Actual source code: mpirowbs.c
1: #define PETSCMAT_DLL
3: #include src/mat/impls/rowbs/mpi/mpirowbs.h
5: #define CHUNCKSIZE_LOCAL 10
9: static PetscErrorCode MatFreeRowbs_Private(Mat A,int n,int *i,PetscScalar *v)
10: {
14: if (v) {
15: #if defined(PETSC_USE_LOG)
16: int len = -n*(sizeof(int)+sizeof(PetscScalar));
17: #endif
18: PetscFree(v);
19: PetscLogObjectMemory(A,len);
20: }
21: return(0);
22: }
26: static PetscErrorCode MatMallocRowbs_Private(Mat A,int n,int **i,PetscScalar **v)
27: {
29: int len;
32: if (!n) {
33: *i = 0; *v = 0;
34: } else {
35: len = n*(sizeof(int) + sizeof(PetscScalar));
36: PetscMalloc(len,v);
37: PetscLogObjectMemory(A,len);
38: *i = (int*)(*v + n);
39: }
40: return(0);
41: }
45: PetscErrorCode MatScale_MPIRowbs(Mat inA,PetscScalar alpha)
46: {
47: Mat_MPIRowbs *a = (Mat_MPIRowbs*)inA->data;
48: BSspmat *A = a->A;
49: BSsprow *vs;
50: PetscScalar *ap;
51: int i,m = inA->rmap.n,nrow,j;
55: for (i=0; i<m; i++) {
56: vs = A->rows[i];
57: nrow = vs->length;
58: ap = vs->nz;
59: for (j=0; j<nrow; j++) {
60: ap[j] *= alpha;
61: }
62: }
63: PetscLogFlops(a->nz);
64: return(0);
65: }
67: /* ----------------------------------------------------------------- */
70: static PetscErrorCode MatCreateMPIRowbs_local(Mat A,int nz,const int nnz[])
71: {
72: Mat_MPIRowbs *bsif = (Mat_MPIRowbs*)A->data;
74: int i,len,m = A->rmap.n,*tnnz;
75: BSspmat *bsmat;
76: BSsprow *vs;
79: PetscMalloc((m+1)*sizeof(int),&tnnz);
80: if (!nnz) {
81: if (nz == PETSC_DEFAULT || nz == PETSC_DECIDE) nz = 5;
82: if (nz <= 0) nz = 1;
83: for (i=0; i<m; i++) tnnz[i] = nz;
84: nz = nz*m;
85: } else {
86: nz = 0;
87: for (i=0; i<m; i++) {
88: if (nnz[i] <= 0) tnnz[i] = 1;
89: else tnnz[i] = nnz[i];
90: nz += tnnz[i];
91: }
92: }
94: /* Allocate BlockSolve matrix context */
95: PetscNew(BSspmat,&bsif->A);
96: bsmat = bsif->A;
97: BSset_mat_icc_storage(bsmat,PETSC_FALSE);
98: BSset_mat_symmetric(bsmat,PETSC_FALSE);
99: len = m*(sizeof(BSsprow*)+ sizeof(BSsprow)) + 1;
100: PetscMalloc(len,&bsmat->rows);
101: bsmat->num_rows = m;
102: bsmat->global_num_rows = A->rmap.N;
103: bsmat->map = bsif->bsmap;
104: vs = (BSsprow*)(bsmat->rows + m);
105: for (i=0; i<m; i++) {
106: bsmat->rows[i] = vs;
107: bsif->imax[i] = tnnz[i];
108: vs->diag_ind = -1;
109: MatMallocRowbs_Private(A,tnnz[i],&(vs->col),&(vs->nz));
110: /* put zero on diagonal */
111: /*vs->length = 1;
112: vs->col[0] = i + bsif->rstart;
113: vs->nz[0] = 0.0;*/
114: vs->length = 0;
115: vs++;
116: }
117: PetscLogObjectMemory(A,sizeof(BSspmat) + len);
118: bsif->nz = 0;
119: bsif->maxnz = nz;
120: bsif->sorted = 0;
121: bsif->roworiented = PETSC_TRUE;
122: bsif->nonew = 0;
123: bsif->bs_color_single = 0;
125: PetscFree(tnnz);
126: return(0);
127: }
131: static PetscErrorCode MatSetValues_MPIRowbs_local(Mat AA,int m,const int im[],int n,const int in[],const PetscScalar v[],InsertMode addv)
132: {
133: Mat_MPIRowbs *mat = (Mat_MPIRowbs*)AA->data;
134: BSspmat *A = mat->A;
135: BSsprow *vs;
137: int *rp,k,a,b,t,ii,row,nrow,i,col,l,rmax;
138: int *imax = mat->imax,nonew = mat->nonew,sorted = mat->sorted;
139: PetscScalar *ap,value;
142: for (k=0; k<m; k++) { /* loop over added rows */
143: row = im[k];
144: if (row < 0) SETERRQ1(PETSC_ERR_ARG_OUTOFRANGE,"Negative row: %d",row);
145: if (row >= AA->rmap.n) SETERRQ2(PETSC_ERR_ARG_OUTOFRANGE,"Row too large: row %d max %d",row,AA->rmap.n-1);
146: vs = A->rows[row];
147: ap = vs->nz; rp = vs->col;
148: rmax = imax[row]; nrow = vs->length;
149: a = 0;
150: for (l=0; l<n; l++) { /* loop over added columns */
151: if (in[l] < 0) SETERRQ1(PETSC_ERR_ARG_OUTOFRANGE,"Negative col: %d",in[l]);
152: if (in[l] >= AA->cmap.N) SETERRQ2(PETSC_ERR_ARG_OUTOFRANGE,"Column too large: col %d max %d",in[l],AA->cmap.N-1);
153: col = in[l]; value = *v++;
154: if (!sorted) a = 0; b = nrow;
155: while (b-a > 5) {
156: t = (b+a)/2;
157: if (rp[t] > col) b = t;
158: else a = t;
159: }
160: for (i=a; i<b; i++) {
161: if (rp[i] > col) break;
162: if (rp[i] == col) {
163: if (addv == ADD_VALUES) ap[i] += value;
164: else ap[i] = value;
165: goto noinsert;
166: }
167: }
168: if (nonew) goto noinsert;
169: if (nrow >= rmax) {
170: /* there is no extra room in row, therefore enlarge */
171: int *itemp,*iout,*iin = vs->col;
172: PetscScalar *vout,*vin = vs->nz,*vtemp;
174: /* malloc new storage space */
175: imax[row] += CHUNCKSIZE_LOCAL;
176: MatMallocRowbs_Private(AA,imax[row],&itemp,&vtemp);
177: vout = vtemp; iout = itemp;
178: for (ii=0; ii<i; ii++) {
179: vout[ii] = vin[ii];
180: iout[ii] = iin[ii];
181: }
182: vout[i] = value;
183: iout[i] = col;
184: for (ii=i+1; ii<=nrow; ii++) {
185: vout[ii] = vin[ii-1];
186: iout[ii] = iin[ii-1];
187: }
188: /* free old row storage */
189: if (rmax > 0) {
190: MatFreeRowbs_Private(AA,rmax,vs->col,vs->nz);
191: }
192: vs->col = iout; vs->nz = vout;
193: rmax = imax[row];
194: mat->maxnz += CHUNCKSIZE_LOCAL;
195: mat->reallocs++;
196: } else {
197: /* shift higher columns over to make room for newie */
198: for (ii=nrow-1; ii>=i; ii--) {
199: rp[ii+1] = rp[ii];
200: ap[ii+1] = ap[ii];
201: }
202: rp[i] = col;
203: ap[i] = value;
204: }
205: nrow++;
206: mat->nz++;
207: AA->same_nonzero = PETSC_FALSE;
208: noinsert:;
209: a = i + 1;
210: }
211: vs->length = nrow;
212: }
213: return(0);
214: }
219: static PetscErrorCode MatAssemblyBegin_MPIRowbs_local(Mat A,MatAssemblyType mode)
220: {
222: return(0);
223: }
227: static PetscErrorCode MatAssemblyEnd_MPIRowbs_local(Mat AA,MatAssemblyType mode)
228: {
229: Mat_MPIRowbs *a = (Mat_MPIRowbs*)AA->data;
230: BSspmat *A = a->A;
231: BSsprow *vs;
232: int i,j,rstart = AA->rmap.rstart;
235: if (mode == MAT_FLUSH_ASSEMBLY) return(0);
237: /* Mark location of diagonal */
238: for (i=0; i<AA->rmap.n; i++) {
239: vs = A->rows[i];
240: for (j=0; j<vs->length; j++) {
241: if (vs->col[j] == i + rstart) {
242: vs->diag_ind = j;
243: break;
244: }
245: }
246: if (vs->diag_ind == -1) {
247: SETERRQ(PETSC_ERR_ARG_WRONGSTATE,"no diagonal entry");
248: }
249: }
250: return(0);
251: }
255: static PetscErrorCode MatZeroRows_MPIRowbs_local(Mat A,PetscInt N,const PetscInt rz[],PetscScalar diag)
256: {
257: Mat_MPIRowbs *a = (Mat_MPIRowbs*)A->data;
258: BSspmat *l = a->A;
260: int i,m = A->rmap.n - 1,col,base=A->rmap.rstart;
263: if (a->keepzeroedrows) {
264: for (i=0; i<N; i++) {
265: if (rz[i] < 0 || rz[i] > m) SETERRQ(PETSC_ERR_ARG_OUTOFRANGE,"row out of range");
266: PetscMemzero(l->rows[rz[i]]->nz,l->rows[rz[i]]->length*sizeof(PetscScalar));
267: if (diag != 0.0) {
268: col=rz[i]+base;
269: MatSetValues_MPIRowbs_local(A,1,&rz[i],1,&col,&diag,INSERT_VALUES);
270: }
271: }
272: } else {
273: if (diag != 0.0) {
274: for (i=0; i<N; i++) {
275: if (rz[i] < 0 || rz[i] > m) SETERRQ(PETSC_ERR_ARG_OUTOFRANGE,"Out of range");
276: if (l->rows[rz[i]]->length > 0) { /* in case row was completely empty */
277: l->rows[rz[i]]->length = 1;
278: l->rows[rz[i]]->nz[0] = diag;
279: l->rows[rz[i]]->col[0] = A->rmap.rstart + rz[i];
280: } else {
281: col=rz[i]+base;
282: MatSetValues_MPIRowbs_local(A,1,&rz[i],1,&col,&diag,INSERT_VALUES);
283: }
284: }
285: } else {
286: for (i=0; i<N; i++) {
287: if (rz[i] < 0 || rz[i] > m) SETERRQ(PETSC_ERR_ARG_OUTOFRANGE,"Out of range");
288: l->rows[rz[i]]->length = 0;
289: }
290: }
291: A->same_nonzero = PETSC_FALSE;
292: }
293: MatAssemblyBegin(A,MAT_FINAL_ASSEMBLY);
294: MatAssemblyEnd(A,MAT_FINAL_ASSEMBLY);
295: return(0);
296: }
300: static PetscErrorCode MatNorm_MPIRowbs_local(Mat A,NormType type,PetscReal *norm)
301: {
302: Mat_MPIRowbs *mat = (Mat_MPIRowbs*)A->data;
303: BSsprow *vs,**rs;
304: PetscScalar *xv;
305: PetscReal sum = 0.0;
307: int *xi,nz,i,j;
310: rs = mat->A->rows;
311: if (type == NORM_FROBENIUS) {
312: for (i=0; i<A->rmap.n; i++) {
313: vs = *rs++;
314: nz = vs->length;
315: xv = vs->nz;
316: while (nz--) {
317: #if defined(PETSC_USE_COMPLEX)
318: sum += PetscRealPart(PetscConj(*xv)*(*xv)); xv++;
319: #else
320: sum += (*xv)*(*xv); xv++;
321: #endif
322: }
323: }
324: *norm = sqrt(sum);
325: } else if (type == NORM_1) { /* max column norm */
326: PetscReal *tmp;
327: PetscMalloc(A->cmap.n*sizeof(PetscReal),&tmp);
328: PetscMemzero(tmp,A->cmap.n*sizeof(PetscReal));
329: *norm = 0.0;
330: for (i=0; i<A->rmap.n; i++) {
331: vs = *rs++;
332: nz = vs->length;
333: xi = vs->col;
334: xv = vs->nz;
335: while (nz--) {
336: tmp[*xi] += PetscAbsScalar(*xv);
337: xi++; xv++;
338: }
339: }
340: for (j=0; j<A->rmap.n; j++) {
341: if (tmp[j] > *norm) *norm = tmp[j];
342: }
343: PetscFree(tmp);
344: } else if (type == NORM_INFINITY) { /* max row norm */
345: *norm = 0.0;
346: for (i=0; i<A->rmap.n; i++) {
347: vs = *rs++;
348: nz = vs->length;
349: xv = vs->nz;
350: sum = 0.0;
351: while (nz--) {
352: sum += PetscAbsScalar(*xv); xv++;
353: }
354: if (sum > *norm) *norm = sum;
355: }
356: } else {
357: SETERRQ(PETSC_ERR_SUP,"No support for the two norm");
358: }
359: return(0);
360: }
362: /* ----------------------------------------------------------------- */
366: PetscErrorCode MatSetValues_MPIRowbs(Mat mat,int m,const int im[],int n,const int in[],const PetscScalar v[],InsertMode av)
367: {
368: Mat_MPIRowbs *a = (Mat_MPIRowbs*)mat->data;
370: int i,j,row,col,rstart = mat->rmap.rstart,rend = mat->rmap.rend;
371: PetscTruth roworiented = a->roworiented;
374: /* Note: There's no need to "unscale" the matrix, since scaling is
375: confined to a->pA, and we're working with a->A here */
376: for (i=0; i<m; i++) {
377: if (im[i] < 0) continue;
378: if (im[i] >= mat->rmap.N) SETERRQ2(PETSC_ERR_ARG_OUTOFRANGE,"Row too large: row %d max %d",im[i],mat->rmap.N-1);
379: if (im[i] >= rstart && im[i] < rend) {
380: row = im[i] - rstart;
381: for (j=0; j<n; j++) {
382: if (in[j] < 0) continue;
383: if (in[j] >= mat->cmap.N) SETERRQ2(PETSC_ERR_ARG_OUTOFRANGE,"Column too large: col %d max %d",in[j],mat->cmap.N-1);
384: if (in[j] >= 0 && in[j] < mat->cmap.N){
385: col = in[j];
386: if (roworiented) {
387: MatSetValues_MPIRowbs_local(mat,1,&row,1,&col,v+i*n+j,av);
388: } else {
389: MatSetValues_MPIRowbs_local(mat,1,&row,1,&col,v+i+j*m,av);
390: }
391: } else {SETERRQ(PETSC_ERR_ARG_OUTOFRANGE,"Invalid column");}
392: }
393: } else {
394: if (!a->donotstash) {
395: if (roworiented) {
396: MatStashValuesRow_Private(&mat->stash,im[i],n,in,v+i*n);
397: } else {
398: MatStashValuesCol_Private(&mat->stash,im[i],n,in,v+i,m);
399: }
400: }
401: }
402: }
403: return(0);
404: }
408: PetscErrorCode MatAssemblyBegin_MPIRowbs(Mat mat,MatAssemblyType mode)
409: {
410: MPI_Comm comm = mat->comm;
412: int nstash,reallocs;
413: InsertMode addv;
416: /* Note: There's no need to "unscale" the matrix, since scaling is
417: confined to a->pA, and we're working with a->A here */
419: /* make sure all processors are either in INSERTMODE or ADDMODE */
420: MPI_Allreduce(&mat->insertmode,&addv,1,MPI_INT,MPI_BOR,comm);
421: if (addv == (ADD_VALUES|INSERT_VALUES)) {
422: SETERRQ(PETSC_ERR_ARG_WRONGSTATE,"Some procs inserted; others added");
423: }
424: mat->insertmode = addv; /* in case this processor had no cache */
426: MatStashScatterBegin_Private(&mat->stash,mat->rmap.range);
427: MatStashGetInfo_Private(&mat->stash,&nstash,&reallocs);
428: PetscInfo2(0,"Block-Stash has %d entries, uses %d mallocs.\n",nstash,reallocs);
429: return(0);
430: }
434: static PetscErrorCode MatView_MPIRowbs_ASCII(Mat mat,PetscViewer viewer)
435: {
436: Mat_MPIRowbs *a = (Mat_MPIRowbs*)mat->data;
438: int i,j;
439: PetscTruth iascii;
440: BSspmat *A = a->A;
441: BSsprow **rs = A->rows;
442: PetscViewerFormat format;
445: PetscViewerGetFormat(viewer,&format);
446: PetscTypeCompare((PetscObject)viewer,PETSC_VIEWER_ASCII,&iascii);
448: if (format == PETSC_VIEWER_ASCII_INFO || format == PETSC_VIEWER_ASCII_INFO_DETAIL) {
449: int ind_l,ind_g,clq_l,clq_g,color;
450: ind_l = BSlocal_num_inodes(a->pA);CHKERRBS(0);
451: ind_g = BSglobal_num_inodes(a->pA);CHKERRBS(0);
452: clq_l = BSlocal_num_cliques(a->pA);CHKERRBS(0);
453: clq_g = BSglobal_num_cliques(a->pA);CHKERRBS(0);
454: color = BSnum_colors(a->pA);CHKERRBS(0);
455: PetscViewerASCIIPrintf(viewer," %d global inode(s), %d global clique(s), %d color(s)\n",ind_g,clq_g,color);
