1 /* 2 Defines the basic matrix operations for the SELL matrix storage format. 3 */ 4 #include <../src/mat/impls/sell/seq/sell.h> /*I "petscmat.h" I*/ 5 #include <petscblaslapack.h> 6 #include <petsc/private/kernels/blocktranspose.h> 7 8 static PetscBool cited = PETSC_FALSE; 9 static const char citation[] = "@inproceedings{ZhangELLPACK2018,\n" 10 " author = {Hong Zhang and Richard T. Mills and Karl Rupp and Barry F. Smith},\n" 11 " title = {Vectorized Parallel Sparse Matrix-Vector Multiplication in {PETSc} Using {AVX-512}},\n" 12 " booktitle = {Proceedings of the 47th International Conference on Parallel Processing},\n" 13 " year = 2018\n" 14 "}\n"; 15 16 #if defined(PETSC_HAVE_IMMINTRIN_H) && (defined(__AVX512F__) || (defined(__AVX2__) && defined(__FMA__)) || defined(__AVX__)) && defined(PETSC_USE_REAL_DOUBLE) && !defined(PETSC_USE_COMPLEX) && !defined(PETSC_USE_64BIT_INDICES) 17 18 #include <immintrin.h> 19 20 #if !defined(_MM_SCALE_8) 21 #define _MM_SCALE_8 8 22 #endif 23 24 #if defined(__AVX512F__) 25 /* these do not work 26 vec_idx = _mm512_loadunpackhi_epi32(vec_idx,acolidx); 27 vec_vals = _mm512_loadunpackhi_pd(vec_vals,aval); 28 */ 29 #define AVX512_Mult_Private(vec_idx, vec_x, vec_vals, vec_y) \ 30 /* if the mask bit is set, copy from acolidx, otherwise from vec_idx */ \ 31 vec_idx = _mm256_loadu_si256((__m256i const *)acolidx); \ 32 vec_vals = _mm512_loadu_pd(aval); \ 33 vec_x = _mm512_i32gather_pd(vec_idx, x, _MM_SCALE_8); \ 34 vec_y = _mm512_fmadd_pd(vec_x, vec_vals, vec_y) 35 #elif defined(__AVX2__) && defined(__FMA__) 36 #define AVX2_Mult_Private(vec_idx, vec_x, vec_vals, vec_y) \ 37 vec_vals = _mm256_loadu_pd(aval); \ 38 vec_idx = _mm_loadu_si128((__m128i const *)acolidx); /* SSE2 */ \ 39 vec_x = _mm256_i32gather_pd(x, vec_idx, _MM_SCALE_8); \ 40 vec_y = _mm256_fmadd_pd(vec_x, vec_vals, vec_y) 41 #endif 42 #endif /* PETSC_HAVE_IMMINTRIN_H */ 43 44 /*@C 45 MatSeqSELLSetPreallocation - For good matrix assembly performance 46 the user should preallocate the matrix storage by setting the parameter `nz` 47 (or the array `nnz`). 48 49 Collective 50 51 Input Parameters: 52 + B - The `MATSEQSELL` matrix 53 . rlenmax - number of nonzeros per row (same for all rows), ignored if `rlen` is provided 54 - rlen - array containing the number of nonzeros in the various rows (possibly different for each row) or `NULL` 55 56 Level: intermediate 57 58 Notes: 59 Specify the preallocated storage with either `rlenmax` or `rlen` (not both). 60 Set `rlenmax` = `PETSC_DEFAULT` and `rlen` = `NULL` for PETSc to control dynamic memory 61 allocation. 62 63 You can call `MatGetInfo()` to get information on how effective the preallocation was; 64 for example the fields mallocs,nz_allocated,nz_used,nz_unneeded; 65 You can also run with the option `-info` and look for messages with the string 66 malloc in them to see if additional memory allocation was needed. 67 68 Developer Notes: 69 Use `rlenmax` of `MAT_SKIP_ALLOCATION` to not allocate any space for the matrix 70 entries or columns indices. 71 72 The maximum number of nonzeos in any row should be as accurate as possible. 73 If it is underestimated, you will get bad performance due to reallocation 74 (`MatSeqXSELLReallocateSELL()`). 75 76 .seealso: `Mat`, `MATSEQSELL`, `MATSELL`, `MatCreate()`, `MatCreateSELL()`, `MatSetValues()`, `MatGetInfo()` 77 @*/ 78 PetscErrorCode MatSeqSELLSetPreallocation(Mat B, PetscInt rlenmax, const PetscInt rlen[]) 79 { 80 PetscFunctionBegin; 81 PetscValidHeaderSpecific(B, MAT_CLASSID, 1); 82 PetscValidType(B, 1); 83 PetscTryMethod(B, "MatSeqSELLSetPreallocation_C", (Mat, PetscInt, const PetscInt[]), (B, rlenmax, rlen)); 84 PetscFunctionReturn(PETSC_SUCCESS); 85 } 86 87 PetscErrorCode MatSeqSELLSetPreallocation_SeqSELL(Mat B, PetscInt maxallocrow, const PetscInt rlen[]) 88 { 89 Mat_SeqSELL *b; 90 PetscInt i, j, totalslices; 91 #if defined(PETSC_HAVE_CUPM) 92 PetscInt rlenmax = 0; 93 #endif 94 PetscBool skipallocation = PETSC_FALSE, realalloc = PETSC_FALSE; 95 96 PetscFunctionBegin; 97 if (maxallocrow >= 0 || rlen) realalloc = PETSC_TRUE; 98 if (maxallocrow == MAT_SKIP_ALLOCATION) { 99 skipallocation = PETSC_TRUE; 100 maxallocrow = 0; 101 } 102 103 PetscCall(PetscLayoutSetUp(B->rmap)); 104 PetscCall(PetscLayoutSetUp(B->cmap)); 105 106 /* FIXME: if one preallocates more space than needed, the matrix does not shrink automatically, but for best performance it should */ 107 if (maxallocrow == PETSC_DEFAULT || maxallocrow == PETSC_DECIDE) maxallocrow = 5; 108 PetscCheck(maxallocrow >= 0, PETSC_COMM_SELF, PETSC_ERR_ARG_OUTOFRANGE, "maxallocrow cannot be less than 0: value %" PetscInt_FMT, maxallocrow); 109 if (rlen) { 110 for (i = 0; i < B->rmap->n; i++) { 111 PetscCheck(rlen[i] >= 0, PETSC_COMM_SELF, PETSC_ERR_ARG_OUTOFRANGE, "rlen cannot be less than 0: local row %" PetscInt_FMT " value %" PetscInt_FMT, i, rlen[i]); 112 PetscCheck(rlen[i] <= B->cmap->n, PETSC_COMM_SELF, PETSC_ERR_ARG_OUTOFRANGE, "rlen cannot be greater than row length: local row %" PetscInt_FMT " value %" PetscInt_FMT " rowlength %" PetscInt_FMT, i, rlen[i], B->cmap->n); 113 } 114 } 115 116 B->preallocated = PETSC_TRUE; 117 118 b = (Mat_SeqSELL *)B->data; 119 120 if (!b->sliceheight) { /* not set yet */ 121 #if defined(PETSC_HAVE_CUPM) 122 b->sliceheight = 16; 123 #else 124 b->sliceheight = 8; 125 #endif 126 } 127 totalslices = PetscCeilInt(B->rmap->n, b->sliceheight); 128 b->totalslices = totalslices; 129 if (!skipallocation) { 130 if (B->rmap->n % b->sliceheight) PetscCall(PetscInfo(B, "Padding rows to the SEQSELL matrix because the number of rows is not the multiple of the slice height (value %" PetscInt_FMT ")\n", B->rmap->n)); 131 132 if (!b->sliidx) { /* sliidx gives the starting index of each slice, the last element is the total space allocated */ 133 PetscCall(PetscMalloc1(totalslices + 1, &b->sliidx)); 134 } 135 if (!rlen) { /* if rlen is not provided, allocate same space for all the slices */ 136 if (maxallocrow == PETSC_DEFAULT || maxallocrow == PETSC_DECIDE) maxallocrow = 10; 137 else if (maxallocrow < 0) maxallocrow = 1; 138 #if defined(PETSC_HAVE_CUPM) 139 rlenmax = maxallocrow; 140 /* Pad the slice to DEVICE_MEM_ALIGN */ 141 while (b->sliceheight * maxallocrow % DEVICE_MEM_ALIGN) maxallocrow++; 142 #endif 143 for (i = 0; i <= totalslices; i++) b->sliidx[i] = b->sliceheight * i * maxallocrow; 144 } else { 145 #if defined(PETSC_HAVE_CUPM) 146 PetscInt mul = DEVICE_MEM_ALIGN / b->sliceheight; 147 #endif 148 maxallocrow = 0; 149 b->sliidx[0] = 0; 150 for (i = 1; i < totalslices; i++) { 151 b->sliidx[i] = 0; 152 for (j = 0; j < b->sliceheight; j++) { b->sliidx[i] = PetscMax(b->sliidx[i], rlen[b->sliceheight * (i - 1) + j]); } 153 #if defined(PETSC_HAVE_CUPM) 154 if (mul != 0) { /* Pad the slice to DEVICE_MEM_ALIGN if sliceheight < DEVICE_MEM_ALIGN */ 155 rlenmax = PetscMax(b->sliidx[i], rlenmax); 156 b->sliidx[i] = ((b->sliidx[i] - 1) / mul + 1) * mul; 157 } 158 #endif 159 maxallocrow = PetscMax(b->sliidx[i], maxallocrow); 160 PetscCall(PetscIntSumError(b->sliidx[i - 1], b->sliceheight * b->sliidx[i], &b->sliidx[i])); 161 } 162 /* last slice */ 163 b->sliidx[totalslices] = 0; 164 for (j = b->sliceheight * (totalslices - 1); j < B->rmap->n; j++) b->sliidx[totalslices] = PetscMax(b->sliidx[totalslices], rlen[j]); 165 #if defined(PETSC_HAVE_CUPM) 166 if (mul != 0) { 167 rlenmax = PetscMax(b->sliidx[i], rlenmax); 168 b->sliidx[totalslices] = ((b->sliidx[totalslices] - 1) / mul + 1) * mul; 169 } 170 #endif 171 maxallocrow = PetscMax(b->sliidx[totalslices], maxallocrow); 172 b->sliidx[totalslices] = b->sliidx[totalslices - 1] + b->sliceheight * b->sliidx[totalslices]; 173 } 174 175 /* allocate space for val, colidx, rlen */ 176 /* FIXME: should B's old memory be unlogged? */ 177 PetscCall(MatSeqXSELLFreeSELL(B, &b->val, &b->colidx)); 178 /* FIXME: assuming an element of the bit array takes 8 bits */ 179 PetscCall(PetscMalloc2(b->sliidx[totalslices], &b->val, b->sliidx[totalslices], &b->colidx)); 180 /* b->rlen will count nonzeros in each row so far. We dont copy rlen to b->rlen because the matrix has not been set. */ 181 PetscCall(PetscCalloc1(b->sliceheight * totalslices, &b->rlen)); 182 183 b->singlemalloc = PETSC_TRUE; 184 b->free_val = PETSC_TRUE; 185 b->free_colidx = PETSC_TRUE; 186 } else { 187 b->free_val = PETSC_FALSE; 188 b->free_colidx = PETSC_FALSE; 189 } 190 191 b->nz = 0; 192 b->maxallocrow = maxallocrow; 193 #if defined(PETSC_HAVE_CUPM) 194 b->rlenmax = rlenmax; 195 #else 196 b->rlenmax = maxallocrow; 197 #endif 198 b->maxallocmat = b->sliidx[totalslices]; 199 B->info.nz_unneeded = (double)b->maxallocmat; 200 if (realalloc) PetscCall(MatSetOption(B, MAT_NEW_NONZERO_ALLOCATION_ERR, PETSC_TRUE)); 201 PetscFunctionReturn(PETSC_SUCCESS); 202 } 203 204 static PetscErrorCode MatGetRow_SeqSELL(Mat A, PetscInt row, PetscInt *nz, PetscInt **idx, PetscScalar **v) 205 { 206 Mat_SeqSELL *a = (Mat_SeqSELL *)A->data; 207 PetscInt shift; 208 209 PetscFunctionBegin; 210 PetscCheck(row >= 0 && row < A->rmap->n, PETSC_COMM_SELF, PETSC_ERR_ARG_OUTOFRANGE, "Row %" PetscInt_FMT " out of range", row); 211 if (nz) *nz = a->rlen[row]; 212 shift = a->sliidx[row / a->sliceheight] + (row % a->sliceheight); 213 if (!a->getrowcols) { PetscCall(PetscMalloc2(a->rlenmax, &a->getrowcols, a->rlenmax, &a->getrowvals)); } 214 if (idx) { 215 PetscInt j; 216 for (j = 0; j < a->rlen[row]; j++) a->getrowcols[j] = a->colidx[shift + a->sliceheight * j]; 217 *idx = a->getrowcols; 218 } 219 if (v) { 220 PetscInt j; 221 for (j = 0; j < a->rlen[row]; j++) a->getrowvals[j] = a->val[shift + a->sliceheight * j]; 222 *v = a->getrowvals; 223 } 224 PetscFunctionReturn(PETSC_SUCCESS); 225 } 226 227 static PetscErrorCode MatRestoreRow_SeqSELL(Mat A, PetscInt row, PetscInt *nz, PetscInt **idx, PetscScalar **v) 228 { 229 PetscFunctionBegin; 230 PetscFunctionReturn(PETSC_SUCCESS); 231 } 232 233 PetscErrorCode MatConvert_SeqSELL_SeqAIJ(Mat A, MatType newtype, MatReuse reuse, Mat *newmat) 234 { 235 Mat B; 236 Mat_SeqSELL *a = (Mat_SeqSELL *)A->data; 237 PetscInt i; 238 239 PetscFunctionBegin; 240 if (reuse == MAT_REUSE_MATRIX) { 241 B = *newmat; 242 PetscCall(MatZeroEntries(B)); 243 } else { 244 PetscCall(MatCreate(PetscObjectComm((PetscObject)A), &B)); 245 PetscCall(MatSetSizes(B, A->rmap->n, A->cmap->n, A->rmap->N, A->cmap->N)); 246 PetscCall(MatSetType(B, MATSEQAIJ)); 247 PetscCall(MatSeqAIJSetPreallocation(B, 0, a->rlen)); 248 } 249 250 for (i = 0; i < A->rmap->n; i++) { 251 PetscInt nz = 0, *cols = NULL; 252 PetscScalar *vals = NULL; 253 254 PetscCall(MatGetRow_SeqSELL(A, i, &nz, &cols, &vals)); 255 PetscCall(MatSetValues(B, 1, &i, nz, cols, vals, INSERT_VALUES)); 256 PetscCall(MatRestoreRow_SeqSELL(A, i, &nz, &cols, &vals)); 257 } 258 259 PetscCall(MatAssemblyBegin(B, MAT_FINAL_ASSEMBLY)); 260 PetscCall(MatAssemblyEnd(B, MAT_FINAL_ASSEMBLY)); 261 B->rmap->bs = A->rmap->bs; 262 263 if (reuse == MAT_INPLACE_MATRIX) { 264 PetscCall(MatHeaderReplace(A, &B)); 265 } else { 266 *newmat = B; 267 } 268 PetscFunctionReturn(PETSC_SUCCESS); 269 } 270 271 #include <../src/mat/impls/aij/seq/aij.h> 272 273 PetscErrorCode MatConvert_SeqAIJ_SeqSELL(Mat A, MatType newtype, MatReuse reuse, Mat *newmat) 274 { 275 Mat B; 276 Mat_SeqAIJ *a = (Mat_SeqAIJ *)A->data; 277 PetscInt *ai = a->i, m = A->rmap->N, n = A->cmap->N, i, *rowlengths, row, ncols; 278 const PetscInt *cols; 279 const PetscScalar *vals; 280 281 PetscFunctionBegin; 282 if (reuse == MAT_REUSE_MATRIX) { 283 B = *newmat; 284 } else { 285 if (PetscDefined(USE_DEBUG) || !a->ilen) { 286 PetscCall(PetscMalloc1(m, &rowlengths)); 287 for (i = 0; i < m; i++) rowlengths[i] = ai[i + 1] - ai[i]; 288 } 289 if (PetscDefined(USE_DEBUG) && a->ilen) { 290 PetscBool eq; 291 PetscCall(PetscMemcmp(rowlengths, a->ilen, m * sizeof(PetscInt), &eq)); 292 PetscCheck(eq, PETSC_COMM_SELF, PETSC_ERR_PLIB, "SeqAIJ ilen array incorrect"); 293 PetscCall(PetscFree(rowlengths)); 294 rowlengths = a->ilen; 295 } else if (a->ilen) rowlengths = a->ilen; 296 PetscCall(MatCreate(PetscObjectComm((PetscObject)A), &B)); 297 PetscCall(MatSetSizes(B, m, n, m, n)); 298 PetscCall(MatSetType(B, MATSEQSELL)); 299 