Actual source code: ex96.c
petsc-dev 2014-02-02
2: static char help[] ="Tests sequential and parallel DMCreateMatrix(), MatMatMult() and MatPtAP()\n\
3: -Mx <xg>, where <xg> = number of coarse grid points in the x-direction\n\
4: -My <yg>, where <yg> = number of coarse grid points in the y-direction\n\
5: -Mz <zg>, where <zg> = number of coarse grid points in the z-direction\n\
6: -Npx <npx>, where <npx> = number of processors in the x-direction\n\
7: -Npy <npy>, where <npy> = number of processors in the y-direction\n\
8: -Npz <npz>, where <npz> = number of processors in the z-direction\n\n";
10: /*
11: This test is modified from ~src/ksp/examples/tests/ex19.c.
12: Example of usage: mpiexec -n 3 ./ex96 -Mx 10 -My 10 -Mz 10
13: */
15: #include <petscdmda.h>
16: #include <../src/mat/impls/aij/seq/aij.h>
17: #include <../src/mat/impls/aij/mpi/mpiaij.h>
19: /* User-defined application contexts */
20: typedef struct {
21: PetscInt mx,my,mz; /* number grid points in x, y and z direction */
22: Vec localX,localF; /* local vectors with ghost region */
23: DM da;
24: Vec x,b,r; /* global vectors */
25: Mat J; /* Jacobian on grid */
26: } GridCtx;
27: typedef struct {
28: GridCtx fine;
29: GridCtx coarse;
30: PetscInt ratio;
31: Mat Ii; /* interpolation from coarse to fine */
32: } AppCtx;
34: #define COARSE_LEVEL 0
35: #define FINE_LEVEL 1
37: /*
38: Mm_ratio - ration of grid lines between fine and coarse grids.
39: */
42: int main(int argc,char **argv)
43: {
45: AppCtx user;
46: PetscInt Npx=PETSC_DECIDE,Npy=PETSC_DECIDE,Npz=PETSC_DECIDE;
47: PetscMPIInt size,rank;
48: PetscInt m,n,M,N,i,nrows;
49: PetscScalar one = 1.0;
50: PetscReal fill=2.0;
51: Mat A,A_tmp,P,C,C1,C2;
52: PetscScalar *array,none = -1.0,alpha;
53: Vec x,v1,v2,v3,v4;
54: PetscReal norm,norm_tmp,norm_tmp1,tol=1.e-12;
55: PetscRandom rdm;
56: PetscBool Test_MatMatMult=PETSC_TRUE,Test_MatPtAP=PETSC_TRUE,Test_3D=PETSC_FALSE,flg;
58: PetscInitialize(&argc,&argv,NULL,help);
59: PetscOptionsGetReal(NULL,"-tol",&tol,NULL);
61: user.ratio = 2;
62: user.coarse.mx = 2; user.coarse.my = 2; user.coarse.mz = 0;
64: PetscOptionsGetInt(NULL,"-Mx",&user.coarse.mx,NULL);
65: PetscOptionsGetInt(NULL,"-My",&user.coarse.my,NULL);
66: PetscOptionsGetInt(NULL,"-Mz",&user.coarse.mz,NULL);
67: PetscOptionsGetInt(NULL,"-ratio",&user.ratio,NULL);
69: if (user.coarse.mz) Test_3D = PETSC_TRUE;
71: user.fine.mx = user.ratio*(user.coarse.mx-1)+1;
72: user.fine.my = user.ratio*(user.coarse.my-1)+1;
73: user.fine.mz = user.ratio*(user.coarse.mz-1)+1;
75: MPI_Comm_size(PETSC_COMM_WORLD,&size);
76: MPI_Comm_rank(PETSC_COMM_WORLD,&rank);
77: PetscOptionsGetInt(NULL,"-Npx",&Npx,NULL);
78: PetscOptionsGetInt(NULL,"-Npy",&Npy,NULL);
79: PetscOptionsGetInt(NULL,"-Npz",&Npz,NULL);
81: /* Set up distributed array for fine grid */
82: if (!Test_3D) {
