC_TRUE);
    1541:   } else {
    1542:     PetscViewerASCIIUseTabs(viewer,PETSC_FALSE);
    1543:     for (i=0; i<a->mbs; i++) {
    1544:       for (j=0; j<bs; j++) {
    1545:         PetscViewerASCIIPrintf(viewer,"row %D:",i*bs+j);
    1546:         for (k=a->i[i]; k<a->i[i+1]; k++) {
    1547:           for (l=0; l<bs; l++) {
    1548: #if defined(PETSC_USE_COMPLEX)
    1549:             if (PetscImaginaryPart(a->a[bs2*k + l*bs + j]) > 0.0) {
    1550:               PetscViewerASCIIPrintf(viewer," (%D, %g + %g i) ",bs*a->j[k]+l,
    1551:                                             (double)PetscRealPart(a->a[bs2*k + l*bs + j]),(double)PetscImaginaryPart(a->a[bs2*k + l*bs + j]));
    1552:             } else if (PetscImaginaryPart(a->a[bs2*k + l*bs + j]) < 0.0) {
    1553:               PetscViewerASCIIPrintf(viewer," (%D, %g - %g i) ",bs*a->j[k]+l,
    1554:                                             (double)PetscRealPart(a->a[bs2*k + l*bs + j]),-(double)PetscImaginaryPart(a->a[bs2*k + l*bs + j]));
    1555:             } else {
    1556:               PetscViewerASCIIPrintf(viewer," (%D, %g) ",bs*a->j[k]+l,(double)PetscRealPart(a->a[bs2*k + l*bs + j]));
    1557:             }
    1558: #else
    1559:             PetscViewerASCIIPrintf(viewer," (%D, %g) ",bs*a->j[k]+l,(double)a->a[bs2*k + l*bs + j]);
    1560: #endif
    1561:           }
    1562:         }
    1563:         PetscViewerASCIIPrintf(viewer,"\n");
    1564:       }
    1565:     }
    1566:     PetscViewerASCIIUseTabs(viewer,PETSC_TRUE);
    1567:   }
    1568:   PetscViewerFlush(viewer);
    1569:   return(0);
    1570: }

    1572:  #include <petscdraw.h>
    1573: static PetscErrorCode MatView_SeqBAIJ_Draw_Zoom(PetscDraw draw,void *Aa)
    1574: {
    1575:   Mat               A = (Mat) Aa;
    1576:   Mat_SeqBAIJ       *a=(Mat_SeqBAIJ*)A->data;
    1577:   PetscErrorCode    ierr;
    1578:   PetscInt          row,i,j,k,l,mbs=a->mbs,color,bs=A->rmap->bs,bs2=a->bs2;
    1579:   PetscReal         xl,yl,xr,yr,x_l,x_r,y_l,y_r;
    1580:   MatScalar         *aa;
    1581:   PetscViewer       viewer;
    1582:   PetscViewerFormat format;

    1585:   PetscObjectQuery((PetscObject)A,"Zoomviewer",(PetscObject*)&viewer);
    1586:   PetscViewerGetFormat(viewer,&format);
    1587:   PetscDrawGetCoordinates(draw,&xl,&yl,&xr,&yr);

    1589:   /* loop over matrix elements drawing boxes */

    1591:   if (format != PETSC_VIEWER_DRAW_CONTOUR) {
    1592:     PetscDrawCollectiveBegin(draw);
    1593:     /* Blue for negative, Cyan for zero and  Red for positive */
    1594:     color = PETSC_DRAW_BLUE;
    1595:     for (i=0,row=0; i<mbs; i++,row+=bs) {
    1596:       for (j=a->i[i]; j<a->i[i+1]; j++) {
    1597:         y_l = A->rmap->N - row - 1.0; y_r = y_l + 1.0;
    1598:         x_l = a->j[j]*bs; x_r = x_l + 1.0;
    1599:         aa  = a->a + j*bs2;
    1600:         for (k=0; k<bs; k++) {
    1601:           for (l=0; l<bs; l++) {
    1602:             if (PetscRealPart(*aa++) >=  0.) continue;
    1603:             PetscDrawRectangle(draw,x_l+k,y_l-l,x_r+k,y_r-l,color,color,color,color);
    1604:           }
    1605:         }
    1606:       }
    1607:     }
    1608:     color = PETSC_DRAW_CYAN;
    1609:     for (i=0,row=0; i<mbs; i++,row+=bs) {
    1610:       for (j=a->i[i]; j<a->i[i+1]; j++) {
    1611:         y_l = A->rmap->N - row - 1.0; y_r = y_l + 1.0;
    1612:         x_l = a->j[j]*bs; x_r = x_l + 1.0;
    1613:         aa  = a->a + j*bs2;
    1614:         for (k=0; k<bs; k++) {
    1615:           for (l=0; l<bs; l++) {
    1616:             if (PetscRealPart(*aa++) != 0.) continue;
    1617:             PetscDrawRectangle(draw,x_l+k,y_l-l,x_r+k,y_r-l,color,color,color,color);
    1618:           }
    1619:         }
    1620:       }
    1621:     }
    1622:     color = PETSC_DRAW_RED;
    1623:     for (i=0,row=0; i<mbs; i++,row+=bs) {
    1624:       for (j=a->i[i]; j<a->i[i+1]; j++) {
    1625:         y_l = A->rmap->N - row - 1.0; y_r = y_l + 1.0;
    1626:         x_l = a->j[j]*bs; x_r = x_l + 1.0;
    1627:         aa  = a->a + j*bs2;
    1628:         for (k=0; k<bs; k++) {
    1629:           for (l=0; l<bs; l++) {
    1630:             if (PetscRealPart(*aa++) <= 0.) continue;
    1631:             PetscDrawRectangle(draw,x_l+k,y_l-l,x_r+k,y_r-l,color,color,color,color);
    1632:           }
    1633:         }
    1634:       }
    1635:     }
    1636:     PetscDrawCollectiveEnd(draw);
    1637:   } else {
    1638:     /* use contour shading to indicate magnitude of values */
    1639:     /* first determine max of all nonzero values */
    1640:     PetscReal minv = 0.0, maxv = 0.0;
    1641:     PetscDraw popup;

    1643:     for (i=0; i<a->nz*a->bs2; i++) {
    1644:       if (PetscAbsScalar(a->a[i]) > maxv) maxv = PetscAbsScalar(a->a[i]);
    1645:     }
    1646:     if (minv >= maxv) maxv = minv + PETSC_SMALL;
    1647:     PetscDrawGetPopup(draw,&popup);
    1648:     PetscDrawScalePopup(popup,0.0,maxv);

    1650:     PetscDrawCollectiveBegin(draw);
    1651:     for (i=0,row=0; i<mbs; i++,row+=bs) {
    1652:       for (j=a->i[i]; j<a->i[i+1]; j++) {
    1653:         y_l = A->rmap->N - row - 1.0; y_r = y_l + 1.0;
    1654:         x_l = a->j[j]*bs; x_r = x_l + 1.0;
    1655:         aa  = a->a + j*bs2;
    1656:         for (k=0; k<bs; k++) {
    1657:           for (l=0; l<bs; l++) {
    1658:             MatScalar v = *aa++;
    1659:             color = PetscDrawRealToColor(PetscAbsScalar(v),minv,maxv);
    1660:             PetscDrawRectangle(draw,x_l+k,y_l-l,x_r+k,y_r-l,color,color,color,color);
    1661:           }
    1662:         }
    1663:       }
    1664:     }
    1665:     PetscDrawCollectiveEnd(draw);
    1666:   }
    1667:   return(0);
    1668: }

    1670: static PetscErrorCode MatView_SeqBAIJ_Draw(Mat A,PetscViewer viewer)
    1671: {
    1673:   PetscReal      xl,yl,xr,yr,w,h;
    1674:   PetscDraw      draw;
    1675:   PetscBool      isnull;

    1678:   PetscViewerDrawGetDraw(viewer,0,&draw);
    1679:   PetscDrawIsNull(draw,&isnull);
    1680:   if (isnull) return(0);

    1682:   xr   = A->cmap->n; yr = A->rmap->N; h = yr/10.0; w = xr/10.0;
    1683:   xr  += w;          yr += h;        xl = -w;     yl = -h;
    1684:   PetscDrawSetCoordinates(draw,xl,yl,xr,yr);
    1685:   PetscObjectCompose((PetscObject)A,"Zoomviewer",(PetscObject)viewer);
    1686:   PetscDrawZoom(draw,MatView_SeqBAIJ_Draw_Zoom,A);
    1687:   PetscObjectCompose((PetscObject)A,"Zoomviewer",NULL);
    1688:   PetscDrawSave(draw);
    1689:   return(0);
    1690: }

    1692: PetscErrorCode MatView_SeqBAIJ(Mat A,PetscViewer viewer)
    1693: {
    1695:   PetscBool      iascii,isbinary,isdraw;

    1698:   PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERASCII,&iascii);
    1699:   PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERBINARY,&isbinary);
    1700:   PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERDRAW,&isdraw);
    1701:   if (iascii) {
    1702:     MatView_SeqBAIJ_ASCII(A,viewer);
    1703:   } else if (isbinary) {
    1704:     MatView_SeqBAIJ_Binary(A,viewer);
    1705:   } else if (isdraw) {
    1706:     MatView_SeqBAIJ_Draw(A,viewer);
    1707:   } else {
    1708:     Mat B;
    1709:     MatConvert(A,MATSEQAIJ,MAT_INITIAL_MATRIX,&B);
    1710:     MatView(B,viewer);
    1711:     MatDestroy(&B);
    1712:   }
    1713:   return(0);
    1714: }

    1717: PetscErrorCode MatGetValues_SeqBAIJ(Mat A,PetscInt m,const PetscInt im[],PetscInt n,const PetscInt in[],PetscScalar v[])
    1718: {
    1719:   Mat_SeqBAIJ *a = (Mat_SeqBAIJ*)A->data;
    1720:   PetscInt    *rp,k,low,high,t,row,nrow,i,col,l,*aj = a->j;
    1721:   PetscInt    *ai = a->i,*ailen = a->ilen;
    1722:   PetscInt    brow,bcol,ridx,cidx,bs=A->rmap->bs,bs2=a->bs2;
    1723:   MatScalar   *ap,*aa = a->a;

    1726:   for (k=0; k<m; k++) { /* loop over rows */
    1727:     row = im[k]; brow = row/bs;
    1728:     if (row < 0) {v += n; continue;} /* SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Negative row"); */
    1729:     if (row >= A->rmap->N) SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Row %D too large", row);
    1730:     rp   = aj + ai[brow]; ap = aa + bs2*ai[brow];
    1731:     nrow = ailen[brow];
    1732:     for (l=0; l<n; l++) { /* loop over columns */
    1733:       if (in[l] < 0) {v++; continue;} /* SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Negative column"); */
    1734:       if (in[l] >= A->cmap->n) SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Column %D too large", in[l]);
    1735:       col  = in[l];
    1736:       bcol = col/bs;
    1737:       cidx = col%bs;
    1738:       ridx = row%bs;
    1739:       high = nrow;
    1740:       low  = 0; /* assume unsorted */
    1741:       while (high-low > 5) {
    1742:         t = (low+high)/2;
    1743:         if (rp[t] > bcol) high = t;
    1744:         else             low  = t;
    1745:       }
    1746:       for (i=low; i<high; i++) {
    1747:         if (rp[i] > bcol) break;
    1748:         if (rp[i] == bcol) {
    1749:           *v++ = ap[bs2*i+bs*cidx+ridx];
    1750:           goto finished;
    1751:         }
    1752:       }
    1753:       *v++ = 0.0;
    1754: finished:;
    1755:     }
    1756:   }
    1757:   return(0);
    1758: }

    1760: PetscErrorCode MatSetValuesBlocked_SeqBAIJ(Mat A,PetscInt m,const PetscInt im[],PetscInt n,const PetscInt in[],const PetscScalar v[],InsertMode is)
    1761: {
    1762:   Mat_SeqBAIJ       *a = (Mat_SeqBAIJ*)A->data;
    1763:   PetscInt          *rp,k,low,high,t,ii,jj,row,nrow,i,col,l,rmax,N,lastcol = -1;
    1764:   PetscInt          *imax=a->imax,*ai=a->i,*ailen=a->ilen;
    1765:   PetscErrorCode    ierr;
    1766:   PetscInt          *aj        =a->j,nonew=a->nonew,bs2=a->bs2,bs=A->rmap->bs,stepval;
    1767:   PetscBool         roworiented=a->roworiented;
    1768:   const PetscScalar *value     = v;
    1769:   MatScalar         *ap=NULL,*aa = a->a,*bap;

