Actual source code: mmdense.c
petsc-3.10.5 2019-03-28
2: /*
3: Support for the parallel dense matrix vector multiply
4: */
5: #include <../src/mat/impls/dense/mpi/mpidense.h>
6: #include <petscblaslapack.h>
8: PetscErrorCode MatSetUpMultiply_MPIDense(Mat mat)
9: {
10: Mat_MPIDense *mdn = (Mat_MPIDense*)mat->data;
12: IS from,to;
13: Vec gvec;
16: /* Create local vector that is used to scatter into */
17: VecCreateSeq(PETSC_COMM_SELF,mat->cmap->N,&mdn->lvec);
19: /* Create temporary index set for building scatter gather */
20: ISCreateStride(PetscObjectComm((PetscObject)mat),mat->cmap->N,0,1,&from);
21: ISCreateStride(PETSC_COMM_SELF,mat->cmap->N,0,1,&to);
23: /* Create temporary global vector to generate scatter context */
24: /* n = mdn->cowners[mdn->rank+1] - mdn->cowners[mdn->rank]; */
26: VecCreateMPIWithArray(PetscObjectComm((PetscObject)mat),1,mdn->nvec,mat->cmap->N,NULL,&gvec);
28: /* Generate the scatter context */
29: VecScatterCreate(gvec,from,mdn->lvec,to,&mdn->Mvctx);
30: PetscLogObjectParent((PetscObject)mat,(PetscObject)mdn->Mvctx);
31: PetscLogObjectParent((PetscObject)mat,(PetscObject)mdn->lvec);
32: PetscLogObjectParent((PetscObject)mat,(PetscObject)from);
33: PetscLogObjectParent((PetscObject)mat,(PetscObject)to);
34: PetscLogObjectParent((PetscObject)mat,(PetscObject)gvec);
36: ISDestroy(&to);
37: ISDestroy(&from);
38: VecDestroy(&gvec);
39: return(0);
40: }
42: extern PetscErrorCode MatCreateSubMatrices_MPIDense_Local(Mat,PetscInt,const IS[],const IS[],MatReuse,Mat*);
43: PetscErrorCode MatCreateSubMatrices_MPIDense(Mat C,PetscInt ismax,const IS isrow[],const IS iscol[],MatReuse scall,Mat *submat[])
44: {
46: PetscInt nmax,nstages_local,nstages,i,pos,max_no;
49: /* Allocate memory to hold all the submatrices */
50: if (scall != MAT_REUSE_MATRIX) {
51: PetscCalloc1(ismax+1,submat);
52: }
53: /* Determine the number of stages through which submatrices are done */
54: nmax = 20*1000000 / (C->cmap->N * sizeof(PetscInt));
55: if (!nmax) nmax = 1;
56: nstages_local = ismax/nmax + ((ismax % nmax) ? 1 : 0);
58: /* Make sure every processor loops through the nstages */
59: MPIU_Allreduce(&nstages_local,&nstages,1,MPIU_INT,MPI_MAX,PetscObjectComm((PetscObject)C));
62: for (i=0,pos=0; i<nstages; i++) {
63: if (pos+nmax <= ismax) max_no = nmax;
64: else if (pos == ismax) max_no = 0;
65: else max_no = ismax-pos;
66: MatCreateSubMatrices_MPIDense_Local(C,max_no,isrow+pos,iscol+pos,scall,*submat+pos);
67: pos += max_no;
68: }
69: return(0);
70: }
71: /* -------------------------------------------------------------------------*/
72: PetscErrorCode MatCreateSubMatrices_MPIDense_Local(Mat C,PetscInt ismax,const IS isrow[],const IS iscol[],MatReuse scall,Mat *submats)
73: {
74: Mat_MPIDense *c = (Mat_MPIDense*)C->data;
