Date: 2016-07-24T16:54:26+00:00

Actual source code: baij.c
petsc-3.7.3 2016-07-24
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      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>  /*I   "petscmat.h"  I*/
      7: #include <petscblaslapack.h>
      8: #include <petsc/private/kernels/blockinvert.h>
      9: #include <petsc/private/kernels/blockmatmult.h>

     13: PetscErrorCode MatInvertBlockDiagonal_SeqBAIJ(Mat A,const PetscScalar **values)
     14: {
     15:   Mat_SeqBAIJ    *a = (Mat_SeqBAIJ*) A->data;
     17:   PetscInt       *diag_offset,i,bs = A->rmap->bs,mbs = a->mbs,ipvt[5],bs2 = bs*bs,*v_pivots;
     18:   MatScalar      *v    = a->a,*odiag,*diag,*mdiag,work[25],*v_work;
     19:   PetscReal      shift = 0.0;
     20:   PetscBool      allowzeropivot,zeropivotdetected=PETSC_FALSE;

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

     25:   if (a->idiagvalid) {
     26:     if (values) *values = a->idiag;
     27:     return(0);
     28:   }
     29:   MatMarkDiagonal_SeqBAIJ(A);
     30:   diag_offset = a->diag;
     31:   if (!a->idiag) {
     32:     PetscMalloc1(2*bs2*mbs,&a->idiag);
     33:     PetscLogObjectMemory((PetscObject)A,2*bs2*mbs*sizeof(PetscScalar));
     34:   }
     35:   diag  = a->idiag;
     36:   mdiag = a->idiag+bs2*mbs;
     37:   if (values) *values = a->idiag;
     38:   /* factor and invert each block */
     39:   switch (bs) {
     40:   case 1:
     41:     for (i=0; i<mbs; i++) {
     42:       odiag    = v + 1*diag_offset[i];
     43:       diag[0]  = odiag[0];
     44:       mdiag[0] = odiag[0];
     45:
     46:       if (PetscAbsScalar(diag[0] + shift) < PETSC_MACHINE_EPSILON) {
     47:         if (allowzeropivot) {
     48:           A->errortype = MAT_FACTOR_NUMERIC_ZEROPIVOT;
     49:           PetscInfo1(A,"Zero pivot, row %D\n",i);
     50:         } else SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_MAT_LU_ZRPVT,"Zero pivot, row %D",i);
     51:       }
     52:
     53:       diag[0]  = (PetscScalar)1.0 / (diag[0] + shift);
     54:       diag    += 1;
     55:       mdiag   += 1;
     56:     }
     57:     break;
     58:   case 2:
     59:     for (i=0; i<mbs; i++) {
     60:       odiag    = v + 4*diag_offset[i];
     61:       diag[0]  = odiag[0]; diag[1] = odiag[1]; diag[2] = odiag[2]; diag[3] = odiag[3];
     62:       mdiag[0] = odiag[0]; mdiag[1] = odiag[1]; mdiag[2] = odiag[2]; mdiag[3] = odiag[3];
     63:       PetscKernel_A_gets_inverse_A_2(diag,shift,allowzeropivot,&zeropivotdetected);
     64:       if (zeropivotdetected) A->errortype = MAT_FACTOR_NUMERIC_ZEROPIVOT;
     65:       diag    += 4;
     66:       mdiag   += 4;
     67:     }
     68:     break;
     69:   case 3:
     70:     for (i=0; i<mbs; i++) {
     71:       odiag    = v + 9*diag_offset[i];
     72:       diag[0]  = odiag[0]; diag[1] = odiag[1]; diag[2] = odiag[2]; diag[3] = odiag[3];
     73:       diag[4]  = odiag[4]; diag[5] = odiag[5]; diag[6] = odiag[6]; diag[7] = odiag[7];
     74:       diag[8]  = odiag[8];
     75:       mdiag[0] = odiag[0]; mdiag[1] = odiag[1]; mdiag[2] = odiag[2]; mdiag[3] = odiag[3];
     76:       mdiag[4] = odiag[4]; mdiag[5] = odiag[5]; mdiag[6] = odiag[6]; mdiag[7] = odiag[7];
     77:       mdiag[8] = odiag[8];
     78:       PetscKernel_A_gets_inverse_A_3(diag,shift,allowzeropivot,&zeropivotdetected);
     79:       if (zeropivotdetected) A->errortype = MAT_FACTOR_NUMERIC_ZEROPIVOT;
     80:       diag    += 9;
     81:       mdiag   += 9;
     82:     }
     83:     break;
     84:   case 4:
     85:     for (i=0; i<mbs; i++) {
     86:       odiag  = v + 16*diag_offset[i];
     87:       PetscMemcpy(diag,odiag,16*sizeof(PetscScalar));
     88:       PetscMemcpy(mdiag,odiag,16*sizeof(PetscScalar));
     89:       PetscKernel_A_gets_inverse_A_4(diag,shift,allowzeropivot,&zeropivotdetected);
     90:       if (zeropivotdetected) A->errortype = MAT_FACTOR_NUMERIC_ZEROPIVOT;
     91:       diag  += 16;
     92:       mdiag += 16;
     93:     }
     94:     break;
     95:   case 5:
     96:     for (i=0; i<mbs; i++) {
     97:       odiag  = v + 25*diag_offset[i];
     98:       PetscMemcpy(diag,odiag,25*sizeof(PetscScalar));
     99:       PetscMemcpy(mdiag,odiag,25*sizeof(PetscScalar));
    100:       PetscKernel_A_gets_inverse_A_5(diag,ipvt,work,shift,allowzeropivot,&zeropivotdetected);
    101:       if (zeropivotdetected) A->errortype = MAT_FACTOR_NUMERIC_ZEROPIVOT;
    102:       diag  += 25;
    103:       mdiag += 25;
    104:     }
    105:     break;
    106:   case 6:
    107:     for (i=0; i<mbs; i++) {
    108:       odiag  = v + 36*diag_offset[i];
    109:       PetscMemcpy(diag,odiag,36*sizeof(PetscScalar));
    110:       PetscMemcpy(mdiag,odiag,36*sizeof(PetscScalar));
    111:       PetscKernel_A_gets_inverse_A_6(diag,shift,allowzeropivot,&zeropivotdetected);
    112:       if (zeropivotdetected) A->errortype = MAT_FACTOR_NUMERIC_ZEROPIVOT;
    113:       diag  += 36;
    114:       mdiag += 36;
    115:     }
    116:     break;
    117:   case 7:
    118:     for (i=0; i<mbs; i++) {
    119:       odiag  = v + 49*diag_offset[i];
    120:       PetscMemcpy(diag,odiag,49*sizeof(PetscScalar));
    121:       PetscMemcpy(mdiag,odiag,49*sizeof(PetscScalar));
    122:       PetscKernel_A_gets_inverse_A_7(diag,shift,allowzeropivot,&zeropivotdetected);
    123:       if (zeropivotdetected) A->errortype = MAT_FACTOR_NUMERIC_ZEROPIVOT;
    124:       diag  += 49;
    125:       mdiag += 49;
    126:     }
    127:     break;
    128:   default:
    129:     PetscMalloc2(bs,&v_work,bs,&v_pivots);
    130:     for (i=0; i<mbs; i++) {
    131:       odiag  = v + bs2*diag_offset[i];
    132:       PetscMemcpy(diag,odiag,bs2*sizeof(PetscScalar));
    133:       PetscMemcpy(mdiag,odiag,bs2*sizeof(PetscScalar));
    134:       PetscKernel_A_gets_inverse_A(bs,diag,v_pivots,v_work,allowzeropivot,&zeropivotdetected);
    135:       if (zeropivotdetected) A->errortype = MAT_FACTOR_NUMERIC_ZEROPIVOT;
    136:       diag  += bs2;
    137:       mdiag += bs2;
    138:     }
    139:     PetscFree2(v_work,v_pivots);
    140:   }
    141:   a->idiagvalid = PETSC_TRUE;
    142:   return(0);
    143: }

    147: PetscErrorCode MatSOR_SeqBAIJ(Mat A,Vec bb,PetscReal omega,MatSORType flag,PetscReal fshift,PetscInt its,PetscInt lits,Vec xx)
    148: {
    149:   Mat_SeqBAIJ       *a = (Mat_SeqBAIJ*)A->data;
    150:   PetscScalar       *x,*work,*w,*workt,*t;
    151:   const MatScalar   *v,*aa = a->a, *idiag;
    152:   const PetscScalar *b,*xb;
    153:   PetscScalar       s[7], xw[7]={0}; /* avoid some compilers thinking xw is uninitialized */
    154:   PetscErrorCode    ierr;
    155:   PetscInt          m = a->mbs,i,i2,nz,bs = A->rmap->bs,bs2 = bs*bs,k,j,idx,it;
    156:   const PetscInt    *diag,*ai = a->i,*aj = a->j,*vi;

    159:   if (fshift == -1.0) fshift = 0.0; /* negative fshift indicates do not error on zero diagonal; this code never errors on zero diagonal */
    160:   its = its*lits;
    161:   if (flag & SOR_EISENSTAT) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"No support yet for Eisenstat");
    162:   if (its <= 0) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONG,"Relaxation requires global its %D and local its %D both positive",its,lits);
    163:   if (fshift) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"Sorry, no support for diagonal shift");
    164:   if (omega != 1.0) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"Sorry, no support for non-trivial relaxation factor");
    165:   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");

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

    169:   if (!m) return(0);
    170:   diag  = a->diag;
    171:   idiag = a->idiag;
    172:   k    = PetscMax(A->rmap->n,A->cmap->n);
    173:   if (!a->mult_work) {
    174:     PetscMalloc1(k+1,&a->mult_work);
    175:   }
    176:   if (!a->sor_workt) {
    177:     PetscMalloc1(k,&a->sor_workt);
    178:   }
    179:   if (!a->sor_work) {
    180:     PetscMalloc1(bs,&a->sor_work);
    181:   }
    182:   work = a->mult_work;
    183:   t    = a->sor_workt;
    184:   w    = a->sor_work;

    186:   VecGetArray(xx,&x);
    187:   VecGetArrayRead(bb,&b);

    189:   if (flag & SOR_ZERO_INITIAL_GUESS) {
    190:     if (flag & SOR_FORWARD_SWEEP || flag & SOR_LOCAL_FORWARD_SWEEP) {
    191:       switch (bs) {
    192:       case 1:
    193:         PetscKernel_v_gets_A_times_w_1(x,idiag,b);
    194:         t[0] = b[0];
    195:         i2     = 1;
    196:         idiag += 1;
    197:         for (i=1; i<m; i++) {
    198:           v  = aa + ai[i];
    199:           vi = aj + ai[i];
    200:           nz = diag[i] - ai[i];
    201:           s[0] = b[i2];
    202:           for (j=0; j<nz; j++) {
    203:             xw[0] = x[vi[j]];
    204:             PetscKernel_v_gets_v_minus_A_times_w_1(s,(v+j),xw);
    205:           }
    206:           t[i2] = s[0];
    207:           PetscKernel_v_gets_A_times_w_1(xw,idiag,s);
    208:           x[i2]  = xw[0];
    209:           idiag += 1;
    210:           i2    += 1;
    211:         }
    212:         break;
    213:       case 2:
    214:         PetscKernel_v_gets_A_times_w_2(x,idiag,b);
    215:         t[0] = b[0]; t[1] = b[1];
    216:         i2     = 2;
    217:         idiag += 4;
    218:         for (i=1; i<m; i++) {
    219:           v  = aa + 4*ai[i];
    220:           vi = aj + ai[i];
    221:           nz = diag[i] - ai[i];
    222:           s[0] = b[i2]; s[1] = b[i2+1];
    223:           for (j=0; j<nz; j++) {
    224:             idx = 2*vi[j];
    225:             it  = 4*j;
    226:             xw[0] = x[idx]; xw[1] = x[1+idx];
    227:             PetscKernel_v_gets_v_minus_A_times_w_2(s,(v+it),xw);
    228:           }
    229:           t[i2] = s[0]; t[i2+1] = s[1];
    230:           PetscKernel_v_gets_A_times_w_2(xw,idiag,s);
    231:           x[i2]   = xw[0]; x[i2+1] = xw[1];
    232:           idiag  += 4;
    233:           i2     += 2;
    234:         }
    235:         break;
    236:       case 3:
    237:         PetscKernel_v_gets_A_times_w_3(x,idiag,b);
    238:         t[0] = b[0]; t[1] = b[1]; t[2] = b[2];
    239:         i2     = 3;
    240:         idiag += 9;
    241:         for (i=1; i<m; i++) {
    242:           v  = aa + 9*ai[i];
    243:           vi = aj + ai[i];
    244:           nz = diag[i] - ai[i];
    245:           s[0] = b[i2]; s[1] = b[i2+1]; s[2] = b[i2+2];
    246:           while (nz--) {
    247:             idx = 3*(*vi++);
    248:             xw[0] = x[idx]; xw[1] = x[1+idx]; xw[2] = x[2+idx];
    249:             PetscKernel_v_gets_v_minus_A_times_w_3(s,v,xw);
    250:             v  += 9;
    251:           }
    252:           t[i2] = s[0]; t[i2+1] = s[1]; t[i2+2] = s[2];
    253:           PetscKernel_v_gets_A_times_w_3(xw,idiag,s);
    254:           x[i2] = xw[0]; x[i2+1] = xw[1]; x[i2+2] = xw[2];
    255:           idiag  += 9;
    256:           i2     += 3;
    257:         }
    258:         break;
    259:       case 4:
    260:         PetscKernel_v_gets_A_times_w_4(x,idiag,b);
    261:         t[0] = b[0]; t[1] = b[1]; t[2] = b[2]; t[3] = b[3];
    262:         i2     = 4;
    263:         idiag += 16;
    264:         for (i=1; i<m; i++) {
    265:           v  = aa + 16*ai[i];
    266:           vi = aj + ai[i];
    267:           nz = diag[i] - ai[i];
    268:           s[0] = b[i2]; s[1] = b[i2+1]; s[2] = b[i2+2]; s[3] = b[i2+3];
    269:           while (nz--) {
    270:             idx = 4*(*vi++);
    271:             xw[0]  = x[idx]; xw[1] = x[1+idx]; xw[2] = x[2+idx]; xw[3] = x[3+idx];
    272:             PetscKernel_v_gets_v_minus_A_times_w_4(s,v,xw);
    273:             v  += 16;
    274:           }
    275:           t[i2] = s[0]; t[i2+1] = s[1]; t[i2+2] = s[2]; t[i2 + 3] = s[3];
    276:           PetscKernel_v_gets_A_times_w_4(xw,idiag,s);
    277:           x[i2] = xw[0]; x[i2+1] = xw[1]; x[i2+2] = xw[2]; x[i2+3] = xw[3];
    278:           idiag  += 16;
    279:           i2     += 4;
    280:         }
    281:         break;
    282:       case 5:
    283:         PetscKernel_v_gets_A_times_w_5(x,idiag,b);
    284:         t[0] = b[0]; t[1] = b[1]; t[2] = b[2]; t[3] = b[3]; t[4] = b[4];
    285:         i2     = 5;
    286:         idiag += 25;
    287:         for (i=1; i<m; i++) {
    288:           v  = aa + 25*ai[i];
    289:           vi = aj + ai[i];
    290:           nz = diag[i] - ai[i];
    291:           s[0] = b[i2]; s[1] = b[i2+1]; s[2] = b[i2+2]; s[3] = b[i2+3]; s[4] = b[i2+4];
    292:           while (nz--) {
    293:             idx = 5*(*vi++);
    294:             xw[0]  = x[idx]; xw[1] = x[1+idx]; xw[2] = x[2+idx]; xw[3] = x[3+idx]; xw[4] = x[4+idx];
    295:             PetscKernel_v_gets_v_minus_A_times_w_5(s,v,xw);
    296:             v  += 25;
    297:           }
    298:           t[i2] = s[0]; t[i2+1] = s[1]; t[i2+2] = s[2]; t[i2+3] = s[3]; t[i2+4] = s[4];
    299:           PetscKernel_v_gets_A_times_w_5(xw,idiag,s);
    300:           x[i2] = xw[0]; x[i2+1] = xw[1]; x[i2+2] = xw[2]; x[i2+3] = xw[3]; x[i2+4] = xw[4];
    301:           idiag  += 25;
    302:           i2     += 5;
    303:         }
    304:         break;
    305:       case 6:
    306:         PetscKernel_v_gets_A_times_w_6(x,idiag,b);
    307:         t[0] = b[0]; t[1] = b[1]; t[2] = b[2]; t[3] = b[3]; t[4] = b[4]; t[5] = b[5];
    308:         i2     = 6;
    309:         idiag += 36;
    310:         for (i=1; i<m; i++) {
    311:           v  = aa + 36*ai[i];
    312:           vi = aj + ai[i];
    313:           nz = diag[i] - ai[i];
    314:           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];
    315:           while (nz--) {
    316:             idx = 6*(*vi++);
    317:             xw[0] = x[idx];   xw[1] = x[1+idx]; xw[2] = x[2+idx];
    318:             xw[3] = x[3+idx]; xw[4] = x[4+idx]; xw[5] = x[5+idx];
    319:             PetscKernel_v_gets_v_minus_A_times_w_6(s,v,xw);
    320:             v  += 36;
    321:           }
    322:           t[i2]   = s[0]; t[i2+1] = s[1]; t[i2+2] = s[2];
    323:           t[i2+3] = s[3]; t[i2+4] = s[4]; t[i2+5] = s[5];
    324:           PetscKernel_v_gets_A_times_w_6(xw,idiag,s);
    325:           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];
    326:           idiag  += 36;
    327:           i2     += 6;
    328:         }
    329:         break;
    330:       case 7:
    331:         PetscKernel_v_gets_A_times_w_7(x,idiag,b);
    332:         t[0] = b[0]; t[1] = b[1]; t[2] = b[2];
    333:         t[3] = b[3]; t[4] = b[4]; t[5] = b[5]; t[6] = b[6];
    334:         i2     = 7;
    335:         idiag += 49;
    336:         for (i=1; i<m; i++) {
    337:           v  = aa + 49*ai[i];
    338:           vi = aj + ai[i];
    339:           nz = diag[i] - ai[i];
    340:           s[0] = b[i2];   s[1] = b[i2+1]; s[2] = b[i2+2];
    341:           s[3] = b[i2+3]; s[4] = b[i2+4]; s[5] = b[i2+5]; s[6] = b[i2+6];
    342:           while (nz--) {
    343:             idx = 7*(*vi++);
    344:             xw[0] = x[idx];   xw[1] = x[1+idx]; xw[2] = x[2+idx];
    345:             xw[3] = x[3+idx]; xw[4] = x[4+idx]; xw[5] = x[5+idx]; xw[6] = x[6+idx];
    346:             PetscKernel_v_gets_v_minus_A_times_w_7(s,v,xw);
    347:             v  += 49;
    348:           }
    349:           t[i2]   = s[0]; t[i2+1] = s[1]; t[i2+2] = s[2];
    350:           t[i2+3] = s[3]; t[i2+4] = s[4]; t[i2+5] = s[5]; t[i2+6] = s[6];
    351:           PetscKernel_v_gets_A_times_w_7(xw,idiag,s);
    352:           x[i2] =   xw[0]; x[i2+1] = xw[1]; x[i2+2] = xw[2];
    353:           x[i2+3] = xw[3]; x[i2+4] = xw[4]; x[i2+5] = xw[5]; x[i2+6] = xw[6];
    354:           idiag  += 49;
    355:           i2     += 7;
    356:         }
    357:         break;
    358:       default:
    359:         PetscKernel_w_gets_Ar_times_v(bs,bs,b,idiag,x);
    360:         PetscMemcpy(t,b,bs*sizeof(PetscScalar));
    361:         i2     = bs;
    362:         idiag += bs2;
    363:         for (i=1; i<m; i++) {
    364:           v  = aa + bs2*ai[i];
    365:           vi = aj + ai[i];
    366:           nz = diag[i] - ai[i];

    368:           PetscMemcpy(w,b+i2,bs*sizeof(PetscScalar));
    369:           /* copy all rows of x that are needed into contiguous space */
    370:           workt = work;
    371:           for (j=0; j<nz; j++) {
    372:             PetscMemcpy(workt,x + bs*(*vi++),bs*sizeof(PetscScalar));
    373:             workt += bs;
    374:           }
    375:           PetscKernel_w_gets_w_minus_Ar_times_v(bs,bs*nz,w,v,work);
    376:           PetscMemcpy(t+i2,w,bs*sizeof(PetscScalar));
    377:           PetscKernel_w_gets_Ar_times_v(bs,bs,w,idiag,x+i2);