PetscCall(MatSeqSELLSetPreallocation(B, 0, rowlengths)); 300 if (rowlengths != a->ilen) PetscCall(PetscFree(rowlengths)); 301 } 302 303 for (row = 0; row < m; row++) { 304 PetscCall(MatGetRow_SeqAIJ(A, row, &ncols, (PetscInt **)&cols, (PetscScalar **)&vals)); 305 PetscCall(MatSetValues_SeqSELL(B, 1, &row, ncols, cols, vals, INSERT_VALUES)); 306 PetscCall(MatRestoreRow_SeqAIJ(A, row, &ncols, (PetscInt **)&cols, (PetscScalar **)&vals)); 307 } 308 PetscCall(MatAssemblyBegin(B, MAT_FINAL_ASSEMBLY)); 309 PetscCall(MatAssemblyEnd(B, MAT_FINAL_ASSEMBLY)); 310 B->rmap->bs = A->rmap->bs; 311 312 if (reuse == MAT_INPLACE_MATRIX) { 313 PetscCall(MatHeaderReplace(A, &B)); 314 } else { 315 *newmat = B; 316 } 317 PetscFunctionReturn(PETSC_SUCCESS); 318 } 319 320 PetscErrorCode MatMult_SeqSELL(Mat A, Vec xx, Vec yy) 321 { 322 Mat_SeqSELL *a = (Mat_SeqSELL *)A->data; 323 PetscScalar *y; 324 const PetscScalar *x; 325 const MatScalar *aval = a->val; 326 PetscInt totalslices = a->totalslices; 327 const PetscInt *acolidx = a->colidx; 328 PetscInt i, j; 329 #if defined(PETSC_HAVE_IMMINTRIN_H) && defined(__AVX512F__) && defined(PETSC_USE_REAL_DOUBLE) && !defined(PETSC_USE_COMPLEX) && !defined(PETSC_USE_64BIT_INDICES) 330 __m512d vec_x, vec_y, vec_vals; 331 __m256i vec_idx; 332 __mmask8 mask; 333 __m512d vec_x2, vec_y2, vec_vals2, vec_x3, vec_y3, vec_vals3, vec_x4, vec_y4, vec_vals4; 334 __m256i vec_idx2, vec_idx3, vec_idx4; 335 #elif defined(PETSC_HAVE_IMMINTRIN_H) && defined(__AVX2__) && defined(__FMA__) && defined(PETSC_USE_REAL_DOUBLE) && !defined(PETSC_USE_COMPLEX) && !defined(PETSC_USE_64BIT_INDICES) 336 __m128i vec_idx; 337 __m256d vec_x, vec_y, vec_y2, vec_vals; 338 MatScalar yval; 339 PetscInt r, rows_left, row, nnz_in_row; 340 #elif defined(PETSC_HAVE_IMMINTRIN_H) && defined(__AVX__) && defined(PETSC_USE_REAL_DOUBLE) && !defined(PETSC_USE_COMPLEX) && !defined(PETSC_USE_64BIT_INDICES) 341 __m128d vec_x_tmp; 342 __m256d vec_x, vec_y, vec_y2, vec_vals; 343 MatScalar yval; 344 PetscInt r, rows_left, row, nnz_in_row; 345 #else 346 PetscInt k, sliceheight = a->sliceheight; 347 PetscScalar *sum; 348 #endif 349 350 #if defined(PETSC_HAVE_PRAGMA_DISJOINT) 351 #pragma disjoint(*x, *y, *aval) 352 #endif 353 354 PetscFunctionBegin; 355 PetscCall(VecGetArrayRead(xx, &x)); 356 PetscCall(VecGetArray(yy, &y)); 357 #if defined(PETSC_HAVE_IMMINTRIN_H) && defined(__AVX512F__) && defined(PETSC_USE_REAL_DOUBLE) && !defined(PETSC_USE_COMPLEX) && !defined(PETSC_USE_64BIT_INDICES) 358 PetscCheck(a->sliceheight == 8, PETSC_COMM_SELF, PETSC_ERR_SUP, "The kernel requires a slice height of 8, but the input matrix has a slice height of %" PetscInt_FMT, a->sliceheight); 359 for (i = 0; i < totalslices; i++) { /* loop over slices */ 360 PetscPrefetchBlock(acolidx, a->sliidx[i + 1] - a->sliidx[i], 0, PETSC_PREFETCH_HINT_T0); 361 PetscPrefetchBlock(aval, a->sliidx[i + 1] - a->sliidx[i], 0, PETSC_PREFETCH_HINT_T0); 362 363 vec_y = _mm512_setzero_pd(); 364 vec_y2 = _mm512_setzero_pd(); 365 vec_y3 = _mm512_setzero_pd(); 366 vec_y4 = _mm512_setzero_pd(); 367 368 j = a->sliidx[i] >> 3; /* 8 bytes are read at each time, corresponding to a slice column */ 369 switch ((a->sliidx[i + 1] - a->sliidx[i]) / 8 & 3) { 370 case 3: 371 AVX512_Mult_Private(vec_idx, vec_x, vec_vals, vec_y); 372 acolidx += 8; 373 aval += 8; 374 AVX512_Mult_Private(vec_idx2, vec_x2, vec_vals2, vec_y2); 375 acolidx += 8; 376 aval += 8; 377 AVX512_Mult_Private(vec_idx3, vec_x3, vec_vals3, vec_y3); 378 acolidx += 8; 379 aval += 8; 380 j += 3; 381 break; 382 case 2: 383 AVX512_Mult_Private(vec_idx, vec_x, vec_vals, vec_y); 384 acolidx += 8; 385 aval += 8; 386 AVX512_Mult_Private(vec_idx2, vec_x2, vec_vals2, vec_y2); 387 acolidx += 8; 388 aval += 8; 389 j += 2; 390 break; 391 case 1: 392 AVX512_Mult_Private(vec_idx, vec_x, vec_vals, vec_y); 393 acolidx += 8; 394 aval += 8; 395 j += 1; 396 break; 397 } 398 #pragma novector 399 for (; j < (a->sliidx[i + 1] >> 3); j += 4) { 400 AVX512_Mult_Private(vec_idx, vec_x, vec_vals, vec_y); 401 acolidx += 8; 402 aval += 8; 403 AVX512_Mult_Private(vec_idx2, vec_x2, vec_vals2, vec_y2); 404 acolidx += 8; 405 aval += 8; 406 AVX512_Mult_Private(vec_idx3, vec_x3, vec_vals3, vec_y3); 407 acolidx += 8; 408 aval += 8; 409 AVX512_Mult_Private(vec_idx4, vec_x4, vec_vals4, vec_y4); 410 acolidx += 8; 411 aval += 8; 412 } 413 414 vec_y = _mm512_add_pd(vec_y, vec_y2); 415 vec_y = _mm512_add_pd(vec_y, vec_y3); 416 vec_y = _mm512_add_pd(vec_y, vec_y4); 417 if (i == totalslices - 1 && A->rmap->n & 0x07) { /* if last slice has padding rows */ 418 mask = (__mmask8)(0xff >> (8 - (A->rmap->n & 0x07))); 419 _mm512_mask_storeu_pd(&y[8 * i], mask, vec_y); 420 } else { 421 _mm512_storeu_pd(&y[8 * i], vec_y); 422 } 423 } 424 #elif defined(PETSC_HAVE_IMMINTRIN_H) && defined(__AVX2__) && defined(__FMA__) && defined(PETSC_USE_REAL_DOUBLE) && !defined(PETSC_USE_COMPLEX) && !defined(PETSC_USE_64BIT_INDICES) 425 PetscCheck(a->sliceheight == 8, PETSC_COMM_SELF, PETSC_ERR_SUP, "The kernel requires a slice height of 8, but the input matrix has a slice height of %" PetscInt_FMT, a->sliceheight); 426 for (i = 0; i < totalslices; i++) { /* loop over full slices */ 427 PetscPrefetchBlock(acolidx, a->sliidx[i + 1] - a->sliidx[i], 0, PETSC_PREFETCH_HINT_T0); 428 PetscPrefetchBlock(aval, a->sliidx[i + 1] - a->sliidx[i], 0, PETSC_PREFETCH_HINT_T0); 429 430 /* last slice may have padding rows. Don't use vectorization. */ 431 if (i == totalslices - 1 && (A->rmap->n & 0x07)) { 432 rows_left = A->rmap->n - 8 * i; 433 for (r = 0; r < rows_left; ++r) { 434 yval = (MatScalar)0; 435 row = 8 * i + r; 436 nnz_in_row = a->rlen[row]; 437 for (j = 0; j < nnz_in_row; ++j) yval += aval[8 * j + r] * x[acolidx[8 * j + r]]; 438 y[row] = yval; 439 } 440 break; 441 } 442 443 vec_y = _mm256_setzero_pd(); 444 vec_y2 = _mm256_setzero_pd(); 445 446 /* Process slice of height 8 (512 bits) via two subslices of height 4 (256 bits) via AVX */ 447 #pragma novector 448 #pragma unroll(2) 449 for (j = a->sliidx[i]; j < a->sliidx[i + 1]; j += 8) { 450 AVX2_Mult_Private(vec_idx, vec_x, vec_vals, vec_y); 451 aval += 4; 452 acolidx += 4; 453 AVX2_Mult_Private(vec_idx, vec_x, vec_vals, vec_y2); 454 aval += 4; 455 acolidx += 4; 456 } 457 458 _mm256_storeu_pd(y + i * 8, vec_y); 459 _mm256_storeu_pd(y + i * 8 + 4, vec_y2); 460 } 461 #elif defined(PETSC_HAVE_IMMINTRIN_H) && defined(__AVX__) && defined(PETSC_USE_REAL_DOUBLE) && !defined(PETSC_USE_COMPLEX) && !defined(PETSC_USE_64BIT_INDICES) 462 PetscCheck(a->sliceheight == 8, PETSC_COMM_SELF, PETSC_ERR_SUP, "The kernel requires a slice height of 8, but the input matrix has a slice height of %" PetscInt_FMT, a->sliceheight); 463 for (i = 0; i < totalslices; i++) { /* loop over full slices */ 464 PetscPrefetchBlock(acolidx, a->sliidx[i + 1] - a->sliidx[i], 0, PETSC_PREFETCH_HINT_T0); 465 PetscPrefetchBlock(aval, a->sliidx[i + 1] - a->sliidx[i], 0, PETSC_PREFETCH_HINT_T0); 466 467 vec_y = _mm256_setzero_pd(); 468 vec_y2 = _mm256_setzero_pd(); 469 470 /* last slice may have padding rows. Don't use vectorization. */ 471 if (i == totalslices - 1 && (A->rmap->n & 0x07)) { 472 rows_left = A->rmap->n - 8 * i; 473 for (r = 0; r < rows_left; ++r) { 474 yval = (MatScalar)0; 475 row = 8 * i + r; 476 nnz_in_row = a->rlen[row]; 477 for (j = 0; j < nnz_in_row; ++j) yval += aval[8 * j + r] * x[acolidx[8 * j + r]]; 478 y[row] = yval; 479 } 480 break; 481 } 482 483 /* Process slice of height 8 (512 bits) via two subslices of height 4 (256 bits) via AVX */ 484 #pragma novector 485 #pragma unroll(2) 486 for (j = a->sliidx[i]; j < a->sliidx[i + 1]; j += 8) { 487 vec_vals = _mm256_loadu_pd(aval); 488 vec_x_tmp = _mm_setzero_pd(); 489 vec_x_tmp = _mm_loadl_pd(vec_x_tmp, x + *acolidx++); 490 vec_x_tmp = _mm_loadh_pd(vec_x_tmp, x + *acolidx++); 491 vec_x = _mm256_insertf128_pd(vec_x, vec_x_tmp, 0); 492 vec_x_tmp = _mm_loadl_pd(vec_x_tmp, x + *acolidx++); 493 vec_x_tmp = _mm_loadh_pd(vec_x_tmp, x + *acolidx++); 494 vec_x = _mm256_insertf128_pd(vec_x, vec_x_tmp, 1); 495 vec_y = _mm256_add_pd(_mm256_mul_pd(vec_x, vec_vals), vec_y); 496 aval += 4; 497 498 vec_vals = _mm256_loadu_pd(aval); 499 vec_x_tmp = _mm_loadl_pd(vec_x_tmp, x + *acolidx++); 500 vec_x_tmp = _mm_loadh_pd(vec_x_tmp, x + *acolidx++); 501 vec_x = _mm256_insertf128_pd(vec_x, vec_x_tmp, 0); 502 vec_x_tmp = _mm_loadl_pd(vec_x_tmp, x + *acolidx++); 503 vec_x_tmp = _mm_loadh_pd(vec_x_tmp, x + *acolidx++); 504 vec_x = _mm256_insertf128_pd(vec_x, vec_x_tmp, 1); 505 vec_y2 = _mm256_add_pd(_mm256_mul_pd(vec_x, vec_vals), vec_y2); 506 aval += 4; 507 } 508 509 _mm256_storeu_pd(y + i * 8, vec_y); 510 _mm256_storeu_pd(y + i * 8 + 4, vec_y2); 511 } 512 #else 513 PetscCall(PetscMalloc1(sliceheight, &sum)); 514 for (i = 0; i < totalslices; i++) { /* loop over slices */ 515 for (j = 0; j < sliceheight; j++) { 516 sum[j] = 0.0; 517 for (k = a->sliidx[i] + j; k < a->sliidx[i + 1]; k += sliceheight) sum[j] += aval[k] * x[acolidx[k]]; 518 } 519 if (i == totalslices - 1 && (A->rmap->n % sliceheight)) { /* if last slice has padding rows */ 520 for (j = 0; j < (A->rmap->n % sliceheight); j++) y[sliceheight * i + j] = sum[j]; 521 } else { 522 for (j = 0; j < sliceheight; j++) y[sliceheight * i + j] = sum[j]; 523 } 524 } 525 PetscCall(PetscFree(sum)); 526 #endif 527 528 PetscCall(PetscLogFlops(2.0 * a->nz - a->nonzerorowcnt)); /* theoretical minimal FLOPs */ 529 PetscCall(VecRestoreArrayRead(xx, &x)); 530 PetscCall(VecRestoreArray(yy, &y)); 531 PetscFunctionReturn(PETSC_SUCCESS); 532 } 533 534 #include <../src/mat/impls/aij/seq/ftn-kernels/fmultadd.h> 535 PetscErrorCode MatMultAdd_SeqSELL(Mat A, Vec xx, Vec yy, Vec zz) 536 { 537 Mat_SeqSELL *a = (Mat_SeqSELL *)A->data; 538 PetscScalar *y, *z; 539 const PetscScalar *x; 540 const MatScalar *aval = a->val; 541 PetscInt totalslices = a->totalslices; 542 const PetscInt *acolidx = a->colidx; 543 PetscInt i, j; 544 #if defined(PETSC_HAVE_IMMINTRIN_H) && defined(__AVX512F__) && defined(PETSC_USE_REAL_DOUBLE) && !defined(PETSC_USE_COMPLEX) && !defined(PETSC_USE_64BIT_INDICES) 545 __m512d vec_x, vec_y, vec_vals; 546 __m256i vec_idx; 547 __mmask8 mask = 0; 548 __m512d vec_x2, vec_y2, vec_vals2, vec_x3, vec_y3, vec_vals3, vec_x4, vec_y4, vec_vals4; 549 __m256i vec_idx2, vec_idx3, vec_idx4; 550 #elif defined(PETSC_HAVE_IMMINTRIN_H) && defined(__AVX__) && defined(PETSC_USE_REAL_DOUBLE) && !defined(PETSC_USE_COMPLEX) && !defined(PETSC_USE_64BIT_INDICES) 551 __m128d vec_x_tmp; 552 __m256d vec_x, vec_y, vec_y2, vec_vals; 553 MatScalar yval; 554 PetscInt r, row, nnz_in_row; 555 #else 556 PetscInt k, sliceheight = a->sliceheight; 557 PetscScalar *sum; 558 #endif 559 560 #if defined(PETSC_HAVE_PRAGMA_DISJOINT) 561 #pragma disjoint(*x, *y, *aval) 562 #endif 563 564 PetscFunctionBegin; 565 if (!a->nz) { 566 PetscCall(VecCopy(yy, zz)); 567 PetscFunctionReturn(PETSC_SUCCESS); 568 } 569 PetscCall(VecGetArrayRead(xx, &x)); 570 PetscCall(VecGetArrayPair(yy, zz, &y, &z)); 571 #if defined(PETSC_HAVE_IMMINTRIN_H) && defined(__AVX512F__) && defined(PETSC_USE_REAL_DOUBLE) && !defined(PETSC_USE_COMPLEX) && !defined(PETSC_USE_64BIT_INDICES) 572 PetscCheck(a->sliceheight == 8, PETSC_COMM_SELF, PETSC_ERR_SUP, "The kernel requires a slice height of 8, but the input matrix has a slice height of %" PetscInt_FMT, a->sliceheight); 573 for (i = 0; i < totalslices; i++) { /* loop over slices */ 574 PetscPrefetchBlock(acolidx, a->sliidx[i + 1] - a->sliidx[i], 0, PETSC_PREFETCH_HINT_T0); 575 PetscPrefetchBlock(aval, a->sliidx[i + 1] - a->sliidx[i], 0, PETSC_PREFETCH_HINT_T0); 576 577 if (i == totalslices - 1 && A->rmap->n & 0x07) { /* if last slice has padding rows */ 578 mask = (__mmask8)(0xff >> (8 - (A->rmap->n & 0x07))); 579 vec_y = _mm512_mask_loadu_pd(vec_y, mask, &y[8 * i]); 580 } else { 581 vec_y = _mm512_loadu_pd(&y[8 * i]); 582 } 583 vec_y2 = _mm512_setzero_pd(); 584 vec_y3 = _mm512_setzero_pd(); 585 vec_y4 = _mm512_setzero_pd(); 586 587 j = a->sliidx[i] >> 3; /* 8 bytes are read at each time, corresponding to a slice column */ 588 switch ((a->sliidx[i + 1] - a->sliidx[i]) / 8 & 3) { 589 case 3: 590 AVX512_Mult_Private(vec_idx, vec_x, vec_vals, vec_y); 591 acolidx += 