75: Mat A = c->A;
76: Mat_SeqDense *a = (Mat_SeqDense*)A->data,*mat;
78: PetscMPIInt rank,size,tag0,tag1,idex,end,i;
79: PetscInt N = C->cmap->N,rstart = C->rmap->rstart,count;
80: const PetscInt **irow,**icol,*irow_i;
81: PetscInt *nrow,*ncol,*w1,*w3,*w4,*rtable,start;
82: PetscInt **sbuf1,m,j,k,l,ct1,**rbuf1,row,proc;
83: PetscInt nrqs,msz,**ptr,*ctr,*pa,*tmp,bsz,nrqr;
84: PetscInt is_no,jmax,**rmap,*rmap_i;
85: PetscInt ctr_j,*sbuf1_j,*rbuf1_i;
86: MPI_Request *s_waits1,*r_waits1,*s_waits2,*r_waits2;
87: MPI_Status *r_status1,*r_status2,*s_status1,*s_status2;
88: MPI_Comm comm;
89: PetscScalar **rbuf2,**sbuf2;
90: PetscBool sorted;
93: PetscObjectGetComm((PetscObject)C,&comm);
94: tag0 = ((PetscObject)C)->tag;
95: size = c->size;
96: rank = c->rank;
97: m = C->rmap->N;
99: /* Get some new tags to keep the communication clean */
100: PetscObjectGetNewTag((PetscObject)C,&tag1);
102: /* Check if the col indices are sorted */
103: for (i=0; i<ismax; i++) {
104: ISSorted(isrow[i],&sorted);
105: if (!sorted) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"ISrow is not sorted");
106: ISSorted(iscol[i],&sorted);
107: if (!sorted) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"IScol is not sorted");
108: }
110: PetscMalloc5(ismax,(PetscInt***)&irow,ismax,(PetscInt***)&icol,ismax,&nrow,ismax,&ncol,m,&rtable);
111: for (i=0; i<ismax; i++) {
112: ISGetIndices(isrow[i],&irow[i]);
113: ISGetIndices(iscol[i],&icol[i]);
114: ISGetLocalSize(isrow[i],&nrow[i]);
115: ISGetLocalSize(iscol[i],&ncol[i]);
116: }
118: /* Create hash table for the mapping :row -> proc*/
119: for (i=0,j=0; i<size; i++) {
120: jmax = C->rmap->range[i+1];
121: for (; j<jmax; j++) rtable[j] = i;
122: }
124: /* evaluate communication - mesg to who,length of mesg, and buffer space
125: required. Based on this, buffers are allocated, and data copied into them*/
126: PetscMalloc3(2*size,&w1,size,&w3,size,&w4);
127: PetscMemzero(w1,size*2*sizeof(PetscInt)); /* initialize work vector*/
128: PetscMemzero(w3,size*sizeof(PetscInt)); /* initialize work vector*/
129: for (i=0; i<ismax; i++) {
130: PetscMemzero(w4,size*sizeof(PetscInt)); /* initialize work vector*/
131: jmax = nrow[i];
132: irow_i = irow[i];
133: for (j=0; j<jmax; j++) {
134: row = irow_i[j];
135: proc = rtable[row];
136: w4[proc]++;
137: }
138: for (j=0; j<size; j++) {
139: if (w4[j]) { w1[2*j] += w4[j]; w3[j]++;}
140: }
141: }
143: nrqs = 0; /* no of outgoing messages */
144: msz = 0; /* total mesg length (for all procs) */
145: w1[2*rank] = 0; /* no mesg sent to self */
146: w3[rank] = 0;
147: for (i=0; i<size; i++) {
148: if (w1[2*i]) { w1[2*i+1] = 1; nrqs++;} /* there exists a message to proc i */
149: }
150: PetscMalloc1(nrqs+1,&pa); /*(proc -array)*/
151: for (i=0,j=0; i<size; i++) {