    379:           idiag += bs2;
    380:           i2    += bs;
    381:         }
    382:         break;
    383:       }
    384:       /* for logging purposes assume number of nonzero in lower half is 1/2 of total */
    385:       PetscLogFlops(1.0*bs2*a->nz);
    386:       xb = t;
    387:     }
    388:     else xb = b;
    389:     if (flag & SOR_BACKWARD_SWEEP || flag & SOR_LOCAL_BACKWARD_SWEEP) {
    390:       idiag = a->idiag+bs2*(a->mbs-1);
    391:       i2 = bs * (m-1);
    392:       switch (bs) {
    393:       case 1:
    394:         s[0]  = xb[i2];
    395:         PetscKernel_v_gets_A_times_w_1(xw,idiag,s);
    396:         x[i2] = xw[0];
    397:         i2   -= 1;
    398:         for (i=m-2; i>=0; i--) {
    399:           v  = aa + (diag[i]+1);
    400:           vi = aj + diag[i] + 1;
    401:           nz = ai[i+1] - diag[i] - 1;
    402:           s[0] = xb[i2];
    403:           for (j=0; j<nz; j++) {
    404:             xw[0] = x[vi[j]];
    405:             PetscKernel_v_gets_v_minus_A_times_w_1(s,(v+j),xw);
    406:           }
    407:           PetscKernel_v_gets_A_times_w_1(xw,idiag,s);
    408:           x[i2]  = xw[0];
    409:           idiag -= 1;
    410:           i2    -= 1;
    411:         }
    412:         break;
    413:       case 2:
    414:         s[0]  = xb[i2]; s[1] = xb[i2+1];
    415:         PetscKernel_v_gets_A_times_w_2(xw,idiag,s);
    416:         x[i2] = xw[0]; x[i2+1] = xw[1];
    417:         i2    -= 2;
    418:         idiag -= 4;
    419:         for (i=m-2; i>=0; i--) {
    420:           v  = aa + 4*(diag[i] + 1);
    421:           vi = aj + diag[i] + 1;
    422:           nz = ai[i+1] - diag[i] - 1;
    423:           s[0] = xb[i2]; s[1] = xb[i2+1];
    424:           for (j=0; j<nz; j++) {
    425:             idx = 2*vi[j];
    426:             it  = 4*j;
    427:             xw[0] = x[idx]; xw[1] = x[1+idx];
    428:             PetscKernel_v_gets_v_minus_A_times_w_2(s,(v+it),xw);
    429:           }
    430:           PetscKernel_v_gets_A_times_w_2(xw,idiag,s);
    431:           x[i2]   = xw[0]; x[i2+1] = xw[1];
    432:           idiag  -= 4;
    433:           i2     -= 2;
    434:         }
    435:         break;
    436:       case 3:
    437:         s[0]  = xb[i2]; s[1] = xb[i2+1]; s[2] = xb[i2+2];
    438:         PetscKernel_v_gets_A_times_w_3(xw,idiag,s);
    439:         x[i2] = xw[0]; x[i2+1] = xw[1]; x[i2+2] = xw[2];
    440:         i2    -= 3;
    441:         idiag -= 9;
    442:         for (i=m-2; i>=0; i--) {
    443:           v  = aa + 9*(diag[i]+1);
    444:           vi = aj + diag[i] + 1;
    445:           nz = ai[i+1] - diag[i] - 1;
    446:           s[0] = xb[i2]; s[1] = xb[i2+1]; s[2] = xb[i2+2];
    447:           while (nz--) {
    448:             idx = 3*(*vi++);
    449:             xw[0] = x[idx]; xw[1] = x[1+idx]; xw[2] = x[2+idx];
    450:             PetscKernel_v_gets_v_minus_A_times_w_3(s,v,xw);
    451:             v  += 9;
    452:           }
    453:           PetscKernel_v_gets_A_times_w_3(xw,idiag,s);
    454:           x[i2] = xw[0]; x[i2+1] = xw[1]; x[i2+2] = xw[2];
    455:           idiag  -= 9;
    456:           i2     -= 3;
    457:         }
    458:         break;
    459:       case 4:
    460:         s[0]  = xb[i2]; s[1] = xb[i2+1]; s[2] = xb[i2+2]; s[3] = xb[i2+3];
    461:         PetscKernel_v_gets_A_times_w_4(xw,idiag,s);
    462:         x[i2] = xw[0]; x[i2+1] = xw[1]; x[i2+2] = xw[2]; x[i2+3] = xw[3];
    463:         i2    -= 4;
    464:         idiag -= 16;
    465:         for (i=m-2; i>=0; i--) {
    466:           v  = aa + 16*(diag[i]+1);
    467:           vi = aj + diag[i] + 1;
    468:           nz = ai[i+1] - diag[i] - 1;
    469:           s[0] = xb[i2]; s[1] = xb[i2+1]; s[2] = xb[i2+2]; s[3] = xb[i2+3];
    470:           while (nz--) {
    471:             idx = 4*(*vi++);
    472:             xw[0]  = x[idx]; xw[1] = x[1+idx]; xw[2] = x[2+idx]; xw[3] = x[3+idx];
    473:             PetscKernel_v_gets_v_minus_A_times_w_4(s,v,xw);
    474:             v  += 16;
    475:           }
    476:           PetscKernel_v_gets_A_times_w_4(xw,idiag,s);
    477:           x[i2] = xw[0]; x[i2+1] = xw[1]; x[i2+2] = xw[2]; x[i2+3] = xw[3];
    478:           idiag  -= 16;
    479:           i2     -= 4;
    480:         }
    481:         break;
    482:       case 5:
    483:         s[0]  = xb[i2]; s[1] = xb[i2+1]; s[2] = xb[i2+2]; s[3] = xb[i2+3]; s[4] = xb[i2+4];
    484:         PetscKernel_v_gets_A_times_w_5(xw,idiag,s);
    485:         x[i2] = xw[0]; x[i2+1] = xw[1]; x[i2+2] = xw[2]; x[i2+3] = xw[3]; x[i2+4] = xw[4];
    486:         i2    -= 5;
    487:         idiag -= 25;
    488:         for (i=m-2; i>=0; i--) {
    489:           v  = aa + 25*(diag[i]+1);
    490:           vi = aj + diag[i] + 1;
    491:           nz = ai[i+1] - diag[i] - 1;
    492:           s[0] = xb[i2]; s[1] = xb[i2+1]; s[2] = xb[i2+2]; s[3] = xb[i2+3]; s[4] = xb[i2+4];
    493:           while (nz--) {
    494:             idx = 5*(*vi++);
    495:             xw[0]  = x[idx]; xw[1] = x[1+idx]; xw[2] = x[2+idx]; xw[3] = x[3+idx]; xw[4] = x[4+idx];
    496:             PetscKernel_v_gets_v_minus_A_times_w_5(s,v,xw);
    497:             v  += 25;
    498:           }
    499:           PetscKernel_v_gets_A_times_w_5(xw,idiag,s);
    500:           x[i2] = xw[0]; x[i2+1] = xw[1]; x[i2+2] = xw[2]; x[i2+3] = xw[3]; x[i2+4] = xw[4];
    501:           idiag  -= 25;
    502:           i2     -= 5;
    503:         }
    504:         break;
    505:       case 6:
    506:         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];
    507:         PetscKernel_v_gets_A_times_w_6(xw,idiag,s);
    508:         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];
    509:         i2    -= 6;
    510:         idiag -= 36;
    511:         for (i=m-2; i>=0; i--) {
    512:           v  = aa + 36*(diag[i]+1);
    513:           vi = aj + diag[i] + 1;
    514:           nz = ai[i+1] - diag[i] - 1;
    515:           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];
    516:           while (nz--) {
    517:             idx = 6*(*vi++);
    518:             xw[0] = x[idx];   xw[1] = x[1+idx]; xw[2] = x[2+idx];
    519:             xw[3] = x[3+idx]; xw[4] = x[4+idx]; xw[5] = x[5+idx];
    520:             PetscKernel_v_gets_v_minus_A_times_w_6(s,v,xw);
    521:             v  += 36;
    522:           }
    523:           PetscKernel_v_gets_A_times_w_6(xw,idiag,s);
    524:           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];
    525:           idiag  -= 36;
    526:           i2     -= 6;
    527:         }
    528:         break;
    529:       case 7:
    530:         s[0] = xb[i2];   s[1] = xb[i2+1]; s[2] = xb[i2+2];
    531:         s[3] = xb[i2+3]; s[4] = xb[i2+4]; s[5] = xb[i2+5]; s[6] = xb[i2+6];
    532:         PetscKernel_v_gets_A_times_w_7(x,idiag,b);
    533:         x[i2]   = xw[0]; x[i2+1] = xw[1]; x[i2+2] = xw[2];
    534:         x[i2+3] = xw[3]; x[i2+4] = xw[4]; x[i2+5] = xw[5]; x[i2+6] = xw[6];
    535:         i2    -= 7;
    536:         idiag -= 49;
    537:         for (i=m-2; i>=0; i--) {
    538:           v  = aa + 49*(diag[i]+1);
    539:           vi = aj + diag[i] + 1;
    540:           nz = ai[i+1] - diag[i] - 1;
    541:           s[0] = xb[i2];   s[1] = xb[i2+1]; s[2] = xb[i2+2];
    542:           s[3] = xb[i2+3]; s[4] = xb[i2+4]; s[5] = xb[i2+5]; s[6] = xb[i2+6];
    543:           while (nz--) {
    544:             idx = 7*(*vi++);
    545:             xw[0] = x[idx];   xw[1] = x[1+idx]; xw[2] = x[2+idx];
    546:             xw[3] = x[3+idx]; xw[4] = x[4+idx]; xw[5] = x[5+idx]; xw[6] = x[6+idx];
    547:             PetscKernel_v_gets_v_minus_A_times_w_7(s,v,xw);
    548:             v  += 49;
    549:           }
    550:           PetscKernel_v_gets_A_times_w_7(xw,idiag,s);
    551:           x[i2] =   xw[0]; x[i2+1] = xw[1]; x[i2+2] = xw[2];
    552:           x[i2+3] = xw[3]; x[i2+4] = xw[4]; x[i2+5] = xw[5]; x[i2+6] = xw[6];
    553:           idiag  -= 49;
    554:           i2     -= 7;
    555:         }
    556:         break;
    557:       default:
    558:         PetscMemcpy(w,xb+i2,bs*sizeof(PetscScalar));
    559:         PetscKernel_w_gets_Ar_times_v(bs,bs,w,idiag,x+i2);
    560:         i2    -= bs;
    561:         idiag -= bs2;
    562:         for (i=m-2; i>=0; i--) {
    563:           v  = aa + bs2*(diag[i]+1);
    564:           vi = aj + diag[i] + 1;
    565:           nz = ai[i+1] - diag[i] - 1;

    567:           PetscMemcpy(w,xb+i2,bs*sizeof(PetscScalar));
    568:           /* copy all rows of x that are needed into contiguous space */
    569:           workt = work;
    570:           for (j=0; j<nz; j++) {
    571:             PetscMemcpy(workt,x + bs*(*vi++),bs*sizeof(PetscScalar));
    572:             workt += bs;
    573:           }
    574:           PetscKernel_w_gets_w_minus_Ar_times_v(bs,bs*nz,w,v,work);
    575:           PetscKernel_w_gets_Ar_times_v(bs,bs,w,idiag,x+i2);

    577:           idiag -= bs2;
    578:           i2    -= bs;
    579:         }
    580:         break;
    581:       }
    582:       PetscLogFlops(1.0*bs2*(a->nz));
    583:     }
    584:     its--;
    585:   }
    586:   while (its--) {
    587:     if (flag & SOR_FORWARD_SWEEP || flag & SOR_LOCAL_FORWARD_SWEEP) {
    588:       idiag = a->idiag;
    589:       i2 = 0;
    590:       switch (bs) {
    591:       case 1:
    592:         for (i=0; i<m; i++) {
    593:           v  = aa + ai[i];
    594:           vi = aj + ai[i];
    595:           nz = ai[i+1] - ai[i];
    596:           s[0] = b[i2];
    597:           for (j=0; j<nz; j++) {
    598:             xw[0] = x[vi[j]];
    599:             PetscKernel_v_gets_v_minus_A_times_w_1(s,(v+j),xw);
    600:           }
    601:           PetscKernel_v_gets_A_times_w_1(xw,idiag,s);
    602:           x[i2] += xw[0];
    603:           idiag += 1;
    604:           i2    += 1;
    605:         }
    606:         break;
    607:       case 2:
    608:         for (i=0; i<m; i++) {
    609:           v  = aa + 4*ai[i];
    610:           vi = aj + ai[i];
    611:           nz = ai[i+1] - ai[i];
    612:           s[0] = b[i2]; s[1] = b[i2+1];
    613:           for (j=0; j<nz; j++) {
    614:             idx = 2*vi[j];
    615:             it  = 4*j;
    616:             xw[0] = x[idx]; xw[1] = x[1+idx];
    617:             PetscKernel_v_gets_v_minus_A_times_w_2(s,(v+it),xw);
    618:           }
    619:           PetscKernel_v_gets_A_times_w_2(xw,idiag,s);
    620:           x[i2]  += xw[0]; x[i2+1] += xw[1];
    621:           idiag  += 4;
    622:           i2     += 2;
    623:         }
    624:         break;
    625:       case 3:
    626:         for (i=0; i<m; i++) {
    627:           v  = aa + 9*ai[i];
    628:           vi = aj + ai[i];
    629:           nz = ai[i+1] - ai[i];
    630:           s[0] = b[i2]; s[1] = b[i2+1]; s[2] = b[i2+2];
    631:           while (nz--) {
    632:             idx = 3*(*vi++);
    633:             xw[0] = x[idx]; xw[1] = x[1+idx]; xw[2] = x[2+idx];
    634:             PetscKernel_v_gets_v_minus_A_times_w_3(s,v,xw);
    635:             v  += 9;
    636:           }
    637:           PetscKernel_v_gets_A_times_w_3(xw,idiag,s);
    638:           x[i2] += xw[0]; x[i2+1] += xw[1]; x[i2+2] += xw[2];
    639:           idiag  += 9;
    640:           i2     += 3;
    641:         }
    642:         break;
    643:       case 4:
    644:         for (i=0; i<m; i++) {
    645:           v  = aa + 16*ai[i];
    646:           vi = aj + ai[i];
    647:           nz = ai[i+1] - ai[i];
    648:           s[0] = b[i2]; s[1] = b[i2+1]; s[2] = b[i2+2]; s[3] = b[i2+3];
    649:           while (nz--) {
    650:             idx = 4*(*vi++);
    651:             xw[0]  = x[idx]; xw[1] = x[1+idx]; xw[2] = x[2+idx]; xw[3] = x[3+idx];
    652:             PetscKernel_v_gets_v_minus_A_times_w_4(s,v,xw);
    653:             v  += 16;
    654:           }
    655:           PetscKernel_v_gets_A_times_w_4(xw,idiag,s);
    656:           x[i2] += xw[0]; x[i2+1] += xw[1]; x[i2+2] += xw[2]; x[i2+3] += xw[3];
    657:           idiag  += 16;
    658:           i2     += 4;
    659:         }
    660:         break;
    661:       case 5:
    662:         for (i=0; i<m; i++) {
    663:           v  = aa + 25*ai[i];
    664:           vi = aj + ai[i];
    665:           nz = ai[i+1] - ai[i];
    666:           s[0] = b[i2]; s[1] = b[i2+1]; s[2] = b[i2+2]; s[3] = b[i2+3]; s[4] = b[i2+4];
    667:           while (nz--) {
    668:             idx = 5*(*vi++);
    669:             xw[0]  = x[idx]; xw[1] = x[1+idx]; xw[2] = x[2+idx]; xw[3] = x[3+idx]; xw[4] = x[4+idx];
    670:             PetscKernel_v_gets_v_minus_A_times_w_5(s,v,xw);
    671:             v  += 25;
    672:           }
    673:           PetscKernel_v_gets_A_times_w_5(xw,idiag,s);
    674:           x[i2] += xw[0]; x[i2+1] += xw[1]; x[i2+2] += xw[2]; x[i2+3] += xw[3]; x[i2+4] += xw[4];
    675:           idiag  += 25;
    676:           i2     += 5;
    677:         }
    678:         break;
    679:       case 6:
    680:         for (i=0; i<m; i++) {
    681:           v  = aa + 36*ai[i];
    682:           vi = aj + ai[i];
    683:           nz = ai[i+1] - ai[i];
    684:           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];
    685:           while (nz--) {
    686:             idx = 6*(*vi++);
    687:             xw[0] = x[idx];   xw[1] = x[1+idx]; xw[2] = x[2+idx];
    688:             xw[3] = x[3+idx]; xw[4] = x[4+idx]; xw[5] = x[5+idx];
    689:             PetscKernel_v_gets_v_minus_A_times_w_6(s,v,xw);
    690:             v  += 36;
    691:           }
    692:           PetscKernel_v_gets_A_times_w_6(xw,idiag,s);
    693:           x[i2] += xw[0]; x[i2+1] += xw[1]; x[i2+2] += xw[2];
    694:           x[i2+3] += xw[3]; x[i2+4] += xw[4]; x[i2+5] += xw[5];
    695:           idiag  += 36;
    696:           i2     += 6;
    697:         }
    698:         break;
    699:       case 7:
    700:         for (i=0; i<m; i++) {
    701:           v  = aa + 49*ai[i];
    702:           vi = aj + ai[i];
    703:           nz = ai[i+1] - ai[i];
    704:           s[0] = b[i2];   s[1] = b[i2+1]; s[2] = b[i2+2];
    705:           s[3] = b[i2+3]; s[4] = b[i2+4]; s[5] = b[i2+5]; s[6] = b[i2+6];
    706:           while (nz--) {
    707:             idx = 7*(*vi++);
    708:             xw[0] = x[idx];   xw[1] = x[1+idx]; xw[2] = x[2+idx];
    709:             xw[3] = x[3+idx]; xw[4] = x[4+idx]; xw[5] = x[5+idx]; xw[6] = x[6+idx];
    710:             PetscKernel_v_gets_v_minus_A_times_w_7(s,v,xw);
    711:             v  += 49;
    712:           }
    713:           PetscKernel_v_gets_A_times_w_7(xw,idiag,s);
    714:           x[i2]   += xw[0]; x[i2+1] += xw[1]; x[i2+2] += xw[2];
    715:           x[i2+3] += xw[3]; x[i2+4] += xw[4]; x[i2+5] += xw[5]; x[i2+6] += xw[6];
    716:           idiag  += 49;
    717:           i2     += 7;
    718:         }
    719:         break;
    720:       default:
    721:         for (i=0; i<m; i++) {
    722:           v  = aa + bs2*ai[i];
    723:           vi = aj + ai[i];
    724:           nz = ai[i+1] - ai[i];

    726:           PetscMemcpy(w,b+i2,bs*sizeof(PetscScalar));
    727:           /* copy all rows of x that are needed into contiguous space */
    728:           workt = work;
    729:           for (j=0; j<nz; j++) {
    730:             PetscMemcpy(workt,x + bs*(*vi++),bs*sizeof(PetscScalar));
    731:             workt += bs;
    732:           }
    733:           PetscKernel_w_gets_w_minus_Ar_times_v(bs,bs*nz,w,v,work);
    734:           PetscKernel_w_gets_w_plus_Ar_times_v(bs,bs,w,idiag,x+i2);