8; 592 aval += 8; 593 AVX512_Mult_Private(vec_idx2, vec_x2, vec_vals2, vec_y2); 594 acolidx += 8; 595 aval += 8; 596 AVX512_Mult_Private(vec_idx3, vec_x3, vec_vals3, vec_y3); 597 acolidx += 8; 598 aval += 8; 599 j += 3; 600 break; 601 case 2: 602 AVX512_Mult_Private(vec_idx, vec_x, vec_vals, vec_y); 603 acolidx += 8; 604 aval += 8; 605 AVX512_Mult_Private(vec_idx2, vec_x2, vec_vals2, vec_y2); 606 acolidx += 8; 607 aval += 8; 608 j += 2; 609 break; 610 case 1: 611 AVX512_Mult_Private(vec_idx, vec_x, vec_vals, vec_y); 612 acolidx += 8; 613 aval += 8; 614 j += 1; 615 break; 616 } 617 #pragma novector 618 for (; j < (a->sliidx[i + 1] >> 3); j += 4) { 619 AVX512_Mult_Private(vec_idx, vec_x, vec_vals, vec_y); 620 acolidx += 8; 621 aval += 8; 622 AVX512_Mult_Private(vec_idx2, vec_x2, vec_vals2, vec_y2); 623 acolidx += 8; 624 aval += 8; 625 AVX512_Mult_Private(vec_idx3, vec_x3, vec_vals3, vec_y3); 626 acolidx += 8; 627 aval += 8; 628 AVX512_Mult_Private(vec_idx4, vec_x4, vec_vals4, vec_y4); 629 acolidx += 8; 630 aval += 8; 631 } 632 633 vec_y = _mm512_add_pd(vec_y, vec_y2); 634 vec_y = _mm512_add_pd(vec_y, vec_y3); 635 vec_y = _mm512_add_pd(vec_y, vec_y4); 636 if (i == totalslices - 1 && A->rmap->n & 0x07) { /* if last slice has padding rows */ 637 _mm512_mask_storeu_pd(&z[8 * i], mask, vec_y); 638 } else { 639 _mm512_storeu_pd(&z[8 * i], vec_y); 640 } 641 } 642 #elif defined(PETSC_HAVE_IMMINTRIN_H) && defined(__AVX__) && defined(PETSC_USE_REAL_DOUBLE) && !defined(PETSC_USE_COMPLEX) && !defined(PETSC_USE_64BIT_INDICES) 643 PetscCheck(a->sliceheight == 8, PETSC_COMM_SELF, PETSC_ERR_SUP, "The kernel requires a slice height of 8, but the input matrix has a slice height of %" PetscInt_FMT, a->sliceheight); 644 for (i = 0; i < totalslices; i++) { /* loop over full slices */ 645 PetscPrefetchBlock(acolidx, a->sliidx[i + 1] - a->sliidx[i], 0, PETSC_PREFETCH_HINT_T0); 646 PetscPrefetchBlock(aval, a->sliidx[i + 1] - a->sliidx[i], 0, PETSC_PREFETCH_HINT_T0); 647 648 /* last slice may have padding rows. Don't use vectorization. */ 649 if (i == totalslices - 1 && (A->rmap->n & 0x07)) { 650 for (r = 0; r < (A->rmap->n & 0x07); ++r) { 651 row = 8 * i + r; 652 yval = (MatScalar)0.0; 653 nnz_in_row = a->rlen[row]; 654 for (j = 0; j < nnz_in_row; ++j) yval += aval[8 * j + r] * x[acolidx[8 * j + r]]; 655 z[row] = y[row] + yval; 656 } 657 break; 658 } 659 660 vec_y = _mm256_loadu_pd(y + 8 * i); 661 vec_y2 = _mm256_loadu_pd(y + 8 * i + 4); 662 663 /* Process slice of height 8 (512 bits) via two subslices of height 4 (256 bits) via AVX */ 664 for (j = a->sliidx[i]; j < a->sliidx[i + 1]; j += 8) { 665 vec_vals = _mm256_loadu_pd(aval); 666 vec_x_tmp = _mm_setzero_pd(); 667 vec_x_tmp = _mm_loadl_pd(vec_x_tmp, x + *acolidx++); 668 vec_x_tmp = _mm_loadh_pd(vec_x_tmp, x + *acolidx++); 669 vec_x = _mm256_setzero_pd(); 670 vec_x = _mm256_insertf128_pd(vec_x, vec_x_tmp, 0); 671 vec_x_tmp = _mm_loadl_pd(vec_x_tmp, x + *acolidx++); 672 vec_x_tmp = _mm_loadh_pd(vec_x_tmp, x + *acolidx++); 673 vec_x = _mm256_insertf128_pd(vec_x, vec_x_tmp, 1); 674 vec_y = _mm256_add_pd(_mm256_mul_pd(vec_x, vec_vals), vec_y); 675 aval += 4; 676 677 vec_vals = _mm256_loadu_pd(aval); 678 vec_x_tmp = _mm_loadl_pd(vec_x_tmp, x + *acolidx++); 679 vec_x_tmp = _mm_loadh_pd(vec_x_tmp, x + *acolidx++); 680 vec_x = _mm256_insertf128_pd(vec_x, vec_x_tmp, 0); 681 vec_x_tmp = _mm_loadl_pd(vec_x_tmp, x + *acolidx++); 682 vec_x_tmp = _mm_loadh_pd(vec_x_tmp, x + *acolidx++); 683 vec_x = _mm256_insertf128_pd(vec_x, vec_x_tmp, 1); 684 vec_y2 = _mm256_add_pd(_mm256_mul_pd(vec_x, vec_vals), vec_y2); 685 aval += 4; 686 } 687 688 _mm256_storeu_pd(z + i * 8, vec_y); 689 _mm256_storeu_pd(z + i * 8 + 4, vec_y2); 690 } 691 #else 692 PetscCall(PetscMalloc1(sliceheight, &sum)); 693 for (i = 0; i < totalslices; i++) { /* loop over slices */ 694 for (j = 0; j < sliceheight; j++) { 695 sum[j] = 0.0; 696 for (k = a->sliidx[i] + j; k < a->sliidx[i + 1]; k += sliceheight) sum[j] += aval[k] * x[acolidx[k]]; 697 } 698 if (i == totalslices - 1 && (A->rmap->n % sliceheight)) { 699 for (j = 0; j < (A->rmap->n % sliceheight); j++) z[sliceheight * i + j] = y[sliceheight * i + j] + sum[j]; 700 } else { 701 for (j = 0; j < sliceheight; j++) z[sliceheight * i + j] = y[sliceheight * i + j] + sum[j]; 702 } 703 } 704 PetscCall(PetscFree(sum)); 705 #endif 706 707 PetscCall(PetscLogFlops(2.0 * a->nz)); 708 PetscCall(VecRestoreArrayRead(xx, &x)); 709 PetscCall(VecRestoreArrayPair(yy, zz, &y, &z)); 710 PetscFunctionReturn(PETSC_SUCCESS); 711 } 712 713 PetscErrorCode MatMultTransposeAdd_SeqSELL(Mat A, Vec xx, Vec zz, Vec yy) 714 { 715 Mat_SeqSELL *a = (Mat_SeqSELL *)A->data; 716 PetscScalar *y; 717 const PetscScalar *x; 718 const MatScalar *aval = a->val; 719 const PetscInt *acolidx = a->colidx; 720 PetscInt i, j, r, row, nnz_in_row, totalslices = a->totalslices, sliceheight = a->sliceheight; 721 722 #if defined(PETSC_HAVE_PRAGMA_DISJOINT) 723 #pragma disjoint(*x, *y, *aval) 724 #endif 725 726 PetscFunctionBegin; 727 if (A->symmetric == PETSC_BOOL3_TRUE) { 728 PetscCall(MatMultAdd_SeqSELL(A, xx, zz, yy)); 729 PetscFunctionReturn(PETSC_SUCCESS); 730 } 731 if (zz != yy) PetscCall(VecCopy(zz, yy)); 732 733 if (a->nz) { 734 PetscCall(VecGetArrayRead(xx, &x)); 735 PetscCall(VecGetArray(yy, &y)); 736 for (i = 0; i < a->totalslices; i++) { /* loop over slices */ 737 if (i == totalslices - 1 && (A->rmap->n % sliceheight)) { 738 for (r = 0; r < (A->rmap->n % sliceheight); ++r) { 739 row = sliceheight * i + r; 740 nnz_in_row = a->rlen[row]; 741 for (j = 0; j < nnz_in_row; ++j) y[acolidx[sliceheight * j + r]] += aval[sliceheight * j + r] * x[row]; 742 } 743 break; 744 } 745 for (r = 0; r < sliceheight; ++r) 746 for (j = a->sliidx[i] + r; j < a->sliidx[i + 1]; j += sliceheight) y[acolidx[j]] += aval[j] * x[sliceheight * i + r]; 747 } 748 PetscCall(PetscLogFlops(2.0 * a->nz)); 749 PetscCall(VecRestoreArrayRead(xx, &x)); 750 PetscCall(VecRestoreArray(yy, &y)); 751 } 752 PetscFunctionReturn(PETSC_SUCCESS); 753 } 754 755 PetscErrorCode MatMultTranspose_SeqSELL(Mat A, Vec xx, Vec yy) 756 { 757 PetscFunctionBegin; 758 if (A->symmetric == PETSC_BOOL3_TRUE) { 759 PetscCall(MatMult_SeqSELL(A, xx, yy)); 760 } else { 761 PetscCall(VecSet(yy, 0.0)); 762 PetscCall(MatMultTransposeAdd_SeqSELL(A, xx, yy, yy)); 763 } 764 PetscFunctionReturn(PETSC_SUCCESS); 765 } 766 767 /* 768 Checks for missing diagonals 769 */ 770 PetscErrorCode MatMissingDiagonal_SeqSELL(Mat A, PetscBool *missing, PetscInt *d) 771 { 772 Mat_SeqSELL *a = (Mat_SeqSELL *)A->data; 773 PetscInt *diag, i; 774 775 PetscFunctionBegin; 776 *missing = PETSC_FALSE; 777 if (A->rmap->n > 0 && !a->colidx) { 778 *missing = PETSC_TRUE; 779 if (d) *d = 0; 780 PetscCall(PetscInfo(A, "Matrix has no entries therefore is missing diagonal\n")); 781 } else { 782 diag = a->diag; 783 for (i = 0; i < A->rmap->n; i++) { 784 if (diag[i] == -1) { 785 *missing = PETSC_TRUE; 786 if (d) *d = i; 787 PetscCall(PetscInfo(A, "Matrix is missing diagonal number %" PetscInt_FMT "\n", i)); 788 break; 789 } 790 } 791 } 792 PetscFunctionReturn(PETSC_SUCCESS); 793 } 794 795 PetscErrorCode MatMarkDiagonal_SeqSELL(Mat A) 796 { 797 Mat_SeqSELL *a = (Mat_SeqSELL *)A->data; 798 PetscInt i, j, m = A->rmap->n, shift; 799 800 PetscFunctionBegin; 801 if (!a->diag) { 802 PetscCall(PetscMalloc1(m, &a->diag)); 803 a->free_diag = PETSC_TRUE; 804 } 805 for (i = 0; i < m; i++) { /* loop over rows */ 806 shift = a->sliidx[i / a->sliceheight] + i % a->sliceheight; /* starting index of the row i */ 807 a->diag[i] = -1; 808 for (j = 0; j < a->rlen[i]; j++) { 809 if (a->colidx[shift + a->sliceheight * j] == i) { 810 a->diag[i] = shift + a->sliceheight * j; 811 break; 812 } 813 } 814 } 815 PetscFunctionReturn(PETSC_SUCCESS); 816 } 817 818 /* 819 Negative shift indicates do not generate an error if there is a zero diagonal, just invert it anyways 820 */ 821 PetscErrorCode MatInvertDiagonal_SeqSELL(Mat A, PetscScalar omega, PetscScalar fshift) 822 { 823 Mat_SeqSELL *a = (Mat_SeqSELL *)A->data; 824 PetscInt i, *diag, m = A->rmap->n; 825 MatScalar *val = a->val; 826 PetscScalar *idiag, *mdiag; 827 828 PetscFunctionBegin; 829 if (a->idiagvalid) PetscFunctionReturn(PETSC_SUCCESS); 830 PetscCall(MatMarkDiagonal_SeqSELL(A)); 831 diag = a->diag; 832 if (!a->idiag) { 833 PetscCall(PetscMalloc3(m, &a->idiag, m, &a->mdiag, m, &a->ssor_work)); 834 val = a->val; 835 } 836 mdiag = a->mdiag; 837 idiag = a->idiag; 838 839 if (omega == 1.0 && PetscRealPart(fshift) <= 0.0) { 840 for (i = 0; i < m; i++) { 841 mdiag[i] = val[diag[i]]; 842 if (!PetscAbsScalar(mdiag[i])) { /* zero diagonal */ 843 PetscCheck(PetscRealPart(fshift), PETSC_COMM_SELF, PETSC_ERR_ARG_INCOMP, "Zero diagonal on row %" PetscInt_FMT, i); 844 PetscCall(PetscInfo(A, "Zero diagonal on row %" PetscInt_FMT "\n", i)); 845 A->factorerrortype = MAT_FACTOR_NUMERIC_ZEROPIVOT; 846 A->factorerror_zeropivot_value = 0.0; 847 A->factorerror_zeropivot_row = i; 848 } 849 idiag[i] = 1.0 / val[diag[i]]; 850 } 851 PetscCall(PetscLogFlops(m)); 852 } else { 853 for (i = 0; i < m; i++) { 854 mdiag[i] = val[diag[i]]; 855 idiag[i] = omega / (fshift + val[diag[i]]); 856 } 857 PetscCall(PetscLogFlops(2.0 * m)); 858 } 859 a->idiagvalid = PETSC_TRUE; 860 PetscFunctionReturn(PETSC_SUCCESS); 861 } 862 863 PetscErrorCode MatZeroEntries_SeqSELL(Mat A) 864 { 865 Mat_SeqSELL *a = (Mat_SeqSELL *)A->data; 866 867 PetscFunctionBegin; 868 PetscCall(PetscArrayzero(a->val, a->sliidx[a->totalslices])); 869 PetscCall(MatSeqSELLInvalidateDiagonal(A)); 870 PetscFunctionReturn(PETSC_SUCCESS); 871 } 872 873 PetscErrorCode MatDestroy_SeqSELL(Mat A) 874 { 875 Mat_SeqSELL *a = (Mat_SeqSELL *)A->data; 876 877 PetscFunctionBegin; 878 PetscCall(PetscLogObjectState((PetscObject)A, "Rows=%" PetscInt_FMT ", Cols=%" PetscInt_FMT ", NZ=%" PetscInt_FMT, A->rmap->n, A->cmap->n, a->nz)); 879 PetscCall(MatSeqXSELLFreeSELL(A, &a->val, &a->colidx)); 880 PetscCall(ISDestroy(&a->row)); 881 PetscCall(ISDestroy(&a->col)); 882 PetscCall(PetscFree(a->diag)); 883 PetscCall(PetscFree(a->rlen)); 884 PetscCall(PetscFree(a->sliidx)); 885 PetscCall(PetscFree3(a->idiag, a->mdiag, a->ssor_work)); 886 PetscCall(PetscFree(a->solve_work)); 887 PetscCall(ISDestroy(&a->icol)); 888 PetscCall(PetscFree(a->saved_values)); 889 PetscCall(PetscFree2(a->getrowcols, a->getrowvals)); 890 PetscCall(PetscFree(A->data)); 891 #if defined(PETSC_HAVE_CUPM) 892 PetscCall(PetscFree(a->chunk_slice_map)); 893 #endif 894 895 PetscCall(PetscObjectChangeTypeName((PetscObject)A, NULL)); 896 PetscCall(PetscObjectComposeFunction((PetscObject)A, "MatStoreValues_C", NULL)); 897 PetscCall(PetscObjectComposeFunction((PetscObject)A, "MatRetrieveValues_C", NULL)); 898 PetscCall(PetscObjectComposeFunction((PetscObject)A, "MatSeqSELLSetPreallocation_C", NULL)); 899 PetscCall(PetscObjectComposeFunction((PetscObject)A, "MatSeqSELLGetArray_C", NULL)); 900 PetscCall(PetscObjectComposeFunction((PetscObject)A, "MatSeqSELLRestoreArray_C", NULL)); 901 PetscCall(PetscObjectComposeFunction((PetscObject)A, "MatConvert_seqsell_seqaij_C", NULL)); 902 #if defined(PETSC_HAVE_CUDA) 903 PetscCall(PetscObjectComposeFunction((PetscObject)A, "MatConvert_seqsell_seqsellcuda_C", NULL)); 904 #endif 905 #if defined(PETSC_HAVE_HIP) 906 PetscCall(PetscObjectComposeFunction((PetscObject)A, "MatConvert_seqsell_seqsellhip_C", NULL)); 907 #endif 908 PetscCall(PetscObjectComposeFunction((PetscObject)A, "MatSeqSELLGetFillRatio_C", NULL)); 909 PetscCall(PetscObjectComposeFunction((PetscObject)A, "MatSeqSELLGetMaxSliceWidth_C", NULL)); 910 PetscCall(PetscObjectComposeFunction((PetscObject)A, "MatSeqSELLGetAvgSliceWidth_C", NULL)); 911 PetscCall(PetscObjectComposeFunction((PetscObject)A, "MatSeqSELLGetVarSliceSize_C", NULL)); 912 PetscCall(PetscObjectComposeFunction((PetscObject)A, "MatSeqSELLSetSliceHeight_C", NULL)); 913 PetscFunctionReturn(PETSC_SUCCESS); 914 } 915 916 PetscErrorCode MatSetOption_SeqSELL(Mat A, MatOption op, PetscBool flg) 917 { 918 Mat_SeqSELL *a = (Mat_SeqSELL *)A->data; 919 920 PetscFunctionBegin; 921 switch (op) { 922 case MAT_ROW_ORIENTED: 923 a->roworiented = flg; 924 break; 925 case MAT_KEEP_NONZERO_PATTERN: 926 a->keepnonzeropattern = flg; 927 break; 928 case MAT_NEW_NONZERO_LOCATIONS: 929 a->nonew = (flg ? 