xref: /petsc/src/mat/tests/ex237.c (revision 2fa40bb9206b96114faa7cb222621ec184d31cd2)
1 static char help[] = "Mini-app to benchmark matrix--matrix multiplication\n\n";
2 
3 /*
4   See the paper below for more information
5 
6    "KSPHPDDM and PCHPDDM: Extending PETSc with Robust Overlapping Schwarz Preconditioners and Advanced Krylov Methods",
7    P. Jolivet, J. E. Roman, and S. Zampini (2020).
8 */
9 
10 #include <petsc.h>
11 
12 #if defined(PETSC_HAVE_MKL) && defined(PETSC_HAVE_MKL_SPARSE_OPTIMIZE)
13 #include <mkl.h>
14 #define PetscStackCallMKLSparse(func, args) do {               \
15     sparse_status_t __ierr;                                    \
16     PetscStackPush(#func);                                     \
17     __ierr = func args;                                        \
18     PetscStackPop;                                             \
19     if (__ierr != SPARSE_STATUS_SUCCESS) SETERRQ2(PETSC_COMM_SELF, PETSC_ERR_LIB, "Error in %s(): error code %d", #func, (int)__ierr); \
20   } while (0)
21 #else
22 #define PetscStackCallMKLSparse(func, args) do {               \
23     SETERRQ(PETSC_COMM_SELF, PETSC_ERR_SUP, "No MKL support"); \
24   } while (0)
25 #endif
26 
27 int main(int argc, char** argv)
28 {
29   Mat            A, C, D, E;
30   PetscInt       nbs = 10, ntype = 10, nN = 8, m, M, trial = 5;
31   PetscViewer    viewer;
32   PetscInt       bs[10], N[8];
33   char           *type[10];
34   PetscMPIInt    size;
35   PetscBool      flg, cuda, maij = PETSC_FALSE, check = PETSC_FALSE, trans = PETSC_FALSE, convert = PETSC_FALSE, mkl;
36   char           file[PETSC_MAX_PATH_LEN];
37   PetscErrorCode ierr;
38 
39   ierr = PetscInitialize(&argc, &argv, NULL, help);if (ierr) return ierr;
40   if (ierr) return ierr;
41   ierr = MPI_Comm_size(PETSC_COMM_WORLD, &size);CHKERRMPI(ierr);
42   if (size != 1) SETERRQ(PETSC_COMM_WORLD, PETSC_ERR_WRONG_MPI_SIZE, "This is a uniprocessor example only");
43   ierr = PetscOptionsGetString(NULL, NULL, "-f", file, PETSC_MAX_PATH_LEN, &flg);CHKERRQ(ierr);
44   if (!flg) SETERRQ(PETSC_COMM_WORLD, PETSC_ERR_USER_INPUT, "Must indicate binary file with the -f option");
45   ierr = PetscOptionsGetInt(NULL, NULL, "-trial", &trial, NULL);CHKERRQ(ierr);
46   ierr = PetscOptionsGetIntArray(NULL, NULL, "-bs", bs, &nbs, &flg);CHKERRQ(ierr);
47   if (!flg) {
48     nbs = 1;
49     bs[0] = 1;
50   }
51   ierr = PetscOptionsGetIntArray(NULL, NULL, "-N", N, &nN, &flg);CHKERRQ(ierr);
52   if (!flg) {
53     nN = 8;
54     N[0] = 1;  N[1] = 2;  N[2] = 4;  N[3] = 8;
55     N[4] = 16; N[5] = 32; N[6] = 64; N[7] = 128;
56   }
57   ierr = PetscOptionsGetStringArray(NULL, NULL, "-type", type, &ntype, &flg);CHKERRQ(ierr);
58   if (!flg) {
59     ntype = 1;
60     ierr = PetscStrallocpy(MATSEQAIJ, &type[0]);CHKERRQ(ierr);
61   }
62   ierr = PetscOptionsGetBool(NULL, NULL, "-check", &check, NULL);CHKERRQ(ierr);
63   ierr = PetscOptionsGetBool(NULL, NULL, "-trans", &trans, NULL);CHKERRQ(ierr);