    736:           idiag += bs2;
    737:           i2    += bs;
    738:         }
    739:         break;
    740:       }
    741:       PetscLogFlops(2.0*bs2*a->nz);
    742:     }
    743:     if (flag & SOR_BACKWARD_SWEEP || flag & SOR_LOCAL_BACKWARD_SWEEP) {
    744:       idiag = a->idiag+bs2*(a->mbs-1);
    745:       i2 = bs * (m-1);
    746:       switch (bs) {
    747:       case 1:
    748:         for (i=m-1; i>=0; i--) {
    749:           v  = aa + ai[i];
    750:           vi = aj + ai[i];
    751:           nz = ai[i+1] - ai[i];
    752:           s[0] = b[i2];
    753:           for (j=0; j<nz; j++) {
    754:             xw[0] = x[vi[j]];
    755:             PetscKernel_v_gets_v_minus_A_times_w_1(s,(v+j),xw);
    756:           }
    757:           PetscKernel_v_gets_A_times_w_1(xw,idiag,s);
    758:           x[i2] += xw[0];
    759:           idiag -= 1;
    760:           i2    -= 1;
    761:         }
    762:         break;
    763:       case 2:
    764:         for (i=m-1; i>=0; i--) {
    765:           v  = aa + 4*ai[i];
    766:           vi = aj + ai[i];
    767:           nz = ai[i+1] - ai[i];
    768:           s[0] = b[i2]; s[1] = b[i2+1];
    769:           for (j=0; j<nz; j++) {
    770:             idx = 2*vi[j];
    771:             it  = 4*j;
    772:             xw[0] = x[idx]; xw[1] = x[1+idx];
    773:             PetscKernel_v_gets_v_minus_A_times_w_2(s,(v+it),xw);
    774:           }
    775:           PetscKernel_v_gets_A_times_w_2(xw,idiag,s);
    776:           x[i2]  += xw[0]; x[i2+1] += xw[1];
    777:           idiag  -= 4;
    778:           i2     -= 2;
    779:         }
    780:         break;
    781:       case 3:
    782:         for (i=m-1; i>=0; i--) {
    783:           v  = aa + 9*ai[i];
    784:           vi = aj + ai[i];
    785:           nz = ai[i+1] - ai[i];
    786:           s[0] = b[i2]; s[1] = b[i2+1]; s[2] = b[i2+2];
    787:           while (nz--) {
    788:             idx = 3*(*vi++);
    789:             xw[0] = x[idx]; xw[1] = x[1+idx]; xw[2] = x[2+idx];
    790:             PetscKernel_v_gets_v_minus_A_times_w_3(s,v,xw);
    791:             v  += 9;
    792:           }
    793:           PetscKernel_v_gets_A_times_w_3(xw,idiag,s);
    794:           x[i2] += xw[0]; x[i2+1] += xw[1]; x[i2+2] += xw[2];
    795:           idiag  -= 9;
    796:           i2     -= 3;
    797:         }
    798:         break;
    799:       case 4:
    800:         for (i=m-1; i>=0; i--) {
    801:           v  = aa + 16*ai[i];
    802:           vi = aj + ai[i];
    803:           nz = ai[i+1] - ai[i];
    804:           s[0] = b[i2]; s[1] = b[i2+1]; s[2] = b[i2+2]; s[3] = b[i2+3];
    805:           while (nz--) {
    806:             idx = 4*(*vi++);
    807:             xw[0]  = x[idx]; xw[1] = x[1+idx]; xw[2] = x[2+idx]; xw[3] = x[3+idx];
    808:             PetscKernel_v_gets_v_minus_A_times_w_4(s,v,xw);
    809:             v  += 16;
    810:           }
    811:           PetscKernel_v_gets_A_times_w_4(xw,idiag,s);
    812:           x[i2] += xw[0]; x[i2+1] += xw[1]; x[i2+2] += xw[2]; x[i2+3] += xw[3];
    813:           idiag  -= 16;
    814:           i2     -= 4;
    815:         }
    816:         break;
    817:       case 5:
    818:         for (i=m-1; i>=0; i--) {
    819:           v  = aa + 25*ai[i];
    820:           vi = aj + ai[i];
    821:           nz = ai[i+1] - ai[i];
    822:           s[0] = b[i2]; s[1] = b[i2+1]; s[2] = b[i2+2]; s[3] = b[i2+3]; s[4] = b[i2+4];
    823:           while (nz--) {
    824:             idx = 5*(*vi++);
    825:             xw[0]  = x[idx]; xw[1] = x[1+idx]; xw[2] = x[2+idx]; xw[3] = x[3+idx]; xw[4] = x[4+idx];
    826:             PetscKernel_v_gets_v_minus_A_times_w_5(s,v,xw);
    827:             v  += 25;
    828:           }
    829:           PetscKernel_v_gets_A_times_w_5(xw,idiag,s);
    830:           x[i2] += xw[0]; x[i2+1] += xw[1]; x[i2+2] += xw[2]; x[i2+3] += xw[3]; x[i2+4] += xw[4];
    831:           idiag  -= 25;
    832:           i2     -= 5;
    833:         }
    834:         break;
    835:       case 6:
    836:         for (i=m-1; i>=0; i--) {
    837:           v  = aa + 36*ai[i];
    838:           vi = aj + ai[i];
    839:           nz = ai[i+1] - ai[i];
    840:           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];
    841:           while (nz--) {
    842:             idx = 6*(*vi++);
    843:             xw[0] = x[idx];   xw[1] = x[1+idx]; xw[2] = x[2+idx];
    844:             xw[3] = x[3+idx]; xw[4] = x[4+idx]; xw[5] = x[5+idx];
    845:             PetscKernel_v_gets_v_minus_A_times_w_6(s,v,xw);
    846:             v  += 36;
    847:           }
    848:           PetscKernel_v_gets_A_times_w_6(xw,idiag,s);
    849:           x[i2] += xw[0]; x[i2+1] += xw[1]; x[i2+2] += xw[2];
    850:           x[i2+3] += xw[3]; x[i2+4] += xw[4]; x[i2+5] += xw[5];
    851:           idiag  -= 36;
    852:           i2     -= 6;
    853:         }
    854:         break;
    855:       case 7:
    856:         for (i=m-1; i>=0; i--) {
    857:           v  = aa + 49*ai[i];
    858:           vi = aj + ai[i];
    859:           nz = ai[i+1] - ai[i];
    860:           s[0] = b[i2];   s[1] = b[i2+1]; s[2] = b[i2+2];
    861:           s[3] = b[i2+3]; s[4] = b[i2+4]; s[5] = b[i2+5]; s[6] = b[i2+6];
    862:           while (nz--) {
    863:             idx = 7*(*vi++);
    864:             xw[0] = x[idx];   xw[1] = x[1+idx]; xw[2] = x[2+idx];
    865:             xw[3] = x[3+idx]; xw[4] = x[4+idx]; xw[5] = x[5+idx]; xw[6] = x[6+idx];
    866:             PetscKernel_v_gets_v_minus_A_times_w_7(s,v,xw);
    867:             v  += 49;
    868:           }
    869:           PetscKernel_v_gets_A_times_w_7(xw,idiag,s);
    870:           x[i2] +=   xw[0]; x[i2+1] += xw[1]; x[i2+2] += xw[2];
    871:           x[i2+3] += xw[3]; x[i2+4] += xw[4]; x[i2+5] += xw[5]; x[i2+6] += xw[6];
    872:           idiag  -= 49;
    873:           i2     -= 7;
    874:         }
    875:         break;
    876:       default:
    877:         for (i=m-1; i>=0; i--) {
    878:           v  = aa + bs2*ai[i];
    879:           vi = aj + ai[i];
    880:           nz = ai[i+1] - ai[i];

    882:           PetscMemcpy(w,b+i2,bs*sizeof(PetscScalar));
    883:           /* copy all rows of x that are needed into contiguous space */
    884:           workt = work;
    885:           for (j=0; j<nz; j++) {
    886:             PetscMemcpy(workt,x + bs*(*vi++),bs*sizeof(PetscScalar));
    887:             workt += bs;
    888:           }
    889:           PetscKernel_w_gets_w_minus_Ar_times_v(bs,bs*nz,w,v,work);
    890:           PetscKernel_w_gets_w_plus_Ar_times_v(bs,bs,w,idiag,x+i2);

    892:           idiag -= bs2;
    893:           i2    -= bs;
    894:         }
    895:         break;
    896:       }
    897:       PetscLogFlops(2.0*bs2*(a->nz));
    898:     }
    899:   }
    900:   VecRestoreArray(xx,&x);
    901:   VecRestoreArrayRead(bb,&b);
    902:   return(0);
    903: }

    906: /*
    907:     Special version for direct calls from Fortran (Used in PETSc-fun3d)
    908: */
    909: #if defined(PETSC_HAVE_FORTRAN_CAPS)
    910: #define matsetvaluesblocked4_ MATSETVALUESBLOCKED4
    911: #elif !defined(PETSC_HAVE_FORTRAN_UNDERSCORE)
    912: #define matsetvaluesblocked4_ matsetvaluesblocked4
    913: #endif

    917: PETSC_EXTERN void matsetvaluesblocked4_(Mat *AA,PetscInt *mm,const PetscInt im[],PetscInt *nn,const PetscInt in[],const PetscScalar v[])
    918: {
    919:   Mat               A  = *AA;
    920:   Mat_SeqBAIJ       *a = (Mat_SeqBAIJ*)A->data;
    921:   PetscInt          *rp,k,low,high,t,ii,jj,row,nrow,i,col,l,N,m = *mm,n = *nn;
    922:   PetscInt          *ai    =a->i,*ailen=a->ilen;
    923:   PetscInt          *aj    =a->j,stepval,lastcol = -1;
    924:   const PetscScalar *value = v;
    925:   MatScalar         *ap,*aa = a->a,*bap;

    928:   if (A->rmap->bs != 4) SETERRABORT(PetscObjectComm((PetscObject)A),PETSC_ERR_ARG_WRONG,"Can only be called with a block size of 4");
    929:   stepval = (n-1)*4;
    930:   for (k=0; k<m; k++) { /* loop over added rows */
    931:     row  = im[k];
    932:     rp   = aj + ai[row];
    933:     ap   = aa + 16*ai[row];
    934:     nrow = ailen[row];
    935:     low  = 0;
    936:     high = nrow;
    937:     for (l=0; l<n; l++) { /* loop over added columns */
    938:       col = in[l];
    939:       if (col <= lastcol)  low = 0;
    940:       else                high = nrow;
    941:       lastcol = col;
    942:       value   = v + k*(stepval+4 + l)*4;
    943:       while (high-low > 7) {
    944:         t = (low+high)/2;
    945:         if (rp[t] > col) high = t;
    946:         else             low  = t;
    947:       }
    948:       for (i=low; i<high; i++) {
    949:         if (rp[i] > col) break;
    950:         if (rp[i] == col) {
    951:           bap = ap +  16*i;
    952:           for (ii=0; ii<4; ii++,value+=stepval) {
    953:             for (jj=ii; jj<16; jj+=4) {
    954:               bap[jj] += *value++;
    955:             }
    956:           }
    957:           goto noinsert2;
    958:         }
    959:       }
    960:       N = nrow++ - 1;
    961:       high++; /* added new column index thus must search to one higher than before */
    962:       /* shift up all the later entries in this row */
    963:       for (ii=N; ii>=i; ii--) {
    964:         rp[ii+1] = rp[ii];
    965:         PetscMemcpy(ap+16*(ii+1),ap+16*(ii),16*sizeof(MatScalar));
    966:       }
    967:       if (N >= i) {
    968:         PetscMemzero(ap+16*i,16*sizeof(MatScalar));
    969:       }
    970:       rp[i] = col;
    971:       bap   = ap +  16*i;
    972:       for (ii=0; ii<4; ii++,value+=stepval) {
    973:         for (jj=ii; jj<16; jj+=4) {
    974:           bap[jj] = *value++;
    975:         }
    976:       }
    977:       noinsert2:;
    978:       low = i;
    979:     }
    980:     ailen[row] = nrow;
    981:   }
    982:   PetscFunctionReturnVoid();
    983: }

    985: #if defined(PETSC_HAVE_FORTRAN_CAPS)
    986: #define matsetvalues4_ MATSETVALUES4
    987: #elif !defined(PETSC_HAVE_FORTRAN_UNDERSCORE)
    988: #define matsetvalues4_ matsetvalues4
    989: #endif

    993: PETSC_EXTERN void matsetvalues4_(Mat *AA,PetscInt *mm,PetscInt *im,PetscInt *nn,PetscInt *in,PetscScalar *v)
    994: {
    995:   Mat         A  = *AA;
    996:   Mat_SeqBAIJ *a = (Mat_SeqBAIJ*)A->data;
    997:   PetscInt    *rp,k,low,high,t,ii,row,nrow,i,col,l,N,n = *nn,m = *mm;
    998:   PetscInt    *ai=a->i,*ailen=a->ilen;
    999:   PetscInt    *aj=a->j,brow,bcol;
    1000:   PetscInt    ridx,cidx,lastcol = -1;
    1001:   MatScalar   *ap,value,*aa=a->a,*bap;

    1004:   for (k=0; k<m; k++) { /* loop over added rows */
    1005:     row  = im[k]; brow = row/4;
    1006:     rp   = aj + ai[brow];
    1007:     ap   = aa + 16*ai[brow];
    1008:     nrow = ailen[brow];
    1009:     low  = 0;
    1010:     high = nrow;
    1011:     for (l=0; l<n; l++) { /* loop over added columns */
    1012:       col   = in[l]; bcol = col/4;
    1013:       ridx  = row % 4; cidx = col % 4;
    1014:       value = v[l + k*n];
    1015:       if (col <= lastcol)  low = 0;
    1016:       else                high = nrow;
    1017:       lastcol = col;
    1018:       while (high-low > 7) {
    1019:         t = (low+high)/2;
    1020:         if (rp[t] > bcol) high = t;
    1021:         else              low  = t;
    1022:       }
    1023:       for (i=low; i<high; i++) {
    1024:         if (rp[i] > bcol) break;
    1025:         if (rp[i] == bcol) {
    1026:           bap   = ap +  16*i + 4*cidx + ridx;
    1027:           *bap += value;
    1028:           goto noinsert1;
    1029:         }
    1030:       }
    1031:       N = nrow++ - 1;
    1032:       high++; /* added new column thus must search to one higher than before */
    1033:       /* shift up all the later entries in this row */
    1034:       for (ii=N; ii>=i; ii--) {
    1035:         rp[ii+1] = rp[ii];
    1036:         PetscMemcpy(ap+16*(ii+1),ap+16*(ii),16*sizeof(MatScalar));
    1037:       }
    1038:       if (N>=i) {
    1039:         PetscMemzero(ap+16*i,16*sizeof(MatScalar));
    1040:       }
    1041:       rp[i]                    = bcol;
    1042:       ap[16*i + 4*cidx + ridx] = value;
    1043: noinsert1:;
    1044:       low = i;
    1045:     }
    1046:     ailen[brow] = nrow;
    1047:   }
    1048:   PetscFunctionReturnVoid();
    1049: }

    1051: /*
    1052:      Checks for missing diagonals
    1053: */
    1056: PetscErrorCode MatMissingDiagonal_SeqBAIJ(Mat A,PetscBool  *missing,PetscInt *d)
    1057: {
    1058:   Mat_SeqBAIJ    *a = (Mat_SeqBAIJ*)A->data;
    1060:   PetscInt       *diag,*ii = a->i,i;

    1063:   MatMarkDiagonal_SeqBAIJ(A);
    1064:   *missing = PETSC_FALSE;
    1065:   if (A->rmap->n > 0 && !ii) {
    1066:     *missing = PETSC_TRUE;
    1067:     if (d) *d = 0;
    1068:     PetscInfo(A,"Matrix has no entries therefore is missing diagonal\n");
    1069:   } else {
    1070:     diag = a->diag;
    1071:     for (i=0; i<a->mbs; i++) {
    1072:       if (diag[i] >= ii[i+1]) {
    1073:         *missing = PETSC_TRUE;
    1074:         if (d) *d = i;
    1075:         PetscInfo1(A,"Matrix is missing block diagonal number %D\n",i);
    1076:         break;
    1077:       }
    1078:     }
    1079:   }
    1080:   return(0);
    1081: }

    1085: PetscErrorCode MatMarkDiagonal_SeqBAIJ(Mat A)
    1086: {
    1087:   Mat_SeqBAIJ    *a = (Mat_SeqBAIJ*)A->data;
    1089:   PetscInt       i,j,m = a->mbs;

    1092:   if (!a->diag) {
    1093:     PetscMalloc1(m,&a->diag);
    1094:     PetscLogObjectMemory((PetscObject)A,m*sizeof(PetscInt));
    1095:     a->free_diag = PETSC_TRUE;
    1096:   }
    1097:   for (i=0; i<m; i++) {
    1098:     a->diag[i] = a->i[i+1];
    1099:     for (j=a->i[i]; j<a->i[i+1]; j++) {
    1100:       if (a->j[j] == i) {
    1101:         a->diag[i] = j;
    1102:         break;
    1103:       }
    1104:     }
    1105:   }
    1106:   return(0);
    1107: }

    1112: static PetscErrorCode MatGetRowIJ_SeqBAIJ(Mat A,PetscInt oshift,PetscBool symmetric,PetscBool blockcompressed,PetscInt *nn,const PetscInt *inia[],const PetscInt *inja[],PetscBool  *done)
    1113: {
    1114:   Mat_SeqBAIJ    *a = (Mat_SeqBAIJ*)A->data;
    1116:   PetscInt       i,j,n = a->mbs,nz = a->i[n],*tia,*tja,bs = A->rmap->bs,k,l,cnt;
    1117:   PetscInt       **ia = (PetscInt**)inia,**ja = (PetscInt**)inja;

    1120:   *nn = n;
    1121:   if (!ia) return(0);
    1122:   if (symmetric) {
    1123:     MatToSymmetricIJ_SeqAIJ(n,a->i,a->j,PETSC_TRUE,0,0,&tia,&tja);
    1124:     nz   = tia[n];
    1125:   } else {
    1126:     tia = a->i; tja = a->j;
    1127:   }

    1129:   if (!blockcompressed && bs > 1) {
    1130:     (*nn) *= bs;
    1131:     /* malloc & create the natural set of indices */
    1132:     PetscMalloc1((n+1)*bs,ia);
    1133:     if (n) {
    1134:       (*ia)[0] = oshift;
    1135:       for (j=1; j<bs; j++) {
    1136:         (*ia)[j] = (tia[1]-tia[0])*bs+(*ia)[j-1];
    1137:       }
    1138:     }

    1140:     for (i=1; i<n; i++) {
    1141:       (*ia)[i*bs] = (tia[i]-tia[i-1])*bs + (*ia)[i*bs-1];
    1142:       for (j=1; j<bs; j++) {
    1143:         (*ia)[i*bs+j] = (tia[i+1]-tia[i])*bs + (*ia)[i*bs+j-1];
    1144:       }
    1145:     }
    1146:     if (n) {
    1147:       (*ia)[n*bs] = (tia[n]-tia[n-1])*bs + (*ia)[n*bs-1];
    1148:     }

    1150:     if (inja) {
    1151:       PetscMalloc1(nz*bs*bs,ja);
    1152:       cnt = 0;
    1153:       for (i=0; i<n; i++) {
    1154:         for (j=0; j<bs; j++) {
    1155:           for (k=tia[i]; k<tia[i+1]; k++) {
    1156:             for (l=0; l<bs; l++) {
    1157:               (*ja)[cnt++] = bs*tja[k] + l;
    1158:             }
    1159:           }
    1160:         }
    1161:       }
    1162:     }

    1164:     if (symmetric) { /* deallocate memory allocated in MatToSymmetricIJ_SeqAIJ() */
    1165:       PetscFree(tia);
    1166:       PetscFree(tja);
    1167:     }
    1168:   } else if (oshift == 1) {
    1169:     if (symmetric) {
    1170:       nz = tia[A->rmap->n/bs];
    1171:       /*  add 1 to i and j indices */
    1172:       for (i=0; i<A->rmap->n/bs+1; i++) tia[i] = tia[i] + 1;
    1173:       *ia = tia;
    1174:       if (ja) {
    1175:         for (i=0; i<nz; i++) tja[i] = tja[i] + 1;
    1176:         *ja = tja;
    1177:       }
    1178:     } else {
    1179:       nz = a->i[A->rmap->n/bs];
    1180:       /* malloc space and  add 1 to i and j indices */
    1181:       PetscMalloc1(A->rmap->n/bs+1,ia);
    1182:       for (i=0; i<A->rmap->n/bs+1; i++) (*ia)[i] = a->i[i] + 1;
    1183:       if (ja) {
    1184:         PetscMalloc1(nz,ja);
    1185:         for (i=0; i<nz; i++) (*ja)[i] = a->j[i] + 1;
    1186:       }
    1187:     }
    1188:   } else {
    1189:     *ia = tia;
    1190:     if (ja) *ja = tja;
    1191:   }
    1192:   return(0);
    1193: }

    1197: static PetscErrorCode MatRestoreRowIJ_SeqBAIJ(Mat A,PetscInt oshift,PetscBool symmetric,PetscBool blockcompressed,PetscInt *nn,const PetscInt *ia[],const PetscInt *ja[],PetscBool  *done)
    1198: {

    1202:   if (!ia) return(0);
    1203:   if ((!blockcompressed && A->rmap->bs > 1) || (symmetric || oshift == 1)) {
    1204:     PetscFree(*ia);
    1205:     if (ja) {PetscFree(*ja);}
    1206:   }
    1207:   return(0);
    1208: }

    1212: PetscErrorCode MatDestroy_SeqBAIJ(Mat A)
    1213: {
    1214:   Mat_SeqBAIJ    *a = (Mat_SeqBAIJ*)A->data;

    1218: #if defined(PETSC_USE_LOG)
    1219:   PetscLogObjectState((PetscObject)A,"Rows=%D, Cols=%D, NZ=%D",A->rmap->N,A->cmap->n,a->nz);
    1220: #endif
    1221:   MatSeqXAIJFreeAIJ(A,&a->a,&a->j,&a->i);
    1222:   ISDestroy(&a->row);
    1223:   ISDestroy(&a->col);
    1224:   if (a->free_diag) {PetscFree(a->diag);}
    1225:   PetscFree(a->idiag);
    1226:   if (a->free_imax_ilen) {PetscFree2(a->imax,a->ilen);}
    1227:   PetscFree(a->solve_work);
    1228:   PetscFree(a->mult_work);
    1229:   PetscFree(a->sor_workt);
    1230:   PetscFree(a->sor_work);
    1231:   ISDestroy(&a->icol);
    1232:   PetscFree(a->saved_values);
    1233:   PetscFree2(a->compressedrow.i,a->compressedrow.rindex);

    1235:   MatDestroy(&a->sbaijMat);
    1236:   MatDestroy(&a->parent);
    1237:   PetscFree(A->data);

    1239:   PetscObjectChangeTypeName((PetscObject)A,0);
    1240:   PetscObjectComposeFunction((PetscObject)A,"MatInvertBlockDiagonal_C",NULL);
    1241:   PetscObjectComposeFunction((PetscObject)A,"MatStoreValues_C",NULL);
    1242:   PetscObjectComposeFunction((PetscObject)A,"MatRetrieveValues_C",NULL);
    1243:   PetscObjectComposeFunction((PetscObject)A,"MatSeqBAIJSetColumnIndices_C",NULL);
    1244:   PetscObjectComposeFunction((PetscObject)A,"MatConvert_seqbaij_seqaij_C",NULL);
    1245:   PetscObjectComposeFunction((PetscObject)A,"MatConvert_seqbaij_seqsbaij_C",NULL);
    1246:   PetscObjectComposeFunction((PetscObject)A,"MatSeqBAIJSetPreallocation_C",NULL);
    1247:   PetscObjectComposeFunction((PetscObject)A,"MatSeqBAIJSetPreallocationCSR_C",NULL);
    1248:   PetscObjectComposeFunction((PetscObject)A,"MatConvert_seqbaij_seqbstrm_C",NULL);
    1249:   PetscObjectComposeFunction((PetscObject)A,"MatIsTranspose_C",NULL);
    1250:   return(0);
    1251: }

    1255: PetscErrorCode MatSetOption_SeqBAIJ(Mat A,MatOption op,PetscBool flg)
    1256: {
    1257:   Mat_SeqBAIJ    *a = (Mat_SeqBAIJ*)A->data;

    1261:   switch (op) {
    1262:   case MAT_ROW_ORIENTED:
    1263:     a->roworiented = flg;
    1264:     break;
    1265:   case MAT_KEEP_NONZERO_PATTERN:
    1266:     a->keepnonzeropattern = flg;
    1267:     break;
    1268:   case MAT_NEW_NONZERO_LOCATIONS:
    1269:     a->nonew = (flg ? 0 : 1);
    1270:     break;
    1271:   case MAT_NEW_NONZERO_LOCATION_ERR:
    1272:     a->nonew = (flg ? -1 : 0);
    1273:     break;
    1274:   case MAT_NEW_NONZERO_ALLOCATION_ERR:
    1275:     a->nonew = (flg ? -2 : 0);
    1276:     break;
    1277:   case MAT_UNUSED_NONZERO_LOCATION_ERR:
    1278:     a->nounused = (flg ? -1 : 0);
    1279:     break;
    1280:   case MAT_NEW_DIAGONALS:
    1281:   case MAT_IGNORE_OFF_PROC_ENTRIES:
    1282:   case MAT_USE_HASH_TABLE:
    1283:     PetscInfo1(A,"Option %s ignored\n",MatOptions[op]);
    1284:     break;
    1285:   case MAT_SPD:
    1286:   case MAT_SYMMETRIC:
    1287:   case MAT_STRUCTURALLY_SYMMETRIC:
    1288:   case MAT_HERMITIAN:
    1289:   case MAT_SYMMETRY_ETERNAL:
    1290:     /* These options are handled directly by MatSetOption() */
    1291:     break;
    1292:   default:
    1293:     SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_SUP,"unknown option %d",op);
    1294:   }
    1295:   return(0);
    1296: }

