Actual source code: ex50.c
petsc-3.14.6 2021-03-30
2: static char help[] ="Solves one dimensional Burger's equation compares with exact solution\n\n";
4: /*
6: Not yet tested in parallel
8: */
9: /*
10: Concepts: TS^time-dependent nonlinear problems
11: Concepts: TS^Burger's equation
12: Processors: n
13: */
15: /* ------------------------------------------------------------------------
17: This program uses the one-dimensional Burger's equation
18: u_t = mu*u_xx - u u_x,
19: on the domain 0 <= x <= 1, with periodic boundary conditions
21: The operators are discretized with the spectral element method
23: See the paper PDE-CONSTRAINED OPTIMIZATION WITH SPECTRAL ELEMENTS USING PETSC AND TAO
24: by OANA MARIN, EMIL CONSTANTINESCU, AND BARRY SMITH for details on the exact solution
25: used
27: See src/tao/unconstrained/tutorials/burgers_spectral.c
29: ------------------------------------------------------------------------- */
31: #include <petscts.h>
32: #include <petscdt.h>
33: #include <petscdraw.h>
34: #include <petscdmda.h>
36: /*
37: User-defined application context - contains data needed by the
38: application-provided call-back routines.
39: */
41: typedef struct {
42: PetscInt n; /* number of nodes */
43: PetscReal *nodes; /* GLL nodes */
44: PetscReal *weights; /* GLL weights */
45: } PetscGLL;
47: typedef struct {
48: PetscInt N; /* grid points per elements*/
49: PetscInt E; /* number of elements */
50: PetscReal tol_L2,tol_max; /* error norms */
51: PetscInt steps; /* number of timesteps */
52: PetscReal Tend; /* endtime */
53: PetscReal mu; /* viscosity */
54: PetscReal L; /* total length of domain */
55: PetscReal Le;
56: PetscReal Tadj;
57: } PetscParam;
59: typedef struct {
60: Vec grid; /* total grid */
61: Vec curr_sol;
62: } PetscData;
64: typedef struct {
65: Vec grid; /* total grid */
66: Vec mass; /* mass matrix for total integration */
67: Mat stiff; /* stifness matrix */
68: Mat keptstiff;
69: Mat grad;
70: PetscGLL gll;
71: } PetscSEMOperators;
73: typedef struct {
74: DM da; /* distributed array data structure */
75: PetscSEMOperators SEMop;
76: PetscParam param;
77: PetscData dat;
78: TS ts;
79: PetscReal initial_dt;
80: } AppCtx;
82: /*
83: User-defined routines
84: */
85: extern PetscErrorCode RHSMatrixLaplaciangllDM(TS,PetscReal,Vec,Mat,Mat,void*);
86: extern PetscErrorCode RHSMatrixAdvectiongllDM(TS,PetscReal,Vec,Mat,Mat,void*);
87: extern PetscErrorCode TrueSolution(TS,PetscReal,Vec,AppCtx*);
88: extern PetscErrorCode RHSFunction(TS,PetscReal,Vec,Vec,void*);
89: extern PetscErrorCode RHSJacobian(TS,PetscReal,Vec,Mat,Mat,void*);
91: int main(int argc,char **argv)
92: {
93: AppCtx appctx; /* user-defined application context */
95: PetscInt i, xs, xm, ind, j, lenglob;
96: PetscReal x, *wrk_ptr1, *wrk_ptr2;
97: MatNullSpace nsp;
98: PetscMPIInt size;
100: /* - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
101: Initialize program and set problem parameters
102: - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - */
105: PetscInitialize(&argc,&argv,(char*)0,help);if (ierr) return ierr;
107: /*initialize parameters */
108: appctx.param.N = 10; /* order of the spectral element */
109: appctx.param.E = 10; /* number of elements */
110: appctx.param.L = 4.0; /* length of the domain */
111: appctx.param.mu = 0.01; /* diffusion coefficient */
112: appctx.initial_dt = 5e-3;
113: appctx.param.steps = PETSC_MAX_INT;
114: appctx.param.Tend = 4;
116: PetscOptionsGetInt(NULL,NULL,"-N",&appctx.param.N,NULL);
