Actual source code: mmdense.c
2: /*
3: Support for the parallel dense matrix vector multiply
4: */
5: #include <../src/mat/impls/dense/mpi/mpidense.h>
6: #include <petscblaslapack.h>
10: PetscErrorCode MatSetUpMultiply_MPIDense(Mat mat)
11: {
12: Mat_MPIDense *mdn = (Mat_MPIDense*)mat->data;
14: IS from,to;
15: Vec gvec;
18: /* Create local vector that is used to scatter into */
19: VecCreateSeq(PETSC_COMM_SELF,mat->cmap->N,&mdn->lvec);
21: /* Create temporary index set for building scatter gather */
22: ISCreateStride(((PetscObject)mat)->comm,mat->cmap->N,0,1,&from);
23: ISCreateStride(PETSC_COMM_SELF,mat->cmap->N,0,1,&to);
25: /* Create temporary global vector to generate scatter context */
26: /* n = mdn->cowners[mdn->rank+1] - mdn->cowners[mdn->rank]; */
28: VecCreateMPIWithArray(((PetscObject)mat)->comm,mdn->nvec,mat->cmap->N,PETSC_NULL,&gvec);
30: /* Generate the scatter context */
31: VecScatterCreate(gvec,from,mdn->lvec,to,&mdn->Mvctx);
32: PetscLogObjectParent(mat,mdn->Mvctx);
33: PetscLogObjectParent(mat,mdn->lvec);
34: PetscLogObjectParent(mat,from);
35: PetscLogObjectParent(mat,to);
36: PetscLogObjectParent(mat,gvec);
38: ISDestroy(&to);
39: ISDestroy(&from);
40: VecDestroy(&gvec);
41: return(0);
42: }
47: PetscErrorCode MatGetSubMatrices_MPIDense(Mat C,PetscInt ismax,const IS isrow[],const IS iscol[],MatReuse scall,Mat *submat[])
48: {
50: PetscInt nmax,nstages_local,nstages,i,pos,max_no;
53: /* Allocate memory to hold all the submatrices */
54: if (scall != MAT_REUSE_MATRIX) {
55: PetscMalloc((ismax+1)*sizeof(Mat),submat);
56: }
57: /* Determine the number of stages through which submatrices are done */
58: nmax = 20*1000000 / (C->cmap->N * sizeof(PetscInt));
59: if (!nmax) nmax = 1;
60: nstages_local = ismax/nmax + ((ismax % nmax)?1:0);
62: /* Make sure every processor loops through the nstages */
63: MPI_Allreduce(&nstages_local,&nstages,1,MPIU_INT,MPI_MAX,((PetscObject)C)->comm);
66: for (i=0,pos=0; i<nstages; i++) {
67: if (pos+nmax <= ismax) max_no = nmax;
68: else if (pos == ismax) max_no = 0;
69: else max_no = ismax-pos;
70: MatGetSubMatrices_MPIDense_Local(C,max_no,isrow+pos,iscol+pos,scall,*submat+pos);
71: pos += max_no;
72: }
73: return(0);
74: }
75: /* -------------------------------------------------------------------------*/
78: PetscErrorCode MatGetSubMatrices_MPIDense_Local(Mat C,PetscInt ismax,const IS isrow[],const IS iscol[],MatReuse scall,Mat *submats)
79: {
80: Mat_MPIDense *c = (Mat_MPIDense*)C->data;
81: Mat A = c->A;
82: Mat_SeqDense *a = (Mat_SeqDense*)A->data,*mat;
84: PetscMPIInt rank,size,tag0,tag1,idex,end,i;
85: PetscInt N = C->cmap->N,rstart = C->rmap->rstart,count;
86: const PetscInt **irow,**icol,*irow_i;
87: PetscInt *nrow,*ncol,*w1,*w3,*w4,*rtable,start;
