1 static char help[] = "Tests MatSolve() and MatMatSolve() (interface to superlu_dist, mumps and mkl_pardiso).\n\ 2 Example: mpiexec -n <np> ./ex125 -f <matrix binary file> -nrhs 4 -mat_solver_type <>\n\n"; 3 4 /* 5 -mat_solver_type: 6 superlu 7 superlu_dist 8 mumps 9 mkl_pardiso 10 cusparse 11 petsc 12 */ 13 14 #include <petscmat.h> 15 16 int main(int argc, char **args) 17 { 18 Mat A, RHS = NULL, RHS1 = NULL, C, F, X; 19 Vec u, x, b; 20 PetscMPIInt size; 21 PetscInt m, n, nfact, nsolve, nrhs, ipack = 5; 22 PetscReal norm, tol = 1.e-10; 23 IS perm, iperm; 24 MatFactorInfo info; 25 PetscRandom rand; 26 PetscBool flg, symm, testMatSolve = PETSC_TRUE, testMatMatSolve = PETSC_TRUE, testMatMatSolveTranspose = PETSC_TRUE, testMatSolveTranspose = PETSC_TRUE, match = PETSC_FALSE; 27 PetscBool chol = PETSC_FALSE, view = PETSC_FALSE, matsolvexx = PETSC_FALSE; 28 #if defined(PETSC_HAVE_MUMPS) 29 PetscBool test_mumps_opts = PETSC_FALSE; 30 #endif 31 PetscViewer fd; /* viewer */ 32 char file[PETSC_MAX_PATH_LEN]; /* input file name */ 33 char pack[PETSC_MAX_PATH_LEN]; 34 35 PetscFunctionBeginUser; 36 PetscCall(PetscInitialize(&argc, &args, (char *)0, help)); 37 PetscCallMPI(MPI_Comm_size(PETSC_COMM_WORLD, &size)); 38 39 /* Determine file from which we read the matrix A */ 40 PetscCall(PetscOptionsGetString(NULL, NULL, "-f", file, sizeof(file), &flg)); 41 if (flg) { /* Load matrix A */ 42 PetscCall(PetscViewerBinaryOpen(PETSC_COMM_WORLD, file, FILE_MODE_READ, &fd)); 43 PetscCall(MatCreate(PETSC_COMM_WORLD, &A)); 44 PetscCall(MatSetFromOptions(A)); 45 PetscCall(MatLoad(A, fd)); 46 PetscCall(PetscViewerDestroy(&fd)); 47 } else { 48 n = 13; 49 PetscCall(PetscOptionsGetInt(NULL, NULL, "-n", &n, NULL)); 50 PetscCall(MatCreate(PETSC_COMM_WORLD, &A)); 51 PetscCall(MatSetType(A, MATAIJ)); 52 PetscCall(MatSetFromOptions(A)); 53 PetscCall(MatSetSizes(A, PETSC_DECIDE, PETSC_DECIDE, n, n)); 54 PetscCall(MatSetUp(A)); 55 PetscCall(MatAssemblyBegin(A, MAT_FINAL_ASSEMBLY)); 56 PetscCall(MatAssemblyEnd(A, MAT_FINAL_ASSEMBLY)); 57 PetscCall(MatShift(A, 1.0)); 58 } 59 PetscCall(MatGetLocalSize(A, &m, &n)); 60 PetscCheck(m == n, PETSC_COMM_SELF, PETSC_ERR_ARG_SIZ, "This example is not intended for rectangular matrices (%" PetscInt_FMT ", %" PetscInt_FMT ")", m, n); 61 62 /* if A is symmetric, set its flag -- required by MatGetInertia() */ 63 PetscCall(MatIsSymmetric(A, 0.0, &symm)); 64 PetscCall(MatSetOption(A, MAT_SYMMETRIC, symm)); 65 66 PetscCall(MatViewFromOptions(A, NULL, "-A_view")); 67 68 /* Create dense matrix C and X; C holds true solution with identical columns */ 69 nrhs = 2; 70 PetscCall(PetscOptionsGetInt(NULL, NULL, "-nrhs", &nrhs, NULL)); 71 PetscCall(PetscPrintf(PETSC_COMM_WORLD, "ex125: nrhs %" PetscInt_FMT "\n", nrhs)); 72 PetscCall(MatCreate(PETSC_COMM_WORLD, &C)); 