    1298: /* used for both SeqBAIJ and SeqSBAIJ matrices */
    1301: PetscErrorCode MatGetRow_SeqBAIJ_private(Mat A,PetscInt row,PetscInt *nz,PetscInt **idx,PetscScalar **v,PetscInt *ai,PetscInt *aj,PetscScalar *aa)
    1302: {
    1304:   PetscInt       itmp,i,j,k,M,bn,bp,*idx_i,bs,bs2;
    1305:   MatScalar      *aa_i;
    1306:   PetscScalar    *v_i;

    1309:   bs  = A->rmap->bs;
    1310:   bs2 = bs*bs;
    1311:   if (row < 0 || row >= A->rmap->N) SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Row %D out of range", row);

    1313:   bn  = row/bs;   /* Block number */
    1314:   bp  = row % bs; /* Block Position */
    1315:   M   = ai[bn+1] - ai[bn];
    1316:   *nz = bs*M;

    1318:   if (v) {
    1319:     *v = 0;
    1320:     if (*nz) {
    1321:       PetscMalloc1(*nz,v);
    1322:       for (i=0; i<M; i++) { /* for each block in the block row */
    1323:         v_i  = *v + i*bs;
    1324:         aa_i = aa + bs2*(ai[bn] + i);
    1325:         for (j=bp,k=0; j<bs2; j+=bs,k++) v_i[k] = aa_i[j];
    1326:       }
    1327:     }
    1328:   }

    1330:   if (idx) {
    1331:     *idx = 0;
    1332:     if (*nz) {
    1333:       PetscMalloc1(*nz,idx);
    1334:       for (i=0; i<M; i++) { /* for each block in the block row */
    1335:         idx_i = *idx + i*bs;
    1336:         itmp  = bs*aj[ai[bn] + i];
    1337:         for (j=0; j<bs; j++) idx_i[j] = itmp++;
    1338:       }
    1339:     }
    1340:   }
    1341:   return(0);
    1342: }

    1346: PetscErrorCode MatGetRow_SeqBAIJ(Mat A,PetscInt row,PetscInt *nz,PetscInt **idx,PetscScalar **v)
    1347: {
    1348:   Mat_SeqBAIJ    *a = (Mat_SeqBAIJ*)A->data;

    1352:   MatGetRow_SeqBAIJ_private(A,row,nz,idx,v,a->i,a->j,a->a);
    1353:   return(0);
    1354: }

    1358: PetscErrorCode MatRestoreRow_SeqBAIJ(Mat A,PetscInt row,PetscInt *nz,PetscInt **idx,PetscScalar **v)
    1359: {

    1363:   if (idx) {PetscFree(*idx);}
    1364:   if (v)   {PetscFree(*v);}
    1365:   return(0);
    1366: }

    1368: extern PetscErrorCode MatSetValues_SeqBAIJ(Mat,PetscInt,const PetscInt[],PetscInt,const PetscInt[],const PetscScalar[],InsertMode);

    1372: PetscErrorCode MatTranspose_SeqBAIJ(Mat A,MatReuse reuse,Mat *B)
    1373: {
    1374:   Mat_SeqBAIJ    *a=(Mat_SeqBAIJ*)A->data;
    1375:   Mat            C;
    1377:   PetscInt       i,j,k,*aj=a->j,*ai=a->i,bs=A->rmap->bs,mbs=a->mbs,nbs=a->nbs,len,*col;
    1378:   PetscInt       *rows,*cols,bs2=a->bs2;
    1379:   MatScalar      *array;

    1382:   if (reuse == MAT_REUSE_MATRIX && A == *B && mbs != nbs) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"Square matrix only for in-place");
    1383:   if (reuse == MAT_INITIAL_MATRIX || A == *B) {
    1384:     PetscCalloc1(1+nbs,&col);

    1386:     for (i=0; i<ai[mbs]; i++) col[aj[i]] += 1;
    1387:     MatCreate(PetscObjectComm((PetscObject)A),&C);
    1388:     MatSetSizes(C,A->cmap->n,A->rmap->N,A->cmap->n,A->rmap->N);
    1389:     MatSetType(C,((PetscObject)A)->type_name);
    1390:     MatSeqBAIJSetPreallocation_SeqBAIJ(C,bs,0,col);
    1391:     PetscFree(col);
    1392:   } else {
    1393:     C = *B;
    1394:   }

    1396:   array = a->a;
    1397:   PetscMalloc2(bs,&rows,bs,&cols);
    1398:   for (i=0; i<mbs; i++) {
    1399:     cols[0] = i*bs;
    1400:     for (k=1; k<bs; k++) cols[k] = cols[k-1] + 1;
    1401:     len = ai[i+1] - ai[i];
    1402:     for (j=0; j<len; j++) {
    1403:       rows[0] = (*aj++)*bs;
    1404:       for (k=1; k<bs; k++) rows[k] = rows[k-1] + 1;
    1405:       MatSetValues_SeqBAIJ(C,bs,rows,bs,cols,array,INSERT_VALUES);
    1406:       array += bs2;
    1407:     }
    1408:   }
    1409:   PetscFree2(rows,cols);

    1411:   MatAssemblyBegin(C,MAT_FINAL_ASSEMBLY);
    1412:   MatAssemblyEnd(C,MAT_FINAL_ASSEMBLY);

    1414:   if (reuse == MAT_INITIAL_MATRIX || *B != A) {
    1415:     *B = C;
    1416:   } else {
    1417:     MatHeaderMerge(A,&C);
    1418:   }
    1419:   return(0);
    1420: }

    1424: PetscErrorCode MatIsTranspose_SeqBAIJ(Mat A,Mat B,PetscReal tol,PetscBool  *f)
    1425: {
    1427:   Mat            Btrans;

    1430:   *f   = PETSC_FALSE;
    1431:   MatTranspose_SeqBAIJ(A,MAT_INITIAL_MATRIX,&Btrans);
    1432:   MatEqual_SeqBAIJ(B,Btrans,f);
    1433:   MatDestroy(&Btrans);
    1434:   return(0);
    1435: }

    1439: static PetscErrorCode MatView_SeqBAIJ_Binary(Mat A,PetscViewer viewer)
    1440: {
    1441:   Mat_SeqBAIJ    *a = (Mat_SeqBAIJ*)A->data;
    1443:   PetscInt       i,*col_lens,bs = A->rmap->bs,count,*jj,j,k,l,bs2=a->bs2;
    1444:   int            fd;
    1445:   PetscScalar    *aa;
    1446:   FILE           *file;

    1449:   PetscViewerBinaryGetDescriptor(viewer,&fd);
    1450:   PetscMalloc1(4+A->rmap->N,&col_lens);
    1451:   col_lens[0] = MAT_FILE_CLASSID;

    1453:   col_lens[1] = A->rmap->N;
    1454:   col_lens[2] = A->cmap->n;
    1455:   col_lens[3] = a->nz*bs2;

    1457:   /* store lengths of each row and write (including header) to file */
    1458:   count = 0;
    1459:   for (i=0; i<a->mbs; i++) {
    1460:     for (j=0; j<bs; j++) {
    1461:       col_lens[4+count++] = bs*(a->i[i+1] - a->i[i]);
    1462:     }
    1463:   }
    1464:   PetscBinaryWrite(fd,col_lens,4+A->rmap->N,PETSC_INT,PETSC_TRUE);
    1465:   PetscFree(col_lens);

    1467:   /* store column indices (zero start index) */
    1468:   PetscMalloc1((a->nz+1)*bs2,&jj);
    1469:   count = 0;
    1470:   for (i=0; i<a->mbs; i++) {
    1471:     for (j=0; j<bs; j++) {
    1472:       for (k=a->i[i]; k<a->i[i+1]; k++) {
    1473:         for (l=0; l<bs; l++) {
    1474:           jj[count++] = bs*a->j[k] + l;
    1475:         }
    1476:       }
    1477:     }
    1478:   }
    1479:   PetscBinaryWrite(fd,jj,bs2*a->nz,PETSC_INT,PETSC_FALSE);
    1480:   PetscFree(jj);

    1482:   /* store nonzero values */
    1483:   PetscMalloc1((a->nz+1)*bs2,&aa);
    1484:   count = 0;
    1485:   for (i=0; i<a->mbs; i++) {
    1486:     for (j=0; j<bs; j++) {
    1487:       for (k=a->i[i]; k<a->i[i+1]; k++) {
    1488:         for (l=0; l<bs; l++) {
    1489:           aa[count++] = a->a[bs2*k + l*bs + j];
    1490:         }
    1491:       }
    1492:     }
    1493:   }
    1494:   PetscBinaryWrite(fd,aa,bs2*a->nz,PETSC_SCALAR,PETSC_FALSE);
    1495:   PetscFree(aa);

    1497:   PetscViewerBinaryGetInfoPointer(viewer,&file);
    1498:   if (file) {
    1499:     fprintf(file,"-matload_block_size %d\n",(int)A->rmap->bs);
    1500:   }
    1501:   return(0);
    1502: }

    1506: static PetscErrorCode MatView_SeqBAIJ_ASCII(Mat A,PetscViewer viewer)
    1507: {
    1508:   Mat_SeqBAIJ       *a = (Mat_SeqBAIJ*)A->data;
    1509:   PetscErrorCode    ierr;
    1510:   PetscInt          i,j,bs = A->rmap->bs,k,l,bs2=a->bs2;
    1511:   PetscViewerFormat format;

    1514:   PetscViewerGetFormat(viewer,&format);
    1515:   if (format == PETSC_VIEWER_ASCII_INFO || format == PETSC_VIEWER_ASCII_INFO_DETAIL) {
    1516:     PetscViewerASCIIPrintf(viewer,"  block size is %D\n",bs);
    1517:   } else if (format == PETSC_VIEWER_ASCII_MATLAB) {
    1518:     const char *matname;
    1519:     Mat        aij;
    1520:     MatConvert(A,MATSEQAIJ,MAT_INITIAL_MATRIX,&aij);
    1521:     PetscObjectGetName((PetscObject)A,&matname);
    1522:     PetscObjectSetName((PetscObject)aij,matname);
    1523:     MatView(aij,viewer);
    1524:     MatDestroy(&aij);
    1525:   } else if (format == PETSC_VIEWER_ASCII_FACTOR_INFO) {
    1526:       return(0);
    1527:   } else if (format == PETSC_VIEWER_ASCII_COMMON) {
    1528:     PetscViewerASCIIUseTabs(viewer,PETSC_FALSE);
    1529:     for (i=0; i<a->mbs; i++) {
    1530:       for (j=0; j<bs; j++) {
    1531:         PetscViewerASCIIPrintf(viewer,"row %D:",i*bs+j);
    1532:         for (k=a->i[i]; k<a->i[i+1]; k++) {
    1533:           for (l=0; l<bs; l++) {
    1534: #if defined(PETSC_USE_COMPLEX)
    1535:             if (PetscImaginaryPart(a->a[bs2*k + l*bs + j]) > 0.0 && PetscRealPart(a->a[bs2*k + l*bs + j]) != 0.0) {
    1536:               PetscViewerASCIIPrintf(viewer," (%D, %g + %gi) ",bs*a->j[k]+l,
    1537:                                             (double)PetscRealPart(a->a[bs2*k + l*bs + j]),(double)PetscImaginaryPart(a->a[bs2*k + l*bs + j]));
    1538:             } else if (PetscImaginaryPart(a->a[bs2*k + l*bs + j]) < 0.0 && PetscRealPart(a->a[bs2*k + l*bs + j]) != 0.0) {
    1539:               PetscViewerASCIIPrintf(viewer," (%D, %g - %gi) ",bs*a->j[k]+l,
    1540:                                             (double)PetscRealPart(a->a[bs2*k + l*bs + j]),-(double)PetscImaginaryPart(a->a[bs2*k + l*bs + j]));
    1541:             } else if (PetscRealPart(a->a[bs2*k + l*bs + j]) != 0.0) {
    1542:               PetscViewerASCIIPrintf(viewer," (%D, %g) ",bs*a->j[k]+l,(double)PetscRealPart(a->a[bs2*k + l*bs + j]));
    1543:             }
    1544: #else
    1545:             if (a->a[bs2*k + l*bs + j] != 0.0) {
    1546:               PetscViewerASCIIPrintf(viewer," (%D, %g) ",bs*a->j[k]+l,(double)a->a[bs2*k + l*bs + j]);
    1547:             }
    1548: #endif
    1549:           }
    1550:         }
    1551:         PetscViewerASCIIPrintf(viewer,"\n");
    1552:       }
    1553:     }
    1554:     PetscViewerASCIIUseTabs(viewer,PETSC_TRUE);
    1555:   } else {
    1556:     PetscViewerASCIIUseTabs(viewer,PETSC_FALSE);
    1557:     for (i=0; i<a->mbs; i++) {
    1558:       for (j=0; j<bs; j++) {
    1559:         PetscViewerASCIIPrintf(viewer,"row %D:",i*bs+j);
    1560:         for (k=a->i[i]; k<a->i[i+1]; k++) {
    1561:           for (l=0; l<bs; l++) {
    1562: #if defined(PETSC_USE_COMPLEX)
    1563:             if (PetscImaginaryPart(a->a[bs2*k + l*bs + j]) > 0.0) {
    1564:               PetscViewerASCIIPrintf(viewer," (%D, %g + %g i) ",bs*a->j[k]+l,
    1565:                                             (double)PetscRealPart(a->a[bs2*k + l*bs + j]),(double)PetscImaginaryPart(a->a[bs2*k + l*bs + j]));
    1566:             } else if (PetscImaginaryPart(a->a[bs2*k + l*bs + j]) < 0.0) {
    1567:               PetscViewerASCIIPrintf(viewer," (%D, %g - %g i) ",bs*a->j[k]+l,
    1568:                                             (double)PetscRealPart(a->a[bs2*k + l*bs + j]),-(double)PetscImaginaryPart(a->a[bs2*k + l*bs + j]));
    1569:             } else {
    1570:               PetscViewerASCIIPrintf(viewer," (%D, %g) ",bs*a->j[k]+l,(double)PetscRealPart(a->a[bs2*k + l*bs + j]));
    1571:             }
    1572: #else
    1573:             PetscViewerASCIIPrintf(viewer," (%D, %g) ",bs*a->j[k]+l,(double)a->a[bs2*k + l*bs + j]);
    1574: #endif
    1575:           }
    1576:         }
    1577:         PetscViewerASCIIPrintf(viewer,"\n");
    1578:       }
    1579:     }
    1580:     PetscViewerASCIIUseTabs(viewer,PETSC_TRUE);
    1581:   }
    1582:   PetscViewerFlush(viewer);
    1583:   return(0);
    1584: }

    1586: #include <petscdraw.h>
    1589: static PetscErrorCode MatView_SeqBAIJ_Draw_Zoom(PetscDraw draw,void *Aa)
    1590: {
    1591:   Mat               A = (Mat) Aa;
    1592:   Mat_SeqBAIJ       *a=(Mat_SeqBAIJ*)A->data;
    1593:   PetscErrorCode    ierr;
    1594:   PetscInt          row,i,j,k,l,mbs=a->mbs,color,bs=A->rmap->bs,bs2=a->bs2;
    1595:   PetscReal         xl,yl,xr,yr,x_l,x_r,y_l,y_r;
    1596:   MatScalar         *aa;
    1597:   PetscViewer       viewer;
    1598:   PetscViewerFormat format;

    1601:   PetscObjectQuery((PetscObject)A,"Zoomviewer",(PetscObject*)&viewer);
    1602:   PetscViewerGetFormat(viewer,&format);
    1603:   PetscDrawGetCoordinates(draw,&xl,&yl,&xr,&yr);

    1605:   /* loop over matrix elements drawing boxes */

    1607:   if (format != PETSC_VIEWER_DRAW_CONTOUR) {
    1608:     PetscDrawCollectiveBegin(draw);
    1609:     /* Blue for negative, Cyan for zero and  Red for positive */
    1610:     color = PETSC_DRAW_BLUE;
    1611:     for (i=0,row=0; i<mbs; i++,row+=bs) {
    1612:       for (j=a->i[i]; j<a->i[i+1]; j++) {
    1613:         y_l = A->rmap->N - row - 1.0; y_r = y_l + 1.0;
    1614:         x_l = a->j[j]*bs; x_r = x_l + 1.0;
    1615:         aa  = a->a + j*bs2;
    1616:         for (k=0; k<bs; k++) {
    1617:           for (l=0; l<bs; l++) {
    1618:             if (PetscRealPart(*aa++) >=  0.) continue;
    1619:             PetscDrawRectangle(draw,x_l+k,y_l-l,x_r+k,y_r-l,color,color,color,color);
    1620:           }
    1621:         }
    1622:       }
    1623:     }
    1624:     color = PETSC_DRAW_CYAN;
    1625:     for (i=0,row=0; i<mbs; i++,row+=bs) {
    1626:       for (j=a->i[i]; j<a->i[i+1]; j++) {
    1627:         y_l = A->rmap->N - row - 1.0; y_r = y_l + 1.0;
    1628:         x_l = a->j[j]*bs; x_r = x_l + 1.0;
    1629:         aa  = a->a + j*bs2;
    1630:         for (k=0; k<bs; k++) {
    1631:           for (l=0; l<bs; l++) {
    1632:             if (PetscRealPart(*aa++) != 0.) continue;
    1633:             PetscDrawRectangle(draw,x_l+k,y_l-l,x_r+k,y_r-l,color,color,color,color);
    1634:           }
    1635:         }
    1636:       }
    1637:     }
    1638:     color = PETSC_DRAW_RED;
    1639:     for (i=0,row=0; i<mbs; i++,row+=bs) {
    1640:       for (j=a->i[i]; j<a->i[i+1]; j++) {
    1641:         y_l = A->rmap->N - row - 1.0; y_r = y_l + 1.0;
    1642:         x_l = a->j[j]*bs; x_r = x_l + 1.0;
    1643:         aa  = a->a + j*bs2;
    1644:         for (k=0; k<bs; k++) {
    1645:           for (l=0; l<bs; l++) {
    1646:             if (PetscRealPart(*aa++) <= 0.) continue;
    1647:             PetscDrawRectangle(draw,x_l+k,y_l-l,x_r+k,y_r-l,color,color,color,color);
    1648:           }
    1649:         }
    1650:       }
    1651:     }
    1652:     PetscDrawCollectiveEnd(draw);
    1653:   } else {
    1654:     /* use contour shading to indicate magnitude of values */
    1655:     /* first determine max of all nonzero values */
    1656:     PetscReal minv = 0.0, maxv = 0.0;
    1657:     PetscDraw popup;

    1659:     for (i=0; i<a->nz*a->bs2; i++) {
    1660:       if (PetscAbsScalar(a->a[i]) > maxv) maxv = PetscAbsScalar(a->a[i]);
    1661:     }
    1662:     if (minv >= maxv) maxv = minv + PETSC_SMALL;
    1663:     PetscDrawGetPopup(draw,&popup);
    1664:     PetscDrawScalePopup(popup,0.0,maxv);

    1666:     PetscDrawCollectiveBegin(draw);
    1667:     for (i=0,row=0; i<mbs; i++,row+=bs) {
    1668:       for (j=a->i[i]; j<a->i[i+1]; j++) {
    1669:         y_l = A->rmap->N - row - 1.0; y_r = y_l + 1.0;
    1670:         x_l = a->j[j]*bs; x_r = x_l + 1.0;
    1671:         aa  = a->a + j*bs2;
    1672:         for (k=0; k<bs; k++) {
    1673:           for (l=0; l<bs; l++) {
    1674:             MatScalar v = *aa++;
    1675:             color = PetscDrawRealToColor(PetscAbsScalar(v),minv,maxv);
    1676:             PetscDrawRectangle(draw,x_l+k,y_l-l,x_r+k,y_r-l,color,color,color,color);
    1677:           }
    1678:         }
    1679:       }
    1680:     }
    1681:     PetscDrawCollectiveEnd(draw);
    1682:   }
    1683:   return(0);
    1684: }

    1688: static PetscErrorCode MatView_SeqBAIJ_Draw(Mat A,PetscViewer viewer)
    1689: {
    1691:   PetscReal      xl,yl,xr,yr,w,h;
    1692:   PetscDraw      draw;
    1693:   PetscBool      isnull;

    1696:   PetscViewerDrawGetDraw(viewer,0,&draw);
    1697:   PetscDrawIsNull(draw,&isnull);
    1698:   if (isnull) return(0);

    1700:   xr   = A->cmap->n; yr = A->rmap->N; h = yr/10.0; w = xr/10.0;
    1701:   xr  += w;          yr += h;        xl = -w;     yl = -h;
    1702:   PetscDrawSetCoordinates(draw,xl,yl,xr,yr);
    1703:   PetscObjectCompose((PetscObject)A,"Zoomviewer",(PetscObject)viewer);
    1704:   PetscDrawZoom(draw,MatView_SeqBAIJ_Draw_Zoom,A);
    1705:   PetscObjectCompose((PetscObject)A,"Zoomviewer",NULL);
    1706:   PetscDrawSave(draw);
    1707:   return(0);
    1708: }

    1712: PetscErrorCode MatView_SeqBAIJ(Mat A,PetscViewer viewer)
    1713: {
    1715:   PetscBool      iascii,isbinary,isdraw;

