1 2 /* 3 Support for the parallel dense matrix vector multiply 4 */ 5 #include <../src/mat/impls/dense/mpi/mpidense.h> 6 #include <petscblaslapack.h> 7 8 PetscErrorCode MatSetUpMultiply_MPIDense(Mat mat) 9 { 10 Mat_MPIDense *mdn = (Mat_MPIDense *)mat->data; 11 12 PetscFunctionBegin; 13 if (!mdn->Mvctx) { 14 /* Create local vector that is used to scatter into */ 15 PetscCall(VecDestroy(&mdn->lvec)); 16 if (mdn->A) { PetscCall(MatCreateVecs(mdn->A, &mdn->lvec, NULL)); } 17 PetscCall(PetscLayoutSetUp(mat->cmap)); 18 PetscCall(PetscSFCreate(PetscObjectComm((PetscObject)mat), &mdn->Mvctx)); 19 PetscCall(PetscSFSetGraphWithPattern(mdn->Mvctx, mat->cmap, PETSCSF_PATTERN_ALLGATHER)); 20 } 21 PetscFunctionReturn(PETSC_SUCCESS); 22 } 23 24 static PetscErrorCode MatCreateSubMatrices_MPIDense_Local(Mat, PetscInt, const IS[], const IS[], MatReuse, Mat *); 25 26 PetscErrorCode MatCreateSubMatrices_MPIDense(Mat C, PetscInt ismax, const IS isrow[], const IS iscol[], MatReuse scall, Mat *submat[]) 27 { 28 PetscInt nmax, nstages_local, nstages, i, pos, max_no; 29 30 PetscFunctionBegin; 31 /* Allocate memory to hold all the submatrices */ 32 if (scall != MAT_REUSE_MATRIX) PetscCall(PetscCalloc1(ismax + 1, submat)); 33 /* Determine the number of stages through which submatrices are done */ 34 nmax = 20 * 1000000 / (C->cmap->N * sizeof(PetscInt)); 35 if (!nmax) nmax = 1; 36 nstages_local = ismax / nmax + ((ismax % nmax) ? 1 : 0); 37 38 /* Make sure every processor loops through the nstages */ 39 PetscCall(MPIU_Allreduce(&nstages_local, &nstages, 1, MPIU_INT, MPI_MAX, PetscObjectComm((PetscObject)C))); 40 41 for (i = 0, pos = 0; i < nstages; i++) { 42 if (pos + nmax <= ismax) max_no = nmax; 43 else if (pos == ismax) max_no = 0; 44 else max_no = ismax - pos; 45 PetscCall(MatCreateSubMatrices_MPIDense_Local(C, max_no, isrow + pos, iscol + pos, scall, *submat + pos)); 46 pos += max_no; 47 } 48 PetscFunctionReturn(PETSC_SUCCESS); 49 } 50 /* -------------------------------------------------------------------------*/ 51 PetscErrorCode MatCreateSubMatrices_MPIDense_Local(Mat C, PetscInt ismax, const IS isrow[], const IS iscol[], MatReuse scall, Mat *submats) 52 { 53 Mat_MPIDense *c = (Mat_MPIDense *)C->data; 54 Mat A = c->A; 55 Mat_SeqDense *a = (Mat_SeqDense *)A->data, *mat; 56 PetscMPIInt rank, size, tag0, tag1, idex, end, i; 57 PetscInt N = C->cmap->N, rstart = C->rmap->rstart, count; 58 const PetscInt **irow, **icol, *irow_i; 59 PetscInt *nrow, *ncol, *w1, *w3, *w4, *rtable, start; 60 PetscInt **sbuf1, m, j, k, l, ct1, **rbuf1, row, proc; 61 PetscInt nrqs, msz, **ptr, *ctr, *pa, *tmp, bsz, nrqr; 62 PetscInt is_no, jmax, **rmap, *rmap_i; 63 PetscInt ctr_j, *sbuf1_j, *rbuf1_i; 64 MPI_Request *s_waits1, *r_waits1, *s_waits2, *r_waits2; 65 MPI_Status *r_status1, *r_status2, *s_status1, *s_status2; 