73 PetscCall(MatSetOptionsPrefix(C, "rhs_")); 74 PetscCall(MatSetSizes(C, m, PETSC_DECIDE, PETSC_DECIDE, nrhs)); 75 PetscCall(MatSetType(C, MATDENSE)); 76 PetscCall(MatSetFromOptions(C)); 77 PetscCall(MatSetUp(C)); 78 79 PetscCall(PetscOptionsGetBool(NULL, NULL, "-view_factor", &view, NULL)); 80 PetscCall(PetscOptionsGetBool(NULL, NULL, "-test_matmatsolve", &testMatMatSolve, NULL)); 81 PetscCall(PetscOptionsGetBool(NULL, NULL, "-test_matmatsolvetranspose", &testMatMatSolveTranspose, NULL)); 82 PetscCall(PetscOptionsGetBool(NULL, NULL, "-test_matsolvetranspose", &testMatSolveTranspose, NULL)); 83 PetscCall(PetscOptionsGetBool(NULL, NULL, "-cholesky", &chol, NULL)); 84 #if defined(PETSC_HAVE_MUMPS) 85 PetscCall(PetscOptionsGetBool(NULL, NULL, "-test_mumps_opts", &test_mumps_opts, NULL)); 86 #endif 87 88 PetscCall(PetscRandomCreate(PETSC_COMM_WORLD, &rand)); 89 PetscCall(PetscRandomSetFromOptions(rand)); 90 PetscCall(MatSetRandom(C, rand)); 91 PetscCall(MatDuplicate(C, MAT_DO_NOT_COPY_VALUES, &X)); 92 93 /* Create vectors */ 94 PetscCall(MatCreateVecs(A, &x, &b)); 95 PetscCall(VecDuplicate(x, &u)); /* save the true solution */ 96 97 /* Test Factorization */ 98 PetscCall(MatGetOrdering(A, MATORDERINGND, &perm, &iperm)); 99 100 PetscCall(PetscOptionsGetString(NULL, NULL, "-mat_solver_type", pack, sizeof(pack), NULL)); 101 #if defined(PETSC_HAVE_SUPERLU) 102 PetscCall(PetscStrcmp(MATSOLVERSUPERLU, pack, &match)); 103 if (match) { 104 PetscCheck(!chol, PETSC_COMM_WORLD, PETSC_ERR_SUP, "SuperLU does not provide Cholesky!"); 105 PetscCall(PetscPrintf(PETSC_COMM_WORLD, " SUPERLU LU:\n")); 106 PetscCall(MatGetFactor(A, MATSOLVERSUPERLU, MAT_FACTOR_LU, &F)); 107 matsolvexx = PETSC_FALSE; /* Test MatMatSolve(F,RHS,RHS), RHS is a dense matrix, need further work */ 108 ipack = 0; 109 goto skipoptions; 110 } 111 #endif 112 #if defined(PETSC_HAVE_SUPERLU_DIST) 113 PetscCall(PetscStrcmp(MATSOLVERSUPERLU_DIST, pack, &match)); 114 if (match) { 115 PetscCheck(!chol, PETSC_COMM_WORLD, PETSC_ERR_SUP, "SuperLU does not provide Cholesky!"); 116 PetscCall(PetscPrintf(PETSC_COMM_WORLD, " SUPERLU_DIST LU:\n")); 117 PetscCall(MatGetFactor(A, MATSOLVERSUPERLU_DIST, MAT_FACTOR_LU, &F)); 118 matsolvexx = PETSC_TRUE; 119 if (symm) { /* A is symmetric */ 120 testMatMatSolveTranspose = PETSC_TRUE; 121 testMatSolveTranspose = PETSC_TRUE; 122 } else { /* superlu_dist does not support solving A^t x = rhs yet */ 123 testMatMatSolveTranspose = PETSC_FALSE; 124 testMatSolveTranspose = PETSC_FALSE; 125 } 126 ipack = 1; 127 goto skipoptions; 128 } 129 #endif 130 #if defined(PETSC_HAVE_MUMPS) 131 PetscCall(PetscStrcmp(MATSOLVERMUMPS, pack, &match)); 132 if (match) { 133 if (chol) { 134 PetscCall(PetscPrintf(PETSC_COMM_WORLD, " MUMPS CHOLESKY:\n")); 135 