456: PetscViewerASCIISynchronizedPrintf(viewer," [%d] %d local inode(s), %d local clique(s)\n",a->rank,ind_l,clq_l);
457: } else if (format == PETSC_VIEWER_ASCII_COMMON) {
458: for (i=0; i<A->num_rows; i++) {
459: PetscViewerASCIISynchronizedPrintf(viewer,"row %d:",i+mat->rmap.rstart);
460: for (j=0; j<rs[i]->length; j++) {
461: if (rs[i]->nz[j]) {PetscViewerASCIISynchronizedPrintf(viewer," %d %g ",rs[i]->col[j],rs[i]->nz[j]);}
462: }
463: PetscViewerASCIISynchronizedPrintf(viewer,"\n");
464: }
465: } else if (format == PETSC_VIEWER_ASCII_MATLAB) {
466: SETERRQ(PETSC_ERR_SUP,"Matlab format not supported");
467: } else {
468: PetscViewerASCIIUseTabs(viewer,PETSC_NO);
469: for (i=0; i<A->num_rows; i++) {
470: PetscViewerASCIISynchronizedPrintf(viewer,"row %d:",i+mat->rmap.rstart);
471: for (j=0; j<rs[i]->length; j++) {
472: PetscViewerASCIISynchronizedPrintf(viewer," %d %g ",rs[i]->col[j],rs[i]->nz[j]);
473: }
474: PetscViewerASCIISynchronizedPrintf(viewer,"\n");
475: }
476: PetscViewerASCIIUseTabs(viewer,PETSC_YES);
477: }
478: PetscViewerFlush(viewer);
479: return(0);
480: }
484: static PetscErrorCode MatView_MPIRowbs_Binary(Mat mat,PetscViewer viewer)
485: {
486: Mat_MPIRowbs *a = (Mat_MPIRowbs*)mat->data;
488: PetscMPIInt rank,size;
489: PetscInt i,M,m,*sbuff,*rowlengths;
490: PetscInt *recvcts,*recvdisp,fd,*cols,maxnz,nz,j;
491: BSspmat *A = a->A;
492: BSsprow **rs = A->rows;
493: MPI_Comm comm = mat->comm;
494: MPI_Status status;
495: PetscScalar *vals;
496: MatInfo info;
499: MPI_Comm_size(comm,&size);
500: MPI_Comm_rank(comm,&rank);
502: M = mat->rmap.N; m = mat->rmap.n;
503: /* First gather together on the first processor the lengths of
504: each row, and write them out to the file */
505: PetscMalloc(m*sizeof(int),&sbuff);
506: for (i=0; i<A->num_rows; i++) {
507: sbuff[i] = rs[i]->length;
508: }
509: MatGetInfo(mat,MAT_GLOBAL_SUM,&info);
510: if (!rank) {
511: PetscViewerBinaryGetDescriptor(viewer,&fd);
512: PetscMalloc((4+M)*sizeof(int),&rowlengths);
513: PetscMalloc(size*sizeof(int),&recvcts);
514: recvdisp = mat->rmap.range;
515: for (i=0; i<size; i++) {
516: recvcts[i] = recvdisp[i+1] - recvdisp[i];
517: }
518: /* first four elements of rowlength are the header */
519: rowlengths[0] = mat->cookie;
520: rowlengths[1] = mat->rmap.N;
521: rowlengths[2] = mat->cmap.N;
522: rowlengths[3] = (int)info.nz_used;
523: MPI_Gatherv(sbuff,m,MPI_INT,rowlengths+4,recvcts,recvdisp,MPI_INT,0,comm);
524: PetscFree(sbuff);
525: PetscBinaryWrite(fd,rowlengths,4+M,PETSC_INT,PETSC_FALSE);
526: /* count the number of nonzeros on each processor */
527: PetscMemzero(recvcts,size*sizeof(int));
528: for (i=0; i<size; i++) {
529: for (j=recvdisp[i]; j<recvdisp[i+1]; j++) {
530: recvcts[i] += rowlengths[j+3];
531: }
532: }
533: /* allocate buffer long enough to hold largest one */
534: maxnz = 0;
535: for (i=0; i<size; i++) {
536: maxnz = PetscMax(maxnz,recvcts[i]);
537: }
538: PetscFree(rowlengths);
539: PetscFree(recvcts);
540: PetscMalloc(maxnz*sizeof(int),&cols);
542: /* binary store column indices for 0th processor */
543: nz = 0;
544: for (i=0; i<A->num_rows; i++) {
545: for (j=0; j<rs[i]->length; j++) {
546: cols[nz++] = rs[i]->col[j];
547: }
548: }
549: PetscBinaryWrite(fd,cols,nz,PETSC_INT,PETSC_FALSE);
551: /* receive and store column indices for all other processors */
552: for (i=1; i<size; i++) {
553: /* should tell processor that I am now ready and to begin the send */
554: MPI_Recv(cols,maxnz,MPI_INT,i,mat->tag,comm,&status);
555: MPI_Get_count(&status,MPI_INT,&nz);
556: PetscBinaryWrite(fd,cols,nz,PETSC_INT,PETSC_FALSE);
557: }
558: PetscFree(cols);
559: PetscMalloc(maxnz*sizeof(PetscScalar),&vals);
561: /* binary store values for 0th processor */
562: nz = 0;
563: for (i=0; i<A->num_rows; i++) {
564: for (j=0; j<rs[i]->length; j++) {
565: vals[nz++] = rs[i]->nz[j];
566: }
567: }
568: PetscBinaryWrite(fd,vals,nz,PETSC_SCALAR,PETSC_FALSE);
570: /* receive and store nonzeros for all other processors */
571: for (i=1; i<size; i++) {
572: /* should tell processor that I am now ready and to begin the send */
573: MPI_Recv(vals,maxnz,MPIU_SCALAR,i,mat->tag,comm,&status);
574: MPI_Get_count(&status,MPIU_SCALAR,&nz);
575: PetscBinaryWrite(fd,vals,nz,PETSC_SCALAR,PETSC_FALSE);
576: }
577: PetscFree(vals);
578: } else {
579: MPI_Gatherv(sbuff,m,MPI_INT,0,0,0,MPI_INT,0,comm);
580: PetscFree(sbuff);
582: /* count local nonzeros */
583: nz = 0;
584: for (i=0; i<A->num_rows; i++) {
585: for (j=0; j<rs[i]->length; j++) {
586: nz++;
587: }
588: }
589: /* copy into buffer column indices */
590: PetscMalloc(nz*sizeof(int),&cols);
591: nz = 0;
592: for (i=0; i<A->num_rows; i++) {
593: for (j=0; j<rs[i]->length; j++) {
594: cols[nz++] = rs[i]->col[j];
595: }
596: }
597: /* send */ /* should wait until processor zero tells me to go */
598: MPI_Send(cols,nz,MPI_INT,0,mat->tag,comm);
599: PetscFree(cols);
601: /* copy into buffer column values */
602: PetscMalloc(nz*sizeof(PetscScalar),&vals);
603: nz = 0;
604: for (i=0; i<A->num_rows; i++) {
605: for (j=0; j<rs[i]->length; j++) {
606: vals[nz++] = rs[i]->nz[j];
607: }
608: }
609: /* send */ /* should wait until processor zero tells me to go */
610: MPI_Send(vals,nz,MPIU_SCALAR,0,mat->tag,comm);
611: PetscFree(vals);
612: }
614: return(0);
615: }
619: PetscErrorCode MatView_MPIRowbs(Mat mat,PetscViewer viewer)
620: {
621: Mat_MPIRowbs *bsif = (Mat_MPIRowbs*)mat->data;
623: PetscTruth iascii,isbinary;
626: PetscTypeCompare((PetscObject)viewer,PETSC_VIEWER_ASCII,&iascii);
627: PetscTypeCompare((PetscObject)viewer,PETSC_VIEWER_BINARY,&isbinary);
628: if (!bsif->blocksolveassembly) {
629: MatAssemblyEnd_MPIRowbs_ForBlockSolve(mat);
630: }
631: if (iascii) {
632: MatView_MPIRowbs_ASCII(mat,viewer);
633: } else if (isbinary) {
634: MatView_MPIRowbs_Binary(mat,viewer);
635: } else {
636: SETERRQ1(PETSC_ERR_SUP,"Viewer type %s not supported by MPIRowbs matrices",((PetscObject)viewer)->type_name);
637: }
638: return(0);
639: }
640:
643: static PetscErrorCode MatAssemblyEnd_MPIRowbs_MakeSymmetric(Mat mat)
644: {
645: Mat_MPIRowbs *a = (Mat_MPIRowbs*)mat->data;
646: BSspmat *A = a->A;
647: BSsprow *vs;
648: int size,rank,M,rstart,tag,i,j,*rtable,*w1,*w3,*w4,len,proc,nrqs;
649: int msz,*pa,bsz,nrqr,**rbuf1,**sbuf1,**ptr,*tmp,*ctr,col,idx,row;
651: int ctr_j,*sbuf1_j,k;
652: PetscScalar val=0.0;
653: MPI_Comm comm;
654: MPI_Request *s_waits1,*r_waits1;
655: MPI_Status *s_status,*r_status;
658: comm = mat->comm;
659: tag = mat->tag;
660: size = a->size;
661: rank = a->rank;
662: M = mat->rmap.N;
663: rstart = mat->rmap.rstart;
665: PetscMalloc(M*sizeof(int),&rtable);
666: /* Create hash table for the mapping :row -> proc */
667: for (i=0,j=0; i<size; i++) {
668: len = mat->rmap.range[i+1];
669: for (; j<len; j++) {
670: rtable[j] = i;
671: }
672: }
674: /* Evaluate communication - mesg to whom, length of mesg, and buffer space
675: required. Based on this, buffers are allocated, and data copied into them. */
676: PetscMalloc(size*4*sizeof(int),&w1);/* mesg size */
677: w3 = w1 + 2*size; /* no of IS that needs to be sent to proc i */
678: w4 = w3 + size; /* temp work space used in determining w1, w3 */
679: PetscMemzero(w1,size*3*sizeof(int)); /* initialize work vector */
681: for (i=0; i<mat->rmap.n; i++) {
682: PetscMemzero(w4,size*sizeof(int)); /* initialize work vector */
683: vs = A->rows[i];
684: for (j=0; j<vs->length; j++) {
685: proc = rtable[vs->col[j]];
686: w4[proc]++;
687: }
688: for (j=0; j<size; j++) {
689: if (w4[j]) { w1[2*j] += w4[j]; w3[j]++;}
690: }
691: }
692:
693: nrqs = 0; /* number of outgoing messages */
694: msz = 0; /* total mesg length (for all proc */
695: w1[2*rank] = 0; /* no mesg sent to itself */
696: w3[rank] = 0;
697: for (i=0; i<size; i++) {
698: if (w1[2*i]) {w1[2*i+1] = 1; nrqs++;} /* there exists a message to proc i */
699: }
700: /* pa - is list of processors to communicate with */
701: PetscMalloc((nrqs+1)*sizeof(int),&pa);
702: for (i=0,j=0; i<size; i++) {
703: if (w1[2*i]) {pa[j] = i; j++;}
704: }
706: /* Each message would have a header = 1 + 2*(no of ROWS) + data */
707: for (i=0; i<nrqs; i++) {
708: j = pa[i];
709: w1[2*j] += w1[2*j+1] + 2*w3[j];
710: msz += w1[2*j];
711: }
712:
713: /* Do a global reduction to determine how many messages to expect */
714: PetscMaxSum(comm,w1,&bsz,&nrqr);
716: /* Allocate memory for recv buffers . Prob none if nrqr = 0 ???? */
717: len = (nrqr+1)*sizeof(int*) + nrqr*bsz*sizeof(int);
718: PetscMalloc(len,&rbuf1);
719: rbuf1[0] = (int*)(rbuf1 + nrqr);
720: for (i=1; i<nrqr; ++i) rbuf1[i] = rbuf1[i-1] + bsz;
722: /* Post the receives */
723: PetscMalloc((nrqr+1)*sizeof(MPI_Request),&r_waits1);
724: for (i=0; i<nrqr; ++i){
725: MPI_Irecv(rbuf1[i],bsz,MPI_INT,MPI_ANY_SOURCE,tag,comm,r_waits1+i);
726: }
727:
728: /* Allocate Memory for outgoing messages */
729: len = 2*size*sizeof(int*) + (size+msz)*sizeof(int);
730: PetscMalloc(len,&sbuf1);
731: ptr = sbuf1 + size; /* Pointers to the data in outgoing buffers */
732: PetscMemzero(sbuf1,2*size*sizeof(int*));
733: tmp = (int*)(sbuf1 + 2*size);
734: ctr = tmp + msz;
736: {
737: int *iptr = tmp,ict = 0;
738: for (i=0; i<nrqs; i++) {
739: j = pa[i];
740: iptr += ict;
741: sbuf1[j] = iptr;
742: ict = w1[2*j];
743: }
744: }
746: /* Form the outgoing messages */
747: /* Clean up the header space */
748: for (i=0; i<nrqs; i++) {
749: j = pa[i];
750: sbuf1[j][0] = 0;
751: PetscMemzero(sbuf1[j]+1,2*w3[j]*sizeof(int));
752: ptr[j] = sbuf1[j] + 2*w3[j] + 1;
753: }
755: /* Parse the matrix and copy the data into sbuf1 */
756: for (i=0; i<mat->rmap.n; i++) {
757: PetscMemzero(ctr,size*sizeof(int));
758: vs = A->rows[i];
759: for (j=0; j<vs->length; j++) {
760: col = vs->col[j];
761: proc = rtable[col];
762: if (proc != rank) { /* copy to the outgoing buffer */
763: ctr[proc]++;
764: *ptr[proc] = col;
765: ptr[proc]++;
766: } else {
767: row = col - rstart;
768: col = i + rstart;
769: MatSetValues_MPIRowbs_local(mat,1,&row,1,&col,&val,ADD_VALUES);
770: }
771: }
772: /* Update the headers for the current row */
773: for (j=0; j<size; j++) { /* Can Optimise this loop by using pa[] */
774: if ((ctr_j = ctr[j])) {
775: sbuf1_j = sbuf1[j];
776: k = ++sbuf1_j[0];
777: sbuf1_j[2*k] = ctr_j;
778: sbuf1_j[2*k-1] = i + rstart;
779: }
780: }
781: }
782: /* Check Validity of the outgoing messages */
783: {
784: int sum;
785: for (i=0 ; i<nrqs ; i++) {
786: j = pa[i];
787: if (w3[j] != sbuf1[j][0]) {SETERRQ(PETSC_ERR_PLIB,"Blew it! Header[1] mismatch!\n"); }
788: }
790: for (i=0 ; i<nrqs ; i++) {
791: j = pa[i];
792: sum = 1;
793: for (k = 1; k <= w3[j]; k++) sum += sbuf1[j][2*k]+2;
794: if (sum != w1[2*j]) { SETERRQ(PETSC_ERR_PLIB,"Blew it! Header[2-n] mismatch!\n"); }
795: }
796: }
797:
798: /* Now post the sends */
799: PetscMalloc((nrqs+1)*sizeof(MPI_Request),&s_waits1);
800: for (i=0; i<nrqs; ++i) {
801: j = pa[i];
802: MPI_Isend(sbuf1[j],w1[2*j],MPI_INT,j,tag,comm,s_waits1+i);
803: }
804:
805: /* Receive messages*/
806: PetscMalloc((nrqr+1)*sizeof(MPI_Status),&r_status);
807: for (i=0; i<nrqr; ++i) {
808: MPI_Waitany(nrqr,r_waits1,&idx,r_status+i);
809: /* Process the Message */
810: {
811: int *rbuf1_i,n_row,ct1;
813: rbuf1_i = rbuf1[idx];
814: n_row = rbuf1_i[0];
815: ct1 = 2*n_row+1;
816: val = 0.0;
817: /* Optimise this later */
818: for (j=1; j<=n_row; j++) {
819: col = rbuf1_i[2*j-1];
820: for (k=0; k<rbuf1_i[2*j]; k++,ct1++) {
821: row = rbuf1_i[ct1] - rstart;
822: MatSetValues_MPIRowbs_local(mat,1,&row,1,&col,&val,ADD_VALUES);
823: }
824: }
825: }
826: }
828: PetscMalloc((nrqs+1)*sizeof(MPI_Status),&s_status);
829: if (nrqs) {MPI_Waitall(nrqs,s_waits1,s_status);}
831: PetscFree(rtable);
832: PetscFree(w1);
833: PetscFree(pa);
834: PetscFree(rbuf1);
835: PetscFree(sbuf1);
836: PetscFree(r_waits1);
837: PetscFree(s_waits1);
838: PetscFree(r_status);
839: PetscFree(s_status);
840: return(0);
841: }
843: /*
844: This does the BlockSolve portion of the matrix assembly.
845: It is provided in a separate routine so that users can
846: operate on the matrix (using MatScale(), MatShift() etc.) after
847: the matrix has been assembled but before BlockSolve has sucked it
848: in and devoured it.