117: PetscOptionsGetInt(NULL,NULL,"-E",&appctx.param.E,NULL);
118: PetscOptionsGetReal(NULL,NULL,"-Tend",&appctx.param.Tend,NULL);
119: PetscOptionsGetReal(NULL,NULL,"-mu",&appctx.param.mu,NULL);
120: appctx.param.Le = appctx.param.L/appctx.param.E;
122: MPI_Comm_size(PETSC_COMM_WORLD,&size);
123: if (appctx.param.E % size) SETERRQ(PETSC_COMM_WORLD,PETSC_ERR_ARG_WRONG,"Number of elements must be divisible by number of processes");
125: /* - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
126: Create GLL data structures
127: - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - */
128: PetscMalloc2(appctx.param.N,&appctx.SEMop.gll.nodes,appctx.param.N,&appctx.SEMop.gll.weights);
129: PetscDTGaussLobattoLegendreQuadrature(appctx.param.N,PETSCGAUSSLOBATTOLEGENDRE_VIA_LINEAR_ALGEBRA,appctx.SEMop.gll.nodes,appctx.SEMop.gll.weights);
130: appctx.SEMop.gll.n = appctx.param.N;
131: lenglob = appctx.param.E*(appctx.param.N-1);
133: /*
134: Create distributed array (DMDA) to manage parallel grid and vectors
135: and to set up the ghost point communication pattern. There are E*(Nl-1)+1
136: total grid values spread equally among all the processors, except first and last
137: */
139: DMDACreate1d(PETSC_COMM_WORLD,DM_BOUNDARY_PERIODIC,lenglob,1,1,NULL,&appctx.da);
140: DMSetFromOptions(appctx.da);
141: DMSetUp(appctx.da);
143: /*
144: Extract global and local vectors from DMDA; we use these to store the
145: approximate solution. Then duplicate these for remaining vectors that
146: have the same types.
147: */
149: DMCreateGlobalVector(appctx.da,&appctx.dat.curr_sol);
150: VecDuplicate(appctx.dat.curr_sol,&appctx.SEMop.grid);
151: VecDuplicate(appctx.dat.curr_sol,&appctx.SEMop.mass);
153: DMDAGetCorners(appctx.da,&xs,NULL,NULL,&xm,NULL,NULL);
154: DMDAVecGetArray(appctx.da,appctx.SEMop.grid,&wrk_ptr1);
155: DMDAVecGetArray(appctx.da,appctx.SEMop.mass,&wrk_ptr2);
157: /* Compute function over the locally owned part of the grid */
159: xs=xs/(appctx.param.N-1);
160: xm=xm/(appctx.param.N-1);
162: /*
163: Build total grid and mass over entire mesh (multi-elemental)
164: */
166: for (i=xs; i<xs+xm; i++) {
167: for (j=0; j<appctx.param.N-1; j++) {
168: x = (appctx.param.Le/2.0)*(appctx.SEMop.gll.nodes[j]+1.0)+appctx.param.Le*i;
169: ind=i*(appctx.param.N-1)+j;
170: wrk_ptr1[ind]=x;
171: wrk_ptr2[ind]=.5*appctx.param.Le*appctx.SEMop.gll.weights[j];
172: if (j==0) wrk_ptr2[ind]+=.5*appctx.param.Le*appctx.SEMop.gll.weights[j];
173: }
174: }
175: DMDAVecRestoreArray(appctx.da,appctx.SEMop.grid,&wrk_ptr1);
176: DMDAVecRestoreArray(appctx.da,appctx.SEMop.mass,&wrk_ptr2);
178: /* - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
179: Create matrix data structure; set matrix evaluation routine.
180: - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - */
181: DMSetMatrixPreallocateOnly(appctx.da, PETSC_TRUE);
182: DMCreateMatrix(appctx.da,&appctx.SEMop.stiff);
183: DMCreateMatrix(appctx.da,&appctx.SEMop.grad);
184: /*
185: For linear problems with a time-dependent f(u,t) in the equation
186: u_t = f(u,t), the user provides the discretized right-hand-side
187: as a time-dependent matrix.
188: */
189: RHSMatrixLaplaciangllDM(appctx.ts,0.0,appctx.dat.curr_sol,appctx.SEMop.stiff,appctx.SEMop.stiff,&appctx);
190: RHSMatrixAdvectiongllDM(appctx.ts,0.0,appctx.dat.curr_sol,appctx.SEMop.grad,appctx.SEMop.grad,&appctx);
191: /*
192: For linear problems with a time-dependent f(u,t) in the equation
193: u_t = f(u,t), the user provides the discretized right-hand-side
194: as a time-dependent matrix.
