Actual source code: sell.c

petsc-3.9.2 2018-05-20
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  2: /*
  3:   Defines the basic matrix operations for the SELL matrix storage format.
  4: */
  5:  #include <../src/mat/impls/sell/seq/sell.h>
  6:  #include <petscblaslapack.h>
  7:  #include <petsc/private/kernels/blocktranspose.h>
  8: #if defined(PETSC_HAVE_IMMINTRIN_H) && (defined(__AVX512F__) || (defined(__AVX2__) && defined(__FMA__)) || defined(__AVX__)) && defined(PETSC_USE_REAL_DOUBLE) && !defined(PETSC_USE_COMPLEX) && !defined(PETSC_USE_64BIT_INDICES)

 10:   #include <immintrin.h>

 12:   #if !defined(_MM_SCALE_8)
 13:   #define _MM_SCALE_8    8
 14:   #endif

 16:   #if defined(__AVX512F__)
 17:   /* these do not work
 18:    vec_idx  = _mm512_loadunpackhi_epi32(vec_idx,acolidx);
 19:    vec_vals = _mm512_loadunpackhi_pd(vec_vals,aval);
 20:   */
 21:     #define AVX512_Mult_Private(vec_idx,vec_x,vec_vals,vec_y) \
 22:     /* if the mask bit is set, copy from acolidx, otherwise from vec_idx */ \
 23:     vec_idx  = _mm256_loadu_si256((__m256i const*)acolidx); \
 24:     vec_vals = _mm512_loadu_pd(aval); \
 25:     vec_x    = _mm512_i32gather_pd(vec_idx,x,_MM_SCALE_8); \
 26:     vec_y    = _mm512_fmadd_pd(vec_x,vec_vals,vec_y)
 27:   #elif defined(__AVX2__) && defined(__FMA__)
 28:     #define AVX2_Mult_Private(vec_idx,vec_x,vec_vals,vec_y) \
 29:     vec_vals = _mm256_loadu_pd(aval); \
 30:     vec_idx  = _mm_loadu_si128((__m128i const*)acolidx); /* SSE2 */ \
 31:     vec_x    = _mm256_i32gather_pd(x,vec_idx,_MM_SCALE_8); \
 32:     vec_y    = _mm256_fmadd_pd(vec_x,vec_vals,vec_y)
 33:   #endif
 34: #endif  /* PETSC_HAVE_IMMINTRIN_H */

 36: /*@C
 37:  MatSeqSELLSetPreallocation - For good matrix assembly performance
 38:  the user should preallocate the matrix storage by setting the parameter nz
 39:  (or the array nnz).  By setting these parameters accurately, performance
 40:  during matrix assembly can be increased significantly.

 42:  Collective on MPI_Comm

 44:  Input Parameters:
 45:  +  B - The matrix
 46:  .  nz - number of nonzeros per row (same for all rows)
 47:  -  nnz - array containing the number of nonzeros in the various rows
 48:  (possibly different for each row) or NULL

 50:  Notes:
 51:  If nnz is given then nz is ignored.

 53:  Specify the preallocated storage with either nz or nnz (not both).
 54:  Set nz=PETSC_DEFAULT and nnz=NULL for PETSc to control dynamic memory
 55:  allocation.  For large problems you MUST preallocate memory or you
 56:  will get TERRIBLE performance, see the users' manual chapter on matrices.

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

 63:  Developers: Use nz of MAT_SKIP_ALLOCATION to not allocate any space for the matrix
 64:  entries or columns indices.

 66:  The maximum number of nonzeos in any row should be as accuate as possible.
 67:  If it is underesitmated, you will get bad performance due to reallocation
 68:  (MatSeqXSELLReallocateSELL).

 70:  Level: intermediate

 72:  .seealso: MatCreate(), MatCreateSELL(), MatSetValues(), MatGetInfo()

 74:  @*/
 75: PetscErrorCode MatSeqSELLSetPreallocation(Mat B,PetscInt rlenmax,const PetscInt rlen[])
 76: {

 82:   PetscTryMethod(B,"MatSeqSELLSetPreallocation_C",(Mat,PetscInt,const PetscInt[]),(B,rlenmax,rlen));
 83:   return(0);
 84: }

 86: PetscErrorCode MatSeqSELLSetPreallocation_SeqSELL(Mat B,PetscInt maxallocrow,const PetscInt rlen[])
 87: {
 88:   Mat_SeqSELL    *b;
 89:   PetscInt       i,j,totalslices;
 90:   PetscBool      skipallocation=PETSC_FALSE,realalloc=PETSC_FALSE;

 94:   if (maxallocrow >= 0 || rlen) realalloc = PETSC_TRUE;
 95:   if (maxallocrow == MAT_SKIP_ALLOCATION) {
 96:     skipallocation = PETSC_TRUE;
 97:     maxallocrow    = 0;
 98:   }

100:   PetscLayoutSetUp(B->rmap);
101:   PetscLayoutSetUp(B->cmap);

103:   /* FIXME: if one preallocates more space than needed, the matrix does not shrink automatically, but for best performance it should */
104:   if (maxallocrow == PETSC_DEFAULT || maxallocrow == PETSC_DECIDE) maxallocrow = 5;
105:   if (maxallocrow < 0) SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"maxallocrow cannot be less than 0: value %D",maxallocrow);
106:   if (rlen) {
107:     for (i=0; i<B->rmap->n; i++) {
108:       if (rlen[i] < 0) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"rlen cannot be less than 0: local row %D value %D",i,rlen[i]);
109:       if (rlen[i] > B->cmap->n) SETERRQ3(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"rlen cannot be greater than row length: local row %D value %D rowlength %D",i,rlen[i],B->cmap->n);
110:     }
111:   }

113:   B->preallocated = PETSC_TRUE;

115:   b = (Mat_SeqSELL*)B->data;

117:   totalslices = B->rmap->n/8+((B->rmap->n & 0x07)?1:0); /* ceil(n/8) */
118:   b->totalslices = totalslices;
119:   if (!skipallocation) {
120:     if (B->rmap->n & 0x07) PetscInfo1(B,"Padding rows to the SEQSELL matrix because the number of rows is not the multiple of 8 (value %D)\n",B->rmap->n);

122:     if (!b->sliidx) { /* sliidx gives the starting index of each slice, the last element is the total space allocated */
123:       PetscMalloc1(totalslices+1,&b->sliidx);
124:       PetscLogObjectMemory((PetscObject)B,(totalslices+1)*sizeof(PetscInt));
125:     }
126:     if (!rlen) { /* if rlen is not provided, allocate same space for all the slices */
127:       if (maxallocrow == PETSC_DEFAULT || maxallocrow == PETSC_DECIDE) maxallocrow = 10;
128:       else if (maxallocrow < 0) maxallocrow = 1;
129:       for (i=0; i<=totalslices; i++) b->sliidx[i] = i*8*maxallocrow;
130:     } else {
131:       maxallocrow = 0;
132:       b->sliidx[0] = 0;
133:       for (i=1; i<totalslices; i++) {
134:         b->sliidx[i] = 0;
135:         for (j=0;j<8;j++) {
136:           b->sliidx[i] = PetscMax(b->sliidx[i],rlen[8*(i-1)+j]);
137:         }
138:         maxallocrow = PetscMax(b->sliidx[i],maxallocrow);
139:         b->sliidx[i] = b->sliidx[i-1] + 8*b->sliidx[i];
140:       }
141:       /* last slice */
142:       b->sliidx[totalslices] = 0;
143:       for (j=(totalslices-1)*8;j<B->rmap->n;j++) b->sliidx[totalslices] = PetscMax(b->sliidx[totalslices],rlen[j]);
144:       maxallocrow = PetscMax(b->sliidx[totalslices],maxallocrow);
145:       b->sliidx[totalslices] = b->sliidx[totalslices-1] + 8*b->sliidx[totalslices];
146:     }

148:     /* allocate space for val, colidx, rlen */
149:     /* FIXME: should B's old memory be unlogged? */
150:     MatSeqXSELLFreeSELL(B,&b->val,&b->colidx);
151:     /* FIXME: assuming an element of the bit array takes 8 bits */
152:     PetscMalloc2(b->sliidx[totalslices],&b->val,b->sliidx[totalslices],&b->colidx);
153:     PetscLogObjectMemory((PetscObject)B,b->sliidx[totalslices]*(sizeof(PetscScalar)+sizeof(PetscInt)));
154:     /* b->rlen will count nonzeros in each row so far. We dont copy rlen to b->rlen because the matrix has not been set. */
155:     PetscCalloc1(8*totalslices,&b->rlen);
156:     PetscLogObjectMemory((PetscObject)B,8*totalslices*sizeof(PetscInt));

158:     b->singlemalloc = PETSC_TRUE;
159:     b->free_val     = PETSC_TRUE;
160:     b->free_colidx  = PETSC_TRUE;
161:   } else {
162:     b->free_val    = PETSC_FALSE;
163:     b->free_colidx = PETSC_FALSE;
164:   }

166:   b->nz               = 0;
167:   b->maxallocrow      = maxallocrow;
168:   b->rlenmax          = maxallocrow;
169:   b->maxallocmat      = b->sliidx[totalslices];
170:   B->info.nz_unneeded = (double)b->maxallocmat;
171:   if (realalloc) {
172:     MatSetOption(B,MAT_NEW_NONZERO_ALLOCATION_ERR,PETSC_TRUE);
173:   }
174:   return(0);
175: }

177: PetscErrorCode MatGetRow_SeqSELL(Mat A,PetscInt row,PetscInt *nz,PetscInt **idx,PetscScalar **v)
178: {
179:   Mat_SeqSELL *a = (Mat_SeqSELL*)A->data;
180:   PetscInt    shift;

183:   if (row < 0 || row >= A->rmap->n) SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Row %D out of range",row);
184:   if (nz) *nz = a->rlen[row];
185:   shift = a->sliidx[row>>3]+(row&0x07);
186:   if (!a->getrowcols) {

189:     PetscMalloc2(a->rlenmax,&a->getrowcols,a->rlenmax,&a->getrowvals);
190:   }
191:   if (idx) {
192:     PetscInt j;
193:     for (j=0; j<a->rlen[row]; j++) a->getrowcols[j] = a->colidx[shift+8*j];
194:     *idx = a->getrowcols;
195:   }
196:   if (v) {
197:     PetscInt j;
198:     for (j=0; j<a->rlen[row]; j++) a->getrowvals[j] = a->val[shift+8*j];
199:     *v = a->getrowvals;
200:   }
201:   return(0);
202: }

204: PetscErrorCode MatRestoreRow_SeqSELL(Mat A,PetscInt row,PetscInt *nz,PetscInt **idx,PetscScalar **v)
205: {
207:   return(0);
208: }

210: PetscErrorCode MatConvert_SeqSELL_SeqAIJ(Mat A, MatType newtype,MatReuse reuse,Mat *newmat)
211: {
212:   Mat            B;
213:   Mat_SeqSELL    *a=(Mat_SeqSELL*)A->data;
214:   PetscInt       i;

218:   if (reuse == MAT_REUSE_MATRIX) {
219:     B    = *newmat;
220:     MatZeroEntries(B);
221:   } else {
222:     MatCreate(PetscObjectComm((PetscObject)A),&B);
223:     MatSetSizes(B,A->rmap->n,A->cmap->n,A->rmap->N,A->cmap->N);
224:     MatSetType(B,MATSEQAIJ);
225:     MatSeqAIJSetPreallocation(B,0,a->rlen);
226:   }

228:   for (i=0; i<A->rmap->n; i++) {
229:     PetscInt    nz,*cols;
230:     PetscScalar *vals;

232:     MatGetRow_SeqSELL(A,i,&nz,&cols,&vals);
233:     MatSetValues(B,1,&i,nz,cols,vals,INSERT_VALUES);
234:     MatRestoreRow_SeqSELL(A,i,&nz,&cols,&vals);
235:   }

237:   MatAssemblyBegin(B,MAT_FINAL_ASSEMBLY);
238:   MatAssemblyEnd(B,MAT_FINAL_ASSEMBLY);
239:   B->rmap->bs = A->rmap->bs;

241:   if (reuse == MAT_INPLACE_MATRIX) {
242:     MatHeaderReplace(A,&B);
243:   } else {
244:     *newmat = B;
245:   }
246:   return(0);
247: }

249:  #include <../src/mat/impls/aij/seq/aij.h>

251: PetscErrorCode MatConvert_SeqAIJ_SeqSELL(Mat A,MatType newtype,MatReuse reuse,Mat *newmat)
252: {
253:   Mat               B;
254:   Mat_SeqAIJ        *a=(Mat_SeqAIJ*)A->data;
255:   PetscInt          *ai=a->i,m=A->rmap->N,n=A->cmap->N,i,*rowlengths,row,ncols;
256:   const PetscInt    *cols;
257:   const PetscScalar *vals;
258:   PetscErrorCode    ierr;

261:   if (A->rmap->bs > 1) {
262:     MatConvert_Basic(A,newtype,reuse,newmat);
263:     return(0);
264:   }

266:   if (reuse == MAT_REUSE_MATRIX) {
267:     B = *newmat;
268:   } else {
269:     /* Can we just use ilen? */
270:     PetscMalloc1(m,&rowlengths);
271:     for (i=0; i<m; i++) {
272:       rowlengths[i] = ai[i+1] - ai[i];
273:     }

275:     MatCreate(PetscObjectComm((PetscObject)A),&B);
276:     MatSetSizes(B,m,n,m,n);
277:     MatSetType(B,MATSEQSELL);
278:     MatSeqSELLSetPreallocation(B,0,rowlengths);
279:     PetscFree(rowlengths);
280:   }