849: */
852: PetscErrorCode MatAssemblyEnd_MPIRowbs_ForBlockSolve(Mat mat)
853: {
854: Mat_MPIRowbs *a = (Mat_MPIRowbs*)mat->data;
856: int ldim,low,high,i;
857: PetscScalar *diag;
860: if ((mat->was_assembled) && (!mat->same_nonzero)) { /* Free the old info */
861: if (a->pA) {BSfree_par_mat(a->pA);CHKERRBS(0);}
862: if (a->comm_pA) {BSfree_comm(a->comm_pA);CHKERRBS(0);}
863: }
865: if ((!mat->same_nonzero) || (!mat->was_assembled)) {
866: /* Indicates bypassing cliques in coloring */
867: if (a->bs_color_single) {
868: BSctx_set_si(a->procinfo,100);
869: }
870: /* Form permuted matrix for efficient parallel execution */
871: a->pA = BSmain_perm(a->procinfo,a->A);CHKERRBS(0);
872: /* Set up the communication */
873: a->comm_pA = BSsetup_forward(a->pA,a->procinfo);CHKERRBS(0);
874: } else {
875: /* Repermute the matrix */
876: BSmain_reperm(a->procinfo,a->A,a->pA);CHKERRBS(0);
877: }
879: /* Symmetrically scale the matrix by the diagonal */
880: BSscale_diag(a->pA,a->pA->diag,a->procinfo);CHKERRBS(0);
882: /* Store inverse of square root of permuted diagonal scaling matrix */
883: VecGetLocalSize(a->diag,&ldim);
884: VecGetOwnershipRange(a->diag,&low,&high);
885: VecGetArray(a->diag,&diag);
886: for (i=0; i<ldim; i++) {
887: if (a->pA->scale_diag[i] != 0.0) {
888: diag[i] = 1.0/sqrt(PetscAbsScalar(a->pA->scale_diag[i]));
889: } else {
890: diag[i] = 1.0;
891: }
892: }
893: VecRestoreArray(a->diag,&diag);
894: a->assembled_icc_storage = a->A->icc_storage;
895: a->blocksolveassembly = 1;
896: mat->was_assembled = PETSC_TRUE;
897: mat->same_nonzero = PETSC_TRUE;
898: PetscInfo(mat,"Completed BlockSolve95 matrix assembly\n");
899: return(0);
900: }
904: PetscErrorCode MatAssemblyEnd_MPIRowbs(Mat mat,MatAssemblyType mode)
905: {
906: Mat_MPIRowbs *a = (Mat_MPIRowbs*)mat->data;
908: int i,n,row,col,*rows,*cols,rstart,nzcount,flg,j,ncols;
909: PetscScalar *vals,val;
910: InsertMode addv = mat->insertmode;
913: while (1) {
914: MatStashScatterGetMesg_Private(&mat->stash,&n,&rows,&cols,&vals,&flg);
915: if (!flg) break;
916:
917: for (i=0; i<n;) {
918: /* Now identify the consecutive vals belonging to the same row */
919: for (j=i,rstart=rows[j]; j<n; j++) { if (rows[j] != rstart) break; }
920: if (j < n) ncols = j-i;
921: else ncols = n-i;
922: /* Now assemble all these values with a single function call */
923: MatSetValues_MPIRowbs(mat,1,rows+i,ncols,cols+i,vals+i,addv);
924: i = j;
925: }
926: }
927: MatStashScatterEnd_Private(&mat->stash);
929: rstart = mat->rmap.rstart;
930: nzcount = a->nz; /* This is the number of nonzeros entered by the user */
931: /* BlockSolve requires that the matrix is structurally symmetric */
932: if (mode == MAT_FINAL_ASSEMBLY && !mat->structurally_symmetric) {
933: MatAssemblyEnd_MPIRowbs_MakeSymmetric(mat);
934: }
935:
936: /* BlockSolve requires that all the diagonal elements are set */
937: val = 0.0;
938: for (i=0; i<mat->rmap.n; i++) {
939: row = i; col = i + rstart;
940: MatSetValues_MPIRowbs_local(mat,1,&row,1,&col,&val,ADD_VALUES);
941: }
942:
943: MatAssemblyBegin_MPIRowbs_local(mat,mode);
944: MatAssemblyEnd_MPIRowbs_local(mat,mode);
945:
946: a->blocksolveassembly = 0;
947: PetscInfo4(mat,"Matrix size: %d X %d; storage space: %d unneeded,%d used\n",mat->rmap.n,mat->cmap.n,a->maxnz-a->nz,a->nz);
948: PetscInfo2(mat,"User entered %d nonzeros, PETSc added %d\n",nzcount,a->nz-nzcount);
949: PetscInfo1(mat,"Number of mallocs during MatSetValues is %d\n",a->reallocs);
950: return(0);
951: }
955: PetscErrorCode MatZeroEntries_MPIRowbs(Mat mat)
956: {
957: Mat_MPIRowbs *l = (Mat_MPIRowbs*)mat->data;
958: BSspmat *A = l->A;
959: BSsprow *vs;
960: int i,j;
963: for (i=0; i <mat->rmap.n; i++) {
964: vs = A->rows[i];
965: for (j=0; j< vs->length; j++) vs->nz[j] = 0.0;
966: }
967: return(0);
968: }
970: /* the code does not do the diagonal entries correctly unless the
971: matrix is square and the column and row owerships are identical.
972: This is a BUG.
973: */
977: PetscErrorCode MatZeroRows_MPIRowbs(Mat A,PetscInt N,const PetscInt rows[],PetscScalar diag)
978: {
979: Mat_MPIRowbs *l = (Mat_MPIRowbs*)A->data;
981: int i,*owners = A->rmap.range,size = l->size;
982: int *nprocs,j,idx,nsends;
983: int nmax,*svalues,*starts,*owner,nrecvs,rank = l->rank;
984: int *rvalues,tag = A->tag,count,base,slen,n,*source;
985: int *lens,imdex,*lrows,*values;
986: MPI_Comm comm = A->comm;
987: MPI_Request *send_waits,*recv_waits;
988: MPI_Status recv_status,*send_status;
989: PetscTruth found;
992: /* first count number of contributors to each processor */
993: PetscMalloc(2*size*sizeof(int),&nprocs);
994: PetscMemzero(nprocs,2*size*sizeof(int));
995: PetscMalloc((N+1)*sizeof(int),&owner); /* see note*/
996: for (i=0; i<N; i++) {
997: idx = rows[i];
998: found = PETSC_FALSE;
999: for (j=0; j<size; j++) {
1000: if (idx >= owners[j] && idx < owners[j+1]) {
1001: nprocs[2*j]++; nprocs[2*j+1] = 1; owner[i] = j; found = PETSC_TRUE; break;
1002: }
1003: }
1004: if (!found) SETERRQ(PETSC_ERR_ARG_OUTOFRANGE,"Row out of range");
1005: }
1006: nsends = 0; for (i=0; i<size; i++) {nsends += nprocs[2*i+1];}
1008: /* inform other processors of number of messages and max length*/
1009: PetscMaxSum(comm,nprocs,&nmax,&nrecvs);
1011: /* post receives: */
1012: PetscMalloc((nrecvs+1)*(nmax+1)*sizeof(int),&rvalues);
1013: PetscMalloc((nrecvs+1)*sizeof(MPI_Request),&recv_waits);
1014: for (i=0; i<nrecvs; i++) {
1015: MPI_Irecv(rvalues+nmax*i,nmax,MPI_INT,MPI_ANY_SOURCE,tag,comm,recv_waits+i);
1016: }
1018: /* do sends:
1019: 1) starts[i] gives the starting index in svalues for stuff going to
1020: the ith processor
1021: */
1022: PetscMalloc((N+1)*sizeof(int),&svalues);
1023: PetscMalloc((nsends+1)*sizeof(MPI_Request),&send_waits);
1024: PetscMalloc((size+1)*sizeof(int),&starts);
1025: starts[0] = 0;
1026: for (i=1; i<size; i++) { starts[i] = starts[i-1] + nprocs[2*i-2];}
1027: for (i=0; i<N; i++) {
1028: svalues[starts[owner[i]]++] = rows[i];
1029: }
1031: starts[0] = 0;
1032: for (i=1; i<size+1; i++) { starts[i] = starts[i-1] + nprocs[2*i-2];}
1033: count = 0;
1034: for (i=0; i<size; i++) {
1035: if (nprocs[2*i+1]) {
1036: MPI_Isend(svalues+starts[i],nprocs[2*i],MPI_INT,i,tag,comm,send_waits+count++);
1037: }
1038: }
1039: PetscFree(starts);
1041: base = owners[rank];
1043: /* wait on receives */
1044: PetscMalloc(2*(nrecvs+1)*sizeof(int),&lens);
1045: source = lens + nrecvs;
1046: count = nrecvs; slen = 0;
1047: while (count) {
1048: MPI_Waitany(nrecvs,recv_waits,&imdex,&recv_status);
1049: /* unpack receives into our local space */
1050: MPI_Get_count(&recv_status,MPI_INT,&n);
1051: source[imdex] = recv_status.MPI_SOURCE;
1052: lens[imdex] = n;
1053: slen += n;
1054: count--;
1055: }
1056: PetscFree(recv_waits);
1057:
1058: /* move the data into the send scatter */
1059: PetscMalloc((slen+1)*sizeof(int),&lrows);
1060: count = 0;
1061: for (i=0; i<nrecvs; i++) {
1062: values = rvalues + i*nmax;
1063: for (j=0; j<lens[i]; j++) {
1064: lrows[count++] = values[j] - base;
1065: }
1066: }
1067: PetscFree(rvalues);
1068: PetscFree(lens);
1069: PetscFree(owner);
1070: PetscFree(nprocs);
1071:
1072: /* actually zap the local rows */
1073: MatZeroRows_MPIRowbs_local(A,slen,lrows,diag);
1074: PetscFree(lrows);
1076: /* wait on sends */
1077: if (nsends) {
1078: PetscMalloc(nsends*sizeof(MPI_Status),&send_status);
1079: MPI_Waitall(nsends,send_waits,send_status);
1080: PetscFree(send_status);
1081: }
1082: PetscFree(send_waits);
1083: PetscFree(svalues);
1085: return(0);
1086: }
1090: PetscErrorCode MatNorm_MPIRowbs(Mat mat,NormType type,PetscReal *norm)
1091: {
1092: Mat_MPIRowbs *a = (Mat_MPIRowbs*)mat->data;
1093: BSsprow *vs,**rs;
1094: PetscScalar *xv;
1095: PetscReal sum = 0.0;
1097: int *xi,nz,i,j;
1100: if (a->size == 1) {
1101: MatNorm_MPIRowbs_local(mat,type,norm);
1102: } else {
1103: rs = a->A->rows;
1104: if (type == NORM_FROBENIUS) {
1105: for (i=0; i<mat->rmap.n; i++) {
1106: vs = *rs++;
1107: nz = vs->length;
1108: xv = vs->nz;
1109: while (nz--) {
1110: #if defined(PETSC_USE_COMPLEX)
1111: sum += PetscRealPart(PetscConj(*xv)*(*xv)); xv++;
1112: #else
1113: sum += (*xv)*(*xv); xv++;
1114: #endif
1115: }
1116: }
1117: MPI_Allreduce(&sum,norm,1,MPIU_REAL,MPI_SUM,mat->comm);
1118: *norm = sqrt(*norm);
1119: } else if (type == NORM_1) { /* max column norm */
1120: PetscReal *tmp,*tmp2;
1121: PetscMalloc(mat->cmap.n*sizeof(PetscReal),&tmp);
1122: PetscMalloc(mat->cmap.n*sizeof(PetscReal),&tmp2);
1123: PetscMemzero(tmp,mat->cmap.n*sizeof(PetscReal));
1124: *norm = 0.0;
1125: for (i=0; i<mat->rmap.n; i++) {
1126: vs = *rs++;
1127: nz = vs->length;
1128: xi = vs->col;
1129: xv = vs->nz;
1130: while (nz--) {
1131: tmp[*xi] += PetscAbsScalar(*xv);
1132: xi++; xv++;
1133: }
1134: }
1135: MPI_Allreduce(tmp,tmp2,mat->cmap.N,MPIU_REAL,MPI_SUM,mat->comm);
1136: for (j=0; j<mat->cmap.n; j++) {
1137: if (tmp2[j] > *norm) *norm = tmp2[j];
1138: }
1139: PetscFree(tmp);
1140: PetscFree(tmp2);
1141: } else if (type == NORM_INFINITY) { /* max row norm */
1142: PetscReal ntemp = 0.0;
1143: for (i=0; i<mat->rmap.n; i++) {
1144: vs = *rs++;
1145: nz = vs->length;
1146: xv = vs->nz;
1147: sum = 0.0;
1148: while (nz--) {
1149: sum += PetscAbsScalar(*xv); xv++;
1150: }
1151: if (sum > ntemp) ntemp = sum;
1152: }
1153: MPI_Allreduce(&ntemp,norm,1,MPIU_REAL,MPI_MAX,mat->comm);
1154: } else {
1155: SETERRQ(PETSC_ERR_SUP,"No support for two norm");
1156: }
1157: }
1158: return(0);
1159: }
1163: PetscErrorCode MatMult_MPIRowbs(Mat mat,Vec xx,Vec yy)
1164: {
1165: Mat_MPIRowbs *bsif = (Mat_MPIRowbs*)mat->data;
1166: BSprocinfo *bspinfo = bsif->procinfo;
1167: PetscScalar *xxa,*xworka,*yya;
1171: if (!bsif->blocksolveassembly) {
1172: MatAssemblyEnd_MPIRowbs_ForBlockSolve(mat);
1173: }
1175: /* Permute and apply diagonal scaling: [ xwork = D^{1/2} * x ] */
1176: if (!bsif->vecs_permscale) {
1177: VecGetArray(bsif->xwork,&xworka);
1178: VecGetArray(xx,&xxa);
1179: BSperm_dvec(xxa,xworka,bsif->pA->perm);CHKERRBS(0);
1180: VecRestoreArray(bsif->xwork,&xworka);
1181: VecRestoreArray(xx,&xxa);
1182: VecPointwiseDivide(xx,bsif->xwork,bsif->diag);
1183: }
1185: VecGetArray(xx,&xxa);
1186: VecGetArray(yy,&yya);
1187: /* Do lower triangular multiplication: [ y = L * xwork ] */
1188: if (bspinfo->single) {
1189: BSforward1(bsif->pA,xxa,yya,bsif->comm_pA,bspinfo);CHKERRBS(0);
1190: } else {
1191: BSforward(bsif->pA,xxa,yya,bsif->comm_pA,bspinfo);CHKERRBS(0);
1192: }
1193:
1194: /* Do upper triangular multiplication: [ y = y + L^{T} * xwork ] */
1195: if (mat->symmetric) {
1196: if (bspinfo->single){
1197: BSbackward1(bsif->pA,xxa,yya,bsif->comm_pA,bspinfo);CHKERRBS(0);
1198: } else {
1199: BSbackward(bsif->pA,xxa,yya,bsif->comm_pA,bspinfo);CHKERRBS(0);
1200: }
1201: }
1202: /* not needed for ILU version since forward does it all */
1203: VecRestoreArray(xx,&xxa);
1204: VecRestoreArray(yy,&yya);
1206: /* Apply diagonal scaling to vector: [ y = D^{1/2} * y ] */
1207: if (!bsif->vecs_permscale) {
1208: VecGetArray(bsif->xwork,&xworka);
1209: VecGetArray(xx,&xxa);
1210: BSiperm_dvec(xworka,xxa,bsif->pA->perm);CHKERRBS(0);
1211: VecRestoreArray(bsif->xwork,&xworka);
1212: VecRestoreArray(xx,&xxa);
1213: VecPointwiseDivide(bsif->xwork,yy,bsif->diag);
1214: VecGetArray(bsif->xwork,&xworka);
1215: VecGetArray(yy,&yya);
1216: BSiperm_dvec(xworka,yya,bsif->pA->perm);CHKERRBS(0);
1217: VecRestoreArray(bsif->xwork,&xworka);
1218: VecRestoreArray(yy,&yya);
1219: }
1220: PetscLogFlops(2*bsif->nz - mat->cmap.n);
1222: return(0);
1223: }
1227: PetscErrorCode MatMultAdd_MPIRowbs(Mat mat,Vec xx,Vec yy,Vec zz)
1228: {
1230: PetscScalar one = 1.0;
1233: (*mat->ops->mult)(mat,xx,zz);
1234: VecAXPY(zz,one,yy);
1235: return(0);
1236: }
1240: PetscErrorCode MatGetInfo_MPIRowbs(Mat A,MatInfoType flag,MatInfo *info)
1241: {
1242: Mat_MPIRowbs *mat = (Mat_MPIRowbs*)A->data;
1243: PetscReal isend[5],irecv[5];
1247: info->rows_global = (double)A->rmap.N;
1248: info->columns_global = (double)A->cmap.N;
1249: info->rows_local = (double)A->cmap.n;
1250: info->columns_local = (double)A->rmap.n;
1251: info->block_size = 1.0;
1252: info->mallocs = (double)mat->reallocs;
1253: isend[0] = mat->nz; isend[1] = mat->maxnz; isend[2] = mat->maxnz - mat->nz;
1254: isend[3] = A->mem; isend[4] = info->mallocs;
1256: if (flag == MAT_LOCAL) {
1257: info->nz_used = isend[0];
1258: info->nz_allocated = isend[1];
1259: info->nz_unneeded = isend[2];
1260: info->memory = isend[3];
1261: info->mallocs = isend[4];
1262: } else if (flag == MAT_GLOBAL_MAX) {
1263: MPI_Allreduce(isend,irecv,3,MPIU_REAL,MPI_MAX,A->comm);
1264: info->nz_used = irecv[0];