    1772:   if (roworiented) {
    1773:     stepval = (n-1)*bs;
    1774:   } else {
    1775:     stepval = (m-1)*bs;
    1776:   }
    1777:   for (k=0; k<m; k++) { /* loop over added rows */
    1778:     row = im[k];
    1779:     if (row < 0) continue;
    1780: #if defined(PETSC_USE_DEBUG)
    1781:     if (row >= a->mbs) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Block row index too large %D max %D",row,a->mbs-1);
    1782: #endif
    1783:     rp   = aj + ai[row];
    1784:     if (!A->structure_only) ap = aa + bs2*ai[row];
    1785:     rmax = imax[row];
    1786:     nrow = ailen[row];
    1787:     low  = 0;
    1788:     high = nrow;
    1789:     for (l=0; l<n; l++) { /* loop over added columns */
    1790:       if (in[l] < 0) continue;
    1791: #if defined(PETSC_USE_DEBUG)
    1792:       if (in[l] >= a->nbs) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Block column index too large %D max %D",in[l],a->nbs-1);
    1793: #endif
    1794:       col = in[l];
    1795:       if (!A->structure_only) {
    1796:         if (roworiented) {
    1797:           value = v + (k*(stepval+bs) + l)*bs;
    1798:         } else {
    1799:           value = v + (l*(stepval+bs) + k)*bs;
    1800:         }
    1801:       }
    1802:       if (col <= lastcol) low = 0;
    1803:       else high = nrow;
    1804:       lastcol = col;
    1805:       while (high-low > 7) {
    1806:         t = (low+high)/2;
    1807:         if (rp[t] > col) high = t;
    1808:         else             low  = t;
    1809:       }
    1810:       for (i=low; i<high; i++) {
    1811:         if (rp[i] > col) break;
    1812:         if (rp[i] == col) {
    1813:           if (A->structure_only) goto noinsert2;
    1814:           bap = ap +  bs2*i;
    1815:           if (roworiented) {
    1816:             if (is == ADD_VALUES) {
    1817:               for (ii=0; ii<bs; ii++,value+=stepval) {
    1818:                 for (jj=ii; jj<bs2; jj+=bs) {
    1819:                   bap[jj] += *value++;
    1820:                 }
    1821:               }
    1822:             } else {
    1823:               for (ii=0; ii<bs; ii++,value+=stepval) {
    1824:                 for (jj=ii; jj<bs2; jj+=bs) {
    1825:                   bap[jj] = *value++;
    1826:                 }
    1827:               }
    1828:             }
    1829:           } else {
    1830:             if (is == ADD_VALUES) {
    1831:               for (ii=0; ii<bs; ii++,value+=bs+stepval) {
    1832:                 for (jj=0; jj<bs; jj++) {
    1833:                   bap[jj] += value[jj];
    1834:                 }
    1835:                 bap += bs;
    1836:               }
    1837:             } else {
    1838:               for (ii=0; ii<bs; ii++,value+=bs+stepval) {
    1839:                 for (jj=0; jj<bs; jj++) {
    1840:                   bap[jj]  = value[jj];
    1841:                 }
    1842:                 bap += bs;
    1843:               }
    1844:             }
    1845:           }
    1846:           goto noinsert2;
    1847:         }
    1848:       }
    1849:       if (nonew == 1) goto noinsert2;
    1850:       if (nonew == -1) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Inserting a new blocked index new nonzero block (%D, %D) in the matrix", row, col);
    1851:       if (A->structure_only) {
    1852:         MatSeqXAIJReallocateAIJ_structure_only(A,a->mbs,bs2,nrow,row,col,rmax,ai,aj,rp,imax,nonew,MatScalar);
    1853:       } else {
    1854:         MatSeqXAIJReallocateAIJ(A,a->mbs,bs2,nrow,row,col,rmax,aa,ai,aj,rp,ap,imax,nonew,MatScalar);
    1855:       }
    1856:       N = nrow++ - 1; high++;
    1857:       /* shift up all the later entries in this row */
    1858:       for (ii=N; ii>=i; ii--) {
    1859:         rp[ii+1] = rp[ii];
    1860:         if (!A->structure_only) {
    1861:           PetscMemcpy(ap+bs2*(ii+1),ap+bs2*(ii),bs2*sizeof(MatScalar));
    1862:         }
    1863:       }
    1864:       if (N >= i && !A->structure_only) {
    1865:         PetscMemzero(ap+bs2*i,bs2*sizeof(MatScalar));
    1866:       }

    1868:       rp[i] = col;
    1869:       if (!A->structure_only) {
    1870:         bap   = ap +  bs2*i;
    1871:         if (roworiented) {
    1872:           for (ii=0; ii<bs; ii++,value+=stepval) {
    1873:             for (jj=ii; jj<bs2; jj+=bs) {
    1874:               bap[jj] = *value++;
    1875:             }
    1876:           }
    1877:         } else {
    1878:           for (ii=0; ii<bs; ii++,value+=stepval) {
    1879:             for (jj=0; jj<bs; jj++) {
    1880:               *bap++ = *value++;
    1881:             }
    1882:           }
    1883:         }
    1884:       }
    1885: noinsert2:;
    1886:       low = i;
    1887:     }
    1888:     ailen[row] = nrow;
    1889:   }
    1890:   return(0);
    1891: }

    1893: PetscErrorCode MatAssemblyEnd_SeqBAIJ(Mat A,MatAssemblyType mode)
    1894: {
    1895:   Mat_SeqBAIJ    *a     = (Mat_SeqBAIJ*)A->data;
    1896:   PetscInt       fshift = 0,i,j,*ai = a->i,*aj = a->j,*imax = a->imax;
    1897:   PetscInt       m      = A->rmap->N,*ip,N,*ailen = a->ilen;
    1899:   PetscInt       mbs  = a->mbs,bs2 = a->bs2,rmax = 0;
    1900:   MatScalar      *aa  = a->a,*ap;
    1901:   PetscReal      ratio=0.6;

    1904:   if (mode == MAT_FLUSH_ASSEMBLY) return(0);

    1906:   if (m) rmax = ailen[0];
    1907:   for (i=1; i<mbs; i++) {
    1908:     /* move each row back by the amount of empty slots (fshift) before it*/
    1909:     fshift += imax[i-1] - ailen[i-1];
    1910:     rmax    = PetscMax(rmax,ailen[i]);
    1911:     if (fshift) {
    1912:       ip = aj + ai[i]; ap = aa + bs2*ai[i];
    1913:       N  = ailen[i];
    1914:       for (j=0; j<N; j++) {
    1915:         ip[j-fshift] = ip[j];
    1916:         if (!A->structure_only) {
    1917:           PetscMemcpy(ap+(j-fshift)*bs2,ap+j*bs2,bs2*sizeof(MatScalar));
    1918:         }
    1919:       }
    1920:     }
    1921:     ai[i] = ai[i-1] + ailen[i-1];
    1922:   }
    1923:   if (mbs) {
    1924:     fshift += imax[mbs-1] - ailen[mbs-1];
    1925:     ai[mbs] = ai[mbs-1] + ailen[mbs-1];
    1926:   }

    1928:   /* reset ilen and imax for each row */
    1929:   a->nonzerorowcnt = 0;
    1930:   if (A->structure_only) {
    1931:     PetscFree2(a->imax,a->ilen);
    1932:   } else { /* !A->structure_only */
    1933:     for (i=0; i<mbs; i++) {
    1934:       ailen[i] = imax[i] = ai[i+1] - ai[i];
    1935:       a->nonzerorowcnt += ((ai[i+1] - ai[i]) > 0);
    1936:     }
    1937:   }
    1938:   a->nz = ai[mbs];

    1940:   /* diagonals may have moved, so kill the diagonal pointers */
    1941:   a->idiagvalid = PETSC_FALSE;
    1942:   if (fshift && a->diag) {
    1943:     PetscFree(a->diag);
    1944:     PetscLogObjectMemory((PetscObject)A,-(mbs+1)*sizeof(PetscInt));
    1945:     a->diag = 0;
    1946:   }
    1947:   if (fshift && a->nounused == -1) SETERRQ4(PETSC_COMM_SELF,PETSC_ERR_PLIB, "Unused space detected in matrix: %D X %D block size %D, %D unneeded", m, A->cmap->n, A->rmap->bs, fshift*bs2);
    1948:   PetscInfo5(A,"Matrix size: %D X %D, block size %D; storage space: %D unneeded, %D used\n",m,A->cmap->n,A->rmap->bs,fshift*bs2,a->nz*bs2);
    1949:   PetscInfo1(A,"Number of mallocs during MatSetValues is %D\n",a->reallocs);
    1950:   PetscInfo1(A,"Most nonzeros blocks in any row is %D\n",rmax);

    1952:   A->info.mallocs    += a->reallocs;
    1953:   a->reallocs         = 0;
    1954:   A->info.nz_unneeded = (PetscReal)fshift*bs2;
    1955:   a->rmax             = rmax;

    1957:   if (!A->structure_only) {
    1958:     MatCheckCompressedRow(A,a->nonzerorowcnt,&a->compressedrow,a->i,mbs,ratio);
    1959:   }
    1960:   return(0);
    1961: }

    1963: /*
    1964:    This function returns an array of flags which indicate the locations of contiguous
    1965:    blocks that should be zeroed. for eg: if bs = 3  and is = [0,1,2,3,5,6,7,8,9]
    1966:    then the resulting sizes = [3,1,1,3,1] correspondig to sets [(0,1,2),(3),(5),(6,7,8),(9)]
    1967:    Assume: sizes should be long enough to hold all the values.
    1968: */
    1969: static PetscErrorCode MatZeroRows_SeqBAIJ_Check_Blocks(PetscInt idx[],PetscInt n,PetscInt bs,PetscInt sizes[], PetscInt *bs_max)
    1970: {
    1971:   PetscInt  i,j,k,row;
    1972:   PetscBool flg;

    1975:   for (i=0,j=0; i<n; j++) {
    1976:     row = idx[i];
    1977:     if (row%bs!=0) { /* Not the begining of a block */
    1978:       sizes[j] = 1;
    1979:       i++;
    1980:     } else if (i+bs > n) { /* complete block doesn't exist (at idx end) */
    1981:       sizes[j] = 1;         /* Also makes sure atleast 'bs' values exist for next else */
    1982:       i++;
    1983:     } else { /* Begining of the block, so check if the complete block exists */
    1984:       flg = PETSC_TRUE;
    1985:       for (k=1; k<bs; k++) {
    1986:         if (row+k != idx[i+k]) { /* break in the block */
    1987:           flg = PETSC_FALSE;
    1988:           break;
    1989:         }
    1990:       }
    1991:       if (flg) { /* No break in the bs */
    1992:         sizes[j] = bs;
    1993:         i       += bs;
    1994:       } else {
    1995:         sizes[j] = 1;
    1996:         i++;
    1997:       }
    1998:     }
    1999:   }
    2000:   *bs_max = j;
    2001:   return(0);
    2002: }

    2004: PetscErrorCode MatZeroRows_SeqBAIJ(Mat A,PetscInt is_n,const PetscInt is_idx[],PetscScalar diag,Vec x, Vec b)
    2005: {
    2006:   Mat_SeqBAIJ       *baij=(Mat_SeqBAIJ*)A->data;
    2007:   PetscErrorCode    ierr;
    2008:   PetscInt          i,j,k,count,*rows;
    2009:   PetscInt          bs=A->rmap->bs,bs2=baij->bs2,*sizes,row,bs_max;
    2010:   PetscScalar       zero = 0.0;
    2011:   MatScalar         *aa;
    2012:   const PetscScalar *xx;
    2013:   PetscScalar       *bb;

    2016:   /* fix right hand side if needed */
    2017:   if (x && b) {
    2018:     VecGetArrayRead(x,&xx);
    2019:     VecGetArray(b,&bb);
    2020:     for (i=0; i<is_n; i++) {
    2021:       bb[is_idx[i]] = diag*xx[is_idx[i]];
    2022:     }
    2023:     VecRestoreArrayRead(x,&xx);
    2024:     VecRestoreArray(b,&bb);
    2025:   }

    2027:   /* Make a copy of the IS and  sort it */
    2028:   /* allocate memory for rows,sizes */
    2029:   PetscMalloc2(is_n,&rows,2*is_n,&sizes);

    2031:   /* copy IS values to rows, and sort them */
    2032:   for (i=0; i<is_n; i++) rows[i] = is_idx[i];
    2033:   PetscSortInt(is_n,rows);

    2035:   if (baij->keepnonzeropattern) {
    2036:     for (i=0; i<is_n; i++) sizes[i] = 1;
    2037:     bs_max          = is_n;
    2038:   } else {
    2039:     MatZeroRows_SeqBAIJ_Check_Blocks(rows,is_n,bs,sizes,&bs_max);
    2040:     A->nonzerostate++;
    2041:   }