83: DMDACreate2d(PETSC_COMM_WORLD, DMDA_BOUNDARY_NONE, DMDA_BOUNDARY_NONE,DMDA_STENCIL_STAR,user.fine.mx,
84: user.fine.my,Npx,Npy,1,1,NULL,NULL,&user.fine.da);
85: } else {
86: DMDACreate3d(PETSC_COMM_WORLD,DMDA_BOUNDARY_NONE,DMDA_BOUNDARY_NONE,DMDA_BOUNDARY_NONE,DMDA_STENCIL_STAR,
87: user.fine.mx,user.fine.my,user.fine.mz,Npx,Npy,Npz,
88: 1,1,NULL,NULL,NULL,&user.fine.da);
89: }
91: /* Test DMCreateMatrix() */
92: /*------------------------------------------------------------*/
93: DMSetMatType(user.fine.da,MATAIJ);
94: DMCreateMatrix(user.fine.da,&A);
95: DMSetMatType(user.fine.da,MATBAIJ);
96: DMCreateMatrix(user.fine.da,&C);
98: MatConvert(C,MATAIJ,MAT_INITIAL_MATRIX,&A_tmp); /* not work for mpisbaij matrix! */
99: MatEqual(A,A_tmp,&flg);
100: if (!flg) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_NOTSAMETYPE,"A != C");
101: MatDestroy(&C);
102: MatDestroy(&A_tmp);
104: /*------------------------------------------------------------*/
106: MatGetLocalSize(A,&m,&n);
107: MatGetSize(A,&M,&N);
108: /* set val=one to A */
109: if (size == 1) {
110: const PetscInt *ia,*ja;
111: MatGetRowIJ(A,0,PETSC_FALSE,PETSC_FALSE,&nrows,&ia,&ja,&flg);
112: if (flg) {
113: MatSeqAIJGetArray(A,&array);
114: for (i=0; i<ia[nrows]; i++) array[i] = one;
115: MatSeqAIJRestoreArray(A,&array);
116: }
117: MatRestoreRowIJ(A,0,PETSC_FALSE,PETSC_FALSE,&nrows,&ia,&ja,&flg);
118: } else {
119: Mat_MPIAIJ *aij = (Mat_MPIAIJ*)A->data;
120: Mat_SeqAIJ *a = (Mat_SeqAIJ*)(aij->A)->data, *b=(Mat_SeqAIJ*)(aij->B)->data;
121: /* A_part */
122: for (i=0; i<a->i[m]; i++) a->a[i] = one;
123: /* B_part */
124: for (i=0; i<b->i[m]; i++) b->a[i] = one;
126: }
127: /* MatView(A, PETSC_VIEWER_STDOUT_WORLD); */
129: /* Set up distributed array for coarse grid */
130: if (!Test_3D) {
131: DMDACreate2d(PETSC_COMM_WORLD, DMDA_BOUNDARY_NONE, DMDA_BOUNDARY_NONE,DMDA_STENCIL_STAR,user.coarse.mx,
132: user.coarse.my,Npx,Npy,1,1,NULL,NULL,&user.coarse.da);
133: } else {
134: DMDACreate3d(PETSC_COMM_WORLD,DMDA_BOUNDARY_NONE,DMDA_BOUNDARY_NONE,DMDA_BOUNDARY_NONE,DMDA_STENCIL_STAR,
135: user.coarse.mx,user.coarse.my,user.coarse.mz,Npx,Npy,Npz,
136: 1,1,NULL,NULL,NULL,&user.coarse.da);
137: }
139: /* Create interpolation between the levels */
140: DMCreateInterpolation(user.coarse.da,user.fine.da,&P,NULL);
142: MatGetLocalSize(P,&m,&n);
143: MatGetSize(P,&M,&N);
145: /* Create vectors v1 and v2 that are compatible with A */
146: VecCreate(PETSC_COMM_WORLD,&v1);
147: MatGetLocalSize(A,&m,NULL);
148: VecSetSizes(v1,m,PETSC_DECIDE);
149: VecSetFromOptions(v1);
150: VecDuplicate(v1,&v2);
151: PetscRandomCreate(PETSC_COMM_WORLD,&rdm);
152: PetscRandomSetFromOptions(rdm);
154: /* Test MatMatMult(): C = A*P */
155: /*----------------------------*/
156: if (Test_MatMatMult) {
157: MatDuplicate(A,MAT_COPY_VALUES,&A_tmp);
158: MatMatMult(A_tmp,P,MAT_INITIAL_MATRIX,fill,&C);
