Actual source code: mpibdiag.c
1: #define PETSCMAT_DLL
3: /*
4: The basic matrix operations for the Block diagonal parallel
5: matrices.
6: */
7: #include src/mat/impls/bdiag/mpi/mpibdiag.h
11: PetscErrorCode MatSetValues_MPIBDiag(Mat mat,PetscInt m,const PetscInt idxm[],PetscInt n,const PetscInt idxn[],const PetscScalar v[],InsertMode addv)
12: {
13: Mat_MPIBDiag *mbd = (Mat_MPIBDiag*)mat->data;
15: PetscInt i,j,row,rstart = mat->rmap.rstart,rend = mat->rmap.rend;
16: PetscTruth roworiented = mbd->roworiented;
19: for (i=0; i<m; i++) {
20: if (idxm[i] < 0) continue;
21: if (idxm[i] >= mat->rmap.N) SETERRQ(PETSC_ERR_ARG_OUTOFRANGE,"Row too large");
22: if (idxm[i] >= rstart && idxm[i] < rend) {
23: row = idxm[i] - rstart;
24: for (j=0; j<n; j++) {
25: if (idxn[j] < 0) continue;
26: if (idxn[j] >= mat->cmap.N) SETERRQ(PETSC_ERR_ARG_OUTOFRANGE,"Column too large");
27: if (roworiented) {
28: MatSetValues(mbd->A,1,&row,1,&idxn[j],v+i*n+j,addv);
29: } else {
30: MatSetValues(mbd->A,1,&row,1,&idxn[j],v+i+j*m,addv);
31: }
32: }
33: } else {
34: if (!mbd->donotstash) {
35: if (roworiented) {
36: MatStashValuesRow_Private(&mat->stash,idxm[i],n,idxn,v+i*n);
37: } else {
38: MatStashValuesCol_Private(&mat->stash,idxm[i],n,idxn,v+i,m);
39: }
40: }
41: }
42: }
43: return(0);
44: }
48: PetscErrorCode MatGetValues_MPIBDiag(Mat mat,PetscInt m,const PetscInt idxm[],PetscInt n,const PetscInt idxn[],PetscScalar v[])
49: {
50: Mat_MPIBDiag *mbd = (Mat_MPIBDiag*)mat->data;
52: PetscInt i,j,row,rstart = mat->rmap.rstart,rend = mat->rmap.rend;
55: for (i=0; i<m; i++) {
56: if (idxm[i] < 0) SETERRQ(PETSC_ERR_ARG_OUTOFRANGE,"Negative row");
57: if (idxm[i] >= mat->rmap.N) SETERRQ(PETSC_ERR_ARG_OUTOFRANGE,"Row too large");
58: if (idxm[i] >= rstart && idxm[i] < rend) {
59: row = idxm[i] - rstart;
60: for (j=0; j<n; j++) {
61: if (idxn[j] < 0) SETERRQ(PETSC_ERR_ARG_OUTOFRANGE,"Negative column");
62: if (idxn[j] >= mat->cmap.N) SETERRQ(PETSC_ERR_ARG_OUTOFRANGE,"Column too large");
63: MatGetValues(mbd->A,1,&row,1,&idxn[j],v+i*n+j);
64: }
65: } else {
66: SETERRQ(PETSC_ERR_SUP,"Only local values currently supported");
67: }
68: }
69: return(0);
70: }
74: PetscErrorCode MatAssemblyBegin_MPIBDiag(Mat mat,MatAssemblyType mode)
75: {
76: MPI_Comm comm = mat->comm;
78: PetscInt nstash,reallocs;
79: InsertMode addv;
82: MPI_Allreduce(&mat->insertmode,&addv,1,MPI_INT,MPI_BOR,comm);
83: if (addv == (ADD_VALUES|INSERT_VALUES)) {
84: SETERRQ(PETSC_ERR_ARG_WRONGSTATE,"Cannot mix adds/inserts on different procs");
85: }
86: mat->insertmode = addv; /* in case this processor had no cache */
87: MatStashScatterBegin_Private(&mat->stash,mat->rmap.range);
88: MatStashGetInfo_Private(&mat->stash,&nstash,&reallocs);
89: PetscInfo2(0,"Stash has %D entries,uses %D mallocs.\n",nstash,reallocs);
90: return(0);
91: }
95: PetscErrorCode MatAssemblyEnd_MPIBDiag(Mat mat,MatAssemblyType mode)
96: {
97: Mat_MPIBDiag *mbd = (Mat_MPIBDiag*)mat->data;
98: Mat_SeqBDiag *mlocal;
100: PetscMPIInt n;
101: PetscInt i,*row,*col;
102: PetscInt *tmp1,*tmp2,len,ict,Mblock,Nblock,flg,j,rstart,ncols;
103: PetscScalar *val;
104: InsertMode addv = mat->insertmode;
108: while (1) {
109: MatStashScatterGetMesg_Private(&mat->stash,&n,&row,&col,&val,&flg);
110: if (!flg) break;
111:
112: for (i=0; i<n;) {
113: /* Now identify the consecutive vals belonging to the same row */
114: for (j=i,rstart=row[j]; j<n; j++) { if (row[j] != rstart) break; }
115: if (j < n) ncols = j-i;
116: else ncols = n-i;
117: /* Now assemble all these values with a single function call */
118: MatSetValues_MPIBDiag(mat,1,row+i,ncols,col+i,val+i,addv);
119: i = j;
120: }
121: }
122: MatStashScatterEnd_Private(&mat->stash);
124: MatAssemblyBegin(mbd->A,mode);
125: MatAssemblyEnd(mbd->A,mode);
127: /* Fix main diagonal location and determine global diagonals */
128: mlocal = (Mat_SeqBDiag*)mbd->A->data;
129: Mblock = mat->rmap.N/mat->rmap.bs; Nblock = mat->cmap.N/mat->rmap.bs;
130: len = Mblock + Nblock + 1; /* add 1 to prevent 0 malloc */
131: PetscMalloc(2*len*sizeof(PetscInt),&tmp1);
132: tmp2 = tmp1 + len;
133: PetscMemzero(tmp1,2*len*sizeof(PetscInt));
134: mlocal->mainbd = -1;
135: for (i=0; i<mlocal->nd; i++) {
136: if (mlocal->diag[i] + mbd->brstart == 0) mlocal->mainbd = i;
137: tmp1[mlocal->diag[i] + mbd->brstart + Mblock] = 1;
138: }
139: MPI_Allreduce(tmp1,tmp2,len,MPIU_INT,MPI_SUM,mat->comm);
140: ict = 0;
141: for (i=0; i<len; i++) {
142: if (tmp2[i]) {
143: mbd->gdiag[ict] = i - Mblock;
144: ict++;
145: }
146: }
147: mbd->gnd = ict;
148: PetscFree(tmp1);
150: if (!mat->was_assembled && mode == MAT_FINAL_ASSEMBLY) {
151: MatSetUpMultiply_MPIBDiag(mat);
152: }
153: return(0);
154: }
158: PetscErrorCode MatZeroEntries_MPIBDiag(Mat A)
159: {
160: Mat_MPIBDiag *l = (Mat_MPIBDiag*)A->data;
164: MatZeroEntries(l->A);
165: return(0);
166: }
168: /* again this uses the same basic stratagy as in the assembly and
169: scatter create routines, we should try to do it systematically
170: if we can figure out the proper level of generality. */
172: /* the code does not do the diagonal entries correctly unless the
173: matrix is square and the column and row owerships are identical.