88: PetscInt **sbuf1,m,j,k,l,ct1,**rbuf1,row,proc;
89: PetscInt nrqs,msz,**ptr,*ctr,*pa,*tmp,bsz,nrqr;
90: PetscInt is_no,jmax,**rmap,*rmap_i;
91: PetscInt ctr_j,*sbuf1_j,*rbuf1_i;
92: MPI_Request *s_waits1,*r_waits1,*s_waits2,*r_waits2;
93: MPI_Status *r_status1,*r_status2,*s_status1,*s_status2;
94: MPI_Comm comm;
95: PetscScalar **rbuf2,**sbuf2;
96: PetscBool sorted;
99: comm = ((PetscObject)C)->comm;
100: tag0 = ((PetscObject)C)->tag;
101: size = c->size;
102: rank = c->rank;
103: m = C->rmap->N;
104:
105: /* Get some new tags to keep the communication clean */
106: PetscObjectGetNewTag((PetscObject)C,&tag1);
108: /* Check if the col indices are sorted */
109: for (i=0; i<ismax; i++) {
110: ISSorted(isrow[i],&sorted);
111: if (!sorted) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"ISrow is not sorted");
112: ISSorted(iscol[i],&sorted);
113: if (!sorted) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"IScol is not sorted");
114: }
116: PetscMalloc5(ismax,const PetscInt*,&irow,ismax,const PetscInt*,&icol,ismax,PetscInt,&nrow,ismax,PetscInt,&ncol,m,PetscInt,&rtable);
117: for (i=0; i<ismax; i++) {
118: ISGetIndices(isrow[i],&irow[i]);
119: ISGetIndices(iscol[i],&icol[i]);
120: ISGetLocalSize(isrow[i],&nrow[i]);
121: ISGetLocalSize(iscol[i],&ncol[i]);
122: }
124: /* Create hash table for the mapping :row -> proc*/
125: for (i=0,j=0; i<size; i++) {
126: jmax = C->rmap->range[i+1];
127: for (; j<jmax; j++) {
128: rtable[j] = i;
129: }
130: }
132: /* evaluate communication - mesg to who,length of mesg, and buffer space
133: required. Based on this, buffers are allocated, and data copied into them*/
134: PetscMalloc3(2*size,PetscInt,&w1,size,PetscInt,&w3,size,PetscInt,&w4);
135: PetscMemzero(w1,size*2*sizeof(PetscInt)); /* initialize work vector*/
136: PetscMemzero(w3,size*sizeof(PetscInt)); /* initialize work vector*/
137: for (i=0; i<ismax; i++) {
138: PetscMemzero(w4,size*sizeof(PetscInt)); /* initialize work vector*/
139: jmax = nrow[i];
140: irow_i = irow[i];
141: for (j=0; j<jmax; j++) {
142: row = irow_i[j];
143: proc = rtable[row];
144: w4[proc]++;
145: }
146: for (j=0; j<size; j++) {
147: if (w4[j]) { w1[2*j] += w4[j]; w3[j]++;}
148: }
149: }
150:
151: nrqs = 0; /* no of outgoing messages */
152: msz = 0; /* total mesg length (for all procs) */
153: w1[2*rank] = 0; /* no mesg sent to self */
154: w3[rank] = 0;
155: for (i=0; i<size; i++) {
156: if (w1[2*i]) { w1[2*i+1] = 1; nrqs++;} /* there exists a message to proc i */
157: }
158: PetscMalloc((nrqs+1)*sizeof(PetscInt),&pa); /*(proc -array)*/
159: for (i=0,j=0; i<size; i++) {
160: if (w1[2*i]) { pa[j] = i; j++; }
161: }
163: /* Each message would have a header = 1 + 2*(no of IS) + data */
164: for (i=0; i<nrqs; i++) {
165: j = pa[i];
166: w1[2*j] += w1[2*j+1] + 2* w3[j];