64   ierr = PetscOptionsGetBool(NULL, NULL, "-convert_aij", &convert, NULL);CHKERRQ(ierr);
65   for (PetscInt j = 0; j < nbs; ++j) {
66     ierr = PetscViewerBinaryOpen(PETSC_COMM_WORLD, file, FILE_MODE_READ, &viewer);CHKERRQ(ierr);
67     ierr = MatCreate(PETSC_COMM_WORLD, &A);CHKERRQ(ierr);
68     ierr = MatSetFromOptions(A);CHKERRQ(ierr);
69     ierr = MatLoad(A, viewer);CHKERRQ(ierr);
70     ierr = PetscViewerDestroy(&viewer);CHKERRQ(ierr);
71     ierr = PetscObjectTypeCompareAny((PetscObject)A, &flg, MATSEQAIJ, MATMPIAIJ, "");CHKERRQ(ierr);
72     if (!flg) SETERRQ(PETSC_COMM_WORLD, PETSC_ERR_USER_INPUT, "Must indicate a MatAIJ input matrix");
73     ierr = MatGetSize(A, &m, &M);CHKERRQ(ierr);
74     if (m == M) {
75       Mat oA;
76       ierr = MatTranspose(A, MAT_INITIAL_MATRIX, &oA);CHKERRQ(ierr);
77       ierr = MatAXPY(A, 1.0, oA, DIFFERENT_NONZERO_PATTERN);CHKERRQ(ierr);
78       ierr = MatDestroy(&oA);CHKERRQ(ierr);
79     }
80     ierr = MatGetLocalSize(A, &m, NULL);CHKERRQ(ierr);
81     ierr = MatGetSize(A, &M, NULL);CHKERRQ(ierr);
82     if (bs[j] > 1) {
83       Mat               T, Tt, B;
84       const PetscScalar *ptr;
85       PetscScalar       *val, *Aa;
86       const PetscInt    *Ai, *Aj;
87       PetscInt          An, i, k;
88       PetscBool         done;
89 
90       ierr = MatCreateDense(PETSC_COMM_SELF, bs[j], bs[j], bs[j], bs[j], NULL, &T);CHKERRQ(ierr);
91       ierr = MatSetRandom(T, NULL);CHKERRQ(ierr);
92       ierr = MatTranspose(T, MAT_INITIAL_MATRIX, &Tt);CHKERRQ(ierr);
93       ierr = MatAXPY(T, 1.0, Tt, SAME_NONZERO_PATTERN);CHKERRQ(ierr);
94       ierr = MatDestroy(&Tt);CHKERRQ(ierr);
95       ierr = MatDenseGetArrayRead(T, &ptr);CHKERRQ(ierr);
96       ierr = MatGetRowIJ(A, 0, PETSC_FALSE, PETSC_FALSE, &An, &Ai, &Aj, &done);CHKERRQ(ierr);
97       if (!done || An != m) SETERRQ(PETSC_COMM_SELF, PETSC_ERR_ARG_SIZ, "Inconsistent sizes");
98       ierr = MatSeqAIJGetArray(A, &Aa);CHKERRQ(ierr);
99       ierr = MatCreate(PETSC_COMM_WORLD, &B);CHKERRQ(ierr);
100       ierr = MatSetType(B, MATSEQBAIJ);CHKERRQ(ierr);
101       ierr = MatSetSizes(B, bs[j] * An, bs[j] * An, PETSC_DECIDE, PETSC_DECIDE);CHKERRQ(ierr);
102       ierr = PetscMalloc1(Ai[An] * bs[j] * bs[j], &val);CHKERRQ(ierr);
103       for (i = 0; i < Ai[An]; ++i)
104         for (k = 0; k < bs[j] * bs[j]; ++k)
105           val[i * bs[j] * bs[j] + k] = Aa[i] * ptr[k];
106       ierr = MatSetOption(B, MAT_ROW_ORIENTED, PETSC_FALSE);CHKERRQ(ierr);
107       ierr = MatSeqBAIJSetPreallocationCSR(B, bs[j], Ai, Aj, val);CHKERRQ(ierr);
108       ierr = PetscFree(val);CHKERRQ(ierr);
109       ierr = MatSeqAIJRestoreArray(A, &Aa);CHKERRQ(ierr);
110       ierr = MatRestoreRowIJ(A, 0, PETSC_FALSE, PETSC_FALSE, &An, &Ai, &Aj, &done);CHKERRQ(ierr);
111       ierr = MatDenseRestoreArrayRead(T, &ptr);CHKERRQ(ierr);
112       ierr = MatDestroy(&T);CHKERRQ(ierr);
113       ierr = MatDestroy(&A);CHKERRQ(ierr);
114       A    = B;
115     }
116     /* reconvert back to SeqAIJ before converting to the desired type later */