174: This is a BUG. The only way to fix it seems to be to access
175: aij->A and aij->B directly and not through the MatZeroRows()
176: routine.
177: */
181: PetscErrorCode MatZeroRows_MPIBDiag(Mat A,PetscInt N,const PetscInt rows[],PetscScalar diag)
182: {
183: Mat_MPIBDiag *l = (Mat_MPIBDiag*)A->data;
185: PetscMPIInt n,imdex,size = l->size,rank = l->rank,tag = A->tag;
186: PetscInt i,*owners = A->rmap.range;
187: PetscInt *nprocs,j,idx,nsends;
188: PetscInt nmax,*svalues,*starts,*owner,nrecvs;
189: PetscInt *rvalues,count,base,slen,*source;
190: PetscInt *lens,*lrows,*values;
191: MPI_Comm comm = A->comm;
192: MPI_Request *send_waits,*recv_waits;
193: MPI_Status recv_status,*send_status;
194: PetscTruth found;
197: /* first count number of contributors to each processor */
198: PetscMalloc(2*size*sizeof(PetscInt),&nprocs);
199: PetscMemzero(nprocs,2*size*sizeof(PetscInt));
200: PetscMalloc((N+1)*sizeof(PetscInt),&owner); /* see note*/
201: for (i=0; i<N; i++) {
202: idx = rows[i];
203: found = PETSC_FALSE;
204: for (j=0; j<size; j++) {
205: if (idx >= owners[j] && idx < owners[j+1]) {
206: nprocs[2*j]++; nprocs[2*j+1] = 1; owner[i] = j; found = PETSC_TRUE; break;
207: }
208: }
209: if (!found) SETERRQ(PETSC_ERR_ARG_OUTOFRANGE,"row out of range");
210: }
211: nsends = 0; for (i=0; i<size; i++) {nsends += nprocs[2*i+1];}
213: /* inform other processors of number of messages and max length*/
214: PetscMaxSum(comm,nprocs,&nmax,&nrecvs);
216: /* post receives: */
217: PetscMalloc((nrecvs+1)*(nmax+1)*sizeof(PetscInt),&rvalues);
218: PetscMalloc((nrecvs+1)*sizeof(MPI_Request),&recv_waits);
219: for (i=0; i<nrecvs; i++) {
220: MPI_Irecv(rvalues+nmax*i,nmax,MPIU_INT,MPI_ANY_SOURCE,tag,comm,recv_waits+i);
221: }
223: /* do sends:
224: 1) starts[i] gives the starting index in svalues for stuff going to
225: the ith processor
226: */
227: PetscMalloc((N+1)*sizeof(PetscInt),&svalues);
228: PetscMalloc((nsends+1)*sizeof(MPI_Request),&send_waits);
229: PetscMalloc((size+1)*sizeof(PetscInt),&starts);
230: starts[0] = 0;
231: for (i=1; i<size; i++) { starts[i] = starts[i-1] + nprocs[2*i-2];}
232: for (i=0; i<N; i++) {
233: svalues[starts[owner[i]]++] = rows[i];
234: }
236: starts[0] = 0;
237: for (i=1; i<size+1; i++) { starts[i] = starts[i-1] + nprocs[2*i-2];}
238: count = 0;
239: for (i=0; i<size; i++) {
240: if (nprocs[2*i+1]) {
241: MPI_Isend(svalues+starts[i],nprocs[2*i],MPIU_INT,i,tag,comm,send_waits+count++);
242: }
243: }
244: PetscFree(starts);
246: base = owners[rank];
248: /* wait on receives */
249: PetscMalloc(2*(nrecvs+1)*sizeof(PetscInt),&lens);
250: source = lens + nrecvs;
251: count = nrecvs;
252: slen = 0;
253: while (count) {
254: MPI_Waitany(nrecvs,recv_waits,&imdex,&recv_status);
255: /* unpack receives into our local space */
256: MPI_Get_count(&recv_status,MPIU_INT,&n);
257: source[imdex] = recv_status.MPI_SOURCE;
258: lens[imdex] = n;
259: slen += n;
260: count--;
261: }
262: PetscFree(recv_waits);
263:
264: /* move the data into the send scatter */
265: PetscMalloc((slen+1)*sizeof(PetscInt),&lrows);
266: count = 0;
267: for (i=0; i<nrecvs; i++) {
268: values = rvalues + i*nmax;
269: for (j=0; j<lens[i]; j++) {
270: lrows[count++] = values[j] - base;
271: }
272: }
273: PetscFree(rvalues);
274: PetscFree(lens);
275: PetscFree(owner);
276: PetscFree(nprocs);
277:
278: /* actually zap the local rows */
279: MatZeroRows(l->A,slen,lrows,diag);
280: PetscFree(lrows);
282: /* wait on sends */
283: if (nsends) {
284: PetscMalloc(nsends*sizeof(MPI_Status),&send_status);
285: MPI_Waitall(nsends,send_waits,send_status);
286: PetscFree(send_status);
287: }
288: PetscFree(send_waits);
289: PetscFree(svalues);
291: return(0);
292: }
296: PetscErrorCode MatMult_MPIBDiag(Mat mat,Vec xx,Vec yy)
297: {
298: Mat_MPIBDiag *mbd = (Mat_MPIBDiag*)mat->data;
302: VecScatterBegin(xx,mbd->lvec,INSERT_VALUES,SCATTER_FORWARD,mbd->Mvctx);
303: VecScatterEnd(xx,mbd->lvec,INSERT_VALUES,SCATTER_FORWARD,mbd->Mvctx);
304: (*mbd->A->ops->mult)(mbd->A,mbd->lvec,yy);
305: return(0);
306: }
310: PetscErrorCode MatMultAdd_MPIBDiag(Mat mat,Vec xx,Vec yy,Vec zz)
311: {
312: Mat_MPIBDiag *mbd = (Mat_MPIBDiag*)mat->data;
316: VecScatterBegin(xx,mbd->lvec,INSERT_VALUES,SCATTER_FORWARD,mbd->Mvctx);
317: VecScatterEnd(xx,mbd->lvec,INSERT_VALUES,SCATTER_FORWARD,mbd->Mvctx);
318: (*mbd->A->ops->multadd)(mbd->A,mbd->lvec,yy,zz);
319: return(0);
320: }
324: PetscErrorCode MatMultTranspose_MPIBDiag(Mat A,Vec xx,Vec yy)
325: {
326: Mat_MPIBDiag *a = (Mat_MPIBDiag*)A->data;
328: PetscScalar zero = 0.0;
331: VecSet(yy,zero);
332: (*a->A->ops->multtranspose)(a->A,xx,a->lvec);
333: VecScatterBegin(a->lvec,yy,ADD_VALUES,SCATTER_REVERSE,a->Mvctx);
334: VecScatterEnd(a->lvec,yy,ADD_VALUES,SCATTER_REVERSE,a->Mvctx);
335: return(0);
336: }
340: PetscErrorCode MatMultTransposeAdd_MPIBDiag(Mat A,Vec xx,Vec yy,Vec zz)
341: {
342: Mat_MPIBDiag *a = (Mat_MPIBDiag*)A->data;
346: VecCopy(yy,zz);
347: (*a->A->ops->multtranspose)(a->A,xx,a->lvec);
348: VecScatterBegin(a->lvec,zz,ADD_VALUES,SCATTER_REVERSE,a->Mvctx);