PetscCall(MatGetFactor(A, MATSOLVERMUMPS, MAT_FACTOR_CHOLESKY, &F)); 136 } else { 137 PetscCall(PetscPrintf(PETSC_COMM_WORLD, " MUMPS LU:\n")); 138 PetscCall(MatGetFactor(A, MATSOLVERMUMPS, MAT_FACTOR_LU, &F)); 139 } 140 matsolvexx = PETSC_TRUE; 141 if (test_mumps_opts) { 142 /* test mumps options */ 143 PetscInt icntl; 144 PetscReal cntl; 145 146 icntl = 2; /* sequential matrix ordering */ 147 PetscCall(MatMumpsSetIcntl(F, 7, icntl)); 148 149 cntl = 1.e-6; /* threshold for row pivot detection */ 150 PetscCall(MatMumpsSetIcntl(F, 24, 1)); 151 PetscCall(MatMumpsSetCntl(F, 3, cntl)); 152 } 153 ipack = 2; 154 goto skipoptions; 155 } 156 #endif 157 #if defined(PETSC_HAVE_MKL_PARDISO) 158 PetscCall(PetscStrcmp(MATSOLVERMKL_PARDISO, pack, &match)); 159 if (match) { 160 if (chol) { 161 PetscCall(PetscPrintf(PETSC_COMM_WORLD, " MKL_PARDISO CHOLESKY:\n")); 162 PetscCall(MatGetFactor(A, MATSOLVERMKL_PARDISO, MAT_FACTOR_CHOLESKY, &F)); 163 } else { 164 PetscCall(PetscPrintf(PETSC_COMM_WORLD, " MKL_PARDISO LU:\n")); 165 PetscCall(MatGetFactor(A, MATSOLVERMKL_PARDISO, MAT_FACTOR_LU, &F)); 166 } 167 ipack = 3; 168 goto skipoptions; 169 } 170 #endif 171 #if defined(PETSC_HAVE_CUDA) 172 PetscCall(PetscStrcmp(MATSOLVERCUSPARSE, pack, &match)); 173 if (match) { 174 if (chol) { 175 PetscCall(PetscPrintf(PETSC_COMM_WORLD, " CUSPARSE CHOLESKY:\n")); 176 PetscCall(MatGetFactor(A, MATSOLVERCUSPARSE, MAT_FACTOR_CHOLESKY, &F)); 177 } else { 178 PetscCall(PetscPrintf(PETSC_COMM_WORLD, " CUSPARSE LU:\n")); 179 PetscCall(MatGetFactor(A, MATSOLVERCUSPARSE, MAT_FACTOR_LU, &F)); 180 } 181 testMatSolveTranspose = PETSC_FALSE; 182 testMatMatSolveTranspose = PETSC_FALSE; 183 ipack = 4; 184 goto skipoptions; 185 } 186 #endif 187 /* PETSc */ 188 match = PETSC_TRUE; 189 if (match) { 190 if (chol) { 191 PetscCall(PetscPrintf(PETSC_COMM_WORLD, " PETSC CHOLESKY:\n")); 192 PetscCall(MatGetFactor(A, MATSOLVERPETSC, MAT_FACTOR_CHOLESKY, &F)); 193 } else { 194 PetscCall(PetscPrintf(PETSC_COMM_WORLD, " PETSC LU:\n")); 195 PetscCall(MatGetFactor(A, MATSOLVERPETSC, MAT_FACTOR_LU, &F)); 196 } 197 matsolvexx = PETSC_TRUE; 198 ipack = 5; 199 goto skipoptions; 200 } 201 202 skipoptions: 203 PetscCall(MatFactorInfoInitialize(&info)); 204 info.fill = 5.0; 205 info.shifttype = (PetscReal)MAT_SHIFT_NONE; 206 if (chol) { 207 PetscCall(MatCholeskyFactorSymbolic(F, A, perm, &info)); 208 } else { 209 PetscCall(MatLUFactorSymbolic(F, A, perm, iperm, &info)); 210 } 211 212 for (nfact = 0; nfact < 2; nfact++) { 213 if (chol) { 214 PetscCall(PetscPrintf(PETSC_COMM_WORLD, " %" PetscInt_FMT "-the CHOLESKY numfactorization \n", nfact)); 215 PetscCall(MatCholeskyFactorNumeric(F, A, &info)); 216 } else { 217 PetscCall(PetscPrintf(PETSC_COMM_WORLD, " %" PetscInt_FMT "-the LU numfactorization \n", nfact)); 218 PetscCall(MatLUFactorNumeric(F, A, &info)); 