152: if (w1[2*i]) { pa[j] = i; j++; }
153: }
155: /* Each message would have a header = 1 + 2*(no of IS) + data */
156: for (i=0; i<nrqs; i++) {
157: j = pa[i];
158: w1[2*j] += w1[2*j+1] + 2* w3[j];
159: msz += w1[2*j];
160: }
161: /* Do a global reduction to determine how many messages to expect*/
162: PetscMaxSum(comm,w1,&bsz,&nrqr);
164: /* Allocate memory for recv buffers . Make sure rbuf1[0] exists by adding 1 to the buffer length */
165: PetscMalloc1(nrqr+1,&rbuf1);
166: PetscMalloc1(nrqr*bsz,&rbuf1[0]);
167: for (i=1; i<nrqr; ++i) rbuf1[i] = rbuf1[i-1] + bsz;
169: /* Post the receives */
170: PetscMalloc1(nrqr+1,&r_waits1);
171: for (i=0; i<nrqr; ++i) {
172: MPI_Irecv(rbuf1[i],bsz,MPIU_INT,MPI_ANY_SOURCE,tag0,comm,r_waits1+i);
173: }
175: /* Allocate Memory for outgoing messages */
176: PetscMalloc4(size,&sbuf1,size,&ptr,2*msz,&tmp,size,&ctr);
177: PetscMemzero(sbuf1,size*sizeof(PetscInt*));
178: PetscMemzero(ptr,size*sizeof(PetscInt*));
179: {
180: PetscInt *iptr = tmp,ict = 0;
181: for (i=0; i<nrqs; i++) {
182: j = pa[i];
183: iptr += ict;
184: sbuf1[j] = iptr;
185: ict = w1[2*j];
186: }
187: }
189: /* Form the outgoing messages */
190: /* Initialize the header space */
191: for (i=0; i<nrqs; i++) {
192: j = pa[i];
193: sbuf1[j][0] = 0;
194: PetscMemzero(sbuf1[j]+1,2*w3[j]*sizeof(PetscInt));
195: ptr[j] = sbuf1[j] + 2*w3[j] + 1;
196: }
198: /* Parse the isrow and copy data into outbuf */
199: for (i=0; i<ismax; i++) {
200: PetscMemzero(ctr,size*sizeof(PetscInt));
201: irow_i = irow[i];
202: jmax = nrow[i];
203: for (j=0; j<jmax; j++) { /* parse the indices of each IS */
204: row = irow_i[j];
205: proc = rtable[row];
206: if (proc != rank) { /* copy to the outgoing buf*/
207: ctr[proc]++;
208: *ptr[proc] = row;
209: ptr[proc]++;
210: }
211: }
212: /* Update the headers for the current IS */
213: for (j=0; j<size; j++) { /* Can Optimise this loop too */
214: if ((ctr_j = ctr[j])) {
215: sbuf1_j = sbuf1[j];
216: k = ++sbuf1_j[0];
217: sbuf1_j[2*k] = ctr_j;
218: sbuf1_j[2*k-1] = i;
219: }
220: }
221: }
223: /* Now post the sends */
224: PetscMalloc1(nrqs+1,&s_waits1);
225: for (i=0; i<nrqs; ++i) {
226: j = pa[i];
227: MPI_Isend(sbuf1[j],w1[2*j],MPIU_INT,j,tag0,comm,s_waits1+i);
228: }
230: /* Post recieves to capture the row_data from other procs */
231: PetscMalloc1(nrqs+1,&r_waits2);
232: PetscMalloc1(nrqs+1,&rbuf2);
233: for (i=0; i<nrqs; i++) {
234: j = pa[i];
235: count = (w1[2*j] - (2*sbuf1[j][0] + 1))*N;
236: PetscMalloc1(count+1,&rbuf2[i]);
237: MPI_Irecv(rbuf2[i],count,MPIU_SCALAR,j,tag1,comm,r_waits2+i);
238: }
240: /* Receive messages(row_nos) and then, pack and send off the rowvalues
241: to the correct processors */
243: PetscMalloc1(nrqr+1,&s_waits2);
244: PetscMalloc1(nrqr+1,&r_status1);