349: VecScatterEnd(a->lvec,zz,ADD_VALUES,SCATTER_REVERSE,a->Mvctx);
350: return(0);
351: }
355: PetscErrorCode MatGetInfo_MPIBDiag(Mat matin,MatInfoType flag,MatInfo *info)
356: {
357: Mat_MPIBDiag *mat = (Mat_MPIBDiag*)matin->data;
359: PetscReal isend[5],irecv[5];
362: info->block_size = (PetscReal)mat->A->rmap.bs;
363: MatGetInfo(mat->A,MAT_LOCAL,info);
364: isend[0] = info->nz_used; isend[1] = info->nz_allocated; isend[2] = info->nz_unneeded;
365: isend[3] = info->memory; isend[4] = info->mallocs;
366: if (flag == MAT_LOCAL) {
367: info->nz_used = isend[0];
368: info->nz_allocated = isend[1];
369: info->nz_unneeded = isend[2];
370: info->memory = isend[3];
371: info->mallocs = isend[4];
372: } else if (flag == MAT_GLOBAL_MAX) {
373: MPI_Allreduce(isend,irecv,5,MPIU_REAL,MPI_MAX,matin->comm);
374: info->nz_used = irecv[0];
375: info->nz_allocated = irecv[1];
376: info->nz_unneeded = irecv[2];
377: info->memory = irecv[3];
378: info->mallocs = irecv[4];
379: } else if (flag == MAT_GLOBAL_SUM) {
380: MPI_Allreduce(isend,irecv,5,MPIU_REAL,MPI_SUM,matin->comm);
381: info->nz_used = irecv[0];
382: info->nz_allocated = irecv[1];
383: info->nz_unneeded = irecv[2];
384: info->memory = irecv[3];
385: info->mallocs = irecv[4];
386: }
387: info->rows_global = (double)matin->rmap.N;
388: info->columns_global = (double)matin->cmap.N;
389: info->rows_local = (double)matin->rmap.n;
390: info->columns_local = (double)matin->cmap.N;
391: return(0);
392: }
396: PetscErrorCode MatGetDiagonal_MPIBDiag(Mat mat,Vec v)
397: {
399: Mat_MPIBDiag *A = (Mat_MPIBDiag*)mat->data;
402: MatGetDiagonal(A->A,v);
403: return(0);
404: }
408: PetscErrorCode MatDestroy_MPIBDiag(Mat mat)
409: {
410: Mat_MPIBDiag *mbd = (Mat_MPIBDiag*)mat->data;
412: #if defined(PETSC_USE_LOG)
413: Mat_SeqBDiag *ms = (Mat_SeqBDiag*)mbd->A->data;
416: PetscLogObjectState((PetscObject)mat,"Rows=%D, Cols=%D, BSize=%D, NDiag=%D",mat->rmap.N,mat->cmap.N,mat->rmap.bs,ms->nd);
417: #else
419: #endif
420: MatStashDestroy_Private(&mat->stash);
421: PetscFree(mbd->gdiag);
422: MatDestroy(mbd->A);
423: if (mbd->lvec) {VecDestroy(mbd->lvec);}
424: if (mbd->Mvctx) {VecScatterDestroy(mbd->Mvctx);}
425: PetscFree(mbd);
427: PetscObjectChangeTypeName((PetscObject)mat,0);
428: PetscObjectComposeFunction((PetscObject)mat,"MatGetDiagonalBlock_C","",PETSC_NULL);
429: PetscObjectComposeFunction((PetscObject)mat,"MatMPIBDiagSetPreallocation_C","",PETSC_NULL);
430: return(0);
431: }
436: static PetscErrorCode MatView_MPIBDiag_Binary(Mat mat,PetscViewer viewer)
437: {
438: Mat_MPIBDiag *mbd = (Mat_MPIBDiag*)mat->data;
442: if (mbd->size == 1) {
443: MatView(mbd->A,viewer);
444: } else SETERRQ(PETSC_ERR_SUP,"Only uniprocessor output supported");
445: return(0);
446: }
450: static PetscErrorCode MatView_MPIBDiag_ASCIIorDraw(Mat mat,PetscViewer viewer)
451: {
452: Mat_MPIBDiag *mbd = (Mat_MPIBDiag*)mat->data;
453: PetscErrorCode ierr;
454: PetscMPIInt size = mbd->size,rank = mbd->rank;
455: PetscInt i;
456: PetscTruth iascii,isdraw;
457: PetscViewer sviewer;
458: PetscViewerFormat format;
461: PetscTypeCompare((PetscObject)viewer,PETSC_VIEWER_ASCII,&iascii);
462: PetscTypeCompare((PetscObject)viewer,PETSC_VIEWER_DRAW,&isdraw);
463: if (iascii) {
464: PetscViewerGetFormat(viewer,&format);
465: if (format == PETSC_VIEWER_ASCII_INFO || format == PETSC_VIEWER_ASCII_INFO_DETAIL) {
466: PetscInt nline = PetscMin(10,mbd->gnd),k,nk,np;
467: PetscViewerASCIIPrintf(viewer," block size=%D, total number of diagonals=%D\n",mat->rmap.bs,mbd->gnd);
468: nk = (mbd->gnd-1)/nline + 1;
469: for (k=0; k<nk; k++) {
470: PetscViewerASCIIPrintf(viewer," global diag numbers:");
471: np = PetscMin(nline,mbd->gnd - nline*k);
472: for (i=0; i<np; i++) {
473: PetscViewerASCIIPrintf(viewer," %D",mbd->gdiag[i+nline*k]);
474: }
475: PetscViewerASCIIPrintf(viewer,"\n");
476: }
477: if (format == PETSC_VIEWER_ASCII_INFO_DETAIL) {
478: MatInfo info;
479: MPI_Comm_rank(mat->comm,&rank);
480: MatGetInfo(mat,MAT_LOCAL,&info);
481: PetscViewerASCIISynchronizedPrintf(viewer,"[%d] local rows %D nz %D nz alloced %D mem %D \n",rank,mat->rmap.N,
482: (PetscInt)info.nz_used,(PetscInt)info.nz_allocated,(PetscInt)info.memory);
483: PetscViewerFlush(viewer);
484: VecScatterView(mbd->Mvctx,viewer);
485: }
486: return(0);
487: }
488: }
490: if (isdraw) {
491: PetscDraw draw;
492: PetscTruth isnull;
493: PetscViewerDrawGetDraw(viewer,0,&draw);
494: PetscDrawIsNull(draw,&isnull); if (isnull) return(0);
495: }
497: if (size == 1) {
498: MatView(mbd->A,viewer);
499: } else {
500: /* assemble the entire matrix onto first processor. */
501: Mat A;
502: PetscInt M = mat->rmap.N,N = mat->cmap.N,m,row,nz,*cols;
503: PetscScalar *vals;
505: /* Here we are constructing a temporary matrix, so we will explicitly set the type to MPIBDiag */
506: MatCreate(mat->comm,&A);
507: if (!rank) {
508: MatSetSizes(A,M,N,M,N);
509: MatSetType(A,MATMPIBDIAG);
510: MatMPIBDiagSetPreallocation(A,mbd->gnd,mbd->A->rmap.bs,mbd->gdiag,PETSC_NULL);
511: } else {
512: MatSetSizes(A,0,0,M,N);
513: MatSetType(A,MATMPIBDIAG);
514: MatMPIBDiagSetPreallocation(A,0,mbd->A->rmap.bs,PETSC_NULL,PETSC_NULL);