219 } 220 if (view) { 221 PetscCall(PetscViewerPushFormat(PETSC_VIEWER_STDOUT_WORLD, PETSC_VIEWER_ASCII_INFO)); 222 PetscCall(MatView(F, PETSC_VIEWER_STDOUT_WORLD)); 223 PetscCall(PetscViewerPopFormat(PETSC_VIEWER_STDOUT_WORLD)); 224 view = PETSC_FALSE; 225 } 226 227 #if defined(PETSC_HAVE_SUPERLU_DIST) 228 if (ipack == 1) { /* Test MatSuperluDistGetDiagU() 229 -- input: matrix factor F; output: main diagonal of matrix U on all processes */ 230 PetscInt M; 231 PetscScalar *diag; 232 #if !defined(PETSC_USE_COMPLEX) 233 PetscInt nneg, nzero, npos; 234 #endif 235 236 PetscCall(MatGetSize(F, &M, NULL)); 237 PetscCall(PetscMalloc1(M, &diag)); 238 PetscCall(MatSuperluDistGetDiagU(F, diag)); 239 PetscCall(PetscFree(diag)); 240 241 #if !defined(PETSC_USE_COMPLEX) 242 /* Test MatGetInertia() */ 243 if (symm) { /* A is symmetric */ 244 PetscCall(MatGetInertia(F, &nneg, &nzero, &npos)); 245 PetscCall(PetscViewerASCIIPrintf(PETSC_VIEWER_STDOUT_WORLD, " MatInertia: nneg: %" PetscInt_FMT ", nzero: %" PetscInt_FMT ", npos: %" PetscInt_FMT "\n", nneg, nzero, npos)); 246 } 247 #endif 248 } 249 #endif 250 251 #if defined(PETSC_HAVE_MUMPS) 252 /* mumps interface allows repeated call of MatCholeskyFactorSymbolic(), while the succession calls do nothing */ 253 if (ipack == 2) { 254 if (chol) { 255 PetscCall(MatCholeskyFactorSymbolic(F, A, perm, &info)); 256 PetscCall(MatCholeskyFactorNumeric(F, A, &info)); 257 } else { 258 PetscCall(MatLUFactorSymbolic(F, A, perm, iperm, &info)); 259 PetscCall(MatLUFactorNumeric(F, A, &info)); 260 } 261 } 262 #endif 263 264 /* Test MatMatSolve(), A X = B, where B can be dense or sparse */ 265 if (testMatMatSolve) { 266 if (!nfact) { 267 PetscCall(MatMatMult(A, C, MAT_INITIAL_MATRIX, 2.0, &RHS)); 268 } else { 269 PetscCall(MatMatMult(A, C, MAT_REUSE_MATRIX, 2.0, &RHS)); 270 } 271 for (nsolve = 0; nsolve < 2; nsolve++) { 272 PetscCall(PetscPrintf(PETSC_COMM_WORLD, " %" PetscInt_FMT "-the MatMatSolve \n", nsolve)); 273 PetscCall(MatMatSolve(F, RHS, X)); 274 275 /* Check the error */ 276 PetscCall(MatAXPY(X, -1.0, C, SAME_NONZERO_PATTERN)); 277 PetscCall(MatNorm(X, NORM_FROBENIUS, &norm)); 278 if (norm > tol) PetscCall(PetscPrintf(PETSC_COMM_WORLD, "%" PetscInt_FMT "-the MatMatSolve: Norm of error %g, nsolve %" PetscInt_FMT "\n", nsolve, (double)norm, nsolve)); 279 } 280 281 if (matsolvexx) { 282 /* Test MatMatSolve(F,RHS,RHS), RHS is a dense matrix */ 283 PetscCall(MatCopy(RHS, X, SAME_NONZERO_PATTERN)); 284 PetscCall(MatMatSolve(F, X, X)); 285 /* Check the error */ 286 PetscCall(MatAXPY(X, -1.0, C, SAME_NONZERO_PATTERN)); 287 PetscCall(MatNorm(X, NORM_FROBENIUS, &norm)); 288 if (norm > tol) PetscCall(PetscPrintf(PETSC_COMM_WORLD, "MatMatSolve(F,RHS,RHS): Norm of error %g\n", (double)norm)); 289 } 290 291 if (ipack == 