117     if (!convert) E = A;
118     ierr = MatConvert(A, MATSEQAIJ, convert ? MAT_INITIAL_MATRIX : MAT_INPLACE_MATRIX, &E);CHKERRQ(ierr);
119     ierr = MatSetOption(E, MAT_SYMMETRIC, PETSC_TRUE);CHKERRQ(ierr);
120     for (PetscInt i = 0; i < ntype; ++i) {
121       char        *tmp;
122       PetscInt    *ia_ptr, *ja_ptr, k;
123       PetscScalar *a_ptr;
124 #if defined(PETSC_HAVE_MKL) && defined(PETSC_HAVE_MKL_SPARSE_OPTIMIZE)
125       struct matrix_descr descr;
126       sparse_matrix_t     spr;
127       descr.type = SPARSE_MATRIX_TYPE_GENERAL;
128       descr.diag = SPARSE_DIAG_NON_UNIT;
129 #endif
130       if (convert) {
131         ierr = MatDestroy(&A);CHKERRQ(ierr);
132       }
133       ierr = PetscStrstr(type[i], "mkl", &tmp);CHKERRQ(ierr);
134       if (tmp) {
135         size_t mlen, tlen;
136         char base[256];
137 
138         mkl  = PETSC_TRUE;
139         ierr = PetscStrlen(tmp, &mlen);CHKERRQ(ierr);
140         ierr = PetscStrlen(type[i], &tlen);CHKERRQ(ierr);
141         ierr = PetscStrncpy(base, type[i], tlen-mlen + 1);CHKERRQ(ierr);
142         ierr = MatConvert(E, base, convert ? MAT_INITIAL_MATRIX : MAT_INPLACE_MATRIX, &A);CHKERRQ(ierr);
143       } else {
144         mkl  = PETSC_FALSE;
145         ierr = PetscStrstr(type[i], "maij", &tmp);CHKERRQ(ierr);
146         if (!tmp) {
147           ierr = MatConvert(E, type[i], convert ? MAT_INITIAL_MATRIX : MAT_INPLACE_MATRIX, &A);CHKERRQ(ierr);
148         } else {
149           ierr = MatConvert(E, MATAIJ, convert ? MAT_INITIAL_MATRIX : MAT_INPLACE_MATRIX, &A);CHKERRQ(ierr);
150           maij = PETSC_TRUE;
151         }
152       }
153       ierr = PetscObjectTypeCompareAny((PetscObject)A, &cuda, MATSEQAIJCUSPARSE, MATMPIAIJCUSPARSE, "");CHKERRQ(ierr);
154       if (mkl) {
155         const PetscInt *Ai, *Aj;
156         PetscInt       An;
157         PetscBool      done;
158 
159         ierr = PetscObjectTypeCompareAny((PetscObject)A, &flg, MATSEQAIJ, MATSEQBAIJ, MATSEQSBAIJ, "");CHKERRQ(ierr);
160         if (!flg) SETERRQ(PETSC_COMM_WORLD, PETSC_ERR_USER_INPUT, "Not implemented");
161         ierr = PetscObjectTypeCompare((PetscObject)A, MATSEQAIJ, &flg);CHKERRQ(ierr);
162         ierr = MatGetRowIJ(A, 0, PETSC_FALSE, flg ? PETSC_FALSE : PETSC_TRUE, &An, &Ai, &Aj, &done);CHKERRQ(ierr);
163         if (!done) SETERRQ(PETSC_COMM_SELF, PETSC_ERR_ARG_SIZ, "Inconsistent sizes");
164         ierr = PetscMalloc1(An + 1, &ia_ptr);CHKERRQ(ierr);
165         ierr = PetscMalloc1(Ai[An], &ja_ptr);CHKERRQ(ierr);
166         if (flg) { /* SeqAIJ */
167           for (k = 0; k < An + 1; ++k) ia_ptr[k] = Ai[k];
168           for (k = 0; k < Ai[An]; ++k) ja_ptr[k] = Aj[k];
169           ierr = MatSeqAIJGetArray(A, &a_ptr);CHKERRQ(ierr);
170           PetscStackCallMKLSparse(mkl_sparse_d_create_csr, (&spr, SPARSE_INDEX_BASE_ZERO, An, An, ia_ptr, ia_ptr + 1, ja_ptr, a_ptr));
171         } else {
172           ierr = PetscObjectTypeCompare((PetscObject)A, MATSEQBAIJ, &flg);CHKERRQ(ierr);