282:   for (row=0; row<m; row++) {
283:     MatGetRow(A,row,&ncols,&cols,&vals);
284:     MatSetValues(B,1,&row,ncols,cols,vals,INSERT_VALUES);
285:     MatRestoreRow(A,row,&ncols,&cols,&vals);
286:   }
287:   MatAssemblyBegin(B,MAT_FINAL_ASSEMBLY);
288:   MatAssemblyEnd(B,MAT_FINAL_ASSEMBLY);
289:   B->rmap->bs = A->rmap->bs;

291:   if (reuse == MAT_INPLACE_MATRIX) {
292:     MatHeaderReplace(A,&B);
293:   } else {
294:     *newmat = B;
295:   }
296:   return(0);
297: }

299: PetscErrorCode MatMult_SeqSELL(Mat A,Vec xx,Vec yy)
300: {
301:   Mat_SeqSELL       *a=(Mat_SeqSELL*)A->data;
302:   PetscScalar       *y;
303:   const PetscScalar *x;
304:   const MatScalar   *aval=a->val;
305:   PetscInt          totalslices=a->totalslices;
306:   const PetscInt    *acolidx=a->colidx;
307:   PetscInt          i,j;
308:   PetscErrorCode    ierr;
309: #if defined(PETSC_HAVE_IMMINTRIN_H) && defined(__AVX512F__) && defined(PETSC_USE_REAL_DOUBLE) && !defined(PETSC_USE_COMPLEX) && !defined(PETSC_USE_64BIT_INDICES)
310:   __m512d           vec_x,vec_y,vec_vals;
311:   __m256i           vec_idx;
312:   __mmask8          mask;
313:   __m512d           vec_x2,vec_y2,vec_vals2,vec_x3,vec_y3,vec_vals3,vec_x4,vec_y4,vec_vals4;
314:   __m256i           vec_idx2,vec_idx3,vec_idx4;
315: #elif defined(PETSC_HAVE_IMMINTRIN_H) && defined(__AVX2__) && defined(__FMA__) && defined(PETSC_USE_REAL_DOUBLE) && !defined(PETSC_USE_COMPLEX) && !defined(PETSC_USE_64BIT_INDICES)
316:   __m128i           vec_idx;
317:   __m256d           vec_x,vec_y,vec_y2,vec_vals;
318:   MatScalar         yval;
319:   PetscInt          r,rows_left,row,nnz_in_row;
320: #elif defined(PETSC_HAVE_IMMINTRIN_H) && defined(__AVX__) && defined(PETSC_USE_REAL_DOUBLE) && !defined(PETSC_USE_COMPLEX) && !defined(PETSC_USE_64BIT_INDICES)
321:   __m128d           vec_x_tmp;
322:   __m256d           vec_x,vec_y,vec_y2,vec_vals;
323:   MatScalar         yval;
324:   PetscInt          r,rows_left,row,nnz_in_row;
325: #else
326:   PetscScalar       sum[8];
327: #endif

329: #if defined(PETSC_HAVE_PRAGMA_DISJOINT)
330: #pragma disjoint(*x,*y,*aval)
331: #endif

334:   VecGetArrayRead(xx,&x);
335:   VecGetArray(yy,&y);
336: #if defined(PETSC_HAVE_IMMINTRIN_H) && defined(__AVX512F__) && defined(PETSC_USE_REAL_DOUBLE) && !defined(PETSC_USE_COMPLEX) && !defined(PETSC_USE_64BIT_INDICES)
337:   for (i=0; i<totalslices; i++) { /* loop over slices */
338:     PetscPrefetchBlock(acolidx,a->sliidx[i+1]-a->sliidx[i],0,PETSC_PREFETCH_HINT_T0);
339:     PetscPrefetchBlock(aval,a->sliidx[i+1]-a->sliidx[i],0,PETSC_PREFETCH_HINT_T0);

341:     vec_y  = _mm512_setzero_pd();
342:     vec_y2 = _mm512_setzero_pd();
343:     vec_y3 = _mm512_setzero_pd();
344:     vec_y4 = _mm512_setzero_pd();

346:     j = a->sliidx[i]>>3; /* 8 bytes are read at each time, corresponding to a slice columnn */
347:     switch ((a->sliidx[i+1]-a->sliidx[i])/8 & 3) {
348:     case 3:
349:       AVX512_Mult_Private(vec_idx,vec_x,vec_vals,vec_y);
350:       acolidx += 8; aval += 8;
351:       AVX512_Mult_Private(vec_idx2,vec_x2,vec_vals2,vec_y2);
352:       acolidx += 8; aval += 8;
353:       AVX512_Mult_Private(vec_idx3,vec_x3,vec_vals3,vec_y3);
354:       acolidx += 8; aval += 8;
355:       j += 3;
356:       break;
357:     case 2:
358:       AVX512_Mult_Private(vec_idx,vec_x,vec_vals,vec_y);
359:       acolidx += 8; aval += 8;
360:       AVX512_Mult_Private(vec_idx2,vec_x2,vec_vals2,vec_y2);
361:       acolidx += 8; aval += 8;
362:       j += 2;
363:       break;
364:     case 1:
365:       AVX512_Mult_Private(vec_idx,vec_x,vec_vals,vec_y);
366:       acolidx += 8; aval += 8;
367:       j += 1;
368:       break;
369:     }
370:     #pragma novector
371:     for (; j<(a->sliidx[i+1]>>3); j+=4) {
372:       AVX512_Mult_Private(vec_idx,vec_x,vec_vals,vec_y);
373:       acolidx += 8; aval += 8;
374:       AVX512_Mult_Private(vec_idx2,vec_x2,vec_vals2,vec_y2);
375:       acolidx += 8; aval += 8;
376:       AVX512_Mult_Private(vec_idx3,vec_x3,vec_vals3,vec_y3);
377:       acolidx += 8; aval += 8;
378:       AVX512_Mult_Private(vec_idx4,vec_x4,vec_vals4,vec_y4);
379:       acolidx += 8; aval += 8;
380:     }

382:     vec_y = _mm512_add_pd(vec_y,vec_y2);
383:     vec_y = _mm512_add_pd(vec_y,vec_y3);
384:     vec_y = _mm512_add_pd(vec_y,vec_y4);
385:     if (i == totalslices-1 && A->rmap->n & 0x07) { /* if last slice has padding rows */
386:       mask = (__mmask8)(0xff >> (8-(A->rmap->n & 0x07)));
387:       _mm512_mask_storeu_pd(&y[8*i],mask,vec_y);
388:     } else {
389:       _mm512_storeu_pd(&y[8*i],vec_y);
390:     }
391:   }
392: #elif defined(PETSC_HAVE_IMMINTRIN_H) && defined(__AVX2__) && defined(__FMA__) && defined(PETSC_USE_REAL_DOUBLE) && !defined(PETSC_USE_COMPLEX) && !defined(PETSC_USE_64BIT_INDICES)
393:   for (i=0; i<totalslices; i++) { /* loop over full slices */
394:     PetscPrefetchBlock(acolidx,a->sliidx[i+1]-a->sliidx[i],0,PETSC_PREFETCH_HINT_T0);
395:     PetscPrefetchBlock(aval,a->sliidx[i+1]-a->sliidx[i],0,PETSC_PREFETCH_HINT_T0);

397:     /* last slice may have padding rows. Don't use vectorization. */
398:     if (i == totalslices-1 && (A->rmap->n & 0x07)) {
399:       rows_left = A->rmap->n - 8*i;
400:       for (r=0; r<rows_left; ++r) {
401:         yval = (MatScalar)0;
402:         row = 8*i + r;
403:         nnz_in_row = a->rlen[row];
404:         for (j=0; j<nnz_in_row; ++j) yval += aval[8*j+r] * x[acolidx[8*j+r]];
405:         y[row] = yval;
406:       }
407:       break;
408:     }

410:     vec_y  = _mm256_setzero_pd();
411:     vec_y2 = _mm256_setzero_pd();

413:     /* Process slice of height 8 (512 bits) via two subslices of height 4 (256 bits) via AVX */
414:     #pragma novector
415:     #pragma unroll(2)
416:     for (j=a->sliidx[i]; j<a->sliidx[i+1]; j+=8) {
417:       AVX2_Mult_Private(vec_idx,vec_x,vec_vals,vec_y);
418:       aval += 4; acolidx += 4;
419:       AVX2_Mult_Private(vec_idx,vec_x,vec_vals,vec_y2);
420:       aval += 4; acolidx += 4;
421:     }

423:     _mm256_storeu_pd(y+i*8,vec_y);
424:     _mm256_storeu_pd(y+i*8+4,vec_y2);
425:   }
426: #elif defined(PETSC_HAVE_IMMINTRIN_H) && defined(__AVX__) && defined(PETSC_USE_REAL_DOUBLE) && !defined(PETSC_USE_COMPLEX) && !defined(PETSC_USE_64BIT_INDICES)
427:   for (i=0; i<totalslices; i++) { /* loop over full slices */
428:     PetscPrefetchBlock(acolidx,a->sliidx[i+1]-a->sliidx[i],0,PETSC_PREFETCH_HINT_T0);
429:     PetscPrefetchBlock(aval,a->sliidx[i+1]-a->sliidx[i],0,PETSC_PREFETCH_HINT_T0);

431:     vec_y  = _mm256_setzero_pd();
432:     vec_y2 = _mm256_setzero_pd();

434:     /* last slice may have padding rows. Don't use vectorization. */
435:     if (i == totalslices-1 && (A->rmap->n & 0x07)) {
436:       rows_left = A->rmap->n - 8*i;
437:       for (r=0; r<rows_left; ++r) {
438:         yval = (MatScalar)0;
439:         row = 8*i + r;
440:         nnz_in_row = a->rlen[row];
441:         for (j=0; j<nnz_in_row; ++j) yval += aval[8*j + r] * x[acolidx[8*j + r]];
442:         y[row] = yval;
443:       }
444:       break;
445:     }

447:     /* Process slice of height 8 (512 bits) via two subslices of height 4 (256 bits) via AVX */
448:     #pragma novector
449:     #pragma unroll(2)
450:     for (j=a->sliidx[i]; j<a->sliidx[i+1]; j+=8) {
451:       vec_vals  = _mm256_loadu_pd(aval);
452:       vec_x_tmp = _mm_loadl_pd(vec_x_tmp, x + *acolidx++);
453:       vec_x_tmp = _mm_loadh_pd(vec_x_tmp, x + *acolidx++);
454:       vec_x     = _mm256_insertf128_pd(vec_x,vec_x_tmp,0);
455:       vec_x_tmp = _mm_loadl_pd(vec_x_tmp, x + *acolidx++);
456:       vec_x_tmp = _mm_loadh_pd(vec_x_tmp, x + *acolidx++);
457:       vec_x     = _mm256_insertf128_pd(vec_x,vec_x_tmp,1);
458:       vec_y     = _mm256_add_pd(_mm256_mul_pd(vec_x,vec_vals),vec_y);
459:       aval     += 4;

461:       vec_vals  = _mm256_loadu_pd(aval);
462:       vec_x_tmp = _mm_loadl_pd(vec_x_tmp, x + *acolidx++);
463:       vec_x_tmp = _mm_loadh_pd(vec_x_tmp, x + *acolidx++);
464:       vec_x     = _mm256_insertf128_pd(vec_x,vec_x_tmp,0);
465:       vec_x_tmp = _mm_loadl_pd(vec_x_tmp, x + *acolidx++);
466:       vec_x_tmp = _mm_loadh_pd(vec_x_tmp, x + *acolidx++);
467:       vec_x     = _mm256_insertf128_pd(vec_x,vec_x_tmp,1);
468:       vec_y2    = _mm256_add_pd(_mm256_mul_pd(vec_x,vec_vals),vec_y2);
469:       aval     += 4;
470:     }

472:     _mm256_storeu_pd(y + i*8,     vec_y);
473:     _mm256_storeu_pd(y + i*8 + 4, vec_y2);
474:   }
475: #else
476:   for (i=0; i<totalslices; i++) { /* loop over slices */
477:     for (j=0; j<8; j++) sum[j] = 0.0;
478:     for (j=a->sliidx[i]; j<a->sliidx[i+1]; j+=8) {
479:       sum[0] += aval[j] * x[acolidx[j]];
480:       sum[1] += aval[j+1] * x[acolidx[j+1]];
481:       sum[2] += aval[j+2] * x[acolidx[j+2]];
482:       sum[3] += aval[j+3] * x[acolidx[j+3]];
483:       sum[4] += aval[j+4] * x[acolidx[j+4]];
484:       sum[5] += aval[j+5] * x[acolidx[j+5]];
485:       sum[6] += aval[j+6] * x[acolidx[j+6]];
486:       sum[7] += aval[j+7] * x[acolidx[j+7]];
487:     }
488:     if (i == totalslices-1 && (A->rmap->n & 0x07)) { /* if last slice has padding rows */
489:       for(j=0; j<(A->rmap->n & 0x07); j++) y[8*i+j] = sum[j];
490:     } else {
491:       for(j=0; j<8; j++) y[8*i+j] = sum[j];
492:     }
493:   }
494: #endif

496:   PetscLogFlops(2.0*a->nz-a->nonzerorowcnt); /* theoretical minimal FLOPs */
497:   VecRestoreArrayRead(xx,&x);
498:   VecRestoreArray(yy,&y);
499:   return(0);
500: }