245: PetscMalloc1(nrqr+1,&sbuf2);
247: {
248: PetscScalar *sbuf2_i,*v_start;
249: PetscInt s_proc;
250: for (i=0; i<nrqr; ++i) {
251: MPI_Waitany(nrqr,r_waits1,&idex,r_status1+i);
252: s_proc = r_status1[i].MPI_SOURCE; /* send processor */
253: rbuf1_i = rbuf1[idex]; /* Actual message from s_proc */
254: /* no of rows = end - start; since start is array idex[], 0idex, whel end
255: is length of the buffer - which is 1idex */
256: start = 2*rbuf1_i[0] + 1;
257: MPI_Get_count(r_status1+i,MPIU_INT,&end);
258: /* allocate memory sufficinet to hold all the row values */
259: PetscMalloc1((end-start)*N,&sbuf2[idex]);
260: sbuf2_i = sbuf2[idex];
261: /* Now pack the data */
262: for (j=start; j<end; j++) {
263: row = rbuf1_i[j] - rstart;
264: v_start = a->v + row;
265: for (k=0; k<N; k++) {
266: sbuf2_i[0] = v_start[0];
267: sbuf2_i++;
268: v_start += C->rmap->n;
269: }
270: }
271: /* Now send off the data */
272: MPI_Isend(sbuf2[idex],(end-start)*N,MPIU_SCALAR,s_proc,tag1,comm,s_waits2+i);
273: }
274: }
275: /* End Send-Recv of IS + row_numbers */
276: PetscFree(r_status1);
277: PetscFree(r_waits1);
278: PetscMalloc1(nrqs+1,&s_status1);
279: if (nrqs) {MPI_Waitall(nrqs,s_waits1,s_status1);}
280: PetscFree(s_status1);
281: PetscFree(s_waits1);
283: /* Create the submatrices */
284: if (scall == MAT_REUSE_MATRIX) {
285: for (i=0; i<ismax; i++) {
286: mat = (Mat_SeqDense*)(submats[i]->data);
287: if ((submats[i]->rmap->n != nrow[i]) || (submats[i]->cmap->n != ncol[i])) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"Cannot reuse matrix. wrong size");
288: PetscMemzero(mat->v,submats[i]->rmap->n*submats[i]->cmap->n*sizeof(PetscScalar));
290: submats[i]->factortype = C->factortype;
291: }
292: } else {
293: for (i=0; i<ismax; i++) {
294: MatCreate(PETSC_COMM_SELF,submats+i);
295: MatSetSizes(submats[i],nrow[i],ncol[i],nrow[i],ncol[i]);
296: MatSetType(submats[i],((PetscObject)A)->type_name);
297: MatSeqDenseSetPreallocation(submats[i],NULL);
298: }
299: }
301: /* Assemble the matrices */
302: {
303: PetscInt col;
304: PetscScalar *imat_v,*mat_v,*imat_vi,*mat_vi;
306: for (i=0; i<ismax; i++) {
307: mat = (Mat_SeqDense*)submats[i]->data;
308: mat_v = a->v;
309: imat_v = mat->v;
310: irow_i = irow[i];
311: m = nrow[i];
312: for (j=0; j<m; j++) {
313: row = irow_i[j];
314: proc = rtable[row];
315: if (proc == rank) {
316: row = row - rstart;
317: mat_vi = mat_v + row;
318: imat_vi = imat_v + j;
319: for (k=0; k<ncol[i]; k++) {
320: col = icol[i][k];
321: imat_vi[k*m] = mat_vi[col*C->rmap->n];
322: }
323: }
324: }
325: }
326: }
328: /* Create row map-> This maps c->row to submat->row for each submat*/
329: /* this is a very expensive operation wrt memory usage */
330: PetscMalloc1(ismax,&rmap);