173           if (flg) {
174             for (k = 0; k < An + 1; ++k) ia_ptr[k] = Ai[k] + 1; /* Fortran indexing to maximize cases covered by _mm routines */
175             for (k = 0; k < Ai[An]; ++k) ja_ptr[k] = Aj[k] + 1; /* Fortran indexing to maximize cases covered by _mm routines */
176             ierr = MatSeqBAIJGetArray(A, &a_ptr);CHKERRQ(ierr);
177             PetscStackCallMKLSparse(mkl_sparse_d_create_bsr, (&spr, SPARSE_INDEX_BASE_ONE, SPARSE_LAYOUT_COLUMN_MAJOR, An, An, bs[j], ia_ptr, ia_ptr + 1, ja_ptr, a_ptr));
178           } else {
179             ierr = PetscObjectTypeCompare((PetscObject)A, MATSEQSBAIJ, &flg);CHKERRQ(ierr);
180             if (flg) {
181               for (k = 0; k < An + 1; ++k) ia_ptr[k] = Ai[k] + 1; /* Fortran indexing to maximize cases covered by _mm routines */
182               for (k = 0; k < Ai[An]; ++k) ja_ptr[k] = Aj[k] + 1; /* Fortran indexing to maximize cases covered by _mm routines */
183               ierr = MatSeqSBAIJGetArray(A, &a_ptr);CHKERRQ(ierr);
184               PetscStackCallMKLSparse(mkl_sparse_d_create_bsr, (&spr, SPARSE_INDEX_BASE_ONE, SPARSE_LAYOUT_COLUMN_MAJOR, An, An, bs[j], ia_ptr, ia_ptr + 1, ja_ptr, a_ptr));
185 #if defined(PETSC_HAVE_MKL) && defined(PETSC_HAVE_MKL_SPARSE_OPTIMIZE)
186               descr.type = SPARSE_MATRIX_TYPE_SYMMETRIC;
187               descr.mode = SPARSE_FILL_MODE_UPPER;
188               descr.diag = SPARSE_DIAG_NON_UNIT;
189 #endif
190             }
191           }
192         }
193         ierr = PetscObjectTypeCompare((PetscObject)A, MATSEQAIJ, &flg);CHKERRQ(ierr);
194         ierr = MatRestoreRowIJ(A, 0, PETSC_FALSE, flg ? PETSC_FALSE : PETSC_TRUE, &An, &Ai, &Aj, &done);CHKERRQ(ierr);
195       }
196 
197       ierr = MatViewFromOptions(A, NULL, "-A_view");CHKERRQ(ierr);
198 
199       for (k = 0; k < nN; ++k) {
200         MatType       Atype, Ctype;
201         PetscInt      AM, AN, CM, CN, t;
202 #if defined(PETSC_USE_LOG)
203         PetscLogStage stage, tstage;
204         char          stage_s[256];
205 #endif
206 
207         ierr = MatCreateDense(PETSC_COMM_WORLD, bs[j] * m, PETSC_DECIDE, bs[j] * M, N[k], NULL, &C);CHKERRQ(ierr);
208         ierr = MatCreateDense(PETSC_COMM_WORLD, bs[j] * m, PETSC_DECIDE, bs[j] * M, N[k], NULL, &D);CHKERRQ(ierr);
209         ierr = MatSetRandom(C, NULL);CHKERRQ(ierr);
210         if (cuda) { /* convert to GPU if needed */
211           ierr = MatConvert(C, MATDENSECUDA, MAT_INPLACE_MATRIX, &C);CHKERRQ(ierr);
212           ierr = MatConvert(D, MATDENSECUDA, MAT_INPLACE_MATRIX, &D);CHKERRQ(ierr);
213         }
214         if (mkl) {
215           if (N[k] > 1) PetscStackCallMKLSparse(mkl_sparse_set_mm_hint, (spr, SPARSE_OPERATION_NON_TRANSPOSE, descr, SPARSE_LAYOUT_COLUMN_MAJOR, N[k], 1 + trial));
216           else          PetscStackCallMKLSparse(mkl_sparse_set_mv_hint, (spr, SPARSE_OPERATION_NON_TRANSPOSE, descr, 1 + trial));
217           PetscStackCallMKLSparse(mkl_sparse_set_memory_hint, (spr, SPARSE_MEMORY_AGGRESSIVE));