    2043:   for (i=0,j=0; i<bs_max; j+=sizes[i],i++) {
    2044:     row = rows[j];
    2045:     if (row < 0 || row > A->rmap->N) SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"row %D out of range",row);
    2046:     count = (baij->i[row/bs +1] - baij->i[row/bs])*bs;
    2047:     aa    = ((MatScalar*)(baij->a)) + baij->i[row/bs]*bs2 + (row%bs);
    2048:     if (sizes[i] == bs && !baij->keepnonzeropattern) {
    2049:       if (diag != (PetscScalar)0.0) {
    2050:         if (baij->ilen[row/bs] > 0) {
    2051:           baij->ilen[row/bs]       = 1;
    2052:           baij->j[baij->i[row/bs]] = row/bs;

    2054:           PetscMemzero(aa,count*bs*sizeof(MatScalar));
    2055:         }
    2056:         /* Now insert all the diagonal values for this bs */
    2057:         for (k=0; k<bs; k++) {
    2058:           (*A->ops->setvalues)(A,1,rows+j+k,1,rows+j+k,&diag,INSERT_VALUES);
    2059:         }
    2060:       } else { /* (diag == 0.0) */
    2061:         baij->ilen[row/bs] = 0;
    2062:       } /* end (diag == 0.0) */
    2063:     } else { /* (sizes[i] != bs) */
    2064: #if defined(PETSC_USE_DEBUG)
    2065:       if (sizes[i] != 1) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_PLIB,"Internal Error. Value should be 1");
    2066: #endif
    2067:       for (k=0; k<count; k++) {
    2068:         aa[0] =  zero;
    2069:         aa   += bs;
    2070:       }
    2071:       if (diag != (PetscScalar)0.0) {
    2072:         (*A->ops->setvalues)(A,1,rows+j,1,rows+j,&diag,INSERT_VALUES);
    2073:       }
    2074:     }
    2075:   }

    2077:   PetscFree2(rows,sizes);
    2078:   MatAssemblyEnd_SeqBAIJ(A,MAT_FINAL_ASSEMBLY);
    2079:   return(0);
    2080: }

    2082: PetscErrorCode MatZeroRowsColumns_SeqBAIJ(Mat A,PetscInt is_n,const PetscInt is_idx[],PetscScalar diag,Vec x, Vec b)
    2083: {
    2084:   Mat_SeqBAIJ       *baij=(Mat_SeqBAIJ*)A->data;
    2085:   PetscErrorCode    ierr;
    2086:   PetscInt          i,j,k,count;
    2087:   PetscInt          bs   =A->rmap->bs,bs2=baij->bs2,row,col;
    2088:   PetscScalar       zero = 0.0;
    2089:   MatScalar         *aa;
    2090:   const PetscScalar *xx;
    2091:   PetscScalar       *bb;
    2092:   PetscBool         *zeroed,vecs = PETSC_FALSE;

    2095:   /* fix right hand side if needed */
    2096:   if (x && b) {
    2097:     VecGetArrayRead(x,&xx);
    2098:     VecGetArray(b,&bb);
    2099:     vecs = PETSC_TRUE;
    2100:   }

    2102:   /* zero the columns */
    2103:   PetscCalloc1(A->rmap->n,&zeroed);
    2104:   for (i=0; i<is_n; i++) {
    2105:     if (is_idx[i] < 0 || is_idx[i] >= A->rmap->N) SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"row %D out of range",is_idx[i]);
    2106:     zeroed[is_idx[i]] = PETSC_TRUE;
    2107:   }
    2108:   for (i=0; i<A->rmap->N; i++) {
    2109:     if (!zeroed[i]) {
    2110:       row = i/bs;
    2111:       for (j=baij->i[row]; j<baij->i[row+1]; j++) {
    2112:         for (k=0; k<bs; k++) {
    2113:           col = bs*baij->j[j] + k;
    2114:           if (zeroed[col]) {
    2115:             aa = ((MatScalar*)(baij->a)) + j*bs2 + (i%bs) + bs*k;
    2116:             if (vecs) bb[i] -= aa[0]*xx[col];
    2117:             aa[0] = 0.0;
    2118:           }
    2119:         }
    2120:       }
    2121:     } else if (vecs) bb[i] = diag*xx[i];
    2122:   }
    2123:   PetscFree(zeroed);
    2124:   if (vecs) {
    2125:     VecRestoreArrayRead(x,&xx);
    2126:     VecRestoreArray(b,&bb);
    2127:   }

    2129:   /* zero the rows */
    2130:   for (i=0; i<is_n; i++) {
    2131:     row   = is_idx[i];
    2132:     count = (baij->i[row/bs +1] - baij->i[row/bs])*bs;
    2133:     aa    = ((MatScalar*)(baij->a)) + baij->i[row/bs]*bs2 + (row%bs);
    2134:     for (k=0; k<count; k++) {
    2135:       aa[0] =  zero;
    2136:       aa   += bs;
    2137:     }
    2138:     if (diag != (PetscScalar)0.0) {
    2139:       (*A->ops->setvalues)(A,1,&row,1,&row,&diag,INSERT_VALUES);
    2140:     }
    2141:   }
    2142:   MatAssemblyEnd_SeqBAIJ(A,MAT_FINAL_ASSEMBLY);
    2143:   return(0);
    2144: }

    2146: PetscErrorCode MatSetValues_SeqBAIJ(Mat A,PetscInt m,const PetscInt im[],PetscInt n,const PetscInt in[],const PetscScalar v[],InsertMode is)
    2147: {
    2148:   Mat_SeqBAIJ    *a = (Mat_SeqBAIJ*)A->data;
    2149:   PetscInt       *rp,k,low,high,t,ii,row,nrow,i,col,l,rmax,N,lastcol = -1;
    2150:   PetscInt       *imax=a->imax,*ai=a->i,*ailen=a->ilen;
    2151:   PetscInt       *aj  =a->j,nonew=a->nonew,bs=A->rmap->bs,brow,bcol;
    2153:   PetscInt       ridx,cidx,bs2=a->bs2;
    2154:   PetscBool      roworiented=a->roworiented;
    2155:   MatScalar      *ap=NULL,value=0.0,*aa=a->a,*bap;

    2158:   for (k=0; k<m; k++) { /* loop over added rows */
    2159:     row  = im[k];
    2160:     brow = row/bs;
    2161:     if (row < 0) continue;
    2162: #if defined(PETSC_USE_DEBUG)
    2163:     if (row >= A->rmap->N) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Row too large: row %D max %D",row,A->rmap->N-1);
    2164: #endif
    2165:     rp   = aj + ai[brow];
    2166:     if (!A->structure_only) ap = aa + bs2*ai[brow];
    2167:     rmax = imax[brow];
    2168:     nrow = ailen[brow];
    2169:     low  = 0;
    2170:     high = nrow;
    2171:     for (l=0; l<n; l++) { /* loop over added columns */
    2172:       if (in[l] < 0) continue;
    2173: #if defined(PETSC_USE_DEBUG)
    2174:       if (in[l] >= A->cmap->n) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Column too large: col %D max %D",in[l],A->cmap->n-1);
    2175: #endif
    2176:       col  = in[l]; bcol = col/bs;
    2177:       ridx = row % bs; cidx = col % bs;
    2178:       if (!A->structure_only) {
    2179:         if (roworiented) {
    2180:           value = v[l + k*n];
    2181:         } else {
    2182:           value = v[k + l*m];
    2183:         }
    2184:       }
    2185:       if (col <= lastcol) low = 0; else high = nrow;
    2186:       lastcol = col;
    2187:       while (high-low > 7) {
    2188:         t = (low+high)/2;
    2189:         if (rp[t] > bcol) high = t;
    2190:         else              low  = t;
    2191:       }
    2192:       for (i=low; i<high; i++) {
    2193:         if (rp[i] > bcol) break;
    2194:         if (rp[i] == bcol) {
    2195:           bap = ap +  bs2*i + bs*cidx + ridx;
    2196:           if (!A->structure_only) {
    2197:             if (is == ADD_VALUES) *bap += value;
    2198:             else                  *bap  = value;
    2199:           }
    2200:           goto noinsert1;
    2201:         }
    2202:       }
    2203:       if (nonew == 1) goto noinsert1;
    2204:       if (nonew == -1) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Inserting a new nonzero (%D, %D) in the matrix", row, col);
    2205:       if (A->structure_only) {
    2206:         MatSeqXAIJReallocateAIJ_structure_only(A,a->mbs,bs2,nrow,brow,bcol,rmax,ai,aj,rp,imax,nonew,MatScalar);
    2207:       } else {
    2208:         MatSeqXAIJReallocateAIJ(A,a->mbs,bs2,nrow,brow,bcol,rmax,aa,ai,aj,rp,ap,imax,nonew,MatScalar);
    2209:       }
    2210:       N = nrow++ - 1; high++;
    2211:       /* shift up all the later entries in this row */
    2212:       for (ii=N; ii>=i; ii--) {
    2213:         rp[ii+1] = rp[ii];
    2214:         if (!A->structure_only) {
    2215:           PetscMemcpy(ap+bs2*(ii+1),ap+bs2*(ii),bs2*sizeof(MatScalar));
    2216:         }
    2217:       }
    2218:       if (N>=i && !A->structure_only) {
    2219:         PetscMemzero(ap+bs2*i,bs2*sizeof(MatScalar));
    2220:       }
    2221:       rp[i]                      = bcol;
    2222:       if (!A->structure_only) ap[bs2*i + bs*cidx + ridx] = value;
    2223:       a->nz++;
    2224:       A->nonzerostate++;
    2225: noinsert1:;
    2226:       low = i;
    2227:     }
    2228:     ailen[brow] = nrow;
    2229:   }
    2230:   return(0);
    2231: }

    2233: PetscErrorCode MatILUFactor_SeqBAIJ(Mat inA,IS row,IS col,const MatFactorInfo *info)
    2234: {
    2235:   Mat_SeqBAIJ    *a = (Mat_SeqBAIJ*)inA->data;
    2236:   Mat            outA;
    2238:   PetscBool      row_identity,col_identity;

    2241:   if (info->levels != 0) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"Only levels = 0 supported for in-place ILU");
    2242:   ISIdentity(row,&row_identity);
    2243:   ISIdentity(col,&col_identity);
    2244:   if (!row_identity || !col_identity) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONG,"Row and column permutations must be identity for in-place ILU");

    2246:   outA            = inA;
    2247:   inA->factortype = MAT_FACTOR_LU;
    2248:   PetscFree(inA->solvertype);
    2249:   PetscStrallocpy(MATSOLVERPETSC,&inA->solvertype);

    2251:   MatMarkDiagonal_SeqBAIJ(inA);

    2253:   PetscObjectReference((PetscObject)row);
    2254:   ISDestroy(&a->row);
    2255:   a->row = row;
    2256:   PetscObjectReference((PetscObject)col);
    2257:   ISDestroy(&a->col);
    2258:   a->col = col;

    2260:   /* Create the invert permutation so that it can be used in MatLUFactorNumeric() */
    2261:   ISDestroy(&a->icol);
    2262:   ISInvertPermutation(col,PETSC_DECIDE,&a->icol);
    2263:   PetscLogObjectParent((PetscObject)inA,(PetscObject)a->icol);

    2265:   MatSeqBAIJSetNumericFactorization_inplace(inA,(PetscBool)(row_identity && col_identity));
    2266:   if (!a->solve_work) {
    2267:     PetscMalloc1(inA->rmap->N+inA->rmap->bs,&a->solve_work);
    2268:     PetscLogObjectMemory((PetscObject)inA,(inA->rmap->N+inA->rmap->bs)*sizeof(PetscScalar));
    2269:   }
    2270:   MatLUFactorNumeric(outA,inA,info);
    2271:   return(0);
    2272: }

    2274: PetscErrorCode  MatSeqBAIJSetColumnIndices_SeqBAIJ(Mat mat,PetscInt *indices)
    2275: {
    2276:   Mat_SeqBAIJ *baij = (Mat_SeqBAIJ*)mat->data;
    2277:   PetscInt    i,nz,mbs;

    2280:   nz  = baij->maxnz;
    2281:   mbs = baij->mbs;
    2282:   for (i=0; i<nz; i++) {
    2283:     baij->j[i] = indices[i];
    2284:   }
    2285:   baij->nz = nz;
    2286:   for (i=0; i<mbs; i++) {
    2287:     baij->ilen[i] = baij->imax[i];
    2288:   }
    2289:   return(0);
    2290: }

    2292: /*@
    2293:     MatSeqBAIJSetColumnIndices - Set the column indices for all the rows
    2294:        in the matrix.

    2296:   Input Parameters:
    2297: +  mat - the SeqBAIJ matrix
    2298: -  indices - the column indices

    2300:   Level: advanced

    2302:   Notes:
    2303:     This can be called if you have precomputed the nonzero structure of the
    2304:   matrix and want to provide it to the matrix object to improve the performance
    2305:   of the MatSetValues() operation.

    2307:     You MUST have set the correct numbers of nonzeros per row in the call to
    2308:   MatCreateSeqBAIJ(), and the columns indices MUST be sorted.