167: msz += w1[2*j];
168: }
169: /* Do a global reduction to determine how many messages to expect*/
170: PetscMaxSum(comm,w1,&bsz,&nrqr);
172: /* Allocate memory for recv buffers . Make sure rbuf1[0] exists by adding 1 to the buffer length */
173: PetscMalloc((nrqr+1)*sizeof(PetscInt*),&rbuf1);
174: PetscMalloc(nrqr*bsz*sizeof(PetscInt),&rbuf1[0]);
175: for (i=1; i<nrqr; ++i) rbuf1[i] = rbuf1[i-1] + bsz;
176:
177: /* Post the receives */
178: PetscMalloc((nrqr+1)*sizeof(MPI_Request),&r_waits1);
179: for (i=0; i<nrqr; ++i) {
180: MPI_Irecv(rbuf1[i],bsz,MPIU_INT,MPI_ANY_SOURCE,tag0,comm,r_waits1+i);
181: }
183: /* Allocate Memory for outgoing messages */
184: PetscMalloc4(size,PetscInt*,&sbuf1,size,PetscInt*,&ptr,2*msz,PetscInt,&tmp,size,PetscInt,&ctr);
185: PetscMemzero(sbuf1,size*sizeof(PetscInt*));
186: PetscMemzero(ptr,size*sizeof(PetscInt*));
187: {
188: PetscInt *iptr = tmp,ict = 0;
189: for (i=0; i<nrqs; i++) {
190: j = pa[i];
191: iptr += ict;
192: sbuf1[j] = iptr;
193: ict = w1[2*j];
194: }
195: }
197: /* Form the outgoing messages */
198: /* Initialize the header space */
199: for (i=0; i<nrqs; i++) {
200: j = pa[i];
201: sbuf1[j][0] = 0;
202: PetscMemzero(sbuf1[j]+1,2*w3[j]*sizeof(PetscInt));
203: ptr[j] = sbuf1[j] + 2*w3[j] + 1;
204: }
205:
206: /* Parse the isrow and copy data into outbuf */
207: for (i=0; i<ismax; i++) {
208: PetscMemzero(ctr,size*sizeof(PetscInt));
209: irow_i = irow[i];
210: jmax = nrow[i];
211: for (j=0; j<jmax; j++) { /* parse the indices of each IS */
212: row = irow_i[j];
213: proc = rtable[row];
214: if (proc != rank) { /* copy to the outgoing buf*/
215: ctr[proc]++;
216: *ptr[proc] = row;
217: ptr[proc]++;
218: }
219: }
220: /* Update the headers for the current IS */
221: for (j=0; j<size; j++) { /* Can Optimise this loop too */
222: if ((ctr_j = ctr[j])) {
223: sbuf1_j = sbuf1[j];
224: k = ++sbuf1_j[0];
225: sbuf1_j[2*k] = ctr_j;
226: sbuf1_j[2*k-1] = i;
227: }
228: }
229: }
231: /* Now post the sends */
232: PetscMalloc((nrqs+1)*sizeof(MPI_Request),&s_waits1);
233: for (i=0; i<nrqs; ++i) {
234: j = pa[i];
235: MPI_Isend(sbuf1[j],w1[2*j],MPIU_INT,j,tag0,comm,s_waits1+i);
236: }
238: /* Post recieves to capture the row_data from other procs */
239: PetscMalloc((nrqs+1)*sizeof(MPI_Request),&r_waits2);
240: PetscMalloc((nrqs+1)*sizeof(PetscScalar*),&rbuf2);
241: for (i=0; i<nrqs; i++) {
242: j = pa[i];
243: count = (w1[2*j] - (2*sbuf1[j][0] + 1))*N;
244: PetscMalloc((count+1)*sizeof(PetscScalar),&rbuf2[i]);
245: MPI_Irecv(rbuf2[i],count,MPIU_SCALAR,j,tag1,comm,r_waits2+i);
246: }
248: /* Receive messages(row_nos) and then, pack and send off the rowvalues
249: to the correct processors */
251: PetscMalloc((nrqr+1)*sizeof(MPI_Request),&s_waits2);
252: PetscMalloc((nrqr+1)*sizeof(MPI_Status),&r_status1);