218           PetscStackCallMKLSparse(mkl_sparse_optimize, (spr));
219         }
220         ierr = MatGetType(A, &Atype);CHKERRQ(ierr);
221         ierr = MatGetType(C, &Ctype);CHKERRQ(ierr);
222         ierr = MatGetSize(A, &AM, &AN);CHKERRQ(ierr);
223         ierr = MatGetSize(C, &CM, &CN);CHKERRQ(ierr);
224 
225 #if defined(PETSC_USE_LOG)
226         if (!maij || N[k] > 1) {
227           ierr = PetscSNPrintf(stage_s, sizeof(stage_s), "type_%s-bs_%D-N_%02d", type[i], bs[j], (int)N[k]);CHKERRQ(ierr);
228           ierr = PetscLogStageRegister(stage_s, &stage);CHKERRQ(ierr);
229         }
230         if (trans && N[k] > 1) {
231           ierr = PetscSNPrintf(stage_s, sizeof(stage_s), "trans_type_%s-bs_%D-N_%02d", type[i], bs[j], (int)N[k]);CHKERRQ(ierr);
232           ierr = PetscLogStageRegister(stage_s, &tstage);CHKERRQ(ierr);
233         }
234 #endif
235         /* A*B */
236         if (N[k] > 1) {
237           if (!maij) {
238             ierr = MatProductCreateWithMat(A, C, NULL, D);CHKERRQ(ierr);
239             ierr = MatProductSetType(D, MATPRODUCT_AB);CHKERRQ(ierr);
240             ierr = MatProductSetFromOptions(D);CHKERRQ(ierr);
241             ierr = MatProductSymbolic(D);CHKERRQ(ierr);
242           }
243 
244           if (!mkl) {
245             if (!maij) {
246               ierr = MatProductNumeric(D);CHKERRQ(ierr);
247               ierr = PetscPrintf(PETSC_COMM_WORLD, "Benchmarking MatProduct %s: with A %s %Dx%D and B %s %Dx%D\n", MatProductTypes[MATPRODUCT_AB], Atype, AM, AN, Ctype, CM, CN);CHKERRQ(ierr);
248               ierr = PetscLogStagePush(stage);CHKERRQ(ierr);
249               for (t = 0; t < trial; ++t) {
250                 ierr = MatProductNumeric(D);CHKERRQ(ierr);
251               }
252               ierr = PetscLogStagePop();CHKERRQ(ierr);
253             } else {
254               Mat               E, Ct, Dt;
255               Vec               cC, cD;
256               const PetscScalar *c_ptr;
257               PetscScalar       *d_ptr;
258               ierr = MatCreateMAIJ(A, N[k], &E);CHKERRQ(ierr);
259               ierr = MatDenseGetLocalMatrix(C, &Ct);CHKERRQ(ierr);
260               ierr = MatDenseGetLocalMatrix(D, &Dt);CHKERRQ(ierr);
261               ierr = MatTranspose(Ct, MAT_INPLACE_MATRIX, &Ct);CHKERRQ(ierr);
262               ierr = MatTranspose(Dt, MAT_INPLACE_MATRIX, &Dt);CHKERRQ(ierr);
263               ierr = MatDenseGetArrayRead(Ct, &c_ptr);CHKERRQ(ierr);
264               ierr = MatDenseGetArrayWrite(Dt, &d_ptr);CHKERRQ(ierr);
265               ierr = VecCreateMPIWithArray(PETSC_COMM_WORLD, 1, AM * N[k], PETSC_DECIDE, c_ptr, &cC);CHKERRQ(ierr);
266               ierr = VecCreateMPIWithArray(PETSC_COMM_WORLD, 1, AM * N[k], PETSC_DECIDE, d_ptr, &cD);CHKERRQ(ierr);
267               ierr = MatMult(E, cC, cD);CHKERRQ(ierr);
268               ierr = PetscPrintf(PETSC_COMM_WORLD, "Benchmarking MatMult: with A %s %Dx%D and B %s %Dx%D\n", MATMAIJ, AM, AN, VECMPI, AM * N[k], 1);CHKERRQ(ierr);