    2310:     MUST be called before any calls to MatSetValues();

    2312: @*/
    2313: PetscErrorCode  MatSeqBAIJSetColumnIndices(Mat mat,PetscInt *indices)
    2314: {

    2320:   PetscUseMethod(mat,"MatSeqBAIJSetColumnIndices_C",(Mat,PetscInt*),(mat,indices));
    2321:   return(0);
    2322: }

    2324: PetscErrorCode MatGetRowMaxAbs_SeqBAIJ(Mat A,Vec v,PetscInt idx[])
    2325: {
    2326:   Mat_SeqBAIJ    *a = (Mat_SeqBAIJ*)A->data;
    2328:   PetscInt       i,j,n,row,bs,*ai,*aj,mbs;
    2329:   PetscReal      atmp;
    2330:   PetscScalar    *x,zero = 0.0;
    2331:   MatScalar      *aa;
    2332:   PetscInt       ncols,brow,krow,kcol;

    2335:   if (A->factortype) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Not for factored matrix");
    2336:   bs  = A->rmap->bs;
    2337:   aa  = a->a;
    2338:   ai  = a->i;
    2339:   aj  = a->j;
    2340:   mbs = a->mbs;

    2342:   VecSet(v,zero);
    2343:   VecGetArray(v,&x);
    2344:   VecGetLocalSize(v,&n);
    2345:   if (n != A->rmap->N) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"Nonconforming matrix and vector");
    2346:   for (i=0; i<mbs; i++) {
    2347:     ncols = ai[1] - ai[0]; ai++;
    2348:     brow  = bs*i;
    2349:     for (j=0; j<ncols; j++) {
    2350:       for (kcol=0; kcol<bs; kcol++) {
    2351:         for (krow=0; krow<bs; krow++) {
    2352:           atmp = PetscAbsScalar(*aa);aa++;
    2353:           row  = brow + krow;   /* row index */
    2354:           if (PetscAbsScalar(x[row]) < atmp) {x[row] = atmp; if (idx) idx[row] = bs*(*aj) + kcol;}
    2355:         }
    2356:       }
    2357:       aj++;
    2358:     }
    2359:   }
    2360:   VecRestoreArray(v,&x);
    2361:   return(0);
    2362: }

    2364: PetscErrorCode MatCopy_SeqBAIJ(Mat A,Mat B,MatStructure str)
    2365: {

    2369:   /* If the two matrices have the same copy implementation, use fast copy. */
    2370:   if (str == SAME_NONZERO_PATTERN && (A->ops->copy == B->ops->copy)) {
    2371:     Mat_SeqBAIJ *a  = (Mat_SeqBAIJ*)A->data;
    2372:     Mat_SeqBAIJ *b  = (Mat_SeqBAIJ*)B->data;
    2373:     PetscInt    ambs=a->mbs,bmbs=b->mbs,abs=A->rmap->bs,bbs=B->rmap->bs,bs2=abs*abs;

    2375:     if (a->i[ambs] != b->i[bmbs]) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_INCOMP,"Number of nonzero blocks in matrices A %D and B %D are different",a->i[ambs],b->i[bmbs]);
    2376:     if (abs != bbs) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_INCOMP,"Block size A %D and B %D are different",abs,bbs);
    2377:     PetscMemcpy(b->a,a->a,(bs2*a->i[ambs])*sizeof(PetscScalar));
    2378:     PetscObjectStateIncrease((PetscObject)B);
    2379:   } else {
    2380:     MatCopy_Basic(A,B,str);
    2381:   }
    2382:   return(0);
    2383: }

    2385: PetscErrorCode MatSetUp_SeqBAIJ(Mat A)
    2386: {

    2390:   MatSeqBAIJSetPreallocation(A,A->rmap->bs,PETSC_DEFAULT,0);
    2391:   return(0);
    2392: }

    2394: PetscErrorCode MatSeqBAIJGetArray_SeqBAIJ(Mat A,PetscScalar *array[])
    2395: {
    2396:   Mat_SeqBAIJ *a = (Mat_SeqBAIJ*)A->data;

    2399:   *array = a->a;
    2400:   return(0);
    2401: }

    2403: PetscErrorCode MatSeqBAIJRestoreArray_SeqBAIJ(Mat A,PetscScalar *array[])
    2404: {
    2406:   return(0);
    2407: }

    2409: PetscErrorCode MatAXPYGetPreallocation_SeqBAIJ(Mat Y,Mat X,PetscInt *nnz)
    2410: {
    2411:   PetscInt       bs = Y->rmap->bs,mbs = Y->rmap->N/bs;
    2412:   Mat_SeqBAIJ    *x = (Mat_SeqBAIJ*)X->data;
    2413:   Mat_SeqBAIJ    *y = (Mat_SeqBAIJ*)Y->data;

    2417:   /* Set the number of nonzeros in the new matrix */
    2418:   MatAXPYGetPreallocation_SeqX_private(mbs,x->i,x->j,y->i,y->j,nnz);
    2419:   return(0);
    2420: }

    2422: PetscErrorCode MatAXPY_SeqBAIJ(Mat Y,PetscScalar a,Mat X,MatStructure str)
    2423: {
    2424:   Mat_SeqBAIJ    *x = (Mat_SeqBAIJ*)X->data,*y = (Mat_SeqBAIJ*)Y->data;
    2426:   PetscInt       bs=Y->rmap->bs,bs2=bs*bs;
    2427:   PetscBLASInt   one=1;

    2430:   if (str == SAME_NONZERO_PATTERN) {
    2431:     PetscScalar  alpha = a;
    2432:     PetscBLASInt bnz;
    2433:     PetscBLASIntCast(x->nz*bs2,&bnz);
    2434:     PetscStackCallBLAS("BLASaxpy",BLASaxpy_(&bnz,&alpha,x->a,&one,y->a,&one));
    2435:     PetscObjectStateIncrease((PetscObject)Y);
    2436:   } else if (str == SUBSET_NONZERO_PATTERN) { /* nonzeros of X is a subset of Y's */
    2437:     MatAXPY_Basic(Y,a,X,str);
    2438:   } else {
    2439:     Mat      B;
    2440:     PetscInt *nnz;
    2441:     if (bs != X->rmap->bs) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"Matrices must have same block size");
    2442:     PetscMalloc1(Y->rmap->N,&nnz);
    2443:     MatCreate(PetscObjectComm((PetscObject)Y),&B);
    2444:     PetscObjectSetName((PetscObject)B,((PetscObject)Y)->name);
    2445:     MatSetSizes(B,Y->rmap->n,Y->cmap->n,Y->rmap->N,Y->cmap->N);
    2446:     MatSetBlockSizesFromMats(B,Y,Y);
    2447:     MatSetType(B,(MatType) ((PetscObject)Y)->type_name);
    2448:     MatAXPYGetPreallocation_SeqBAIJ(Y,X,nnz);
    2449:     MatSeqBAIJSetPreallocation(B,bs,0,nnz);
    2450:     MatAXPY_BasicWithPreallocation(B,Y,a,X,str);
    2451:     MatHeaderReplace(Y,&B);
    2452:     PetscFree(nnz);
    2453:   }
    2454:   return(0);
    2455: }

    2457: PetscErrorCode MatRealPart_SeqBAIJ(Mat A)
    2458: {
    2459:   Mat_SeqBAIJ *a = (Mat_SeqBAIJ*)A->data;
    2460:   PetscInt    i,nz = a->bs2*a->i[a->mbs];
    2461:   MatScalar   *aa = a->a;

    2464:   for (i=0; i<nz; i++) aa[i] = PetscRealPart(aa[i]);
    2465:   return(0);
    2466: }

    2468: PetscErrorCode MatImaginaryPart_SeqBAIJ(Mat A)
    2469: {
    2470:   Mat_SeqBAIJ *a = (Mat_SeqBAIJ*)A->data;
    2471:   PetscInt    i,nz = a->bs2*a->i[a->mbs];
    2472:   MatScalar   *aa = a->a;

    2475:   for (i=0; i<nz; i++) aa[i] = PetscImaginaryPart(aa[i]);
    2476:   return(0);
    2477: }

    2479: /*
    2480:     Code almost idential to MatGetColumnIJ_SeqAIJ() should share common code
    2481: */
    2482: PetscErrorCode MatGetColumnIJ_SeqBAIJ(Mat A,PetscInt oshift,PetscBool symmetric,PetscBool inodecompressed,PetscInt *nn,const PetscInt *ia[],const PetscInt *ja[],PetscBool  *done)
    2483: {
    2484:   Mat_SeqBAIJ    *a = (Mat_SeqBAIJ*)A->data;
    2486:   PetscInt       bs = A->rmap->bs,i,*collengths,*cia,*cja,n = A->cmap->n/bs,m = A->rmap->n/bs;
    2487:   PetscInt       nz = a->i[m],row,*jj,mr,col;

    2490:   *nn = n;
    2491:   if (!ia) return(0);
    2492:   if (symmetric) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"Not for BAIJ matrices");
    2493:   else {
    2494:     PetscCalloc1(n+1,&collengths);
    2495:     PetscMalloc1(n+1,&cia);
    2496:     PetscMalloc1(nz+1,&cja);
    2497:     jj   = a->j;
    2498:     for (i=0; i<nz; i++) {
    2499:       collengths[jj[i]]++;
    2500:     }
    2501:     cia[0] = oshift;
    2502:     for (i=0; i<n; i++) {
    2503:       cia[i+1] = cia[i] + collengths[i];
    2504:     }
    2505:     PetscMemzero(collengths,n*sizeof(PetscInt));
    2506:     jj   = a->j;
    2507:     for (row=0; row<m; row++) {
    2508:       mr = a->i[row+1] - a->i[row];
    2509:       for (i=0; i<mr; i++) {
    2510:         col = *jj++;

    2512:         cja[cia[col] + collengths[col]++ - oshift] = row + oshift;
    2513:       }
    2514:     }
    2515:     PetscFree(collengths);
    2516:     *ia  = cia; *ja = cja;
    2517:   }
    2518:   return(0);
    2519: }

    2521: PetscErrorCode MatRestoreColumnIJ_SeqBAIJ(Mat A,PetscInt oshift,PetscBool symmetric,PetscBool inodecompressed,PetscInt *n,const PetscInt *ia[],const PetscInt *ja[],PetscBool  *done)
    2522: {

    2526:   if (!ia) return(0);
    2527:   PetscFree(*ia);
    2528:   PetscFree(*ja);
    2529:   return(0);
    2530: }

    2532: /*
    2533:  MatGetColumnIJ_SeqBAIJ_Color() and MatRestoreColumnIJ_SeqBAIJ_Color() are customized from
    2534:  MatGetColumnIJ_SeqBAIJ() and MatRestoreColumnIJ_SeqBAIJ() by adding an output
    2535:  spidx[], index of a->a, to be used in MatTransposeColoringCreate() and MatFDColoringCreate()
    2536:  */
    2537: PetscErrorCode MatGetColumnIJ_SeqBAIJ_Color(Mat A,PetscInt oshift,PetscBool symmetric,PetscBool inodecompressed,PetscInt *nn,const PetscInt *ia[],const PetscInt *ja[],PetscInt *spidx[],PetscBool  *done)
    2538: {
    2539:   Mat_SeqBAIJ    *a = (Mat_SeqBAIJ*)A->data;
    2541:   PetscInt       i,*collengths,*cia,*cja,n=a->nbs,m=a->mbs;
    2542:   PetscInt       nz = a->i[m],row,*jj,mr,col;
    2543:   PetscInt       *cspidx;

    2546:   *nn = n;
    2547:   if (!ia) return(0);

    2549:   PetscCalloc1(n+1,&collengths);
    2550:   PetscMalloc1(n+1,&cia);
    2551:   PetscMalloc1(nz+1,&cja);
    2552:   PetscMalloc1(nz+1,&cspidx);
    2553:   jj   = a->j;
    2554:   for (i=0; i<nz; i++) {
    2555:     collengths[jj[i]]++;
    2556:   }
    2557:   cia[0] = oshift;
    2558:   for (i=0; i<n; i++) {
    2559:     cia[i+1] = cia[i] + collengths[i];
    2560:   }
    2561:   PetscMemzero(collengths,n*sizeof(PetscInt));
    2562:   jj   = a->j;
    2563:   for (row=0; row<m; row++) {
    2564:     mr = a->i[row+1] - a->i[row];
    2565:     for (i=0; i<mr; i++) {
    2566:       col = *jj++;
    2567:       cspidx[cia[col] + collengths[col] - oshift] = a->i[row] + i; /* index of a->j */
    2568:       cja[cia[col] + collengths[col]++ - oshift]  = row + oshift;
    2569:     }
    2570:   }
    2571:   PetscFree(collengths);
    2572:   *ia    = cia; *ja = cja;
    2573:   *spidx = cspidx;
    2574:   return(0);
    2575: }