502: #include <../src/mat/impls/aij/seq/ftn-kernels/fmultadd.h>
503: PetscErrorCode MatMultAdd_SeqSELL(Mat A,Vec xx,Vec yy,Vec zz)
504: {
505:   Mat_SeqSELL       *a=(Mat_SeqSELL*)A->data;
506:   PetscScalar       *y,*z;
507:   const PetscScalar *x;
508:   const MatScalar   *aval=a->val;
509:   PetscInt          totalslices=a->totalslices;
510:   const PetscInt    *acolidx=a->colidx;
511:   PetscInt          i,j;
512:   PetscErrorCode    ierr;
513: #if defined(PETSC_HAVE_IMMINTRIN_H) && defined(__AVX512F__) && defined(PETSC_USE_REAL_DOUBLE) && !defined(PETSC_USE_COMPLEX) && !defined(PETSC_USE_64BIT_INDICES)
514:   __m512d           vec_x,vec_y,vec_vals;
515:   __m256i           vec_idx;
516:   __mmask8          mask;
517:   __m512d           vec_x2,vec_y2,vec_vals2,vec_x3,vec_y3,vec_vals3,vec_x4,vec_y4,vec_vals4;
518:   __m256i           vec_idx2,vec_idx3,vec_idx4;
519: #elif defined(PETSC_HAVE_IMMINTRIN_H) && defined(__AVX__) && defined(PETSC_USE_REAL_DOUBLE) && !defined(PETSC_USE_COMPLEX) && !defined(PETSC_USE_64BIT_INDICES)
520:   __m128d           vec_x_tmp;
521:   __m256d           vec_x,vec_y,vec_y2,vec_vals;
522:   MatScalar         yval;
523:   PetscInt          r,row,nnz_in_row;
524: #else
525:   PetscScalar       sum[8];
526: #endif

528: #if defined(PETSC_HAVE_PRAGMA_DISJOINT)
529: #pragma disjoint(*x,*y,*aval)
530: #endif

533:   VecGetArrayRead(xx,&x);
534:   VecGetArrayPair(yy,zz,&y,&z);
535: #if defined(PETSC_HAVE_IMMINTRIN_H) && defined(__AVX512F__) && defined(PETSC_USE_REAL_DOUBLE) && !defined(PETSC_USE_COMPLEX) && !defined(PETSC_USE_64BIT_INDICES)
536:   for (i=0; i<totalslices; i++) { /* loop over slices */
537:     PetscPrefetchBlock(acolidx,a->sliidx[i+1]-a->sliidx[i],0,PETSC_PREFETCH_HINT_T0);
538:     PetscPrefetchBlock(aval,a->sliidx[i+1]-a->sliidx[i],0,PETSC_PREFETCH_HINT_T0);

540:     if (i == totalslices-1 && A->rmap->n & 0x07) { /* if last slice has padding rows */
541:       mask   = (__mmask8)(0xff >> (8-(A->rmap->n & 0x07)));
542:       vec_y  = _mm512_mask_loadu_pd(vec_y,mask,&y[8*i]);
543:     } else {
544:       vec_y  = _mm512_loadu_pd(&y[8*i]);
545:     }
546:     vec_y2 = _mm512_setzero_pd();
547:     vec_y3 = _mm512_setzero_pd();
548:     vec_y4 = _mm512_setzero_pd();

550:     j = a->sliidx[i]>>3; /* 8 bytes are read at each time, corresponding to a slice columnn */
551:     switch ((a->sliidx[i+1]-a->sliidx[i])/8 & 3) {
552:     case 3:
553:       AVX512_Mult_Private(vec_idx,vec_x,vec_vals,vec_y);
554:       acolidx += 8; aval += 8;
555:       AVX512_Mult_Private(vec_idx2,vec_x2,vec_vals2,vec_y2);
556:       acolidx += 8; aval += 8;
557:       AVX512_Mult_Private(vec_idx3,vec_x3,vec_vals3,vec_y3);
558:       acolidx += 8; aval += 8;
559:       j += 3;
560:       break;
561:     case 2:
562:       AVX512_Mult_Private(vec_idx,vec_x,vec_vals,vec_y);
563:       acolidx += 8; aval += 8;
564:       AVX512_Mult_Private(vec_idx2,vec_x2,vec_vals2,vec_y2);
565:       acolidx += 8; aval += 8;
566:       j += 2;
567:       break;
568:     case 1:
569:       AVX512_Mult_Private(vec_idx,vec_x,vec_vals,vec_y);
570:       acolidx += 8; aval += 8;
571:       j += 1;
572:       break;
573:     }
574:     #pragma novector
575:     for (; j<(a->sliidx[i+1]>>3); j+=4) {
576:       AVX512_Mult_Private(vec_idx,vec_x,vec_vals,vec_y);
577:       acolidx += 8; aval += 8;
578:       AVX512_Mult_Private(vec_idx2,vec_x2,vec_vals2,vec_y2);
579:       acolidx += 8; aval += 8;
580:       AVX512_Mult_Private(vec_idx3,vec_x3,vec_vals3,vec_y3);
581:       acolidx += 8; aval += 8;
582:       AVX512_Mult_Private(vec_idx4,vec_x4,vec_vals4,vec_y4);
583:       acolidx += 8; aval += 8;
584:     }

586:     vec_y = _mm512_add_pd(vec_y,vec_y2);
587:     vec_y = _mm512_add_pd(vec_y,vec_y3);
588:     vec_y = _mm512_add_pd(vec_y,vec_y4);
589:     if (i == totalslices-1 && A->rmap->n & 0x07) { /* if last slice has padding rows */
590:       _mm512_mask_storeu_pd(&z[8*i],mask,vec_y);
591:     } else {
592:       _mm512_storeu_pd(&z[8*i],vec_y);
593:     }
594:   }
595: #elif defined(PETSC_HAVE_IMMINTRIN_H) && defined(__AVX__) && defined(PETSC_USE_REAL_DOUBLE) && !defined(PETSC_USE_COMPLEX) && !defined(PETSC_USE_64BIT_INDICES)
596:   for (i=0; i<totalslices; i++) { /* loop over full slices */
597:     PetscPrefetchBlock(acolidx,a->sliidx[i+1]-a->sliidx[i],0,PETSC_PREFETCH_HINT_T0);
598:     PetscPrefetchBlock(aval,a->sliidx[i+1]-a->sliidx[i],0,PETSC_PREFETCH_HINT_T0);

600:     /* last slice may have padding rows. Don't use vectorization. */
601:     if (i == totalslices-1 && (A->rmap->n & 0x07)) {
602:       for (r=0; r<(A->rmap->n & 0x07); ++r) {
603:         row        = 8*i + r;
604:         yval       = (MatScalar)0.0;
605:         nnz_in_row = a->rlen[row];
606:         for (j=0; j<nnz_in_row; ++j) yval += aval[8*j+r] * x[acolidx[8*j+r]];
607:         z[row] = y[row] + yval;
608:       }
609:       break;
610:     }

612:     vec_y  = _mm256_loadu_pd(y+8*i);
613:     vec_y2 = _mm256_loadu_pd(y+8*i+4);

615:     /* Process slice of height 8 (512 bits) via two subslices of height 4 (256 bits) via AVX */
616:     for (j=a->sliidx[i]; j<a->sliidx[i+1]; j+=8) {
617:       vec_vals  = _mm256_loadu_pd(aval);
618:       vec_x_tmp = _mm_loadl_pd(vec_x_tmp, x + *acolidx++);
619:       vec_x_tmp = _mm_loadh_pd(vec_x_tmp, x + *acolidx++);
620:       vec_x     = _mm256_insertf128_pd(vec_x,vec_x_tmp,0);
621:       vec_x_tmp = _mm_loadl_pd(vec_x_tmp, x + *acolidx++);
622:       vec_x_tmp = _mm_loadh_pd(vec_x_tmp, x + *acolidx++);
623:       vec_x     = _mm256_insertf128_pd(vec_x,vec_x_tmp,1);
624:       vec_y     = _mm256_add_pd(_mm256_mul_pd(vec_x,vec_vals),vec_y);
625:       aval     += 4;

627:       vec_vals  = _mm256_loadu_pd(aval);
628:       vec_x_tmp = _mm_loadl_pd(vec_x_tmp, x + *acolidx++);
629:       vec_x_tmp = _mm_loadh_pd(vec_x_tmp, x + *acolidx++);
630:       vec_x     = _mm256_insertf128_pd(vec_x,vec_x_tmp,0);
631:       vec_x_tmp = _mm_loadl_pd(vec_x_tmp, x + *acolidx++);
632:       vec_x_tmp = _mm_loadh_pd(vec_x_tmp, x + *acolidx++);
633:       vec_x     = _mm256_insertf128_pd(vec_x,vec_x_tmp,1);
634:       vec_y2    = _mm256_add_pd(_mm256_mul_pd(vec_x,vec_vals),vec_y2);
635:       aval     += 4;
636:     }

638:     _mm256_storeu_pd(z+i*8,vec_y);
639:     _mm256_storeu_pd(z+i*8+4,vec_y2);
640:   }
641: #else
642:   for (i=0; i<totalslices; i++) { /* loop over slices */
643:     for (j=0; j<8; j++) sum[j] = 0.0;
644:     for (j=a->sliidx[i]; j<a->sliidx[i+1]; j+=8) {
645:       sum[0] += aval[j] * x[acolidx[j]];
646:       sum[1] += aval[j+1] * x[acolidx[j+1]];
647:       sum[2] += aval[j+2] * x[acolidx[j+2]];
648:       sum[3] += aval[j+3] * x[acolidx[j+3]];
649:       sum[4] += aval[j+4] * x[acolidx[j+4]];
650:       sum[5] += aval[j+5] * x[acolidx[j+5]];
651:       sum[6] += aval[j+6] * x[acolidx[j+6]];
652:       sum[7] += aval[j+7] * x[acolidx[j+7]];
653:     }
654:     if (i == totalslices-1 && (A->rmap->n & 0x07)) {
655:       for (j=0; j<(A->rmap->n & 0x07); j++) z[8*i+j] = y[8*i+j] + sum[j];
656:     } else {
657:       for (j=0; j<8; j++) z[8*i+j] = y[8*i+j] + sum[j];
658:     }
659:   }
660: #endif

662:   PetscLogFlops(2.0*a->nz);
663:   VecRestoreArrayRead(xx,&x);
664:   VecRestoreArrayPair(yy,zz,&y,&z);
665:   return(0);
666: }

668: PetscErrorCode MatMultTransposeAdd_SeqSELL(Mat A,Vec xx,Vec zz,Vec yy)
669: {
670:   Mat_SeqSELL       *a=(Mat_SeqSELL*)A->data;
671:   PetscScalar       *y;
672:   const PetscScalar *x;
673:   const MatScalar   *aval=a->val;
674:   const PetscInt    *acolidx=a->colidx;
675:   PetscInt          i,j,r,row,nnz_in_row,totalslices=a->totalslices;
676:   PetscErrorCode    ierr;

678: #if defined(PETSC_HAVE_PRAGMA_DISJOINT)
679: #pragma disjoint(*x,*y,*aval)
680: #endif

683:   if (A->symmetric) {
684:     MatMultAdd_SeqSELL(A,xx,zz,yy);
685:     return(0);
686:   }
687:   if (zz != yy) { VecCopy(zz,yy); }
688:   VecGetArrayRead(xx,&x);
689:   VecGetArray(yy,&y);
690:   for (i=0; i<a->totalslices; i++) { /* loop over slices */
691:     if (i == totalslices-1 && (A->rmap->n & 0x07)) {
692:       for (r=0; r<(A->rmap->n & 0x07); ++r) {
693:         row        = 8*i + r;
694:         nnz_in_row = a->rlen[row];
695:         for (j=0; j<nnz_in_row; ++j) y[acolidx[8*j+r]] += aval[8*j+r] * x[row];
696:       }
697:       break;
698:     }
699:     for (j=a->sliidx[i]; j<a->sliidx[i+1]; j+=8) {
700:       y[acolidx[j]]   += aval[j] * x[8*i];
701:       y[acolidx[j+1]] += aval[j+1] * x[8*i+1];
702:       y[acolidx[j+2]] += aval[j+2] * x[8*i+2];
703:       y[acolidx[j+3]] += aval[j+3] * x[8*i+3];
704:       y[acolidx[j+4]] += aval[j+4] * x[8*i+4];
705:       y[acolidx[j+5]] += aval[j+5] * x[8*i+5];
706:       y[acolidx[j+6]] += aval[j+6] * x[8*i+6];
707:       y[acolidx[j+7]] += aval[j+7] * x[8*i+7];
708:     }
709:   }
710:   PetscLogFlops(2.0*a->sliidx[a->totalslices]);
711:   VecRestoreArrayRead(xx,&x);
712:   VecRestoreArray(yy,&y);
713:   return(0);
714: }

716: PetscErrorCode MatMultTranspose_SeqSELL(Mat A,Vec xx,Vec yy)
717: {

721:   if (A->symmetric) {
722:     MatMult_SeqSELL(A,xx,yy);
723:   } else {
724:     VecSet(yy,0.0);
725:     MatMultTransposeAdd_SeqSELL(A,xx,yy,yy);
726:   }
727:   return(0);
728: }

730: /*
731:      Checks for missing diagonals
732: */
733: PetscErrorCode MatMissingDiagonal_SeqSELL(Mat A,PetscBool  *missing,PetscInt *d)
734: {
735:   Mat_SeqSELL *a=(Mat_SeqSELL*)A->data;
736:   PetscInt    *diag,i;