1265: info->nz_allocated = irecv[1];
1266: info->nz_unneeded = irecv[2];
1267: info->memory = irecv[3];
1268: info->mallocs = irecv[4];
1269: } else if (flag == MAT_GLOBAL_SUM) {
1270: MPI_Allreduce(isend,irecv,3,MPIU_REAL,MPI_SUM,A->comm);
1271: info->nz_used = irecv[0];
1272: info->nz_allocated = irecv[1];
1273: info->nz_unneeded = irecv[2];
1274: info->memory = irecv[3];
1275: info->mallocs = irecv[4];
1276: }
1277: return(0);
1278: }
1282: PetscErrorCode MatGetDiagonal_MPIRowbs(Mat mat,Vec v)
1283: {
1284: Mat_MPIRowbs *a = (Mat_MPIRowbs*)mat->data;
1285: BSsprow **rs = a->A->rows;
1287: int i,n;
1288: PetscScalar *x,zero = 0.0;
1291: if (mat->factor) SETERRQ(PETSC_ERR_ARG_WRONGSTATE,"Not for factored matrix");
1292: if (!a->blocksolveassembly) {
1293: MatAssemblyEnd_MPIRowbs_ForBlockSolve(mat);
1294: }
1296: VecSet(v,zero);
1297: VecGetLocalSize(v,&n);
1298: if (n != mat->rmap.n) SETERRQ(PETSC_ERR_ARG_SIZ,"Nonconforming mat and vec");
1299: VecGetArray(v,&x);
1300: for (i=0; i<mat->rmap.n; i++) {
1301: x[i] = rs[i]->nz[rs[i]->diag_ind];
1302: }
1303: VecRestoreArray(v,&x);
1304: return(0);
1305: }
1309: PetscErrorCode MatDestroy_MPIRowbs(Mat mat)
1310: {
1311: Mat_MPIRowbs *a = (Mat_MPIRowbs*)mat->data;
1312: BSspmat *A = a->A;
1313: BSsprow *vs;
1315: int i;
1318: #if defined(PETSC_USE_LOG)
1319: PetscLogObjectState((PetscObject)mat,"Rows=%d, Cols=%d",mat->rmap.N,mat->cmap.N);
1320: #endif
1321: MatStashDestroy_Private(&mat->stash);
1322: if (a->bsmap) {
1323: PetscFree(a->bsmap->vlocal2global);
1324: PetscFree(a->bsmap->vglobal2local);
1325: if (a->bsmap->vglobal2proc) (*a->bsmap->free_g2p)(a->bsmap->vglobal2proc);
1326: PetscFree(a->bsmap);
1327: }
1329: if (A) {
1330: for (i=0; i<mat->rmap.n; i++) {
1331: vs = A->rows[i];
1332: MatFreeRowbs_Private(mat,vs->length,vs->col,vs->nz);
1333: }
1334: /* Note: A->map = a->bsmap is freed above */
1335: PetscFree(A->rows);
1336: PetscFree(A);
1337: }
1338: if (a->procinfo) {BSfree_ctx(a->procinfo);CHKERRBS(0);}
1339: if (a->diag) {VecDestroy(a->diag);}
1340: if (a->xwork) {VecDestroy(a->xwork);}
1341: if (a->pA) {BSfree_par_mat(a->pA);CHKERRBS(0);}
1342: if (a->fpA) {BSfree_copy_par_mat(a->fpA);CHKERRBS(0);}
1343: if (a->comm_pA) {BSfree_comm(a->comm_pA);CHKERRBS(0);}
1344: if (a->comm_fpA) {BSfree_comm(a->comm_fpA);CHKERRBS(0);}
1345: PetscFree(a->imax);
1346: MPI_Comm_free(&(a->comm_mpirowbs));
1347: PetscFree(a);
1349: PetscObjectChangeTypeName((PetscObject)mat,0);
1350: PetscObjectComposeFunction((PetscObject)mat,"MatMPIRowbsSetPreallocation_C","",PETSC_NULL);
1351: return(0);
1352: }
1356: PetscErrorCode MatSetOption_MPIRowbs(Mat A,MatOption op)
1357: {
1358: Mat_MPIRowbs *a = (Mat_MPIRowbs*)A->data;
1362: switch (op) {
1363: case MAT_ROW_ORIENTED:
1364: a->roworiented = PETSC_TRUE;
1365: break;
1366: case MAT_COLUMN_ORIENTED:
1367: a->roworiented = PETSC_FALSE;
1368: break;
1369: case MAT_COLUMNS_SORTED:
1370: a->sorted = 1;
1371: break;
1372: case MAT_COLUMNS_UNSORTED:
1373: a->sorted = 0;
1374: break;
1375: case MAT_NO_NEW_NONZERO_LOCATIONS:
1376: a->nonew = 1;
1377: break;
1378: case MAT_YES_NEW_NONZERO_LOCATIONS:
1379: a->nonew = 0;
1380: break;
1381: case MAT_DO_NOT_USE_INODES:
1382: a->bs_color_single = 1;
1383: break;
1384: case MAT_YES_NEW_DIAGONALS:
1385: case MAT_ROWS_SORTED:
1386: case MAT_NEW_NONZERO_LOCATION_ERR:
1387: case MAT_NEW_NONZERO_ALLOCATION_ERR:
1388: case MAT_ROWS_UNSORTED:
1389: case MAT_USE_HASH_TABLE:
1390: PetscInfo1(A,"Option %d ignored\n",op);
1391: break;
1392: case MAT_IGNORE_OFF_PROC_ENTRIES:
1393: a->donotstash = PETSC_TRUE;
1394: break;
1395: case MAT_NO_NEW_DIAGONALS:
1396: SETERRQ(PETSC_ERR_SUP,"MAT_NO_NEW_DIAGONALS");
1397: break;
1398: case MAT_KEEP_ZEROED_ROWS:
1399: a->keepzeroedrows = PETSC_TRUE;
1400: break;
1401: case MAT_SYMMETRIC:
1402: BSset_mat_symmetric(a->A,PETSC_TRUE);CHKERRBS(0);
1403: break;
1404: case MAT_STRUCTURALLY_SYMMETRIC:
1405: case MAT_NOT_SYMMETRIC:
1406: case MAT_NOT_STRUCTURALLY_SYMMETRIC:
1407: case MAT_HERMITIAN:
1408: case MAT_NOT_HERMITIAN:
1409: case MAT_SYMMETRY_ETERNAL:
1410: case MAT_NOT_SYMMETRY_ETERNAL:
1411: break;
1412: default:
1413: SETERRQ1(PETSC_ERR_SUP,"unknown option %d",op);
1414: break;
1415: }
1416: return(0);
1417: }
1421: PetscErrorCode MatGetRow_MPIRowbs(Mat AA,int row,int *nz,int **idx,PetscScalar **v)
1422: {
1423: Mat_MPIRowbs *mat = (Mat_MPIRowbs*)AA->data;
1424: BSspmat *A = mat->A;
1425: BSsprow *rs;
1426:
1428: if (row < AA->rmap.rstart || row >= AA->rmap.rend) SETERRQ(PETSC_ERR_ARG_OUTOFRANGE,"Only local rows");
1430: rs = A->rows[row - AA->rmap.rstart];
1431: *nz = rs->length;
1432: if (v) *v = rs->nz;
1433: if (idx) *idx = rs->col;
1434: return(0);
1435: }
1439: PetscErrorCode MatRestoreRow_MPIRowbs(Mat A,int row,int *nz,int **idx,PetscScalar **v)
1440: {
1442: return(0);
1443: }
1445: /* ------------------------------------------------------------------ */
1449: PetscErrorCode MatSetUpPreallocation_MPIRowbs(Mat A)
1450: {
1454: MatMPIRowbsSetPreallocation(A,PETSC_DEFAULT,0);
1455: return(0);
1456: }
1458: /* -------------------------------------------------------------------*/
1459: static struct _MatOps MatOps_Values = {MatSetValues_MPIRowbs,
1460: MatGetRow_MPIRowbs,
1461: MatRestoreRow_MPIRowbs,
1462: MatMult_MPIRowbs,
1463: /* 4*/ MatMultAdd_MPIRowbs,
1464: MatMult_MPIRowbs,
1465: MatMultAdd_MPIRowbs,
1466: MatSolve_MPIRowbs,
1467: 0,
1468: 0,
1469: /*10*/ 0,
1470: 0,
1471: 0,
1472: 0,
1473: 0,
1474: /*15*/ MatGetInfo_MPIRowbs,
1475: 0,
1476: MatGetDiagonal_MPIRowbs,
1477: 0,
1478: MatNorm_MPIRowbs,
1479: /*20*/ MatAssemblyBegin_MPIRowbs,
1480: MatAssemblyEnd_MPIRowbs,
1481: 0,
1482: MatSetOption_MPIRowbs,
1483: MatZeroEntries_MPIRowbs,
1484: /*25*/ MatZeroRows_MPIRowbs,
1485: 0,
1486: MatLUFactorNumeric_MPIRowbs,
1487: 0,
1488: MatCholeskyFactorNumeric_MPIRowbs,
1489: /*30*/ MatSetUpPreallocation_MPIRowbs,
1490: MatILUFactorSymbolic_MPIRowbs,
1491: MatIncompleteCholeskyFactorSymbolic_MPIRowbs,
1492: 0,
1493: 0,
1494: /*35*/ 0,
1495: MatForwardSolve_MPIRowbs,
1496: MatBackwardSolve_MPIRowbs,
1497: 0,
1498: 0,
1499: /*40*/ 0,
1500: MatGetSubMatrices_MPIRowbs,
1501: 0,
1502: 0,
1503: 0,
1504: /*45*/ 0,
1505: MatScale_MPIRowbs,
1506: 0,
1507: 0,
1508: 0,
1509: /*50*/ 0,
1510: 0,
1511: 0,
1512: 0,
1513: 0,
1514: /*55*/ 0,
1515: 0,
1516: 0,
1517: 0,
1518: 0,
1519: /*60*/ MatGetSubMatrix_MPIRowbs,
1520: MatDestroy_MPIRowbs,
1521: MatView_MPIRowbs,
1522: 0,
1523: MatUseScaledForm_MPIRowbs,
1524: /*65*/ MatScaleSystem_MPIRowbs,
1525: MatUnScaleSystem_MPIRowbs,
1526: 0,
1527: 0,
1528: 0,
1529: /*70*/ 0,
1530: 0,
1531: 0,
1532: 0,
1533: 0,
1534: /*75*/ 0,
1535: 0,
1536: 0,
1537: 0,
1538: 0,
1539: /*80*/ 0,
1540: 0,
1541: 0,
1542: 0,
1543: MatLoad_MPIRowbs,
1544: /*85*/ 0,
1545: 0,
1546: 0,
1547: 0,
1548: 0,
1549: /*90*/ 0,
1550: 0,
1551: 0,
1552: 0,
1553: 0,
1554: /*95*/ 0,
1555: 0,
1556: 0,
1557: 0};
1559: /* ------------------------------------------------------------------- */
1564: PetscErrorCode MatMPIRowbsSetPreallocation_MPIRowbs(Mat mat,int nz,const int nnz[])
1565: {
1569: mat->preallocated = PETSC_TRUE;
1570: MatCreateMPIRowbs_local(mat,nz,nnz);
1571: return(0);
1572: }
1575: /*MC
1576: MATMPIROWBS - MATMPIROWBS = "mpirowbs" - A matrix type providing ILU and ICC for distributed sparse matrices for use
1577: with the external package BlockSolve95. If BlockSolve95 is installed (see the manual for instructions
1578: on how to declare the existence of external packages), a matrix type can be constructed which invokes
1579: BlockSolve95 preconditioners and solvers.
1581: Options Database Keys:
1582: . -mat_type mpirowbs - sets the matrix type to "mpirowbs" during a call to MatSetFromOptions()
1584: Level: beginner
1586: .seealso: MatCreateMPIRowbs
1587: M*/
1592: PetscErrorCode MatCreate_MPIRowbs(Mat A)
1593: {
1594: Mat_MPIRowbs *a;
1595: BSmapping *bsmap;
1596: BSoff_map *bsoff;
1598: int *offset,m,M;
1599: PetscTruth flg1,flg3;
1600: BSprocinfo *bspinfo;
1601: MPI_Comm comm;
1602:
1604: comm = A->comm;
1606: PetscNew(Mat_MPIRowbs,&a);
1607: A->data = (void*)a;
1608: PetscMemcpy(A->ops,&MatOps_Values,sizeof(struct _MatOps));
1609: A->factor = 0;
1610: A->mapping = 0;
1611: a->vecs_permscale = PETSC_FALSE;
1612: A->insertmode = NOT_SET_VALUES;
1613: a->blocksolveassembly = 0;
1614: a->keepzeroedrows = PETSC_FALSE;
1616: MPI_Comm_rank(comm,&a->rank);
1617: MPI_Comm_size(comm,&a->size);
1620: PetscMapInitialize(comm,&A->rmap);
1621: PetscMapInitialize(comm,&A->cmap);
1622: m = A->rmap.n;
1623: M = A->rmap.N;
1625: PetscMalloc((A->rmap.n+1)*sizeof(int),&a->imax);
1626: a->reallocs = 0;
1628: /* build cache for off array entries formed */
1629: MatStashCreate_Private(A->comm,1,&A->stash);
1630: a->donotstash = PETSC_FALSE;
1632: /* Initialize BlockSolve information */
1633: a->A = 0;
1634: a->pA = 0;
1635: a->comm_pA = 0;
1636: a->fpA = 0;
1637: a->comm_fpA = 0;
1638: a->alpha = 1.0;
1639: a->0;
1640: a->failures = 0;
1641: MPI_Comm_dup(A->comm,&(a->comm_mpirowbs));
1642: VecCreateMPI(A->comm,A->rmap.n,A->rmap.N,&(a->diag));
1643: VecDuplicate(a->diag,&(a->xwork));
1644: PetscLogObjectParent(A,a->diag); PetscLogObjectParent(A,a->xwork);
1645: PetscLogObjectMemory(A,(A->rmap.n+1)*sizeof(PetscScalar));
1646: bspinfo = BScreate_ctx();CHKERRBS(0);
1647: a->procinfo = bspinfo;
1648: BSctx_set_id(bspinfo,a->rank);CHKERRBS(0);
1649: BSctx_set_np(bspinfo,a->size);CHKERRBS(0);
1650: BSctx_set_ps(bspinfo,a->comm_mpirowbs);CHKERRBS(0);
1651: BSctx_set_cs(bspinfo,INT_MAX);CHKERRBS(0);
1652: BSctx_set_is(bspinfo,INT_MAX);CHKERRBS(0);
1653: BSctx_set_ct(bspinfo,IDO);CHKERRBS(0);
1654: #if defined(PETSC_USE_DEBUG)
1655: BSctx_set_err(bspinfo,1);CHKERRBS(0); /* BS error checking */
1656: #endif
1657: BSctx_set_rt(bspinfo,1);CHKERRBS(0);
1658: #if defined (PETSC_USE_INFO)
1659: PetscOptionsHasName(PETSC_NULL,"-info",&flg1);
1660: if (flg1) {
1661: BSctx_set_pr(bspinfo,1);CHKERRBS(0);
1662: }
1663: #endif
1664: PetscOptionsBegin(A->comm,PETSC_NULL,"Options for MPIROWBS matrix","Mat");
1665: PetscOptionsTruth("-pc_factor_factorpointwise","Do not optimize for inodes (slow)",PETSC_NULL,PETSC_FALSE,&flg1,PETSC_NULL);
1666: PetscOptionsTruth("-mat_rowbs_no_inode","Do not optimize for inodes (slow)",PETSC_NULL,PETSC_FALSE,&flg3,PETSC_NULL);
1667: PetscOptionsEnd();
1668: if (flg1 || flg3) {
1669: BSctx_set_si(bspinfo,1);CHKERRBS(0);
1670: } else {
1671: BSctx_set_si(bspinfo,0);CHKERRBS(0);
1672: }
1673: #if defined(PETSC_USE_LOG)
1674: MLOG_INIT(); /* Initialize logging */
1675: #endif
1677: /* Compute global offsets */
1678: offset = &A->rmap.rstart;
1680: PetscNew(BSmapping,&a->bsmap);
1681: PetscLogObjectMemory(A,sizeof(BSmapping));
1682: bsmap = a->bsmap;
1683: PetscMalloc(sizeof(int),&bsmap->vlocal2global);
1684: *((int*)bsmap->vlocal2global) = (*offset);
1685: bsmap->flocal2global = BSloc2glob;
1686: bsmap->free_l2g = 0;
1687: PetscMalloc(sizeof(int),&bsmap->vglobal2local);
1688: *((int*)bsmap->vglobal2local) = (*offset);
1689: bsmap->fglobal2local = BSglob2loc;
1690: bsmap->free_g2l = 0;
1691: bsoff = BSmake_off_map(*offset,bspinfo,A->rmap.N);
1692: bsmap->vglobal2proc = (void*)bsoff;
1693: bsmap->fglobal2proc = BSglob2proc;
1694: bsmap->free_g2p = (void(*)(void*)) BSfree_off_map;
1695: PetscObjectComposeFunctionDynamic((PetscObject)A,"MatMPIRowbsSetPreallocation_C",
1696: "MatMPIRowbsSetPreallocation_MPIRowbs",
1697: MatMPIRowbsSetPreallocation_MPIRowbs);
1698: PetscObjectChangeTypeName((PetscObject)A,MATMPIROWBS);
1699: return(0);
1700: }
1705: /* @
1706: MatMPIRowbsSetPreallocation - Sets the number of expected nonzeros
1707: per row in the matrix.
1709: Input Parameter:
1710: + mat - matrix
1711: . nz - maximum expected for any row
1712: - nzz - number expected in each row
1714: Note:
1715: This routine is valid only for matrices stored in the MATMPIROWBS
1716: format.
1717: @ */
1718: PetscErrorCode MatMPIRowbsSetPreallocation(Mat mat,int nz,const int nnz[])
1719: {
1720: PetscErrorCode ierr,(*f)(Mat,int,const int[]);
1723: PetscObjectQueryFunction((PetscObject)mat,"MatMPIRowbsSetPreallocation_C",(void (**)(void))&f);
1724: if (f) {
1725: (*f)(mat,nz,nnz);
1726: }
1727: return(0);
1728: }
1730: /* --------------- extra BlockSolve-specific routines -------------- */
1733: /* @
1734: MatGetBSProcinfo - Gets the BlockSolve BSprocinfo context, which the
1735: user can then manipulate to alter the default parameters.
1737: Input Parameter:
1738: mat - matrix
1740: Output Parameter:
1741: procinfo - processor information context
1743: Note:
1744: This routine is valid only for matrices stored in the MATMPIROWBS
1745: format.