    2577: PetscErrorCode MatRestoreColumnIJ_SeqBAIJ_Color(Mat A,PetscInt oshift,PetscBool symmetric,PetscBool inodecompressed,PetscInt *n,const PetscInt *ia[],const PetscInt *ja[],PetscInt *spidx[],PetscBool  *done)
    2578: {

    2582:   MatRestoreColumnIJ_SeqBAIJ(A,oshift,symmetric,inodecompressed,n,ia,ja,done);
    2583:   PetscFree(*spidx);
    2584:   return(0);
    2585: }

    2587: PetscErrorCode MatShift_SeqBAIJ(Mat Y,PetscScalar a)
    2588: {
    2590:   Mat_SeqBAIJ     *aij = (Mat_SeqBAIJ*)Y->data;

    2593:   if (!Y->preallocated || !aij->nz) {
    2594:     MatSeqBAIJSetPreallocation(Y,Y->rmap->bs,1,NULL);
    2595:   }
    2596:   MatShift_Basic(Y,a);
    2597:   return(0);
    2598: }

    2600: /* -------------------------------------------------------------------*/
    2601: static struct _MatOps MatOps_Values = {MatSetValues_SeqBAIJ,
    2602:                                        MatGetRow_SeqBAIJ,
    2603:                                        MatRestoreRow_SeqBAIJ,
    2604:                                        MatMult_SeqBAIJ_N,
    2605:                                /* 4*/  MatMultAdd_SeqBAIJ_N,
    2606:                                        MatMultTranspose_SeqBAIJ,
    2607:                                        MatMultTransposeAdd_SeqBAIJ,
    2608:                                        0,
    2609:                                        0,
    2610:                                        0,
    2611:                                /* 10*/ 0,
    2612:                                        MatLUFactor_SeqBAIJ,
    2613:                                        0,
    2614:                                        0,
    2615:                                        MatTranspose_SeqBAIJ,
    2616:                                /* 15*/ MatGetInfo_SeqBAIJ,
    2617:                                        MatEqual_SeqBAIJ,
    2618:                                        MatGetDiagonal_SeqBAIJ,
    2619:                                        MatDiagonalScale_SeqBAIJ,
    2620:                                        MatNorm_SeqBAIJ,
    2621:                                /* 20*/ 0,
    2622:                                        MatAssemblyEnd_SeqBAIJ,
    2623:                                        MatSetOption_SeqBAIJ,
    2624:                                        MatZeroEntries_SeqBAIJ,
    2625:                                /* 24*/ MatZeroRows_SeqBAIJ,
    2626:                                        0,
    2627:                                        0,
    2628:                                        0,
    2629:                                        0,
    2630:                                /* 29*/ MatSetUp_SeqBAIJ,
    2631:                                        0,
    2632:                                        0,
    2633:                                        0,
    2634:                                        0,
    2635:                                /* 34*/ MatDuplicate_SeqBAIJ,
    2636:                                        0,
    2637:                                        0,
    2638:                                        MatILUFactor_SeqBAIJ,
    2639:                                        0,
    2640:                                /* 39*/ MatAXPY_SeqBAIJ,
    2641:                                        MatCreateSubMatrices_SeqBAIJ,
    2642:                                        MatIncreaseOverlap_SeqBAIJ,
    2643:                                        MatGetValues_SeqBAIJ,
    2644:                                        MatCopy_SeqBAIJ,
    2645:                                /* 44*/ 0,
    2646:                                        MatScale_SeqBAIJ,
    2647:                                        MatShift_SeqBAIJ,
    2648:                                        0,
    2649:                                        MatZeroRowsColumns_SeqBAIJ,
    2650:                                /* 49*/ 0,
    2651:                                        MatGetRowIJ_SeqBAIJ,
    2652:                                        MatRestoreRowIJ_SeqBAIJ,
    2653:                                        MatGetColumnIJ_SeqBAIJ,
    2654:                                        MatRestoreColumnIJ_SeqBAIJ,
    2655:                                /* 54*/ MatFDColoringCreate_SeqXAIJ,
    2656:                                        0,
    2657:                                        0,
    2658:                                        0,
    2659:                                        MatSetValuesBlocked_SeqBAIJ,
    2660:                                /* 59*/ MatCreateSubMatrix_SeqBAIJ,
    2661:                                        MatDestroy_SeqBAIJ,
    2662:                                        MatView_SeqBAIJ,
    2663:                                        0,
    2664:                                        0,
    2665:                                /* 64*/ 0,
    2666:                                        0,
    2667:                                        0,
    2668:                                        0,
    2669:                                        0,
    2670:                                /* 69*/ MatGetRowMaxAbs_SeqBAIJ,
    2671:                                        0,
    2672:                                        MatConvert_Basic,
    2673:                                        0,
    2674:                                        0,
    2675:                                /* 74*/ 0,
    2676:                                        MatFDColoringApply_BAIJ,
    2677:                                        0,
    2678:                                        0,
    2679:                                        0,
    2680:                                /* 79*/ 0,
    2681:                                        0,
    2682:                                        0,
    2683:                                        0,
    2684:                                        MatLoad_SeqBAIJ,
    2685:                                /* 84*/ 0,
    2686:                                        0,
    2687:                                        0,
    2688:                                        0,
    2689:                                        0,
    2690:                                /* 89*/ 0,
    2691:                                        0,
    2692:                                        0,
    2693:                                        0,
    2694:                                        0,
    2695:                                /* 94*/ 0,
    2696:                                        0,
    2697:                                        0,
    2698:                                        0,
    2699:                                        0,
    2700:                                /* 99*/ 0,
    2701:                                        0,
    2702:                                        0,
    2703:                                        0,
    2704:                                        0,
    2705:                                /*104*/ 0,
    2706:                                        MatRealPart_SeqBAIJ,
    2707:                                        MatImaginaryPart_SeqBAIJ,
    2708:                                        0,
    2709:                                        0,
    2710:                                /*109*/ 0,
    2711:                                        0,
    2712:                                        0,
    2713:                                        0,
    2714:                                        MatMissingDiagonal_SeqBAIJ,
    2715:                                /*114*/ 0,
    2716:                                        0,
    2717:                                        0,
    2718:                                        0,
    2719:                                        0,
    2720:                                /*119*/ 0,
    2721:                                        0,
    2722:                                        MatMultHermitianTranspose_SeqBAIJ,
    2723:                                        MatMultHermitianTransposeAdd_SeqBAIJ,
    2724:                                        0,
    2725:                                /*124*/ 0,
    2726:                                        0,
    2727:                                        MatInvertBlockDiagonal_SeqBAIJ,
    2728:                                        0,
    2729:                                        0,
    2730:                                /*129*/ 0,
    2731:                                        0,
    2732:                                        0,
    2733:                                        0,
    2734:                                        0,
    2735:                                /*134*/ 0,
    2736:                                        0,
    2737:                                        0,
    2738:                                        0,
    2739:                                        0,
    2740:                                /*139*/ MatSetBlockSizes_Default,
    2741:                                        0,
    2742:                                        0,
    2743:                                        MatFDColoringSetUp_SeqXAIJ,
    2744:                                        0,
    2745:                                 /*144*/MatCreateMPIMatConcatenateSeqMat_SeqBAIJ,
    2746:                                        MatDestroySubMatrices_SeqBAIJ
    2747: };

    2749: PetscErrorCode  MatStoreValues_SeqBAIJ(Mat mat)
    2750: {
    2751:   Mat_SeqBAIJ    *aij = (Mat_SeqBAIJ*)mat->data;
    2752:   PetscInt       nz   = aij->i[aij->mbs]*aij->bs2;

    2756:   if (aij->nonew != 1) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ORDER,"Must call MatSetOption(A,MAT_NEW_NONZERO_LOCATIONS,PETSC_FALSE);first");

    2758:   /* allocate space for values if not already there */
    2759:   if (!aij->saved_values) {
    2760:     PetscMalloc1(nz+1,&aij->saved_values);
    2761:     PetscLogObjectMemory((PetscObject)mat,(nz+1)*sizeof(PetscScalar));
    2762:   }

    2764:   /* copy values over */
    2765:   PetscMemcpy(aij->saved_values,aij->a,nz*sizeof(PetscScalar));
    2766:   return(0);
    2767: }

    2769: PetscErrorCode  MatRetrieveValues_SeqBAIJ(Mat mat)
    2770: {
    2771:   Mat_SeqBAIJ    *aij = (Mat_SeqBAIJ*)mat->data;
    2773:   PetscInt       nz = aij->i[aij->mbs]*aij->bs2;

    2776:   if (aij->nonew != 1) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ORDER,"Must call MatSetOption(A,MAT_NEW_NONZERO_LOCATIONS,PETSC_FALSE);first");
    2777:   if (!aij->saved_values) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ORDER,"Must call MatStoreValues(A);first");

    2779:   /* copy values over */
    2780:   PetscMemcpy(aij->a,aij->saved_values,nz*sizeof(PetscScalar));
    2781:   return(0);
    2782: }

    2784: PETSC_INTERN PetscErrorCode MatConvert_SeqBAIJ_SeqAIJ(Mat, MatType,MatReuse,Mat*);
    2785: PETSC_INTERN PetscErrorCode MatConvert_SeqBAIJ_SeqSBAIJ(Mat, MatType,MatReuse,Mat*);

    2787: PetscErrorCode  MatSeqBAIJSetPreallocation_SeqBAIJ(Mat B,PetscInt bs,PetscInt nz,PetscInt *nnz)
    2788: {
    2789:   Mat_SeqBAIJ    *b;
    2791:   PetscInt       i,mbs,nbs,bs2;
    2792:   PetscBool      flg = PETSC_FALSE,skipallocation = PETSC_FALSE,realalloc = PETSC_FALSE;

    2795:   if (nz >= 0 || nnz) realalloc = PETSC_TRUE;
    2796:   if (nz == MAT_SKIP_ALLOCATION) {
    2797:     skipallocation = PETSC_TRUE;
    2798:     nz             = 0;
    2799:   }

    2801:   MatSetBlockSize(B,PetscAbs(bs));
    2802:   PetscLayoutSetUp(B->rmap);
    2803:   PetscLayoutSetUp(B->cmap);
    2804:   PetscLayoutGetBlockSize(B->rmap,&bs);

    2806:   B->preallocated = PETSC_TRUE;

    2808:   mbs = B->rmap->n/bs;
    2809:   nbs = B->cmap->n/bs;
    2810:   bs2 = bs*bs;

    2812:   if (mbs*bs!=B->rmap->n || nbs*bs!=B->cmap->n) SETERRQ3(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"Number rows %D, cols %D must be divisible by blocksize %D",B->rmap->N,B->cmap->n,bs);

    2814:   if (nz == PETSC_DEFAULT || nz == PETSC_DECIDE) nz = 5;
    2815:   if (nz < 0) SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"nz cannot be less than 0: value %D",nz);
    2816:   if (nnz) {
    2817:     for (i=0; i<mbs; i++) {
    2818:       if (nnz[i] < 0) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"nnz cannot be less than 0: local row %D value %D",i,nnz[i]);
    2819:       if (nnz[i] > nbs) SETERRQ3(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"nnz cannot be greater than block row length: local row %D value %D rowlength %D",i,nnz[i],nbs);
    2820:     }
    2821:   }

    2823:   b    = (Mat_SeqBAIJ*)B->data;
    2824:   PetscOptionsBegin(PetscObjectComm((PetscObject)B),NULL,"Optimize options for SEQBAIJ matrix 2 ","Mat");
    2825:   PetscOptionsBool("-mat_no_unroll","Do not optimize for block size (slow)",NULL,flg,&flg,NULL);
    2826:   PetscOptionsEnd();