    1718:   PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERASCII,&iascii);
    1719:   PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERBINARY,&isbinary);
    1720:   PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERDRAW,&isdraw);
    1721:   if (iascii) {
    1722:     MatView_SeqBAIJ_ASCII(A,viewer);
    1723:   } else if (isbinary) {
    1724:     MatView_SeqBAIJ_Binary(A,viewer);
    1725:   } else if (isdraw) {
    1726:     MatView_SeqBAIJ_Draw(A,viewer);
    1727:   } else {
    1728:     Mat B;
    1729:     MatConvert(A,MATSEQAIJ,MAT_INITIAL_MATRIX,&B);
    1730:     MatView(B,viewer);
    1731:     MatDestroy(&B);
    1732:   }
    1733:   return(0);
    1734: }

    1739: PetscErrorCode MatGetValues_SeqBAIJ(Mat A,PetscInt m,const PetscInt im[],PetscInt n,const PetscInt in[],PetscScalar v[])
    1740: {
    1741:   Mat_SeqBAIJ *a = (Mat_SeqBAIJ*)A->data;
    1742:   PetscInt    *rp,k,low,high,t,row,nrow,i,col,l,*aj = a->j;
    1743:   PetscInt    *ai = a->i,*ailen = a->ilen;
    1744:   PetscInt    brow,bcol,ridx,cidx,bs=A->rmap->bs,bs2=a->bs2;
    1745:   MatScalar   *ap,*aa = a->a;

    1748:   for (k=0; k<m; k++) { /* loop over rows */
    1749:     row = im[k]; brow = row/bs;
    1750:     if (row < 0) {v += n; continue;} /* SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Negative row"); */
    1751:     if (row >= A->rmap->N) SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Row %D too large", row);
    1752:     rp   = aj + ai[brow]; ap = aa + bs2*ai[brow];
    1753:     nrow = ailen[brow];
    1754:     for (l=0; l<n; l++) { /* loop over columns */
    1755:       if (in[l] < 0) {v++; continue;} /* SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Negative column"); */
    1756:       if (in[l] >= A->cmap->n) SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Column %D too large", in[l]);
    1757:       col  = in[l];
    1758:       bcol = col/bs;
    1759:       cidx = col%bs;
    1760:       ridx = row%bs;
    1761:       high = nrow;
    1762:       low  = 0; /* assume unsorted */
    1763:       while (high-low > 5) {
    1764:         t = (low+high)/2;
    1765:         if (rp[t] > bcol) high = t;
    1766:         else             low  = t;
    1767:       }
    1768:       for (i=low; i<high; i++) {
    1769:         if (rp[i] > bcol) break;
    1770:         if (rp[i] == bcol) {
    1771:           *v++ = ap[bs2*i+bs*cidx+ridx];
    1772:           goto finished;
    1773:         }
    1774:       }
    1775:       *v++ = 0.0;
    1776: finished:;
    1777:     }
    1778:   }
    1779:   return(0);
    1780: }

    1784: PetscErrorCode MatSetValuesBlocked_SeqBAIJ(Mat A,PetscInt m,const PetscInt im[],PetscInt n,const PetscInt in[],const PetscScalar v[],InsertMode is)
    1785: {
    1786:   Mat_SeqBAIJ       *a = (Mat_SeqBAIJ*)A->data;
    1787:   PetscInt          *rp,k,low,high,t,ii,jj,row,nrow,i,col,l,rmax,N,lastcol = -1;
    1788:   PetscInt          *imax=a->imax,*ai=a->i,*ailen=a->ilen;
    1789:   PetscErrorCode    ierr;
    1790:   PetscInt          *aj        =a->j,nonew=a->nonew,bs2=a->bs2,bs=A->rmap->bs,stepval;
    1791:   PetscBool         roworiented=a->roworiented;
    1792:   const PetscScalar *value     = v;
    1793:   MatScalar         *ap,*aa = a->a,*bap;

    1796:   if (roworiented) {
    1797:     stepval = (n-1)*bs;
    1798:   } else {
    1799:     stepval = (m-1)*bs;
    1800:   }
    1801:   for (k=0; k<m; k++) { /* loop over added rows */
    1802:     row = im[k];
    1803:     if (row < 0) continue;
    1804: #if defined(PETSC_USE_DEBUG)
    1805:     if (row >= a->mbs) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Block row index too large %D max %D",row,a->mbs-1);
    1806: #endif
    1807:     rp   = aj + ai[row];
    1808:     ap   = aa + bs2*ai[row];
    1809:     rmax = imax[row];
    1810:     nrow = ailen[row];
    1811:     low  = 0;
    1812:     high = nrow;
    1813:     for (l=0; l<n; l++) { /* loop over added columns */
    1814:       if (in[l] < 0) continue;
    1815: #if defined(PETSC_USE_DEBUG)
    1816:       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);
    1817: #endif
    1818:       col = in[l];
    1819:       if (roworiented) {
    1820:         value = v + (k*(stepval+bs) + l)*bs;
    1821:       } else {
    1822:         value = v + (l*(stepval+bs) + k)*bs;
    1823:       }
    1824:       if (col <= lastcol) low = 0;
    1825:       else high = nrow;
    1826:       lastcol = col;
    1827:       while (high-low > 7) {
    1828:         t = (low+high)/2;
    1829:         if (rp[t] > col) high = t;
    1830:         else             low  = t;
    1831:       }
    1832:       for (i=low; i<high; i++) {
    1833:         if (rp[i] > col) break;
    1834:         if (rp[i] == col) {
    1835:           bap = ap +  bs2*i;
    1836:           if (roworiented) {
    1837:             if (is == ADD_VALUES) {
    1838:               for (ii=0; ii<bs; ii++,value+=stepval) {
    1839:                 for (jj=ii; jj<bs2; jj+=bs) {
    1840:                   bap[jj] += *value++;
    1841:                 }
    1842:               }
    1843:             } else {
    1844:               for (ii=0; ii<bs; ii++,value+=stepval) {
    1845:                 for (jj=ii; jj<bs2; jj+=bs) {
    1846:                   bap[jj] = *value++;
    1847:                 }
    1848:               }
    1849:             }
    1850:           } else {
    1851:             if (is == ADD_VALUES) {
    1852:               for (ii=0; ii<bs; ii++,value+=bs+stepval) {
    1853:                 for (jj=0; jj<bs; jj++) {
    1854:                   bap[jj] += value[jj];
    1855:                 }
    1856:                 bap += bs;
    1857:               }
    1858:             } else {
    1859:               for (ii=0; ii<bs; ii++,value+=bs+stepval) {
    1860:                 for (jj=0; jj<bs; jj++) {
    1861:                   bap[jj]  = value[jj];
    1862:                 }
    1863:                 bap += bs;
    1864:               }
    1865:             }
    1866:           }
    1867:           goto noinsert2;
    1868:         }
    1869:       }
    1870:       if (nonew == 1) goto noinsert2;
    1871:       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);
    1872:       MatSeqXAIJReallocateAIJ(A,a->mbs,bs2,nrow,row,col,rmax,aa,ai,aj,rp,ap,imax,nonew,MatScalar);
    1873:       N = nrow++ - 1; high++;
    1874:       /* shift up all the later entries in this row */
    1875:       for (ii=N; ii>=i; ii--) {
    1876:         rp[ii+1] = rp[ii];
    1877:         PetscMemcpy(ap+bs2*(ii+1),ap+bs2*(ii),bs2*sizeof(MatScalar));
    1878:       }
    1879:       if (N >= i) {
    1880:         PetscMemzero(ap+bs2*i,bs2*sizeof(MatScalar));
    1881:       }
    1882:       rp[i] = col;
    1883:       bap   = ap +  bs2*i;
    1884:       if (roworiented) {
    1885:         for (ii=0; ii<bs; ii++,value+=stepval) {
    1886:           for (jj=ii; jj<bs2; jj+=bs) {
    1887:             bap[jj] = *value++;
    1888:           }
    1889:         }
    1890:       } else {
    1891:         for (ii=0; ii<bs; ii++,value+=stepval) {
    1892:           for (jj=0; jj<bs; jj++) {
    1893:             *bap++ = *value++;
    1894:           }
    1895:         }
    1896:       }
    1897: noinsert2:;
    1898:       low = i;
    1899:     }
    1900:     ailen[row] = nrow;
    1901:   }
    1902:   return(0);
    1903: }

    1907: PetscErrorCode MatAssemblyEnd_SeqBAIJ(Mat A,MatAssemblyType mode)
    1908: {
    1909:   Mat_SeqBAIJ    *a     = (Mat_SeqBAIJ*)A->data;
    1910:   PetscInt       fshift = 0,i,j,*ai = a->i,*aj = a->j,*imax = a->imax;
    1911:   PetscInt       m      = A->rmap->N,*ip,N,*ailen = a->ilen;
    1913:   PetscInt       mbs  = a->mbs,bs2 = a->bs2,rmax = 0;
    1914:   MatScalar      *aa  = a->a,*ap;
    1915:   PetscReal      ratio=0.6;

    1918:   if (mode == MAT_FLUSH_ASSEMBLY) return(0);

    1920:   if (m) rmax = ailen[0];
    1921:   for (i=1; i<mbs; i++) {
    1922:     /* move each row back by the amount of empty slots (fshift) before it*/
    1923:     fshift += imax[i-1] - ailen[i-1];
    1924:     rmax    = PetscMax(rmax,ailen[i]);
    1925:     if (fshift) {
    1926:       ip = aj + ai[i]; ap = aa + bs2*ai[i];
    1927:       N  = ailen[i];
    1928:       for (j=0; j<N; j++) {
    1929:         ip[j-fshift] = ip[j];

    1931:         PetscMemcpy(ap+(j-fshift)*bs2,ap+j*bs2,bs2*sizeof(MatScalar));
    1932:       }
    1933:     }
    1934:     ai[i] = ai[i-1] + ailen[i-1];
    1935:   }
    1936:   if (mbs) {
    1937:     fshift += imax[mbs-1] - ailen[mbs-1];
    1938:     ai[mbs] = ai[mbs-1] + ailen[mbs-1];
    1939:   }

    1941:   /* reset ilen and imax for each row */
    1942:   a->nonzerorowcnt = 0;
    1943:   for (i=0; i<mbs; i++) {
    1944:     ailen[i] = imax[i] = ai[i+1] - ai[i];
    1945:     a->nonzerorowcnt += ((ai[i+1] - ai[i]) > 0);
    1946:   }
    1947:   a->nz = ai[mbs];

    1949:   /* diagonals may have moved, so kill the diagonal pointers */
    1950:   a->idiagvalid = PETSC_FALSE;
    1951:   if (fshift && a->diag) {
    1952:     PetscFree(a->diag);
    1953:     PetscLogObjectMemory((PetscObject)A,-(mbs+1)*sizeof(PetscInt));
    1954:     a->diag = 0;
    1955:   }
    1956:   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);
    1957:   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);
    1958:   PetscInfo1(A,"Number of mallocs during MatSetValues is %D\n",a->reallocs);
    1959:   PetscInfo1(A,"Most nonzeros blocks in any row is %D\n",rmax);

    1961:   A->info.mallocs    += a->reallocs;
    1962:   a->reallocs         = 0;
    1963:   A->info.nz_unneeded = (PetscReal)fshift*bs2;
    1964:   a->rmax             = rmax;

    1966:   MatCheckCompressedRow(A,a->nonzerorowcnt,&a->compressedrow,a->i,mbs,ratio);
    1967:   return(0);
    1968: }

    1970: /*
    1971:    This function returns an array of flags which indicate the locations of contiguous
    1972:    blocks that should be zeroed. for eg: if bs = 3  and is = [0,1,2,3,5,6,7,8,9]
    1973:    then the resulting sizes = [3,1,1,3,1] correspondig to sets [(0,1,2),(3),(5),(6,7,8),(9)]
    1974:    Assume: sizes should be long enough to hold all the values.
    1975: */
    1978: static PetscErrorCode MatZeroRows_SeqBAIJ_Check_Blocks(PetscInt idx[],PetscInt n,PetscInt bs,PetscInt sizes[], PetscInt *bs_max)
    1979: {
    1980:   PetscInt  i,j,k,row;
    1981:   PetscBool flg;

    1984:   for (i=0,j=0; i<n; j++) {
    1985:     row = idx[i];
    1986:     if (row%bs!=0) { /* Not the begining of a block */
    1987:       sizes[j] = 1;
    1988:       i++;
    1989:     } else if (i+bs > n) { /* complete block doesn't exist (at idx end) */
    1990:       sizes[j] = 1;         /* Also makes sure atleast 'bs' values exist for next else */
    1991:       i++;
    1992:     } else { /* Begining of the block, so check if the complete block exists */
    1993:       flg = PETSC_TRUE;
    1994:       for (k=1; k<bs; k++) {
    1995:         if (row+k != idx[i+k]) { /* break in the block */
    1996:           flg = PETSC_FALSE;
    1997:           break;
    1998:         }
    1999:       }
    2000:       if (flg) { /* No break in the bs */
    2001:         sizes[j] = bs;
    2002:         i       += bs;
    2003:       } else {
    2004:         sizes[j] = 1;
    2005:         i++;
    2006:       }
    2007:     }
    2008:   }
    2009:   *bs_max = j;
    2010:   return(0);
    2011: }

    2015: PetscErrorCode MatZeroRows_SeqBAIJ(Mat A,PetscInt is_n,const PetscInt is_idx[],PetscScalar diag,Vec x, Vec b)
    2016: {
    2017:   Mat_SeqBAIJ       *baij=(Mat_SeqBAIJ*)A->data;
    2018:   PetscErrorCode    ierr;
    2019:   PetscInt          i,j,k,count,*rows;
    2020:   PetscInt          bs=A->rmap->bs,bs2=baij->bs2,*sizes,row,bs_max;
    2021:   PetscScalar       zero = 0.0;
    2022:   MatScalar         *aa;
    2023:   const PetscScalar *xx;
    2024:   PetscScalar       *bb;

    2027:   /* fix right hand side if needed */
    2028:   if (x && b) {
    2029:     VecGetArrayRead(x,&xx);
    2030:     VecGetArray(b,&bb);
    2031:     for (i=0; i<is_n; i++) {
    2032:       bb[is_idx[i]] = diag*xx[is_idx[i]];
    2033:     }
    2034:     VecRestoreArrayRead(x,&xx);
    2035:     VecRestoreArray(b,&bb);
    2036:   }

    2038:   /* Make a copy of the IS and  sort it */
    2039:   /* allocate memory for rows,sizes */
    2040:   PetscMalloc2(is_n,&rows,2*is_n,&sizes);

    2042:   /* copy IS values to rows, and sort them */
    2043:   for (i=0; i<is_n; i++) rows[i] = is_idx[i];
    2044:   PetscSortInt(is_n,rows);

    2046:   if (baij->keepnonzeropattern) {
    2047:     for (i=0; i<is_n; i++) sizes[i] = 1;
    2048:     bs_max          = is_n;
    2049:   } else {
    2050:     MatZeroRows_SeqBAIJ_Check_Blocks(rows,is_n,bs,sizes,&bs_max);
    2051:     A->nonzerostate++;
    2052:   }

    2054:   for (i=0,j=0; i<bs_max; j+=sizes[i],i++) {
    2055:     row = rows[j];
    2056:     if (row < 0 || row > A->rmap->N) SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"row %D out of range",row);
    2057:     count = (baij->i[row/bs +1] - baij->i[row/bs])*bs;
    2058:     aa    = ((MatScalar*)(baij->a)) + baij->i[row/bs]*bs2 + (row%bs);
    2059:     if (sizes[i] == bs && !baij->keepnonzeropattern) {
    2060:       if (diag != (PetscScalar)0.0) {
    2061:         if (baij->ilen[row/bs] > 0) {
    2062:           baij->ilen[row/bs]       = 1;
    2063:           baij->j[baij->i[row/bs]] = row/bs;

    2065:           PetscMemzero(aa,count*bs*sizeof(MatScalar));
    2066:         }
    2067:         /* Now insert all the diagonal values for this bs */
    2068:         for (k=0; k<bs; k++) {
    2069:           (*A->ops->setvalues)(A,1,rows+j+k,1,rows+j+k,&diag,INSERT_VALUES);
    2070:         }
    2071:       } else { /* (diag == 0.0) */
    2072:         baij->ilen[row/bs] = 0;
    2073:       } /* end (diag == 0.0) */
    2074:     } else { /* (sizes[i] != bs) */
    2075: #if defined(PETSC_USE_DEBUG)
    2076:       if (sizes[i] != 1) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_PLIB,"Internal Error. Value should be 1");
    2077: #endif
    2078:       for (k=0; k<count; k++) {
    2079:         aa[0] =  zero;
    2080:         aa   += bs;
    2081:       }
    2082:       if (diag != (PetscScalar)0.0) {
    2083:         (*A->ops->setvalues)(A,1,rows+j,1,rows+j,&diag,INSERT_VALUES);
    2084:       }
    2085:     }
    2086:   }

    2088:   PetscFree2(rows,sizes);
    2089:   MatAssemblyEnd_SeqBAIJ(A,MAT_FINAL_ASSEMBLY);
    2090:   return(0);
    2091: }

    2095: PetscErrorCode MatZeroRowsColumns_SeqBAIJ(Mat A,PetscInt is_n,const PetscInt is_idx[],PetscScalar diag,Vec x, Vec b)
    2096: {
    2097:   Mat_SeqBAIJ       *baij=(Mat_SeqBAIJ*)A->data;
    2098:   PetscErrorCode    ierr;
    2099:   PetscInt          i,j,k,count;
    2100:   PetscInt          bs   =A->rmap->bs,bs2=baij->bs2,row,col;
    2101:   PetscScalar       zero = 0.0;
    2102:   MatScalar         *aa;
    2103:   const PetscScalar *xx;
    2104:   PetscScalar       *bb;
    2105:   PetscBool         *zeroed,vecs = PETSC_FALSE;

    2108:   /* fix right hand side if needed */
    2109:   if (x && b) {
    2110:     VecGetArrayRead(x,&xx);
    2111:     VecGetArray(b,&bb);
    2112:     vecs = PETSC_TRUE;
    2113:   }

    2115:   /* zero the columns */
    2116:   PetscCalloc1(A->rmap->n,&zeroed);
    2117:   for (i=0; i<is_n; i++) {
    2118:     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]);
    2119:     zeroed[is_idx[i]] = PETSC_TRUE;
    2120:   }
    2121:   for (i=0; i<A->rmap->N; i++) {
    2122:     if (!zeroed[i]) {
    2123:       row = i/bs;
    2124:       for (j=baij->i[row]; j<baij->i[row+1]; j++) {
    2125:         for (k=0; k<bs; k++) {
    2126:           col = bs*baij->j[j] + k;
    2127:           if (zeroed[col]) {
    2128:             aa = ((MatScalar*)(baij->a)) + j*bs2 + (i%bs) + bs*k;
    2129:             if (vecs) bb[i] -= aa[0]*xx[col];
    2130:             aa[0] = 0.0;
    2131:           }
    2132:         }
    2133:       }
    2134:     } else if (vecs) bb[i] = diag*xx[i];
    2135:   }
    2136:   PetscFree(zeroed);
    2137:   if (vecs) {
    2138:     VecRestoreArrayRead(x,&xx);
    2139:     VecRestoreArray(b,&bb);
    2140:   }

    2142:   /* zero the rows */
    2143:   for (i=0; i<is_n; i++) {
    2144:     row   = is_idx[i];
    2145:     count = (baij->i[row/bs +1] - baij->i[row/bs])*bs;
    2146:     aa    = ((MatScalar*)(baij->a)) + baij->i[row/bs]*bs2 + (row%bs);
    2147:     for (k=0; k<count; k++) {
    2148:       aa[0] =  zero;
    2149:       aa   += bs;
    2150:     }
    2151:     if (diag != (PetscScalar)0.0) {
    2152:       (*A->ops->setvalues)(A,1,&row,1,&row,&diag,INSERT_VALUES);
    2153:     }
    2154:   }
    2155:   MatAssemblyEnd_SeqBAIJ(A,MAT_FINAL_ASSEMBLY);
    2156:   return(0);
    2157: }

    2161: PetscErrorCode MatSetValues_SeqBAIJ(Mat A,PetscInt m,const PetscInt im[],PetscInt n,const PetscInt in[],const PetscScalar v[],InsertMode is)
    2162: {
    2163:   Mat_SeqBAIJ    *a = (Mat_SeqBAIJ*)A->data;
    2164:   PetscInt       *rp,k,low,high,t,ii,row,nrow,i,col,l,rmax,N,lastcol = -1;
    2165:   PetscInt       *imax=a->imax,*ai=a->i,*ailen=a->ilen;
    2166:   PetscInt       *aj  =a->j,nonew=a->nonew,bs=A->rmap->bs,brow,bcol;
    2168:   PetscInt       ridx,cidx,bs2=a->bs2;
    2169:   PetscBool      roworiented=a->roworiented;
    2170:   MatScalar      *ap,value,*aa=a->a,*bap;