739:   *missing = PETSC_FALSE;
740:   if (A->rmap->n > 0 && !(a->colidx)) {
741:     *missing = PETSC_TRUE;
742:     if (d) *d = 0;
743:     PetscInfo(A,"Matrix has no entries therefore is missing diagonal\n");
744:   } else {
745:     diag = a->diag;
746:     for (i=0; i<A->rmap->n; i++) {
747:       if (diag[i] == -1) {
748:         *missing = PETSC_TRUE;
749:         if (d) *d = i;
750:         PetscInfo1(A,"Matrix is missing diagonal number %D\n",i);
751:         break;
752:       }
753:     }
754:   }
755:   return(0);
756: }

758: PetscErrorCode MatMarkDiagonal_SeqSELL(Mat A)
759: {
760:   Mat_SeqSELL    *a=(Mat_SeqSELL*)A->data;
761:   PetscInt       i,j,m=A->rmap->n,shift;

765:   if (!a->diag) {
766:     PetscMalloc1(m,&a->diag);
767:     PetscLogObjectMemory((PetscObject)A,m*sizeof(PetscInt));
768:     a->free_diag = PETSC_TRUE;
769:   }
770:   for (i=0; i<m; i++) { /* loop over rows */
771:     shift = a->sliidx[i>>3]+(i&0x07); /* starting index of the row i */
772:     a->diag[i] = -1;
773:     for (j=0; j<a->rlen[i]; j++) {
774:       if (a->colidx[shift+j*8] == i) {
775:         a->diag[i] = shift+j*8;
776:         break;
777:       }
778:     }
779:   }
780:   return(0);
781: }

783: /*
784:   Negative shift indicates do not generate an error if there is a zero diagonal, just invert it anyways
785: */
786: PetscErrorCode MatInvertDiagonal_SeqSELL(Mat A,PetscScalar omega,PetscScalar fshift)
787: {
788:   Mat_SeqSELL    *a=(Mat_SeqSELL*) A->data;
789:   PetscInt       i,*diag,m = A->rmap->n;
790:   MatScalar      *val = a->val;
791:   PetscScalar    *idiag,*mdiag;

795:   if (a->idiagvalid) return(0);
796:   MatMarkDiagonal_SeqSELL(A);
797:   diag = a->diag;
798:   if (!a->idiag) {
799:     PetscMalloc3(m,&a->idiag,m,&a->mdiag,m,&a->ssor_work);
800:     PetscLogObjectMemory((PetscObject)A, 3*m*sizeof(PetscScalar));
801:     val  = a->val;
802:   }
803:   mdiag = a->mdiag;
804:   idiag = a->idiag;

806:   if (omega == 1.0 && PetscRealPart(fshift) <= 0.0) {
807:     for (i=0; i<m; i++) {
808:       mdiag[i] = val[diag[i]];
809:       if (!PetscAbsScalar(mdiag[i])) { /* zero diagonal */
810:         if (PetscRealPart(fshift)) {
811:           PetscInfo1(A,"Zero diagonal on row %D\n",i);
812:           A->factorerrortype             = MAT_FACTOR_NUMERIC_ZEROPIVOT;
813:           A->factorerror_zeropivot_value = 0.0;
814:           A->factorerror_zeropivot_row   = i;
815:         } else SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_INCOMP,"Zero diagonal on row %D",i);
816:       }
817:       idiag[i] = 1.0/val[diag[i]];
818:     }
819:     PetscLogFlops(m);
820:   } else {
821:     for (i=0; i<m; i++) {
822:       mdiag[i] = val[diag[i]];
823:       idiag[i] = omega/(fshift + val[diag[i]]);
824:     }
825:     PetscLogFlops(2.0*m);
826:   }
827:   a->idiagvalid = PETSC_TRUE;
828:   return(0);
829: }

831: PetscErrorCode MatZeroEntries_SeqSELL(Mat A)
832: {
833:   Mat_SeqSELL    *a=(Mat_SeqSELL*)A->data;

837:   PetscMemzero(a->val,(a->sliidx[a->totalslices])*sizeof(PetscScalar));
838:   MatSeqSELLInvalidateDiagonal(A);
839:   return(0);
840: }

842: PetscErrorCode MatDestroy_SeqSELL(Mat A)
843: {
844:   Mat_SeqSELL    *a=(Mat_SeqSELL*)A->data;

848: #if defined(PETSC_USE_LOG)
849:   PetscLogObjectState((PetscObject)A,"Rows=%D, Cols=%D, NZ=%D",A->rmap->n,A->cmap->n,a->nz);
850: #endif
851:   MatSeqXSELLFreeSELL(A,&a->val,&a->colidx);
852:   ISDestroy(&a->row);
853:   ISDestroy(&a->col);
854:   PetscFree(a->diag);
855:   PetscFree(a->rlen);
856:   PetscFree(a->sliidx);
857:   PetscFree3(a->idiag,a->mdiag,a->ssor_work);
858:   PetscFree(a->solve_work);
859:   ISDestroy(&a->icol);
860:   PetscFree(a->saved_values);
861:   PetscFree2(a->getrowcols,a->getrowvals);

863:   PetscFree(A->data);

865:   PetscObjectChangeTypeName((PetscObject)A,0);
866:   PetscObjectComposeFunction((PetscObject)A,"MatStoreValues_C",NULL);
867:   PetscObjectComposeFunction((PetscObject)A,"MatRetrieveValues_C",NULL);
868: #if defined(PETSC_HAVE_ELEMENTAL)
869: #endif
870:   PetscObjectComposeFunction((PetscObject)A,"MatSeqSELLSetPreallocation_C",NULL);
871:   return(0);
872: }

874: PetscErrorCode MatSetOption_SeqSELL(Mat A,MatOption op,PetscBool flg)
875: {
876:   Mat_SeqSELL    *a=(Mat_SeqSELL*)A->data;

880:   switch (op) {
881:   case MAT_ROW_ORIENTED:
882:     a->roworiented = flg;
883:     break;
884:   case MAT_KEEP_NONZERO_PATTERN:
885:     a->keepnonzeropattern = flg;
886:     break;
887:   case MAT_NEW_NONZERO_LOCATIONS:
888:     a->nonew = (flg ? 0 : 1);
889:     break;
890:   case MAT_NEW_NONZERO_LOCATION_ERR:
891:     a->nonew = (flg ? -1 : 0);
892:     break;
893:   case MAT_NEW_NONZERO_ALLOCATION_ERR:
894:     a->nonew = (flg ? -2 : 0);
895:     break;
896:   case MAT_UNUSED_NONZERO_LOCATION_ERR:
897:     a->nounused = (flg ? -1 : 0);
898:     break;
899:   case MAT_NEW_DIAGONALS:
900:   case MAT_IGNORE_OFF_PROC_ENTRIES:
901:   case MAT_USE_HASH_TABLE:
902:     PetscInfo1(A,"Option %s ignored\n",MatOptions[op]);
903:     break;
904:   case MAT_SPD:
905:   case MAT_SYMMETRIC:
906:   case MAT_STRUCTURALLY_SYMMETRIC:
907:   case MAT_HERMITIAN:
908:   case MAT_SYMMETRY_ETERNAL:
909:     /* These options are handled directly by MatSetOption() */
910:     break;
911:   default:
912:     SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_SUP,"unknown option %d",op);
913:   }
914:   return(0);
915: }

917: PetscErrorCode MatGetDiagonal_SeqSELL(Mat A,Vec v)
918: {
919:   Mat_SeqSELL    *a=(Mat_SeqSELL*)A->data;
920:   PetscInt       i,j,n,shift;
921:   PetscScalar    *x,zero=0.0;

925:   VecGetLocalSize(v,&n);
926:   if (n != A->rmap->n) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"Nonconforming matrix and vector");

928:   if (A->factortype == MAT_FACTOR_ILU || A->factortype == MAT_FACTOR_LU) {
929:     PetscInt *diag=a->diag;
930:     VecGetArray(v,&x);
931:     for (i=0; i<n; i++) x[i] = 1.0/a->val[diag[i]];
932:     VecRestoreArray(v,&x);
933:     return(0);
934:   }

936:   VecSet(v,zero);
937:   VecGetArray(v,&x);
938:   for (i=0; i<n; i++) { /* loop over rows */
939:     shift = a->sliidx[i>>3]+(i&0x07); /* starting index of the row i */
940:     x[i] = 0;
941:     for (j=0; j<a->rlen[i]; j++) {
942:       if (a->colidx[shift+j*8] == i) {
943:         x[i] = a->val[shift+j*8];
944:         break;
945:       }
946:     }
947:   }
948:   VecRestoreArray(v,&x);
949:   return(0);
950: }

952: PetscErrorCode MatDiagonalScale_SeqSELL(Mat A,Vec ll,Vec rr)
953: {
954:   Mat_SeqSELL       *a=(Mat_SeqSELL*)A->data;
955:   const PetscScalar *l,*r;
956:   PetscInt          i,j,m,n,row;
957:   PetscErrorCode    ierr;

960:   if (ll) {
961:     /* The local size is used so that VecMPI can be passed to this routine
962:        by MatDiagonalScale_MPISELL */
963:     VecGetLocalSize(ll,&m);
964:     if (m != A->rmap->n) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"Left scaling vector wrong length");
965:     VecGetArrayRead(ll,&l);
966:     for (i=0; i<a->totalslices; i++) { /* loop over slices */
967:       for (j=a->sliidx[i],row=0; j<a->sliidx[i+1]; j++,row=((row+1)&0x07)) {
968:         a->val[j] *= l[8*i+row];
969:       }
970:     }
971:     VecRestoreArrayRead(ll,&l);
972:     PetscLogFlops(a->nz);
973:   }
974:   if (rr) {
975:     VecGetLocalSize(rr,&n);
976:     if (n != A->cmap->n) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"Right scaling vector wrong length");
977:     VecGetArrayRead(rr,&r);
978:     for (i=0; i<a->totalslices; i++) { /* loop over slices */
979:       for (j=a->sliidx[i]; j<a->sliidx[i+1]; j++) {
980:         a->val[j] *= r[a->colidx[j]];
981:       }
982:     }
983:     VecRestoreArrayRead(rr,&r);
984:     PetscLogFlops(a->nz);
985:   }
986:   MatSeqSELLInvalidateDiagonal(A);
987:   return(0);
988: }

990: extern PetscErrorCode MatSetValues_SeqSELL(Mat,PetscInt,const PetscInt[],PetscInt,const PetscInt[],const PetscScalar[],InsertMode);

992: PetscErrorCode MatGetValues_SeqSELL(Mat A,PetscInt m,const PetscInt im[],PetscInt n,const PetscInt in[],PetscScalar v[])
993: {
994:   Mat_SeqSELL *a=(Mat_SeqSELL*)A->data;
995:   PetscInt    *cp,i,k,low,high,t,row,col,l;
996:   PetscInt    shift;
997:   MatScalar   *vp;

1000:   for (k=0; k<m; k++) { /* loop over requested rows */
1001:     row = im[k];
1002:     if (row<0) continue;
1003: #if defined(PETSC_USE_DEBUG)
1004:     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);
1005: #endif
1006:     shift = a->sliidx[row>>3]+(row&0x07); /* starting index of the row */
1007:     cp = a->colidx+shift; /* pointer to the row */
1008:     vp = a->val+shift; /* pointer to the row */
1009:     for (l=0; l<n; l++) { /* loop over requested columns */
1010:       col = in[l];
1011:       if (col<0) continue;
1012: #if defined(PETSC_USE_DEBUG)
1013:       if (col >= A->cmap->n) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Column too large: row %D max %D",col,A->cmap->n-1);
1014: #endif
1015:       high = a->rlen[row]; low = 0; /* assume unsorted */
1016:       while (high-low > 5) {
1017:         t = (low+high)/2;
1018:         if (*(cp+t*8) > col) high = t;
1019:         else low = t;
1020:       }
1021:       for (i=low; i<high; i++) {
1022:         if (*(cp+8*i) > col) break;
1023:         if (*(cp+8*i) == col) {
1024:           *v++ = *(vp+8*i);
1025:           goto finished;
1026:         }
1027:       }
1028:       *v++ = 0.0;
1029:     finished:;
1030:     }
1031:   }
1032:   return(0);
1033: }

1035: PetscErrorCode MatView_SeqSELL_ASCII(Mat A,PetscViewer viewer)
1036: {
1037:   Mat_SeqSELL       *a=(Mat_SeqSELL*)A->data;
1038:   PetscInt          i,j,m=A->rmap->n,shift;
1039:   const char        *name;
1040:   PetscViewerFormat format;
1041:   PetscErrorCode    ierr;

1044:   PetscViewerGetFormat(viewer,&format);
1045:   if (format == PETSC_VIEWER_ASCII_MATLAB) {
1046:     PetscInt nofinalvalue = 0;
1047:     /*
1048:     if (m && ((a->i[m] == a->i[m-1]) || (a->j[a->nz-1] != A->cmap->n-1))) {
1049:       nofinalvalue = 1;
1050:     }
1051:     */
1052:     PetscViewerASCIIUseTabs(viewer,PETSC_FALSE);
1053:     PetscViewerASCIIPrintf(viewer,"%% Size = %D %D \n",m,A->cmap->n);
1054:     PetscViewerASCIIPrintf(viewer,"%% Nonzeros = %D \n",a->nz);
1055: #if defined(PETSC_USE_COMPLEX)
1056:     PetscViewerASCIIPrintf(viewer,"zzz = zeros(%D,4);\n",a->nz+nofinalvalue);
1057: #else
1058:     PetscViewerASCIIPrintf(viewer,"zzz = zeros(%D,3);\n",a->nz+nofinalvalue);
1059: #endif
1060:     PetscViewerASCIIPrintf(viewer,"zzz = [\n");