269               ierr = PetscLogStagePush(stage);CHKERRQ(ierr);
270               for (t = 0; t < trial; ++t) {
271                 ierr = MatMult(E, cC, cD);CHKERRQ(ierr);
272               }
273               ierr = PetscLogStagePop();CHKERRQ(ierr);
274               ierr = VecDestroy(&cD);CHKERRQ(ierr);
275               ierr = VecDestroy(&cC);CHKERRQ(ierr);
276               ierr = MatDestroy(&E);CHKERRQ(ierr);
277               ierr = MatDenseRestoreArrayWrite(Dt, &d_ptr);CHKERRQ(ierr);
278               ierr = MatDenseRestoreArrayRead(Ct, &c_ptr);CHKERRQ(ierr);
279               ierr = MatTranspose(Ct, MAT_INPLACE_MATRIX, &Ct);CHKERRQ(ierr);
280               ierr = MatTranspose(Dt, MAT_INPLACE_MATRIX, &Dt);CHKERRQ(ierr);
281             }
282           } else {
283             const PetscScalar *c_ptr;
284             PetscScalar       *d_ptr;
285 
286             ierr = MatDenseGetArrayRead(C, &c_ptr);CHKERRQ(ierr);
287             ierr = MatDenseGetArrayWrite(D, &d_ptr);CHKERRQ(ierr);
288             PetscStackCallMKLSparse(mkl_sparse_d_mm,(SPARSE_OPERATION_NON_TRANSPOSE, 1.0, spr, descr, SPARSE_LAYOUT_COLUMN_MAJOR, c_ptr, CN, CM, 0.0, d_ptr, CM));
289             ierr = PetscPrintf(PETSC_COMM_WORLD, "Benchmarking mkl_sparse_d_mm (COLUMN_MAJOR): with A %s %Dx%D and B %s %Dx%D\n", Atype, AM, AN, Ctype, CM, CN);CHKERRQ(ierr);
290             ierr = PetscLogStagePush(stage);CHKERRQ(ierr);
291             for (t = 0; t < trial; ++t) {
292               PetscStackCallMKLSparse(mkl_sparse_d_mm, (SPARSE_OPERATION_NON_TRANSPOSE, 1.0, spr, descr, SPARSE_LAYOUT_COLUMN_MAJOR, c_ptr, CN, CM, 0.0, d_ptr, CM));
293             }
294             ierr = PetscLogStagePop();CHKERRQ(ierr);
295             ierr = MatDenseRestoreArrayWrite(D, &d_ptr);CHKERRQ(ierr);
296             ierr = MatDenseRestoreArrayRead(C, &c_ptr);CHKERRQ(ierr);
297           }
298         } else if (maij) {
299           ierr = MatDestroy(&C);CHKERRQ(ierr);
300           ierr = MatDestroy(&D);CHKERRQ(ierr);
301           continue;
302         } else if (!mkl) {
303           Vec cC, cD;
304 
305           ierr = MatDenseGetColumnVecRead(C, 0, &cC);CHKERRQ(ierr);
306           ierr = MatDenseGetColumnVecWrite(D, 0, &cD);CHKERRQ(ierr);
307           ierr = MatMult(A, cC, cD);CHKERRQ(ierr);
308           ierr = PetscPrintf(PETSC_COMM_WORLD, "Benchmarking MatMult: with A %s %Dx%D\n", Atype, AM, AN);CHKERRQ(ierr);
309           ierr = PetscLogStagePush(stage);CHKERRQ(ierr);
310           for (t = 0; t < trial; ++t) {
311             ierr = MatMult(A, cC, cD);CHKERRQ(ierr);
312           }
313           ierr = PetscLogStagePop();CHKERRQ(ierr);
314           ierr = MatDenseRestoreColumnVecRead(C, 0, &cC);CHKERRQ(ierr);
315           ierr = MatDenseRestoreColumnVecWrite(D, 0, &cD);CHKERRQ(ierr);
316         } else {
317           const PetscScalar *c_ptr;
318           PetscScalar       *d_ptr;
319 
320           ierr = MatDenseGetArrayRead(C, &c_ptr);CHKERRQ(ierr);