1746: @ */
1747: PetscErrorCode MatGetBSProcinfo(Mat mat,BSprocinfo *procinfo)
1748: {
1749: Mat_MPIRowbs *a = (Mat_MPIRowbs*)mat->data;
1750: PetscTruth ismpirowbs;
1754: PetscTypeCompare((PetscObject)mat,MATMPIROWBS,&ismpirowbs);
1755: if (!ismpirowbs) SETERRQ(PETSC_ERR_ARG_WRONG,"For MATMPIROWBS matrix type");
1756: procinfo = a->procinfo;
1757: return(0);
1758: }
1762: PetscErrorCode MatLoad_MPIRowbs(PetscViewer viewer,MatType type,Mat *newmat)
1763: {
1764: Mat_MPIRowbs *a;
1765: BSspmat *A;
1766: BSsprow **rs;
1767: Mat mat;
1769: int i,nz,j,rstart,rend,fd,*ourlens,*sndcounts = 0,*procsnz;
1770: int header[4],rank,size,*rowlengths = 0,M,m,*rowners,maxnz,*cols;
1771: PetscScalar *vals;
1772: MPI_Comm comm = ((PetscObject)viewer)->comm;
1773: MPI_Status status;
1776: MPI_Comm_size(comm,&size);
1777: MPI_Comm_rank(comm,&rank);
1778: if (!rank) {
1779: PetscViewerBinaryGetDescriptor(viewer,&fd);
1780: PetscBinaryRead(fd,(char *)header,4,PETSC_INT);
1781: if (header[0] != MAT_FILE_COOKIE) SETERRQ(PETSC_ERR_FILE_UNEXPECTED,"Not matrix object");
1782: if (header[3] < 0) {
1783: SETERRQ(PETSC_ERR_FILE_UNEXPECTED,"Matrix stored in special format,cannot load as MPIRowbs");
1784: }
1785: }
1787: MPI_Bcast(header+1,3,MPI_INT,0,comm);
1788: M = header[1];
1790: /* determine ownership of all rows */
1791: m = M/size + ((M % size) > rank);
1792: PetscMalloc((size+2)*sizeof(int),&rowners);
1793: MPI_Allgather(&m,1,MPI_INT,rowners+1,1,MPI_INT,comm);
1794: rowners[0] = 0;
1795: for (i=2; i<=size; i++) {
1796: rowners[i] += rowners[i-1];
1797: }
1798: rstart = rowners[rank];
1799: rend = rowners[rank+1];
1801: /* distribute row lengths to all processors */
1802: PetscMalloc((rend-rstart)*sizeof(int),&ourlens);
1803: if (!rank) {
1804: PetscMalloc(M*sizeof(int),&rowlengths);
1805: PetscBinaryRead(fd,rowlengths,M,PETSC_INT);
1806: PetscMalloc(size*sizeof(int),&sndcounts);
1807: for (i=0; i<size; i++) sndcounts[i] = rowners[i+1] - rowners[i];
1808: MPI_Scatterv(rowlengths,sndcounts,rowners,MPI_INT,ourlens,rend-rstart,MPI_INT,0,comm);
1809: PetscFree(sndcounts);
1810: } else {
1811: MPI_Scatterv(0,0,0,MPI_INT,ourlens,rend-rstart,MPI_INT,0,comm);
1812: }
1814: /* create our matrix */
1815: MatCreate(comm,newmat);
1816: MatSetSizes(*newmat,m,m,M,M);
1817: MatSetType(*newmat,type);
1818: MatMPIRowbsSetPreallocation(*newmat,0,ourlens);
1819: mat = *newmat;
1820: PetscFree(ourlens);
1822: a = (Mat_MPIRowbs*)mat->data;
1823: A = a->A;
1824: rs = A->rows;
1826: if (!rank) {
1827: /* calculate the number of nonzeros on each processor */
1828: PetscMalloc(size*sizeof(int),&procsnz);
1829: PetscMemzero(procsnz,size*sizeof(int));
1830: for (i=0; i<size; i++) {
1831: for (j=rowners[i]; j< rowners[i+1]; j++) {
1832: procsnz[i] += rowlengths[j];
1833: }
1834: }
1835: PetscFree(rowlengths);
1837: /* determine max buffer needed and allocate it */
1838: maxnz = 0;
1839: for (i=0; i<size; i++) {
1840: maxnz = PetscMax(maxnz,procsnz[i]);
1841: }
1842: PetscMalloc(maxnz*sizeof(int),&cols);
1844: /* read in my part of the matrix column indices */
1845: nz = procsnz[0];
1846: PetscBinaryRead(fd,cols,nz,PETSC_INT);
1847:
1848: /* insert it into my part of matrix */
1849: nz = 0;
1850: for (i=0; i<A->num_rows; i++) {
1851: for (j=0; j<a->imax[i]; j++) {
1852: rs[i]->col[j] = cols[nz++];
1853: }
1854: rs[i]->length = a->imax[i];
1855: }
1856: /* read in parts for all other processors */
1857: for (i=1; i<size; i++) {
1858: nz = procsnz[i];
1859: PetscBinaryRead(fd,cols,nz,PETSC_INT);
1860: MPI_Send(cols,nz,MPI_INT,i,mat->tag,comm);
1861: }
1862: PetscFree(cols);
1863: PetscMalloc(maxnz*sizeof(PetscScalar),&vals);
1865: /* read in my part of the matrix numerical values */
1866: nz = procsnz[0];
1867: PetscBinaryRead(fd,vals,nz,PETSC_SCALAR);
1868:
1869: /* insert it into my part of matrix */
1870: nz = 0;
1871: for (i=0; i<A->num_rows; i++) {
1872: for (j=0; j<a->imax[i]; j++) {
1873: rs[i]->nz[j] = vals[nz++];
1874: }
1875: }
1876: /* read in parts for all other processors */
1877: for (i=1; i<size; i++) {
1878: nz = procsnz[i];
1879: PetscBinaryRead(fd,vals,nz,PETSC_SCALAR);
1880: MPI_Send(vals,nz,MPIU_SCALAR,i,mat->tag,comm);
1881: }
1882: PetscFree(vals);
1883: PetscFree(procsnz);
1884: } else {
1885: /* determine buffer space needed for message */
1886: nz = 0;
1887: for (i=0; i<A->num_rows; i++) {
1888: nz += a->imax[i];
1889: }
1890: PetscMalloc(nz*sizeof(int),&cols);
1892: /* receive message of column indices*/
1893: MPI_Recv(cols,nz,MPI_INT,0,mat->tag,comm,&status);
1894: MPI_Get_count(&status,MPI_INT,&maxnz);
1895: if (maxnz != nz) SETERRQ(PETSC_ERR_FILE_UNEXPECTED,"something is wrong");
1897: /* insert it into my part of matrix */
1898: nz = 0;
1899: for (i=0; i<A->num_rows; i++) {
1900: for (j=0; j<a->imax[i]; j++) {
1901: rs[i]->col[j] = cols[nz++];
1902: }
1903: rs[i]->length = a->imax[i];
1904: }
1905: PetscFree(cols);
1906: PetscMalloc(nz*sizeof(PetscScalar),&vals);
1908: /* receive message of values*/
1909: MPI_Recv(vals,nz,MPIU_SCALAR,0,mat->tag,comm,&status);
1910: MPI_Get_count(&status,MPIU_SCALAR,&maxnz);
1911: if (maxnz != nz) SETERRQ(PETSC_ERR_FILE_UNEXPECTED,"something is wrong");
1913: /* insert it into my part of matrix */
1914: nz = 0;
1915: for (i=0; i<A->num_rows; i++) {
1916: for (j=0; j<a->imax[i]; j++) {
1917: rs[i]->nz[j] = vals[nz++];
1918: }
1919: rs[i]->length = a->imax[i];
1920: }
1921: PetscFree(vals);
1922: }
1923: PetscFree(rowners);
1924: a->nz = a->maxnz;
1925: MatAssemblyBegin(mat,MAT_FINAL_ASSEMBLY);
1926: MatAssemblyEnd(mat,MAT_FINAL_ASSEMBLY);
1927: return(0);
1928: }
1930: /*
1931: Special destroy and view routines for factored matrices
1932: */
1935: static PetscErrorCode MatDestroy_MPIRowbs_Factored(Mat mat)
1936: {
1938: #if defined(PETSC_USE_LOG)
1939: PetscLogObjectState((PetscObject)mat,"Rows=%d, Cols=%d",mat->rmap.N,mat->cmap.N);
1940: #endif
1941: return(0);
1942: }
1946: static PetscErrorCode MatView_MPIRowbs_Factored(Mat mat,PetscViewer viewer)
1947: {
1951: MatView((Mat) mat->data,viewer);
1952: return(0);
1953: }
1957: PetscErrorCode MatIncompleteCholeskyFactorSymbolic_MPIRowbs(Mat mat,IS isrow,MatFactorInfo *info,Mat *newfact)
1958: {
1959: /* Note: f is not currently used in BlockSolve */
1960: Mat newmat;
1961: Mat_MPIRowbs *mbs = (Mat_MPIRowbs*)mat->data;
1963: PetscTruth idn;
1966: if (isrow) {
1967: ISIdentity(isrow,&idn);
1968: if (!idn) SETERRQ(PETSC_ERR_SUP,"Only identity row permutation supported");
1969: }
1971: if (!mat->symmetric) {
1972: SETERRQ(PETSC_ERR_ARG_WRONGSTATE,"To use incomplete Cholesky \n\
1973: preconditioning with a MATMPIROWBS matrix you must declare it to be \n\
1974: symmetric using the option MatSetOption(A,MAT_SYMMETRIC)");
1975: }
1977: /* If the icc_storage flag wasn't set before the last blocksolveassembly, */
1978: /* we must completely redo the assembly as a different storage format is required. */
1979: if (mbs->blocksolveassembly && !mbs->assembled_icc_storage) {
1980: mat->same_nonzero = PETSC_FALSE;
1981: mbs->blocksolveassembly = 0;
1982: }
1984: if (!mbs->blocksolveassembly) {
1985: BSset_mat_icc_storage(mbs->A,PETSC_TRUE);CHKERRBS(0);
1986: BSset_mat_symmetric(mbs->A,PETSC_TRUE);CHKERRBS(0);
1987: MatAssemblyEnd_MPIRowbs_ForBlockSolve(mat);
1988: }
1990: /* Copy permuted matrix */
1991: if (mbs->fpA) {BSfree_copy_par_mat(mbs->fpA);CHKERRBS(0);}
1992: mbs->fpA = BScopy_par_mat(mbs->pA);CHKERRBS(0);
1994: /* Set up the communication for factorization */
1995: if (mbs->comm_fpA) {BSfree_comm(mbs->comm_fpA);CHKERRBS(0);}
1996: mbs->comm_fpA = BSsetup_factor(mbs->fpA,mbs->procinfo);CHKERRBS(0);
1998: /*
1999: Create a new Mat structure to hold the "factored" matrix,
2000: not this merely contains a pointer to the original matrix, since
2001: the original matrix contains the factor information.
2002: */
2003: PetscHeaderCreate(newmat,_p_Mat,struct _MatOps,MAT_COOKIE,-1,"Mat",mat->comm,MatDestroy,MatView);
2004: PetscLogObjectMemory(newmat,sizeof(struct _p_Mat));
2006: newmat->data = (void*)mat;
2007: PetscMemcpy(newmat->ops,&MatOps_Values,sizeof(struct _MatOps));
2008: newmat->ops->destroy = MatDestroy_MPIRowbs_Factored;
2009: newmat->ops->view = MatView_MPIRowbs_Factored;
2010: newmat->factor = 1;
2011: newmat->preallocated = PETSC_TRUE;
2012: PetscMapCopy(mat->comm,&mat->rmap,&newmat->rmap);
2013: PetscMapCopy(mat->comm,&mat->cmap,&newmat->cmap);
2015: PetscStrallocpy(MATMPIROWBS,&newmat->type_name);
2017: *newfact = newmat;
2018: return(0);
2019: }
2023: PetscErrorCode MatILUFactorSymbolic_MPIRowbs(Mat mat,IS isrow,IS iscol,MatFactorInfo* info,Mat *newfact)
2024: {
2025: Mat newmat;
2026: Mat_MPIRowbs *mbs = (Mat_MPIRowbs*)mat->data;
2028: PetscTruth idn;
2031: if (info->levels) SETERRQ(PETSC_ERR_SUP,"Blocksolve ILU only supports 0 fill");
2032: if (isrow) {
2033: ISIdentity(isrow,&idn);
2034: if (!idn) SETERRQ(PETSC_ERR_SUP,"Only identity row permutation supported");
2035: }
2036: if (iscol) {
2037: ISIdentity(iscol,&idn);
2038: if (!idn) SETERRQ(PETSC_ERR_SUP,"Only identity column permutation supported");
2039: }
2041: if (!mbs->blocksolveassembly) {
2042: MatAssemblyEnd_MPIRowbs_ForBlockSolve(mat);
2043: }
2044:
2045: /* if (mat->symmetric) { */
2046: /* SETERRQ(PETSC_ERR_ARG_WRONGSTATE,"To use ILU preconditioner with \n\ */
2047: /* MatCreateMPIRowbs() matrix you CANNOT declare it to be a symmetric matrix\n\ */
2048: /* using the option MatSetOption(A,MAT_SYMMETRIC)"); */
2049: /* } */
2051: /* Copy permuted matrix */
2052: if (mbs->fpA) {BSfree_copy_par_mat(mbs->fpA);CHKERRBS(0);}
2053: mbs->fpA = BScopy_par_mat(mbs->pA);CHKERRBS(0);
2055: /* Set up the communication for factorization */
2056: if (mbs->comm_fpA) {BSfree_comm(mbs->comm_fpA);CHKERRBS(0);}
2057: mbs->comm_fpA = BSsetup_factor(mbs->fpA,mbs->procinfo);CHKERRBS(0);
2059: /*
2060: Create a new Mat structure to hold the "factored" matrix,
2061: not this merely contains a pointer to the original matrix, since
2062: the original matrix contains the factor information.
2063: */
2064: PetscHeaderCreate(newmat,_p_Mat,struct _MatOps,MAT_COOKIE,-1,"Mat",mat->comm,MatDestroy,MatView);
2065: PetscLogObjectMemory(newmat,sizeof(struct _p_Mat));
2067: newmat->data = (void*)mat;
2068: PetscMemcpy(newmat->ops,&MatOps_Values,sizeof(struct _MatOps));
2069: newmat->ops->destroy = MatDestroy_MPIRowbs_Factored;
2070: newmat->ops->view = MatView_MPIRowbs_Factored;
2071: newmat->factor = 1;
2072: newmat->preallocated = PETSC_TRUE;
2074: PetscMapCopy(mat->comm,&mat->rmap,&newmat->rmap);
2075: PetscMapCopy(mat->comm,&mat->cmap,&newmat->cmap);
2077: PetscStrallocpy(MATMPIROWBS,&newmat->type_name);
2079: *newfact = newmat;
2080: return(0);
2081: }
2085: /*@C
2086: MatCreateMPIRowbs - Creates a sparse parallel matrix in the MATMPIROWBS
2087: format. This format is intended primarily as an interface for BlockSolve95.
2089: Collective on MPI_Comm
2091: Input Parameters:
2092: + comm - MPI communicator
2093: . m - number of local rows (or PETSC_DECIDE to have calculated)
2094: . M - number of global rows (or PETSC_DECIDE to have calculated)
2095: . nz - number of nonzeros per row (same for all local rows)
2096: - nnz - number of nonzeros per row (possibly different for each row).
2098: Output Parameter:
2099: . newA - the matrix
2101: Notes:
2102: If PETSC_DECIDE or PETSC_DETERMINE is used for a particular argument on one processor
2103: than it must be used on all processors that share the object for that argument.
2105: The user MUST specify either the local or global matrix dimensions
2106: (possibly both).
2108: Specify the preallocated storage with either nz or nnz (not both). Set
2109: nz=PETSC_DEFAULT and nnz=PETSC_NULL for PETSc to control dynamic memory
2110: allocation.
2112: Notes:
2113: By default, the matrix is assumed to be nonsymmetric; the user can
2114: take advantage of special optimizations for symmetric matrices by calling
2115: $ MatSetOption(mat,MAT_SYMMETRIC)
2116: $ MatSetOption(mat,MAT_SYMMETRY_ETERNAL)
2117: BEFORE calling the routine MatAssemblyBegin().
2119: Internally, the MATMPIROWBS format inserts zero elements to the
2120: matrix if necessary, so that nonsymmetric matrices are considered
2121: to be symmetric in terms of their sparsity structure; this format
2122: is required for use of the parallel communication routines within
2123: BlockSolve95. In particular, if the matrix element A[i,j] exists,
2124: then PETSc will internally allocate a 0 value for the element
2125: A[j,i] during MatAssemblyEnd() if the user has not already set
2126: a value for the matrix element A[j,i].
2128: Options Database Keys:
2129: . -mat_rowbs_no_inode - Do not use inodes.