1062:     for (i=0; i<m; i++) {
1063:       shift = a->sliidx[i>>3]+(i&0x07);
1064:       for (j=0; j<a->rlen[i]; j++) {
1065: #if defined(PETSC_USE_COMPLEX)
1066:         PetscViewerASCIIPrintf(viewer,"%D %D  %18.16e %18.16e\n",i+1,a->colidx[shift+8*j]+1,(double)PetscRealPart(a->val[shift+8*j]),(double)PetscImaginaryPart(a->val[shift+8*j]));
1067: #else
1068:         PetscViewerASCIIPrintf(viewer,"%D %D  %18.16e\n",i+1,a->colidx[shift+8*j]+1,(double)a->val[shift+8*j]);
1069: #endif
1070:       }
1071:     }
1072:     /*
1073:     if (nofinalvalue) {
1074: #if defined(PETSC_USE_COMPLEX)
1075:       PetscViewerASCIIPrintf(viewer,"%D %D  %18.16e %18.16e\n",m,A->cmap->n,0.,0.);
1076: #else
1077:       PetscViewerASCIIPrintf(viewer,"%D %D  %18.16e\n",m,A->cmap->n,0.0);
1078: #endif
1079:     }
1080:     */
1081:     PetscObjectGetName((PetscObject)A,&name);
1082:     PetscViewerASCIIPrintf(viewer,"];\n %s = spconvert(zzz);\n",name);
1083:     PetscViewerASCIIUseTabs(viewer,PETSC_TRUE);
1084:   } else if (format == PETSC_VIEWER_ASCII_FACTOR_INFO || format == PETSC_VIEWER_ASCII_INFO) {
1085:     return(0);
1086:   } else if (format == PETSC_VIEWER_ASCII_COMMON) {
1087:     PetscViewerASCIIUseTabs(viewer,PETSC_FALSE);
1088:     for (i=0; i<m; i++) {
1089:       PetscViewerASCIIPrintf(viewer,"row %D:",i);
1090:       shift = a->sliidx[i>>3]+(i&0x07);
1091:       for (j=0; j<a->rlen[i]; j++) {
1092: #if defined(PETSC_USE_COMPLEX)
1093:         if (PetscImaginaryPart(a->val[shift+8*j]) > 0.0 && PetscRealPart(a->val[shift+8*j]) != 0.0) {
1094:           PetscViewerASCIIPrintf(viewer," (%D, %g + %g i)",a->colidx[shift+8*j],(double)PetscRealPart(a->val[shift+8*j]),(double)PetscImaginaryPart(a->val[shift+8*j]));
1095:         } else if (PetscImaginaryPart(a->val[shift+8*j]) < 0.0 && PetscRealPart(a->val[shift+8*j]) != 0.0) {
1096:           PetscViewerASCIIPrintf(viewer," (%D, %g - %g i)",a->colidx[shift+8*j],(double)PetscRealPart(a->val[shift+8*j]),(double)-PetscImaginaryPart(a->val[shift+8*j]));
1097:         } else if (PetscRealPart(a->val[shift+8*j]) != 0.0) {
1098:           PetscViewerASCIIPrintf(viewer," (%D, %g) ",a->colidx[shift+8*j],(double)PetscRealPart(a->val[shift+8*j]));
1099:         }
1100: #else
1101:         if (a->val[shift+8*j] != 0.0) {PetscViewerASCIIPrintf(viewer," (%D, %g) ",a->colidx[shift+8*j],(double)a->val[shift+8*j]);}
1102: #endif
1103:       }
1104:       PetscViewerASCIIPrintf(viewer,"\n");
1105:     }
1106:     PetscViewerASCIIUseTabs(viewer,PETSC_TRUE);
1107:   } else if (format == PETSC_VIEWER_ASCII_DENSE) {
1108:     PetscInt    cnt=0,jcnt;
1109:     PetscScalar value;
1110: #if defined(PETSC_USE_COMPLEX)
1111:     PetscBool   realonly=PETSC_TRUE;
1112:     for (i=0; i<a->sliidx[a->totalslices]; i++) {
1113:       if (PetscImaginaryPart(a->val[i]) != 0.0) {
1114:         realonly = PETSC_FALSE;
1115:         break;
1116:       }
1117:     }
1118: #endif

1120:     PetscViewerASCIIUseTabs(viewer,PETSC_FALSE);
1121:     for (i=0; i<m; i++) {
1122:       jcnt = 0;
1123:       shift = a->sliidx[i>>3]+(i&0x07);
1124:       for (j=0; j<A->cmap->n; j++) {
1125:         if (jcnt < a->rlen[i] && j == a->colidx[shift+8*j]) {
1126:           value = a->val[cnt++];
1127:           jcnt++;
1128:         } else {
1129:           value = 0.0;
1130:         }
1131: #if defined(PETSC_USE_COMPLEX)
1132:         if (realonly) {
1133:           PetscViewerASCIIPrintf(viewer," %7.5e ",(double)PetscRealPart(value));
1134:         } else {
1135:           PetscViewerASCIIPrintf(viewer," %7.5e+%7.5e i ",(double)PetscRealPart(value),(double)PetscImaginaryPart(value));
1136:         }
1137: #else
1138:         PetscViewerASCIIPrintf(viewer," %7.5e ",(double)value);
1139: #endif
1140:       }
1141:       PetscViewerASCIIPrintf(viewer,"\n");
1142:     }
1143:     PetscViewerASCIIUseTabs(viewer,PETSC_TRUE);
1144:   } else if (format == PETSC_VIEWER_ASCII_MATRIXMARKET) {
1145:     PetscInt fshift=1;
1146:     PetscViewerASCIIUseTabs(viewer,PETSC_FALSE);
1147: #if defined(PETSC_USE_COMPLEX)
1148:     PetscViewerASCIIPrintf(viewer,"%%%%MatrixMarket matrix coordinate complex general\n");
1149: #else
1150:     PetscViewerASCIIPrintf(viewer,"%%%%MatrixMarket matrix coordinate real general\n");
1151: #endif
1152:     PetscViewerASCIIPrintf(viewer,"%D %D %D\n", m, A->cmap->n, a->nz);
1153:     for (i=0; i<m; i++) {
1154:       shift = a->sliidx[i>>3]+(i&0x07);
1155:       for (j=0; j<a->rlen[i]; j++) {
1156: #if defined(PETSC_USE_COMPLEX)
1157:         PetscViewerASCIIPrintf(viewer,"%D %D %g %g\n",i+fshift,a->colidx[shift+8*j]+fshift,(double)PetscRealPart(a->val[shift+8*j]),(double)PetscImaginaryPart(a->val[shift+8*j]));
1158: #else
1159:         PetscViewerASCIIPrintf(viewer,"%D %D %g\n",i+fshift,a->colidx[shift+8*j]+fshift,(double)a->val[shift+8*j]);
1160: #endif
1161:       }
1162:     }
1163:     PetscViewerASCIIUseTabs(viewer,PETSC_TRUE);
1164:   } else if (format == PETSC_VIEWER_NATIVE) {
1165:     for (i=0; i<a->totalslices; i++) { /* loop over slices */
1166:       PetscInt row;
1167:       PetscViewerASCIIPrintf(viewer,"slice %D: %D %D\n",i,a->sliidx[i],a->sliidx[i+1]);
1168:       for (j=a->sliidx[i],row=0; j<a->sliidx[i+1]; j++,row=((row+1)&0x07)) {
1169: #if defined(PETSC_USE_COMPLEX)
1170:         if (PetscImaginaryPart(a->val[j]) > 0.0) {
1171:           PetscViewerASCIIPrintf(viewer,"  %D %D %g + %g i\n",8*i+row,a->colidx[j],(double)PetscRealPart(a->val[j]),(double)PetscImaginaryPart(a->val[j]));
1172:         } else if (PetscImaginaryPart(a->val[j]) < 0.0) {
1173:           PetscViewerASCIIPrintf(viewer,"  %D %D %g - %g i\n",8*i+row,a->colidx[j],(double)PetscRealPart(a->val[j]),-(double)PetscImaginaryPart(a->val[j]));
1174:         } else {
1175:           PetscViewerASCIIPrintf(viewer,"  %D %D %g\n",8*i+row,a->colidx[j],(double)PetscRealPart(a->val[j]));
1176:         }
1177: #else
1178:         PetscViewerASCIIPrintf(viewer,"  %D %D %g\n",8*i+row,a->colidx[j],(double)a->val[j]);
1179: #endif
1180:       }
1181:     }
1182:   } else {
1183:     PetscViewerASCIIUseTabs(viewer,PETSC_FALSE);
1184:     if (A->factortype) {
1185:       for (i=0; i<m; i++) {
1186:         shift = a->sliidx[i>>3]+(i&0x07);
1187:         PetscViewerASCIIPrintf(viewer,"row %D:",i);
1188:         /* L part */
1189:         for (j=shift; j<a->diag[i]; j+=8) {
1190: #if defined(PETSC_USE_COMPLEX)
1191:           if (PetscImaginaryPart(a->val[shift+8*j]) > 0.0) {
1192:             PetscViewerASCIIPrintf(viewer," (%D, %g + %g i)",a->colidx[j],(double)PetscRealPart(a->val[j]),(double)PetscImaginaryPart(a->val[j]));
1193:           } else if (PetscImaginaryPart(a->val[shift+8*j]) < 0.0) {
1194:             PetscViewerASCIIPrintf(viewer," (%D, %g - %g i)",a->colidx[j],(double)PetscRealPart(a->val[j]),(double)(-PetscImaginaryPart(a->val[j])));
1195:           } else {
1196:             PetscViewerASCIIPrintf(viewer," (%D, %g) ",a->colidx[j],(double)PetscRealPart(a->val[j]));
1197:           }
1198: #else
1199:           PetscViewerASCIIPrintf(viewer," (%D, %g) ",a->colidx[j],(double)a->val[j]);
1200: #endif
1201:         }
1202:         /* diagonal */
1203:         j = a->diag[i];
1204: #if defined(PETSC_USE_COMPLEX)
1205:         if (PetscImaginaryPart(a->val[j]) > 0.0) {
1206:           PetscViewerASCIIPrintf(viewer," (%D, %g + %g i)",a->colidx[j],(double)PetscRealPart(1.0/a->val[j]),(double)PetscImaginaryPart(1.0/a->val[j]));
1207:         } else if (PetscImaginaryPart(a->val[j]) < 0.0) {
1208:           PetscViewerASCIIPrintf(viewer," (%D, %g - %g i)",a->colidx[j],(double)PetscRealPart(1.0/a->val[j]),(double)(-PetscImaginaryPart(1.0/a->val[j])));
1209:         } else {
1210:           PetscViewerASCIIPrintf(viewer," (%D, %g) ",a->colidx[j],(double)PetscRealPart(1.0/a->val[j]));
1211:         }
1212: #else
1213:         PetscViewerASCIIPrintf(viewer," (%D, %g) ",a->colidx[j],(double)(1.0/a->val[j]));
1214: #endif

1216:         /* U part */
1217:         for (j=a->diag[i]+1; j<shift+8*a->rlen[i]; j+=8) {
1218: #if defined(PETSC_USE_COMPLEX)
1219:           if (PetscImaginaryPart(a->val[j]) > 0.0) {
1220:             PetscViewerASCIIPrintf(viewer," (%D, %g + %g i)",a->colidx[j],(double)PetscRealPart(a->val[j]),(double)PetscImaginaryPart(a->val[j]));
1221:           } else if (PetscImaginaryPart(a->val[j]) < 0.0) {
1222:             PetscViewerASCIIPrintf(viewer," (%D, %g - %g i)",a->colidx[j],(double)PetscRealPart(a->val[j]),(double)(-PetscImaginaryPart(a->val[j])));
1223:           } else {
1224:             PetscViewerASCIIPrintf(viewer," (%D, %g) ",a->colidx[j],(double)PetscRealPart(a->val[j]));
1225:           }
1226: #else
1227:           PetscViewerASCIIPrintf(viewer," (%D, %g) ",a->colidx[j],(double)a->val[j]);
1228: #endif
1229:         }
1230:         PetscViewerASCIIPrintf(viewer,"\n");
1231:       }
1232:     } else {
1233:       for (i=0; i<m; i++) {
1234:         shift = a->sliidx[i>>3]+(i&0x07);
1235:         PetscViewerASCIIPrintf(viewer,"row %D:",i);
1236:         for (j=0; j<a->rlen[i]; j++) {
1237: #if defined(PETSC_USE_COMPLEX)
1238:           if (PetscImaginaryPart(a->val[j]) > 0.0) {
1239:             PetscViewerASCIIPrintf(viewer," (%D, %g + %g i)",a->colidx[shift+8*j],(double)PetscRealPart(a->val[shift+8*j]),(double)PetscImaginaryPart(a->val[shift+8*j]));
1240:           } else if (PetscImaginaryPart(a->val[j]) < 0.0) {
1241:             PetscViewerASCIIPrintf(viewer," (%D, %g - %g i)",a->colidx[shift+8*j],(double)PetscRealPart(a->val[shift+8*j]),(double)-PetscImaginaryPart(a->val[shift+8*j]));
1242:           } else {
1243:             PetscViewerASCIIPrintf(viewer," (%D, %g) ",a->colidx[shift+8*j],(double)PetscRealPart(a->val[shift+8*j]));
1244:           }
1245: #else
1246:           PetscViewerASCIIPrintf(viewer," (%D, %g) ",a->colidx[shift+8*j],(double)a->val[shift+8*j]);
1247: #endif
1248:         }
1249:         PetscViewerASCIIPrintf(viewer,"\n");
1250:       }
1251:     }
1252:     PetscViewerASCIIUseTabs(viewer,PETSC_TRUE);
1253:   }
1254:   PetscViewerFlush(viewer);
1255:   return(0);
1256: }