195: */
197: MatDuplicate(appctx.SEMop.stiff,MAT_COPY_VALUES,&appctx.SEMop.keptstiff);
199: /* attach the null space to the matrix, this probably is not needed but does no harm */
200: MatNullSpaceCreate(PETSC_COMM_WORLD,PETSC_TRUE,0,NULL,&nsp);
201: MatSetNullSpace(appctx.SEMop.stiff,nsp);
202: MatSetNullSpace(appctx.SEMop.keptstiff,nsp);
203: MatNullSpaceTest(nsp,appctx.SEMop.stiff,NULL);
204: MatNullSpaceDestroy(&nsp);
205: /* attach the null space to the matrix, this probably is not needed but does no harm */
206: MatNullSpaceCreate(PETSC_COMM_WORLD,PETSC_TRUE,0,NULL,&nsp);
207: MatSetNullSpace(appctx.SEMop.grad,nsp);
208: MatNullSpaceTest(nsp,appctx.SEMop.grad,NULL);
209: MatNullSpaceDestroy(&nsp);
211: /* Create the TS solver that solves the ODE and its adjoint; set its options */
212: TSCreate(PETSC_COMM_WORLD,&appctx.ts);
213: TSSetProblemType(appctx.ts,TS_NONLINEAR);
214: TSSetType(appctx.ts,TSRK);
215: TSSetDM(appctx.ts,appctx.da);
216: TSSetTime(appctx.ts,0.0);
217: TSSetTimeStep(appctx.ts,appctx.initial_dt);
218: TSSetMaxSteps(appctx.ts,appctx.param.steps);
219: TSSetMaxTime(appctx.ts,appctx.param.Tend);
220: TSSetExactFinalTime(appctx.ts,TS_EXACTFINALTIME_MATCHSTEP);
221: TSSetTolerances(appctx.ts,1e-7,NULL,1e-7,NULL);
222: TSSetSaveTrajectory(appctx.ts);
223: TSSetFromOptions(appctx.ts);
224: TSSetRHSFunction(appctx.ts,NULL,RHSFunction,&appctx);
225: TSSetRHSJacobian(appctx.ts,appctx.SEMop.stiff,appctx.SEMop.stiff,RHSJacobian,&appctx);
227: /* Set Initial conditions for the problem */
228: TrueSolution(appctx.ts,0,appctx.dat.curr_sol,&appctx);
230: TSSetSolutionFunction(appctx.ts,(PetscErrorCode (*)(TS,PetscReal,Vec,void *))TrueSolution,&appctx);
231: TSSetTime(appctx.ts,0.0);
232: TSSetStepNumber(appctx.ts,0);
234: TSSolve(appctx.ts,appctx.dat.curr_sol);
236: MatDestroy(&appctx.SEMop.stiff);
237: MatDestroy(&appctx.SEMop.keptstiff);
238: MatDestroy(&appctx.SEMop.grad);
239: VecDestroy(&appctx.SEMop.grid);
240: VecDestroy(&appctx.SEMop.mass);
241: VecDestroy(&appctx.dat.curr_sol);
242: PetscFree2(appctx.SEMop.gll.nodes,appctx.SEMop.gll.weights);
243: DMDestroy(&appctx.da);
244: TSDestroy(&appctx.ts);
246: /*
247: Always call PetscFinalize() before exiting a program. This routine
248: - finalizes the PETSc libraries as well as MPI
249: - provides summary and diagnostic information if certain runtime
250: options are chosen (e.g., -log_summary).