2131: Level: intermediate
2132:
2133: .keywords: matrix, row, symmetric, sparse, parallel, BlockSolve
2135: .seealso: MatCreate(), MatSetValues()
2136: @*/
2137: PetscErrorCode MatCreateMPIRowbs(MPI_Comm comm,int m,int M,int nz,const int nnz[],Mat *newA)
2138: {
2140:
2142: MatCreate(comm,newA);
2143: MatSetSizes(*newA,m,m,M,M);
2144: MatSetType(*newA,MATMPIROWBS);
2145: MatMPIRowbsSetPreallocation(*newA,nz,nnz);
2146: return(0);
2147: }
2150: /* -------------------------------------------------------------------------*/
2152: #include src/mat/impls/aij/seq/aij.h
2153: #include src/mat/impls/aij/mpi/mpiaij.h
2157: PetscErrorCode MatGetSubMatrices_MPIRowbs(Mat C,int ismax,const IS isrow[],const IS iscol[],MatReuse scall,Mat *submat[])
2158: {
2160: int nmax,nstages_local,nstages,i,pos,max_no;
2164: /* Allocate memory to hold all the submatrices */
2165: if (scall != MAT_REUSE_MATRIX) {
2166: PetscMalloc((ismax+1)*sizeof(Mat),submat);
2167: }
2168:
2169: /* Determine the number of stages through which submatrices are done */
2170: nmax = 20*1000000 / (C->cmap.N * sizeof(int));
2171: if (!nmax) nmax = 1;
2172: nstages_local = ismax/nmax + ((ismax % nmax)?1:0);
2174: /* Make sure every processor loops through the nstages */
2175: MPI_Allreduce(&nstages_local,&nstages,1,MPI_INT,MPI_MAX,C->comm);
2177: for (i=0,pos=0; i<nstages; i++) {
2178: if (pos+nmax <= ismax) max_no = nmax;
2179: else if (pos == ismax) max_no = 0;
2180: else max_no = ismax-pos;
2181: MatGetSubMatrices_MPIRowbs_Local(C,max_no,isrow+pos,iscol+pos,scall,*submat+pos);
2182: pos += max_no;
2183: }
2184: return(0);
2185: }
2186: /* -------------------------------------------------------------------------*/
2187: /* for now MatGetSubMatrices_MPIRowbs_Local get MPIAij submatrices of input
2188: matrix and preservs zeroes from structural symetry
2189: */
2192: PetscErrorCode MatGetSubMatrices_MPIRowbs_Local(Mat C,int ismax,const IS isrow[],const IS iscol[],MatReuse scall,Mat *submats)
2193: {
2194: Mat_MPIRowbs *c = (Mat_MPIRowbs *)(C->data);
2195: BSspmat *A = c->A;
2196: Mat_SeqAIJ *mat;
2198: int **irow,**icol,*nrow,*ncol,*w1,*w2,*w3,*w4,*rtable,start,end,size;
2199: int **sbuf1,**sbuf2,rank,m,i,j,k,l,ct1,ct2,**rbuf1,row,proc;
2200: int nrqs,msz,**ptr,idx,*req_size,*ctr,*pa,*tmp,tcol,nrqr;
2201: int **rbuf3,*req_source,**sbuf_aj,**rbuf2,max1,max2,**rmap;
2202: int **cmap,**lens,is_no,ncols,*cols,mat_i,*mat_j,tmp2,jmax,*irow_i;
2203: int len,ctr_j,*sbuf1_j,*sbuf_aj_i,*rbuf1_i,kmax,*cmap_i,*lens_i;
2204: int *rmap_i,tag0,tag1,tag2,tag3;
2205: MPI_Request *s_waits1,*r_waits1,*s_waits2,*r_waits2,*r_waits3;
2206: MPI_Request *r_waits4,*s_waits3,*s_waits4;
2207: MPI_Status *r_status1,*r_status2,*s_status1,*s_status3,*s_status2;
2208: MPI_Status *r_status3,*r_status4,*s_status4;
2209: MPI_Comm comm;
2210: FLOAT **rbuf4,**sbuf_aa,*vals,*sbuf_aa_i;
2211: PetscScalar *mat_a;
2212: PetscTruth sorted;
2213: int *onodes1,*olengths1;
2216: comm = C->comm;
2217: tag0 = C->tag;
2218: size = c->size;
2219: rank = c->rank;
2220: m = C->rmap.N;
2221:
2222: /* Get some new tags to keep the communication clean */
2223: PetscObjectGetNewTag((PetscObject)C,&tag1);
2224: PetscObjectGetNewTag((PetscObject)C,&tag2);
2225: PetscObjectGetNewTag((PetscObject)C,&tag3);
2227: /* Check if the col indices are sorted */
2228: for (i=0; i<ismax; i++) {
2229: ISSorted(isrow[i],&sorted);
2230: if (!sorted) SETERRQ(PETSC_ERR_ARG_WRONGSTATE,"ISrow is not sorted");
2231: ISSorted(iscol[i],&sorted);
2232: /* if (!sorted) SETERRQ(PETSC_ERR_ARG_WRONGSTATE,"IScol is not sorted"); */
2233: }
2235: len = (2*ismax+1)*(sizeof(int*)+ sizeof(int)) + (m+1)*sizeof(int);
2236: PetscMalloc(len,&irow);
2237: icol = irow + ismax;
2238: nrow = (int*)(icol + ismax);
2239: ncol = nrow + ismax;
2240: rtable = ncol + ismax;
2242: for (i=0; i<ismax; i++) {
2243: ISGetIndices(isrow[i],&irow[i]);
2244: ISGetIndices(iscol[i],&icol[i]);
2245: ISGetLocalSize(isrow[i],&nrow[i]);
2246: ISGetLocalSize(iscol[i],&ncol[i]);
2247: }
2249: /* Create hash table for the mapping :row -> proc*/
2250: for (i=0,j=0; i<size; i++) {
2251: jmax = C->rmap.range[i+1];
2252: for (; j<jmax; j++) {
2253: rtable[j] = i;
2254: }
2255: }
2257: /* evaluate communication - mesg to who, length of mesg, and buffer space
2258: required. Based on this, buffers are allocated, and data copied into them*/
2259: PetscMalloc(size*4*sizeof(int),&w1); /* mesg size */
2260: w2 = w1 + size; /* if w2[i] marked, then a message to proc i*/
2261: w3 = w2 + size; /* no of IS that needs to be sent to proc i */
2262: w4 = w3 + size; /* temp work space used in determining w1, w2, w3 */
2263: PetscMemzero(w1,size*3*sizeof(int)); /* initialize work vector*/
2264: for (i=0; i<ismax; i++) {
2265: PetscMemzero(w4,size*sizeof(int)); /* initialize work vector*/
2266: jmax = nrow[i];
2267: irow_i = irow[i];
2268: for (j=0; j<jmax; j++) {
2269: row = irow_i[j];
2270: proc = rtable[row];
2271: w4[proc]++;
2272: }
2273: for (j=0; j<size; j++) {
2274: if (w4[j]) { w1[j] += w4[j]; w3[j]++;}
2275: }
2276: }
2277:
2278: nrqs = 0; /* no of outgoing messages */
2279: msz = 0; /* total mesg length (for all procs) */
2280: w1[rank] = 0; /* no mesg sent to self */
2281: w3[rank] = 0;
2282: for (i=0; i<size; i++) {
2283: if (w1[i]) { w2[i] = 1; nrqs++;} /* there exists a message to proc i */
2284: }
2285: PetscMalloc((nrqs+1)*sizeof(int),&pa); /*(proc -array)*/
2286: for (i=0,j=0; i<size; i++) {
2287: if (w1[i]) { pa[j] = i; j++; }
2288: }
2290: /* Each message would have a header = 1 + 2*(no of IS) + data */
2291: for (i=0; i<nrqs; i++) {
2292: j = pa[i];
2293: w1[j] += w2[j] + 2* w3[j];
2294: msz += w1[j];
2295: }
2297: /* Determine the number of messages to expect, their lengths, from from-ids */
2298: PetscGatherNumberOfMessages(comm,w2,w1,&nrqr);
2299: PetscGatherMessageLengths(comm,nrqs,nrqr,w1,&onodes1,&olengths1);
2301: /* Now post the Irecvs corresponding to these messages */
2302: PetscPostIrecvInt(comm,tag0,nrqr,onodes1,olengths1,&rbuf1,&r_waits1);
2303:
2304: PetscFree(onodes1);
2305: PetscFree(olengths1);
2306:
2307: /* Allocate Memory for outgoing messages */
2308: len = 2*size*sizeof(int*) + 2*msz*sizeof(int) + size*sizeof(int);
2309: PetscMalloc(len,&sbuf1);
2310: ptr = sbuf1 + size; /* Pointers to the data in outgoing buffers */
2311: PetscMemzero(sbuf1,2*size*sizeof(int*));
2312: /* allocate memory for outgoing data + buf to receive the first reply */
2313: tmp = (int*)(ptr + size);
2314: ctr = tmp + 2*msz;
2316: {
2317: int *iptr = tmp,ict = 0;
2318: for (i=0; i<nrqs; i++) {
2319: j = pa[i];
2320: iptr += ict;
2321: sbuf1[j] = iptr;
2322: ict = w1[j];
2323: }
2324: }
2326: /* Form the outgoing messages */
2327: /* Initialize the header space */
2328: for (i=0; i<nrqs; i++) {
2329: j = pa[i];
2330: sbuf1[j][0] = 0;
2331: PetscMemzero(sbuf1[j]+1,2*w3[j]*sizeof(int));
2332: ptr[j] = sbuf1[j] + 2*w3[j] + 1;
2333: }
2334:
2335: /* Parse the isrow and copy data into outbuf */
2336: for (i=0; i<ismax; i++) {
2337: PetscMemzero(ctr,size*sizeof(int));
2338: irow_i = irow[i];
2339: jmax = nrow[i];
2340: for (j=0; j<jmax; j++) { /* parse the indices of each IS */
2341: row = irow_i[j];
2342: proc = rtable[row];
2343: if (proc != rank) { /* copy to the outgoing buf*/
2344: ctr[proc]++;
2345: *ptr[proc] = row;
2346: ptr[proc]++;
2347: }
2348: }
2349: /* Update the headers for the current IS */
2350: for (j=0; j<size; j++) { /* Can Optimise this loop too */
2351: if ((ctr_j = ctr[j])) {
2352: sbuf1_j = sbuf1[j];
2353: k = ++sbuf1_j[0];
2354: sbuf1_j[2*k] = ctr_j;
2355: sbuf1_j[2*k-1] = i;
2356: }
2357: }
2358: }
2360: /* Now post the sends */
2361: PetscMalloc((nrqs+1)*sizeof(MPI_Request),&s_waits1);
2362: for (i=0; i<nrqs; ++i) {
2363: j = pa[i];
2364: MPI_Isend(sbuf1[j],w1[j],MPI_INT,j,tag0,comm,s_waits1+i);
2365: }
2367: /* Post Receives to capture the buffer size */
2368: PetscMalloc((nrqs+1)*sizeof(MPI_Request),&r_waits2);
2369: PetscMalloc((nrqs+1)*sizeof(int*),&rbuf2);
2370: rbuf2[0] = tmp + msz;
2371: for (i=1; i<nrqs; ++i) {
2372: rbuf2[i] = rbuf2[i-1]+w1[pa[i-1]];
2373: }
2374: for (i=0; i<nrqs; ++i) {
2375: j = pa[i];
2376: MPI_Irecv(rbuf2[i],w1[j],MPI_INT,j,tag1,comm,r_waits2+i);
2377: }
2379: /* Send to other procs the buf size they should allocate */
2380:
2382: /* Receive messages*/
2383: PetscMalloc((nrqr+1)*sizeof(MPI_Request),&s_waits2);
2384: PetscMalloc((nrqr+1)*sizeof(MPI_Status),&r_status1);
2385: len = 2*nrqr*sizeof(int) + (nrqr+1)*sizeof(int*);
2386: PetscMalloc(len,&sbuf2);
2387: req_size = (int*)(sbuf2 + nrqr);
2388: req_source = req_size + nrqr;
2389:
2390: {
2391: BSsprow **sAi = A->rows;
2392: int id,rstart = C->rmap.rstart;
2393: int *sbuf2_i;
2395: for (i=0; i<nrqr; ++i) {
2396: MPI_Waitany(nrqr,r_waits1,&idx,r_status1+i);
2397: req_size[idx] = 0;
2398: rbuf1_i = rbuf1[idx];
2399: start = 2*rbuf1_i[0] + 1;
2400: MPI_Get_count(r_status1+i,MPI_INT,&end);
2401: PetscMalloc((end+1)*sizeof(int),&sbuf2[idx]);
2402: sbuf2_i = sbuf2[idx];
2403: for (j=start; j<end; j++) {
2404: id = rbuf1_i[j] - rstart;
2405: ncols = (sAi[id])->length;
2406: sbuf2_i[j] = ncols;
2407: req_size[idx] += ncols;
2408: }
2409: req_source[idx] = r_status1[i].MPI_SOURCE;
2410: /* form the header */
2411: sbuf2_i[0] = req_size[idx];
2412: for (j=1; j<start; j++) { sbuf2_i[j] = rbuf1_i[j]; }
2413: MPI_Isend(sbuf2_i,end,MPI_INT,req_source[idx],tag1,comm,s_waits2+i);
2414: }
2415: }
2416: PetscFree(r_status1);
2417: PetscFree(r_waits1);
2419: /* recv buffer sizes */
2420: /* Receive messages*/
2421:
2422: PetscMalloc((nrqs+1)*sizeof(int*),&rbuf3);
2423: PetscMalloc((nrqs+1)*sizeof(FLOAT *),&rbuf4);
2424: PetscMalloc((nrqs+1)*sizeof(MPI_Request),&r_waits3);
2425: PetscMalloc((nrqs+1)*sizeof(MPI_Request),&r_waits4);
2426: PetscMalloc((nrqs+1)*sizeof(MPI_Status),&r_status2);
2428: for (i=0; i<nrqs; ++i) {
2429: MPI_Waitany(nrqs,r_waits2,&idx,r_status2+i);
2430: PetscMalloc((rbuf2[idx][0]+1)*sizeof(int),&rbuf3[idx]);
2431: PetscMalloc((rbuf2[idx][0]+1)*sizeof(FLOAT),&rbuf4[idx]);
2432: MPI_Irecv(rbuf3[idx],rbuf2[idx][0],MPI_INT,r_status2[i].MPI_SOURCE,tag2,comm,r_waits3+idx);
2433: MPI_Irecv(rbuf4[idx],rbuf2[idx][0],MPIU_SCALAR,r_status2[i].MPI_SOURCE,tag3,comm,r_waits4+idx);
2434: }
2435: PetscFree(r_status2);
2436: PetscFree(r_waits2);
2437:
2438: /* Wait on sends1 and sends2 */
2439: PetscMalloc((nrqs+1)*sizeof(MPI_Status),&s_status1);
2440: PetscMalloc((nrqr+1)*sizeof(MPI_Status),&s_status2);
2442: if (nrqs) {MPI_Waitall(nrqs,s_waits1,s_status1);}
2443: if (nrqr) {MPI_Waitall(nrqr,s_waits2,s_status2);}
2444: PetscFree(s_status1);
2445: PetscFree(s_status2);
2446: PetscFree(s_waits1);
2447: PetscFree(s_waits2);
2449: /* Now allocate buffers for a->j, and send them off */
2450: PetscMalloc((nrqr+1)*sizeof(int*),&sbuf_aj);
2451: for (i=0,j=0; i<nrqr; i++) j += req_size[i];
2452: PetscMalloc((j+1)*sizeof(int),&sbuf_aj[0]);
2453: for (i=1; i<nrqr; i++) sbuf_aj[i] = sbuf_aj[i-1] + req_size[i-1];
2454:
2455: PetscMalloc((nrqr+1)*sizeof(MPI_Request),&s_waits3);
2456: {
2457: BSsprow *brow;
2458: int *Acol;
2459: int rstart = C->rmap.rstart;
2461: for (i=0; i<nrqr; i++) {
2462: rbuf1_i = rbuf1[i];
2463: sbuf_aj_i = sbuf_aj[i];
2464: ct1 = 2*rbuf1_i[0] + 1;
2465: ct2 = 0;
2466: for (j=1,max1=rbuf1_i[0]; j<=max1; j++) {
2467: kmax = rbuf1[i][2*j];
2468: for (k=0; k<kmax; k++,ct1++) {
2469: brow = A->rows[rbuf1_i[ct1] - rstart];
2470: ncols = brow->length;
2471: Acol = brow->col;
2472: /* load the column indices for this row into cols*/
2473: cols = sbuf_aj_i + ct2;
2474: PetscMemcpy(cols,Acol,ncols*sizeof(int));
2475: /*for (l=0; l<ncols;l++) cols[l]=Acol[l]; */ /* How is it with
2476: mappings?? */
2477: ct2 += ncols;
2478: }
2479: }
2480: MPI_Isend(sbuf_aj_i,req_size[i],MPI_INT,req_source[i],tag2,comm,s_waits3+i);
2481: }
2482: }
2483: PetscMalloc((nrqs+1)*sizeof(MPI_Status),&r_status3);
2484: PetscMalloc((nrqr+1)*sizeof(MPI_Status),&s_status3);
2486: /* Allocate buffers for a->a, and send them off */
2487: PetscMalloc((nrqr+1)*sizeof(FLOAT*),&sbuf_aa);
2488: for (i=0,j=0; i<nrqr; i++) j += req_size[i];
2489: PetscMalloc((j+1)*sizeof(FLOAT),&sbuf_aa[0]);
2490: for (i=1; i<nrqr; i++) sbuf_aa[i] = sbuf_aa[i-1] + req_size[i-1];
2491:
2492: PetscMalloc((nrqr+1)*sizeof(MPI_Request),&s_waits4);
2493: {
2494: BSsprow *brow;
2495: FLOAT *Aval;
2496: int rstart = C->rmap.rstart;
2497:
2498: for (i=0; i<nrqr; i++) {
2499: rbuf1_i = rbuf1[i];
2500: sbuf_aa_i = sbuf_aa[i];
2501: ct1 = 2*rbuf1_i[0]+1;
2502: ct2 = 0;
2503: for (j=1,max1=rbuf1_i[0]; j<=max1; j++) {
2504: kmax = rbuf1_i[2*j];
2505: for (k=0; k<kmax; k++,ct1++) {
2506: brow = A->rows[rbuf1_i[ct1] - rstart];
2507: ncols = brow->length;
2508: Aval = brow->nz;
2509: /* load the column values for this row into vals*/
2510: vals = sbuf_aa_i+ct2;
2511: PetscMemcpy(vals,Aval,ncols*sizeof(FLOAT));
2512: ct2 += ncols;
2513: }
2514: }
2515: MPI_Isend(sbuf_aa_i,req_size[i],MPIU_SCALAR,req_source[i],tag3,comm,s_waits4+i);
2516: }
2517: }
2518: PetscMalloc((nrqs+1)*sizeof(MPI_Status),&r_status4);
2519: PetscMalloc((nrqr+1)*sizeof(MPI_Status),&s_status4);
2520: PetscFree(rbuf1);
2522: /* Form the matrix */
2523: /* create col map */
2524: {
2525: int *icol_i;
2526:
2527: len = (1+ismax)*sizeof(int*)+ ismax*C->cmap.N*sizeof(int);
2528: PetscMalloc(len,&cmap);
2529: cmap[0] = (int*)(cmap + ismax);
2530: PetscMemzero(cmap[0],(1+ismax*C->cmap.N)*sizeof(int));
2531: for (i=1; i<ismax; i++) { cmap[i] = cmap[i-1] + C->cmap.N; }
2532: for (i=0; i<ismax; i++) {
2533: jmax = ncol[i];
2534: icol_i = icol[i];
2535: cmap_i = cmap[i];
2536: for (j=0; j<jmax; j++) {
2537: cmap_i[icol_i[j]] = j+1;
2538: }
2539: }
2540: }
2542: /* Create lens which is required for MatCreate... */
2543: for (i=0,j=0; i<ismax; i++) { j += nrow[i]; }
2544: len = (1+ismax)*sizeof(int*)+ j*sizeof(int);
2545: PetscMalloc(len,&lens);
2546: lens[0] = (int*)(lens + ismax);
2547: PetscMemzero(lens[0],j*sizeof(int));
2548: for (i=1; i<ismax; i++) { lens[i] = lens[i-1] + nrow[i-1]; }
2549:
2550: /* Update lens from local data */
2551: { BSsprow *Arow;
2552: for (i=0; i<ismax; i++) {
2553: jmax = nrow[i];
2554: cmap_i = cmap[i];
2555: irow_i = irow[i];
2556: lens_i = lens[i];
2557: for (j=0; j<jmax; j++) {
2558: row = irow_i[j];
2559: proc = rtable[row];
2560: if (proc == rank) {
2561: Arow=A->rows[row-C->rmap.rstart];
2562: ncols=Arow->length;
2563: cols=Arow->col;
2564: for (k=0; k<ncols; k++) {
2565: if (cmap_i[cols[k]]) { lens_i[j]++;}
2566: }
2567: }
2568: }
2569: }
2570: }
2571:
2572: /* Create row map*/
2573: len = (1+ismax)*sizeof(int*)+ ismax*C->rmap.N*sizeof(int);
2574: PetscMalloc(len,&rmap);
2575: rmap[0] = (int*)(rmap + ismax);
2576: PetscMemzero(rmap[0],ismax*C->rmap.N*sizeof(int));
2577: for (i=1; i<ismax; i++) { rmap[i] = rmap[i-1] + C->rmap.N;}
2578: for (i=0; i<ismax; i++) {
2579: rmap_i = rmap[i];
2580: irow_i = irow[i];
2581: jmax = nrow[i];
2582: for (j=0; j<jmax; j++) {
2583: rmap_i[irow_i[j]] = j;
2584: }
2585: }
2586:
2587: /* Update lens from offproc data */
2588: {
2589: int *rbuf2_i,*rbuf3_i,*sbuf1_i;
2591: for (tmp2=0; tmp2<nrqs; tmp2++) {
2592: MPI_Waitany(nrqs,r_waits3,&i,r_status3+tmp2);
2593: idx = pa[i];
2594: sbuf1_i = sbuf1[idx];
2595: jmax = sbuf1_i[0];
2596: ct1 = 2*jmax+1;
2597: ct2 = 0;
2598: rbuf2_i = rbuf2[i];
2599: rbuf3_i = rbuf3[i];
2600: for (j=1; j<=jmax; j++) {
2601: is_no = sbuf1_i[2*j-1];
2602: max1 = sbuf1_i[2*j];
2603: lens_i = lens[is_no];
2604: cmap_i = cmap[is_no];
2605: rmap_i = rmap[is_no];
2606: for (k=0; k<max1; k++,ct1++) {
2607: row = rmap_i[sbuf1_i[ct1]]; /* the val in the new matrix to be */
2608: max2 = rbuf2_i[ct1];
2609: for (l=0; l<max2; l++,ct2++) {
2610: if (cmap_i[rbuf3_i[ct2]]) {
2611: lens_i[row]++;
2612: }
2613: }
2614: }
2615: }
2616: }
2617: }
2618: PetscFree(r_status3);
2619: PetscFree(r_waits3);
2620: if (nrqr) {MPI_Waitall(nrqr,s_waits3,s_status3);}
2621: PetscFree(s_status3);
2622: PetscFree(s_waits3);
2624: /* Create the submatrices */
2625: if (scall == MAT_REUSE_MATRIX) {
2626: PetscTruth same;
2627:
2628: /*
2629: Assumes new rows are same length as the old rows,hence bug!