1258:  #include <petscdraw.h>
1259: PetscErrorCode MatView_SeqSELL_Draw_Zoom(PetscDraw draw,void *Aa)
1260: {
1261:   Mat               A=(Mat)Aa;
1262:   Mat_SeqSELL       *a=(Mat_SeqSELL*)A->data;
1263:   PetscInt          i,j,m=A->rmap->n,shift;
1264:   int               color;
1265:   PetscReal         xl,yl,xr,yr,x_l,x_r,y_l,y_r;
1266:   PetscViewer       viewer;
1267:   PetscViewerFormat format;
1268:   PetscErrorCode    ierr;

1271:   PetscObjectQuery((PetscObject)A,"Zoomviewer",(PetscObject*)&viewer);
1272:   PetscViewerGetFormat(viewer,&format);
1273:   PetscDrawGetCoordinates(draw,&xl,&yl,&xr,&yr);

1275:   /* loop over matrix elements drawing boxes */

1277:   if (format != PETSC_VIEWER_DRAW_CONTOUR) {
1278:     PetscDrawCollectiveBegin(draw);
1279:     /* Blue for negative, Cyan for zero and  Red for positive */
1280:     color = PETSC_DRAW_BLUE;
1281:     for (i=0; i<m; i++) {
1282:       shift = a->sliidx[i>>3]+(i&0x07); /* starting index of the row i */
1283:       y_l = m - i - 1.0; y_r = y_l + 1.0;
1284:       for (j=0; j<a->rlen[i]; j++) {
1285:         x_l = a->colidx[shift+j*8]; x_r = x_l + 1.0;
1286:         if (PetscRealPart(a->val[shift+8*j]) >=  0.) continue;
1287:         PetscDrawRectangle(draw,x_l,y_l,x_r,y_r,color,color,color,color);
1288:       }
1289:     }
1290:     color = PETSC_DRAW_CYAN;
1291:     for (i=0; i<m; i++) {
1292:       shift = a->sliidx[i>>3]+(i&0x07);
1293:       y_l = m - i - 1.0; y_r = y_l + 1.0;
1294:       for (j=0; j<a->rlen[i]; j++) {
1295:         x_l = a->colidx[shift+j*8]; x_r = x_l + 1.0;
1296:         if (a->val[shift+8*j] !=  0.) continue;
1297:         PetscDrawRectangle(draw,x_l,y_l,x_r,y_r,color,color,color,color);
1298:       }
1299:     }
1300:     color = PETSC_DRAW_RED;
1301:     for (i=0; i<m; i++) {
1302:       shift = a->sliidx[i>>3]+(i&0x07);
1303:       y_l = m - i - 1.0; y_r = y_l + 1.0;
1304:       for (j=0; j<a->rlen[i]; j++) {
1305:         x_l = a->colidx[shift+j*8]; x_r = x_l + 1.0;
1306:         if (PetscRealPart(a->val[shift+8*j]) <=  0.) continue;
1307:         PetscDrawRectangle(draw,x_l,y_l,x_r,y_r,color,color,color,color);
1308:       }
1309:     }
1310:     PetscDrawCollectiveEnd(draw);
1311:   } else {
1312:     /* use contour shading to indicate magnitude of values */
1313:     /* first determine max of all nonzero values */
1314:     PetscReal minv=0.0,maxv=0.0;
1315:     PetscInt  count=0;
1316:     PetscDraw popup;
1317:     for (i=0; i<a->sliidx[a->totalslices]; i++) {
1318:       if (PetscAbsScalar(a->val[i]) > maxv) maxv = PetscAbsScalar(a->val[i]);
1319:     }
1320:     if (minv >= maxv) maxv = minv + PETSC_SMALL;
1321:     PetscDrawGetPopup(draw,&popup);
1322:     PetscDrawScalePopup(popup,minv,maxv);

1324:     PetscDrawCollectiveBegin(draw);
1325:     for (i=0; i<m; i++) {
1326:       shift = a->sliidx[i>>3]+(i&0x07);
1327:       y_l = m - i - 1.0;
1328:       y_r = y_l + 1.0;
1329:       for (j=0; j<a->rlen[i]; j++) {
1330:         x_l = a->colidx[shift+j*8];
1331:         x_r = x_l + 1.0;
1332:         color = PetscDrawRealToColor(PetscAbsScalar(a->val[count]),minv,maxv);
1333:         PetscDrawRectangle(draw,x_l,y_l,x_r,y_r,color,color,color,color);
1334:         count++;
1335:       }
1336:     }
1337:     PetscDrawCollectiveEnd(draw);
1338:   }
1339:   return(0);
1340: }

1342:  #include <petscdraw.h>
1343: PetscErrorCode MatView_SeqSELL_Draw(Mat A,PetscViewer viewer)
1344: {
1345:   PetscDraw      draw;
1346:   PetscReal      xr,yr,xl,yl,h,w;
1347:   PetscBool      isnull;

1351:   PetscViewerDrawGetDraw(viewer,0,&draw);
1352:   PetscDrawIsNull(draw,&isnull);
1353:   if (isnull) return(0);

1355:   xr   = A->cmap->n; yr  = A->rmap->n; h = yr/10.0; w = xr/10.0;
1356:   xr  += w;          yr += h;         xl = -w;     yl = -h;
1357:   PetscDrawSetCoordinates(draw,xl,yl,xr,yr);
1358:   PetscObjectCompose((PetscObject)A,"Zoomviewer",(PetscObject)viewer);
1359:   PetscDrawZoom(draw,MatView_SeqSELL_Draw_Zoom,A);
1360:   PetscObjectCompose((PetscObject)A,"Zoomviewer",NULL);
1361:   PetscDrawSave(draw);
1362:   return(0);
1363: }

1365: PetscErrorCode MatView_SeqSELL(Mat A,PetscViewer viewer)
1366: {
1367:   PetscBool      iascii,isbinary,isdraw;

1371:   PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERASCII,&iascii);
1372:   PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERBINARY,&isbinary);
1373:   PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERDRAW,&isdraw);
1374:   if (iascii) {
1375:     MatView_SeqSELL_ASCII(A,viewer);
1376:   } else if (isbinary) {
1377:     /* MatView_SeqSELL_Binary(A,viewer); */
1378:   } else if (isdraw) {
1379:     MatView_SeqSELL_Draw(A,viewer);
1380:   }
1381:   return(0);
1382: }

1384: PetscErrorCode MatAssemblyEnd_SeqSELL(Mat A,MatAssemblyType mode)
1385: {
1386:   Mat_SeqSELL    *a=(Mat_SeqSELL*)A->data;
1387:   PetscInt       i,shift,row_in_slice,row,nrow,*cp,lastcol,j,k;
1388:   MatScalar      *vp;

1392:   if (mode == MAT_FLUSH_ASSEMBLY) return(0);
1393:   /* To do: compress out the unused elements */
1394:   MatMarkDiagonal_SeqSELL(A);
1395:   PetscInfo6(A,"Matrix size: %D X %D; storage space: %D allocated %D used (%D nonzeros+%D paddedzeros)\n",A->rmap->n,A->cmap->n,a->maxallocmat,a->sliidx[a->totalslices],a->nz,a->sliidx[a->totalslices]-a->nz);
1396:   PetscInfo1(A,"Number of mallocs during MatSetValues() is %D\n",a->reallocs);
1397:   PetscInfo1(A,"Maximum nonzeros in any row is %D\n",a->rlenmax);
1398:   /* Set unused slots for column indices to last valid column index. Set unused slots for values to zero. This allows for a use of unmasked intrinsics -> higher performance */
1399:   for (i=0; i<a->totalslices; ++i) {
1400:     shift = a->sliidx[i];    /* starting index of the slice */
1401:     cp    = a->colidx+shift; /* pointer to the column indices of the slice */
1402:     vp    = a->val+shift;    /* pointer to the nonzero values of the slice */
1403:     for (row_in_slice=0; row_in_slice<8; ++row_in_slice) { /* loop over rows in the slice */
1404:       row  = 8*i + row_in_slice;
1405:       nrow = a->rlen[row]; /* number of nonzeros in row */
1406:       /*
1407:         Search for the nearest nonzero. Normally setting the index to zero may cause extra communication.
1408:         But if the entire slice are empty, it is fine to use 0 since the index will not be loaded.
1409:       */
1410:       lastcol = 0;
1411:       if (nrow>0) { /* nonempty row */
1412:         lastcol = cp[8*(nrow-1)+row_in_slice]; /* use the index from the last nonzero at current row */
1413:       } else if (!row_in_slice) { /* first row of the currect slice is empty */
1414:         for (j=1;j<8;j++) {
1415:           if (a->rlen[8*i+j]) {
1416:             lastcol = cp[j];
1417:             break;
1418:           }
1419:         }
1420:       } else {
1421:         if (a->sliidx[i+1] != shift) lastcol = cp[row_in_slice-1]; /* use the index from the previous row */
1422:       }

1424:       for (k=nrow; k<(a->sliidx[i+1]-shift)/8; ++k) {
1425:         cp[8*k+row_in_slice] = lastcol;
1426:         vp[8*k+row_in_slice] = (MatScalar)0;
1427:       }
1428:     }
1429:   }

1431:   A->info.mallocs += a->reallocs;
1432:   a->reallocs      = 0;

1434:   MatSeqSELLInvalidateDiagonal(A);
1435:   return(0);
1436: }

1438: PetscErrorCode MatGetInfo_SeqSELL(Mat A,MatInfoType flag,MatInfo *info)
1439: {
1440:   Mat_SeqSELL *a=(Mat_SeqSELL*)A->data;

1443:   info->block_size   = 1.0;
1444:   info->nz_allocated = (double)a->maxallocmat;
1445:   info->nz_used      = (double)a->sliidx[a->totalslices]; /* include padding zeros */
1446:   info->nz_unneeded  = (double)(a->maxallocmat-a->sliidx[a->totalslices]);
1447:   info->assemblies   = (double)A->num_ass;
1448:   info->mallocs      = (double)A->info.mallocs;
1449:   info->memory       = ((PetscObject)A)->mem;
1450:   if (A->factortype) {
1451:     info->fill_ratio_given  = A->info.fill_ratio_given;
1452:     info->fill_ratio_needed = A->info.fill_ratio_needed;
1453:     info->factor_mallocs    = A->info.factor_mallocs;
1454:   } else {
1455:     info->fill_ratio_given  = 0;
1456:     info->fill_ratio_needed = 0;
1457:     info->factor_mallocs    = 0;
1458:   }
1459:   return(0);
1460: }

1462: PetscErrorCode MatSetValues_SeqSELL(Mat A,PetscInt m,const PetscInt im[],PetscInt n,const PetscInt in[],const PetscScalar v[],InsertMode is)
1463: {
1464:   Mat_SeqSELL    *a=(Mat_SeqSELL*)A->data;
1465:   PetscInt       shift,i,k,l,low,high,t,ii,row,col,nrow;
1466:   PetscInt       *cp,nonew=a->nonew,lastcol=-1;
1467:   MatScalar      *vp,value;

1471:   for (k=0; k<m; k++) { /* loop over added rows */
1472:     row = im[k];
1473:     if (row < 0) continue;
1474: #if defined(PETSC_USE_DEBUG)
1475:     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);
1476: #endif
1477:     shift = a->sliidx[row>>3]+(row&0x07); /* starting index of the row */
1478:     cp    = a->colidx+shift; /* pointer to the row */
1479:     vp    = a->val+shift; /* pointer to the row */
1480:     nrow  = a->rlen[row];
1481:     low   = 0;
1482:     high  = nrow;

1484:     for (l=0; l<n; l++) { /* loop over added columns */
1485:       col = in[l];
1486:       if (col<0) continue;
1487: #if defined(PETSC_USE_DEBUG)
1488:       if (col >= A->cmap->n) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Col too large: row %D max %D",col,A->cmap->n-1);
1489: #endif
1490:       if (a->roworiented) {
1491:         value = v[l+k*n];
1492:       } else {
1493:         value = v[k+l*m];
1494:       }
1495:       if ((value == 0.0 && a->ignorezeroentries) && (is == ADD_VALUES)) continue;

1497:       /* search in this row for the specified colmun, i indicates the column to be set */
1498:       if (col <= lastcol) low = 0;
1499:       else high = nrow;
1500:       lastcol = col;
1501:       while (high-low > 5) {
1502:         t = (low+high)/2;
1503:         if (*(cp+t*8) > col) high = t;
1504:         else low = t;
1505:       }
1506:       for (i=low; i<high; i++) {
1507:         if (*(cp+i*8) > col) break;
1508:         if (*(cp+i*8) == col) {
1509:           if (is == ADD_VALUES) *(vp+i*8) += value;
1510:           else *(vp+i*8) = value;
1511:           low = i + 1;
1512:           goto noinsert;
1513:         }
1514:       }
1515:       if (value == 0.0 && a->ignorezeroentries) goto noinsert;
1516:       if (nonew == 1) goto noinsert;
1517:       if (nonew == -1) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Inserting a new nonzero (%D, %D) in the matrix", row, col);
1518:       /* If the current row length exceeds the slice width (e.g. nrow==slice_width), allocate a new space, otherwise do nothing */
1519:       MatSeqXSELLReallocateSELL(A,A->rmap->n,1,nrow,a->sliidx,row/8,row,col,a->colidx,a->val,cp,vp,nonew,MatScalar);
1520:       /* add the new nonzero to the high position, shift the remaining elements in current row to the right by one slot */
1521:       for (ii=nrow-1; ii>=i; ii--) {
1522:         *(cp+(ii+1)*8) = *(cp+ii*8);
1523:         *(vp+(ii+1)*8) = *(vp+ii*8);
1524:       }
1525:       a->rlen[row]++;
1526:       *(cp+i*8) = col;
1527:       *(vp+i*8) = value;
1528:       a->nz++;
1529:       A->nonzerostate++;
1530:       low = i+1; high++; nrow++;
1531: noinsert:;
1532:     }
1533:     a->rlen[row] = nrow;
1534:   }
1535:   return(0);
1536: }