251: */
252: PetscFinalize();
253: return ierr;
254: }
256: /*
257: TrueSolution() computes the true solution for the PDE
259: Input Parameter:
260: u - uninitialized solution vector (global)
261: appctx - user-defined application context
263: Output Parameter:
264: u - vector with solution at initial time (global)
265: */
266: PetscErrorCode TrueSolution(TS ts, PetscReal t, Vec u,AppCtx *appctx)
267: {
268: PetscScalar *s;
269: const PetscScalar *xg;
270: PetscErrorCode ierr;
271: PetscInt i,xs,xn;
273: DMDAVecGetArray(appctx->da,u,&s);
274: DMDAVecGetArrayRead(appctx->da,appctx->SEMop.grid,(void*)&xg);
275: DMDAGetCorners(appctx->da,&xs,NULL,NULL,&xn,NULL,NULL);
276: for (i=xs; i<xs+xn; i++) {
277: s[i]=2.0*appctx->param.mu*PETSC_PI*PetscSinScalar(PETSC_PI*xg[i])*PetscExpReal(-appctx->param.mu*PETSC_PI*PETSC_PI*t)/(2.0+PetscCosScalar(PETSC_PI*xg[i])*PetscExpReal(-appctx->param.mu*PETSC_PI*PETSC_PI*t));
278: }
279: DMDAVecRestoreArray(appctx->da,u,&s);
280: DMDAVecRestoreArrayRead(appctx->da,appctx->SEMop.grid,(void*)&xg);
281: return 0;
282: }
284: PetscErrorCode RHSFunction(TS ts,PetscReal t,Vec globalin,Vec globalout,void *ctx)
285: {
287: AppCtx *appctx = (AppCtx*)ctx;
290: MatMult(appctx->SEMop.grad,globalin,globalout); /* grad u */
291: VecPointwiseMult(globalout,globalin,globalout); /* u grad u */
292: VecScale(globalout, -1.0);
293: MatMultAdd(appctx->SEMop.keptstiff,globalin,globalout,globalout);
294: return(0);
295: }
297: /*
299: K is the discretiziation of the Laplacian
300: G is the discretization of the gradient
302: Computes Jacobian of K u + diag(u) G u which is given by
303: K + diag(u)G + diag(Gu)
304: */
305: PetscErrorCode RHSJacobian(TS ts,PetscReal t,Vec globalin,Mat A, Mat B,void *ctx)
306: {
308: AppCtx *appctx = (AppCtx*)ctx;
309: Vec Gglobalin;
312: /* A = diag(u) G */
314: MatCopy(appctx->SEMop.grad,A,SAME_NONZERO_PATTERN);
315: MatDiagonalScale(A,globalin,NULL);
317: /* A = A + diag(Gu) */
318: VecDuplicate(globalin,&Gglobalin);
319: MatMult(appctx->SEMop.grad,globalin,Gglobalin);
320: MatDiagonalSet(A,Gglobalin,ADD_VALUES);
321: VecDestroy(&Gglobalin);
323: /* A = K - A */
324: MatScale(A,-1.0);
325: MatAXPY(A,0.0,appctx->SEMop.keptstiff,SAME_NONZERO_PATTERN);
326: return(0);
327: }
329: /* --------------------------------------------------------------------- */
331: #include "petscblaslapack.h"
332: /*
333: Matrix free operation of 1d Laplacian and Grad for GLL spectral elements
334: */
335: PetscErrorCode MatMult_Laplacian(Mat A,Vec x,Vec y)
336: {
337: AppCtx *appctx;
338: PetscErrorCode ierr;
339: PetscReal **temp,vv;
340: PetscInt i,j,xs,xn;
341: Vec xlocal,ylocal;
342: const PetscScalar *xl;
343: PetscScalar *yl;
344: PetscBLASInt _One = 1,n;
345: PetscScalar _DOne = 1;
347: MatShellGetContext(A,&appctx);
348: DMGetLocalVector(appctx->da,&xlocal);
349: DMGlobalToLocalBegin(appctx->da,x,INSERT_VALUES,xlocal);
350: DMGlobalToLocalEnd(appctx->da,x,INSERT_VALUES,xlocal);
351: DMGetLocalVector(appctx->da,&ylocal);
352: VecSet(ylocal,0.0);
353: PetscGaussLobattoLegendreElementLaplacianCreate(appctx->SEMop.gll.n,appctx->SEMop.gll.nodes,appctx->SEMop.gll.weights,&temp);
354: for (i=0; i<appctx->param.N; i++) {
355: vv =-appctx->param.mu*2.0/appctx->param.Le;