331: PetscMalloc1(ismax*C->rmap->N,&rmap[0]);
332: PetscMemzero(rmap[0],ismax*C->rmap->N*sizeof(PetscInt));
333: for (i=1; i<ismax; i++) rmap[i] = rmap[i-1] + C->rmap->N;
334: for (i=0; i<ismax; i++) {
335: rmap_i = rmap[i];
336: irow_i = irow[i];
337: jmax = nrow[i];
338: for (j=0; j<jmax; j++) {
339: rmap_i[irow_i[j]] = j;
340: }
341: }
343: /* Now Receive the row_values and assemble the rest of the matrix */
344: PetscMalloc1(nrqs+1,&r_status2);
345: {
346: PetscInt is_max,tmp1,col,*sbuf1_i,is_sz;
347: PetscScalar *rbuf2_i,*imat_v,*imat_vi;
349: for (tmp1=0; tmp1<nrqs; tmp1++) { /* For each message */
350: MPI_Waitany(nrqs,r_waits2,&i,r_status2+tmp1);
351: /* Now dig out the corresponding sbuf1, which contains the IS data_structure */
352: sbuf1_i = sbuf1[pa[i]];
353: is_max = sbuf1_i[0];
354: ct1 = 2*is_max+1;
355: rbuf2_i = rbuf2[i];
356: for (j=1; j<=is_max; j++) { /* For each IS belonging to the message */
357: is_no = sbuf1_i[2*j-1];
358: is_sz = sbuf1_i[2*j];
359: mat = (Mat_SeqDense*)submats[is_no]->data;
360: imat_v = mat->v;
361: rmap_i = rmap[is_no];
362: m = nrow[is_no];
363: for (k=0; k<is_sz; k++,rbuf2_i+=N) { /* For each row */
364: row = sbuf1_i[ct1]; ct1++;
365: row = rmap_i[row];
366: imat_vi = imat_v + row;
367: for (l=0; l<ncol[is_no]; l++) { /* For each col */
368: col = icol[is_no][l];
369: imat_vi[l*m] = rbuf2_i[col];
370: }
371: }
372: }
373: }
374: }
375: /* End Send-Recv of row_values */
376: PetscFree(r_status2);
377: PetscFree(r_waits2);
378: PetscMalloc1(nrqr+1,&s_status2);
379: if (nrqr) {MPI_Waitall(nrqr,s_waits2,s_status2);}
380: PetscFree(s_status2);
381: PetscFree(s_waits2);
383: /* Restore the indices */
384: for (i=0; i<ismax; i++) {
385: ISRestoreIndices(isrow[i],irow+i);
386: ISRestoreIndices(iscol[i],icol+i);
387: }
389: PetscFree5(*(PetscInt***)&irow,*(PetscInt***)&icol,nrow,ncol,rtable);
390: PetscFree3(w1,w3,w4);
391: PetscFree(pa);
393: for (i=0; i<nrqs; ++i) {
394: PetscFree(rbuf2[i]);
395: }
396: PetscFree(rbuf2);
397: PetscFree4(sbuf1,ptr,tmp,ctr);
398: PetscFree(rbuf1[0]);
399: PetscFree(rbuf1);
401: for (i=0; i<nrqr; ++i) {
402: PetscFree(sbuf2[i]);
403: }
405: PetscFree(sbuf2);
406: PetscFree(rmap[0]);
407: PetscFree(rmap);
409: for (i=0; i<ismax; i++) {
410: MatAssemblyBegin(submats[i],MAT_FINAL_ASSEMBLY);
411: MatAssemblyEnd(submats[i],MAT_FINAL_ASSEMBLY);
412: }
413: return(0);
414: }
416: PetscErrorCode MatScale_MPIDense(Mat inA,PetscScalar alpha)
417: {
418: Mat_MPIDense *A = (Mat_MPIDense*)inA->data;
419: Mat_SeqDense *a = (Mat_SeqDense*)A->A->data;
420: PetscScalar oalpha = alpha;
422: PetscBLASInt one = 1,nz;
425: PetscBLASIntCast(inA->rmap->n*inA->cmap->N,&nz);
426: PetscStackCallBLAS("BLASscal",BLASscal_(&nz,&oalpha,a->v,&one));
427: PetscLogFlops(nz);
428: return(0);
429: }