253: PetscMalloc((nrqr+1)*sizeof(PetscScalar*),&sbuf2);
254:
255: {
256: PetscScalar *sbuf2_i,*v_start;
257: PetscInt s_proc;
258: for (i=0; i<nrqr; ++i) {
259: MPI_Waitany(nrqr,r_waits1,&idex,r_status1+i);
260: s_proc = r_status1[i].MPI_SOURCE; /* send processor */
261: rbuf1_i = rbuf1[idex]; /* Actual message from s_proc */
262: /* no of rows = end - start; since start is array idex[], 0idex, whel end
263: is length of the buffer - which is 1idex */
264: start = 2*rbuf1_i[0] + 1;
265: MPI_Get_count(r_status1+i,MPIU_INT,&end);
266: /* allocate memory sufficinet to hold all the row values */
267: PetscMalloc((end-start)*N*sizeof(PetscScalar),&sbuf2[idex]);
268: sbuf2_i = sbuf2[idex];
269: /* Now pack the data */
270: for (j=start; j<end; j++) {
271: row = rbuf1_i[j] - rstart;
272: v_start = a->v + row;
273: for (k=0; k<N; k++) {
274: sbuf2_i[0] = v_start[0];
275: sbuf2_i++; v_start += C->rmap->n;
276: }
277: }
278: /* Now send off the data */
279: MPI_Isend(sbuf2[idex],(end-start)*N,MPIU_SCALAR,s_proc,tag1,comm,s_waits2+i);
280: }
281: }
282: /* End Send-Recv of IS + row_numbers */
283: PetscFree(r_status1);
284: PetscFree(r_waits1);
285: PetscMalloc((nrqs+1)*sizeof(MPI_Status),&s_status1);
286: if (nrqs) {MPI_Waitall(nrqs,s_waits1,s_status1);}
287: PetscFree(s_status1);
288: PetscFree(s_waits1);
290: /* Create the submatrices */
291: if (scall == MAT_REUSE_MATRIX) {
292: for (i=0; i<ismax; i++) {
293: mat = (Mat_SeqDense *)(submats[i]->data);
294: 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");
295: PetscMemzero(mat->v,submats[i]->rmap->n*submats[i]->cmap->n*sizeof(PetscScalar));
296: submats[i]->factortype = C->factortype;
297: }
298: } else {
299: for (i=0; i<ismax; i++) {
300: MatCreate(PETSC_COMM_SELF,submats+i);
301: MatSetSizes(submats[i],nrow[i],ncol[i],nrow[i],ncol[i]);
302: MatSetType(submats[i],((PetscObject)A)->type_name);
303: MatSeqDenseSetPreallocation(submats[i],PETSC_NULL);
304: }
305: }
306:
307: /* Assemble the matrices */
308: {
309: PetscInt col;
310: PetscScalar *imat_v,*mat_v,*imat_vi,*mat_vi;
311:
312: for (i=0; i<ismax; i++) {
313: mat = (Mat_SeqDense*)submats[i]->data;
314: mat_v = a->v;
315: imat_v = mat->v;
316: irow_i = irow[i];
317: m = nrow[i];
318: for (j=0; j<m; j++) {
319: row = irow_i[j] ;
320: proc = rtable[row];
321: if (proc == rank) {
322: row = row - rstart;
323: mat_vi = mat_v + row;
324: imat_vi = imat_v + j;
325: for (k=0; k<ncol[i]; k++) {
326: col = icol[i][k];
327: imat_vi[k*m] = mat_vi[col*C->rmap->n];
328: }
329: }
330: }
331: }
332: }
334: /* Create row map-> This maps c->row to submat->row for each submat*/
335: /* this is a very expensive operation wrt memory usage */
336: PetscMalloc(ismax*sizeof(PetscInt*),&rmap);
337: PetscMalloc(ismax*C->rmap->N*sizeof(PetscInt),&rmap[0]);