515: }
516: PetscLogObjectParent(mat,A);
518: /* Copy the matrix ... This isn't the most efficient means,
519: but it's quick for now */
520: row = mat->rmap.rstart;
521: m = mbd->A->rmap.N;
522: for (i=0; i<m; i++) {
523: MatGetRow_MPIBDiag(mat,row,&nz,&cols,&vals);
524: MatSetValues(A,1,&row,nz,cols,vals,INSERT_VALUES);
525: MatRestoreRow_MPIBDiag(mat,row,&nz,&cols,&vals);
526: row++;
527: }
528: MatAssemblyBegin(A,MAT_FINAL_ASSEMBLY);
529: MatAssemblyEnd(A,MAT_FINAL_ASSEMBLY);
530: PetscViewerGetSingleton(viewer,&sviewer);
531: if (!rank) {
532: MatView(((Mat_MPIBDiag*)(A->data))->A,sviewer);
533: }
534: PetscViewerRestoreSingleton(viewer,&sviewer);
535: PetscViewerFlush(viewer);
536: MatDestroy(A);
537: }
538: return(0);
539: }
543: PetscErrorCode MatView_MPIBDiag(Mat mat,PetscViewer viewer)
544: {
546: PetscTruth iascii,isdraw,isbinary;
549: PetscTypeCompare((PetscObject)viewer,PETSC_VIEWER_ASCII,&iascii);
550: PetscTypeCompare((PetscObject)viewer,PETSC_VIEWER_DRAW,&isdraw);
551: PetscTypeCompare((PetscObject)viewer,PETSC_VIEWER_BINARY,&isbinary);
552: if (iascii || isdraw) {
553: MatView_MPIBDiag_ASCIIorDraw(mat,viewer);
554: } else if (isbinary) {
555: MatView_MPIBDiag_Binary(mat,viewer);
556: } else {
557: SETERRQ1(PETSC_ERR_SUP,"Viewer type %s not supported by MPIBdiag matrices",((PetscObject)viewer)->type_name);
558: }
559: return(0);
560: }
564: PetscErrorCode MatSetOption_MPIBDiag(Mat A,MatOption op)
565: {
566: Mat_MPIBDiag *mbd = (Mat_MPIBDiag*)A->data;
569: switch (op) {
570: case MAT_NO_NEW_NONZERO_LOCATIONS:
571: case MAT_YES_NEW_NONZERO_LOCATIONS:
572: case MAT_NEW_NONZERO_LOCATION_ERR:
573: case MAT_NEW_NONZERO_ALLOCATION_ERR:
574: case MAT_NO_NEW_DIAGONALS:
575: case MAT_YES_NEW_DIAGONALS:
576: MatSetOption(mbd->A,op);
577: break;
578: case MAT_ROW_ORIENTED:
579: mbd->roworiented = PETSC_TRUE;
580: MatSetOption(mbd->A,op);
581: break;
582: case MAT_COLUMN_ORIENTED:
583: mbd->roworiented = PETSC_FALSE;
584: MatSetOption(mbd->A,op);
585: break;
586: case MAT_IGNORE_OFF_PROC_ENTRIES:
587: mbd->donotstash = PETSC_TRUE;
588: break;
589: case MAT_ROWS_SORTED:
590: case MAT_ROWS_UNSORTED:
591: case MAT_COLUMNS_SORTED:
592: case MAT_COLUMNS_UNSORTED:
593: case MAT_SYMMETRIC:
594: case MAT_STRUCTURALLY_SYMMETRIC:
595: case MAT_NOT_SYMMETRIC:
596: case MAT_NOT_STRUCTURALLY_SYMMETRIC:
597: case MAT_HERMITIAN:
598: case MAT_NOT_HERMITIAN:
599: case MAT_SYMMETRY_ETERNAL:
600: case MAT_NOT_SYMMETRY_ETERNAL:
601: PetscInfo1(A,"Option %s ignored\n",MatOptions[op]);
602: break;
603: default:
604: SETERRQ1(PETSC_ERR_SUP,"unknown option %d",op);
605: }
606: return(0);
607: }
612: PetscErrorCode MatGetRow_MPIBDiag(Mat matin,PetscInt row,PetscInt *nz,PetscInt **idx,PetscScalar **v)
613: {
614: Mat_MPIBDiag *mat = (Mat_MPIBDiag*)matin->data;
616: PetscInt lrow;
619: if (row < matin->rmap.rstart || row >= matin->rmap.rend) SETERRQ(PETSC_ERR_SUP,"only for local rows")
620: lrow = row - matin->rmap.rstart;
621: MatGetRow_SeqBDiag(mat->A,lrow,nz,idx,v);
622: return(0);
623: }
627: PetscErrorCode MatRestoreRow_MPIBDiag(Mat matin,PetscInt row,PetscInt *nz,PetscInt **idx,PetscScalar **v)
628: {
629: Mat_MPIBDiag *mat = (Mat_MPIBDiag*)matin->data;
631: PetscInt lrow;
634: lrow = row - matin->rmap.rstart;
635: MatRestoreRow_SeqBDiag(mat->A,lrow,nz,idx,v);
636: return(0);
637: }
642: PetscErrorCode MatNorm_MPIBDiag(Mat A,NormType type,PetscReal *nrm)
643: {
644: Mat_MPIBDiag *mbd = (Mat_MPIBDiag*)A->data;
645: Mat_SeqBDiag *a = (Mat_SeqBDiag*)mbd->A->data;
646: PetscReal sum = 0.0;
648: PetscInt d,i,nd = a->nd,bs = A->rmap.bs,len;
649: PetscScalar *dv;
652: if (type == NORM_FROBENIUS) {
653: for (d=0; d<nd; d++) {
654: dv = a->diagv[d];
655: len = a->bdlen[d]*bs*bs;
656: for (i=0; i<len; i++) {
657: #if defined(PETSC_USE_COMPLEX)
658: sum += PetscRealPart(PetscConj(dv[i])*dv[i]);
659: #else
660: sum += dv[i]*dv[i];
661: #endif
662: }
663: }
664: MPI_Allreduce(&sum,nrm,1,MPIU_REAL,MPI_SUM,A->comm);
665: *nrm = sqrt(*nrm);
666: PetscLogFlops(2*A->rmap.n*A->rmap.N);
667: } else if (type == NORM_1) { /* max column norm */
668: PetscReal *tmp,*tmp2;
669: PetscInt j;
670: PetscMalloc((mbd->A->cmap.n+1)*sizeof(PetscReal),&tmp);
671: PetscMalloc((mbd->A->cmap.n+1)*sizeof(PetscReal),&tmp2);
672: MatNorm_SeqBDiag_Columns(mbd->A,tmp,mbd->A->cmap.n);
673: *nrm = 0.0;
674: MPI_Allreduce(tmp,tmp2,mbd->A->cmap.n,MPIU_REAL,MPI_SUM,A->comm);
675: for (j=0; j<mbd->A->cmap.n; j++) {
676: if (tmp2[j] > *nrm) *nrm = tmp2[j];
677: }
678: PetscFree(tmp);
679: PetscFree(tmp2);
680: } else if (type == NORM_INFINITY) { /* max row norm */
681: PetscReal normtemp;
682: MatNorm(mbd->A,type,&normtemp);
683: MPI_Allreduce(&normtemp,nrm,1,MPIU_REAL,MPI_MAX,A->comm);
684: }
685: return(0);
686: }
690: PetscErrorCode MatScale_MPIBDiag(Mat A,PetscScalar alpha)
691: {
693: Mat_MPIBDiag *a = (Mat_MPIBDiag*)A->data;
696: MatScale_SeqBDiag(a->A,alpha);
697: return(0);
698: }
702: PetscErrorCode MatSetUpPreallocation_MPIBDiag(Mat A)
703: {
707: MatMPIBDiagSetPreallocation(A,PETSC_DEFAULT,PETSC_DEFAULT,0,0);
708: return(0);