356: for (j=0; j<appctx->param.N; j++) temp[i][j]=temp[i][j]*vv;
357: }
358: DMDAVecGetArrayRead(appctx->da,xlocal,(void*)&xl);
359: DMDAVecGetArray(appctx->da,ylocal,&yl);
360: DMDAGetCorners(appctx->da,&xs,NULL,NULL,&xn,NULL,NULL);
361: PetscBLASIntCast(appctx->param.N,&n);
362: for (j=xs; j<xs+xn; j += appctx->param.N-1) {
363: PetscStackCallBLAS("BLASgemv",BLASgemv_("N",&n,&n,&_DOne,&temp[0][0],&n,&xl[j],&_One,&_DOne,&yl[j],&_One));
364: }
365: DMDAVecRestoreArrayRead(appctx->da,xlocal,(void*)&xl);
366: DMDAVecRestoreArray(appctx->da,ylocal,&yl);
367: PetscGaussLobattoLegendreElementLaplacianDestroy(appctx->SEMop.gll.n,appctx->SEMop.gll.nodes,appctx->SEMop.gll.weights,&temp);
368: VecSet(y,0.0);
369: DMLocalToGlobalBegin(appctx->da,ylocal,ADD_VALUES,y);
370: DMLocalToGlobalEnd(appctx->da,ylocal,ADD_VALUES,y);
371: DMRestoreLocalVector(appctx->da,&xlocal);
372: DMRestoreLocalVector(appctx->da,&ylocal);
373: VecPointwiseDivide(y,y,appctx->SEMop.mass);
374: return 0;
375: }
377: PetscErrorCode MatMult_Advection(Mat A,Vec x,Vec y)
378: {
379: AppCtx *appctx;
380: PetscErrorCode ierr;
381: PetscReal **temp;
382: PetscInt j,xs,xn;
383: Vec xlocal,ylocal;
384: const PetscScalar *xl;
385: PetscScalar *yl;
386: PetscBLASInt _One = 1,n;
387: PetscScalar _DOne = 1;
389: MatShellGetContext(A,&appctx);
390: DMGetLocalVector(appctx->da,&xlocal);
391: DMGlobalToLocalBegin(appctx->da,x,INSERT_VALUES,xlocal);
392: DMGlobalToLocalEnd(appctx->da,x,INSERT_VALUES,xlocal);
393: DMGetLocalVector(appctx->da,&ylocal);
394: VecSet(ylocal,0.0);
395: PetscGaussLobattoLegendreElementAdvectionCreate(appctx->SEMop.gll.n,appctx->SEMop.gll.nodes,appctx->SEMop.gll.weights,&temp);
396: DMDAVecGetArrayRead(appctx->da,xlocal,(void*)&xl);
397: DMDAVecGetArray(appctx->da,ylocal,&yl);
398: DMDAGetCorners(appctx->da,&xs,NULL,NULL,&xn,NULL,NULL);
399: PetscBLASIntCast(appctx->param.N,&n);
400: for (j=xs; j<xs+xn; j += appctx->param.N-1) {
401: PetscStackCallBLAS("BLASgemv",BLASgemv_("N",&n,&n,&_DOne,&temp[0][0],&n,&xl[j],&_One,&_DOne,&yl[j],&_One));
402: }
403: DMDAVecRestoreArrayRead(appctx->da,xlocal,(void*)&xl);
404: DMDAVecRestoreArray(appctx->da,ylocal,&yl);
405: PetscGaussLobattoLegendreElementAdvectionDestroy(appctx->SEMop.gll.n,appctx->SEMop.gll.nodes,appctx->SEMop.gll.weights,&temp);
406: VecSet(y,0.0);
407: DMLocalToGlobalBegin(appctx->da,ylocal,ADD_VALUES,y);
408: DMLocalToGlobalEnd(appctx->da,ylocal,ADD_VALUES,y);
409: DMRestoreLocalVector(appctx->da,&xlocal);
410: DMRestoreLocalVector(appctx->da,&ylocal);
411: VecPointwiseDivide(y,y,appctx->SEMop.mass);
412: VecScale(y,-1.0);
413: return 0;
414: }
416: /*
417: RHSMatrixLaplacian - User-provided routine to compute the right-hand-side
418: matrix for the Laplacian operator
420: Input Parameters:
421: ts - the TS context
422: t - current time (ignored)
423: X - current solution (ignored)
424: dummy - optional user-defined context, as set by TSetRHSJacobian()
426: Output Parameters:
427: AA - Jacobian matrix
428: BB - optionally different matrix from which the preconditioner is built
429: str - flag indicating matrix structure
431: */
432: PetscErrorCode RHSMatrixLaplaciangllDM(TS ts,PetscReal t,Vec X,Mat A,Mat BB,void *ctx)