0 : 1); 930 break; 931 case MAT_NEW_NONZERO_LOCATION_ERR: 932 a->nonew = (flg ? -1 : 0); 933 break; 934 case MAT_NEW_NONZERO_ALLOCATION_ERR: 935 a->nonew = (flg ? -2 : 0); 936 break; 937 case MAT_UNUSED_NONZERO_LOCATION_ERR: 938 a->nounused = (flg ? -1 : 0); 939 break; 940 case MAT_FORCE_DIAGONAL_ENTRIES: 941 case MAT_IGNORE_OFF_PROC_ENTRIES: 942 case MAT_USE_HASH_TABLE: 943 case MAT_SORTED_FULL: 944 PetscCall(PetscInfo(A, "Option %s ignored\n", MatOptions[op])); 945 break; 946 case MAT_SPD: 947 case MAT_SYMMETRIC: 948 case MAT_STRUCTURALLY_SYMMETRIC: 949 case MAT_HERMITIAN: 950 case MAT_SYMMETRY_ETERNAL: 951 case MAT_STRUCTURAL_SYMMETRY_ETERNAL: 952 case MAT_SPD_ETERNAL: 953 /* These options are handled directly by MatSetOption() */ 954 break; 955 default: 956 SETERRQ(PETSC_COMM_SELF, PETSC_ERR_SUP, "unknown option %d", op); 957 } 958 PetscFunctionReturn(PETSC_SUCCESS); 959 } 960 961 PetscErrorCode MatGetDiagonal_SeqSELL(Mat A, Vec v) 962 { 963 Mat_SeqSELL *a = (Mat_SeqSELL *)A->data; 964 PetscInt i, j, n, shift; 965 PetscScalar *x, zero = 0.0; 966 967 PetscFunctionBegin; 968 PetscCall(VecGetLocalSize(v, &n)); 969 PetscCheck(n == A->rmap->n, PETSC_COMM_SELF, PETSC_ERR_ARG_SIZ, "Nonconforming matrix and vector"); 970 971 if (A->factortype == MAT_FACTOR_ILU || A->factortype == MAT_FACTOR_LU) { 972 PetscInt *diag = a->diag; 973 PetscCall(VecGetArray(v, &x)); 974 for (i = 0; i < n; i++) x[i] = 1.0 / a->val[diag[i]]; 975 PetscCall(VecRestoreArray(v, &x)); 976 PetscFunctionReturn(PETSC_SUCCESS); 977 } 978 979 PetscCall(VecSet(v, zero)); 980 PetscCall(VecGetArray(v, &x)); 981 for (i = 0; i < n; i++) { /* loop over rows */ 982 shift = a->sliidx[i / a->sliceheight] + i % a->sliceheight; /* starting index of the row i */ 983 x[i] = 0; 984 for (j = 0; j < a->rlen[i]; j++) { 985 if (a->colidx[shift + a->sliceheight * j] == i) { 986 x[i] = a->val[shift + a->sliceheight * j]; 987 break; 988 } 989 } 990 } 991 PetscCall(VecRestoreArray(v, &x)); 992 PetscFunctionReturn(PETSC_SUCCESS); 993 } 994 995 PetscErrorCode MatDiagonalScale_SeqSELL(Mat A, Vec ll, Vec rr) 996 { 997 Mat_SeqSELL *a = (Mat_SeqSELL *)A->data; 998 const PetscScalar *l, *r; 999 PetscInt i, j, m, n, row; 1000 1001 PetscFunctionBegin; 1002 if (ll) { 1003 /* The local size is used so that VecMPI can be passed to this routine 1004 by MatDiagonalScale_MPISELL */ 1005 PetscCall(VecGetLocalSize(ll, &m)); 1006 PetscCheck(m == A->rmap->n, PETSC_COMM_SELF, PETSC_ERR_ARG_SIZ, "Left scaling vector wrong length"); 1007 PetscCall(VecGetArrayRead(ll, &l)); 1008 for (i = 0; i < a->totalslices; i++) { /* loop over slices */ 1009 if (i == a->totalslices - 1 && (A->rmap->n % a->sliceheight)) { /* if last slice has padding rows */ 1010 for (j = a->sliidx[i], row = 0; j < a->sliidx[i + 1]; j++, row = (row + 1) % a->sliceheight) { 1011 if (row < (A->rmap->n % a->sliceheight)) a->val[j] *= l[a->sliceheight * i + row]; 1012 } 1013 } else { 1014 for (j = a->sliidx[i], row = 0; j < a->sliidx[i + 1]; j++, row = (row + 1) % a->sliceheight) { a->val[j] *= l[a->sliceheight * i + row]; } 1015 } 1016 } 1017 PetscCall(VecRestoreArrayRead(ll, &l)); 1018 PetscCall(PetscLogFlops(a->nz)); 1019 } 1020 if (rr) { 1021 PetscCall(VecGetLocalSize(rr, &n)); 1022 PetscCheck(n == A->cmap->n, PETSC_COMM_SELF, PETSC_ERR_ARG_SIZ, "Right scaling vector wrong length"); 1023 PetscCall(VecGetArrayRead(rr, &r)); 1024 for (i = 0; i < a->totalslices; i++) { /* loop over slices */ 1025 if (i == a->totalslices - 1 && (A->rmap->n % a->sliceheight)) { /* if last slice has padding rows */ 1026 for (j = a->sliidx[i], row = 0; j < a->sliidx[i + 1]; j++, row = ((row + 1) % a->sliceheight)) { 1027 if (row < (A->rmap->n % a->sliceheight)) a->val[j] *= r[a->colidx[j]]; 1028 } 1029 } else { 1030 for (j = a->sliidx[i]; j < a->sliidx[i + 1]; j++) a->val[j] *= r[a->colidx[j]]; 1031 } 1032 } 1033 PetscCall(VecRestoreArrayRead(rr, &r)); 1034 PetscCall(PetscLogFlops(a->nz)); 1035 } 1036 PetscCall(MatSeqSELLInvalidateDiagonal(A)); 1037 #if defined(PETSC_HAVE_CUPM) 1038 if (A->offloadmask != PETSC_OFFLOAD_UNALLOCATED) A->offloadmask = PETSC_OFFLOAD_CPU; 1039 #endif 1040 PetscFunctionReturn(PETSC_SUCCESS); 1041 } 1042 1043 PetscErrorCode MatGetValues_SeqSELL(Mat A, PetscInt m, const PetscInt im[], PetscInt n, const PetscInt in[], PetscScalar v[]) 1044 { 1045 Mat_SeqSELL *a = (Mat_SeqSELL *)A->data; 1046 PetscInt *cp, i, k, low, high, t, row, col, l; 1047 PetscInt shift; 1048 MatScalar *vp; 1049 1050 PetscFunctionBegin; 1051 for (k = 0; k < m; k++) { /* loop over requested rows */ 1052 row = im[k]; 1053 if (row < 0) continue; 1054 PetscCheck(row < A->rmap->n, PETSC_COMM_SELF, PETSC_ERR_ARG_OUTOFRANGE, "Row too large: row %" PetscInt_FMT " max %" PetscInt_FMT, row, A->rmap->n - 1); 1055 shift = a->sliidx[row / a->sliceheight] + (row % a->sliceheight); /* starting index of the row */ 1056 cp = a->colidx + shift; /* pointer to the row */ 1057 vp = a->val + shift; /* pointer to the row */ 1058 for (l = 0; l < n; l++) { /* loop over requested columns */ 1059 col = in[l]; 1060 if (col < 0) continue; 1061 PetscCheck(col < A->cmap->n, PETSC_COMM_SELF, PETSC_ERR_ARG_OUTOFRANGE, "Column too large: row %" PetscInt_FMT " max %" PetscInt_FMT, col, A->cmap->n - 1); 1062 high = a->rlen[row]; 1063 low = 0; /* assume unsorted */ 1064 while (high - low > 5) { 1065 t = (low + high) / 2; 1066 if (*(cp + a->sliceheight * t) > col) high = t; 1067 else low = t; 1068 } 1069 for (i = low; i < high; i++) { 1070 if (*(cp + a->sliceheight * i) > col) break; 1071 if (*(cp + a->sliceheight * i) == col) { 1072 *v++ = *(vp + a->sliceheight * i); 1073 goto finished; 1074 } 1075 } 1076 *v++ = 0.0; 1077 finished:; 1078 } 1079 } 1080 PetscFunctionReturn(PETSC_SUCCESS); 1081 } 1082 1083 static PetscErrorCode MatView_SeqSELL_ASCII(Mat A, PetscViewer viewer) 1084 { 1085 Mat_SeqSELL *a = (Mat_SeqSELL *)A->data; 1086 PetscInt i, j, m = A->rmap->n, shift; 1087 const char *name; 1088 PetscViewerFormat format; 1089 1090 PetscFunctionBegin; 1091 PetscCall(PetscViewerGetFormat(viewer, &format)); 1092 if (format == PETSC_VIEWER_ASCII_MATLAB) { 1093 PetscInt nofinalvalue = 0; 1094 /* 1095 if (m && ((a->i[m] == a->i[m-1]) || (a->j[a->nz-1] != A->cmap->n-1))) { 1096 nofinalvalue = 1; 1097 } 1098 */ 1099 PetscCall(PetscViewerASCIIUseTabs(viewer, PETSC_FALSE)); 1100 PetscCall(PetscViewerASCIIPrintf(viewer, "%% Size = %" PetscInt_FMT " %" PetscInt_FMT " \n", m, A->cmap->n)); 1101 PetscCall(PetscViewerASCIIPrintf(viewer, "%% Nonzeros = %" PetscInt_FMT " \n", a->nz)); 1102 #if defined(PETSC_USE_COMPLEX) 1103 PetscCall(PetscViewerASCIIPrintf(viewer, "zzz = zeros(%" PetscInt_FMT ",4);\n", a->nz + nofinalvalue)); 1104 #else 1105 PetscCall(PetscViewerASCIIPrintf(viewer, "zzz = zeros(%" PetscInt_FMT ",3);\n", a->nz + nofinalvalue)); 1106 #endif 1107 PetscCall(PetscViewerASCIIPrintf(viewer, "zzz = [\n")); 1108 1109 for (i = 0; i < m; i++) { 1110 shift = a->sliidx[i / a->sliceheight] + i % a->sliceheight; 1111 for (j = 0; j < a->rlen[i]; j++) { 1112 #if defined(PETSC_USE_COMPLEX) 1113 PetscCall(PetscViewerASCIIPrintf(viewer, "%" PetscInt_FMT " %" PetscInt_FMT " %18.16e %18.16e\n", i + 1, a->colidx[shift + a->sliceheight * j] + 1, (double)PetscRealPart(a->val[shift + a->sliceheight * j]), (double)PetscImaginaryPart(a->val[shift + a->sliceheight * j]))); 1114 #else 1115 PetscCall(PetscViewerASCIIPrintf(viewer, "%" PetscInt_FMT " %" PetscInt_FMT " %18.16e\n", i + 1, a->colidx[shift + a->sliceheight * j] + 1, (double)a->val[shift + a->sliceheight * j])); 1116 #endif 1117 } 1118 } 1119 /* 1120 if (nofinalvalue) { 1121 #if defined(PETSC_USE_COMPLEX) 1122 PetscCall(PetscViewerASCIIPrintf(viewer,"%" PetscInt_FMT " %" PetscInt_FMT " %18.16e %18.16e\n",m,A->cmap->n,0.,0.)); 1123 #else 1124 PetscCall(PetscViewerASCIIPrintf(viewer,"%" PetscInt_FMT " %" PetscInt_FMT " %18.16e\n",m,A->cmap->n,0.0)); 1125 #endif 1126 } 1127 */ 1128 PetscCall(PetscObjectGetName((PetscObject)A, &name)); 1129 PetscCall(PetscViewerASCIIPrintf(viewer, "];\n %s = spconvert(zzz);\n", name)); 1130 PetscCall(PetscViewerASCIIUseTabs(viewer, PETSC_TRUE)); 1131 } else if (format == PETSC_VIEWER_ASCII_FACTOR_INFO || format == PETSC_VIEWER_ASCII_INFO) { 1132 PetscFunctionReturn(PETSC_SUCCESS); 1133 } else if (format == PETSC_VIEWER_ASCII_COMMON) { 1134 PetscCall(PetscViewerASCIIUseTabs(viewer, PETSC_FALSE)); 1135 for (i = 0; i < m; i++) { 1136 PetscCall(PetscViewerASCIIPrintf(viewer, "row %" PetscInt_FMT ":", i)); 1137 shift = a->sliidx[i / a->sliceheight] + i % a->sliceheight; 1138 for (j = 0; j < a->rlen[i]; j++) { 1139 #if defined(PETSC_USE_COMPLEX) 1140 if (PetscImaginaryPart(a->val[shift + a->sliceheight * j]) > 0.0 && PetscRealPart(a->val[shift + a->sliceheight * j]) != 0.0) { 1141 PetscCall(PetscViewerASCIIPrintf(viewer, " (%" PetscInt_FMT ", %g + %g i)", a->colidx[shift + a->sliceheight * j], (double)PetscRealPart(a->val[shift + a->sliceheight * j]), (double)PetscImaginaryPart(a->val[shift + a->sliceheight * j]))); 1142 } else if (PetscImaginaryPart(a->val[shift + a->sliceheight * j]) < 0.0 && PetscRealPart(a->val[shift + a->sliceheight * j]) != 0.0) { 1143 PetscCall(PetscViewerASCIIPrintf(viewer, " (%" PetscInt_FMT ", %g - %g i)", a->colidx[shift + a->sliceheight * j], (double)PetscRealPart(a->val[shift + a->sliceheight * j]), (double)-PetscImaginaryPart(a->val[shift + a->sliceheight * j]))); 1144 } else if (PetscRealPart(a->val[shift + a->sliceheight * j]) != 0.0) { 1145 PetscCall(PetscViewerASCIIPrintf(viewer, " (%" PetscInt_FMT ", %g) ", a->colidx[shift + a->sliceheight * j], (double)PetscRealPart(a->val[shift + a->sliceheight * j]))); 1146 } 1147 #else 1148 if (a->val[shift + a->sliceheight * j] != 0.0) PetscCall(PetscViewerASCIIPrintf(viewer, " (%" PetscInt_FMT ", %g) ", a->colidx[shift + a->sliceheight * j], (double)a->val[shift + a->sliceheight * j])); 1149 #endif 1150 } 1151 PetscCall(PetscViewerASCIIPrintf(viewer, "\n")); 1152 } 1153 PetscCall(PetscViewerASCIIUseTabs(viewer, PETSC_TRUE)); 1154 } else if (format == PETSC_VIEWER_ASCII_DENSE) { 1155 PetscInt cnt = 0, jcnt; 1156 PetscScalar value; 1157 #if defined(PETSC_USE_COMPLEX) 1158 PetscBool realonly = PETSC_TRUE; 1159 for (i = 0; i < a->sliidx[a->totalslices]; i++) { 1160 if (PetscImaginaryPart(a->val[i]) != 0.0) { 1161 realonly = PETSC_FALSE; 1162 break; 1163 } 1164 } 1165 #endif 1166 1167 PetscCall(PetscViewerASCIIUseTabs(viewer, PETSC_FALSE)); 1168 for (i = 0; i < m; i++) { 1169 jcnt = 0; 1170 shift = a->sliidx[i / a->sliceheight] + i % a->sliceheight; 1171 for (j = 0; j < A->cmap->n; j++) { 1172 if (jcnt < a->rlen[i] && j == a->colidx[shift + a->sliceheight * j]) { 1173 value = a->val[cnt++]; 1174 jcnt++; 1175 } else { 1176 value = 0.0; 1177 } 1178 #if defined(PETSC_USE_COMPLEX) 1179 if (realonly) { 1180 PetscCall(PetscViewerASCIIPrintf(viewer, " %7.5e ", (double)PetscRealPart(value))); 1181 } else { 1182 PetscCall(PetscViewerASCIIPrintf(viewer, " %7.5e+%7.5e i ", (double)PetscRealPart(value), (double)PetscImaginaryPart(value))); 1183 } 1184 #else 1185 PetscCall(PetscViewerASCIIPrintf(viewer, " %7.5e ", (double)value)); 1186 #endif 1187 } 1188 PetscCall(PetscViewerASCIIPrintf(viewer, "\n")); 1189 } 1190 PetscCall(PetscViewerASCIIUseTabs(viewer, PETSC_TRUE)); 1191 } else if (format == PETSC_VIEWER_ASCII_MATRIXMARKET) { 1192 PetscInt fshift = 1; 1193 PetscCall(PetscViewerASCIIUseTabs(viewer, PETSC_FALSE)); 1194 #if defined(PETSC_USE_COMPLEX) 1195 PetscCall(PetscViewerASCIIPrintf(viewer, "%%%%MatrixMarket matrix coordinate complex general\n")); 1196 #else 1197 PetscCall(PetscViewerASCIIPrintf(viewer, "%%%%MatrixMarket matrix coordinate real general\n")); 1198 #endif 1199 PetscCall(PetscViewerASCIIPrintf(viewer, "%" PetscInt_FMT " %" PetscInt_FMT " %" PetscInt_FMT "\n", m, A->cmap->n, a->nz)); 1200 for (i = 0; i < m; i++) { 1201 shift = a->sliidx[i / a->sliceheight] + i % a->sliceheight; 1202 for (j = 0; j < a->rlen[i]; j++) { 1203 #if defined(PETSC_USE_COMPLEX) 1204 PetscCall(PetscViewerASCIIPrintf(viewer, "%" PetscInt_FMT " %" PetscInt_FMT " %g %g\n", i + fshift, a->colidx[shift + a->sliceheight * j] + fshift, (double)PetscRealPart(a->val[shift + a->sliceheight * j]), (double)PetscImaginaryPart(a->val[shift + a->sliceheight * j]))); 1205 #else 1206 PetscCall(PetscViewerASCIIPrintf(viewer, "%" PetscInt_FMT " %" PetscInt_FMT " %g\n", i + fshift, a->colidx[shift + a->sliceheight * j] + fshift, (double)a->val[shift + a->sliceheight * j])); 1207 #endif 1208 } 1209 } 1210 PetscCall(PetscViewerASCIIUseTabs(viewer, PETSC_TRUE)); 1211 } else if (format == PETSC_VIEWER_NATIVE) { 1212 for (i = 0; i < a->totalslices; i++) { /* loop over slices */ 1213 PetscInt row; 1214 PetscCall(PetscViewerASCIIPrintf(viewer, "slice %" PetscInt_FMT ": %" PetscInt_FMT " %" PetscInt_FMT "\n", i, a->sliidx[i], a->sliidx[i + 1])); 1215 for (j = a->sliidx[i], row = 0; j < a->sliidx[i + 1]; j++, row = (row + 1) % a->sliceheight) { 1216 #if defined(PETSC_USE_COMPLEX) 1217 if (PetscImaginaryPart(a->val[j]) > 0.0) { 1218 PetscCall(PetscViewerASCIIPrintf(viewer, " %" PetscInt_FMT " %" PetscInt_FMT " %g + %g i\n", a->sliceheight * i + row, a->colidx[j], (double)PetscRealPart(a->val[j]), (double)PetscImaginaryPart(a->val[j]))); 1219 } else if (PetscImaginaryPart(a->val[j]) < 0.0) { 1220 PetscCall(PetscViewerASCIIPrintf(viewer, " %" PetscInt_FMT " %" PetscInt_FMT " %g - %g i\n", a->sliceheight * i + row, a->colidx[j], (double)PetscRealPart(a->val[j]), -(double)PetscImaginaryPart(a->val[j]))); 1221 } else { 1222 PetscCall(PetscViewerASCIIPrintf(viewer, " %" PetscInt_FMT " %" PetscInt_FMT " %g\n", a->sliceheight * i + row, a->colidx[j], (double)PetscRealPart(a->val[j]))); 1223 } 1224 #else 1225 PetscCall(PetscViewerASCIIPrintf(viewer, " %" PetscInt_FMT " %" PetscInt_FMT " %g\n", a->sliceheight * i + row, a->colidx[j], (double)a->val[j])); 1226 #endif 1227 } 1228 } 1229 } else { 1230 PetscCall(PetscViewerASCIIUseTabs(viewer, PETSC_FALSE)); 1231 if (A->factortype) { 1232 for (i = 0; i < m; i++) { 1233 shift = a->sliidx[i / a->sliceheight] + i % a->sliceheight; 1234 PetscCall(PetscViewerASCIIPrintf(viewer, "row %" PetscInt_FMT ":", i)); 1235 /* L part */ 1236 for (j = shift; j < a->diag[i]; j += a->sliceheight) { 1237 #if defined(PETSC_USE_COMPLEX) 1238 if (PetscImaginaryPart(a->val[shift + a->sliceheight * j]) > 0.0) { 1239 PetscCall(PetscViewerASCIIPrintf(viewer, " (%" PetscInt_FMT ", %g + %g i)", a->colidx[j], (double)PetscRealPart(a->val[j]), (double)PetscImaginaryPart(a->val[j]))); 1240 } else if (PetscImaginaryPart(a->val[shift + a->sliceheight * j]) < 0.0) { 1241 PetscCall(PetscViewerASCIIPrintf(viewer, " (%" PetscInt_FMT ", %g - %g i)", a->colidx[j], (double)PetscRealPart(a->val[j]), (double)(-PetscImaginaryPart(a->val[j])))); 1242 } else { 1243 PetscCall(PetscViewerASCIIPrintf(viewer, " (%" PetscInt_FMT ", %g) ", a->colidx[j], (double)PetscRealPart(a->val[j]))); 1244 } 1245 #else 1246 PetscCall(PetscViewerASCIIPrintf(viewer, " (%" PetscInt_FMT ", %g) ", a->colidx[j], (double)a->val[j])); 1247 #endif 1248 } 1249 /* diagonal */ 1250 j = a->diag[i]; 1251 #if defined(PETSC_USE_COMPLEX) 1252 if (PetscImaginaryPart(a->val[j]) > 0.0) { 1253 PetscCall(PetscViewerASCIIPrintf(viewer, " (%" PetscInt_FMT ", %g + %g i)", a->colidx[j], (double)PetscRealPart(1.0 / a->val[j]), (double)PetscImaginaryPart(1.0 / a->val[j]))); 1254 } else if (PetscImaginaryPart(a->val[j]) < 0.0) { 1255 PetscCall(PetscViewerASCIIPrintf(viewer, " (%" PetscInt_FMT ", %g - %g i)", a->colidx[j], (double)PetscRealPart(1.0 / a->val[j]), (double)(-PetscImaginaryPart(1.0 / a->val[j])))); 1256 } else { 1257 PetscCall(PetscViewerASCIIPrintf(viewer, " (%" PetscInt_FMT ", %g) ", a->colidx[j], (double)PetscRealPart(1.0 / a->val[j]))); 1258 } 1259 #else 1260 PetscCall(PetscViewerASCIIPrintf(viewer, " (%" PetscInt_FMT ", %g) ", a->colidx[j], (double)(1.0 / a->val[j]))); 1261 #endif 1262 1263 /* U part */ 1264 for (j = a->diag[i] + 1; j < shift + a->sliceheight * a->rlen[i]; j += a->sliceheight) { 1265 #if defined(PETSC_USE_COMPLEX) 1266 if (PetscImaginaryPart(a->val[j]) > 0.0) { 1267 PetscCall(PetscViewerASCIIPrintf(viewer, " (%" PetscInt_FMT ", %g + %g i)", a->colidx[j], (double)PetscRealPart(a->val[j]), (double)PetscImaginaryPart(a->val[j]))); 1268 } else if (PetscImaginaryPart(a->val[j]) < 0.0) { 1269 PetscCall(PetscViewerASCIIPrintf(viewer, " (%" PetscInt_FMT ", %g - %g i)", a->colidx[j], (double)PetscRealPart(a->val[j]), (double)(-PetscImaginaryPart(a->val[j])))); 1270 } else { 1271 PetscCall(PetscViewerASCIIPrintf(viewer, " (%" PetscInt_FMT ", %g) ", a->colidx[j], (double)PetscRealPart(a->val[j]))); 1272 } 1273 #else 1274 PetscCall(PetscViewerASCIIPrintf(viewer, " (%" PetscInt_FMT ", %g) ", a->colidx[j], (double)a->val[j])); 1275 #endif 1276 } 1277 PetscCall(PetscViewerASCIIPrintf(viewer, "\n")); 1278 } 1279 } else { 1280 for (i = 0; i < m; i++) { 1281 shift = a->sliidx[i / a->sliceheight] + i % a->sliceheight; 1282 PetscCall(PetscViewerASCIIPrintf(viewer, "row %" PetscInt_FMT ":", i)); 1283 for (j = 0; j < a->rlen[i]; j++) { 1284 #if defined(PETSC_USE_COMPLEX) 1285 if (PetscImaginaryPart(a->val[j]) > 0.0) { 1286 PetscCall(PetscViewerASCIIPrintf(viewer, " (%" PetscInt_FMT ", %g + %g i)", a->colidx[shift + a->sliceheight * j], (double)PetscRealPart(a->val[shift + a->sliceheight * j]), (double)PetscImaginaryPart(a->val[shift + a->sliceheight * j]))); 1287 } else if (PetscImaginaryPart(a->val[j]) < 0.0) { 1288 PetscCall(PetscViewerASCIIPrintf(viewer, " (%" PetscInt_FMT ", %g - %g i)", a->colidx[shift + a->sliceheight * j], (double)PetscRealPart(a->val[shift + a->sliceheight * j]), (double)-PetscImaginaryPart(a->val[shift + a->sliceheight * j]))); 1289 } else { 1290 PetscCall(PetscViewerASCIIPrintf(viewer, " (%" PetscInt_FMT ", %g) ", a->colidx[shift + a->sliceheight * j], (double)PetscRealPart(a->val[shift + a->sliceheight * j]))); 1291 } 1292 #else 1293 PetscCall(PetscViewerASCIIPrintf(viewer, " (%" PetscInt_FMT ", %g) ", a->colidx[shift + a->sliceheight * j], (double)a->val[shift + a->sliceheight * j])); 1294 #endif 1295 } 1296 PetscCall(PetscViewerASCIIPrintf(viewer, "\n")); 1297 } 1298 } 1299 PetscCall(PetscViewerASCIIUseTabs(viewer, PETSC_TRUE)); 1300 } 1301 PetscCall(PetscViewerFlush(viewer)); 1302 PetscFunctionReturn(PETSC_SUCCESS); 1303 } 1304 1305 #include <petscdraw.h> 1306 static PetscErrorCode MatView_SeqSELL_Draw_Zoom(PetscDraw draw, void *Aa) 1307 { 1308 Mat A = (Mat)Aa; 1309 Mat_SeqSELL *a = (Mat_SeqSELL *)A->data; 1310 PetscInt i, j, m = A->rmap->n, shift; 1311 int color; 1312 PetscReal xl, yl, xr, yr, x_l, x_r, y_l, y_r; 1313 PetscViewer viewer; 1314 PetscViewerFormat format; 1315 1316 PetscFunctionBegin; 1317 PetscCall(PetscObjectQuery((PetscObject)A, "Zoomviewer", (PetscObject *)&viewer)); 1318 PetscCall(PetscViewerGetFormat(viewer, &format)); 1319 PetscCall(PetscDrawGetCoordinates(draw, &xl, &yl, &xr, &yr)); 1320 1321 /* loop over matrix elements drawing boxes */ 1322 1323 if (format != PETSC_VIEWER_DRAW_CONTOUR) { 1324 PetscDrawCollectiveBegin(draw); 1325 /* Blue for negative, Cyan for zero and Red for positive */ 1326 color = PETSC_DRAW_BLUE; 1327 for (i = 0; i < m; i++) { 1328 shift = a->sliidx[i / a->sliceheight] + i % a->sliceheight; /* starting index of the row i */ 1329 y_l = m - i - 1.0; 1330 y_r = y_l + 1.0; 1331 for (j = 0; j < a->rlen[i]; j++) { 1332 x_l = a->colidx[shift + a->sliceheight * j]; 1333 x_r = x_l + 1.0; 1334 if (PetscRealPart(a->val[shift + a->sliceheight * j]) >= 0.) continue; 1335 PetscCall(PetscDrawRectangle(draw, x_l, y_l, x_r, y_r, color, color, color, color)); 1336 } 1337 } 1338 color = PETSC_DRAW_CYAN; 1339 for (i = 0; i < m; i++) { 1340 shift = a->sliidx[i / a->sliceheight] + i % a->sliceheight; 1341 y_l = m - i - 1.0; 1342 y_r = y_l + 1.0; 1343 for (j = 0; j < a->rlen[i]; j++) { 1344 x_l = a->colidx[shift + a->sliceheight * j]; 1345 x_r = x_l + 1.0; 1346 if (a->val[shift + a->sliceheight * j] != 0.) continue; 1347 PetscCall(PetscDrawRectangle(draw, x_l, y_l, x_r, y_r, color, color, color, color)); 1348 } 1349 } 1350 color = PETSC_DRAW_RED; 1351 for (i = 0; i < m; i++) { 1352 shift = a->sliidx[i / a->sliceheight] + i % a->sliceheight; 1353 y_l = m - i - 1.0; 1354 y_r = y_l + 1.0; 1355 for (j = 0; j < a->rlen[i]; j++) { 1356 x_l = a->colidx[shift + a->sliceheight * j]; 1357 x_r = x_l + 1.0; 1358 if (PetscRealPart(a->val[shift + a->sliceheight * j]) <= 0.) continue; 1359 PetscCall(PetscDrawRectangle(draw, x_l, y_l, x_r, y_r, color, color, color, color)); 1360 } 1361 } 1362 PetscDrawCollectiveEnd(draw); 1363 } else { 1364 /* use contour shading to indicate magnitude of values */ 1365 /* first determine max of all nonzero values */ 1366 PetscReal minv = 0.0, maxv = 0.0; 1367 PetscInt count = 0; 1368 PetscDraw popup; 1369 for (i = 0; i < a->sliidx[a->totalslices]; i++) { 1370 if (PetscAbsScalar(a->val[i]) > maxv) maxv = PetscAbsScalar(a->val[i]); 1371 } 1372 if (minv >= maxv) maxv = minv + PETSC_SMALL; 1373 PetscCall(PetscDrawGetPopup(draw, &popup)); 1374 PetscCall(PetscDrawScalePopup(popup, minv, maxv)); 1375 1376 PetscDrawCollectiveBegin(draw); 1377 for (i = 0; i < m; i++) { 1378 shift = a->sliidx[i / a->sliceheight] + i % a->sliceheight; 1379 y_l = m - i - 1.0; 1380 y_r = y_l + 1.0; 1381 for (j = 0; j < a->rlen[i]; j++) { 1382 x_l = a->colidx[shift + a->sliceheight * j]; 1383 x_r = x_l + 1.0; 1384 color = PetscDrawRealToColor(PetscAbsScalar(a->val[count]), minv, maxv); 1385 PetscCall(PetscDrawRectangle(draw, x_l, y_l, x_r, y_r, color, color, color, color)); 1386 count++; 1387 } 1388 } 1389 PetscDrawCollectiveEnd(draw); 1390 } 1391 PetscFunctionReturn(PETSC_SUCCESS); 1392 } 1393 1394 #include <petscdraw.h> 1395 static PetscErrorCode MatView_SeqSELL_Draw(Mat A, PetscViewer viewer) 1396 { 1397 PetscDraw draw; 1398 PetscReal xr, yr, xl, yl, h, w; 1399 PetscBool isnull; 1400 1401 PetscFunctionBegin; 1402 PetscCall(PetscViewerDrawGetDraw(viewer, 0, &draw)); 1403 PetscCall(PetscDrawIsNull(draw, &isnull)); 1404 if (isnull) PetscFunctionReturn(PETSC_SUCCESS); 1405 1406 xr = A->cmap->n; 1407 yr = A->rmap->n; 1408 h = yr / 10.0; 1409 w = xr / 10.0; 1410 xr += w; 1411 yr += h; 1412 xl = -w; 1413 yl = -h; 1414 PetscCall(PetscDrawSetCoordinates(draw, xl, yl, xr, yr)); 1415 PetscCall(PetscObjectCompose((PetscObject)A, "Zoomviewer", (PetscObject)viewer)); 1416 PetscCall(PetscDrawZoom(draw, MatView_SeqSELL_Draw_Zoom, A)); 1417 PetscCall(PetscObjectCompose((PetscObject)A, "Zoomviewer", NULL)); 1418 PetscCall(PetscDrawSave(draw)); 1419 PetscFunctionReturn(PETSC_SUCCESS); 1420 } 1421 1422 PetscErrorCode MatView_SeqSELL(Mat A, PetscViewer viewer) 1423 { 1424 PetscBool iascii, isbinary, isdraw; 1425 1426 PetscFunctionBegin; 1427 PetscCall(PetscObjectTypeCompare((PetscObject)viewer, PETSCVIEWERASCII, &iascii)); 1428 PetscCall(PetscObjectTypeCompare((PetscObject)viewer, PETSCVIEWERBINARY, &isbinary)); 1429 PetscCall(PetscObjectTypeCompare((PetscObject)viewer, PETSCVIEWERDRAW, &isdraw)); 1430 if (iascii) { 1431 PetscCall(MatView_SeqSELL_ASCII(A, viewer)); 1432 } else if (isbinary) { 1433 /* PetscCall(MatView_SeqSELL_Binary(A,viewer)); */ 1434 } else if (isdraw) PetscCall(MatView_SeqSELL_Draw(A, viewer)); 1435 PetscFunctionReturn(PETSC_SUCCESS); 1436 } 1437 1438 PetscErrorCode MatAssemblyEnd_SeqSELL(Mat A, MatAssemblyType mode) 1439 { 1440 Mat_SeqSELL *a = (Mat_SeqSELL *)A->data; 1441 PetscInt i, shift, row_in_slice, row, nrow, *cp, lastcol, j, k; 1442 MatScalar *vp; 1443 #if defined(PETSC_HAVE_CUPM) 1444 PetscInt totalchunks = 0; 1445 #endif 1446 1447 PetscFunctionBegin; 1448 if (mode == MAT_FLUSH_ASSEMBLY) PetscFunctionReturn(PETSC_SUCCESS); 1449 /* To do: compress out the unused elements */ 1450 PetscCall(MatMarkDiagonal_SeqSELL(A)); 1451 PetscCall(PetscInfo(A, "Matrix size: %" PetscInt_FMT " X %" PetscInt_FMT "; storage space: %" PetscInt_FMT " allocated %" PetscInt_FMT " used (%" PetscInt_FMT " nonzeros+%" PetscInt_FMT " paddedzeros)\n", A->rmap->n, A->cmap->n, a->maxallocmat, a->sliidx[a->totalslices], a->nz, a->sliidx[a->totalslices] - a->nz)); 1452 PetscCall(PetscInfo(A, "Number of mallocs during MatSetValues() is %" PetscInt_FMT "\n", a->reallocs)); 1453 PetscCall(PetscInfo(A, "Maximum nonzeros in any row is %" PetscInt_FMT "\n", a->rlenmax)); 1454 a->nonzerorowcnt = 0; 1455 /* Set unused slots for column indices to last valid column index. Set unused slots for values to zero. This allows for a use of unmasked intrinsics -> higher performance */ 1456 for (i = 0; i < a->totalslices; ++i) { 1457 shift = a->sliidx[i]; /* starting index of the slice */ 1458 cp = PetscSafePointerPlusOffset(a->colidx, shift); /* pointer to the column indices of the slice */ 1459 vp = PetscSafePointerPlusOffset(a->val, shift); /* pointer to the nonzero values of the slice */ 1460 for (row_in_slice = 0; row_in_slice < a->sliceheight; ++row_in_slice) { /* loop over rows in the slice */ 1461 row = a->sliceheight * i + row_in_slice; 1462 nrow = a->rlen[row]; /* number of nonzeros in row */ 1463 /* 1464 Search for the nearest nonzero. Normally setting the index to zero may cause extra communication. 