160: /* Test MAT_REUSE_MATRIX - reuse symbolic C */
161: alpha=1.0;
162: for (i=0; i<2; i++) {
163: alpha -=0.1;
164: MatScale(A_tmp,alpha);
165: MatMatMult(A_tmp,P,MAT_REUSE_MATRIX,fill,&C);
166: }
168: /* Test MatDuplicate() */
169: /*----------------------------*/
170: MatDuplicate(C,MAT_COPY_VALUES,&C1);
171: MatDuplicate(C1,MAT_COPY_VALUES,&C2);
172: MatDestroy(&C1);
173: MatDestroy(&C2);
175: /* Create vector x that is compatible with P */
176: VecCreate(PETSC_COMM_WORLD,&x);
177: MatGetLocalSize(P,NULL,&n);
178: VecSetSizes(x,n,PETSC_DECIDE);
179: VecSetFromOptions(x);
181: norm = 0.0;
182: for (i=0; i<10; i++) {
183: VecSetRandom(x,rdm);
184: MatMult(P,x,v1);
185: MatMult(A_tmp,v1,v2); /* v2 = A*P*x */
186: MatMult(C,x,v1); /* v1 = C*x */
187: VecAXPY(v1,none,v2);
188: VecNorm(v1,NORM_1,&norm_tmp);
189: VecNorm(v2,NORM_1,&norm_tmp1);
190: norm_tmp /= norm_tmp1;
191: if (norm_tmp > norm) norm = norm_tmp;
192: }
193: if (norm >= tol && !rank) {
194: PetscPrintf(PETSC_COMM_SELF,"Error: MatMatMult(), |v1 - v2|/|v2|: %g\n",(double)norm);
195: }
197: VecDestroy(&x);
198: MatDestroy(&C);
199: MatDestroy(&A_tmp);
200: }
202: /* Test P^T * A * P - MatPtAP() */
203: /*------------------------------*/
204: if (Test_MatPtAP) {
205: MatPtAP(A,P,MAT_INITIAL_MATRIX,fill,&C);
206: MatGetLocalSize(C,&m,&n);
208: /* Test MAT_REUSE_MATRIX - reuse symbolic C */
209: alpha=1.0;
210: for (i=0; i<1; i++) {
211: alpha -=0.1;
212: MatScale(A,alpha);
213: MatPtAP(A,P,MAT_REUSE_MATRIX,fill,&C);
214: }
216: /* Test MatDuplicate() */
217: /*----------------------------*/
218: MatDuplicate(C,MAT_COPY_VALUES,&C1);
219: MatDuplicate(C1,MAT_COPY_VALUES,&C2);
220: MatDestroy(&C1);
221: MatDestroy(&C2);
223: /* Create vector x that is compatible with P */
224: VecCreate(PETSC_COMM_WORLD,&x);
225: MatGetLocalSize(P,&m,&n);
226: VecSetSizes(x,n,PETSC_DECIDE);
227: VecSetFromOptions(x);
229: VecCreate(PETSC_COMM_WORLD,&v3);
230: VecSetSizes(v3,n,PETSC_DECIDE);
231: VecSetFromOptions(v3);
232: VecDuplicate(v3,&v4);
234: norm = 0.0;
235: for (i=0; i<10; i++) {
236: VecSetRandom(x,rdm);
237: MatMult(P,x,v1);
238: MatMult(A,v1,v2); /* v2 = A*P*x */
240: MatMultTranspose(P,v2,v3); /* v3 = Pt*A*P*x */
241: MatMult(C,x,v4); /* v3 = C*x */
242: VecAXPY(v4,none,v3);
243: VecNorm(v4,NORM_1,&norm_tmp);
244: VecNorm(v3,NORM_1,&norm_tmp1);
246: norm_tmp /= norm_tmp1;
247: if (norm_tmp > norm) norm = norm_tmp;
248: }
249: if (norm >= tol && !rank) {
250: PetscPrintf(PETSC_COMM_SELF,"Error: MatPtAP(), |v3 - v4|/|v3|: %g\n",(double)norm);
251: }
252: MatDestroy(&C);
253: VecDestroy(&v3);
254: VecDestroy(&v4);
255: VecDestroy(&x);
256: }
258: /* Clean up */
259: MatDestroy(&A);
260: PetscRandomDestroy(&rdm);
261: VecDestroy(&v1);
262: VecDestroy(&v2);
263: DMDestroy(&user.fine.da);
264: DMDestroy(&user.coarse.da);
265: MatDestroy(&P);
266: PetscFinalize();
267: return 0;
268: }