709: }
711: /* -------------------------------------------------------------------*/
713: static struct _MatOps MatOps_Values = {MatSetValues_MPIBDiag,
714: MatGetRow_MPIBDiag,
715: MatRestoreRow_MPIBDiag,
716: MatMult_MPIBDiag,
717: /* 4*/ MatMultAdd_MPIBDiag,
718: MatMultTranspose_MPIBDiag,
719: MatMultTransposeAdd_MPIBDiag,
720: 0,
721: 0,
722: 0,
723: /*10*/ 0,
724: 0,
725: 0,
726: 0,
727: 0,
728: /*15*/ MatGetInfo_MPIBDiag,
729: 0,
730: MatGetDiagonal_MPIBDiag,
731: 0,
732: MatNorm_MPIBDiag,
733: /*20*/ MatAssemblyBegin_MPIBDiag,
734: MatAssemblyEnd_MPIBDiag,
735: 0,
736: MatSetOption_MPIBDiag,
737: MatZeroEntries_MPIBDiag,
738: /*25*/ MatZeroRows_MPIBDiag,
739: 0,
740: 0,
741: 0,
742: 0,
743: /*30*/ MatSetUpPreallocation_MPIBDiag,
744: 0,
745: 0,
746: 0,
747: 0,
748: /*35*/ 0,
749: 0,
750: 0,
751: 0,
752: 0,
753: /*40*/ 0,
754: 0,
755: 0,
756: MatGetValues_MPIBDiag,
757: 0,
758: /*45*/ 0,
759: MatScale_MPIBDiag,
760: 0,
761: 0,
762: 0,
763: /*50*/ 0,
764: 0,
765: 0,
766: 0,
767: 0,
768: /*55*/ 0,
769: 0,
770: 0,
771: 0,
772: 0,
773: /*60*/ 0,
774: MatDestroy_MPIBDiag,
775: MatView_MPIBDiag,
776: 0,
777: 0,
778: /*65*/ 0,
779: 0,
780: 0,
781: 0,
782: 0,
783: /*70*/ 0,
784: 0,
785: 0,
786: 0,
787: 0,
788: /*75*/ 0,
789: 0,
790: 0,
791: 0,
792: 0,
793: /*80*/ 0,
794: 0,
795: 0,
796: 0,
797: MatLoad_MPIBDiag,
798: /*85*/ 0,
799: 0,
800: 0,
801: 0,
802: 0,
803: /*90*/ 0,
804: 0,
805: 0,
806: 0,
807: 0,
808: /*95*/ 0,
809: 0,
810: 0,
811: 0};
816: PetscErrorCode MatGetDiagonalBlock_MPIBDiag(Mat A,PetscTruth *iscopy,MatReuse reuse,Mat *a)
817: {
818: Mat_MPIBDiag *matin = (Mat_MPIBDiag *)A->data;
820: PetscInt lrows,lcols,rstart,rend;
821: IS localc,localr;
824: MatGetLocalSize(A,&lrows,&lcols);
825: MatGetOwnershipRange(A,&rstart,&rend);
826: ISCreateStride(PETSC_COMM_SELF,lrows,rstart,1,&localc);
827: ISCreateStride(PETSC_COMM_SELF,lrows,0,1,&localr);
828: MatGetSubMatrix(matin->A,localr,localc,PETSC_DECIDE,reuse,a);
829: ISDestroy(localr);
830: ISDestroy(localc);
832: *iscopy = PETSC_TRUE;
833: return(0);
834: }
840: PetscErrorCode MatMPIBDiagSetPreallocation_MPIBDiag(Mat B,PetscInt nd,PetscInt bs,PetscInt *diag,PetscScalar **diagv)
841: {
842: Mat_MPIBDiag *b;
844: PetscInt i,k,*ldiag,len,nd2;
845: PetscScalar **ldiagv = 0;
846: PetscTruth flg2;
849: B->preallocated = PETSC_TRUE;
850: if (bs == PETSC_DEFAULT) bs = 1;
851: if (nd == PETSC_DEFAULT) nd = 0;
852: PetscOptionsGetInt(PETSC_NULL,"-mat_block_size",&bs,PETSC_NULL);
853: PetscOptionsGetInt(PETSC_NULL,"-mat_bdiag_ndiag",&nd,PETSC_NULL);
854: PetscOptionsHasName(PETSC_NULL,"-mat_bdiag_diags",&flg2);
855: if (nd && !diag) {
856: PetscMalloc(nd*sizeof(PetscInt),&diag);
857: nd2 = nd;
858: PetscOptionsGetIntArray(PETSC_NULL,"-mat_bdiag_dvals",diag,&nd2,PETSC_NULL);
859: if (nd2 != nd) {
860: SETERRQ(PETSC_ERR_ARG_INCOMP,"Incompatible number of diags and diagonal vals");
861: }
862: } else if (flg2) {
863: SETERRQ(PETSC_ERR_ARG_WRONG,"Must specify number of diagonals with -mat_bdiag_ndiag");
864: }
866: if (bs <= 0) SETERRQ(PETSC_ERR_ARG_OUTOFRANGE,"Blocksize must be positive");
868: B->rmap.bs = B->cmap.bs = bs;
870: PetscMapInitialize(B->comm,&B->rmap);
871: PetscMapInitialize(B->comm,&B->cmap);
873: if ((B->cmap.N%bs)) SETERRQ(PETSC_ERR_ARG_OUTOFRANGE,"Invalid block size - bad column number");
874: if ((B->rmap.N%bs)) SETERRQ(PETSC_ERR_ARG_OUTOFRANGE,"Invalid block size - bad local row number");
875: if ((B->rmap.N%bs)) SETERRQ(PETSC_ERR_ARG_OUTOFRANGE,"Invalid block size - bad global row number");
878: b = (Mat_MPIBDiag*)B->data;
879: b->gnd = nd;
880: b->brstart = (B->rmap.rstart)/bs;
881: b->brend = (B->rmap.rend)/bs;
884: /* Determine local diagonals; for now, assume global rows = global cols */
885: /* These are sorted in MatCreateSeqBDiag */
886: PetscMalloc((nd+1)*sizeof(PetscInt),&ldiag);
887: len = B->rmap.N/bs + B->cmap.N/bs + 1;
888: PetscMalloc(len*sizeof(PetscInt),&b->gdiag);
889: k = 0;
890: if (diagv) {
891: PetscMalloc((nd+1)*sizeof(PetscScalar*),&ldiagv);
892: }
893: for (i=0; i<nd; i++) {
894: b->gdiag[i] = diag[i];
895: if (diag[i] > 0) { /* lower triangular */
896: if (diag[i] < b->brend) {
897: ldiag[k] = diag[i] - b->brstart;
898: if (diagv) ldiagv[k] = diagv[i];
899: k++;
900: }
901: } else { /* upper triangular */
902: if (B->rmap.N/bs - diag[i] > B->cmap.N/bs) {
903: if (B->rmap.N/bs + diag[i] > b->brstart) {
904: ldiag[k] = diag[i] - b->brstart;
905: if (diagv) ldiagv[k] = diagv[i];
906: k++;
907: }
908: } else {
909: if (B->rmap.N/bs > b->brstart) {
910: ldiag[k] = diag[i] - b->brstart;
911: if (diagv) ldiagv[k] = diagv[i];
912: k++;
913: }
914: }
915: }
916: }
918: /* Form local matrix */
919: MatCreate(PETSC_COMM_SELF,&b->A);
920: MatSetSizes(b->A,B->rmap.n,B->cmap.N,B->rmap.n,B->cmap.N);
921: MatSetType(b->A,MATSEQBDIAG);
922: MatSeqBDiagSetPreallocation(b->A,k,bs,ldiag,ldiagv);
923: PetscLogObjectParent(B,b->A);
924: PetscFree(ldiag);
925: PetscFree(ldiagv);
927: return(0);
928: }
931: /*MC
932: MATMPIBDIAG - MATMPIBDIAG = "mpibdiag" - A matrix type to be used for distributed block diagonal matrices.