    2828:   if (!flg) {
    2829:     switch (bs) {
    2830:     case 1:
    2831:       B->ops->mult    = MatMult_SeqBAIJ_1;
    2832:       B->ops->multadd = MatMultAdd_SeqBAIJ_1;
    2833:       break;
    2834:     case 2:
    2835:       B->ops->mult    = MatMult_SeqBAIJ_2;
    2836:       B->ops->multadd = MatMultAdd_SeqBAIJ_2;
    2837:       break;
    2838:     case 3:
    2839:       B->ops->mult    = MatMult_SeqBAIJ_3;
    2840:       B->ops->multadd = MatMultAdd_SeqBAIJ_3;
    2841:       break;
    2842:     case 4:
    2843:       B->ops->mult    = MatMult_SeqBAIJ_4;
    2844:       B->ops->multadd = MatMultAdd_SeqBAIJ_4;
    2845:       break;
    2846:     case 5:
    2847:       B->ops->mult    = MatMult_SeqBAIJ_5;
    2848:       B->ops->multadd = MatMultAdd_SeqBAIJ_5;
    2849:       break;
    2850:     case 6:
    2851:       B->ops->mult    = MatMult_SeqBAIJ_6;
    2852:       B->ops->multadd = MatMultAdd_SeqBAIJ_6;
    2853:       break;
    2854:     case 7:
    2855:       B->ops->mult    = MatMult_SeqBAIJ_7;
    2856:       B->ops->multadd = MatMultAdd_SeqBAIJ_7;
    2857:       break;
    2858:     case 9:
    2859: #if defined(PETSC_HAVE_IMMINTRIN_H) && defined(__AVX2__) && defined(__FMA__) && defined(PETSC_USE_REAL_DOUBLE) && !defined(PETSC_USE_COMPLEX) && !defined(PETSC_USE_64BIT_INDICES)
    2860:       B->ops->mult    = MatMult_SeqBAIJ_9_AVX2;
    2861:       B->ops->multadd = MatMultAdd_SeqBAIJ_9_AVX2;
    2862: #else
    2863:       B->ops->mult    = MatMult_SeqBAIJ_N;
    2864:       B->ops->multadd = MatMultAdd_SeqBAIJ_N;
    2865: #endif
    2866:       break;
    2867:     case 11:
    2868:       B->ops->mult    = MatMult_SeqBAIJ_11;
    2869:       B->ops->multadd = MatMultAdd_SeqBAIJ_11;
    2870:       break;
    2871:     case 15:
    2872:       B->ops->mult    = MatMult_SeqBAIJ_15_ver1;
    2873:       B->ops->multadd = MatMultAdd_SeqBAIJ_N;
    2874:       break;
    2875:     default:
    2876:       B->ops->mult    = MatMult_SeqBAIJ_N;
    2877:       B->ops->multadd = MatMultAdd_SeqBAIJ_N;
    2878:       break;
    2879:     }
    2880:   }
    2881:   B->ops->sor = MatSOR_SeqBAIJ;
    2882:   b->mbs = mbs;
    2883:   b->nbs = nbs;
    2884:   if (!skipallocation) {
    2885:     if (!b->imax) {
    2886:       PetscMalloc2(mbs,&b->imax,mbs,&b->ilen);
    2887:       PetscLogObjectMemory((PetscObject)B,2*mbs*sizeof(PetscInt));

    2889:       b->free_imax_ilen = PETSC_TRUE;
    2890:     }
    2891:     /* b->ilen will count nonzeros in each block row so far. */
    2892:     for (i=0; i<mbs; i++) b->ilen[i] = 0;
    2893:     if (!nnz) {
    2894:       if (nz == PETSC_DEFAULT || nz == PETSC_DECIDE) nz = 5;
    2895:       else if (nz < 0) nz = 1;
    2896:       for (i=0; i<mbs; i++) b->imax[i] = nz;
    2897:       nz = nz*mbs;
    2898:     } else {
    2899:       nz = 0;
    2900:       for (i=0; i<mbs; i++) {b->imax[i] = nnz[i]; nz += nnz[i];}
    2901:     }

    2903:     /* allocate the matrix space */
    2904:     MatSeqXAIJFreeAIJ(B,&b->a,&b->j,&b->i);
    2905:     if (B->structure_only) {
    2906:       PetscMalloc1(nz,&b->j);
    2907:       PetscMalloc1(B->rmap->N+1,&b->i);
    2908:       PetscLogObjectMemory((PetscObject)B,(B->rmap->N+1)*sizeof(PetscInt)+nz*sizeof(PetscInt));
    2909:     } else {
    2910:       PetscMalloc3(bs2*nz,&b->a,nz,&b->j,B->rmap->N+1,&b->i);
    2911:       PetscLogObjectMemory((PetscObject)B,(B->rmap->N+1)*sizeof(PetscInt)+nz*(bs2*sizeof(PetscScalar)+sizeof(PetscInt)));
    2912:       PetscMemzero(b->a,nz*bs2*sizeof(MatScalar));
    2913:     }
    2914:     PetscMemzero(b->j,nz*sizeof(PetscInt));

    2916:     if (B->structure_only) {
    2917:       b->singlemalloc = PETSC_FALSE;
    2918:       b->free_a       = PETSC_FALSE;
    2919:     } else {
    2920:       b->singlemalloc = PETSC_TRUE;
    2921:       b->free_a       = PETSC_TRUE;
    2922:     }
    2923:     b->free_ij = PETSC_TRUE;

    2925:     b->i[0] = 0;
    2926:     for (i=1; i<mbs+1; i++) {
    2927:       b->i[i] = b->i[i-1] + b->imax[i-1];
    2928:     }

    2930:   } else {
    2931:     b->free_a  = PETSC_FALSE;
    2932:     b->free_ij = PETSC_FALSE;
    2933:   }

    2935:   b->bs2              = bs2;
    2936:   b->mbs              = mbs;
    2937:   b->nz               = 0;
    2938:   b->maxnz            = nz;
    2939:   B->info.nz_unneeded = (PetscReal)b->maxnz*bs2;
    2940:   B->was_assembled    = PETSC_FALSE;
    2941:   B->assembled        = PETSC_FALSE;
    2942:   if (realalloc) {MatSetOption(B,MAT_NEW_NONZERO_ALLOCATION_ERR,PETSC_TRUE);}
    2943:   return(0);
    2944: }

    2946: PetscErrorCode MatSeqBAIJSetPreallocationCSR_SeqBAIJ(Mat B,PetscInt bs,const PetscInt ii[],const PetscInt jj[],const PetscScalar V[])
    2947: {
    2948:   PetscInt       i,m,nz,nz_max=0,*nnz;
    2949:   PetscScalar    *values=0;
    2950:   PetscBool      roworiented = ((Mat_SeqBAIJ*)B->data)->roworiented;

    2954:   if (bs < 1) SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Invalid block size specified, must be positive but it is %D",bs);
    2955:   PetscLayoutSetBlockSize(B->rmap,bs);
    2956:   PetscLayoutSetBlockSize(B->cmap,bs);
    2957:   PetscLayoutSetUp(B->rmap);
    2958:   PetscLayoutSetUp(B->cmap);
    2959:   PetscLayoutGetBlockSize(B->rmap,&bs);
    2960:   m    = B->rmap->n/bs;

    2962:   if (ii[0] != 0) SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE, "ii[0] must be 0 but it is %D",ii[0]);
    2963:   PetscMalloc1(m+1, &nnz);
    2964:   for (i=0; i<m; i++) {
    2965:     nz = ii[i+1]- ii[i];
    2966:     if (nz < 0) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE, "Local row %D has a negative number of columns %D",i,nz);
    2967:     nz_max = PetscMax(nz_max, nz);
    2968:     nnz[i] = nz;
    2969:   }
    2970:   MatSeqBAIJSetPreallocation(B,bs,0,nnz);
    2971:   PetscFree(nnz);

    2973:   values = (PetscScalar*)V;
    2974:   if (!values) {
    2975:     PetscCalloc1(bs*bs*(nz_max+1),&values);
    2976:   }
    2977:   for (i=0; i<m; i++) {
    2978:     PetscInt          ncols  = ii[i+1] - ii[i];
    2979:     const PetscInt    *icols = jj + ii[i];
    2980:     const PetscScalar *svals = values + (V ? (bs*bs*ii[i]) : 0);
    2981:     if (!roworiented) {
    2982:       MatSetValuesBlocked_SeqBAIJ(B,1,&i,ncols,icols,svals,INSERT_VALUES);
    2983:     } else {
    2984:       PetscInt j;
    2985:       for (j=0; j<ncols; j++) {
    2986:         const PetscScalar *svals = values + (V ? (bs*bs*(ii[i]+j)) : 0);
    2987:         MatSetValuesBlocked_SeqBAIJ(B,1,&i,1,&icols[j],svals,INSERT_VALUES);
    2988:       }
    2989:     }
    2990:   }
    2991:   if (!V) { PetscFree(values); }
    2992:   MatAssemblyBegin(B,MAT_FINAL_ASSEMBLY);
    2993:   MatAssemblyEnd(B,MAT_FINAL_ASSEMBLY);
    2994:   MatSetOption(B,MAT_NEW_NONZERO_LOCATION_ERR,PETSC_TRUE);
    2995:   return(0);
    2996: }

    2998: /*MC
    2999:    MATSEQBAIJ - MATSEQBAIJ = "seqbaij" - A matrix type to be used for sequential block sparse matrices, based on
    3000:    block sparse compressed row format.

    3002:    Options Database Keys:
    3003: . -mat_type seqbaij - sets the matrix type to "seqbaij" during a call to MatSetFromOptions()

    3005:   Level: beginner

    3007: .seealso: MatCreateSeqBAIJ()
    3008: M*/

    3010: PETSC_INTERN PetscErrorCode MatConvert_SeqBAIJ_SeqBSTRM(Mat, MatType,MatReuse,Mat*);

    3012: PETSC_EXTERN PetscErrorCode MatCreate_SeqBAIJ(Mat B)
    3013: {
    3015:   PetscMPIInt    size;
    3016:   Mat_SeqBAIJ    *b;

    3019:   MPI_Comm_size(PetscObjectComm((PetscObject)B),&size);
    3020:   if (size > 1) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONG,"Comm must be of size 1");

    3022:   PetscNewLog(B,&b);
    3023:   B->data = (void*)b;
    3024:   PetscMemcpy(B->ops,&MatOps_Values,sizeof(struct _MatOps));

    3026:   b->row          = 0;
    3027:   b->col          = 0;
    3028:   b->icol         = 0;
    3029:   b->reallocs     = 0;
    3030:   b->saved_values = 0;

    3032:   b->roworiented        = PETSC_TRUE;
    3033:   b->nonew              = 0;
    3034:   b->diag               = 0;
    3035:   B->spptr              = 0;
    3036:   B->info.nz_unneeded   = (PetscReal)b->maxnz*b->bs2;
    3037:   b->keepnonzeropattern = PETSC_FALSE;

    3039:   PetscObjectComposeFunction((PetscObject)B,"MatInvertBlockDiagonal_C",MatInvertBlockDiagonal_SeqBAIJ);
    3040:   PetscObjectComposeFunction((PetscObject)B,"MatStoreValues_C",MatStoreValues_SeqBAIJ);
    3041:   PetscObjectComposeFunction((PetscObject)B,"MatRetrieveValues_C",MatRetrieveValues_SeqBAIJ);
    3042:   PetscObjectComposeFunction((PetscObject)B,"MatSeqBAIJSetColumnIndices_C",MatSeqBAIJSetColumnIndices_SeqBAIJ);
    3043:   PetscObjectComposeFunction((PetscObject)B,"MatConvert_seqbaij_seqaij_C",MatConvert_SeqBAIJ_SeqAIJ);
    3044:   PetscObjectComposeFunction((PetscObject)B,"MatConvert_seqbaij_seqsbaij_C",MatConvert_SeqBAIJ_SeqSBAIJ);
    3045:   PetscObjectComposeFunction((PetscObject)B,"MatSeqBAIJSetPreallocation_C",MatSeqBAIJSetPreallocation_SeqBAIJ);
    3046:   PetscObjectComposeFunction((PetscObject)B,"MatSeqBAIJSetPreallocationCSR_C",MatSeqBAIJSetPreallocationCSR_SeqBAIJ);
    3047:   PetscObjectComposeFunction((PetscObject)B,"MatIsTranspose_C",MatIsTranspose_SeqBAIJ);
    3048: #if defined(PETSC_HAVE_HYPRE)
    3049:   PetscObjectComposeFunction((PetscObject)B,"MatConvert_seqbaij_hypre_C",MatConvert_AIJ_HYPRE);
    3050: #endif
    3051:   PetscObjectComposeFunction((PetscObject)B,"MatConvert_seqbaij_is_C",MatConvert_XAIJ_IS);
    3052:   PetscObjectComposeFunction((PetscObject)B,"MatPtAP_is_seqbaij_C",MatPtAP_IS_XAIJ);
    3053:   PetscObjectChangeTypeName((PetscObject)B,MATSEQBAIJ);
    3054:   return(0);
    3055: }

    3057: PetscErrorCode MatDuplicateNoCreate_SeqBAIJ(Mat C,Mat A,MatDuplicateOption cpvalues,PetscBool mallocmatspace)
    3058: {
    3059:   Mat_SeqBAIJ    *c = (Mat_SeqBAIJ*)C->data,*a = (Mat_SeqBAIJ*)A->data;
    3061:   PetscInt       i,mbs = a->mbs,nz = a->nz,bs2 = a->bs2;

    3064:   if (a->i[mbs] != nz) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_PLIB,"Corrupt matrix");