2 && size == 1) { 292 Mat spRHS, spRHST, RHST; 293 294 PetscCall(MatTranspose(RHS, MAT_INITIAL_MATRIX, &RHST)); 295 PetscCall(MatConvert(RHST, MATAIJ, MAT_INITIAL_MATRIX, &spRHST)); 296 PetscCall(MatCreateTranspose(spRHST, &spRHS)); 297 for (nsolve = 0; nsolve < 2; nsolve++) { 298 PetscCall(PetscPrintf(PETSC_COMM_WORLD, " %" PetscInt_FMT "-the sparse MatMatSolve \n", nsolve)); 299 PetscCall(MatMatSolve(F, spRHS, X)); 300 301 /* Check the error */ 302 PetscCall(MatAXPY(X, -1.0, C, SAME_NONZERO_PATTERN)); 303 PetscCall(MatNorm(X, NORM_FROBENIUS, &norm)); 304 if (norm > tol) PetscCall(PetscPrintf(PETSC_COMM_WORLD, "%" PetscInt_FMT "-the sparse MatMatSolve: Norm of error %g, nsolve %" PetscInt_FMT "\n", nsolve, (double)norm, nsolve)); 305 } 306 PetscCall(MatDestroy(&spRHST)); 307 PetscCall(MatDestroy(&spRHS)); 308 PetscCall(MatDestroy(&RHST)); 309 } 310 } 311 312 /* Test testMatMatSolveTranspose(), A^T X = B, where B can be dense or sparse */ 313 if (testMatMatSolveTranspose) { 314 if (!nfact) { 315 PetscCall(MatTransposeMatMult(A, C, MAT_INITIAL_MATRIX, 2.0, &RHS1)); 316 } else { 317 PetscCall(MatTransposeMatMult(A, C, MAT_REUSE_MATRIX, 2.0, &RHS1)); 318 } 319 320 for (nsolve = 0; nsolve < 2; nsolve++) { 321 PetscCall(PetscPrintf(PETSC_COMM_WORLD, " %" PetscInt_FMT "-the MatMatSolveTranspose\n", nsolve)); 322 PetscCall(MatMatSolveTranspose(F, RHS1, X)); 323 324 /* Check the error */ 325 PetscCall(MatAXPY(X, -1.0, C, SAME_NONZERO_PATTERN)); 326 PetscCall(MatNorm(X, NORM_FROBENIUS, &norm)); 327 if (norm > tol) PetscCall(PetscPrintf(PETSC_COMM_WORLD, "%" PetscInt_FMT "-the MatMatSolveTranspose: Norm of error %g, nsolve %" PetscInt_FMT "\n", nsolve, (double)norm, nsolve)); 328 } 329 330 if (ipack == 2 && size == 1) { 331 Mat spRHS, spRHST, RHST; 332 333 PetscCall(MatTranspose(RHS1, MAT_INITIAL_MATRIX, &RHST)); 334 PetscCall(MatConvert(RHST, MATAIJ, MAT_INITIAL_MATRIX, &spRHST)); 335 PetscCall(MatCreateTranspose(spRHST, &spRHS)); 336 for (nsolve = 0; nsolve < 2; nsolve++) { 337 PetscCall(MatMatSolveTranspose(F, spRHS, X)); 338 339 /* Check the error */ 340 PetscCall(MatAXPY(X, -1.0, C, SAME_NONZERO_PATTERN)); 341 PetscCall(MatNorm(X, NORM_FROBENIUS, &norm)); 342 if (norm > tol) PetscCall(PetscPrintf(PETSC_COMM_WORLD, "%" PetscInt_FMT "-the sparse MatMatSolveTranspose: Norm of error %g, nsolve %" PetscInt_FMT "\n", nsolve, (double)norm, nsolve)); 343 } 344 PetscCall(MatDestroy(&spRHST)); 345 PetscCall(MatDestroy(&spRHS)); 346 PetscCall(MatDestroy(&RHST)); 347 } 348 } 349 350 /* Test MatSolve() */ 351 if (testMatSolve) { 352 for (nsolve = 0; nsolve < 2; nsolve++) { 353 PetscCall(VecSetRandom(x, rand)); 354 PetscCall(VecCopy(x, u)); 355 PetscCall(MatMult(A, x, b)); 356 357 PetscCall(PetscPrintf(PETSC_COMM_WORLD, " %" PetscInt_FMT "-the MatSolve \n", nsolve)); 