1538: PetscErrorCode MatCopy_SeqSELL(Mat A,Mat B,MatStructure str)
1539: {

1543:   /* If the two matrices have the same copy implementation, use fast copy. */
1544:   if (str == SAME_NONZERO_PATTERN && (A->ops->copy == B->ops->copy)) {
1545:     Mat_SeqSELL *a=(Mat_SeqSELL*)A->data;
1546:     Mat_SeqSELL *b=(Mat_SeqSELL*)B->data;

1548:     if (a->sliidx[a->totalslices] != b->sliidx[b->totalslices]) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_INCOMP,"Number of nonzeros in two matrices are different");
1549:     PetscMemcpy(b->val,a->val,a->sliidx[a->totalslices]*sizeof(PetscScalar));
1550:   } else {
1551:     MatCopy_Basic(A,B,str);
1552:   }
1553:   return(0);
1554: }

1556: PetscErrorCode MatSetUp_SeqSELL(Mat A)
1557: {

1561:   MatSeqSELLSetPreallocation(A,PETSC_DEFAULT,0);
1562:   return(0);
1563: }

1565: PetscErrorCode MatSeqSELLGetArray_SeqSELL(Mat A,PetscScalar *array[])
1566: {
1567:   Mat_SeqSELL *a=(Mat_SeqSELL*)A->data;

1570:   *array = a->val;
1571:   return(0);
1572: }

1574: PetscErrorCode MatSeqSELLRestoreArray_SeqSELL(Mat A,PetscScalar *array[])
1575: {
1577:   return(0);
1578: }

1580: PetscErrorCode MatRealPart_SeqSELL(Mat A)
1581: {
1582:   Mat_SeqSELL *a=(Mat_SeqSELL*)A->data;
1583:   PetscInt    i;
1584:   MatScalar   *aval=a->val;

1587:   for (i=0; i<a->sliidx[a->totalslices]; i++) aval[i]=PetscRealPart(aval[i]);
1588:   return(0);
1589: }

1591: PetscErrorCode MatImaginaryPart_SeqSELL(Mat A)
1592: {
1593:   Mat_SeqSELL    *a=(Mat_SeqSELL*)A->data;
1594:   PetscInt       i;
1595:   MatScalar      *aval=a->val;

1599:   for (i=0; i<a->sliidx[a->totalslices]; i++) aval[i] = PetscImaginaryPart(aval[i]);
1600:   MatSeqSELLInvalidateDiagonal(A);
1601:   return(0);
1602: }

1604: PetscErrorCode MatScale_SeqSELL(Mat inA,PetscScalar alpha)
1605: {
1606:   Mat_SeqSELL    *a=(Mat_SeqSELL*)inA->data;
1607:   MatScalar      *aval=a->val;
1608:   PetscScalar    oalpha=alpha;
1609:   PetscBLASInt   one=1,size;

1613:   PetscBLASIntCast(a->sliidx[a->totalslices],&size);
1614:   PetscStackCallBLAS("BLASscal",BLASscal_(&size,&oalpha,aval,&one));
1615:   PetscLogFlops(a->nz);
1616:   MatSeqSELLInvalidateDiagonal(inA);
1617:   return(0);
1618: }

1620: PetscErrorCode MatShift_SeqSELL(Mat Y,PetscScalar a)
1621: {
1622:   Mat_SeqSELL    *y=(Mat_SeqSELL*)Y->data;

1626:   if (!Y->preallocated || !y->nz) {
1627:     MatSeqSELLSetPreallocation(Y,1,NULL);
1628:   }
1629:   MatShift_Basic(Y,a);
1630:   return(0);
1631: }

1633: PetscErrorCode MatSOR_SeqSELL(Mat A,Vec bb,PetscReal omega,MatSORType flag,PetscReal fshift,PetscInt its,PetscInt lits,Vec xx)
1634: {
1635:   Mat_SeqSELL       *a=(Mat_SeqSELL*)A->data;
1636:   PetscScalar       *x,sum,*t;
1637:   const MatScalar   *idiag=0,*mdiag;
1638:   const PetscScalar *b,*xb;
1639:   PetscInt          n,m=A->rmap->n,i,j,shift;
1640:   const PetscInt    *diag;
1641:   PetscErrorCode    ierr;

1644:   its = its*lits;

1646:   if (fshift != a->fshift || omega != a->omega) a->idiagvalid = PETSC_FALSE; /* must recompute idiag[] */
1647:   if (!a->idiagvalid) {MatInvertDiagonal_SeqSELL(A,omega,fshift);}
1648:   a->fshift = fshift;
1649:   a->omega  = omega;

1651:   diag  = a->diag;
1652:   t     = a->ssor_work;
1653:   idiag = a->idiag;
1654:   mdiag = a->mdiag;

1656:   VecGetArray(xx,&x);
1657:   VecGetArrayRead(bb,&b);
1658:   /* We count flops by assuming the upper triangular and lower triangular parts have the same number of nonzeros */
1659:   if (flag == SOR_APPLY_UPPER) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"SOR_APPLY_UPPER is not implemented");
1660:   if (flag == SOR_APPLY_LOWER) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"SOR_APPLY_LOWER is not implemented");
1661:   if (flag & SOR_EISENSTAT) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"No support yet for Eisenstat");

1663:   if (flag & SOR_ZERO_INITIAL_GUESS) {
1664:     if ((flag & SOR_FORWARD_SWEEP) || (flag & SOR_LOCAL_FORWARD_SWEEP)) {
1665:       for (i=0; i<m; i++) {
1666:         shift = a->sliidx[i>>3]+(i&0x07); /* starting index of the row i */
1667:         sum   = b[i];
1668:         n     = (diag[i]-shift)/8;
1669:         for (j=0; j<n; j++) sum -= a->val[shift+j*8]*x[a->colidx[shift+j*8]];
1670:         t[i]  = sum;
1671:         x[i]  = sum*idiag[i];
1672:       }
1673:       xb   = t;
1674:       PetscLogFlops(a->nz);
1675:     } else xb = b;
1676:     if ((flag & SOR_BACKWARD_SWEEP) || (flag & SOR_LOCAL_BACKWARD_SWEEP)) {
1677:       for (i=m-1; i>=0; i--) {
1678:         shift = a->sliidx[i>>3]+(i&0x07); /* starting index of the row i */
1679:         sum   = xb[i];
1680:         n     = a->rlen[i]-(diag[i]-shift)/8-1;
1681:         for (j=1; j<=n; j++) sum -= a->val[diag[i]+j*8]*x[a->colidx[diag[i]+j*8]];
1682:         if (xb == b) {
1683:           x[i] = sum*idiag[i];
1684:         } else {
1685:           x[i] = (1.-omega)*x[i]+sum*idiag[i];  /* omega in idiag */
1686:         }
1687:       }
1688:       PetscLogFlops(a->nz); /* assumes 1/2 in upper */
1689:     }
1690:     its--;
1691:   }
1692:   while (its--) {
1693:     if ((flag & SOR_FORWARD_SWEEP) || (flag & SOR_LOCAL_FORWARD_SWEEP)) {
1694:       for (i=0; i<m; i++) {
1695:         /* lower */
1696:         shift = a->sliidx[i>>3]+(i&0x07); /* starting index of the row i */
1697:         sum   = b[i];
1698:         n     = (diag[i]-shift)/8;
1699:         for (j=0; j<n; j++) sum -= a->val[shift+j*8]*x[a->colidx[shift+j*8]];
1700:         t[i]  = sum;             /* save application of the lower-triangular part */
1701:         /* upper */
1702:         n     = a->rlen[i]-(diag[i]-shift)/8-1;
1703:         for (j=1; j<=n; j++) sum -= a->val[diag[i]+j*8]*x[a->colidx[diag[i]+j*8]];
1704:         x[i]  = (1.-omega)*x[i]+sum*idiag[i];  /* omega in idiag */
1705:       }
1706:       xb   = t;
1707:       PetscLogFlops(2.0*a->nz);
1708:     } else xb = b;
1709:     if ((flag & SOR_BACKWARD_SWEEP) || (flag & SOR_LOCAL_BACKWARD_SWEEP)) {
1710:       for (i=m-1; i>=0; i--) {
1711:         shift = a->sliidx[i>>3]+(i&0x07); /* starting index of the row i */
1712:         sum = xb[i];
1713:         if (xb == b) {
1714:           /* whole matrix (no checkpointing available) */
1715:           n     = a->rlen[i];
1716:           for (j=0; j<n; j++) sum -= a->val[shift+j*8]*x[a->colidx[shift+j*8]];
1717:           x[i] = (1.-omega)*x[i]+(sum+mdiag[i]*x[i])*idiag[i];
1718:         } else { /* lower-triangular part has been saved, so only apply upper-triangular */
1719:           n     = a->rlen[i]-(diag[i]-shift)/8-1;
1720:           for (j=1; j<=n; j++) sum -= a->val[diag[i]+j*8]*x[a->colidx[diag[i]+j*8]];
1721:           x[i]  = (1.-omega)*x[i]+sum*idiag[i];  /* omega in idiag */
1722:         }
1723:       }
1724:       if (xb == b) {
1725:         PetscLogFlops(2.0*a->nz);
1726:       } else {
1727:         PetscLogFlops(a->nz); /* assumes 1/2 in upper */
1728:       }
1729:     }
1730:   }
1731:   VecRestoreArray(xx,&x);
1732:   VecRestoreArrayRead(bb,&b);
1733:   return(0);
1734: }

1736: /* -------------------------------------------------------------------*/
1737: static struct _MatOps MatOps_Values = {MatSetValues_SeqSELL,
1738:                                        MatGetRow_SeqSELL,
1739:                                        MatRestoreRow_SeqSELL,
1740:                                        MatMult_SeqSELL,
1741:                                /* 4*/  MatMultAdd_SeqSELL,
1742:                                        MatMultTranspose_SeqSELL,
1743:                                        MatMultTransposeAdd_SeqSELL,
1744:                                        0,
1745:                                        0,
1746:                                        0,
1747:                                /* 10*/ 0,
1748:                                        0,
1749:                                        0,
1750:                                        MatSOR_SeqSELL,
1751:                                        0,
1752:                                /* 15*/ MatGetInfo_SeqSELL,
1753:                                        MatEqual_SeqSELL,
1754:                                        MatGetDiagonal_SeqSELL,
1755:                                        MatDiagonalScale_SeqSELL,
1756:                                        0,
1757:                                /* 20*/ 0,
1758:                                        MatAssemblyEnd_SeqSELL,
1759:                                        MatSetOption_SeqSELL,
1760:                                        MatZeroEntries_SeqSELL,
1761:                                /* 24*/ 0,
1762:                                        0,
1763:                                        0,
1764:                                        0,
1765:                                        0,
1766:                                /* 29*/ MatSetUp_SeqSELL,
1767:                                        0,
1768:                                        0,
1769:                                        0,
1770:                                        0,
1771:                                /* 34*/ MatDuplicate_SeqSELL,
1772:                                        0,
1773:                                        0,
1774:                                        0,
1775:                                        0,
1776:                                /* 39*/ 0,
1777:                                        0,
1778:                                        0,
1779:                                        MatGetValues_SeqSELL,
1780:                                        MatCopy_SeqSELL,
1781:                                /* 44*/ 0,
1782:                                        MatScale_SeqSELL,
1783:                                        MatShift_SeqSELL,
1784:                                        0,
1785:                                        0,
1786:                                /* 49*/ 0,
1787:                                        0,
1788:                                        0,
1789:                                        0,
1790:                                        0,
1791:                                /* 54*/ MatFDColoringCreate_SeqXAIJ,
1792:                                        0,
1793:                                        0,
1794:                                        0,
1795:                                        0,
1796:                                /* 59*/ 0,
1797:                                        MatDestroy_SeqSELL,
1798:                                        MatView_SeqSELL,
1799:                                        0,
1800:                                        0,
1801:                                /* 64*/ 0,
1802:                                        0,
1803:                                        0,
1804:                                        0,
1805:                                        0,
1806:                                /* 69*/ 0,
1807:                                        0,
1808:                                        0,
1809:                                        0,
1810:                                        0,
1811:                                /* 74*/ 0,
1812:                                        MatFDColoringApply_AIJ, /* reuse the FDColoring function for AIJ */
1813:                                        0,
1814:                                        0,
1815:                                        0,
1816:                                /* 79*/ 0,
1817:                                        0,
1818:                                        0,
1819:                                        0,
1820:                                        0,
1821:                                /* 84*/ 0,
1822:                                        0,
1823:                                        0,
1824:                                        0,
1825:                                        0,
1826:                                /* 89*/ 0,
1827:                                        0,
1828:                                        0,
1829:                                        0,
1830:                                        0,
1831:                                /* 94*/ 0,
1832:                                        0,
1833:                                        0,
1834:                                        0,
1835:                                        0,
1836:                                /* 99*/ 0,
1837:                                        0,
1838:                                        0,
1839:                                        MatConjugate_SeqSELL,
1840:                                        0,
1841:                                /*104*/ 0,
1842:                                        0,
1843:                                        0,
1844:                                        0,
1845:                                        0,
1846:                                /*109*/ 0,
1847:                                        0,
1848:                                        0,
1849:                                        0,
1850:                                        MatMissingDiagonal_SeqSELL,
1851:                                /*114*/ 0,
1852:                                        0,
1853:                                        0,
1854:                                        0,
1855:                                        0,
1856:                                /*119*/ 0,
1857:                                        0,
1858:                                        0,
1859:                                        0,
1860:                                        0,
1861:                                /*124*/ 0,
1862:                                        0,
1863:                                        0,
1864:                                        0,
1865:                                        0,
1866:                                /*129*/ 0,
1867:                                        0,
1868:                                        0,
1869:                                        0,
1870:                                        0,
1871:                                /*134*/ 0,
1872:                                        0,
1873:                                        0,
1874:                                        0,
1875:                                        0,
1876:                                /*139*/ 0,
1877:                                        0,
1878:                                        0,
1879:                                        MatFDColoringSetUp_SeqXAIJ,
1880:                                        0,
1881:                                 /*144*/0
1882: };