    2173:   for (k=0; k<m; k++) { /* loop over added rows */
    2174:     row  = im[k];
    2175:     brow = row/bs;
    2176:     if (row < 0) continue;
    2177: #if defined(PETSC_USE_DEBUG)
    2178:     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);
    2179: #endif
    2180:     rp   = aj + ai[brow];
    2181:     ap   = aa + bs2*ai[brow];
    2182:     rmax = imax[brow];
    2183:     nrow = ailen[brow];
    2184:     low  = 0;
    2185:     high = nrow;
    2186:     for (l=0; l<n; l++) { /* loop over added columns */
    2187:       if (in[l] < 0) continue;
    2188: #if defined(PETSC_USE_DEBUG)
    2189:       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);
    2190: #endif
    2191:       col  = in[l]; bcol = col/bs;
    2192:       ridx = row % bs; cidx = col % bs;
    2193:       if (roworiented) {
    2194:         value = v[l + k*n];
    2195:       } else {
    2196:         value = v[k + l*m];
    2197:       }
    2198:       if (col <= lastcol) low = 0; else high = nrow;
    2199:       lastcol = col;
    2200:       while (high-low > 7) {
    2201:         t = (low+high)/2;
    2202:         if (rp[t] > bcol) high = t;
    2203:         else              low  = t;
    2204:       }
    2205:       for (i=low; i<high; i++) {
    2206:         if (rp[i] > bcol) break;
    2207:         if (rp[i] == bcol) {
    2208:           bap = ap +  bs2*i + bs*cidx + ridx;
    2209:           if (is == ADD_VALUES) *bap += value;
    2210:           else                  *bap  = value;
    2211:           goto noinsert1;
    2212:         }
    2213:       }
    2214:       if (nonew == 1) goto noinsert1;
    2215:       if (nonew == -1) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Inserting a new nonzero (%D, %D) in the matrix", row, col);
    2216:       MatSeqXAIJReallocateAIJ(A,a->mbs,bs2,nrow,brow,bcol,rmax,aa,ai,aj,rp,ap,imax,nonew,MatScalar);
    2217:       N = nrow++ - 1; high++;
    2218:       /* shift up all the later entries in this row */
    2219:       for (ii=N; ii>=i; ii--) {
    2220:         rp[ii+1] = rp[ii];
    2221:         PetscMemcpy(ap+bs2*(ii+1),ap+bs2*(ii),bs2*sizeof(MatScalar));
    2222:       }
    2223:       if (N>=i) {
    2224:         PetscMemzero(ap+bs2*i,bs2*sizeof(MatScalar));
    2225:       }
    2226:       rp[i]                      = bcol;
    2227:       ap[bs2*i + bs*cidx + ridx] = value;
    2228:       a->nz++;
    2229:       A->nonzerostate++;
    2230: noinsert1:;
    2231:       low = i;
    2232:     }
    2233:     ailen[brow] = nrow;
    2234:   }
    2235:   return(0);
    2236: }

    2240: PetscErrorCode MatILUFactor_SeqBAIJ(Mat inA,IS row,IS col,const MatFactorInfo *info)
    2241: {
    2242:   Mat_SeqBAIJ    *a = (Mat_SeqBAIJ*)inA->data;
    2243:   Mat            outA;
    2245:   PetscBool      row_identity,col_identity;

    2248:   if (info->levels != 0) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"Only levels = 0 supported for in-place ILU");
    2249:   ISIdentity(row,&row_identity);
    2250:   ISIdentity(col,&col_identity);
    2251:   if (!row_identity || !col_identity) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONG,"Row and column permutations must be identity for in-place ILU");

    2253:   outA            = inA;
    2254:   inA->factortype = MAT_FACTOR_LU;
    2255:   PetscFree(inA->solvertype);
    2256:   PetscStrallocpy(MATSOLVERPETSC,&inA->solvertype);

    2258:   MatMarkDiagonal_SeqBAIJ(inA);

    2260:   PetscObjectReference((PetscObject)row);
    2261:   ISDestroy(&a->row);
    2262:   a->row = row;
    2263:   PetscObjectReference((PetscObject)col);
    2264:   ISDestroy(&a->col);
    2265:   a->col = col;

    2267:   /* Create the invert permutation so that it can be used in MatLUFactorNumeric() */
    2268:   ISDestroy(&a->icol);
    2269:   ISInvertPermutation(col,PETSC_DECIDE,&a->icol);
    2270:   PetscLogObjectParent((PetscObject)inA,(PetscObject)a->icol);

    2272:   MatSeqBAIJSetNumericFactorization_inplace(inA,(PetscBool)(row_identity && col_identity));
    2273:   if (!a->solve_work) {
    2274:     PetscMalloc1(inA->rmap->N+inA->rmap->bs,&a->solve_work);
    2275:     PetscLogObjectMemory((PetscObject)inA,(inA->rmap->N+inA->rmap->bs)*sizeof(PetscScalar));
    2276:   }
    2277:   MatLUFactorNumeric(outA,inA,info);
    2278:   return(0);
    2279: }

    2283: PetscErrorCode  MatSeqBAIJSetColumnIndices_SeqBAIJ(Mat mat,PetscInt *indices)
    2284: {
    2285:   Mat_SeqBAIJ *baij = (Mat_SeqBAIJ*)mat->data;
    2286:   PetscInt    i,nz,mbs;

    2289:   nz  = baij->maxnz;
    2290:   mbs = baij->mbs;
    2291:   for (i=0; i<nz; i++) {
    2292:     baij->j[i] = indices[i];
    2293:   }
    2294:   baij->nz = nz;
    2295:   for (i=0; i<mbs; i++) {
    2296:     baij->ilen[i] = baij->imax[i];
    2297:   }
    2298:   return(0);
    2299: }

    2303: /*@
    2304:     MatSeqBAIJSetColumnIndices - Set the column indices for all the rows
    2305:        in the matrix.

    2307:   Input Parameters:
    2308: +  mat - the SeqBAIJ matrix
    2309: -  indices - the column indices

    2311:   Level: advanced

    2313:   Notes:
    2314:     This can be called if you have precomputed the nonzero structure of the
    2315:   matrix and want to provide it to the matrix object to improve the performance
    2316:   of the MatSetValues() operation.

    2318:     You MUST have set the correct numbers of nonzeros per row in the call to
    2319:   MatCreateSeqBAIJ(), and the columns indices MUST be sorted.

    2321:     MUST be called before any calls to MatSetValues();

    2323: @*/
    2324: PetscErrorCode  MatSeqBAIJSetColumnIndices(Mat mat,PetscInt *indices)
    2325: {

    2331:   PetscUseMethod(mat,"MatSeqBAIJSetColumnIndices_C",(Mat,PetscInt*),(mat,indices));
    2332:   return(0);
    2333: }

    2337: PetscErrorCode MatGetRowMaxAbs_SeqBAIJ(Mat A,Vec v,PetscInt idx[])
    2338: {
    2339:   Mat_SeqBAIJ    *a = (Mat_SeqBAIJ*)A->data;
    2341:   PetscInt       i,j,n,row,bs,*ai,*aj,mbs;
    2342:   PetscReal      atmp;
    2343:   PetscScalar    *x,zero = 0.0;
    2344:   MatScalar      *aa;
    2345:   PetscInt       ncols,brow,krow,kcol;

    2348:   if (A->factortype) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Not for factored matrix");
    2349:   bs  = A->rmap->bs;
    2350:   aa  = a->a;
    2351:   ai  = a->i;
    2352:   aj  = a->j;
    2353:   mbs = a->mbs;

    2355:   VecSet(v,zero);
    2356:   VecGetArray(v,&x);
    2357:   VecGetLocalSize(v,&n);
    2358:   if (n != A->rmap->N) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"Nonconforming matrix and vector");
    2359:   for (i=0; i<mbs; i++) {
    2360:     ncols = ai[1] - ai[0]; ai++;
    2361:     brow  = bs*i;
    2362:     for (j=0; j<ncols; j++) {
    2363:       for (kcol=0; kcol<bs; kcol++) {
    2364:         for (krow=0; krow<bs; krow++) {
    2365:           atmp = PetscAbsScalar(*aa);aa++;
    2366:           row  = brow + krow;   /* row index */
    2367:           if (PetscAbsScalar(x[row]) < atmp) {x[row] = atmp; if (idx) idx[row] = bs*(*aj) + kcol;}
    2368:         }
    2369:       }
    2370:       aj++;
    2371:     }
    2372:   }
    2373:   VecRestoreArray(v,&x);
    2374:   return(0);
    2375: }

    2379: PetscErrorCode MatCopy_SeqBAIJ(Mat A,Mat B,MatStructure str)
    2380: {

    2384:   /* If the two matrices have the same copy implementation, use fast copy. */
    2385:   if (str == SAME_NONZERO_PATTERN && (A->ops->copy == B->ops->copy)) {
    2386:     Mat_SeqBAIJ *a  = (Mat_SeqBAIJ*)A->data;
    2387:     Mat_SeqBAIJ *b  = (Mat_SeqBAIJ*)B->data;
    2388:     PetscInt    ambs=a->mbs,bmbs=b->mbs,abs=A->rmap->bs,bbs=B->rmap->bs,bs2=abs*abs;

    2390:     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]);
    2391:     if (abs != bbs) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_INCOMP,"Block size A %D and B %D are different",abs,bbs);
    2392:     PetscMemcpy(b->a,a->a,(bs2*a->i[ambs])*sizeof(PetscScalar));
    2393:   } else {
    2394:     MatCopy_Basic(A,B,str);
    2395:   }
    2396:   return(0);
    2397: }

    2401: PetscErrorCode MatSetUp_SeqBAIJ(Mat A)
    2402: {

    2406:   MatSeqBAIJSetPreallocation_SeqBAIJ(A,A->rmap->bs,PETSC_DEFAULT,0);
    2407:   return(0);
    2408: }

    2412: PetscErrorCode MatSeqBAIJGetArray_SeqBAIJ(Mat A,PetscScalar *array[])
    2413: {
    2414:   Mat_SeqBAIJ *a = (Mat_SeqBAIJ*)A->data;

    2417:   *array = a->a;
    2418:   return(0);
    2419: }

    2423: PetscErrorCode MatSeqBAIJRestoreArray_SeqBAIJ(Mat A,PetscScalar *array[])
    2424: {
    2426:   return(0);
    2427: }

    2431: PetscErrorCode MatAXPYGetPreallocation_SeqBAIJ(Mat Y,Mat X,PetscInt *nnz)
    2432: {
    2433:   PetscInt       bs = Y->rmap->bs,mbs = Y->rmap->N/bs;
    2434:   Mat_SeqBAIJ    *x = (Mat_SeqBAIJ*)X->data;
    2435:   Mat_SeqBAIJ    *y = (Mat_SeqBAIJ*)Y->data;

    2439:   /* Set the number of nonzeros in the new matrix */
    2440:   MatAXPYGetPreallocation_SeqX_private(mbs,x->i,x->j,y->i,y->j,nnz);
    2441:   return(0);
    2442: }

    2446: PetscErrorCode MatAXPY_SeqBAIJ(Mat Y,PetscScalar a,Mat X,MatStructure str)
    2447: {
    2448:   Mat_SeqBAIJ    *x = (Mat_SeqBAIJ*)X->data,*y = (Mat_SeqBAIJ*)Y->data;
    2450:   PetscInt       bs=Y->rmap->bs,bs2=bs*bs;
    2451:   PetscBLASInt   one=1;

    2454:   if (str == SAME_NONZERO_PATTERN) {
    2455:     PetscScalar  alpha = a;
    2456:     PetscBLASInt bnz;
    2457:     PetscBLASIntCast(x->nz*bs2,&bnz);
    2458:     PetscStackCallBLAS("BLASaxpy",BLASaxpy_(&bnz,&alpha,x->a,&one,y->a,&one));
    2459:     PetscObjectStateIncrease((PetscObject)Y);
    2460:   } else if (str == SUBSET_NONZERO_PATTERN) { /* nonzeros of X is a subset of Y's */
    2461:     MatAXPY_Basic(Y,a,X,str);
    2462:   } else {
    2463:     Mat      B;
    2464:     PetscInt *nnz;
    2465:     if (bs != X->rmap->bs) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"Matrices must have same block size");
    2466:     PetscMalloc1(Y->rmap->N,&nnz);
    2467:     MatCreate(PetscObjectComm((PetscObject)Y),&B);
    2468:     PetscObjectSetName((PetscObject)B,((PetscObject)Y)->name);
    2469:     MatSetSizes(B,Y->rmap->n,Y->cmap->n,Y->rmap->N,Y->cmap->N);
    2470:     MatSetBlockSizesFromMats(B,Y,Y);
    2471:     MatSetType(B,(MatType) ((PetscObject)Y)->type_name);
    2472:     MatAXPYGetPreallocation_SeqBAIJ(Y,X,nnz);
    2473:     MatSeqBAIJSetPreallocation(B,bs,0,nnz);
    2474:     MatAXPY_BasicWithPreallocation(B,Y,a,X,str);
    2475:     MatHeaderReplace(Y,&B);
    2476:     PetscFree(nnz);
    2477:   }
    2478:   return(0);
    2479: }

    2483: PetscErrorCode MatRealPart_SeqBAIJ(Mat A)
    2484: {
    2485:   Mat_SeqBAIJ *a = (Mat_SeqBAIJ*)A->data;
    2486:   PetscInt    i,nz = a->bs2*a->i[a->mbs];
    2487:   MatScalar   *aa = a->a;

    2490:   for (i=0; i<nz; i++) aa[i] = PetscRealPart(aa[i]);
    2491:   return(0);
    2492: }

    2496: PetscErrorCode MatImaginaryPart_SeqBAIJ(Mat A)
    2497: {
    2498:   Mat_SeqBAIJ *a = (Mat_SeqBAIJ*)A->data;
    2499:   PetscInt    i,nz = a->bs2*a->i[a->mbs];
    2500:   MatScalar   *aa = a->a;

    2503:   for (i=0; i<nz; i++) aa[i] = PetscImaginaryPart(aa[i]);
    2504:   return(0);
    2505: }

    2509: /*
    2510:     Code almost idential to MatGetColumnIJ_SeqAIJ() should share common code
    2511: */
    2512: PetscErrorCode MatGetColumnIJ_SeqBAIJ(Mat A,PetscInt oshift,PetscBool symmetric,PetscBool inodecompressed,PetscInt *nn,const PetscInt *ia[],const PetscInt *ja[],PetscBool  *done)
    2513: {
    2514:   Mat_SeqBAIJ    *a = (Mat_SeqBAIJ*)A->data;
    2516:   PetscInt       bs = A->rmap->bs,i,*collengths,*cia,*cja,n = A->cmap->n/bs,m = A->rmap->n/bs;
    2517:   PetscInt       nz = a->i[m],row,*jj,mr,col;

    2520:   *nn = n;
    2521:   if (!ia) return(0);
    2522:   if (symmetric) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"Not for BAIJ matrices");
    2523:   else {
    2524:     PetscCalloc1(n+1,&collengths);
    2525:     PetscMalloc1(n+1,&cia);
    2526:     PetscMalloc1(nz+1,&cja);
    2527:     jj   = a->j;
    2528:     for (i=0; i<nz; i++) {
    2529:       collengths[jj[i]]++;
    2530:     }
    2531:     cia[0] = oshift;
    2532:     for (i=0; i<n; i++) {
    2533:       cia[i+1] = cia[i] + collengths[i];
    2534:     }
    2535:     PetscMemzero(collengths,n*sizeof(PetscInt));
    2536:     jj   = a->j;
    2537:     for (row=0; row<m; row++) {
    2538:       mr = a->i[row+1] - a->i[row];
    2539:       for (i=0; i<mr; i++) {
    2540:         col = *jj++;

    2542:         cja[cia[col] + collengths[col]++ - oshift] = row + oshift;
    2543:       }
    2544:     }
    2545:     PetscFree(collengths);
    2546:     *ia  = cia; *ja = cja;
    2547:   }
    2548:   return(0);
    2549: }

    2553: PetscErrorCode MatRestoreColumnIJ_SeqBAIJ(Mat A,PetscInt oshift,PetscBool symmetric,PetscBool inodecompressed,PetscInt *n,const PetscInt *ia[],const PetscInt *ja[],PetscBool  *done)
    2554: {

    2558:   if (!ia) return(0);
    2559:   PetscFree(*ia);
    2560:   PetscFree(*ja);
    2561:   return(0);
    2562: }

    2564: /*
    2565:  MatGetColumnIJ_SeqBAIJ_Color() and MatRestoreColumnIJ_SeqBAIJ_Color() are customized from
    2566:  MatGetColumnIJ_SeqBAIJ() and MatRestoreColumnIJ_SeqBAIJ() by adding an output
    2567:  spidx[], index of a->a, to be used in MatTransposeColoringCreate() and MatFDColoringCreate()
    2568:  */
    2571: PetscErrorCode MatGetColumnIJ_SeqBAIJ_Color(Mat A,PetscInt oshift,PetscBool symmetric,PetscBool inodecompressed,PetscInt *nn,const PetscInt *ia[],const PetscInt *ja[],PetscInt *spidx[],PetscBool  *done)
    2572: {
    2573:   Mat_SeqBAIJ    *a = (Mat_SeqBAIJ*)A->data;
    2575:   PetscInt       i,*collengths,*cia,*cja,n=a->nbs,m=a->mbs;
    2576:   PetscInt       nz = a->i[m],row,*jj,mr,col;
    2577:   PetscInt       *cspidx;

    2580:   *nn = n;
    2581:   if (!ia) return(0);

    2583:   PetscCalloc1(n+1,&collengths);
    2584:   PetscMalloc1(n+1,&cia);
    2585:   PetscMalloc1(nz+1,&cja);
    2586:   PetscMalloc1(nz+1,&cspidx);
    2587:   jj   = a->j;
    2588:   for (i=0; i<nz; i++) {
    2589:     collengths[jj[i]]++;
    2590:   }
    2591:   cia[0] = oshift;
    2592:   for (i=0; i<n; i++) {
    2593:     cia[i+1] = cia[i] + collengths[i];
    2594:   }
    2595:   PetscMemzero(collengths,n*sizeof(PetscInt));
    2596:   jj   = a->j;
    2597:   for (row=0; row<m; row++) {
    2598:     mr = a->i[row+1] - a->i[row];
    2599:     for (i=0; i<mr; i++) {
    2600:       col = *jj++;
    2601:       cspidx[cia[col] + collengths[col] - oshift] = a->i[row] + i; /* index of a->j */
    2602:       cja[cia[col] + collengths[col]++ - oshift]  = row + oshift;
    2603:     }
    2604:   }
    2605:   PetscFree(collengths);
    2606:   *ia    = cia; *ja = cja;
    2607:   *spidx = cspidx;
    2608:   return(0);
    2609: }

    2613: PetscErrorCode MatRestoreColumnIJ_SeqBAIJ_Color(Mat A,PetscInt oshift,PetscBool symmetric,PetscBool inodecompressed,PetscInt *n,const PetscInt *ia[],const PetscInt *ja[],PetscInt *spidx[],PetscBool  *done)
    2614: {

    2618:   MatRestoreColumnIJ_SeqBAIJ(A,oshift,symmetric,inodecompressed,n,ia,ja,done);
    2619:   PetscFree(*spidx);
    2620:   return(0);
    2621: }

    2625: PetscErrorCode MatShift_SeqBAIJ(Mat Y,PetscScalar a)
    2626: {
    2628:   Mat_SeqBAIJ     *aij = (Mat_SeqBAIJ*)Y->data;

    2631:   if (!Y->preallocated || !aij->nz) {
    2632:     MatSeqBAIJSetPreallocation(Y,Y->rmap->bs,1,NULL);
    2633:   }
    2634:   MatShift_Basic(Y,a);
    2635:   return(0);
    2636: }