2630: */
2631: for (i=0; i<ismax; i++) {
2632: PetscTypeCompare((PetscObject)(submats[i]),MATSEQAIJ,&same);
2633: if (!same) {
2634: SETERRQ(PETSC_ERR_ARG_SIZ,"Cannot reuse matrix. wrong type");
2635: }
2636: mat = (Mat_SeqAIJ*)(submats[i]->data);
2637: if ((submats[i]->rmap.n != nrow[i]) || (submats[i]->cmap.n != ncol[i])) {
2638: SETERRQ(PETSC_ERR_ARG_SIZ,"Cannot reuse matrix. wrong size");
2639: }
2640: PetscMemcmp(mat->ilen,lens[i],submats[i]->rmap.n*sizeof(int),&same);
2641: if (!same) {
2642: SETERRQ(PETSC_ERR_ARG_SIZ,"Cannot reuse matrix. wrong no of nonzeros");
2643: }
2644: /* Initial matrix as if empty */
2645: PetscMemzero(mat->ilen,submats[i]->rmap.n*sizeof(int));
2646: submats[i]->factor = C->factor;
2647: }
2648: } else {
2649: for (i=0; i<ismax; i++) {
2650: /* Here we want to explicitly generate SeqAIJ matrices */
2651: MatCreate(PETSC_COMM_SELF,submats+i);
2652: MatSetSizes(submats[i],nrow[i],ncol[i],nrow[i],ncol[i]);
2653: MatSetType(submats[i],MATSEQAIJ);
2654: MatSeqAIJSetPreallocation(submats[i],0,lens[i]);
2655: }
2656: }
2658: /* Assemble the matrices */
2659: /* First assemble the local rows */
2660: {
2661: int ilen_row,*imat_ilen,*imat_j,*imat_i,old_row;
2662: PetscScalar *imat_a;
2663: BSsprow *Arow;
2664:
2665: for (i=0; i<ismax; i++) {
2666: mat = (Mat_SeqAIJ*)submats[i]->data;
2667: imat_ilen = mat->ilen;
2668: imat_j = mat->j;
2669: imat_i = mat->i;
2670: imat_a = mat->a;
2671: cmap_i = cmap[i];
2672: rmap_i = rmap[i];
2673: irow_i = irow[i];
2674: jmax = nrow[i];
2675: for (j=0; j<jmax; j++) {
2676: row = irow_i[j];
2677: proc = rtable[row];
2678: if (proc == rank) {
2679: old_row = row;
2680: row = rmap_i[row];
2681: ilen_row = imat_ilen[row];
2682:
2683: Arow=A->rows[old_row-C->rmap.rstart];
2684: ncols=Arow->length;
2685: cols=Arow->col;
2686: vals=Arow->nz;
2687:
2688: mat_i = imat_i[row];
2689: mat_a = imat_a + mat_i;
2690: mat_j = imat_j + mat_i;
2691: for (k=0; k<ncols; k++) {
2692: if ((tcol = cmap_i[cols[k]])) {
2693: *mat_j++ = tcol - 1;
2694: *mat_a++ = (PetscScalar)vals[k];
2695: ilen_row++;
2696: }
2697: }
2698: imat_ilen[row] = ilen_row;
2699: }
2700: }
2701: }
2702: }
2704: /* Now assemble the off proc rows*/
2705: {
2706: int *sbuf1_i,*rbuf2_i,*rbuf3_i,*imat_ilen,ilen;
2707: int *imat_j,*imat_i;
2708: PetscScalar *imat_a;
2709: FLOAT *rbuf4_i;
2710:
2711: for (tmp2=0; tmp2<nrqs; tmp2++) {
2712: MPI_Waitany(nrqs,r_waits4,&i,r_status4+tmp2);
2713: idx = pa[i];
2714: sbuf1_i = sbuf1[idx];
2715: jmax = sbuf1_i[0];
2716: ct1 = 2*jmax + 1;
2717: ct2 = 0;
2718: rbuf2_i = rbuf2[i];
2719: rbuf3_i = rbuf3[i];
2720: rbuf4_i = rbuf4[i];
2721: for (j=1; j<=jmax; j++) {
2722: is_no = sbuf1_i[2*j-1];
2723: rmap_i = rmap[is_no];
2724: cmap_i = cmap[is_no];
2725: mat = (Mat_SeqAIJ*)submats[is_no]->data;
2726: imat_ilen = mat->ilen;
2727: imat_j = mat->j;
2728: imat_i = mat->i;
2729: imat_a = mat->a;
2730: max1 = sbuf1_i[2*j];
2731: for (k=0; k<max1; k++,ct1++) {
2732: row = sbuf1_i[ct1];
2733: row = rmap_i[row];
2734: ilen = imat_ilen[row];
2735: mat_i = imat_i[row];
2736: mat_a = imat_a + mat_i;
2737: mat_j = imat_j + mat_i;
2738: max2 = rbuf2_i[ct1];
2739: for (l=0; l<max2; l++,ct2++) {
2740: if ((tcol = cmap_i[rbuf3_i[ct2]])) {
2741: *mat_j++ = tcol - 1;
2742: *mat_a++ = (PetscScalar)rbuf4_i[ct2];
2743: ilen++;
2744: }
2745: }
2746: imat_ilen[row] = ilen;
2747: }
2748: }
2749: }
2750: }
2751: PetscFree(r_status4);
2752: PetscFree(r_waits4);
2753: if (nrqr) {MPI_Waitall(nrqr,s_waits4,s_status4);}
2754: PetscFree(s_waits4);
2755: PetscFree(s_status4);
2757: /* Restore the indices */
2758: for (i=0; i<ismax; i++) {
2759: ISRestoreIndices(isrow[i],irow+i);
2760: ISRestoreIndices(iscol[i],icol+i);
2761: }
2763: /* Destroy allocated memory */
2764: PetscFree(irow);
2765: PetscFree(w1);
2766: PetscFree(pa);
2768: PetscFree(sbuf1);
2769: PetscFree(rbuf2);
2770: for (i=0; i<nrqr; ++i) {
2771: PetscFree(sbuf2[i]);
2772: }
2773: for (i=0; i<nrqs; ++i) {
2774: PetscFree(rbuf3[i]);
2775: PetscFree(rbuf4[i]);
2776: }
2778: PetscFree(sbuf2);
2779: PetscFree(rbuf3);
2780: PetscFree(rbuf4);
2781: PetscFree(sbuf_aj[0]);
2782: PetscFree(sbuf_aj);
2783: PetscFree(sbuf_aa[0]);
2784: PetscFree(sbuf_aa);
2785:
2786: PetscFree(cmap);
2787: PetscFree(rmap);
2788: PetscFree(lens);
2790: for (i=0; i<ismax; i++) {
2791: MatAssemblyBegin(submats[i],MAT_FINAL_ASSEMBLY);
2792: MatAssemblyEnd(submats[i],MAT_FINAL_ASSEMBLY);
2793: }
2794: return(0);
2795: }
2797: /*
2798: can be optimized by send only non-zeroes in iscol IS -
2799: so prebuild submatrix on sending side including A,B partitioning
2800: */
2803: #include src/vec/is/impls/general/general.h
2804: PetscErrorCode MatGetSubMatrix_MPIRowbs(Mat C,IS isrow,IS iscol,int csize,MatReuse scall,Mat *submat)
2805: {
2806: Mat_MPIRowbs *c = (Mat_MPIRowbs*)C->data;
2807: BSspmat *A = c->A;
2808: BSsprow *Arow;
2809: Mat_SeqAIJ *matA,*matB; /* on prac , off proc part of submat */
2810: Mat_MPIAIJ *mat; /* submat->data */
2812: int *irow,*icol,nrow,ncol,*rtable,size,rank,tag0,tag1,tag2,tag3;
2813: int *w1,*w2,*pa,nrqs,nrqr,msz,row_t;
2814: int i,j,k,l,len,jmax,proc,idx;
2815: int **sbuf1,**sbuf2,**rbuf1,**rbuf2,*req_size,**sbuf3,**rbuf3;
2816: FLOAT **rbuf4,**sbuf4; /* FLOAT is from Block Solve 95 library */
2818: int *cmap,*rmap,nlocal,*o_nz,*d_nz,cstart,cend;
2819: int *req_source;
2820: int ncols_t;
2821:
2822:
2823: MPI_Request *s_waits1,*r_waits1,*s_waits2,*r_waits2,*r_waits3;
2824: MPI_Request *r_waits4,*s_waits3,*s_waits4;
2825:
2826: MPI_Status *r_status1,*r_status2,*s_status1,*s_status3,*s_status2;
2827: MPI_Status *r_status3,*r_status4,*s_status4;
2828: MPI_Comm comm;
2832: comm = C->comm;
2833: tag0 = C->tag;
2834: size = c->size;
2835: rank = c->rank;
2837: if (size==1) {
2838: if (scall == MAT_REUSE_MATRIX) {
2839: ierr=MatGetSubMatrices(C,1,&isrow,&iscol,MAT_REUSE_MATRIX,&submat);
2840: return(0);
2841: } else {
2842: Mat *newsubmat;
2843:
2844: ierr=MatGetSubMatrices(C,1,&isrow,&iscol,MAT_INITIAL_MATRIX,&newsubmat);
2845: *submat=*newsubmat;
2846: ierr=PetscFree(newsubmat);
2847: return(0);
2848: }
2849: }
2850:
2851: /* Get some new tags to keep the communication clean */
2852: PetscObjectGetNewTag((PetscObject)C,&tag1);
2853: PetscObjectGetNewTag((PetscObject)C,&tag2);
2854: PetscObjectGetNewTag((PetscObject)C,&tag3);
2856: /* Check if the col indices are sorted */
2857: {PetscTruth sorted;
2858: ISSorted(isrow,&sorted);
2859: if (!sorted) SETERRQ(PETSC_ERR_ARG_WRONGSTATE,"ISrow is not sorted");
2860: ISSorted(iscol,&sorted);
2861: if (!sorted) SETERRQ(PETSC_ERR_ARG_WRONGSTATE,"IScol is not sorted");
2862: }
2863:
2864: ISGetIndices(isrow,&irow);
2865: ISGetIndices(iscol,&icol);
2866: ISGetLocalSize(isrow,&nrow);
2867: ISGetLocalSize(iscol,&ncol);
2868:
2869: if (!isrow) SETERRQ(PETSC_ERR_ARG_SIZ,"Empty ISrow");
2870: if (!iscol) SETERRQ(PETSC_ERR_ARG_SIZ,"Empty IScol");
2871:
2872:
2873: len = (C->rmap.N+1)*sizeof(int);
2874: PetscMalloc(len,&rtable);
2875: /* Create hash table for the mapping :row -> proc*/
2876: for (i=0,j=0; i<size; i++) {
2877: jmax = C->rmap.range[i+1];
2878: for (; j<jmax; j++) {
2879: rtable[j] = i;
2880: }
2881: }
2883: /* evaluate communication - mesg to who, length of mesg, and buffer space
2884: required. Based on this, buffers are allocated, and data copied into them*/
2885: PetscMalloc(size*2*sizeof(int),&w1); /* mesg size */
2886: w2 = w1 + size; /* if w2[i] marked, then a message to proc i*/
2887: PetscMemzero(w1,size*2*sizeof(int)); /* initialize work vector*/
2888: for (j=0; j<nrow; j++) {
2889: row_t = irow[j];
2890: proc = rtable[row_t];
2891: w1[proc]++;
2892: }
2893: nrqs = 0; /* no of outgoing messages */
2894: msz = 0; /* total mesg length (for all procs) */
2895: w1[rank] = 0; /* no mesg sent to self */
2896: for (i=0; i<size; i++) {
2897: if (w1[i]) { w2[i] = 1; nrqs++;} /* there exists a message to proc i */
2898: }
2899:
2900: PetscMalloc((nrqs+1)*sizeof(int),&pa); /*(proc -array)*/
2901: for (i=0,j=0; i<size; i++) {
2902: if (w1[i]) {
2903: pa[j++] = i;
2904: w1[i]++; /* header for return data */
2905: msz+=w1[i];
2906: }
2907: }
2908:
2909: {int *onodes1,*olengths1;
2910: /* Determine the number of messages to expect, their lengths, from from-ids */
2911: PetscGatherNumberOfMessages(comm,w2,w1,&nrqr);
2912: PetscGatherMessageLengths(comm,nrqs,nrqr,w1,&onodes1,&olengths1);
2913: /* Now post the Irecvs corresponding to these messages */
2914: PetscPostIrecvInt(comm,tag0,nrqr,onodes1,olengths1,&rbuf1,&r_waits1);
2915: PetscFree(onodes1);
2916: PetscFree(olengths1);
2917: }
2918:
2919: { int **ptr,*iptr,*tmp;
2920: /* Allocate Memory for outgoing messages */
2921: len = 2*size*sizeof(int*) + msz*sizeof(int);
2922: PetscMalloc(len,&sbuf1);
2923: ptr = sbuf1 + size; /* Pointers to the data in outgoing buffers */
2924: PetscMemzero(sbuf1,2*size*sizeof(int*));
2925: /* allocate memory for outgoing data + buf to receive the first reply */
2926: tmp = (int*)(ptr + size);
2928: for (i=0,iptr=tmp; i<nrqs; i++) {
2929: j = pa[i];
2930: sbuf1[j] = iptr;
2931: iptr += w1[j];
2932: }
2934: /* Form the outgoing messages */
2935: for (i=0; i<nrqs; i++) {
2936: j = pa[i];
2937: sbuf1[j][0] = 0; /*header */
2938: ptr[j] = sbuf1[j] + 1;
2939: }
2940:
2941: /* Parse the isrow and copy data into outbuf */
2942: for (j=0; j<nrow; j++) {
2943: row_t = irow[j];
2944: proc = rtable[row_t];
2945: if (proc != rank) { /* copy to the outgoing buf*/
2946: sbuf1[proc][0]++;
2947: *ptr[proc] = row_t;
2948: ptr[proc]++;
2949: }
2950: }
2951: } /* block */
2953: /* Now post the sends */
2954:
2955: /* structure of sbuf1[i]/rbuf1[i] : 1 (num of rows) + nrow-local rows (nuberes
2956: * of requested rows)*/
2958: PetscMalloc((nrqs+1)*sizeof(MPI_Request),&s_waits1);
2959: for (i=0; i<nrqs; ++i) {
2960: j = pa[i];
2961: MPI_Isend(sbuf1[j],w1[j],MPI_INT,j,tag0,comm,s_waits1+i);
2962: }
2964: /* Post Receives to capture the buffer size */
2965: PetscMalloc((nrqs+1)*sizeof(MPI_Request),&r_waits2);
2966: PetscMalloc((nrqs+1)*sizeof(int*),&rbuf2);
2967: PetscMalloc(msz*sizeof(int)+1,&(rbuf2[0]));
2968: for (i=1; i<nrqs; ++i) {
2969: rbuf2[i] = rbuf2[i-1]+w1[pa[i-1]];
2970: }
2971: for (i=0; i<nrqs; ++i) {
2972: j = pa[i];
2973: MPI_Irecv(rbuf2[i],w1[j],MPI_INT,j,tag1,comm,r_waits2+i);
2974: }
2976: /* Send to other procs the buf size they should allocate */
2977: /* structure of sbuf2[i]/rbuf2[i]: 1 (total size to allocate) + nrow-locrow
2978: * (row sizes) */
2980: /* Receive messages*/
2981: PetscMalloc((nrqr+1)*sizeof(MPI_Request),&s_waits2);
2982: PetscMalloc((nrqr+1)*sizeof(MPI_Status),&r_status1);
2983: len = 2*nrqr*sizeof(int) + (nrqr+1)*sizeof(int*);
2984: PetscMalloc(len,&sbuf2);
2985: req_size = (int*)(sbuf2 + nrqr);
2986: req_source = req_size + nrqr;
2987:
2988: {
2989: BSsprow **sAi = A->rows;
2990: int id,rstart = C->rmap.rstart;
2991: int *sbuf2_i,*rbuf1_i,end;
2993: for (i=0; i<nrqr; ++i) {
2994: MPI_Waitany(nrqr,r_waits1,&idx,r_status1+i);
2995: req_size[idx] = 0;
2996: rbuf1_i = rbuf1[idx];
2997: MPI_Get_count(r_status1+i,MPI_INT,&end);
2998: PetscMalloc((end+1)*sizeof(int),&sbuf2[idx]);
2999: sbuf2_i = sbuf2[idx];
3000: for (j=1; j<end; j++) {
3001: id = rbuf1_i[j] - rstart;
3002: ncols_t = (sAi[id])->length;
3003: sbuf2_i[j] = ncols_t;
3004: req_size[idx] += ncols_t;
3005: }
3006: req_source[idx] = r_status1[i].MPI_SOURCE;
3007: /* form the header */
3008: sbuf2_i[0] = req_size[idx];
3009: MPI_Isend(sbuf2_i,end,MPI_INT,req_source[idx],tag1,comm,s_waits2+i);
3010: }
3011: }
3012: PetscFree(r_status1);
3013: PetscFree(r_waits1);
3015: /* recv buffer sizes */
3016: /* Receive messages*/
3017:
3018: PetscMalloc((nrqs+1)*sizeof(int*),&rbuf3);
3019: PetscMalloc((nrqs+1)*sizeof(FLOAT*),&rbuf4);
3020: PetscMalloc((nrqs+1)*sizeof(MPI_Request),&r_waits3);
3021: PetscMalloc((nrqs+1)*sizeof(MPI_Request),&r_waits4);
3022: PetscMalloc((nrqs+1)*sizeof(MPI_Status),&r_status2);
3024: for (i=0; i<nrqs; ++i) {
3025: MPI_Waitany(nrqs,r_waits2,&idx,r_status2+i);
3026: PetscMalloc((rbuf2[idx][0]+1)*sizeof(int),&rbuf3[idx]);
3027: PetscMalloc((rbuf2[idx][0]+1)*sizeof(FLOAT),&rbuf4[idx]);
3028: MPI_Irecv(rbuf3[idx],rbuf2[idx][0],MPI_INT,r_status2[i].MPI_SOURCE,tag2,comm,r_waits3+idx);
3029: MPI_Irecv(rbuf4[idx],rbuf2[idx][0],MPIU_SCALAR,r_status2[i].MPI_SOURCE,tag3,comm,r_waits4+idx);
3030: }
3031: PetscFree(r_status2);
3032: PetscFree(r_waits2);
3033:
3034: /* Wait on sends1 and sends2 */
3035: PetscMalloc((nrqs+1)*sizeof(MPI_Status),&s_status1);
3036: PetscMalloc((nrqr+1)*sizeof(MPI_Status),&s_status2);
3038: if (nrqs) {MPI_Waitall(nrqs,s_waits1,s_status1);}
3039: if (nrqr) {MPI_Waitall(nrqr,s_waits2,s_status2);}
3040: PetscFree(s_status1);
3041: PetscFree(s_status2);
3042: PetscFree(s_waits1);
3043: PetscFree(s_waits2);
3045: /* Now allocate buffers for a->j, and send them off */
3046: /* structure of sbuf3[i]/rbuf3[i],sbuf4[i]/rbuf4[i]: reqsize[i] (cols resp.