934: Options Database Keys:
935: . -mat_type mpibdiag - sets the matrix type to "mpibdiag" during a call to MatSetFromOptions()
937: Level: beginner
939: .seealso: MatCreateMPIBDiag
940: M*/
945: PetscErrorCode MatCreate_MPIBDiag(Mat B)
946: {
947: Mat_MPIBDiag *b;
951: PetscNew(Mat_MPIBDiag,&b);
952: B->data = (void*)b;
953: PetscMemcpy(B->ops,&MatOps_Values,sizeof(struct _MatOps));
954: B->factor = 0;
955: B->mapping = 0;
957: B->insertmode = NOT_SET_VALUES;
958: MPI_Comm_rank(B->comm,&b->rank);
959: MPI_Comm_size(B->comm,&b->size);
961: /* build cache for off array entries formed */
962: MatStashCreate_Private(B->comm,1,&B->stash);
963: b->donotstash = PETSC_FALSE;
965: /* stuff used for matrix-vector multiply */
966: b->lvec = 0;
967: b->Mvctx = 0;
969: /* used for MatSetValues() input */
970: b->roworiented = PETSC_TRUE;
972: PetscObjectComposeFunctionDynamic((PetscObject)B,"MatGetDiagonalBlock_C",
973: "MatGetDiagonalBlock_MPIBDiag",
974: MatGetDiagonalBlock_MPIBDiag);
975: PetscObjectComposeFunctionDynamic((PetscObject)B,"MatMPIBDiagSetPreallocation_C",
976: "MatMPIBDiagSetPreallocation_MPIBDiag",
977: MatMPIBDiagSetPreallocation_MPIBDiag);
978: PetscObjectChangeTypeName((PetscObject)B,MATMPIBDIAG);
979: return(0);
980: }
983: /*MC
984: MATBDIAG - MATBDIAG = "bdiag" - A matrix type to be used for block diagonal matrices.
986: This matrix type is identical to MATSEQBDIAG when constructed with a single process communicator,
987: and MATMPIBDIAG otherwise.
989: Options Database Keys:
990: . -mat_type bdiag - sets the matrix type to "bdiag" during a call to MatSetFromOptions()
992: Level: beginner
994: .seealso: MatCreateMPIBDiag,MATSEQBDIAG,MATMPIBDIAG
995: M*/
1000: PetscErrorCode MatCreate_BDiag(Mat A)
1001: {
1003: PetscMPIInt size;
1006: MPI_Comm_size(A->comm,&size);
1007: if (size == 1) {
1008: MatSetType(A,MATSEQBDIAG);
1009: } else {
1010: MatSetType(A,MATMPIBDIAG);
1011: }
1012: return(0);
1013: }
1018: /*@C
1019: MatMPIBDiagSetPreallocation -
1021: Collective on Mat
1023: Input Parameters:
1024: + A - the matrix
1025: . nd - number of block diagonals (global) (optional)
1026: . bs - each element of a diagonal is an bs x bs dense matrix
1027: . diag - optional array of block diagonal numbers (length nd).
1028: For a matrix element A[i,j], where i=row and j=column, the
1029: diagonal number is
1030: $ diag = i/bs - j/bs (integer division)
1031: Set diag=PETSC_NULL on input for PETSc to dynamically allocate memory as
1032: needed (expensive).
1033: - diagv - pointer to actual diagonals (in same order as diag array),
1034: if allocated by user. Otherwise, set diagv=PETSC_NULL on input for PETSc
1035: to control memory allocation.
1038: Options Database Keys:
1039: . -mat_block_size <bs> - Sets blocksize
1040: . -mat_bdiag_diags <s1,s2,s3,...> - Sets diagonal numbers
1042: Notes:
1043: If PETSC_DECIDE or PETSC_DETERMINE is used for a particular argument on one processor
1044: than it must be used on all processors that share the object for that argument.
1046: The parallel matrix is partitioned across the processors by rows, where
1047: each local rectangular matrix is stored in the uniprocessor block
1048: diagonal format. See the users manual for further details.
1050: The user MUST specify either the local or global numbers of rows
1051: (possibly both).
1053: The case bs=1 (conventional diagonal storage) is implemented as
1054: a special case.
1056: Fortran Notes:
1057: Fortran programmers cannot set diagv; this variable is ignored.
1059: Level: intermediate
1061: .keywords: matrix, block, diagonal, parallel, sparse
1063: .seealso: MatCreate(), MatCreateSeqBDiag(), MatSetValues()
1064: @*/
1065: PetscErrorCode MatMPIBDiagSetPreallocation(Mat B,PetscInt nd,PetscInt bs,const PetscInt diag[],PetscScalar *diagv[])
1066: {
1067: PetscErrorCode ierr,(*f)(Mat,PetscInt,PetscInt,const PetscInt[],PetscScalar*[]);
1070: PetscObjectQueryFunction((PetscObject)B,"MatMPIBDiagSetPreallocation_C",(void (**)(void))&f);
1071: if (f) {
1072: (*f)(B,nd,bs,diag,diagv);
1073: }
1074: return(0);
1075: }
1079: /*@C
1080: MatCreateMPIBDiag - Creates a sparse parallel matrix in MPIBDiag format.