66 MPI_Comm comm; 67 PetscScalar **rbuf2, **sbuf2; 68 PetscBool sorted; 69 70 PetscFunctionBegin; 71 PetscCall(PetscObjectGetComm((PetscObject)C, &comm)); 72 tag0 = ((PetscObject)C)->tag; 73 PetscCallMPI(MPI_Comm_rank(comm, &rank)); 74 PetscCallMPI(MPI_Comm_size(comm, &size)); 75 m = C->rmap->N; 76 77 /* Get some new tags to keep the communication clean */ 78 PetscCall(PetscObjectGetNewTag((PetscObject)C, &tag1)); 79 80 /* Check if the col indices are sorted */ 81 for (i = 0; i < ismax; i++) { 82 PetscCall(ISSorted(isrow[i], &sorted)); 83 PetscCheck(sorted, PETSC_COMM_SELF, PETSC_ERR_ARG_WRONGSTATE, "ISrow is not sorted"); 84 PetscCall(ISSorted(iscol[i], &sorted)); 85 PetscCheck(sorted, PETSC_COMM_SELF, PETSC_ERR_ARG_WRONGSTATE, "IScol is not sorted"); 86 } 87 88 PetscCall(PetscMalloc5(ismax, (PetscInt ***)&irow, ismax, (PetscInt ***)&icol, ismax, &nrow, ismax, &ncol, m, &rtable)); 89 for (i = 0; i < ismax; i++) { 90 PetscCall(ISGetIndices(isrow[i], &irow[i])); 91 PetscCall(ISGetIndices(iscol[i], &icol[i])); 92 PetscCall(ISGetLocalSize(isrow[i], &nrow[i])); 93 PetscCall(ISGetLocalSize(iscol[i], &ncol[i])); 94 } 95 96 /* Create hash table for the mapping :row -> proc*/ 97 for (i = 0, j = 0; i < size; i++) { 98 jmax = C->rmap->range[i + 1]; 99 for (; j < jmax; j++) rtable[j] = i; 100 } 101 102 /* evaluate communication - mesg to who,length of mesg, and buffer space 103 required. Based on this, buffers are allocated, and data copied into them*/ 104 PetscCall(PetscMalloc3(2 * size, &w1, size, &w3, size, &w4)); 105 PetscCall(PetscArrayzero(w1, size * 2)); /* initialize work vector*/ 106 PetscCall(PetscArrayzero(w3, size)); /* initialize work vector*/ 107 for (i = 0; i < ismax; i++) { 108 PetscCall(PetscArrayzero(w4, size)); /* initialize work vector*/ 109 jmax = nrow[i]; 110 irow_i = irow[i]; 111 for (j = 0; j < jmax; j++) { 112 row = irow_i[j]; 113 proc = rtable[row]; 114 w4[proc]++; 115 } 116 for (j = 0; j < size; j++) { 117 if (w4[j]) { 118 w1[2 * j] += w4[j]; 119 w3[j]++; 120 } 121 } 122 } 123 124 nrqs = 0; /* no of outgoing messages */ 125 msz = 0; /* total mesg length (for all procs) */ 126 w1[2 * rank] = 0; /* no mesg sent to self */ 127 w3[rank] = 0; 128 for (i = 0; i < size; i++) { 129 if (w1[2 * i]) { 130 w1[2 * i + 1] = 1; 131 nrqs++; 132 } /* there exists a message to proc i */ 133 } 134 PetscCall(PetscMalloc1(nrqs + 1, &pa)); /*(proc -array)*/ 135 for (i = 0, j = 0; i < size; i++) { 136 if (w1[2 * i]) { 137 pa[j] = i; 138 j++; 139 } 140 } 141 142 /* Each message would have a header = 1 + 2*(no of IS) + data */ 143 for (i = 0; i < nrqs; i++) { 144 j = pa[i]; 145 w1[2 * j] += w1[2 * j + 1] + 2 * w3[j]; 146 msz += w1[2 * j]; 147 } 148 /* Do a global reduction to determine how many messages to expect*/ 149 PetscCall(PetscMaxSum(comm, w1, &bsz, &nrqr)); 150 151 /* Allocate memory for recv buffers . Make sure rbuf1[0] exists by adding 1 to the buffer length */ 152 PetscCall(PetscMalloc1(nrqr + 1, &rbuf1)); 153 PetscCall(PetscMalloc1(nrqr * bsz, &rbuf1[0])); 154 for (i = 1; i < nrqr; ++i) rbuf1[i] = rbuf1[i - 1] + bsz; 155 156 /* Post the receives */ 157 PetscCall(PetscMalloc1(nrqr + 1, &r_waits1)); 158 for (i = 0; i < nrqr; ++i) PetscCallMPI(MPI_Irecv(rbuf1[i], bsz, MPIU_INT, MPI_ANY_SOURCE, tag0, comm, r_waits1 + i)); 159 160 /* Allocate Memory for outgoing messages */ 161 PetscCall(PetscMalloc4(size, &sbuf1, size, &ptr, 2 * msz, &tmp, size, &ctr)); 162 PetscCall(PetscArrayzero(sbuf1, size)); 163 PetscCall(PetscArrayzero(ptr, size)); 164 { 165 PetscInt *iptr = tmp, ict = 0; 166 for (i = 0; i < nrqs; i++) { 167 j = pa[i]; 168 iptr += ict; 169 sbuf1[j] = iptr; 170 ict = w1[2 * j]; 171 } 172 } 173 174 /* Form the outgoing messages */ 175 /* Initialize the header space */ 176 for (i = 0; i < nrqs; i++) { 177 j = pa[i]; 178 sbuf1[j][0] = 0; 179 PetscCall(PetscArrayzero(sbuf1[j] + 1, 2 * w3[j])); 180 ptr[j] = sbuf1[j] + 2 * w3[j] + 1; 181 } 182 183 /* Parse the isrow and copy data into outbuf */ 184 for (i = 0; i < ismax; i++) { 185 PetscCall(PetscArrayzero(ctr, size)); 186 irow_i = irow[i]; 187 jmax = nrow[i]; 188 for (j = 0; j < jmax; j++) { /* parse the indices of each IS */ 189 row = irow_i[j]; 190 proc = rtable[row]; 191 if (proc != rank) { /* copy to the outgoing buf*/ 192 ctr[proc]++; 193 *ptr[proc] = row; 194 ptr[proc]++; 195 } 196 } 197 /* Update the headers for the current IS */ 198 for (j = 0; j < size; j++) { /* Can Optimise this loop too */ 199 if ((ctr_j = ctr[j])) { 200 sbuf1_j = sbuf1[j]; 201 k = ++sbuf1_j[0]; 202 sbuf1_j[2 * k] = ctr_j; 203 sbuf1_j[2 * k - 1] = i; 204 } 205 } 206 } 207 208 /* Now post the sends */ 209 PetscCall(PetscMalloc1(nrqs + 1, &s_waits1)); 210 for (i = 0; i < nrqs; ++i) { 211 j = pa[i]; 212 PetscCallMPI(MPI_Isend(sbuf1[j], w1[2 * j], MPIU_INT, j, tag0, comm, s_waits1 + i)); 213 } 214 215 /* Post receives to capture the row_data from other procs */ 216 PetscCall(PetscMalloc1(nrqs + 1, &r_waits2)); 217 PetscCall(PetscMalloc1(nrqs + 1, &rbuf2)); 218 for (i = 0; i < nrqs; i++) { 219 j = pa[i]; 220 count = (w1[2 * j] - (2 * sbuf1[j][0] + 1)) * N; 221 PetscCall(PetscMalloc1(count + 1, &rbuf2[i])); 222 PetscCallMPI(MPI_Irecv(rbuf2[i], count, MPIU_SCALAR, j, tag1, comm, r_waits2 + i)); 223 } 224 225 /* Receive messages(row_nos) and then, pack and send off the rowvalues 226 to the correct processors */ 227 228 PetscCall(PetscMalloc1(nrqr + 1, &s_waits2)); 229 PetscCall(PetscMalloc1(nrqr + 1, &r_status1)); 230 PetscCall(PetscMalloc1(nrqr + 1, &sbuf2)); 231 232 { 233 PetscScalar *sbuf2_i, *v_start; 234 PetscInt s_proc; 235 for (i = 0; i < nrqr; ++i) { 236 PetscCallMPI(MPI_Waitany(nrqr, r_waits1, &idex, r_status1 + i)); 237 s_proc = r_status1[i].MPI_SOURCE; /* send processor */ 238 rbuf1_i = rbuf1[idex]; /* Actual message from s_proc */ 239 /* no of rows = end - start; since start is array idex[], 0idex, whel end 240 is length of the buffer - which is 1idex */ 241 start = 2 * rbuf1_i[0] + 1; 242 PetscCallMPI(MPI_Get_count(r_status1 + i, MPIU_INT, &end)); 243 /* allocate memory sufficinet to hold all the row values */ 244 PetscCall(PetscMalloc1((end - start) * N, &sbuf2[idex])); 245 sbuf2_i = sbuf2[idex]; 246 /* Now pack the data */ 247 for (j = start; j < end; j++) { 248 row = rbuf1_i[j] - rstart; 249 v_start = a->v + row; 250 for (k = 0; k < N; k++) { 251 sbuf2_i[0] = v_start[0]; 252 sbuf2_i++; 253 v_start += a->lda; 254 } 255 } 256 /* Now send off the data */ 257 PetscCallMPI(MPI_Isend(sbuf2[idex], (end - start) * N, MPIU_SCALAR, s_proc, tag1, comm, s_waits2 + i)); 258 } 259 } 260 /* End Send-Recv of IS + row_numbers */ 261 PetscCall(PetscFree(r_status1)); 262 PetscCall(PetscFree(r_waits1)); 263 PetscCall(PetscMalloc1(nrqs + 1, &s_status1)); 264 if (nrqs) PetscCallMPI(MPI_Waitall(nrqs, s_waits1, s_status1)); 265 PetscCall(PetscFree(s_status1)); 266 PetscCall(PetscFree(s_waits1)); 267 268 /* Create the submatrices */ 269 if (scall == MAT_REUSE_MATRIX) { 270 for (i = 0; i < ismax; i++) { 271 mat = (Mat_SeqDense *)(submats[i]->data); 272 PetscCheck(!(submats[i]->rmap->n != nrow[i]) && !(submats[i]->cmap->n != ncol[i]), PETSC_COMM_SELF, PETSC_ERR_ARG_SIZ, "Cannot reuse matrix. wrong size"); 273 PetscCall(PetscArrayzero(mat->v, submats[i]->rmap->n * submats[i]->cmap->n)); 274 275 submats[i]->factortype = C->factortype; 276 } 277 } else { 278 for (i = 0; i < ismax; i++) { 279 PetscCall(MatCreate(PETSC_COMM_SELF, submats + i)); 280 PetscCall(MatSetSizes(submats[i], nrow[i], ncol[i], nrow[i], ncol[i])); 281 PetscCall(MatSetType(submats[i], ((PetscObject)A)->type_name)); 282 PetscCall(MatSeqDenseSetPreallocation(submats[i], NULL)); 283 } 284 } 285 286 /* Assemble the matrices */ 287 { 288 PetscInt col; 289 PetscScalar *imat_v, *mat_v, *imat_vi, *mat_vi; 290 291 for (i = 0; i < ismax; i++) { 292 mat = (Mat_SeqDense *)submats[i]->data; 293 mat_v = a->v; 294 imat_v = mat->v; 295 irow_i = irow[i]; 296 m = nrow[i]; 297 for (j = 0; j < m; j++) { 298 row = irow_i[j]; 299 proc = rtable[row]; 300 if (proc == rank) { 301 row = row - rstart; 302 mat_vi = mat_v + row; 303 imat_vi = imat_v + j; 304 for (k = 0; k < ncol[i]; k++) { 305 col = icol[i][k]; 306 imat_vi[k * m] = mat_vi[col * a->lda]; 307 } 308 } 309 } 310 } 311 } 312 313 /* Create row map-> This maps c->row to submat->row for each submat*/ 314 /* this is a very expensive operation wrt memory usage */ 315 PetscCall(PetscMalloc1(ismax, &rmap)); 316 PetscCall(PetscCalloc1(ismax * C->rmap->N, &rmap[0])); 317 for (i = 1; i < ismax; i++) rmap[i] = rmap[i - 1] + C->rmap->N; 318 for (i = 0; i < ismax; i++) { 319 rmap_i = rmap[i]; 320 irow_i = irow[i]; 321 jmax = nrow[i]; 322 for (j = 0; j < jmax; j++) rmap_i[irow_i[j]] = j; 323 } 324 325 /* Now Receive the row_values and assemble the rest of the matrix */ 326 PetscCall(PetscMalloc1(nrqs + 1, &r_status2)); 327 { 328 PetscInt is_max, tmp1, col, *sbuf1_i, is_sz; 329 PetscScalar *rbuf2_i, *imat_v, *imat_vi; 330 331 for (tmp1 = 0; tmp1 < nrqs; tmp1++) { /* For each message */ 332 PetscCallMPI(MPI_Waitany(nrqs, r_waits2, &i, r_status2 + tmp1)); 333 /* Now dig out the corresponding sbuf1, which contains the IS data_structure */ 334 sbuf1_i = sbuf1[pa[i]]; 335 is_max = sbuf1_i[0]; 336 ct1 = 2 * is_max + 1; 337 rbuf2_i = rbuf2[i]; 338 for (j = 1; j <= is_max; j++) { /* For each IS belonging to the message */ 339 is_no = sbuf1_i[2 * j - 1]; 340 is_sz = sbuf1_i[2 * j]; 341 mat = (Mat_SeqDense *)submats[is_no]->data; 342 imat_v = mat->v; 343 rmap_i = rmap[is_no]; 344 m = nrow[is_no]; 345 for (k = 0; k < is_sz; k++, rbuf2_i += N) { /* For each row */ 346 row = sbuf1_i[ct1]; 347 ct1++; 348 row = rmap_i[row]; 349 imat_vi = imat_v + row; 350 for (l = 0; l < ncol[is_no]; l++) { /* For each col */ 351 col = icol[is_no][l]; 352 imat_vi[l * m] = rbuf2_i[col]; 353 } 354 } 355 } 356 } 357 } 358 /* End Send-Recv of row_values */ 359 PetscCall(PetscFree(r_status2)); 360 PetscCall(PetscFree(r_waits2)); 361 PetscCall(PetscMalloc1(nrqr + 1, &s_status2)); 362 if (nrqr) PetscCallMPI(MPI_Waitall(nrqr, s_waits2, s_status2)); 363 PetscCall(PetscFree(s_status2)); 364 PetscCall(PetscFree(s_waits2)); 365 366 /* Restore the indices */ 367 for (i = 0; i < ismax; i++) { 368 PetscCall(ISRestoreIndices(isrow[i], irow + i)); 369 PetscCall(ISRestoreIndices(iscol[i], icol + i)); 370 } 371 372 PetscCall(PetscFree5(*(PetscInt ***)&irow, *(PetscInt ***)&icol, nrow, ncol, rtable)); 373 PetscCall(PetscFree3(w1, w3, w4)); 374 PetscCall(PetscFree(pa)); 375 376 for (i = 0; i < nrqs; ++i) PetscCall(PetscFree(rbuf2[i])); 377 PetscCall(PetscFree(rbuf2)); 378 PetscCall(PetscFree4(sbuf1, ptr, tmp, ctr)); 379 PetscCall(PetscFree(rbuf1[0])); 380 PetscCall(PetscFree(rbuf1)); 381 382 for (i = 0; i < nrqr; ++i) PetscCall(PetscFree(sbuf2[i])); 383 384 PetscCall(PetscFree(sbuf2)); 385 PetscCall(PetscFree(rmap[0])); 386 PetscCall(PetscFree(rmap)); 387 388 for (i = 0; i < ismax; i++) { 389 PetscCall(MatAssemblyBegin(submats[i], MAT_FINAL_ASSEMBLY)); 390 PetscCall(MatAssemblyEnd(submats[i], MAT_FINAL_ASSEMBLY)); 391 } 392 PetscFunctionReturn(PETSC_SUCCESS); 393 } 394 395 PETSC_INTERN PetscErrorCode MatScale_MPIDense(Mat inA, PetscScalar alpha) 396 { 397 Mat_MPIDense *A = (Mat_MPIDense *)inA->data; 398 399 PetscFunctionBegin; 400 PetscCall(MatScale(A->A, alpha)); 401 PetscFunctionReturn(PETSC_SUCCESS); 402 } 403