3047: * vals of all req. rows; row sizes was in rbuf2; vals are of FLOAT type */
3048:
3049: PetscMalloc((nrqr+1)*sizeof(int*),&sbuf3);
3050: for (i=0,j=0; i<nrqr; i++) j += req_size[i];
3051: PetscMalloc((j+1)*sizeof(int),&sbuf3[0]);
3052: for (i=1; i<nrqr; i++) sbuf3[i] = sbuf3[i-1] + req_size[i-1];
3053:
3054: PetscMalloc((nrqr+1)*sizeof(MPI_Request),&s_waits3);
3055: {
3056: int *Acol,*rbuf1_i,*sbuf3_i,rqrow,noutcols,kmax,*cols,ncols;
3057: int rstart = C->rmap.rstart;
3059: for (i=0; i<nrqr; i++) {
3060: rbuf1_i = rbuf1[i];
3061: sbuf3_i = sbuf3[i];
3062: noutcols = 0;
3063: kmax = rbuf1_i[0]; /* num. of req. rows */
3064: for (k=0,rqrow=1; k<kmax; k++,rqrow++) {
3065: Arow = A->rows[rbuf1_i[rqrow] - rstart];
3066: ncols = Arow->length;
3067: Acol = Arow->col;
3068: /* load the column indices for this row into cols*/
3069: cols = sbuf3_i + noutcols;
3070: PetscMemcpy(cols,Acol,ncols*sizeof(int));
3071: /*for (l=0; l<ncols;l++) cols[l]=Acol[l]; */ /* How is it with mappings?? */
3072: noutcols += ncols;
3073: }
3074: MPI_Isend(sbuf3_i,req_size[i],MPI_INT,req_source[i],tag2,comm,s_waits3+i);
3075: }
3076: }
3077: PetscMalloc((nrqs+1)*sizeof(MPI_Status),&r_status3);
3078: PetscMalloc((nrqr+1)*sizeof(MPI_Status),&s_status3);
3080: /* Allocate buffers for a->a, and send them off */
3081: /* can be optimized by conect with previous block */
3082: PetscMalloc((nrqr+1)*sizeof(FLOAT*),&sbuf4);
3083: for (i=0,j=0; i<nrqr; i++) j += req_size[i];
3084: PetscMalloc((j+1)*sizeof(FLOAT),&sbuf4[0]);
3085: for (i=1; i<nrqr; i++) sbuf4[i] = sbuf4[i-1] + req_size[i-1];
3086:
3087: PetscMalloc((nrqr+1)*sizeof(MPI_Request),&s_waits4);
3088: {
3089: FLOAT *Aval,*vals,*sbuf4_i;
3090: int rstart = C->rmap.rstart,*rbuf1_i,rqrow,noutvals,kmax,ncols;
3091:
3092:
3093: for (i=0; i<nrqr; i++) {
3094: rbuf1_i = rbuf1[i];
3095: sbuf4_i = sbuf4[i];
3096: rqrow = 1;
3097: noutvals = 0;
3098: kmax = rbuf1_i[0]; /* num of req. rows */
3099: for (k=0; k<kmax; k++,rqrow++) {
3100: Arow = A->rows[rbuf1_i[rqrow] - rstart];
3101: ncols = Arow->length;
3102: Aval = Arow->nz;
3103: /* load the column values for this row into vals*/
3104: vals = sbuf4_i+noutvals;
3105: PetscMemcpy(vals,Aval,ncols*sizeof(FLOAT));
3106: noutvals += ncols;
3107: }
3108: MPI_Isend(sbuf4_i,req_size[i],MPIU_SCALAR,req_source[i],tag3,comm,s_waits4+i);
3109: }
3110: }
3111: PetscMalloc((nrqs+1)*sizeof(MPI_Status),&r_status4);
3112: PetscMalloc((nrqr+1)*sizeof(MPI_Status),&s_status4);
3113: PetscFree(rbuf1);
3115: /* Form the matrix */
3117: /* create col map */
3118: len = C->cmap.N*sizeof(int)+1;
3119: PetscMalloc(len,&cmap);
3120: PetscMemzero(cmap,C->cmap.N*sizeof(int));
3121: for (j=0; j<ncol; j++) {
3122: cmap[icol[j]] = j+1;
3123: }
3124:
3125: /* Create row map / maybe I will need global rowmap but here is local rowmap*/
3126: len = C->rmap.N*sizeof(int)+1;
3127: PetscMalloc(len,&rmap);
3128: PetscMemzero(rmap,C->rmap.N*sizeof(int));
3129: for (j=0; j<nrow; j++) {
3130: rmap[irow[j]] = j;
3131: }
3133: /*
3134: Determine the number of non-zeros in the diagonal and off-diagonal
3135: portions of the matrix in order to do correct preallocation
3136: */
3138: /* first get start and end of "diagonal" columns */
3139: if (csize == PETSC_DECIDE) {
3140: nlocal = ncol/size + ((ncol % size) > rank);
3141: } else {
3142: nlocal = csize;
3143: }
3144: {
3145: int ncols,*cols,olen,dlen,thecol;
3146: int *rbuf2_i,*rbuf3_i,*sbuf1_i,row,kmax,cidx;
3147:
3148: MPI_Scan(&nlocal,&cend,1,MPI_INT,MPI_SUM,comm);
3149: cstart = cend - nlocal;
3150: if (rank == size - 1 && cend != ncol) {
3151: SETERRQ(PETSC_ERR_ARG_SIZ,"Local column sizes do not add up to total number of columns");
3152: }
3154: PetscMalloc((2*nrow+1)*sizeof(int),&d_nz);
3155: o_nz = d_nz + nrow;
3156:
3157: /* Update lens from local data */
3158: for (j=0; j<nrow; j++) {
3159: row = irow[j];
3160: proc = rtable[row];
3161: if (proc == rank) {
3162: Arow=A->rows[row-C->rmap.rstart];
3163: ncols=Arow->length;
3164: cols=Arow->col;
3165: olen=dlen=0;
3166: for (k=0; k<ncols; k++) {
3167: if ((thecol=cmap[cols[k]])) {
3168: if (cstart<thecol && thecol<=cend) dlen++; /* thecol is from 1 */
3169: else olen++;
3170: }
3171: }
3172: o_nz[j]=olen;
3173: d_nz[j]=dlen;
3174: } else d_nz[j]=o_nz[j]=0;
3175: }
3176: /* Update lens from offproc data and done waits */
3177: /* this will be much simplier after sending only appropriate columns */
3178: for (j=0; j<nrqs;j++) {
3179: MPI_Waitany(nrqs,r_waits3,&i,r_status3+j);
3180: proc = pa[i];
3181: sbuf1_i = sbuf1[proc];
3182: cidx = 0;
3183: rbuf2_i = rbuf2[i];
3184: rbuf3_i = rbuf3[i];
3185: kmax = sbuf1_i[0]; /*num of rq. rows*/
3186: for (k=1; k<=kmax; k++) {
3187: row = rmap[sbuf1_i[k]]; /* the val in the new matrix to be */
3188: for (l=0; l<rbuf2_i[k]; l++,cidx++) {
3189: if ((thecol=cmap[rbuf3_i[cidx]])) {
3190:
3191: if (cstart<thecol && thecol<=cend) d_nz[row]++; /* thecol is from 1 */
3192: else o_nz[row]++;
3193: }
3194: }
3195: }
3196: }
3197: }
3198: PetscFree(r_status3);
3199: PetscFree(r_waits3);
3200: if (nrqr) {MPI_Waitall(nrqr,s_waits3,s_status3);}
3201: PetscFree(s_status3);
3202: PetscFree(s_waits3);
3204: if (scall == MAT_INITIAL_MATRIX) {
3205: MatCreate(comm,submat);
3206: MatSetSizes(*submat,nrow,nlocal,PETSC_DECIDE,ncol);
3207: MatSetType(*submat,C->type_name);
3208: MatMPIAIJSetPreallocation(*submat,0,d_nz,0,o_nz);
3209: mat=(Mat_MPIAIJ *)((*submat)->data);
3210: matA=(Mat_SeqAIJ *)(mat->A->data);
3211: matB=(Mat_SeqAIJ *)(mat->B->data);
3212:
3213: } else {
3214: PetscTruth same;
3215: /* folowing code can be optionaly dropped for debuged versions of users
3216: * program, but I don't know PETSc option which can switch off such safety
3217: * tests - in a same way counting of o_nz,d_nz can be droped for REUSE
3218: * matrix */
3219:
3220: PetscTypeCompare((PetscObject)(*submat),MATMPIAIJ,&same);
3221: if (!same) {
3222: SETERRQ(PETSC_ERR_ARG_SIZ,"Cannot reuse matrix. wrong type");
3223: }
3224: if (((*submat)->rmap.n != nrow) || ((*submat)->cmap.N != ncol)) {
3225: SETERRQ(PETSC_ERR_ARG_SIZ,"Cannot reuse matrix. wrong size");
3226: }
3227: mat=(Mat_MPIAIJ *)((*submat)->data);
3228: matA=(Mat_SeqAIJ *)(mat->A->data);
3229: matB=(Mat_SeqAIJ *)(mat->B->data);
3230: PetscMemcmp(matA->ilen,d_nz,nrow*sizeof(int),&same);
3231: if (!same) {
3232: SETERRQ(PETSC_ERR_ARG_SIZ,"Cannot reuse matrix. wrong no of nonzeros");
3233: }
3234: PetscMemcmp(matB->ilen,o_nz,nrow*sizeof(int),&same);
3235: if (!same) {
3236: SETERRQ(PETSC_ERR_ARG_SIZ,"Cannot reuse matrix. wrong no of nonzeros");
3237: }
3238: /* Initial matrix as if empty */
3239: PetscMemzero(matA->ilen,nrow*sizeof(int));
3240: PetscMemzero(matB->ilen,nrow*sizeof(int));
3241: /* Perhaps MatZeroEnteries may be better - look what it is exactly doing - I must
3242: * delete all possibly nonactual inforamtion */
3243: /*submats[i]->factor = C->factor; !!! ??? if factor will be same then I must
3244: * copy some factor information - where are thay */
3245: (*submat)->was_assembled=PETSC_FALSE;
3246: (*submat)->assembled=PETSC_FALSE;
3247:
3248: }
3249: PetscFree(d_nz);
3251: /* Assemble the matrix */
3252: /* First assemble from local rows */
3253: {
3254: int i_row,oldrow,row,ncols,*cols,*matA_j,*matB_j,ilenA,ilenB,tcol;
3255: FLOAT *vals;
3256: PetscScalar *matA_a,*matB_a;
3257:
3258: for (j=0; j<nrow; j++) {
3259: oldrow = irow[j];
3260: proc = rtable[oldrow];
3261: if (proc == rank) {
3262: row = rmap[oldrow];
3263:
3264: Arow = A->rows[oldrow-C->rmap.rstart];
3265: ncols = Arow->length;
3266: cols = Arow->col;
3267: vals = Arow->nz;
3268:
3269: i_row = matA->i[row];
3270: matA_a = matA->a + i_row;
3271: matA_j = matA->j + i_row;
3272: i_row = matB->i[row];
3273: matB_a = matB->a + i_row;
3274: matB_j = matB->j + i_row;
3275: for (k=0,ilenA=0,ilenB=0; k<ncols; k++) {
3276: if ((tcol = cmap[cols[k]])) {
3277: if (tcol<=cstart) {
3278: *matB_j++ = tcol-1;
3279: *matB_a++ = vals[k];
3280: ilenB++;
3281: } else if (tcol<=cend) {
3282: *matA_j++ = (tcol-1)-cstart;
3283: *matA_a++ = (PetscScalar)(vals[k]);
3284: ilenA++;
3285: } else {
3286: *matB_j++ = tcol-1;
3287: *matB_a++ = vals[k];
3288: ilenB++;
3289: }
3290: }
3291: }
3292: matA->ilen[row]=ilenA;
3293: matB->ilen[row]=ilenB;
3294:
3295: }
3296: }
3297: }
3299: /* Now assemble the off proc rows*/
3300: {
3301: int *sbuf1_i,*rbuf2_i,*rbuf3_i,cidx,kmax,row,i_row;
3302: int *matA_j,*matB_j,lmax,tcol,ilenA,ilenB;
3303: PetscScalar *matA_a,*matB_a;
3304: FLOAT *rbuf4_i;
3306: for (j=0; j<nrqs; j++) {
3307: MPI_Waitany(nrqs,r_waits4,&i,r_status4+j);
3308: proc = pa[i];
3309: sbuf1_i = sbuf1[proc];
3310:
3311: cidx = 0;
3312: rbuf2_i = rbuf2[i];
3313: rbuf3_i = rbuf3[i];
3314: rbuf4_i = rbuf4[i];
3315: kmax = sbuf1_i[0];
3316: for (k=1; k<=kmax; k++) {
3317: row = rmap[sbuf1_i[k]];
3318:
3319: i_row = matA->i[row];
3320: matA_a = matA->a + i_row;
3321: matA_j = matA->j + i_row;
3322: i_row = matB->i[row];
3323: matB_a = matB->a + i_row;
3324: matB_j = matB->j + i_row;
3325:
3326: lmax = rbuf2_i[k];
3327: for (l=0,ilenA=0,ilenB=0; l<lmax; l++,cidx++) {
3328: if ((tcol = cmap[rbuf3_i[cidx]])) {
3329: if (tcol<=cstart) {
3330: *matB_j++ = tcol-1;
3331: *matB_a++ = (PetscScalar)(rbuf4_i[cidx]);;
3332: ilenB++;
3333: } else if (tcol<=cend) {
3334: *matA_j++ = (tcol-1)-cstart;
3335: *matA_a++ = (PetscScalar)(rbuf4_i[cidx]);
3336: ilenA++;
3337: } else {
3338: *matB_j++ = tcol-1;
3339: *matB_a++ = (PetscScalar)(rbuf4_i[cidx]);
3340: ilenB++;
3341: }
3342: }
3343: }
3344: matA->ilen[row]=ilenA;
3345: matB->ilen[row]=ilenB;
3346: }
3347: }
3348: }
3350: PetscFree(r_status4);
3351: PetscFree(r_waits4);
3352: if (nrqr) {MPI_Waitall(nrqr,s_waits4,s_status4);}
3353: PetscFree(s_waits4);
3354: PetscFree(s_status4);
3356: /* Restore the indices */
3357: ISRestoreIndices(isrow,&irow);
3358: ISRestoreIndices(iscol,&icol);
3360: /* Destroy allocated memory */
3361: PetscFree(rtable);
3362: PetscFree(w1);
3363: PetscFree(pa);
3365: PetscFree(sbuf1);
3366: PetscFree(rbuf2[0]);
3367: PetscFree(rbuf2);
3368: for (i=0; i<nrqr; ++i) {
3369: PetscFree(sbuf2[i]);
3370: }
3371: for (i=0; i<nrqs; ++i) {
3372: PetscFree(rbuf3[i]);
3373: PetscFree(rbuf4[i]);
3374: }
3376: PetscFree(sbuf2);
3377: PetscFree(rbuf3);
3378: PetscFree(rbuf4);
3379: PetscFree(sbuf3[0]);
3380: PetscFree(sbuf3);
3381: PetscFree(sbuf4[0]);
3382: PetscFree(sbuf4);
3383:
3384: PetscFree(cmap);
3385: PetscFree(rmap);
3388: MatAssemblyBegin(*submat,MAT_FINAL_ASSEMBLY);
3389: MatAssemblyEnd(*submat,MAT_FINAL_ASSEMBLY);
3392: return(0);
3393: }