1082: Collective on MPI_Comm
1084: Input Parameters:
1085: + comm - MPI communicator
1086: . m - number of local rows (or PETSC_DECIDE to have calculated if M is given)
1087: . M - number of global rows (or PETSC_DETERMINE to have calculated if m is given)
1088: . N - number of columns (local and global)
1089: . nd - number of block diagonals (global) (optional)
1090: . bs - each element of a diagonal is an bs x bs dense matrix
1091: . diag - optional array of block diagonal numbers (length nd).
1092: For a matrix element A[i,j], where i=row and j=column, the
1093: diagonal number is
1094: $ diag = i/bs - j/bs (integer division)
1095: Set diag=PETSC_NULL on input for PETSc to dynamically allocate memory as
1096: needed (expensive).
1097: - diagv - pointer to actual diagonals (in same order as diag array),
1098: if allocated by user. Otherwise, set diagv=PETSC_NULL on input for PETSc
1099: to control memory allocation.
1101: Output Parameter:
1102: . A - the matrix
1104: Options Database Keys:
1105: . -mat_block_size <bs> - Sets blocksize
1106: . -mat_bdiag_diags <s1,s2,s3,...> - Sets diagonal numbers
1108: Notes:
1109: If PETSC_DECIDE or PETSC_DETERMINE is used for a particular argument on one processor
1110: than it must be used on all processors that share the object for that argument.
1112: The parallel matrix is partitioned across the processors by rows, where
1113: each local rectangular matrix is stored in the uniprocessor block
1114: diagonal format. See the users manual for further details.
1116: The user MUST specify either the local or global numbers of rows
1117: (possibly both).
1119: The case bs=1 (conventional diagonal storage) is implemented as
1120: a special case.
1122: Fortran Notes:
1123: Fortran programmers cannot set diagv; this variable is ignored.
1125: Level: intermediate
1127: .keywords: matrix, block, diagonal, parallel, sparse
1129: .seealso: MatCreate(), MatCreateSeqBDiag(), MatSetValues()
1130: @*/
1131: PetscErrorCode MatCreateMPIBDiag(MPI_Comm comm,PetscInt m,PetscInt M,PetscInt N,PetscInt nd,PetscInt bs,const PetscInt diag[],PetscScalar *diagv[],Mat *A)
1132: {
1134: PetscMPIInt size;
1137: MatCreate(comm,A);
1138: MatSetSizes(*A,m,m,M,N);
1139: MPI_Comm_size(comm,&size);
1140: if (size > 1) {
1141: MatSetType(*A,MATMPIBDIAG);
1142: MatMPIBDiagSetPreallocation(*A,nd,bs,diag,diagv);
1143: } else {
1144: MatSetType(*A,MATSEQBDIAG);
1145: MatSeqBDiagSetPreallocation(*A,nd,bs,diag,diagv);
1146: }
1147: return(0);
1148: }
1152: /*@C
1153: MatBDiagGetData - Gets the data for the block diagonal matrix format.
1154: For the parallel case, this returns information for the local submatrix.
1156: Input Parameters:
1157: . mat - the matrix, stored in block diagonal format.
1159: Not Collective
1161: Output Parameters:
1162: + m - number of rows
1163: . n - number of columns
1164: . nd - number of block diagonals
1165: . bs - each element of a diagonal is an bs x bs dense matrix
1166: . bdlen - array of total block lengths of block diagonals
1167: . diag - optional array of block diagonal numbers (length nd).
1168: For a matrix element A[i,j], where i=row and j=column, the
1169: diagonal number is
1170: $ diag = i/bs - j/bs (integer division)
1171: Set diag=PETSC_NULL on input for PETSc to dynamically allocate memory as
1172: needed (expensive).
1173: - diagv - pointer to actual diagonals (in same order as diag array),
1175: Level: advanced
1177: Notes:
1178: See the users manual for further details regarding this storage format.
1180: .keywords: matrix, block, diagonal, get, data
1182: .seealso: MatCreateSeqBDiag(), MatCreateMPIBDiag()
1183: @*/
1184: PetscErrorCode MatBDiagGetData(Mat mat,PetscInt *nd,PetscInt *bs,PetscInt *diag[],PetscInt *bdlen[],PetscScalar ***diagv)
1185: {
1186: Mat_MPIBDiag *pdmat;
1187: Mat_SeqBDiag *dmat = 0;
1188: PetscTruth isseq,ismpi;
1193: PetscTypeCompare((PetscObject)mat,MATSEQBDIAG,&isseq);
1194: PetscTypeCompare((PetscObject)mat,MATMPIBDIAG,&ismpi);
1195: if (isseq) {
1196: dmat = (Mat_SeqBDiag*)mat->data;
1197: } else if (ismpi) {
1198: pdmat = (Mat_MPIBDiag*)mat->data;
1199: dmat = (Mat_SeqBDiag*)pdmat->A->data;
1200: } else SETERRQ(PETSC_ERR_SUP,"Valid only for MATSEQBDIAG and MATMPIBDIAG formats");
1201: *nd = dmat->nd;
1202: *bs = mat->rmap.bs;
1203: *diag = dmat->diag;
1204: *bdlen = dmat->bdlen;
1205: *diagv = dmat->diagv;
1206: return(0);
1207: }
1209: #include petscsys.h
1213: PetscErrorCode MatLoad_MPIBDiag(PetscViewer viewer, MatType type,Mat *newmat)
1214: {
1215: Mat A;
1216: PetscScalar *vals,*svals;
1217: MPI_Comm comm = ((PetscObject)viewer)->comm;
1218: MPI_Status status;
1220: int fd;
1221: PetscMPIInt tag = ((PetscObject)viewer)->tag,rank,size,*sndcounts = 0,*rowners,maxnz,mm;
1222: PetscInt bs,i,nz,j,rstart,rend,*cols;
1223: PetscInt header[4],*rowlengths = 0,M,N,m,Mbs;
1224: PetscInt *ourlens,*procsnz = 0,jj,*mycols,*smycols;
1225: PetscInt extra_rows;
1228: MPI_Comm_size(comm,&size);
1229: MPI_Comm_rank(comm,&rank);
1230: if (!rank) {
1231: PetscViewerBinaryGetDescriptor(viewer,&fd);
1232: PetscBinaryRead(fd,(char *)header,4,PETSC_INT);
1233: if (header[0] != MAT_FILE_COOKIE) SETERRQ(PETSC_ERR_FILE_UNEXPECTED,"not matrix object");
1234: if (header[3] < 0) {
1235: SETERRQ(PETSC_ERR_FILE_UNEXPECTED,"Matrix stored in special format,cannot load as MPIBDiag");
1236: }
1237: }
1238: MPI_Bcast(header+1,3,MPIU_INT,0,comm);
1239: M = header[1]; N = header[2];