    3066:   if (cpvalues == MAT_SHARE_NONZERO_PATTERN) {
    3067:     c->imax           = a->imax;
    3068:     c->ilen           = a->ilen;
    3069:     c->free_imax_ilen = PETSC_FALSE;
    3070:   } else {
    3071:     PetscMalloc2(mbs,&c->imax,mbs,&c->ilen);
    3072:     PetscLogObjectMemory((PetscObject)C,2*mbs*sizeof(PetscInt));
    3073:     for (i=0; i<mbs; i++) {
    3074:       c->imax[i] = a->imax[i];
    3075:       c->ilen[i] = a->ilen[i];
    3076:     }
    3077:     c->free_imax_ilen = PETSC_TRUE;
    3078:   }

    3080:   /* allocate the matrix space */
    3081:   if (mallocmatspace) {
    3082:     if (cpvalues == MAT_SHARE_NONZERO_PATTERN) {
    3083:       PetscCalloc1(bs2*nz,&c->a);
    3084:       PetscLogObjectMemory((PetscObject)C,a->i[mbs]*bs2*sizeof(PetscScalar));

    3086:       c->i            = a->i;
    3087:       c->j            = a->j;
    3088:       c->singlemalloc = PETSC_FALSE;
    3089:       c->free_a       = PETSC_TRUE;
    3090:       c->free_ij      = PETSC_FALSE;
    3091:       c->parent       = A;
    3092:       C->preallocated = PETSC_TRUE;
    3093:       C->assembled    = PETSC_TRUE;

    3095:       PetscObjectReference((PetscObject)A);
    3096:       MatSetOption(A,MAT_NEW_NONZERO_LOCATION_ERR,PETSC_TRUE);
    3097:       MatSetOption(C,MAT_NEW_NONZERO_LOCATION_ERR,PETSC_TRUE);
    3098:     } else {
    3099:       PetscMalloc3(bs2*nz,&c->a,nz,&c->j,mbs+1,&c->i);
    3100:       PetscLogObjectMemory((PetscObject)C,a->i[mbs]*(bs2*sizeof(PetscScalar)+sizeof(PetscInt))+(mbs+1)*sizeof(PetscInt));

    3102:       c->singlemalloc = PETSC_TRUE;
    3103:       c->free_a       = PETSC_TRUE;
    3104:       c->free_ij      = PETSC_TRUE;

    3106:       PetscMemcpy(c->i,a->i,(mbs+1)*sizeof(PetscInt));
    3107:       if (mbs > 0) {
    3108:         PetscMemcpy(c->j,a->j,nz*sizeof(PetscInt));
    3109:         if (cpvalues == MAT_COPY_VALUES) {
    3110:           PetscMemcpy(c->a,a->a,bs2*nz*sizeof(MatScalar));
    3111:         } else {
    3112:           PetscMemzero(c->a,bs2*nz*sizeof(MatScalar));
    3113:         }
    3114:       }
    3115:       C->preallocated = PETSC_TRUE;
    3116:       C->assembled    = PETSC_TRUE;
    3117:     }
    3118:   }

    3120:   c->roworiented = a->roworiented;
    3121:   c->nonew       = a->nonew;

    3123:   PetscLayoutReference(A->rmap,&C->rmap);
    3124:   PetscLayoutReference(A->cmap,&C->cmap);

    3126:   c->bs2         = a->bs2;
    3127:   c->mbs         = a->mbs;
    3128:   c->nbs         = a->nbs;

    3130:   if (a->diag) {
    3131:     if (cpvalues == MAT_SHARE_NONZERO_PATTERN) {
    3132:       c->diag      = a->diag;
    3133:       c->free_diag = PETSC_FALSE;
    3134:     } else {
    3135:       PetscMalloc1(mbs+1,&c->diag);
    3136:       PetscLogObjectMemory((PetscObject)C,(mbs+1)*sizeof(PetscInt));
    3137:       for (i=0; i<mbs; i++) c->diag[i] = a->diag[i];
    3138:       c->free_diag = PETSC_TRUE;
    3139:     }
    3140:   } else c->diag = 0;

    3142:   c->nz         = a->nz;
    3143:   c->maxnz      = a->nz;         /* Since we allocate exactly the right amount */
    3144:   c->solve_work = NULL;
    3145:   c->mult_work  = NULL;
    3146:   c->sor_workt  = NULL;
    3147:   c->sor_work   = NULL;

    3149:   c->compressedrow.use   = a->compressedrow.use;
    3150:   c->compressedrow.nrows = a->compressedrow.nrows;
    3151:   if (a->compressedrow.use) {
    3152:     i    = a->compressedrow.nrows;
    3153:     PetscMalloc2(i+1,&c->compressedrow.i,i+1,&c->compressedrow.rindex);
    3154:     PetscLogObjectMemory((PetscObject)C,(2*i+1)*sizeof(PetscInt));
    3155:     PetscMemcpy(c->compressedrow.i,a->compressedrow.i,(i+1)*sizeof(PetscInt));
    3156:     PetscMemcpy(c->compressedrow.rindex,a->compressedrow.rindex,i*sizeof(PetscInt));
    3157:   } else {
    3158:     c->compressedrow.use    = PETSC_FALSE;
    3159:     c->compressedrow.i      = NULL;
    3160:     c->compressedrow.rindex = NULL;
    3161:   }
    3162:   C->nonzerostate = A->nonzerostate;

    3164:   PetscFunctionListDuplicate(((PetscObject)A)->qlist,&((PetscObject)C)->qlist);
    3165:   return(0);
    3166: }

    3168: PetscErrorCode MatDuplicate_SeqBAIJ(Mat A,MatDuplicateOption cpvalues,Mat *B)
    3169: {

    3173:   MatCreate(PetscObjectComm((PetscObject)A),B);
    3174:   MatSetSizes(*B,A->rmap->N,A->cmap->n,A->rmap->N,A->cmap->n);
    3175:   MatSetType(*B,MATSEQBAIJ);
    3176:   MatDuplicateNoCreate_SeqBAIJ(*B,A,cpvalues,PETSC_TRUE);
    3177:   return(0);
    3178: }

    3180: PetscErrorCode MatLoad_SeqBAIJ(Mat newmat,PetscViewer viewer)
    3181: {
    3182:   Mat_SeqBAIJ    *a;
    3184:   PetscInt       i,nz,header[4],*rowlengths=0,M,N,bs = newmat->rmap->bs;
    3185:   PetscInt       *mask,mbs,*jj,j,rowcount,nzcount,k,*browlengths,maskcount;
    3186:   PetscInt       kmax,jcount,block,idx,point,nzcountb,extra_rows,rows,cols;
    3187:   PetscInt       *masked,nmask,tmp,bs2,ishift;
    3188:   PetscMPIInt    size;
    3189:   int            fd;
    3190:   PetscScalar    *aa;
    3191:   MPI_Comm       comm;

    3194:   /* force binary viewer to load .info file if it has not yet done so */
    3195:   PetscViewerSetUp(viewer);
    3196:   PetscObjectGetComm((PetscObject)viewer,&comm);
    3197:   PetscOptionsBegin(comm,NULL,"Options for loading SEQBAIJ matrix","Mat");
    3198:   PetscOptionsInt("-matload_block_size","Set the blocksize used to store the matrix","MatLoad",bs,&bs,NULL);
    3199:   PetscOptionsEnd();
    3200:   if (bs < 0) bs = 1;
    3201:   bs2  = bs*bs;

    3203:   MPI_Comm_size(comm,&size);
    3204:   if (size > 1) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONG,"view must have one processor");
    3205:   PetscViewerBinaryGetDescriptor(viewer,&fd);
    3206:   PetscBinaryRead(fd,header,4,PETSC_INT);
    3207:   if (header[0] != MAT_FILE_CLASSID) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_FILE_UNEXPECTED,"not Mat object");
    3208:   M = header[1]; N = header[2]; nz = header[3];

    3210:   if (header[3] < 0) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_FILE_UNEXPECTED,"Matrix stored in special format, cannot load as SeqBAIJ");
    3211:   if (M != N) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"Can only do square matrices");

    3213:   /*
    3214:      This code adds extra rows to make sure the number of rows is
    3215:     divisible by the blocksize
    3216:   */
    3217:   mbs        = M/bs;
    3218:   extra_rows = bs - M + bs*(mbs);
    3219:   if (extra_rows == bs) extra_rows = 0;
    3220:   else mbs++;
    3221:   if (extra_rows) {
    3222:     PetscInfo(viewer,"Padding loaded matrix to match blocksize\n");
    3223:   }

    3225:   /* Set global sizes if not already set */
    3226:   if (newmat->rmap->n < 0 && newmat->rmap->N < 0 && newmat->cmap->n < 0 && newmat->cmap->N < 0) {
    3227:     MatSetSizes(newmat,PETSC_DECIDE,PETSC_DECIDE,M+extra_rows,N+extra_rows);
    3228:   } else { /* Check if the matrix global sizes are correct */
    3229:     MatGetSize(newmat,&rows,&cols);
    3230:     if (rows < 0 && cols < 0) { /* user might provide local size instead of global size */
    3231:       MatGetLocalSize(newmat,&rows,&cols);
    3232:     }
    3233:     if (M != rows ||  N != cols) SETERRQ4(PETSC_COMM_SELF,PETSC_ERR_FILE_UNEXPECTED,"Matrix in file of different length (%d, %d) than the input matrix (%d, %d)",M,N,rows,cols);
    3234:   }

    3236:   /* read in row lengths */
    3237:   PetscMalloc1(M+extra_rows,&rowlengths);
    3238:   PetscBinaryRead(fd,rowlengths,M,PETSC_INT);
    3239:   for (i=0; i<extra_rows; i++) rowlengths[M+i] = 1;

    3241:   /* read in column indices */
    3242:   PetscMalloc1(nz+extra_rows,&jj);
    3243:   PetscBinaryRead(fd,jj,nz,PETSC_INT);
    3244:   for (i=0; i<extra_rows; i++) jj[nz+i] = M+i;

    3246:   /* loop over row lengths determining block row lengths */
    3247:   PetscCalloc1(mbs,&browlengths);
    3248:   PetscMalloc2(mbs,&mask,mbs,&masked);
    3249:   PetscMemzero(mask,mbs*sizeof(PetscInt));
    3250:   rowcount = 0;
    3251:   nzcount  = 0;
    3252:   for (i=0; i<mbs; i++) {
    3253:     nmask = 0;
    3254:     for (j=0; j<bs; j++) {
    3255:       kmax = rowlengths[rowcount];
    3256:       for (k=0; k<kmax; k++) {
    3257:         tmp = jj[nzcount++]/bs;
    3258:         if (!mask[tmp]) {masked[nmask++] = tmp; mask[tmp] = 1;}
    3259:       }
    3260:       rowcount++;
    3261:     }
    3262:     browlengths[i] += nmask;
    3263:     /* zero out the mask elements we set */
    3264:     for (j=0; j<nmask; j++) mask[masked[j]] = 0;
    3265:   }

    3267:   /* Do preallocation  */
    3268:   MatSeqBAIJSetPreallocation(newmat,bs,0,browlengths);
    3269:   a    = (Mat_SeqBAIJ*)newmat->data;

    3271:   /* set matrix "i" values */
    3272:   a->i[0] = 0;
    3273:   for (i=1; i<= mbs; i++) {
    3274:     a->i[i]      = a->i[i-1] + browlengths[i-1];
    3275:     a->ilen[i-1] = browlengths[i-1];
    3276:   }
    3277:   a->nz = 0;
    3278:   for (i=0; i<mbs; i++) a->nz += browlengths[i];

    3280:   /* read in nonzero values */
    3281:   PetscMalloc1(nz+extra_rows,&aa);
    3282:   PetscBinaryRead(fd,aa,nz,PETSC_SCALAR);
    3283:   for (i=0; i<extra_rows; i++) aa[nz+i] = 1.0;

    3285:   /* set "a" and "j" values into matrix */
    3286:   nzcount = 0; jcount = 0;
    3287:   for (i=0; i<mbs; i++) {
    3288:     nzcountb = nzcount;
    3289:     nmask    = 0;
    3290:     for (j=0; j<bs; j++) {
    3291:       kmax = rowlengths[i*bs+j];
    3292:       for (k=0; k<kmax; k++) {
    3293:         tmp = jj[nzcount++]/bs;
    3294:         if (!mask[tmp]) { masked[nmask++] = tmp; mask[tmp] = 1;}
    3295:       }
    3296:     }
    3297:     /* sort the masked values */
    3298:     PetscSortInt(nmask,masked);

    3300:     /* set "j" values into matrix */
    3301:     maskcount = 1;
    3302:     for (j=0; j<nmask; j++) {
    3303:       a->j[jcount++]  = masked[j];
    3304:       mask[masked[j]] = maskcount++;
    3305:     }
    3306:     /* set "a" values into matrix */
    3307:     ishift = bs2*a->i[i];
    3308:     for (j=0; j<bs; j++) {
    3309:       kmax = rowlengths[i*bs+j];
    3310:       for (k=0; k<kmax; k++) {
    3311:         tmp       = jj[nzcountb]/bs;
    3312:         block     = mask[tmp] - 1;
    3313:         point     = jj[nzcountb] - bs*tmp;
    3314:         idx       = ishift + bs2*block + j + bs*point;
    3315:         a->a[idx] = (MatScalar)aa[nzcountb++];
    3316:       }
    3317:     }
    3318:     /* zero out the mask elements we set */
    3319:     for (j=0; j<nmask; j++) mask[masked[j]] = 0;
    3320:   }
    3321:   if (jcount != a->nz) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_FILE_UNEXPECTED,"Bad binary matrix");

    3323:   PetscFree(rowlengths);
    3324:   PetscFree(browlengths);
    3325:   PetscFree(aa);
    3326:   PetscFree(jj);
    3327:   PetscFree2(mask,masked);

    3329:   MatAssemblyBegin(newmat,MAT_FINAL_ASSEMBLY);
    3330:   MatAssemblyEnd(newmat,MAT_FINAL_ASSEMBLY);
    3331:   return(0);
    3332: }

    3334: /*@C
    3335:    MatCreateSeqBAIJ - Creates a sparse matrix in block AIJ (block
    3336:    compressed row) format.  For good matrix assembly performance the
    3337:    user should preallocate the matrix storage by setting the parameter nz
    3338:    (or the array nnz).  By setting these parameters accurately, performance
    3339:    during matrix assembly can be increased by more than a factor of 50.