1465 But if the entire slice are empty, it is fine to use 0 since the index will not be loaded. 1466 */ 1467 lastcol = 0; 1468 if (nrow > 0) { /* nonempty row */ 1469 a->nonzerorowcnt++; 1470 lastcol = cp[a->sliceheight * (nrow - 1) + row_in_slice]; /* use the index from the last nonzero at current row */ 1471 } else if (!row_in_slice) { /* first row of the correct slice is empty */ 1472 for (j = 1; j < a->sliceheight; j++) { 1473 if (a->rlen[a->sliceheight * i + j]) { 1474 lastcol = cp[j]; 1475 break; 1476 } 1477 } 1478 } else { 1479 if (a->sliidx[i + 1] != shift) lastcol = cp[row_in_slice - 1]; /* use the index from the previous row */ 1480 } 1481 1482 for (k = nrow; k < (a->sliidx[i + 1] - shift) / a->sliceheight; ++k) { 1483 cp[a->sliceheight * k + row_in_slice] = lastcol; 1484 vp[a->sliceheight * k + row_in_slice] = (MatScalar)0; 1485 } 1486 } 1487 } 1488 1489 A->info.mallocs += a->reallocs; 1490 a->reallocs = 0; 1491 1492 PetscCall(MatSeqSELLInvalidateDiagonal(A)); 1493 #if defined(PETSC_HAVE_CUPM) 1494 if (!a->chunksize && a->totalslices) { 1495 a->chunksize = 64; 1496 while (a->chunksize < 1024 && 2 * a->chunksize <= a->sliidx[a->totalslices] / a->totalslices) a->chunksize *= 2; 1497 totalchunks = 1 + (a->sliidx[a->totalslices] - 1) / a->chunksize; 1498 } 1499 if (totalchunks != a->totalchunks) { 1500 PetscCall(PetscFree(a->chunk_slice_map)); 1501 PetscCall(PetscMalloc1(totalchunks, &a->chunk_slice_map)); 1502 a->totalchunks = totalchunks; 1503 } 1504 j = 0; 1505 for (i = 0; i < totalchunks; i++) { 1506 while (a->sliidx[j + 1] <= i * a->chunksize && j < a->totalslices) j++; 1507 a->chunk_slice_map[i] = j; 1508 } 1509 #endif 1510 PetscFunctionReturn(PETSC_SUCCESS); 1511 } 1512 1513 PetscErrorCode MatGetInfo_SeqSELL(Mat A, MatInfoType flag, MatInfo *info) 1514 { 1515 Mat_SeqSELL *a = (Mat_SeqSELL *)A->data; 1516 1517 PetscFunctionBegin; 1518 info->block_size = 1.0; 1519 info->nz_allocated = a->maxallocmat; 1520 info->nz_used = a->sliidx[a->totalslices]; /* include padding zeros */ 1521 info->nz_unneeded = (a->maxallocmat - a->sliidx[a->totalslices]); 1522 info->assemblies = A->num_ass; 1523 info->mallocs = A->info.mallocs; 1524 info->memory = 0; /* REVIEW ME */ 1525 if (A->factortype) { 1526 info->fill_ratio_given = A->info.fill_ratio_given; 1527 info->fill_ratio_needed = A->info.fill_ratio_needed; 1528 info->factor_mallocs = A->info.factor_mallocs; 1529 } else { 1530 info->fill_ratio_given = 0; 1531 info->fill_ratio_needed = 0; 1532 info->factor_mallocs = 0; 1533 } 1534 PetscFunctionReturn(PETSC_SUCCESS); 1535 } 1536 1537 PetscErrorCode MatSetValues_SeqSELL(Mat A, PetscInt m, const PetscInt im[], PetscInt n, const PetscInt in[], const PetscScalar v[], InsertMode is) 1538 { 1539 Mat_SeqSELL *a = (Mat_SeqSELL *)A->data; 1540 PetscInt shift, i, k, l, low, high, t, ii, row, col, nrow; 1541 PetscInt *cp, nonew = a->nonew, lastcol = -1; 1542 MatScalar *vp, value; 1543 #if defined(PETSC_HAVE_CUPM) 1544 PetscBool inserted = PETSC_FALSE; 1545 PetscInt mul = DEVICE_MEM_ALIGN / a->sliceheight; 1546 #endif 1547 1548 PetscFunctionBegin; 1549 for (k = 0; k < m; k++) { /* loop over added rows */ 1550 row = im[k]; 1551 if (row < 0) continue; 1552 PetscCheck(row < A->rmap->n, PETSC_COMM_SELF, PETSC_ERR_ARG_OUTOFRANGE, "Row too large: row %" PetscInt_FMT " max %" PetscInt_FMT, row, A->rmap->n - 1); 1553 shift = a->sliidx[row / a->sliceheight] + row % a->sliceheight; /* starting index of the row */ 1554 cp = a->colidx + shift; /* pointer to the row */ 1555 vp = a->val + shift; /* pointer to the row */ 1556 nrow = a->rlen[row]; 1557 low = 0; 1558 high = nrow; 1559 1560 for (l = 0; l < n; l++) { /* loop over added columns */ 1561 col = in[l]; 1562 if (col < 0) continue; 1563 PetscCheck(col < A->cmap->n, PETSC_COMM_SELF, PETSC_ERR_ARG_OUTOFRANGE, "Col too large: row %" PetscInt_FMT " max %" PetscInt_FMT, col, A->cmap->n - 1); 1564 if (a->roworiented) { 1565 value = v[l + k * n]; 1566 } else { 1567 value = v[k + l * m]; 1568 } 1569 if ((value == 0.0 && a->ignorezeroentries) && (is == ADD_VALUES)) continue; 1570 1571 /* search in this row for the specified column, i indicates the column to be set */ 1572 if (col <= lastcol) low = 0; 1573 else high = nrow; 1574 lastcol = col; 1575 while (high - low > 5) { 1576 t = (low + high) / 2; 1577 if (*(cp + a->sliceheight * t) > col) high = t; 1578 else low = t; 1579 } 1580 for (i = low; i < high; i++) { 1581 if (*(cp + a->sliceheight * i) > col) break; 1582 if (*(cp + a->sliceheight * i) == col) { 1583 if (is == ADD_VALUES) *(vp + a->sliceheight * i) += value; 1584 else *(vp + a->sliceheight * i) = value; 1585 #if defined(PETSC_HAVE_CUPM) 1586 inserted = PETSC_TRUE; 1587 #endif 1588 low = i + 1; 1589 goto noinsert; 1590 } 1591 } 1592 if (value == 0.0 && a->ignorezeroentries) goto noinsert; 1593 if (nonew == 1) goto noinsert; 1594 PetscCheck(nonew != -1, PETSC_COMM_SELF, PETSC_ERR_ARG_OUTOFRANGE, "Inserting a new nonzero (%" PetscInt_FMT ", %" PetscInt_FMT ") in the matrix", row, col); 1595 #if defined(PETSC_HAVE_CUPM) 1596 MatSeqXSELLReallocateSELL(A, A->rmap->n, 1, nrow, a->sliidx, a->sliceheight, row / a->sliceheight, row, col, a->colidx, a->val, cp, vp, nonew, MatScalar, mul); 1597 #else 1598 /* If the current row length exceeds the slice width (e.g. nrow==slice_width), allocate a new space, otherwise do nothing */ 1599 MatSeqXSELLReallocateSELL(A, A->rmap->n, 1, nrow, a->sliidx, a->sliceheight, row / a->sliceheight, row, col, a->colidx, a->val, cp, vp, nonew, MatScalar, 1); 1600 #endif 1601 /* add the new nonzero to the high position, shift the remaining elements in current row to the right by one slot */ 1602 for (ii = nrow - 1; ii >= i; ii--) { 1603 *(cp + a->sliceheight * (ii + 1)) = *(cp + a->sliceheight * ii); 1604 *(vp + a->sliceheight * (ii + 1)) = *(vp + a->sliceheight * ii); 1605 } 1606 a->rlen[row]++; 1607 *(cp + a->sliceheight * i) = col; 1608 *(vp + a->sliceheight * i) = value; 1609 a->nz++; 1610 A->nonzerostate++; 1611 #if defined(PETSC_HAVE_CUPM) 1612 inserted = PETSC_TRUE; 1613 #endif 1614 low = i + 1; 1615 high++; 1616 nrow++; 1617 noinsert:; 1618 } 1619 a->rlen[row] = nrow; 1620 } 1621 #if defined(PETSC_HAVE_CUPM) 1622 if (A->offloadmask != PETSC_OFFLOAD_UNALLOCATED && inserted) A->offloadmask = PETSC_OFFLOAD_CPU; 1623 #endif 1624 PetscFunctionReturn(PETSC_SUCCESS); 1625 } 1626 1627 PetscErrorCode MatCopy_SeqSELL(Mat A, Mat B, MatStructure str) 1628 { 1629 PetscFunctionBegin; 1630 /* If the two matrices have the same copy implementation, use fast copy. */ 1631 if (str == SAME_NONZERO_PATTERN && (A->ops->copy == B->ops->copy)) { 1632 Mat_SeqSELL *a = (Mat_SeqSELL *)A->data; 1633 Mat_SeqSELL *b = (Mat_SeqSELL *)B->data; 1634 1635 PetscCheck(a->sliidx[a->totalslices] == b->sliidx[b->totalslices], PETSC_COMM_SELF, PETSC_ERR_ARG_INCOMP, "Number of nonzeros in two matrices are different"); 1636 PetscCall(PetscArraycpy(b->val, a->val, a->sliidx[a->totalslices])); 1637 } else { 1638 PetscCall(MatCopy_Basic(A, B, str)); 1639 } 1640 PetscFunctionReturn(PETSC_SUCCESS); 1641 } 1642 1643 PetscErrorCode MatSetUp_SeqSELL(Mat A) 1644 { 1645 PetscFunctionBegin; 1646 PetscCall(MatSeqSELLSetPreallocation(A, PETSC_DEFAULT, NULL)); 1647 PetscFunctionReturn(PETSC_SUCCESS); 1648 } 1649 1650 PetscErrorCode MatSeqSELLGetArray_SeqSELL(Mat A, PetscScalar *array[]) 1651 { 1652 Mat_SeqSELL *a = (Mat_SeqSELL *)A->data; 1653 1654 PetscFunctionBegin; 1655 *array = a->val; 1656 PetscFunctionReturn(PETSC_SUCCESS); 1657 } 1658 1659 PetscErrorCode MatSeqSELLRestoreArray_SeqSELL(Mat A, PetscScalar *array[]) 1660 { 1661 PetscFunctionBegin; 1662 PetscFunctionReturn(PETSC_SUCCESS); 1663 } 1664 1665 PetscErrorCode MatScale_SeqSELL(Mat inA, PetscScalar alpha) 1666 { 1667 Mat_SeqSELL *a = (Mat_SeqSELL *)inA->data; 1668 MatScalar *aval = a->val; 1669 PetscScalar oalpha = alpha; 1670 PetscBLASInt one = 1, size; 1671 1672 PetscFunctionBegin; 1673 PetscCall(PetscBLASIntCast(a->sliidx[a->totalslices], &size)); 1674 PetscCallBLAS("BLASscal", BLASscal_(&size, &oalpha, aval, &one)); 1675 PetscCall(PetscLogFlops(a->nz)); 1676 PetscCall(MatSeqSELLInvalidateDiagonal(inA)); 1677 #if defined(PETSC_HAVE_CUPM) 1678 if (inA->offloadmask != PETSC_OFFLOAD_UNALLOCATED) inA->offloadmask = PETSC_OFFLOAD_CPU; 1679 #endif 1680 PetscFunctionReturn(PETSC_SUCCESS); 1681 } 1682 1683 PetscErrorCode MatShift_SeqSELL(Mat Y, PetscScalar a) 1684 { 1685 Mat_SeqSELL *y = (Mat_SeqSELL *)Y->data; 1686 1687 PetscFunctionBegin; 1688 if (!Y->preallocated || !y->nz) PetscCall(MatSeqSELLSetPreallocation(Y, 1, NULL)); 1689 PetscCall(MatShift_Basic(Y, a)); 1690 PetscFunctionReturn(PETSC_SUCCESS); 1691 } 1692 1693 PetscErrorCode MatSOR_SeqSELL(Mat A, Vec bb, PetscReal omega, MatSORType flag, PetscReal fshift, PetscInt its, PetscInt lits, Vec xx) 1694 { 1695 Mat_SeqSELL *a = (Mat_SeqSELL *)A->data; 1696 PetscScalar *x, sum, *t; 1697 const MatScalar *idiag = NULL, *mdiag; 1698 const PetscScalar *b, *xb; 1699 PetscInt n, m = A->rmap->n, i, j, shift; 1700 const PetscInt *diag; 1701 1702 PetscFunctionBegin; 1703 its = its * lits; 1704 1705 if (fshift != a->fshift || omega != a->omega) a->idiagvalid = PETSC_FALSE; /* must recompute idiag[] */ 1706 if (!a->idiagvalid) PetscCall(MatInvertDiagonal_SeqSELL(A, omega, fshift)); 1707 a->fshift = fshift; 1708 a->omega = omega; 1709 1710 diag = a->diag; 1711 t = a->ssor_work; 1712 idiag = a->idiag; 1713 mdiag = a->mdiag; 1714 1715 PetscCall(VecGetArray(xx, &x)); 1716 PetscCall(VecGetArrayRead(bb, &b)); 1717 /* We count flops by assuming the upper triangular and lower triangular parts have the same number of nonzeros */ 1718 PetscCheck(flag != SOR_APPLY_UPPER, PETSC_COMM_SELF, PETSC_ERR_SUP, "SOR_APPLY_UPPER is not implemented"); 1719 PetscCheck(flag != SOR_APPLY_LOWER, PETSC_COMM_SELF, PETSC_ERR_SUP, "SOR_APPLY_LOWER is not implemented"); 1720 PetscCheck(!