358 PetscCall(MatSolve(F, b, x)); 359 360 /* Check the error */ 361 PetscCall(VecAXPY(u, -1.0, x)); /* u <- (-1.0)x + u */ 362 PetscCall(VecNorm(u, NORM_2, &norm)); 363 if (norm > tol) { 364 PetscReal resi; 365 PetscCall(MatMult(A, x, u)); /* u = A*x */ 366 PetscCall(VecAXPY(u, -1.0, b)); /* u <- (-1.0)b + u */ 367 PetscCall(VecNorm(u, NORM_2, &resi)); 368 PetscCall(PetscPrintf(PETSC_COMM_WORLD, "MatSolve: Norm of error %g, resi %g, numfact %" PetscInt_FMT "\n", (double)norm, (double)resi, nfact)); 369 } 370 } 371 } 372 373 /* Test MatSolveTranspose() */ 374 if (testMatSolveTranspose) { 375 for (nsolve = 0; nsolve < 2; nsolve++) { 376 PetscCall(VecSetRandom(x, rand)); 377 PetscCall(VecCopy(x, u)); 378 PetscCall(MatMultTranspose(A, x, b)); 379 380 PetscCall(PetscPrintf(PETSC_COMM_WORLD, " %" PetscInt_FMT "-the MatSolveTranspose\n", nsolve)); 381 PetscCall(MatSolveTranspose(F, b, x)); 382 383 /* Check the error */ 384 PetscCall(VecAXPY(u, -1.0, x)); /* u <- (-1.0)x + u */ 385 PetscCall(VecNorm(u, NORM_2, &norm)); 386 if (norm > tol) { 387 PetscReal resi; 388 PetscCall(VecAXPY(u, -1.0, b)); /* u <- (-1.0)b + u */ 389 PetscCall(VecNorm(u, NORM_2, &resi)); 390 PetscCall(PetscPrintf(PETSC_COMM_WORLD, "MatSolveTranspose: Norm of error %g, resi %g, numfact %" PetscInt_FMT "\n", (double)norm, (double)resi, nfact)); 391 } 392 } 393 } 394 } 395 396 /* Free data structures */ 397 PetscCall(MatDestroy(&A)); 398 PetscCall(MatDestroy(&C)); 399 PetscCall(MatDestroy(&F)); 400 PetscCall(MatDestroy(&X)); 401 PetscCall(MatDestroy(&RHS)); 402 PetscCall(MatDestroy(&RHS1)); 403 404 PetscCall(PetscRandomDestroy(&rand)); 405 PetscCall(ISDestroy(&perm)); 406 PetscCall(ISDestroy(&iperm)); 407 PetscCall(VecDestroy(&x)); 408 PetscCall(VecDestroy(&b)); 409 PetscCall(VecDestroy(&u)); 410 PetscCall(PetscFinalize()); 411 return 0; 412 } 413 414 /*TEST 415 416 test: 417 requires: datafilespath !complex double !defined(PETSC_USE_64BIT_INDICES) 418 args: -f ${DATAFILESPATH}/matrices/medium -mat_solver_type petsc 419 output_file: output/ex125.out 420 421 test: 422 suffix: 2 423 args: -mat_solver_type petsc 424 output_file: output/ex125.out 425 426 test: 427 suffix: mkl_pardiso 428 requires: mkl_pardiso datafilespath !complex double !defined(PETSC_USE_64BIT_INDICES) 429 args: -f ${DATAFILESPATH}/matrices/small -mat_solver_type mkl_pardiso 430 431 test: 432 suffix: mkl_pardiso_2 433 requires: mkl_pardiso 434 args: -mat_solver_type mkl_pardiso 435 output_file: output/ex125_mkl_pardiso.out 436 437 test: 438 suffix: mumps 439 requires: mumps datafilespath !complex double !defined(PETSC_USE_64BIT_INDICES) 440 args: -f ${DATAFILESPATH}/matrices/small -mat_solver_type mumps 441 output_file: output/ex125_mumps_seq.out 442 443 test: 444 suffix: mumps_2 445 nsize: 3 446 requires: mumps datafilespath !complex double !defined(PETSC_USE_64BIT_INDICES) 447 args: -f ${DATAFILESPATH}/matrices/small -mat_solver_type mumps 448 output_file: output/ex125_mumps_par.out 449 450 test: 451 suffix: mumps_3 452 requires: mumps 453 args: -mat_solver_type mumps 454 output_file: output/ex125_mumps_seq.out 455 456 test: 457 suffix: mumps_4 458 nsize: 3 459 requires: mumps 460 args: -mat_solver_type mumps 461 output_file: output/ex125_mumps_par.out 462 463 test: 464 suffix: mumps_5 465 nsize: 3 466 requires: mumps 467 args: -mat_solver_type mumps -cholesky 468 output_file: output/ex125_mumps_par_cholesky.out 469 470 test: 471 suffix: superlu 472 requires: datafilespath double !complex !defined(PETSC_USE_64BIT_INDICES) superlu 473 args: -f ${DATAFILESPATH}/matrices/medium -mat_solver_type superlu 474 output_file: output/ex125_superlu.out 475 476 test: 477 suffix: superlu_dist 478 nsize: {{1 3}} 479 requires: datafilespath double !complex !defined(PETSC_USE_64BIT_INDICES) superlu_dist 480 args: -f ${DATAFILESPATH}/matrices/small -mat_solver_type superlu_dist -mat_superlu_dist_rowperm NOROWPERM 481 output_file: output/ex125_superlu_dist.out 482 483 test: 484 suffix: superlu_dist_2 485 nsize: {{1 3}} 486 requires: superlu_dist !complex 487 args: -n 36 -mat_solver_type superlu_dist -mat_superlu_dist_rowperm NOROWPERM 488 output_file: output/ex125_superlu_dist.out 489 490 test: 491 suffix: superlu_dist_3 492 nsize: {{1 3}} 493 requires: superlu_dist !complex 494 requires: datafilespath double !complex !defined(PETSC_USE_64BIT_INDICES) superlu_dist 495 args: -f ${DATAFILESPATH}/matrices/medium -mat_solver_type superlu_dist -mat_superlu_dist_rowperm NOROWPERM 496 output_file: output/ex125_superlu_dist_nonsymmetric.out 497 498 test: 499 suffix: superlu_dist_complex 500 nsize: 3 501 requires: datafilespath double superlu_dist complex !defined(PETSC_USE_64BIT_INDICES) 502 args: -f ${DATAFILESPATH}/matrices/farzad_B_rhs -mat_solver_type superlu_dist 503 output_file: output/ex125_superlu_dist_complex.out 504 505 test: 506 suffix: superlu_dist_complex_2 507 nsize: 3 508 requires: superlu_dist complex 509 args: -mat_solver_type superlu_dist 510 output_file: output/ex125_superlu_dist_complex_2.out 511 512 test: 513 suffix: cusparse 514 requires: cuda datafilespath !complex double !defined(PETSC_USE_64BIT_INDICES) 515 #todo: fix the bug with cholesky 516 #args: -mat_type aijcusparse -f ${DATAFILESPATH}/matrices/small -mat_solver_type cusparse -cholesky {{0 1}separate output} 517 args: -mat_type aijcusparse -f ${DATAFILESPATH}/matrices/small -mat_solver_type cusparse -cholesky {{0}separate output} 518 519 test: 520 suffix: cusparse_2 521 requires: cuda 522 args: -mat_type aijcusparse -mat_solver_type cusparse -cholesky {{0 1}separate output} 523 524 TEST*/ 525