338: PetscMemzero(rmap[0],ismax*C->rmap->N*sizeof(PetscInt));
339: for (i=1; i<ismax; i++) { rmap[i] = rmap[i-1] + C->rmap->N;}
340: for (i=0; i<ismax; i++) {
341: rmap_i = rmap[i];
342: irow_i = irow[i];
343: jmax = nrow[i];
344: for (j=0; j<jmax; j++) {
345: rmap_i[irow_i[j]] = j;
346: }
347: }
348:
349: /* Now Receive the row_values and assemble the rest of the matrix */
350: PetscMalloc((nrqs+1)*sizeof(MPI_Status),&r_status2);
351: {
352: PetscInt is_max,tmp1,col,*sbuf1_i,is_sz;
353: PetscScalar *rbuf2_i,*imat_v,*imat_vi;
354:
355: for (tmp1=0; tmp1<nrqs; tmp1++) { /* For each message */
356: MPI_Waitany(nrqs,r_waits2,&i,r_status2+tmp1);
357: /* Now dig out the corresponding sbuf1, which contains the IS data_structure */
358: sbuf1_i = sbuf1[pa[i]];
359: is_max = sbuf1_i[0];
360: ct1 = 2*is_max+1;
361: rbuf2_i = rbuf2[i];
362: for (j=1; j<=is_max; j++) { /* For each IS belonging to the message */
363: is_no = sbuf1_i[2*j-1];
364: is_sz = sbuf1_i[2*j];
365: mat = (Mat_SeqDense*)submats[is_no]->data;
366: imat_v = mat->v;
367: rmap_i = rmap[is_no];
368: m = nrow[is_no];
369: for (k=0; k<is_sz; k++,rbuf2_i+=N) { /* For each row */
370: row = sbuf1_i[ct1]; ct1++;
371: row = rmap_i[row];
372: imat_vi = imat_v + row;
373: for (l=0; l<ncol[is_no]; l++) { /* For each col */
374: col = icol[is_no][l];
375: imat_vi[l*m] = rbuf2_i[col];
376: }
377: }
378: }
379: }
380: }
381: /* End Send-Recv of row_values */
382: PetscFree(r_status2);
383: PetscFree(r_waits2);
384: PetscMalloc((nrqr+1)*sizeof(MPI_Status),&s_status2);
385: if (nrqr) {MPI_Waitall(nrqr,s_waits2,s_status2);}
386: PetscFree(s_status2);
387: PetscFree(s_waits2);
389: /* Restore the indices */
390: for (i=0; i<ismax; i++) {
391: ISRestoreIndices(isrow[i],irow+i);
392: ISRestoreIndices(iscol[i],icol+i);
393: }
395: /* Destroy allocated memory */
396: PetscFree5(irow,icol,nrow,ncol,rtable);
397: PetscFree3(w1,w3,w4);
398: PetscFree(pa);
400: for (i=0; i<nrqs; ++i) {
401: PetscFree(rbuf2[i]);
402: }
403: PetscFree(rbuf2);
404: PetscFree4(sbuf1,ptr,tmp,ctr);
405: PetscFree(rbuf1[0]);
406: PetscFree(rbuf1);
408: for (i=0; i<nrqr; ++i) {
409: PetscFree(sbuf2[i]);
410: }
412: PetscFree(sbuf2);
413: PetscFree(rmap[0]);
414: PetscFree(rmap);
416: for (i=0; i<ismax; i++) {
417: MatAssemblyBegin(submats[i],MAT_FINAL_ASSEMBLY);
418: MatAssemblyEnd(submats[i],MAT_FINAL_ASSEMBLY);
419: }
421: return(0);
422: }
426: PetscErrorCode MatScale_MPIDense(Mat inA,PetscScalar alpha)
427: {
428: Mat_MPIDense *A = (Mat_MPIDense*)inA->data;
429: Mat_SeqDense *a = (Mat_SeqDense*)A->A->data;
430: PetscScalar oalpha = alpha;
432: PetscBLASInt one = 1,nz = PetscBLASIntCast(inA->rmap->n*inA->cmap->N);
435: BLASscal_(&nz,&oalpha,a->v,&one);
436: PetscLogFlops(nz);
437: return(0);
438: }