(flag & SOR_EISENSTAT), PETSC_COMM_SELF, PETSC_ERR_SUP, "No support yet for Eisenstat"); 1721 1722 if (flag & SOR_ZERO_INITIAL_GUESS) { 1723 if ((flag & SOR_FORWARD_SWEEP) || (flag & SOR_LOCAL_FORWARD_SWEEP)) { 1724 for (i = 0; i < m; i++) { 1725 shift = a->sliidx[i / a->sliceheight] + i % a->sliceheight; /* starting index of the row i */ 1726 sum = b[i]; 1727 n = (diag[i] - shift) / a->sliceheight; 1728 for (j = 0; j < n; j++) sum -= a->val[shift + a->sliceheight * j] * x[a->colidx[shift + a->sliceheight * j]]; 1729 t[i] = sum; 1730 x[i] = sum * idiag[i]; 1731 } 1732 xb = t; 1733 PetscCall(PetscLogFlops(a->nz)); 1734 } else xb = b; 1735 if ((flag & SOR_BACKWARD_SWEEP) || (flag & SOR_LOCAL_BACKWARD_SWEEP)) { 1736 for (i = m - 1; i >= 0; i--) { 1737 shift = a->sliidx[i / a->sliceheight] + i % a->sliceheight; /* starting index of the row i */ 1738 sum = xb[i]; 1739 n = a->rlen[i] - (diag[i] - shift) / a->sliceheight - 1; 1740 for (j = 1; j <= n; j++) sum -= a->val[diag[i] + a->sliceheight * j] * x[a->colidx[diag[i] + a->sliceheight * j]]; 1741 if (xb == b) { 1742 x[i] = sum * idiag[i]; 1743 } else { 1744 x[i] = (1. - omega) * x[i] + sum * idiag[i]; /* omega in idiag */ 1745 } 1746 } 1747 PetscCall(PetscLogFlops(a->nz)); /* assumes 1/2 in upper */ 1748 } 1749 its--; 1750 } 1751 while (its--) { 1752 if ((flag & SOR_FORWARD_SWEEP) || (flag & SOR_LOCAL_FORWARD_SWEEP)) { 1753 for (i = 0; i < m; i++) { 1754 /* lower */ 1755 shift = a->sliidx[i / a->sliceheight] + i % a->sliceheight; /* starting index of the row i */ 1756 sum = b[i]; 1757 n = (diag[i] - shift) / a->sliceheight; 1758 for (j = 0; j < n; j++) sum -= a->val[shift + a->sliceheight * j] * x[a->colidx[shift + a->sliceheight * j]]; 1759 t[i] = sum; /* save application of the lower-triangular part */ 1760 /* upper */ 1761 n = a->rlen[i] - (diag[i] - shift) / a->sliceheight - 1; 1762 for (j = 1; j <= n; j++) sum -= a->val[diag[i] + a->sliceheight * j] * x[a->colidx[diag[i] + a->sliceheight * j]]; 1763 x[i] = (1. - omega) * x[i] + sum * idiag[i]; /* omega in idiag */ 1764 } 1765 xb = t; 1766 PetscCall(PetscLogFlops(2.0 * a->nz)); 1767 } else xb = b; 1768 if ((flag & SOR_BACKWARD_SWEEP) || (flag & SOR_LOCAL_BACKWARD_SWEEP)) { 1769 for (i = m - 1; i >= 0; i--) { 1770 shift = a->sliidx[i / a->sliceheight] + i % a->sliceheight; /* starting index of the row i */ 1771 sum = xb[i]; 1772 if (xb == b) { 1773 /* whole matrix (no checkpointing available) */ 1774 n = a->rlen[i]; 1775 for (j = 0; j < n; j++) sum -= a->val[shift + a->sliceheight * j] * x[a->colidx[shift + a->sliceheight * j]]; 1776 x[i] = (1. - omega) * x[i] + (sum + mdiag[i] * x[i]) * idiag[i]; 1777 } else { /* lower-triangular part has been saved, so only apply upper-triangular */ 1778 n = a->rlen[i] - (diag[i] - shift) / a->sliceheight - 1; 1779 for (j = 1; j <= n; j++) sum -= a->val[diag[i] + a->sliceheight * j] * x[a->colidx[diag[i] + a->sliceheight * j]]; 1780 x[i] = (1. - omega) * x[i] + sum * idiag[i]; /* omega in idiag */ 1781 } 1782 } 1783 if (xb == b) { 1784 PetscCall(PetscLogFlops(2.0 * a->nz)); 1785 } else { 1786 PetscCall(PetscLogFlops(a->nz)); /* assumes 1/2 in upper */ 1787 } 1788 } 1789 } 1790 PetscCall(VecRestoreArray(xx, &x)); 1791 PetscCall(VecRestoreArrayRead(bb, &b)); 1792 PetscFunctionReturn(PETSC_SUCCESS); 1793 } 1794 1795 static struct _MatOps MatOps_Values = {MatSetValues_SeqSELL, 1796 MatGetRow_SeqSELL, 1797 MatRestoreRow_SeqSELL, 1798 MatMult_SeqSELL, 1799 /* 4*/ MatMultAdd_SeqSELL, 1800 MatMultTranspose_SeqSELL, 1801 MatMultTransposeAdd_SeqSELL, 1802 NULL, 1803 NULL, 1804 NULL, 1805 /* 10*/ NULL, 1806 NULL, 1807 NULL, 1808 MatSOR_SeqSELL, 1809 NULL, 1810 /* 15*/ MatGetInfo_SeqSELL, 1811 MatEqual_SeqSELL, 1812 MatGetDiagonal_SeqSELL, 1813 MatDiagonalScale_SeqSELL, 1814 NULL, 1815 /* 20*/ NULL, 1816 MatAssemblyEnd_SeqSELL, 1817 MatSetOption_SeqSELL, 1818 MatZeroEntries_SeqSELL, 1819 /* 24*/ NULL, 1820 NULL, 1821 NULL, 1822 NULL, 1823 NULL, 1824 /* 29*/ MatSetUp_SeqSELL, 1825 NULL, 1826 NULL, 1827 NULL, 1828 NULL, 1829 /* 34*/ MatDuplicate_SeqSELL, 1830 NULL, 1831 NULL, 1832 NULL, 1833 NULL, 1834 /* 39*/ NULL, 1835 NULL, 1836 NULL, 1837 MatGetValues_SeqSELL, 1838 MatCopy_SeqSELL, 1839 /* 44*/ NULL, 1840 MatScale_SeqSELL, 1841 MatShift_SeqSELL, 1842 NULL, 1843 NULL, 1844 /* 49*/ NULL, 1845 NULL, 1846 NULL, 1847 NULL, 1848 NULL, 1849 /* 54*/ MatFDColoringCreate_SeqXAIJ, 1850 NULL, 1851 NULL, 1852 NULL, 1853 NULL, 1854 /* 59*/ NULL, 1855 MatDestroy_SeqSELL, 1856 MatView_SeqSELL, 1857 NULL, 1858 NULL, 1859 /* 64*/ NULL, 1860 NULL, 1861 NULL, 1862 NULL, 1863 NULL, 1864 /* 69*/ NULL, 1865 NULL, 1866 NULL, 1867 NULL, 1868 NULL, 1869 /* 74*/ NULL, 1870 MatFDColoringApply_AIJ, /* reuse the FDColoring function for AIJ */ 1871 NULL, 1872 NULL, 1873 NULL, 1874 /* 79*/ NULL, 1875 NULL, 1876 NULL, 1877 NULL, 1878 NULL, 1879 /* 84*/ NULL, 1880 NULL, 1881 NULL, 1882 NULL, 1883 NULL, 1884 /* 89*/ NULL, 1885 NULL, 1886 NULL, 1887 NULL, 1888 NULL, 1889 /* 94*/ NULL, 1890 NULL, 1891 NULL, 1892 NULL, 1893 NULL, 1894 /* 99*/ NULL, 1895 NULL, 1896 NULL, 1897 MatConjugate_SeqSELL, 1898 NULL, 1899 /*104*/ NULL, 1900 NULL, 1901 NULL, 1902 NULL, 1903 NULL, 1904 /*109*/ NULL, 1905 NULL, 1906 NULL, 1907 NULL, 1908 MatMissingDiagonal_SeqSELL, 1909 /*114*/ NULL, 1910 NULL, 1911 NULL, 1912 NULL, 1913 NULL, 1914 /*119*/ NULL, 1915 NULL, 1916 NULL, 1917 NULL, 1918 NULL, 1919 /*124*/ NULL, 1920 NULL, 1921 NULL, 1922 NULL, 1923 NULL, 1924 /*129*/ NULL, 1925 NULL, 1926 NULL, 1927 NULL, 1928 NULL, 1929 /*134*/ NULL, 1930 NULL, 1931 NULL, 1932 NULL, 1933 NULL, 1934 /*139*/ NULL, 1935 NULL, 1936 NULL, 1937 MatFDColoringSetUp_SeqXAIJ, 1938 NULL, 1939 /*144*/ NULL, 1940 NULL, 1941 NULL, 1942 NULL, 1943 NULL, 1944 NULL, 1945 /*150*/ NULL, 1946 NULL, 1947 NULL}; 1948 1949 static PetscErrorCode MatStoreValues_SeqSELL(Mat mat) 1950 { 1951 Mat_SeqSELL *a = (Mat_SeqSELL *)mat->data; 1952 1953 PetscFunctionBegin; 1954 PetscCheck(a->nonew, PETSC_COMM_SELF, PETSC_ERR_ORDER, "Must call MatSetOption(A,MAT_NEW_NONZERO_LOCATIONS,PETSC_FALSE);first"); 1955 1956 /* allocate space for values if not already there */ 1957 if (!a->saved_values) PetscCall(PetscMalloc1(a->sliidx[a->totalslices] + 1, &a->saved_values)); 1958 1959 /* copy values over */ 1960 PetscCall(PetscArraycpy(a->saved_values, a->val, a->sliidx[a->totalslices])); 1961 PetscFunctionReturn(PETSC_SUCCESS); 1962 } 1963 1964 static PetscErrorCode MatRetrieveValues_SeqSELL(Mat mat) 1965 { 1966 Mat_SeqSELL *a = (Mat_SeqSELL *)mat->data; 1967 1968 PetscFunctionBegin; 1969 PetscCheck(a->nonew, PETSC_COMM_SELF, PETSC_ERR_ORDER, "Must call MatSetOption(A,MAT_NEW_NONZERO_LOCATIONS,PETSC_FALSE);first"); 1970 PetscCheck(a->saved_values, PETSC_COMM_SELF, PETSC_ERR_ORDER, "Must call MatStoreValues(A);first"); 1971 PetscCall(PetscArraycpy(a->val, a->saved_values, a->sliidx[a->totalslices])); 1972 PetscFunctionReturn(PETSC_SUCCESS); 1973 } 1974 1975 static PetscErrorCode MatSeqSELLGetFillRatio_SeqSELL(Mat mat, PetscReal *ratio) 1976 { 1977 Mat_SeqSELL *a = (Mat_SeqSELL *)mat->data; 1978 1979 PetscFunctionBegin; 1980 if (a->totalslices && a->sliidx[a->totalslices]) { 1981 *ratio = (PetscReal)(a->sliidx[a->totalslices] - a->nz) / a->sliidx[a->totalslices]; 1982 } else { 1983 *ratio = 0.0; 1984 } 1985 PetscFunctionReturn(PETSC_SUCCESS); 1986 } 1987 1988 static PetscErrorCode MatSeqSELLGetMaxSliceWidth_SeqSELL(Mat mat, PetscInt *slicewidth) 1989 { 1990 Mat_SeqSELL *a = (Mat_SeqSELL *)mat->data; 1991 PetscInt i, current_slicewidth; 1992 1993 PetscFunctionBegin; 1994 *slicewidth = 0; 1995 for (i = 0; i < a->totalslices; i++) { 1996 current_slicewidth = (a->sliidx[i + 1] - a->sliidx[i]) / a->sliceheight; 1997 if (current_slicewidth > *slicewidth) *slicewidth = current_slicewidth; 1998 } 1999 PetscFunctionReturn(PETSC_SUCCESS); 2000 } 2001 2002 static PetscErrorCode MatSeqSELLGetAvgSliceWidth_SeqSELL(Mat mat, PetscReal *slicewidth) 2003 { 2004 Mat_SeqSELL *a = (Mat_SeqSELL *)mat->data; 2005 2006 PetscFunctionBegin; 2007 *slicewidth = 0; 2008 if (a->totalslices) { *slicewidth = (PetscReal)a->sliidx[a->totalslices] / a->sliceheight / a->totalslices; } 2009 PetscFunctionReturn(PETSC_SUCCESS); 2010 } 2011 2012 static PetscErrorCode MatSeqSELLGetVarSliceSize_SeqSELL(Mat mat, PetscReal *variance) 2013 { 2014 Mat_SeqSELL *a = (Mat_SeqSELL *)mat->data; 2015 PetscReal mean; 2016 PetscInt i, totalslices = a->totalslices, *sliidx = a->sliidx; 2017 2018 PetscFunctionBegin; 2019 *variance = 0; 2020 if (totalslices) { 2021 mean = (PetscReal)sliidx[totalslices] / totalslices; 2022 for (i = 1; i <= totalslices; i++) { *variance += ((PetscReal)(sliidx[i] - sliidx[i - 1]) - mean) * ((PetscReal)(sliidx[i] - sliidx[i - 1]) - mean) / totalslices; } 2023 } 2024 PetscFunctionReturn(PETSC_SUCCESS); 2025 } 2026 2027 static PetscErrorCode MatSeqSELLSetSliceHeight_SeqSELL(Mat A, PetscInt sliceheight) 2028 { 2029 Mat_SeqSELL *a = (Mat_SeqSELL *)A->data; 2030 2031 PetscFunctionBegin; 2032 if (A->preallocated) PetscFunctionReturn(PETSC_SUCCESS); 2033 PetscCheck(a->sliceheight <= 0 || a->sliceheight == sliceheight, PETSC_COMM_SELF, PETSC_ERR_SUP, "Cannot change slice height %" PetscInt_FMT " to %" PetscInt_FMT, a->sliceheight, sliceheight); 2034 a->sliceheight = sliceheight; 2035 #if defined(PETSC_HAVE_CUPM) 2036 PetscCheck(PetscMax(DEVICE_MEM_ALIGN, sliceheight) % PetscMin(DEVICE_MEM_ALIGN, sliceheight) == 0, PETSC_COMM_SELF, PETSC_ERR_SUP, "The slice height is not compatible with DEVICE_MEM_ALIGN (one must be divisible by the other) %" PetscInt_FMT, sliceheight); 2037 #endif 2038 PetscFunctionReturn(PETSC_SUCCESS); 2039 } 2040 2041 /*@ 2042 MatSeqSELLGetFillRatio - returns a ratio that indicates the irregularity of the matrix. 2043 2044 Not Collective 2045 2046 Input Parameter: 2047 . A - a MATSEQSELL matrix 2048 2049 Output Parameter: 2050 . ratio - ratio of number of padded zeros to number of allocated elements 2051 2052 Level: intermediate 2053 2054 .seealso: `MATSEQSELL`, `MatSeqSELLGetAvgSliceWidth()` 2055 @*/ 2056 PetscErrorCode MatSeqSELLGetFillRatio(Mat A, PetscReal *ratio) 2057 { 2058 PetscFunctionBegin; 2059 PetscUseMethod(A, "MatSeqSELLGetFillRatio_C", (Mat, PetscReal *), (A, ratio)); 2060 PetscFunctionReturn(PETSC_SUCCESS); 2061 } 2062 2063 /*@ 2064 MatSeqSELLGetMaxSliceWidth - returns the maximum slice width. 2065 2066 Not Collective 2067 2068 Input Parameter: 2069 . A - a MATSEQSELL matrix 2070 2071 Output Parameter: 2072 . slicewidth - maximum slice width 2073 2074 Level: intermediate 2075 2076 .seealso: `MATSEQSELL`, `MatSeqSELLGetAvgSliceWidth()` 2077 @*/ 2078 PetscErrorCode MatSeqSELLGetMaxSliceWidth(Mat A, PetscInt *slicewidth) 2079 { 2080 PetscFunctionBegin; 2081 PetscUseMethod(A, "MatSeqSELLGetMaxSliceWidth_C", (Mat, PetscInt *), (A, slicewidth)); 2082 PetscFunctionReturn(PETSC_SUCCESS); 2083 } 2084 2085 /*@ 2086 MatSeqSELLGetAvgSliceWidth - returns the average slice width. 2087 2088 Not Collective 2089 2090 Input Parameter: 2091 . A - a MATSEQSELL matrix 2092 2093 Output Parameter: 2094 . slicewidth - average slice width 2095 2096 Level: intermediate 2097 2098 .seealso: `MATSEQSELL`, `MatSeqSELLGetMaxSliceWidth()` 2099 @*/ 2100 PetscErrorCode MatSeqSELLGetAvgSliceWidth(Mat A, PetscReal *slicewidth) 2101 { 2102 PetscFunctionBegin; 2103 PetscUseMethod(A, "MatSeqSELLGetAvgSliceWidth_C", (Mat, PetscReal *), (A, slicewidth)); 2104 PetscFunctionReturn(PETSC_SUCCESS); 2105 } 2106 2107 /*@ 2108 MatSeqSELLSetSliceHeight - sets the slice height. 2109 2110 Not Collective 2111 2112 Input Parameters: 2113 + A - a MATSEQSELL matrix 2114 - sliceheight - slice height 2115 2116 Notes: 2117 You cannot change the slice height once it have been set. 2118 2119 The slice height must be set before MatSetUp() or MatXXXSetPreallocation() is called. 