    3341:    Collective on MPI_Comm

    3343:    Input Parameters:
    3344: +  comm - MPI communicator, set to PETSC_COMM_SELF
    3345: .  bs - size of block, the blocks are ALWAYS square. One can use MatSetBlockSizes() to set a different row and column blocksize but the row
    3346:           blocksize always defines the size of the blocks. The column blocksize sets the blocksize of the vectors obtained with MatCreateVecs()
    3347: .  m - number of rows
    3348: .  n - number of columns
    3349: .  nz - number of nonzero blocks  per block row (same for all rows)
    3350: -  nnz - array containing the number of nonzero blocks in the various block rows
    3351:          (possibly different for each block row) or NULL

    3353:    Output Parameter:
    3354: .  A - the matrix

    3356:    It is recommended that one use the MatCreate(), MatSetType() and/or MatSetFromOptions(),
    3357:    MatXXXXSetPreallocation() paradgm instead of this routine directly.
    3358:    [MatXXXXSetPreallocation() is, for example, MatSeqAIJSetPreallocation]

    3360:    Options Database Keys:
    3361: .   -mat_no_unroll - uses code that does not unroll the loops in the
    3362:                      block calculations (much slower)
    3363: .    -mat_block_size - size of the blocks to use

    3365:    Level: intermediate

    3367:    Notes:
    3368:    The number of rows and columns must be divisible by blocksize.

    3370:    If the nnz parameter is given then the nz parameter is ignored

    3372:    A nonzero block is any block that as 1 or more nonzeros in it

    3374:    The block AIJ format is fully compatible with standard Fortran 77
    3375:    storage.  That is, the stored row and column indices can begin at
    3376:    either one (as in Fortran) or zero.  See the users' manual for details.

    3378:    Specify the preallocated storage with either nz or nnz (not both).
    3379:    Set nz=PETSC_DEFAULT and nnz=NULL for PETSc to control dynamic memory
    3380:    allocation.  See Users-Manual: ch_mat for details.
    3381:    matrices.

    3383: .seealso: MatCreate(), MatCreateSeqAIJ(), MatSetValues(), MatCreateBAIJ()
    3384: @*/
    3385: PetscErrorCode  MatCreateSeqBAIJ(MPI_Comm comm,PetscInt bs,PetscInt m,PetscInt n,PetscInt nz,const PetscInt nnz[],Mat *A)
    3386: {

    3390:   MatCreate(comm,A);
    3391:   MatSetSizes(*A,m,n,m,n);
    3392:   MatSetType(*A,MATSEQBAIJ);
    3393:   MatSeqBAIJSetPreallocation(*A,bs,nz,(PetscInt*)nnz);
    3394:   return(0);
    3395: }

    3397: /*@C
    3398:    MatSeqBAIJSetPreallocation - Sets the block size and expected nonzeros
    3399:    per row in the matrix. For good matrix assembly performance the
    3400:    user should preallocate the matrix storage by setting the parameter nz
    3401:    (or the array nnz).  By setting these parameters accurately, performance
    3402:    during matrix assembly can be increased by more than a factor of 50.

    3404:    Collective on MPI_Comm

    3406:    Input Parameters:
    3407: +  B - the matrix
    3408: .  bs - size of block, the blocks are ALWAYS square. One can use MatSetBlockSizes() to set a different row and column blocksize but the row
    3409:           blocksize always defines the size of the blocks. The column blocksize sets the blocksize of the vectors obtained with MatCreateVecs()
    3410: .  nz - number of block nonzeros per block row (same for all rows)
    3411: -  nnz - array containing the number of block nonzeros in the various block rows
    3412:          (possibly different for each block row) or NULL

    3414:    Options Database Keys:
    3415: .   -mat_no_unroll - uses code that does not unroll the loops in the
    3416:                      block calculations (much slower)
    3417: .   -mat_block_size - size of the blocks to use

    3419:    Level: intermediate

    3421:    Notes:
    3422:    If the nnz parameter is given then the nz parameter is ignored

    3424:    You can call MatGetInfo() to get information on how effective the preallocation was;
    3425:    for example the fields mallocs,nz_allocated,nz_used,nz_unneeded;
    3426:    You can also run with the option -info and look for messages with the string
    3427:    malloc in them to see if additional memory allocation was needed.

    3429:    The block AIJ format is fully compatible with standard Fortran 77
    3430:    storage.  That is, the stored row and column indices can begin at
    3431:    either one (as in Fortran) or zero.  See the users' manual for details.

    3433:    Specify the preallocated storage with either nz or nnz (not both).
    3434:    Set nz=PETSC_DEFAULT and nnz=NULL for PETSc to control dynamic memory
    3435:    allocation.  See Users-Manual: ch_mat for details.

    3437: .seealso: MatCreate(), MatCreateSeqAIJ(), MatSetValues(), MatCreateBAIJ(), MatGetInfo()
    3438: @*/
    3439: PetscErrorCode  MatSeqBAIJSetPreallocation(Mat B,PetscInt bs,PetscInt nz,const PetscInt nnz[])
    3440: {

    3447:   PetscTryMethod(B,"MatSeqBAIJSetPreallocation_C",(Mat,PetscInt,PetscInt,const PetscInt[]),(B,bs,nz,nnz));
    3448:   return(0);
    3449: }

    3451: /*@C
    3452:    MatSeqBAIJSetPreallocationCSR - Allocates memory for a sparse sequential matrix in AIJ format
    3453:    (the default sequential PETSc format).

    3455:    Collective on MPI_Comm

    3457:    Input Parameters:
    3458: +  B - the matrix
    3459: .  i - the indices into j for the start of each local row (starts with zero)
    3460: .  j - the column indices for each local row (starts with zero) these must be sorted for each row
    3461: -  v - optional values in the matrix

    3463:    Level: developer

    3465:    Notes:
    3466:    The order of the entries in values is specified by the MatOption MAT_ROW_ORIENTED.  For example, C programs
    3467:    may want to use the default MAT_ROW_ORIENTED=PETSC_TRUE and use an array v[nnz][bs][bs] where the second index is
    3468:    over rows within a block and the last index is over columns within a block row.  Fortran programs will likely set
    3469:    MAT_ROW_ORIENTED=PETSC_FALSE and use a Fortran array v(bs,bs,nnz) in which the first index is over rows within a
    3470:    block column and the second index is over columns within a block.

    3472: .keywords: matrix, aij, compressed row, sparse

    3474: .seealso: MatCreate(), MatCreateSeqBAIJ(), MatSetValues(), MatSeqBAIJSetPreallocation(), MATSEQBAIJ
    3475: @*/
    3476: PetscErrorCode  MatSeqBAIJSetPreallocationCSR(Mat B,PetscInt bs,const PetscInt i[],const PetscInt j[], const PetscScalar v[])
    3477: {

    3484:   PetscTryMethod(B,"MatSeqBAIJSetPreallocationCSR_C",(Mat,PetscInt,const PetscInt[],const PetscInt[],const PetscScalar[]),(B,bs,i,j,v));
    3485:   return(0);
    3486: }

    3489: /*@
    3490:      MatCreateSeqBAIJWithArrays - Creates an sequential BAIJ matrix using matrix elements provided by the user.

    3492:      Collective on MPI_Comm

    3494:    Input Parameters:
    3495: +  comm - must be an MPI communicator of size 1
    3496: .  bs - size of block
    3497: .  m - number of rows
    3498: .  n - number of columns
    3499: .  i - row indices
    3500: .  j - column indices
    3501: -  a - matrix values

    3503:    Output Parameter:
    3504: .  mat - the matrix

    3506:    Level: advanced

    3508:    Notes:
    3509:        The i, j, and a arrays are not copied by this routine, the user must free these arrays
    3510:     once the matrix is destroyed

    3512:        You cannot set new nonzero locations into this matrix, that will generate an error.

    3514:        The i and j indices are 0 based

    3516:        When block size is greater than 1 the matrix values must be stored using the BAIJ storage format (see the BAIJ code to determine this).

    3518:       The order of the entries in values is the same as the block compressed sparse row storage format; that is, it is
    3519:       the same as a three dimensional array in Fortran values(bs,bs,nnz) that contains the first column of the first
    3520:       block, followed by the second column of the first block etc etc.  That is, the blocks are contiguous in memory
    3521:       with column-major ordering within blocks.

    3523: .seealso: MatCreate(), MatCreateBAIJ(), MatCreateSeqBAIJ()

    3525: @*/
    3526: PetscErrorCode  MatCreateSeqBAIJWithArrays(MPI_Comm comm,PetscInt bs,PetscInt m,PetscInt n,PetscInt i[],PetscInt j[],PetscScalar a[],Mat *mat)
    3527: {
    3529:   PetscInt       ii;
    3530:   Mat_SeqBAIJ    *baij;

    3533:   if (bs != 1) SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_SUP,"block size %D > 1 is not supported yet",bs);
    3534:   if (m > 0 && i[0]) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"i (row indices) must start with 0");

    3536:   MatCreate(comm,mat);
    3537:   MatSetSizes(*mat,m,n,m,n);
    3538:   MatSetType(*mat,MATSEQBAIJ);
    3539:   MatSeqBAIJSetPreallocation(*mat,bs,MAT_SKIP_ALLOCATION,0);
    3540:   baij = (Mat_SeqBAIJ*)(*mat)->data;
    3541:   PetscMalloc2(m,&baij->imax,m,&baij->ilen);
    3542:   PetscLogObjectMemory((PetscObject)*mat,2*m*sizeof(PetscInt));

    3544:   baij->i = i;
    3545:   baij->j = j;
    3546:   baij->a = a;

    3548:   baij->singlemalloc = PETSC_FALSE;
    3549:   baij->nonew        = -1;             /*this indicates that inserting a new value in the matrix that generates a new nonzero is an error*/
    3550:   baij->free_a       = PETSC_FALSE;
    3551:   baij->free_ij      = PETSC_FALSE;

    3553:   for (ii=0; ii<m; ii++) {
    3554:     baij->ilen[ii] = baij->imax[ii] = i[ii+1] - i[ii];
    3555: #if defined(PETSC_USE_DEBUG)
    3556:     if (i[ii+1] - i[ii] < 0) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Negative row length in i (row indices) row = %d length = %d",ii,i[ii+1] - i[ii]);
    3557: #endif
    3558:   }
    3559: #if defined(PETSC_USE_DEBUG)
    3560:   for (ii=0; ii<baij->i[m]; ii++) {
    3561:     if (j[ii] < 0) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Negative column index at location = %d index = %d",ii,j[ii]);
    3562:     if (j[ii] > n - 1) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Column index to large at location = %d index = %d",ii,j[ii]);
    3563:   }
    3564: #endif

    3566:   MatAssemblyBegin(*mat,MAT_FINAL_ASSEMBLY);
    3567:   MatAssemblyEnd(*mat,MAT_FINAL_ASSEMBLY);
    3568:   return(0);
    3569: }

    3571: PetscErrorCode MatCreateMPIMatConcatenateSeqMat_SeqBAIJ(MPI_Comm comm,Mat inmat,PetscInt n,MatReuse scall,Mat *outmat)
    3572: {
    3574:   PetscMPIInt    size;

    3577:   MPI_Comm_size(comm,&size);
    3578:   if (size == 1 && scall == MAT_REUSE_MATRIX) {
    3579:     MatCopy(inmat,*outmat,SAME_NONZERO_PATTERN);
    3580:   } else {
    3581:     MatCreateMPIMatConcatenateSeqMat_MPIBAIJ(comm,inmat,n,scall,outmat);
    3582:   }
    3583:   return(0);
    3584: }