1884: PetscErrorCode MatStoreValues_SeqSELL(Mat mat)
1885: {
1886:   Mat_SeqSELL    *a=(Mat_SeqSELL*)mat->data;

1890:   if (!a->nonew) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ORDER,"Must call MatSetOption(A,MAT_NEW_NONZERO_LOCATIONS,PETSC_FALSE);first");

1892:   /* allocate space for values if not already there */
1893:   if (!a->saved_values) {
1894:     PetscMalloc1(a->sliidx[a->totalslices]+1,&a->saved_values);
1895:     PetscLogObjectMemory((PetscObject)mat,(a->sliidx[a->totalslices]+1)*sizeof(PetscScalar));
1896:   }

1898:   /* copy values over */
1899:   PetscMemcpy(a->saved_values,a->val,a->sliidx[a->totalslices]*sizeof(PetscScalar));
1900:   return(0);
1901: }

1903: PetscErrorCode MatRetrieveValues_SeqSELL(Mat mat)
1904: {
1905:   Mat_SeqSELL    *a=(Mat_SeqSELL*)mat->data;

1909:   if (!a->nonew) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ORDER,"Must call MatSetOption(A,MAT_NEW_NONZERO_LOCATIONS,PETSC_FALSE);first");
1910:   if (!a->saved_values) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ORDER,"Must call MatStoreValues(A);first");
1911:   /* copy values over */
1912:   PetscMemcpy(a->val,a->saved_values,a->sliidx[a->totalslices]*sizeof(PetscScalar));
1913:   return(0);
1914: }

1916: /*@C
1917:  MatSeqSELLRestoreArray - returns access to the array where the data for a MATSEQSELL matrix is stored obtained by MatSeqSELLGetArray()

1919:  Not Collective

1921:  Input Parameters:
1922:  .  mat - a MATSEQSELL matrix
1923:  .  array - pointer to the data

1925:  Level: intermediate

1927:  .seealso: MatSeqSELLGetArray(), MatSeqSELLRestoreArrayF90()
1928:  @*/
1929: PetscErrorCode MatSeqSELLRestoreArray(Mat A,PetscScalar **array)
1930: {

1934:   PetscUseMethod(A,"MatSeqSELLRestoreArray_C",(Mat,PetscScalar**),(A,array));
1935:   return(0);
1936: }

1938: PETSC_EXTERN PetscErrorCode MatCreate_SeqSELL(Mat B)
1939: {
1940:   Mat_SeqSELL    *b;
1941:   PetscMPIInt    size;

1945:   MPI_Comm_size(PetscObjectComm((PetscObject)B),&size);
1946:   if (size > 1) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Comm must be of size 1");

1948:   PetscNewLog(B,&b);

1950:   B->data = (void*)b;

1952:   PetscMemcpy(B->ops,&MatOps_Values,sizeof(struct _MatOps));

1954:   b->row                = 0;
1955:   b->col                = 0;
1956:   b->icol               = 0;
1957:   b->reallocs           = 0;
1958:   b->ignorezeroentries  = PETSC_FALSE;
1959:   b->roworiented        = PETSC_TRUE;
1960:   b->nonew              = 0;
1961:   b->diag               = 0;
1962:   b->solve_work         = 0;
1963:   B->spptr              = 0;
1964:   b->saved_values       = 0;
1965:   b->idiag              = 0;
1966:   b->mdiag              = 0;
1967:   b->ssor_work          = 0;
1968:   b->omega              = 1.0;
1969:   b->fshift             = 0.0;
1970:   b->idiagvalid         = PETSC_FALSE;
1971:   b->keepnonzeropattern = PETSC_FALSE;

1973:   PetscObjectChangeTypeName((PetscObject)B,MATSEQSELL);
1974:   PetscObjectComposeFunction((PetscObject)B,"MatSeqSELLGetArray_C",MatSeqSELLGetArray_SeqSELL);
1975:   PetscObjectComposeFunction((PetscObject)B,"MatSeqSELLRestoreArray_C",MatSeqSELLRestoreArray_SeqSELL);
1976:   PetscObjectComposeFunction((PetscObject)B,"MatStoreValues_C",MatStoreValues_SeqSELL);
1977:   PetscObjectComposeFunction((PetscObject)B,"MatRetrieveValues_C",MatRetrieveValues_SeqSELL);
1978:   PetscObjectComposeFunction((PetscObject)B,"MatSeqSELLSetPreallocation_C",MatSeqSELLSetPreallocation_SeqSELL);
1979:   PetscObjectComposeFunction((PetscObject)B,"MatConvert_seqsell_seqaij_C",MatConvert_SeqSELL_SeqAIJ);
1980:   return(0);
1981: }

1983: /*
1984:  Given a matrix generated with MatGetFactor() duplicates all the information in A into B
1985:  */
1986: PetscErrorCode MatDuplicateNoCreate_SeqSELL(Mat C,Mat A,MatDuplicateOption cpvalues,PetscBool mallocmatspace)
1987: {
1988:   Mat_SeqSELL    *c,*a=(Mat_SeqSELL*)A->data;
1989:   PetscInt       i,m=A->rmap->n;
1990:   PetscInt       totalslices=a->totalslices;

1994:   c = (Mat_SeqSELL*)C->data;

1996:   C->factortype = A->factortype;
1997:   c->row        = 0;
1998:   c->col        = 0;
1999:   c->icol       = 0;
2000:   c->reallocs   = 0;

2002:   C->assembled = PETSC_TRUE;

2004:   PetscLayoutReference(A->rmap,&C->rmap);
2005:   PetscLayoutReference(A->cmap,&C->cmap);

2007:   PetscMalloc1(8*totalslices,&c->rlen);
2008:   PetscLogObjectMemory((PetscObject)C,m*sizeof(PetscInt));
2009:   PetscMalloc1(totalslices+1,&c->sliidx);
2010:   PetscLogObjectMemory((PetscObject)C, (totalslices+1)*sizeof(PetscInt));

2012:   for (i=0; i<m; i++) c->rlen[i] = a->rlen[i];
2013:   for (i=0; i<totalslices+1; i++) c->sliidx[i] = a->sliidx[i];

2015:   /* allocate the matrix space */
2016:   if (mallocmatspace) {
2017:     PetscMalloc2(a->maxallocmat,&c->val,a->maxallocmat,&c->colidx);
2018:     PetscLogObjectMemory((PetscObject)C,a->maxallocmat*(sizeof(PetscScalar)+sizeof(PetscInt)));

2020:     c->singlemalloc = PETSC_TRUE;

2022:     if (m > 0) {
2023:       PetscMemcpy(c->colidx,a->colidx,(a->maxallocmat)*sizeof(PetscInt));
2024:       if (cpvalues == MAT_COPY_VALUES) {
2025:         PetscMemcpy(c->val,a->val,a->maxallocmat*sizeof(PetscScalar));
2026:       } else {
2027:         PetscMemzero(c->val,a->maxallocmat*sizeof(PetscScalar));
2028:       }
2029:     }
2030:   }

2032:   c->ignorezeroentries = a->ignorezeroentries;
2033:   c->roworiented       = a->roworiented;
2034:   c->nonew             = a->nonew;
2035:   if (a->diag) {
2036:     PetscMalloc1(m,&c->diag);
2037:     PetscLogObjectMemory((PetscObject)C,m*sizeof(PetscInt));
2038:     for (i=0; i<m; i++) {
2039:       c->diag[i] = a->diag[i];
2040:     }
2041:   } else c->diag = 0;

2043:   c->solve_work         = 0;
2044:   c->saved_values       = 0;
2045:   c->idiag              = 0;
2046:   c->ssor_work          = 0;
2047:   c->keepnonzeropattern = a->keepnonzeropattern;
2048:   c->free_val           = PETSC_TRUE;
2049:   c->free_colidx        = PETSC_TRUE;

2051:   c->maxallocmat  = a->maxallocmat;
2052:   c->maxallocrow  = a->maxallocrow;
2053:   c->rlenmax      = a->rlenmax;
2054:   c->nz           = a->nz;
2055:   C->preallocated = PETSC_TRUE;

2057:   c->nonzerorowcnt = a->nonzerorowcnt;
2058:   C->nonzerostate  = A->nonzerostate;

2060:   PetscFunctionListDuplicate(((PetscObject)A)->qlist,&((PetscObject)C)->qlist);
2061:   return(0);
2062: }

2064: PetscErrorCode MatDuplicate_SeqSELL(Mat A,MatDuplicateOption cpvalues,Mat *B)
2065: {

2069:   MatCreate(PetscObjectComm((PetscObject)A),B);
2070:   MatSetSizes(*B,A->rmap->n,A->cmap->n,A->rmap->n,A->cmap->n);
2071:   if (!(A->rmap->n % A->rmap->bs) && !(A->cmap->n % A->cmap->bs)) {
2072:     MatSetBlockSizesFromMats(*B,A,A);
2073:   }
2074:   MatSetType(*B,((PetscObject)A)->type_name);
2075:   MatDuplicateNoCreate_SeqSELL(*B,A,cpvalues,PETSC_TRUE);
2076:   return(0);
2077: }

2079: /*@C
2080:  MatCreateSeqSELL - Creates a sparse matrix in SELL format.

2082:  Collective on MPI_Comm

2084:  Input Parameters:
2085:  +  comm - MPI communicator, set to PETSC_COMM_SELF
2086:  .  m - number of rows
2087:  .  n - number of columns
2088:  .  rlenmax - maximum number of nonzeros in a row
2089:  -  rlen - array containing the number of nonzeros in the various rows
2090:  (possibly different for each row) or NULL

2092:  Output Parameter:
2093:  .  A - the matrix

2095:  It is recommended that one use the MatCreate(), MatSetType() and/or MatSetFromOptions(),
2096:  MatXXXXSetPreallocation() paradgm instead of this routine directly.
2097:  [MatXXXXSetPreallocation() is, for example, MatSeqSELLSetPreallocation]

2099:  Notes:
2100:  If nnz is given then nz is ignored

2102:  Specify the preallocated storage with either rlenmax or rlen (not both).
2103:  Set rlenmax=PETSC_DEFAULT and rlen=NULL for PETSc to control dynamic memory
2104:  allocation.  For large problems you MUST preallocate memory or you
2105:  will get TERRIBLE performance, see the users' manual chapter on matrices.

2107:  Level: intermediate

2109:  .seealso: MatCreate(), MatCreateSELL(), MatSetValues(), MatCreateSeqSELLWithArrays()

2111:  @*/
2112: PetscErrorCode MatCreateSeqSELL(MPI_Comm comm,PetscInt m,PetscInt n,PetscInt maxallocrow,const PetscInt rlen[],Mat *A)
2113: {

2117:   MatCreate(comm,A);
2118:   MatSetSizes(*A,m,n,m,n);
2119:   MatSetType(*A,MATSEQSELL);
2120:   MatSeqSELLSetPreallocation_SeqSELL(*A,maxallocrow,rlen);
2121:   return(0);
2122: }

2124: PetscErrorCode MatEqual_SeqSELL(Mat A,Mat B,PetscBool * flg)
2125: {
2126:   Mat_SeqSELL     *a=(Mat_SeqSELL*)A->data,*b=(Mat_SeqSELL*)B->data;
2127:   PetscInt       totalslices=a->totalslices;

2131:   /* If the  matrix dimensions are not equal,or no of nonzeros */
2132:   if ((A->rmap->n != B->rmap->n) || (A->cmap->n != B->cmap->n) ||(a->nz != b->nz) || (a->rlenmax != b->rlenmax)) {
2133:     *flg = PETSC_FALSE;
2134:     return(0);
2135:   }
2136:   /* if the a->colidx are the same */
2137:   PetscMemcmp(a->colidx,b->colidx,a->sliidx[totalslices]*sizeof(PetscInt),flg);
2138:   if (!*flg) return(0);
2139:   /* if a->val are the same */
2140:   PetscMemcmp(a->val,b->val,a->sliidx[totalslices]*sizeof(PetscScalar),flg);
2141:   return(0);
2142: }

2144: PetscErrorCode MatSeqSELLInvalidateDiagonal(Mat A)
2145: {
2146:   Mat_SeqSELL *a=(Mat_SeqSELL*)A->data;

2149:   a->idiagvalid  = PETSC_FALSE;
2150:   return(0);
2151: }

2153: PetscErrorCode MatConjugate_SeqSELL(Mat A)
2154: {
2155: #if defined(PETSC_USE_COMPLEX)
2156:   Mat_SeqSELL *a=(Mat_SeqSELL*)A->data;
2157:   PetscInt    i;
2158:   PetscScalar *val = a->val;

2161:   for (i=0; i<a->sliidx[a->totalslices]; i++) {
2162:     val[i] = PetscConj(val[i]);
2163:   }
2164: #else
2166: #endif
2167:   return(0);
2168: }