321           ierr = MatDenseGetArrayWrite(D, &d_ptr);CHKERRQ(ierr);
322           ierr = PetscPrintf(PETSC_COMM_WORLD, "Benchmarking mkl_sparse_d_mv: with A %s %Dx%D\n", Atype, AM, AN);CHKERRQ(ierr);
323           PetscStackCallMKLSparse(mkl_sparse_d_mv, (SPARSE_OPERATION_NON_TRANSPOSE, 1.0, spr, descr, c_ptr, 0.0, d_ptr));
324           ierr = PetscLogStagePush(stage);CHKERRQ(ierr);
325           for (t = 0; t < trial; ++t) {
326             PetscStackCallMKLSparse(mkl_sparse_d_mv, (SPARSE_OPERATION_NON_TRANSPOSE, 1.0, spr, descr, c_ptr, 0.0, d_ptr));
327           }
328           ierr = PetscLogStagePop();CHKERRQ(ierr);
329           ierr = MatDenseRestoreArrayWrite(D, &d_ptr);CHKERRQ(ierr);
330           ierr = MatDenseRestoreArrayRead(C, &c_ptr);CHKERRQ(ierr);
331         }
332 
333         if (check) {
334           ierr = MatMatMultEqual(A, C, D, 10, &flg);CHKERRQ(ierr);
335           if (!flg) {
336             MatType Dtype;
337 
338             ierr = MatGetType(D, &Dtype);CHKERRQ(ierr);
339             ierr = PetscPrintf(PETSC_COMM_WORLD, "Error with A %s%s, C %s, D %s, Nk %D\n", Atype, mkl ? "mkl" : "", Ctype, Dtype, N[k]);CHKERRQ(ierr);
340           }
341         }
342 
343         /* MKL implementation seems buggy for ABt */
344         /* A*Bt */
345         if (!mkl && trans && N[k] > 1) {
346           ierr = PetscObjectTypeCompareAny((PetscObject)A, &flg, MATSEQAIJ, MATMPIAIJ, "");CHKERRQ(ierr);
347           if (flg) {
348             ierr = MatTranspose(C, MAT_INPLACE_MATRIX, &C);CHKERRQ(ierr);
349             ierr = MatGetType(C, &Ctype);CHKERRQ(ierr);
350             if (!mkl) {
351               ierr = MatProductCreateWithMat(A, C, NULL, D);CHKERRQ(ierr);
352               ierr = MatProductSetType(D, MATPRODUCT_ABt);CHKERRQ(ierr);
353               ierr = MatProductSetFromOptions(D);CHKERRQ(ierr);
354               ierr = MatProductSymbolic(D);CHKERRQ(ierr);
355               ierr = MatProductNumeric(D);CHKERRQ(ierr);
356               ierr = PetscPrintf(PETSC_COMM_WORLD, "Benchmarking MatProduct %s: with A %s %Dx%D and Bt %s %Dx%D\n", MatProductTypes[MATPRODUCT_ABt], Atype, AM, AN, Ctype, CM, CN);CHKERRQ(ierr);
357               ierr = PetscLogStagePush(tstage);CHKERRQ(ierr);
358               for (t = 0; t < trial; ++t) {
359                 ierr = MatProductNumeric(D);CHKERRQ(ierr);
360               }
361               ierr = PetscLogStagePop();CHKERRQ(ierr);
362             } else {
363               const PetscScalar *c_ptr;
364               PetscScalar       *d_ptr;
365 
366               PetscStackCallMKLSparse(mkl_sparse_set_mm_hint, (spr, SPARSE_OPERATION_NON_TRANSPOSE, descr, SPARSE_LAYOUT_ROW_MAJOR, N[k], 1 + trial));
367               PetscStackCallMKLSparse(mkl_sparse_optimize, (spr));
368               ierr = MatDenseGetArrayRead(C, &c_ptr);CHKERRQ(ierr);
369               ierr = MatDenseGetArrayWrite(D, &d_ptr);CHKERRQ(ierr);