    2638: /* -------------------------------------------------------------------*/
    2639: static struct _MatOps MatOps_Values = {MatSetValues_SeqBAIJ,
    2640:                                        MatGetRow_SeqBAIJ,
    2641:                                        MatRestoreRow_SeqBAIJ,
    2642:                                        MatMult_SeqBAIJ_N,
    2643:                                /* 4*/  MatMultAdd_SeqBAIJ_N,
    2644:                                        MatMultTranspose_SeqBAIJ,
    2645:                                        MatMultTransposeAdd_SeqBAIJ,
    2646:                                        0,
    2647:                                        0,
    2648:                                        0,
    2649:                                /* 10*/ 0,
    2650:                                        MatLUFactor_SeqBAIJ,
    2651:                                        0,
    2652:                                        0,
    2653:                                        MatTranspose_SeqBAIJ,
    2654:                                /* 15*/ MatGetInfo_SeqBAIJ,
    2655:                                        MatEqual_SeqBAIJ,
    2656:                                        MatGetDiagonal_SeqBAIJ,
    2657:                                        MatDiagonalScale_SeqBAIJ,
    2658:                                        MatNorm_SeqBAIJ,
    2659:                                /* 20*/ 0,
    2660:                                        MatAssemblyEnd_SeqBAIJ,
    2661:                                        MatSetOption_SeqBAIJ,
    2662:                                        MatZeroEntries_SeqBAIJ,
    2663:                                /* 24*/ MatZeroRows_SeqBAIJ,
    2664:                                        0,
    2665:                                        0,
    2666:                                        0,
    2667:                                        0,
    2668:                                /* 29*/ MatSetUp_SeqBAIJ,
    2669:                                        0,
    2670:                                        0,
    2671:                                        0,
    2672:                                        0,
    2673:                                /* 34*/ MatDuplicate_SeqBAIJ,
    2674:                                        0,
    2675:                                        0,
    2676:                                        MatILUFactor_SeqBAIJ,
    2677:                                        0,
    2678:                                /* 39*/ MatAXPY_SeqBAIJ,
    2679:                                        MatGetSubMatrices_SeqBAIJ,
    2680:                                        MatIncreaseOverlap_SeqBAIJ,
    2681:                                        MatGetValues_SeqBAIJ,
    2682:                                        MatCopy_SeqBAIJ,
    2683:                                /* 44*/ 0,
    2684:                                        MatScale_SeqBAIJ,
    2685:                                        MatShift_SeqBAIJ,
    2686:                                        0,
    2687:                                        MatZeroRowsColumns_SeqBAIJ,
    2688:                                /* 49*/ 0,
    2689:                                        MatGetRowIJ_SeqBAIJ,
    2690:                                        MatRestoreRowIJ_SeqBAIJ,
    2691:                                        MatGetColumnIJ_SeqBAIJ,
    2692:                                        MatRestoreColumnIJ_SeqBAIJ,
    2693:                                /* 54*/ MatFDColoringCreate_SeqXAIJ,
    2694:                                        0,
    2695:                                        0,
    2696:                                        0,
    2697:                                        MatSetValuesBlocked_SeqBAIJ,
    2698:                                /* 59*/ MatGetSubMatrix_SeqBAIJ,
    2699:                                        MatDestroy_SeqBAIJ,
    2700:                                        MatView_SeqBAIJ,
    2701:                                        0,
    2702:                                        0,
    2703:                                /* 64*/ 0,
    2704:                                        0,
    2705:                                        0,
    2706:                                        0,
    2707:                                        0,
    2708:                                /* 69*/ MatGetRowMaxAbs_SeqBAIJ,
    2709:                                        0,
    2710:                                        MatConvert_Basic,
    2711:                                        0,
    2712:                                        0,
    2713:                                /* 74*/ 0,
    2714:                                        MatFDColoringApply_BAIJ,
    2715:                                        0,
    2716:                                        0,
    2717:                                        0,
    2718:                                /* 79*/ 0,
    2719:                                        0,
    2720:                                        0,
    2721:                                        0,
    2722:                                        MatLoad_SeqBAIJ,
    2723:                                /* 84*/ 0,
    2724:                                        0,
    2725:                                        0,
    2726:                                        0,
    2727:                                        0,
    2728:                                /* 89*/ 0,
    2729:                                        0,
    2730:                                        0,
    2731:                                        0,
    2732:                                        0,
    2733:                                /* 94*/ 0,
    2734:                                        0,
    2735:                                        0,
    2736:                                        0,
    2737:                                        0,
    2738:                                /* 99*/ 0,
    2739:                                        0,
    2740:                                        0,
    2741:                                        0,
    2742:                                        0,
    2743:                                /*104*/ 0,
    2744:                                        MatRealPart_SeqBAIJ,
    2745:                                        MatImaginaryPart_SeqBAIJ,
    2746:                                        0,
    2747:                                        0,
    2748:                                /*109*/ 0,
    2749:                                        0,
    2750:                                        0,
    2751:                                        0,
    2752:                                        MatMissingDiagonal_SeqBAIJ,
    2753:                                /*114*/ 0,
    2754:                                        0,
    2755:                                        0,
    2756:                                        0,
    2757:                                        0,
    2758:                                /*119*/ 0,
    2759:                                        0,
    2760:                                        MatMultHermitianTranspose_SeqBAIJ,
    2761:                                        MatMultHermitianTransposeAdd_SeqBAIJ,
    2762:                                        0,
    2763:                                /*124*/ 0,
    2764:                                        0,
    2765:                                        MatInvertBlockDiagonal_SeqBAIJ,
    2766:                                        0,
    2767:                                        0,
    2768:                                /*129*/ 0,
    2769:                                        0,
    2770:                                        0,
    2771:                                        0,
    2772:                                        0,
    2773:                                /*134*/ 0,
    2774:                                        0,
    2775:                                        0,
    2776:                                        0,
    2777:                                        0,
    2778:                                /*139*/ 0,
    2779:                                        0,
    2780:                                        0,
    2781:                                        MatFDColoringSetUp_SeqXAIJ,
    2782:                                        0,
    2783:                                 /*144*/MatCreateMPIMatConcatenateSeqMat_SeqBAIJ
    2784: };

    2788: PetscErrorCode  MatStoreValues_SeqBAIJ(Mat mat)
    2789: {
    2790:   Mat_SeqBAIJ    *aij = (Mat_SeqBAIJ*)mat->data;
    2791:   PetscInt       nz   = aij->i[aij->mbs]*aij->bs2;

    2795:   if (aij->nonew != 1) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ORDER,"Must call MatSetOption(A,MAT_NEW_NONZERO_LOCATIONS,PETSC_FALSE);first");

    2797:   /* allocate space for values if not already there */
    2798:   if (!aij->saved_values) {
    2799:     PetscMalloc1(nz+1,&aij->saved_values);
    2800:     PetscLogObjectMemory((PetscObject)mat,(nz+1)*sizeof(PetscScalar));
    2801:   }

    2803:   /* copy values over */
    2804:   PetscMemcpy(aij->saved_values,aij->a,nz*sizeof(PetscScalar));
    2805:   return(0);
    2806: }

    2810: PetscErrorCode  MatRetrieveValues_SeqBAIJ(Mat mat)
    2811: {
    2812:   Mat_SeqBAIJ    *aij = (Mat_SeqBAIJ*)mat->data;
    2814:   PetscInt       nz = aij->i[aij->mbs]*aij->bs2;

    2817:   if (aij->nonew != 1) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ORDER,"Must call MatSetOption(A,MAT_NEW_NONZERO_LOCATIONS,PETSC_FALSE);first");
    2818:   if (!aij->saved_values) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ORDER,"Must call MatStoreValues(A);first");

    2820:   /* copy values over */
    2821:   PetscMemcpy(aij->a,aij->saved_values,nz*sizeof(PetscScalar));
    2822:   return(0);
    2823: }

    2825: PETSC_INTERN PetscErrorCode MatConvert_SeqBAIJ_SeqAIJ(Mat, MatType,MatReuse,Mat*);
    2826: PETSC_INTERN PetscErrorCode MatConvert_SeqBAIJ_SeqSBAIJ(Mat, MatType,MatReuse,Mat*);

    2830: PetscErrorCode  MatSeqBAIJSetPreallocation_SeqBAIJ(Mat B,PetscInt bs,PetscInt nz,PetscInt *nnz)
    2831: {
    2832:   Mat_SeqBAIJ    *b;
    2834:   PetscInt       i,mbs,nbs,bs2;
    2835:   PetscBool      flg = PETSC_FALSE,skipallocation = PETSC_FALSE,realalloc = PETSC_FALSE;

    2838:   if (nz >= 0 || nnz) realalloc = PETSC_TRUE;
    2839:   if (nz == MAT_SKIP_ALLOCATION) {
    2840:     skipallocation = PETSC_TRUE;
    2841:     nz             = 0;
    2842:   }

    2844:   MatSetBlockSize(B,PetscAbs(bs));
    2845:   PetscLayoutSetUp(B->rmap);
    2846:   PetscLayoutSetUp(B->cmap);
    2847:   PetscLayoutGetBlockSize(B->rmap,&bs);

    2849:   B->preallocated = PETSC_TRUE;

    2851:   mbs = B->rmap->n/bs;
    2852:   nbs = B->cmap->n/bs;
    2853:   bs2 = bs*bs;

    2855:   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);

    2857:   if (nz == PETSC_DEFAULT || nz == PETSC_DECIDE) nz = 5;
    2858:   if (nz < 0) SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"nz cannot be less than 0: value %D",nz);
    2859:   if (nnz) {
    2860:     for (i=0; i<mbs; i++) {
    2861:       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]);
    2862:       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);
    2863:     }
    2864:   }

    2866:   b    = (Mat_SeqBAIJ*)B->data;
    2867:   PetscOptionsBegin(PetscObjectComm((PetscObject)B),NULL,"Optimize options for SEQBAIJ matrix 2 ","Mat");
    2868:   PetscOptionsBool("-mat_no_unroll","Do not optimize for block size (slow)",NULL,flg,&flg,NULL);
    2869:   PetscOptionsEnd();

    2871:   if (!flg) {
    2872:     switch (bs) {
    2873:     case 1:
    2874:       B->ops->mult    = MatMult_SeqBAIJ_1;
    2875:       B->ops->multadd = MatMultAdd_SeqBAIJ_1;
    2876:       break;
    2877:     case 2:
    2878:       B->ops->mult    = MatMult_SeqBAIJ_2;
    2879:       B->ops->multadd = MatMultAdd_SeqBAIJ_2;
    2880:       break;
    2881:     case 3:
    2882:       B->ops->mult    = MatMult_SeqBAIJ_3;
    2883:       B->ops->multadd = MatMultAdd_SeqBAIJ_3;
    2884:       break;
    2885:     case 4:
    2886:       B->ops->mult    = MatMult_SeqBAIJ_4;
    2887:       B->ops->multadd = MatMultAdd_SeqBAIJ_4;
    2888:       break;
    2889:     case 5:
    2890:       B->ops->mult    = MatMult_SeqBAIJ_5;
    2891:       B->ops->multadd = MatMultAdd_SeqBAIJ_5;
    2892:       break;
    2893:     case 6:
    2894:       B->ops->mult    = MatMult_SeqBAIJ_6;
    2895:       B->ops->multadd = MatMultAdd_SeqBAIJ_6;
    2896:       break;
    2897:     case 7:
    2898:       B->ops->mult    = MatMult_SeqBAIJ_7;
    2899:       B->ops->multadd = MatMultAdd_SeqBAIJ_7;
    2900:       break;
    2901:     case 15:
    2902:       B->ops->mult    = MatMult_SeqBAIJ_15_ver1;
    2903:       B->ops->multadd = MatMultAdd_SeqBAIJ_N;
    2904:       break;
    2905:     default:
    2906:       B->ops->mult    = MatMult_SeqBAIJ_N;
    2907:       B->ops->multadd = MatMultAdd_SeqBAIJ_N;
    2908:       break;
    2909:     }
    2910:   }
    2911:   B->ops->sor = MatSOR_SeqBAIJ;
    2912:   b->mbs = mbs;
    2913:   b->nbs = nbs;
    2914:   if (!skipallocation) {
    2915:     if (!b->imax) {
    2916:       PetscMalloc2(mbs,&b->imax,mbs,&b->ilen);
    2917:       PetscLogObjectMemory((PetscObject)B,2*mbs*sizeof(PetscInt));

    2919:       b->free_imax_ilen = PETSC_TRUE;
    2920:     }
    2921:     /* b->ilen will count nonzeros in each block row so far. */
    2922:     for (i=0; i<mbs; i++) b->ilen[i] = 0;
    2923:     if (!nnz) {
    2924:       if (nz == PETSC_DEFAULT || nz == PETSC_DECIDE) nz = 5;
    2925:       else if (nz < 0) nz = 1;
    2926:       for (i=0; i<mbs; i++) b->imax[i] = nz;
    2927:       nz = nz*mbs;
    2928:     } else {
    2929:       nz = 0;
    2930:       for (i=0; i<mbs; i++) {b->imax[i] = nnz[i]; nz += nnz[i];}
    2931:     }

    2933:     /* allocate the matrix space */
    2934:     MatSeqXAIJFreeAIJ(B,&b->a,&b->j,&b->i);
    2935:     PetscMalloc3(bs2*nz,&b->a,nz,&b->j,B->rmap->N+1,&b->i);
    2936:     PetscLogObjectMemory((PetscObject)B,(B->rmap->N+1)*sizeof(PetscInt)+nz*(bs2*sizeof(PetscScalar)+sizeof(PetscInt)));
    2937:     PetscMemzero(b->a,nz*bs2*sizeof(MatScalar));
    2938:     PetscMemzero(b->j,nz*sizeof(PetscInt));

    2940:     b->singlemalloc = PETSC_TRUE;
    2941:     b->i[0]         = 0;
    2942:     for (i=1; i<mbs+1; i++) {
    2943:       b->i[i] = b->i[i-1] + b->imax[i-1];
    2944:     }
    2945:     b->free_a  = PETSC_TRUE;
    2946:     b->free_ij = PETSC_TRUE;
    2947:   } else {
    2948:     b->free_a  = PETSC_FALSE;
    2949:     b->free_ij = PETSC_FALSE;
    2950:   }

    2952:   b->bs2              = bs2;
    2953:   b->mbs              = mbs;
    2954:   b->nz               = 0;
    2955:   b->maxnz            = nz;
    2956:   B->info.nz_unneeded = (PetscReal)b->maxnz*bs2;
    2957:   if (realalloc) {MatSetOption(B,MAT_NEW_NONZERO_ALLOCATION_ERR,PETSC_TRUE);}
    2958:   return(0);
    2959: }

    2963: PetscErrorCode MatSeqBAIJSetPreallocationCSR_SeqBAIJ(Mat B,PetscInt bs,const PetscInt ii[],const PetscInt jj[],const PetscScalar V[])
    2964: {
    2965:   PetscInt       i,m,nz,nz_max=0,*nnz;
    2966:   PetscScalar    *values=0;
    2967:   PetscBool      roworiented = ((Mat_SeqBAIJ*)B->data)->roworiented;

    2971:   if (bs < 1) SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Invalid block size specified, must be positive but it is %D",bs);
    2972:   PetscLayoutSetBlockSize(B->rmap,bs);
    2973:   PetscLayoutSetBlockSize(B->cmap,bs);
    2974:   PetscLayoutSetUp(B->rmap);
    2975:   PetscLayoutSetUp(B->cmap);
    2976:   PetscLayoutGetBlockSize(B->rmap,&bs);
    2977:   m    = B->rmap->n/bs;

    2979:   if (ii[0] != 0) SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE, "ii[0] must be 0 but it is %D",ii[0]);
    2980:   PetscMalloc1(m+1, &nnz);
    2981:   for (i=0; i<m; i++) {
    2982:     nz = ii[i+1]- ii[i];
    2983:     if (nz < 0) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE, "Local row %D has a negative number of columns %D",i,nz);
    2984:     nz_max = PetscMax(nz_max, nz);
    2985:     nnz[i] = nz;
    2986:   }
    2987:   MatSeqBAIJSetPreallocation(B,bs,0,nnz);
    2988:   PetscFree(nnz);

    2990:   values = (PetscScalar*)V;
    2991:   if (!values) {
    2992:     PetscCalloc1(bs*bs*(nz_max+1),&values);
    2993:   }
    2994:   for (i=0; i<m; i++) {
    2995:     PetscInt          ncols  = ii[i+1] - ii[i];
    2996:     const PetscInt    *icols = jj + ii[i];
    2997:     const PetscScalar *svals = values + (V ? (bs*bs*ii[i]) : 0);
    2998:     if (!roworiented) {
    2999:       MatSetValuesBlocked_SeqBAIJ(B,1,&i,ncols,icols,svals,INSERT_VALUES);
    3000:     } else {
    3001:       PetscInt j;
    3002:       for (j=0; j<ncols; j++) {
    3003:         const PetscScalar *svals = values + (V ? (bs*bs*(ii[i]+j)) : 0);
    3004:         MatSetValuesBlocked_SeqBAIJ(B,1,&i,1,&icols[j],svals,INSERT_VALUES);
    3005:       }
    3006:     }
    3007:   }
    3008:   if (!V) { PetscFree(values); }
    3009:   MatAssemblyBegin(B,MAT_FINAL_ASSEMBLY);
    3010:   MatAssemblyEnd(B,MAT_FINAL_ASSEMBLY);
    3011:   MatSetOption(B,MAT_NEW_NONZERO_LOCATION_ERR,PETSC_TRUE);
    3012:   return(0);
    3013: }

    3015: /*MC
    3016:    MATSEQBAIJ - MATSEQBAIJ = "seqbaij" - A matrix type to be used for sequential block sparse matrices, based on
    3017:    block sparse compressed row format.

    3019:    Options Database Keys:
    3020: . -mat_type seqbaij - sets the matrix type to "seqbaij" during a call to MatSetFromOptions()

    3022:   Level: beginner

    3024: .seealso: MatCreateSeqBAIJ()
    3025: M*/

    3027: PETSC_INTERN PetscErrorCode MatConvert_SeqBAIJ_SeqBSTRM(Mat, MatType,MatReuse,Mat*);

    3031: PETSC_EXTERN PetscErrorCode MatCreate_SeqBAIJ(Mat B)
    3032: {
    3034:   PetscMPIInt    size;
    3035:   Mat_SeqBAIJ    *b;

    3038:   MPI_Comm_size(PetscObjectComm((PetscObject)B),&size);
    3039:   if (size > 1) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONG,"Comm must be of size 1");

    3041:   PetscNewLog(B,&b);
    3042:   B->data = (void*)b;
    3043:   PetscMemcpy(B->ops,&MatOps_Values,sizeof(struct _MatOps));

    3045:   b->row          = 0;
    3046:   b->col          = 0;
    3047:   b->icol         = 0;
    3048:   b->reallocs     = 0;
    3049:   b->saved_values = 0;

    3051:   b->roworiented        = PETSC_TRUE;
    3052:   b->nonew              = 0;
    3053:   b->diag               = 0;
    3054:   B->spptr              = 0;
    3055:   B->info.nz_unneeded   = (PetscReal)b->maxnz*b->bs2;
    3056:   b->keepnonzeropattern = PETSC_FALSE;

    3058:   PetscObjectComposeFunction((PetscObject)B,"MatInvertBlockDiagonal_C",MatInvertBlockDiagonal_SeqBAIJ);
    3059:   PetscObjectComposeFunction((PetscObject)B,"MatStoreValues_C",MatStoreValues_SeqBAIJ);
    3060:   PetscObjectComposeFunction((PetscObject)B,"MatRetrieveValues_C",MatRetrieveValues_SeqBAIJ);
    3061:   PetscObjectComposeFunction((PetscObject)B,"MatSeqBAIJSetColumnIndices_C",MatSeqBAIJSetColumnIndices_SeqBAIJ);
    3062:   PetscObjectComposeFunction((PetscObject)B,"MatConvert_seqbaij_seqaij_C",MatConvert_SeqBAIJ_SeqAIJ);
    3063:   PetscObjectComposeFunction((PetscObject)B,"MatConvert_seqbaij_seqsbaij_C",MatConvert_SeqBAIJ_SeqSBAIJ);
    3064:   PetscObjectComposeFunction((PetscObject)B,"MatSeqBAIJSetPreallocation_C",MatSeqBAIJSetPreallocation_SeqBAIJ);
    3065:   PetscObjectComposeFunction((PetscObject)B,"MatSeqBAIJSetPreallocationCSR_C",MatSeqBAIJSetPreallocationCSR_SeqBAIJ);
    3066:   PetscObjectComposeFunction((PetscObject)B,"MatConvert_seqbaij_seqbstrm_C",MatConvert_SeqBAIJ_SeqBSTRM);
    3067:   PetscObjectComposeFunction((PetscObject)B,"MatIsTranspose_C",MatIsTranspose_SeqBAIJ);
    3068:   PetscObjectChangeTypeName((PetscObject)B,MATSEQBAIJ);
    3069:   return(0);
    3070: }

    3074: PetscErrorCode MatDuplicateNoCreate_SeqBAIJ(Mat C,Mat A,MatDuplicateOption cpvalues,PetscBool mallocmatspace)
    3075: {
    3076:   Mat_SeqBAIJ    *c = (Mat_SeqBAIJ*)C->data,*a = (Mat_SeqBAIJ*)A->data;
    3078:   PetscInt       i,mbs = a->mbs,nz = a->nz,bs2 = a->bs2;

    3081:   if (a->i[mbs] != nz) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_PLIB,"Corrupt matrix");

    3083:   if (cpvalues == MAT_SHARE_NONZERO_PATTERN) {
    3084:     c->imax           = a->imax;
    3085:     c->ilen           = a->ilen;
    3086:     c->free_imax_ilen = PETSC_FALSE;
    3087:   } else {
    3088:     PetscMalloc2(mbs,&c->imax,mbs,&c->ilen);
    3089:     PetscLogObjectMemory((PetscObject)C,2*mbs*sizeof(PetscInt));
    3090:     for (i=0; i<mbs; i++) {
    3091:       c->imax[i] = a->imax[i];
    3092:       c->ilen[i] = a->ilen[i];
    3093:     }
    3094:     c->free_imax_ilen = PETSC_TRUE;
    3095:   }

    3097:   /* allocate the matrix space */
    3098:   if (mallocmatspace) {
    3099:     if (cpvalues == MAT_SHARE_NONZERO_PATTERN) {
    3100:       PetscCalloc1(bs2*nz,&c->a);
    3101:       PetscLogObjectMemory((PetscObject)C,a->i[mbs]*bs2*sizeof(PetscScalar));

    3103:       c->i            = a->i;
    3104:       c->j            = a->j;
    3105:       c->singlemalloc = PETSC_FALSE;
    3106:       c->free_a       = PETSC_TRUE;
    3107:       c->free_ij      = PETSC_FALSE;
    3108:       c->parent       = A;
    3109:       C->preallocated = PETSC_TRUE;
    3110:       C->assembled    = PETSC_TRUE;

    3112:       PetscObjectReference((PetscObject)A);
    3113:       MatSetOption(A,MAT_NEW_NONZERO_LOCATION_ERR,PETSC_TRUE);
    3114:       MatSetOption(C,MAT_NEW_NONZERO_LOCATION_ERR,PETSC_TRUE);
    3115:     } else {
    3116:       PetscMalloc3(bs2*nz,&c->a,nz,&c->j,mbs+1,&c->i);
    3117:       PetscLogObjectMemory((PetscObject)C,a->i[mbs]*(bs2*sizeof(PetscScalar)+sizeof(PetscInt))+(mbs+1)*sizeof(PetscInt));

    3119:       c->singlemalloc = PETSC_TRUE;
    3120:       c->free_a       = PETSC_TRUE;
    3121:       c->free_ij      = PETSC_TRUE;

    3123:       PetscMemcpy(c->i,a->i,(mbs+1)*sizeof(PetscInt));
    3124:       if (mbs > 0) {
    3125:         PetscMemcpy(c->j,a->j,nz*sizeof(PetscInt));
    3126:         if (cpvalues == MAT_COPY_VALUES) {
    3127:           PetscMemcpy(c->a,a->a,bs2*nz*sizeof(MatScalar));
    3128:         } else {
    3129:           PetscMemzero(c->a,bs2*nz*sizeof(MatScalar));
    3130:         }
    3131:       }
    3132:       C->preallocated = PETSC_TRUE;
    3133:       C->assembled    = PETSC_TRUE;
    3134:     }
    3135:   }

    3137:   c->roworiented = a->roworiented;
    3138:   c->nonew       = a->nonew;

    3140:   PetscLayoutReference(A->rmap,&C->rmap);
    3141:   PetscLayoutReference(A->cmap,&C->cmap);