1241: bs = 1; /* uses a block size of 1 by default; */
1242: PetscOptionsGetInt(PETSC_NULL,"-matload_block_size",&bs,PETSC_NULL);
1244: /*
1245: This code adds extra rows to make sure the number of rows is
1246: divisible by the blocksize
1247: */
1248: Mbs = M/bs;
1249: extra_rows = bs - M + bs*(Mbs);
1250: if (extra_rows == bs) extra_rows = 0;
1251: else Mbs++;
1252: if (extra_rows && !rank) {
1253: PetscInfo(0,"Padding loaded matrix to match blocksize\n");
1254: }
1256: /* determine ownership of all rows */
1257: m = bs*(Mbs/size + ((Mbs % size) > rank));
1258: PetscMalloc((size+2)*sizeof(PetscInt),&rowners);
1259: mm = (PetscMPIInt)m;
1260: MPI_Allgather(&mm,1,MPI_INT,rowners+1,1,MPI_INT,comm);
1261: rowners[0] = 0;
1262: for (i=2; i<=size; i++) {
1263: rowners[i] += rowners[i-1];
1264: }
1265: rstart = rowners[rank];
1266: rend = rowners[rank+1];
1268: /* distribute row lengths to all processors */
1269: PetscMalloc((rend-rstart)*sizeof(PetscInt),&ourlens);
1270: if (!rank) {
1271: PetscMalloc((M+extra_rows)*sizeof(PetscInt),&rowlengths);
1272: PetscBinaryRead(fd,rowlengths,M,PETSC_INT);
1273: for (i=0; i<extra_rows; i++) rowlengths[M+i] = 1;
1274: PetscMalloc(size*sizeof(PetscMPIInt),&sndcounts);
1275: for (i=0; i<size; i++) sndcounts[i] = rowners[i+1] - rowners[i];
1276: MPI_Scatterv(rowlengths,sndcounts,rowners,MPIU_INT,ourlens,rend-rstart,MPIU_INT,0,comm);
1277: PetscFree(sndcounts);
1278: } else {
1279: MPI_Scatterv(0,0,0,MPIU_INT,ourlens,rend-rstart,MPIU_INT,0,comm);
1280: }
1282: if (!rank) {
1283: /* calculate the number of nonzeros on each processor */
1284: PetscMalloc(size*sizeof(PetscInt),&procsnz);
1285: PetscMemzero(procsnz,size*sizeof(PetscInt));
1286: for (i=0; i<size; i++) {
1287: for (j=rowners[i]; j<rowners[i+1]; j++) {
1288: procsnz[i] += rowlengths[j];
1289: }
1290: }
1291: PetscFree(rowlengths);
1293: /* determine max buffer needed and allocate it */
1294: maxnz = 0;
1295: for (i=0; i<size; i++) {
1296: maxnz = PetscMax(maxnz,procsnz[i]);
1297: }
1298: PetscMalloc(maxnz*sizeof(PetscInt),&cols);
1300: /* read in my part of the matrix column indices */
1301: nz = procsnz[0];
1302: PetscMalloc(nz*sizeof(PetscInt),&mycols);
1303: if (size == 1) nz -= extra_rows;
1304: PetscBinaryRead(fd,mycols,nz,PETSC_INT);
1305: if (size == 1) for (i=0; i<extra_rows; i++) { mycols[nz+i] = M+i; }
1307: /* read in every one elses and ship off */
1308: for (i=1; i<size-1; i++) {
1309: nz = procsnz[i];
1310: PetscBinaryRead(fd,cols,nz,PETSC_INT);
1311: MPI_Send(cols,nz,MPIU_INT,i,tag,comm);
1312: }
1313: /* read in the stuff for the last proc */
1314: if (size != 1) {
1315: nz = procsnz[size-1] - extra_rows; /* the extra rows are not on the disk */
1316: PetscBinaryRead(fd,cols,nz,PETSC_INT);
1317: for (i=0; i<extra_rows; i++) cols[nz+i] = M+i;
1318: MPI_Send(cols,nz+extra_rows,MPIU_INT,size-1,tag,comm);
1319: }
1320: PetscFree(cols);
1321: } else {
1322: /* determine buffer space needed for message */
1323: nz = 0;
1324: for (i=0; i<m; i++) {
1325: nz += ourlens[i];
1326: }
1327: PetscMalloc(nz*sizeof(PetscInt),&mycols);
1329: /* receive message of column indices*/
1330: MPI_Recv(mycols,nz,MPIU_INT,0,tag,comm,&status);
1331: MPI_Get_count(&status,MPIU_INT,&maxnz);
1332: if (maxnz != nz) SETERRQ(PETSC_ERR_FILE_UNEXPECTED,"something is wrong with file");
1333: }
1335: MatCreate(comm,newmat);
1336: MatSetSizes(*newmat,m,m,M+extra_rows,N+extra_rows);
1337: MatSetType(*newmat,type);
1338: MatMPIBDiagSetPreallocation(*newmat,0,bs,PETSC_NULL,PETSC_NULL);
1339: A = *newmat;
1341: if (!rank) {
1342: PetscMalloc(maxnz*sizeof(PetscScalar),&vals);
1344: /* read in my part of the matrix numerical values */
1345: nz = procsnz[0];
1346: if (size == 1) nz -= extra_rows;
1347: PetscBinaryRead(fd,vals,nz,PETSC_SCALAR);
1348: if (size == 1) for (i=0; i<extra_rows; i++) { vals[nz+i] = 1.0; }
1350: /* insert into matrix */
1351: jj = rstart;
1352: smycols = mycols;
1353: svals = vals;
1354: for (i=0; i<m; i++) {
1355: MatSetValues(A,1,&jj,ourlens[i],smycols,svals,INSERT_VALUES);
1356: smycols += ourlens[i];
1357: svals += ourlens[i];
1358: jj++;
1359: }
1361: /* read in other processors (except the last one) and ship out */
1362: for (i=1; i<size-1; i++) {
1363: nz = procsnz[i];
1364: PetscBinaryRead(fd,vals,nz,PETSC_SCALAR);
1365: MPI_Send(vals,nz,MPIU_SCALAR,i,A->tag,comm);
1366: }
1367: /* the last proc */
1368: if (size != 1){
1369: nz = procsnz[i] - extra_rows;
1370: PetscBinaryRead(fd,vals,nz,PETSC_SCALAR);
1371: for (i=0; i<extra_rows; i++) vals[nz+i] = 1.0;
1372: MPI_Send(vals,nz+extra_rows,MPIU_SCALAR,size-1,A->tag,comm);
1373: }
1374: PetscFree(procsnz);
1375: } else {
1376: /* receive numeric values */
1377: PetscMalloc(nz*sizeof(PetscScalar),&vals);
1379: /* receive message of values*/
1380: MPI_Recv(vals,nz,MPIU_SCALAR,0,A->tag,comm,&status);
1381: MPI_Get_count(&status,MPIU_SCALAR,&maxnz);
1382: if (maxnz != nz) SETERRQ(PETSC_ERR_FILE_UNEXPECTED,"something is wrong with file");
1384: /* insert into matrix */
1385: jj = rstart;
1386: smycols = mycols;
1387: svals = vals;
1388: for (i=0; i<m; i++) {
1389: MatSetValues(A,1,&jj,ourlens[i],smycols,svals,INSERT_VALUES);
1390: smycols += ourlens[i];
1391: svals += ourlens[i];
1392: jj++;
1393: }
1394: }
1395: PetscFree(ourlens);
1396: PetscFree(vals);
1397: PetscFree(mycols);
1398: PetscFree(rowners);
1400: MatAssemblyBegin(A,MAT_FINAL_ASSEMBLY);
1401: MatAssemblyEnd(A,MAT_FINAL_ASSEMBLY);
1402: return(0);
1403: }