370               ierr = PetscPrintf(PETSC_COMM_WORLD, "Benchmarking mkl_sparse_d_mm (ROW_MAJOR): with A %s %Dx%D and B %s %Dx%D\n", Atype, AM, AN, Ctype, CM, CN);CHKERRQ(ierr);
371               PetscStackCallMKLSparse(mkl_sparse_d_mm, (SPARSE_OPERATION_NON_TRANSPOSE, 1.0, spr, descr, SPARSE_LAYOUT_ROW_MAJOR, c_ptr, CN, CM, 0.0, d_ptr, CM));
372               ierr = PetscLogStagePush(stage);CHKERRQ(ierr);
373               for (t = 0; t < trial; ++t) {
374                 PetscStackCallMKLSparse(mkl_sparse_d_mm, (SPARSE_OPERATION_NON_TRANSPOSE, 1.0, spr, descr, SPARSE_LAYOUT_ROW_MAJOR, c_ptr, CN, CM, 0.0, d_ptr, CM));
375               }
376               ierr = PetscLogStagePop();CHKERRQ(ierr);
377               ierr = MatDenseRestoreArrayWrite(D, &d_ptr);CHKERRQ(ierr);
378               ierr = MatDenseRestoreArrayRead(C, &c_ptr);CHKERRQ(ierr);
379             }
380           }
381         }
382 
383         if (!mkl && trans && N[k] > 1 && flg && check) {
384           ierr = MatMatTransposeMultEqual(A, C, D, 10, &flg);CHKERRQ(ierr);
385           if (!flg) {
386             MatType Dtype;
387             ierr = MatGetType(D, &Dtype);CHKERRQ(ierr);
388             ierr = PetscPrintf(PETSC_COMM_WORLD, "Error with A %s%s, C %s, D %s, Nk %D\n", Atype, mkl ? "mkl" : "", Ctype, Dtype, N[k]);CHKERRQ(ierr);
389           }
390         }
391         ierr = MatDestroy(&C);CHKERRQ(ierr);
392         ierr = MatDestroy(&D);CHKERRQ(ierr);
393       }
394       if (mkl) {
395         PetscStackCallMKLSparse(mkl_sparse_destroy, (spr));
396         ierr = PetscFree(ia_ptr);CHKERRQ(ierr);
397         ierr = PetscFree(ja_ptr);CHKERRQ(ierr);
398       }
399       if (cuda && i != ntype - 1) {
400         ierr = PetscPrintf(PETSC_COMM_WORLD, "AIJCUSPARSE must be last, otherwise MatConvert() to another MatType is too slow\n");CHKERRQ(ierr);
401         break;
402       }
403     }
404     if (E != A) {
405       ierr = MatDestroy(&E);CHKERRQ(ierr);
406     }
407     ierr = MatDestroy(&A);CHKERRQ(ierr);
408   }
409   for (m = 0; m < ntype; ++m) {
410     ierr = PetscFree(type[m]);CHKERRQ(ierr);
411   }
412   ierr = PetscFinalize();
413   return 0;
414 }
415 
416 /*TEST
417    build:
418      requires: double !complex !defined(PETSC_USE_64BIT_INDICES)
419 
420    testset:
421      nsize: 1
422      filter: sed "/Benchmarking/d"
423      args: -f ${wPETSC_DIR}/share/petsc/datafiles/matrices/spd-real-int32-float64 -bs 1,2,3 -N 1,2,18 -check -trans -convert_aij {{false true}shared output}
424      test:
425        suffix: basic
426        args: -type aij,sbaij,baij
427        output_file: output/ex237.out
428      test:
429        suffix: maij
430        args: -type aij,maij
431        output_file: output/ex237.out
432      test:
433        suffix: cuda
434        requires: cuda
435        args: -type aij,aijcusparse
436        output_file: output/ex237.out
437      test:
438        suffix: mkl
439        requires: mkl
440        args: -type aij,aijmkl,baijmkl,sbaijmkl
441        output_file: output/ex237.out
442 
443 TEST*/
444