2120 2121 Level: intermediate 2122 2123 .seealso: `MATSEQSELL`, `MatSeqSELLGetVarSliceSize()` 2124 @*/ 2125 PetscErrorCode MatSeqSELLSetSliceHeight(Mat A, PetscInt sliceheight) 2126 { 2127 PetscFunctionBegin; 2128 PetscUseMethod(A, "MatSeqSELLSetSliceHeight_C", (Mat, PetscInt), (A, sliceheight)); 2129 PetscFunctionReturn(PETSC_SUCCESS); 2130 } 2131 2132 /*@ 2133 MatSeqSELLGetVarSliceSize - returns the variance of the slice size. 2134 2135 Not Collective 2136 2137 Input Parameter: 2138 . A - a MATSEQSELL matrix 2139 2140 Output Parameter: 2141 . variance - variance of the slice size 2142 2143 Level: intermediate 2144 2145 .seealso: `MATSEQSELL`, `MatSeqSELLSetSliceHeight()` 2146 @*/ 2147 PetscErrorCode MatSeqSELLGetVarSliceSize(Mat A, PetscReal *variance) 2148 { 2149 PetscFunctionBegin; 2150 PetscUseMethod(A, "MatSeqSELLGetVarSliceSize_C", (Mat, PetscReal *), (A, variance)); 2151 PetscFunctionReturn(PETSC_SUCCESS); 2152 } 2153 2154 #if defined(PETSC_HAVE_CUDA) 2155 PETSC_EXTERN PetscErrorCode MatConvert_SeqSELL_SeqSELLCUDA(Mat); 2156 #endif 2157 #if defined(PETSC_HAVE_HIP) 2158 PETSC_EXTERN PetscErrorCode MatConvert_SeqSELL_SeqSELLHIP(Mat); 2159 #endif 2160 2161 PETSC_EXTERN PetscErrorCode MatCreate_SeqSELL(Mat B) 2162 { 2163 Mat_SeqSELL *b; 2164 PetscMPIInt size; 2165 2166 PetscFunctionBegin; 2167 PetscCall(PetscCitationsRegister(citation, &cited)); 2168 PetscCallMPI(MPI_Comm_size(PetscObjectComm((PetscObject)B), &size)); 2169 PetscCheck(size <= 1, PETSC_COMM_SELF, PETSC_ERR_ARG_OUTOFRANGE, "Comm must be of size 1"); 2170 2171 PetscCall(PetscNew(&b)); 2172 2173 B->data = (void *)b; 2174 B->ops[0] = MatOps_Values; 2175 2176 b->row = NULL; 2177 b->col = NULL; 2178 b->icol = NULL; 2179 b->reallocs = 0; 2180 b->ignorezeroentries = PETSC_FALSE; 2181 b->roworiented = PETSC_TRUE; 2182 b->nonew = 0; 2183 b->diag = NULL; 2184 b->solve_work = NULL; 2185 B->spptr = NULL; 2186 b->saved_values = NULL; 2187 b->idiag = NULL; 2188 b->mdiag = NULL; 2189 b->ssor_work = NULL; 2190 b->omega = 1.0; 2191 b->fshift = 0.0; 2192 b->idiagvalid = PETSC_FALSE; 2193 b->keepnonzeropattern = PETSC_FALSE; 2194 b->sliceheight = 0; 2195 2196 PetscCall(PetscObjectChangeTypeName((PetscObject)B, MATSEQSELL)); 2197 PetscCall(PetscObjectComposeFunction((PetscObject)B, "MatSeqSELLGetArray_C", MatSeqSELLGetArray_SeqSELL)); 2198 PetscCall(PetscObjectComposeFunction((PetscObject)B, "MatSeqSELLRestoreArray_C", MatSeqSELLRestoreArray_SeqSELL)); 2199 PetscCall(PetscObjectComposeFunction((PetscObject)B, "MatStoreValues_C", MatStoreValues_SeqSELL)); 2200 PetscCall(PetscObjectComposeFunction((PetscObject)B, "MatRetrieveValues_C", MatRetrieveValues_SeqSELL)); 2201 PetscCall(PetscObjectComposeFunction((PetscObject)B, "MatSeqSELLSetPreallocation_C", MatSeqSELLSetPreallocation_SeqSELL)); 2202 PetscCall(PetscObjectComposeFunction((PetscObject)B, "MatConvert_seqsell_seqaij_C", MatConvert_SeqSELL_SeqAIJ)); 2203 #if defined(PETSC_HAVE_CUDA) 2204 PetscCall(PetscObjectComposeFunction((PetscObject)B, "MatConvert_seqsell_seqsellcuda_C", MatConvert_SeqSELL_SeqSELLCUDA)); 2205 #endif 2206 #if defined(PETSC_HAVE_HIP) 2207 PetscCall(PetscObjectComposeFunction((PetscObject)B, "MatConvert_seqsell_seqsellhip_C", MatConvert_SeqSELL_SeqSELLHIP)); 2208 #endif 2209 PetscCall(PetscObjectComposeFunction((PetscObject)B, "MatSeqSELLGetFillRatio_C", MatSeqSELLGetFillRatio_SeqSELL)); 2210 PetscCall(PetscObjectComposeFunction((PetscObject)B, "MatSeqSELLGetMaxSliceWidth_C", MatSeqSELLGetMaxSliceWidth_SeqSELL)); 2211 PetscCall(PetscObjectComposeFunction((PetscObject)B, "MatSeqSELLGetAvgSliceWidth_C", MatSeqSELLGetAvgSliceWidth_SeqSELL)); 2212 PetscCall(PetscObjectComposeFunction((PetscObject)B, "MatSeqSELLGetVarSliceSize_C", MatSeqSELLGetVarSliceSize_SeqSELL)); 2213 PetscCall(PetscObjectComposeFunction((PetscObject)B, "MatSeqSELLSetSliceHeight_C", MatSeqSELLSetSliceHeight_SeqSELL)); 2214 2215 PetscObjectOptionsBegin((PetscObject)B); 2216 { 2217 PetscInt newsh = -1; 2218 PetscBool flg; 2219 #if defined(PETSC_HAVE_CUPM) 2220 PetscInt chunksize = 0; 2221 #endif 2222 2223 PetscCall(PetscOptionsInt("-mat_sell_slice_height", "Set the slice height used to store SELL matrix", "MatSELLSetSliceHeight", newsh, &newsh, &flg)); 2224 if (flg) { PetscCall(MatSeqSELLSetSliceHeight(B, newsh)); } 2225 #if defined(PETSC_HAVE_CUPM) 2226 PetscCall(PetscOptionsInt("-mat_sell_chunk_size", "Set the chunksize for load-balanced CUDA/HIP kernels. Choices include 64,128,256,512,1024", NULL, chunksize, &chunksize, &flg)); 2227 if (flg) { 2228 PetscCheck(chunksize >= 64 && chunksize <= 1024 && chunksize % 64 == 0, PETSC_COMM_SELF, PETSC_ERR_ARG_WRONG, "chunksize must be a number in {64,128,256,512,1024}: value %" PetscInt_FMT, chunksize); 2229 b->chunksize = chunksize; 2230 } 2231 #endif 2232 } 2233 PetscOptionsEnd(); 2234 PetscFunctionReturn(PETSC_SUCCESS); 2235 } 2236 2237 /* 2238 Given a matrix generated with MatGetFactor() duplicates all the information in A into B 2239 */ 2240 static PetscErrorCode MatDuplicateNoCreate_SeqSELL(Mat C, Mat A, MatDuplicateOption cpvalues, PetscBool mallocmatspace) 2241 { 2242 Mat_SeqSELL *c = (Mat_SeqSELL *)C->data, *a = (Mat_SeqSELL *)A->data; 2243 PetscInt i, m = A->rmap->n; 2244 PetscInt totalslices = a->totalslices; 2245 2246 PetscFunctionBegin; 2247 C->factortype = A->factortype; 2248 c->row = NULL; 2249 c->col = NULL; 2250 c->icol = NULL; 2251 c->reallocs = 0; 2252 C->assembled = PETSC_TRUE; 2253 2254 PetscCall(PetscLayoutReference(A->rmap, &C->rmap)); 2255 PetscCall(PetscLayoutReference(A->cmap, &C->cmap)); 2256 2257 c->sliceheight = a->sliceheight; 2258 PetscCall(PetscMalloc1(c->sliceheight * totalslices, &c->rlen)); 2259 PetscCall(PetscMalloc1(totalslices + 1, &c->sliidx)); 2260 2261 for (i = 0; i < m; i++) c->rlen[i] = a->rlen[i]; 2262 for (i = 0; i < totalslices + 1; i++) c->sliidx[i] = a->sliidx[i]; 2263 2264 /* allocate the matrix space */ 2265 if (mallocmatspace) { 2266 PetscCall(PetscMalloc2(a->maxallocmat, &c->val, a->maxallocmat, &c->colidx)); 2267 2268 c->singlemalloc = PETSC_TRUE; 2269 2270 if (m > 0) { 2271 PetscCall(PetscArraycpy(c->colidx, a->colidx, a->maxallocmat)); 2272 if (cpvalues == MAT_COPY_VALUES) { 2273 PetscCall(PetscArraycpy(c->val, a->val, a->maxallocmat)); 2274 } else { 2275 PetscCall(PetscArrayzero(c->val, a->maxallocmat)); 2276 } 2277 } 2278 } 2279 2280 c->ignorezeroentries = a->ignorezeroentries; 2281 c->roworiented = a->roworiented; 2282 c->nonew = a->nonew; 2283 if (a->diag) { 2284 PetscCall(PetscMalloc1(m, &c->diag)); 2285 for (i = 0; i < m; i++) c->diag[i] = a->diag[i]; 2286 } else c->diag = NULL; 2287 2288 c->solve_work = NULL; 2289 c->saved_values = NULL; 2290 c->idiag = NULL; 2291 c->ssor_work = NULL; 2292 c->keepnonzeropattern = a->keepnonzeropattern; 2293 c->free_val = PETSC_TRUE; 2294 c->free_colidx = PETSC_TRUE; 2295 2296 c->maxallocmat = a->maxallocmat; 2297 c->maxallocrow = a->maxallocrow; 2298 c->rlenmax = a->rlenmax; 2299 c->nz = a->nz; 2300 C->preallocated = PETSC_TRUE; 2301 2302 c->nonzerorowcnt = a->nonzerorowcnt; 2303 C->nonzerostate = A->nonzerostate; 2304 2305 PetscCall(PetscFunctionListDuplicate(((PetscObject)A)->qlist, &((PetscObject)C)->qlist)); 2306 PetscFunctionReturn(PETSC_SUCCESS); 2307 } 2308 2309 PetscErrorCode MatDuplicate_SeqSELL(Mat A, MatDuplicateOption cpvalues, Mat *B) 2310 { 2311 PetscFunctionBegin; 2312 PetscCall(MatCreate(PetscObjectComm((PetscObject)A), B)); 2313 PetscCall(MatSetSizes(*B, A->rmap->n, A->cmap->n, A->rmap->n, A->cmap->n)); 2314 if (!(A->rmap->n % A->rmap->bs) && !(A->cmap->n % A->cmap->bs)) PetscCall(MatSetBlockSizesFromMats(*B, A, A)); 2315 PetscCall(MatSetType(*B, ((PetscObject)A)->type_name)); 2316 PetscCall(MatDuplicateNoCreate_SeqSELL(*B, A, cpvalues, PETSC_TRUE)); 2317 PetscFunctionReturn(PETSC_SUCCESS); 2318 } 2319 2320 /*MC 2321 MATSEQSELL - MATSEQSELL = "seqsell" - A matrix type to be used for sequential sparse matrices, 2322 based on the sliced Ellpack format, {cite}`zhangellpack2018` 2323 2324 Options Database Key: 2325 . -mat_type seqsell - sets the matrix type to "`MATSEQELL` during a call to `MatSetFromOptions()` 2326 2327 Level: beginner 2328 2329 .seealso: `Mat`, `MatCreateSeqSell()`, `MATSELL`, `MATMPISELL`, `MATSEQAIJ`, `MATAIJ`, `MATMPIAIJ` 2330 M*/ 2331 2332 /*MC 2333 MATSELL - MATSELL = "sell" - A matrix type to be used for sparse matrices, {cite}`zhangellpack2018` 2334 2335 This matrix type is identical to `MATSEQSELL` when constructed with a single process communicator, 2336 and `MATMPISELL` otherwise. As a result, for single process communicators, 2337 `MatSeqSELLSetPreallocation()` is supported, and similarly `MatMPISELLSetPreallocation()` is supported 2338 for communicators controlling multiple processes. It is recommended that you call both of 2339 the above preallocation routines for simplicity. 2340 2341 Options Database Key: 2342 . -mat_type sell - sets the matrix type to "sell" during a call to MatSetFromOptions() 2343 2344 Level: beginner 2345 2346 Notes: 2347 This format is only supported for real scalars, double precision, and 32-bit indices (the defaults). 2348 2349 It can provide better performance on Intel and AMD processes with AVX2 or AVX512 support for matrices that have a similar number of 2350 non-zeros in contiguous groups of rows. However if the computation is memory bandwidth limited it may not provide much improvement. 2351 2352 Developer Notes: 2353 On Intel (and AMD) systems some of the matrix operations use SIMD (AVX) instructions to achieve higher performance. 2354 2355 The sparse matrix format is as follows. For simplicity we assume a slice size of 2, it is actually 8 2356 .vb 2357 (2 0 3 4) 2358 Consider the matrix A = (5 0 6 0) 2359 (0 0 7 8) 2360 (0 0 9 9) 2361 2362 symbolically the Ellpack format can be written as 2363 2364 (2 3 4 |) (0 2 3 |) 2365 v = (5 6 0 |) colidx = (0 2 2 |) 2366 -------- --------- 2367 (7 8 |) (2 3 |) 2368 (9 9 |) (2 3 |) 2369 2370 The data for 2 contiguous rows of the matrix are stored together (in column-major format) (with any left-over rows handled as a special case). 2371 Any of the rows in a slice fewer columns than the rest of the slice (row 1 above) are padded with a previous valid column in their "extra" colidx[] locations and 2372 zeros in their "extra" v locations so that the matrix operations do not need special code to handle different length rows within the 2 rows in a slice. 2373 2374 The one-dimensional representation of v used in the code is (2 5 3 6 4 0 7 9 8 9) and for colidx is (0 0 2 2 3 2 2 2 3 3) 2375 2376 .ve 2377 2378 See `MatMult_SeqSELL()` for how this format is used with the SIMD operations to achieve high performance. 2379 2380 .seealso: `Mat`, `MatCreateSeqSELL()`, `MatCreateSeqAIJ()`, `MatCreateSell()`, `MATSEQSELL`, `MATMPISELL`, `MATSEQAIJ`, `MATMPIAIJ`, `MATAIJ` 2381 M*/ 2382 2383 /*@C 2384 MatCreateSeqSELL - Creates a sparse matrix in `MATSEQSELL` format. 2385 2386 Collective 2387 2388 Input Parameters: 2389 + comm - MPI communicator, set to `PETSC_COMM_SELF` 2390 . m - number of rows 2391 . n - number of columns 2392 . rlenmax - maximum number of nonzeros in a row, ignored if `rlen` is provided 2393 - rlen - array containing the number of nonzeros in the various rows (possibly different for each row) or NULL 2394 2395 Output Parameter: 2396 . A - the matrix 2397 2398 Level: intermediate 2399 2400 Notes: 2401 It is recommended that one use the `MatCreate()`, `MatSetType()` and/or `MatSetFromOptions()`, 2402 MatXXXXSetPreallocation() paradigm instead of this routine directly. 2403 [MatXXXXSetPreallocation() is, for example, `MatSeqSELLSetPreallocation()`] 2404 2405 Specify the preallocated storage with either `rlenmax` or `rlen` (not both). 2406 Set `rlenmax` = `PETSC_DEFAULT` and `rlen` = `NULL` for PETSc to control dynamic memory 2407 allocation. 2408 2409 .seealso: `Mat`, `MATSEQSELL`, `MatCreate()`, `MatCreateSELL()`, `MatSetValues()`, `MatSeqSELLSetPreallocation()`, `MATSELL`, `MATMPISELL` 2410 @*/ 2411 PetscErrorCode MatCreateSeqSELL(MPI_Comm comm, PetscInt m, PetscInt n, PetscInt rlenmax, const PetscInt rlen[], Mat *A) 2412 { 2413 PetscFunctionBegin; 2414 PetscCall(MatCreate(comm, A)); 2415 PetscCall(MatSetSizes(*A, m, n, m, n)); 2416 PetscCall(MatSetType(*A, MATSEQSELL)); 2417 PetscCall(MatSeqSELLSetPreallocation_SeqSELL(*A, rlenmax, rlen)); 2418 PetscFunctionReturn(PETSC_SUCCESS); 2419 } 2420 2421 PetscErrorCode MatEqual_SeqSELL(Mat A, Mat B, PetscBool *flg) 2422 { 2423 Mat_SeqSELL *a = (Mat_SeqSELL *)A->data, *b = (Mat_SeqSELL *)B->data; 2424 PetscInt totalslices = a->totalslices; 2425 2426 PetscFunctionBegin; 2427 /* If the matrix dimensions are not equal,or no of nonzeros */ 2428 if ((A->rmap->n != B->rmap->n) || (A->cmap->n != B->cmap->n) || (a->nz != b->nz) || (a->rlenmax != b->rlenmax)) { 2429 *flg = PETSC_FALSE; 2430 PetscFunctionReturn(PETSC_SUCCESS); 2431 } 2432 /* if the a->colidx are the same */ 2433 PetscCall(PetscArraycmp(a->colidx, b->colidx, a->sliidx[totalslices], flg)); 2434 if (!*flg) PetscFunctionReturn(PETSC_SUCCESS); 2435 /* if a->val are the same */ 2436 PetscCall(PetscArraycmp(a->val, b->val, a->sliidx[totalslices], flg)); 2437 PetscFunctionReturn(PETSC_SUCCESS); 2438 } 2439 2440 PetscErrorCode MatSeqSELLInvalidateDiagonal(Mat A) 2441 { 2442 Mat_SeqSELL *a = (Mat_SeqSELL *)A->data; 2443 2444 PetscFunctionBegin; 2445 a->idiagvalid = PETSC_FALSE; 2446 PetscFunctionReturn(PETSC_SUCCESS); 2447 } 2448 2449 PetscErrorCode MatConjugate_SeqSELL(Mat A) 2450 { 2451 #if defined(PETSC_USE_COMPLEX) 2452 Mat_SeqSELL *a = (Mat_SeqSELL *)A->data; 2453 PetscInt i; 2454 PetscScalar *val = a->val; 2455 2456 PetscFunctionBegin; 2457 for (i = 0; i < a->sliidx[a->totalslices]; i++) { val[i] = PetscConj(val[i]); } 2458 #if defined(PETSC_HAVE_CUPM) 2459 if (A->offloadmask != PETSC_OFFLOAD_UNALLOCATED) A->offloadmask = PETSC_OFFLOAD_CPU; 2460 #endif 2461 #else 2462 PetscFunctionBegin; 2463 #endif 2464 PetscFunctionReturn(PETSC_SUCCESS); 2465 } 2466