    3143:   c->bs2         = a->bs2;
    3144:   c->mbs         = a->mbs;
    3145:   c->nbs         = a->nbs;

    3147:   if (a->diag) {
    3148:     if (cpvalues == MAT_SHARE_NONZERO_PATTERN) {
    3149:       c->diag      = a->diag;
    3150:       c->free_diag = PETSC_FALSE;
    3151:     } else {
    3152:       PetscMalloc1(mbs+1,&c->diag);
    3153:       PetscLogObjectMemory((PetscObject)C,(mbs+1)*sizeof(PetscInt));
    3154:       for (i=0; i<mbs; i++) c->diag[i] = a->diag[i];
    3155:       c->free_diag = PETSC_TRUE;
    3156:     }
    3157:   } else c->diag = 0;

    3159:   c->nz         = a->nz;
    3160:   c->maxnz      = a->nz;         /* Since we allocate exactly the right amount */
    3161:   c->solve_work = NULL;
    3162:   c->mult_work  = NULL;
    3163:   c->sor_workt  = NULL;
    3164:   c->sor_work   = NULL;

    3166:   c->compressedrow.use   = a->compressedrow.use;
    3167:   c->compressedrow.nrows = a->compressedrow.nrows;
    3168:   if (a->compressedrow.use) {
    3169:     i    = a->compressedrow.nrows;
    3170:     PetscMalloc2(i+1,&c->compressedrow.i,i+1,&c->compressedrow.rindex);
    3171:     PetscLogObjectMemory((PetscObject)C,(2*i+1)*sizeof(PetscInt));
    3172:     PetscMemcpy(c->compressedrow.i,a->compressedrow.i,(i+1)*sizeof(PetscInt));
    3173:     PetscMemcpy(c->compressedrow.rindex,a->compressedrow.rindex,i*sizeof(PetscInt));
    3174:   } else {
    3175:     c->compressedrow.use    = PETSC_FALSE;
    3176:     c->compressedrow.i      = NULL;
    3177:     c->compressedrow.rindex = NULL;
    3178:   }
    3179:   C->nonzerostate = A->nonzerostate;

    3181:   PetscFunctionListDuplicate(((PetscObject)A)->qlist,&((PetscObject)C)->qlist);
    3182:   PetscMemcpy(C->ops,A->ops,sizeof(struct _MatOps));
    3183:   return(0);
    3184: }

    3188: PetscErrorCode MatDuplicate_SeqBAIJ(Mat A,MatDuplicateOption cpvalues,Mat *B)
    3189: {

    3193:   MatCreate(PetscObjectComm((PetscObject)A),B);
    3194:   MatSetSizes(*B,A->rmap->N,A->cmap->n,A->rmap->N,A->cmap->n);
    3195:   MatSetType(*B,MATSEQBAIJ);
    3196:   MatDuplicateNoCreate_SeqBAIJ(*B,A,cpvalues,PETSC_TRUE);
    3197:   return(0);
    3198: }

    3202: PetscErrorCode MatLoad_SeqBAIJ(Mat newmat,PetscViewer viewer)
    3203: {
    3204:   Mat_SeqBAIJ    *a;
    3206:   PetscInt       i,nz,header[4],*rowlengths=0,M,N,bs = newmat->rmap->bs;
    3207:   PetscInt       *mask,mbs,*jj,j,rowcount,nzcount,k,*browlengths,maskcount;
    3208:   PetscInt       kmax,jcount,block,idx,point,nzcountb,extra_rows,rows,cols;
    3209:   PetscInt       *masked,nmask,tmp,bs2,ishift;
    3210:   PetscMPIInt    size;
    3211:   int            fd;
    3212:   PetscScalar    *aa;
    3213:   MPI_Comm       comm;

    3216:   /* force binary viewer to load .info file if it has not yet done so */
    3217:   PetscViewerSetUp(viewer);
    3218:   PetscObjectGetComm((PetscObject)viewer,&comm);
    3219:   PetscOptionsBegin(comm,NULL,"Options for loading SEQBAIJ matrix","Mat");
    3220:   PetscOptionsInt("-matload_block_size","Set the blocksize used to store the matrix","MatLoad",bs,&bs,NULL);
    3221:   PetscOptionsEnd();
    3222:   if (bs < 0) bs = 1;
    3223:   bs2  = bs*bs;

    3225:   MPI_Comm_size(comm,&size);
    3226:   if (size > 1) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONG,"view must have one processor");
    3227:   PetscViewerBinaryGetDescriptor(viewer,&fd);
    3228:   PetscBinaryRead(fd,header,4,PETSC_INT);
    3229:   if (header[0] != MAT_FILE_CLASSID) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_FILE_UNEXPECTED,"not Mat object");
    3230:   M = header[1]; N = header[2]; nz = header[3];

    3232:   if (header[3] < 0) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_FILE_UNEXPECTED,"Matrix stored in special format, cannot load as SeqBAIJ");
    3233:   if (M != N) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"Can only do square matrices");

    3235:   /*
    3236:      This code adds extra rows to make sure the number of rows is
    3237:     divisible by the blocksize
    3238:   */
    3239:   mbs        = M/bs;
    3240:   extra_rows = bs - M + bs*(mbs);
    3241:   if (extra_rows == bs) extra_rows = 0;
    3242:   else mbs++;
    3243:   if (extra_rows) {
    3244:     PetscInfo(viewer,"Padding loaded matrix to match blocksize\n");
    3245:   }

    3247:   /* Set global sizes if not already set */
    3248:   if (newmat->rmap->n < 0 && newmat->rmap->N < 0 && newmat->cmap->n < 0 && newmat->cmap->N < 0) {
    3249:     MatSetSizes(newmat,PETSC_DECIDE,PETSC_DECIDE,M+extra_rows,N+extra_rows);
    3250:   } else { /* Check if the matrix global sizes are correct */
    3251:     MatGetSize(newmat,&rows,&cols);
    3252:     if (rows < 0 && cols < 0) { /* user might provide local size instead of global size */
    3253:       MatGetLocalSize(newmat,&rows,&cols);
    3254:     }
    3255:     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);
    3256:   }

    3258:   /* read in row lengths */
    3259:   PetscMalloc1(M+extra_rows,&rowlengths);
    3260:   PetscBinaryRead(fd,rowlengths,M,PETSC_INT);
    3261:   for (i=0; i<extra_rows; i++) rowlengths[M+i] = 1;

    3263:   /* read in column indices */
    3264:   PetscMalloc1(nz+extra_rows,&jj);
    3265:   PetscBinaryRead(fd,jj,nz,PETSC_INT);
    3266:   for (i=0; i<extra_rows; i++) jj[nz+i] = M+i;

    3268:   /* loop over row lengths determining block row lengths */
    3269:   PetscCalloc1(mbs,&browlengths);
    3270:   PetscMalloc2(mbs,&mask,mbs,&masked);
    3271:   PetscMemzero(mask,mbs*sizeof(PetscInt));
    3272:   rowcount = 0;
    3273:   nzcount  = 0;
    3274:   for (i=0; i<mbs; i++) {
    3275:     nmask = 0;
    3276:     for (j=0; j<bs; j++) {
    3277:       kmax = rowlengths[rowcount];
    3278:       for (k=0; k<kmax; k++) {
    3279:         tmp = jj[nzcount++]/bs;
    3280:         if (!mask[tmp]) {masked[nmask++] = tmp; mask[tmp] = 1;}
    3281:       }
    3282:       rowcount++;
    3283:     }
    3284:     browlengths[i] += nmask;
    3285:     /* zero out the mask elements we set */
    3286:     for (j=0; j<nmask; j++) mask[masked[j]] = 0;
    3287:   }

    3289:   /* Do preallocation  */
    3290:   MatSeqBAIJSetPreallocation_SeqBAIJ(newmat,bs,0,browlengths);
    3291:   a    = (Mat_SeqBAIJ*)newmat->data;

    3293:   /* set matrix "i" values */
    3294:   a->i[0] = 0;
    3295:   for (i=1; i<= mbs; i++) {
    3296:     a->i[i]      = a->i[i-1] + browlengths[i-1];
    3297:     a->ilen[i-1] = browlengths[i-1];
    3298:   }
    3299:   a->nz = 0;
    3300:   for (i=0; i<mbs; i++) a->nz += browlengths[i];

    3302:   /* read in nonzero values */
    3303:   PetscMalloc1(nz+extra_rows,&aa);
    3304:   PetscBinaryRead(fd,aa,nz,PETSC_SCALAR);
    3305:   for (i=0; i<extra_rows; i++) aa[nz+i] = 1.0;

    3307:   /* set "a" and "j" values into matrix */
    3308:   nzcount = 0; jcount = 0;
    3309:   for (i=0; i<mbs; i++) {
    3310:     nzcountb = nzcount;
    3311:     nmask    = 0;
    3312:     for (j=0; j<bs; j++) {
    3313:       kmax = rowlengths[i*bs+j];
    3314:       for (k=0; k<kmax; k++) {
    3315:         tmp = jj[nzcount++]/bs;
    3316:         if (!mask[tmp]) { masked[nmask++] = tmp; mask[tmp] = 1;}
    3317:       }
    3318:     }
    3319:     /* sort the masked values */
    3320:     PetscSortInt(nmask,masked);

    3322:     /* set "j" values into matrix */
    3323:     maskcount = 1;
    3324:     for (j=0; j<nmask; j++) {
    3325:       a->j[jcount++]  = masked[j];
    3326:       mask[masked[j]] = maskcount++;
    3327:     }
    3328:     /* set "a" values into matrix */
    3329:     ishift = bs2*a->i[i];
    3330:     for (j=0; j<bs; j++) {
    3331:       kmax = rowlengths[i*bs+j];
    3332:       for (k=0; k<kmax; k++) {
    3333:         tmp       = jj[nzcountb]/bs;
    3334:         block     = mask[tmp] - 1;
    3335:         point     = jj[nzcountb] - bs*tmp;
    3336:         idx       = ishift + bs2*block + j + bs*point;
    3337:         a->a[idx] = (MatScalar)aa[nzcountb++];
    3338:       }
    3339:     }
    3340:     /* zero out the mask elements we set */
    3341:     for (j=0; j<nmask; j++) mask[masked[j]] = 0;
    3342:   }
    3343:   if (jcount != a->nz) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_FILE_UNEXPECTED,"Bad binary matrix");

    3345:   PetscFree(rowlengths);
    3346:   PetscFree(browlengths);
    3347:   PetscFree(aa);
    3348:   PetscFree(jj);
    3349:   PetscFree2(mask,masked);

    3351:   MatAssemblyBegin(newmat,MAT_FINAL_ASSEMBLY);
    3352:   MatAssemblyEnd(newmat,MAT_FINAL_ASSEMBLY);
    3353:   return(0);
    3354: }

    3358: /*@C
    3359:    MatCreateSeqBAIJ - Creates a sparse matrix in block AIJ (block
    3360:    compressed row) format.  For good matrix assembly performance the
    3361:    user should preallocate the matrix storage by setting the parameter nz
    3362:    (or the array nnz).  By setting these parameters accurately, performance
    3363:    during matrix assembly can be increased by more than a factor of 50.

    3365:    Collective on MPI_Comm

    3367:    Input Parameters:
    3368: +  comm - MPI communicator, set to PETSC_COMM_SELF
    3369: .  bs - size of block, the blocks are ALWAYS square. One can use MatSetBlockSizes() to set a different row and column blocksize but the row
    3370:           blocksize always defines the size of the blocks. The column blocksize sets the blocksize of the vectors obtained with MatCreateVecs()
    3371: .  m - number of rows
    3372: .  n - number of columns
    3373: .  nz - number of nonzero blocks  per block row (same for all rows)
    3374: -  nnz - array containing the number of nonzero blocks in the various block rows
    3375:          (possibly different for each block row) or NULL

    3377:    Output Parameter:
    3378: .  A - the matrix

    3380:    It is recommended that one use the MatCreate(), MatSetType() and/or MatSetFromOptions(),
    3381:    MatXXXXSetPreallocation() paradgm instead of this routine directly.
    3382:    [MatXXXXSetPreallocation() is, for example, MatSeqAIJSetPreallocation]

    3384:    Options Database Keys:
    3385: .   -mat_no_unroll - uses code that does not unroll the loops in the
    3386:                      block calculations (much slower)
    3387: .    -mat_block_size - size of the blocks to use

    3389:    Level: intermediate

    3391:    Notes:
    3392:    The number of rows and columns must be divisible by blocksize.

    3394:    If the nnz parameter is given then the nz parameter is ignored

    3396:    A nonzero block is any block that as 1 or more nonzeros in it

    3398:    The block AIJ format is fully compatible with standard Fortran 77
    3399:    storage.  That is, the stored row and column indices can begin at
    3400:    either one (as in Fortran) or zero.  See the users' manual for details.

    3402:    Specify the preallocated storage with either nz or nnz (not both).
    3403:    Set nz=PETSC_DEFAULT and nnz=NULL for PETSc to control dynamic memory
    3404:    allocation.  See Users-Manual: ch_mat for details.
    3405:    matrices.

    3407: .seealso: MatCreate(), MatCreateSeqAIJ(), MatSetValues(), MatCreateBAIJ()
    3408: @*/
    3409: PetscErrorCode  MatCreateSeqBAIJ(MPI_Comm comm,PetscInt bs,PetscInt m,PetscInt n,PetscInt nz,const PetscInt nnz[],Mat *A)
    3410: {

    3414:   MatCreate(comm,A);
    3415:   MatSetSizes(*A,m,n,m,n);
    3416:   MatSetType(*A,MATSEQBAIJ);
    3417:   MatSeqBAIJSetPreallocation_SeqBAIJ(*A,bs,nz,(PetscInt*)nnz);
    3418:   return(0);
    3419: }

    3423: /*@C
    3424:    MatSeqBAIJSetPreallocation - Sets the block size and expected nonzeros
    3425:    per row in the matrix. For good matrix assembly performance the
    3426:    user should preallocate the matrix storage by setting the parameter nz
    3427:    (or the array nnz).  By setting these parameters accurately, performance
    3428:    during matrix assembly can be increased by more than a factor of 50.

    3430:    Collective on MPI_Comm

    3432:    Input Parameters:
    3433: +  B - the matrix
    3434: .  bs - size of block, the blocks are ALWAYS square. One can use MatSetBlockSizes() to set a different row and column blocksize but the row
    3435:           blocksize always defines the size of the blocks. The column blocksize sets the blocksize of the vectors obtained with MatCreateVecs()
    3436: .  nz - number of block nonzeros per block row (same for all rows)
    3437: -  nnz - array containing the number of block nonzeros in the various block rows
    3438:          (possibly different for each block row) or NULL

    3440:    Options Database Keys:
    3441: .   -mat_no_unroll - uses code that does not unroll the loops in the
    3442:                      block calculations (much slower)
    3443: .   -mat_block_size - size of the blocks to use

    3445:    Level: intermediate

    3447:    Notes:
    3448:    If the nnz parameter is given then the nz parameter is ignored

    3450:    You can call MatGetInfo() to get information on how effective the preallocation was;
    3451:    for example the fields mallocs,nz_allocated,nz_used,nz_unneeded;
    3452:    You can also run with the option -info and look for messages with the string
    3453:    malloc in them to see if additional memory allocation was needed.

    3455:    The block AIJ format is fully compatible with standard Fortran 77
    3456:    storage.  That is, the stored row and column indices can begin at
    3457:    either one (as in Fortran) or zero.  See the users' manual for details.

    3459:    Specify the preallocated storage with either nz or nnz (not both).
    3460:    Set nz=PETSC_DEFAULT and nnz=NULL for PETSc to control dynamic memory
    3461:    allocation.  See Users-Manual: ch_mat for details.

    3463: .seealso: MatCreate(), MatCreateSeqAIJ(), MatSetValues(), MatCreateBAIJ(), MatGetInfo()
    3464: @*/
    3465: PetscErrorCode  MatSeqBAIJSetPreallocation(Mat B,PetscInt bs,PetscInt nz,const PetscInt nnz[])
    3466: {

    3473:   PetscTryMethod(B,"MatSeqBAIJSetPreallocation_C",(Mat,PetscInt,PetscInt,const PetscInt[]),(B,bs,nz,nnz));
    3474:   return(0);
    3475: }

    3479: /*@C
    3480:    MatSeqBAIJSetPreallocationCSR - Allocates memory for a sparse sequential matrix in AIJ format
    3481:    (the default sequential PETSc format).

    3483:    Collective on MPI_Comm

    3485:    Input Parameters:
    3486: +  B - the matrix
    3487: .  i - the indices into j for the start of each local row (starts with zero)
    3488: .  j - the column indices for each local row (starts with zero) these must be sorted for each row
    3489: -  v - optional values in the matrix

    3491:    Level: developer

    3493:    Notes:
    3494:    The order of the entries in values is specified by the MatOption MAT_ROW_ORIENTED.  For example, C programs
    3495:    may want to use the default MAT_ROW_ORIENTED=PETSC_TRUE and use an array v[nnz][bs][bs] where the second index is
    3496:    over rows within a block and the last index is over columns within a block row.  Fortran programs will likely set
    3497:    MAT_ROW_ORIENTED=PETSC_FALSE and use a Fortran array v(bs,bs,nnz) in which the first index is over rows within a
    3498:    block column and the second index is over columns within a block.

    3500: .keywords: matrix, aij, compressed row, sparse

    3502: .seealso: MatCreate(), MatCreateSeqBAIJ(), MatSetValues(), MatSeqBAIJSetPreallocation(), MATSEQBAIJ
    3503: @*/
    3504: PetscErrorCode  MatSeqBAIJSetPreallocationCSR(Mat B,PetscInt bs,const PetscInt i[],const PetscInt j[], const PetscScalar v[])
    3505: {

    3512:   PetscTryMethod(B,"MatSeqBAIJSetPreallocationCSR_C",(Mat,PetscInt,const PetscInt[],const PetscInt[],const PetscScalar[]),(B,bs,i,j,v));
    3513:   return(0);
    3514: }

    3519: /*@
    3520:      MatCreateSeqBAIJWithArrays - Creates an sequential BAIJ matrix using matrix elements provided by the user.

    3522:      Collective on MPI_Comm

    3524:    Input Parameters:
    3525: +  comm - must be an MPI communicator of size 1
    3526: .  bs - size of block
    3527: .  m - number of rows
    3528: .  n - number of columns
    3529: .  i - row indices
    3530: .  j - column indices
    3531: -  a - matrix values

    3533:    Output Parameter:
    3534: .  mat - the matrix

    3536:    Level: advanced

    3538:    Notes:
    3539:        The i, j, and a arrays are not copied by this routine, the user must free these arrays
    3540:     once the matrix is destroyed

    3542:        You cannot set new nonzero locations into this matrix, that will generate an error.

    3544:        The i and j indices are 0 based

    3546:        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).

    3548:       The order of the entries in values is the same as the block compressed sparse row storage format; that is, it is
    3549:       the same as a three dimensional array in Fortran values(bs,bs,nnz) that contains the first column of the first
    3550:       block, followed by the second column of the first block etc etc.  That is, the blocks are contiguous in memory
    3551:       with column-major ordering within blocks.

    3553: .seealso: MatCreate(), MatCreateBAIJ(), MatCreateSeqBAIJ()

    3555: @*/
    3556: PetscErrorCode  MatCreateSeqBAIJWithArrays(MPI_Comm comm,PetscInt bs,PetscInt m,PetscInt n,PetscInt *i,PetscInt *j,PetscScalar *a,Mat *mat)
    3557: {
    3559:   PetscInt       ii;
    3560:   Mat_SeqBAIJ    *baij;

    3563:   if (bs != 1) SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_SUP,"block size %D > 1 is not supported yet",bs);
    3564:   if (i[0]) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"i (row indices) must start with 0");

    3566:   MatCreate(comm,mat);
    3567:   MatSetSizes(*mat,m,n,m,n);
    3568:   MatSetType(*mat,MATSEQBAIJ);
    3569:   MatSeqBAIJSetPreallocation_SeqBAIJ(*mat,bs,MAT_SKIP_ALLOCATION,0);
    3570:   baij = (Mat_SeqBAIJ*)(*mat)->data;
    3571:   PetscMalloc2(m,&baij->imax,m,&baij->ilen);
    3572:   PetscLogObjectMemory((PetscObject)*mat,2*m*sizeof(PetscInt));

    3574:   baij->i = i;
    3575:   baij->j = j;
    3576:   baij->a = a;

    3578:   baij->singlemalloc = PETSC_FALSE;
    3579:   baij->nonew        = -1;             /*this indicates that inserting a new value in the matrix that generates a new nonzero is an error*/
    3580:   baij->free_a       = PETSC_FALSE;
    3581:   baij->free_ij      = PETSC_FALSE;

    3583:   for (ii=0; ii<m; ii++) {
    3584:     baij->ilen[ii] = baij->imax[ii] = i[ii+1] - i[ii];
    3585: #if defined(PETSC_USE_DEBUG)
    3586:     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]);
    3587: #endif
    3588:   }
    3589: #if defined(PETSC_USE_DEBUG)
    3590:   for (ii=0; ii<baij->i[m]; ii++) {
    3591:     if (j[ii] < 0) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Negative column index at location = %d index = %d",ii,j[ii]);
    3592:     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]);
    3593:   }
    3594: #endif

    3596:   MatAssemblyBegin(*mat,MAT_FINAL_ASSEMBLY);
    3597:   MatAssemblyEnd(*mat,MAT_FINAL_ASSEMBLY);
    3598:   return(0);
    3599: }

    3603: PetscErrorCode MatCreateMPIMatConcatenateSeqMat_SeqBAIJ(MPI_Comm comm,Mat inmat,PetscInt n,MatReuse scall,Mat *outmat)
    3604: {

    3608:   MatCreateMPIMatConcatenateSeqMat_MPIBAIJ(comm,inmat,n,scall,outmat);
    3609:   return(0);
    3610: }