433: {
434: PetscReal **temp;
435: PetscReal vv;
436: AppCtx *appctx = (AppCtx*)ctx; /* user-defined application context */
438: PetscInt i,xs,xn,l,j;
439: PetscInt *rowsDM;
440: PetscBool flg = PETSC_FALSE;
442: PetscOptionsGetBool(NULL,NULL,"-gll_mf",&flg,NULL);
444: if (!flg) {
445: /*
446: Creates the element stiffness matrix for the given gll
447: */
448: PetscGaussLobattoLegendreElementLaplacianCreate(appctx->SEMop.gll.n,appctx->SEMop.gll.nodes,appctx->SEMop.gll.weights,&temp);
449: /* workarround for clang analyzer warning: Division by zero */
450: if (appctx->param.N <= 1) SETERRQ(PETSC_COMM_WORLD,PETSC_ERR_ARG_WRONG,"Spectral element order should be > 1");
452: /* scale by the size of the element */
453: for (i=0; i<appctx->param.N; i++) {
454: vv=-appctx->param.mu*2.0/appctx->param.Le;
455: for (j=0; j<appctx->param.N; j++) temp[i][j]=temp[i][j]*vv;
456: }
458: MatSetOption(A,MAT_NEW_NONZERO_ALLOCATION_ERR,PETSC_FALSE);
459: DMDAGetCorners(appctx->da,&xs,NULL,NULL,&xn,NULL,NULL);
461: xs = xs/(appctx->param.N-1);
462: xn = xn/(appctx->param.N-1);
464: PetscMalloc1(appctx->param.N,&rowsDM);
465: /*
466: loop over local elements
467: */
468: for (j=xs; j<xs+xn; j++) {
469: for (l=0; l<appctx->param.N; l++) {
470: rowsDM[l] = 1+(j-xs)*(appctx->param.N-1)+l;
471: }
472: MatSetValuesLocal(A,appctx->param.N,rowsDM,appctx->param.N,rowsDM,&temp[0][0],ADD_VALUES);
473: }
474: PetscFree(rowsDM);
475: MatAssemblyBegin(A,MAT_FINAL_ASSEMBLY);
476: MatAssemblyEnd(A,MAT_FINAL_ASSEMBLY);
477: VecReciprocal(appctx->SEMop.mass);
478: MatDiagonalScale(A,appctx->SEMop.mass,0);
479: VecReciprocal(appctx->SEMop.mass);
481: PetscGaussLobattoLegendreElementLaplacianDestroy(appctx->SEMop.gll.n,appctx->SEMop.gll.nodes,appctx->SEMop.gll.weights,&temp);
482: } else {
483: MatSetType(A,MATSHELL);
484: MatSetUp(A);
485: MatShellSetContext(A,appctx);
486: MatShellSetOperation(A,MATOP_MULT,(void (*)(void))MatMult_Laplacian);
487: }
488: return 0;
489: }
491: /*
492: RHSMatrixAdvection - User-provided routine to compute the right-hand-side
493: matrix for the Advection (gradient) operator.
495: Input Parameters:
496: ts - the TS context
497: t - current time
498: global_in - global input vector
499: dummy - optional user-defined context, as set by TSetRHSJacobian()
501: Output Parameters:
502: AA - Jacobian matrix
503: BB - optionally different preconditioning matrix
504: str - flag indicating matrix structure
506: */
507: PetscErrorCode RHSMatrixAdvectiongllDM(TS ts,PetscReal t,Vec X,Mat A,Mat BB,void *ctx)
508: {
509: PetscReal **temp;
510: AppCtx *appctx = (AppCtx*)ctx; /* user-defined application context */
512: PetscInt xs,xn,l,j;
513: PetscInt *rowsDM;
514: PetscBool flg = PETSC_FALSE;
516: PetscOptionsGetBool(NULL,NULL,"-gll_mf",&flg,NULL);
518: if (!flg) {
519: /*
520: Creates the advection matrix for the given gll
521: */
522: PetscGaussLobattoLegendreElementAdvectionCreate(appctx->SEMop.gll.n,appctx->SEMop.gll.nodes,appctx->SEMop.gll.weights,&temp);
523: MatSetOption(A,MAT_NEW_NONZERO_ALLOCATION_ERR,PETSC_FALSE);
524: DMDAGetCorners(appctx->da,&xs,NULL,NULL,&xn,NULL,NULL);
525: xs = xs/(appctx->param.N-1);
526: xn = xn/(appctx->param.N-1);
528: PetscMalloc1(appctx->param.N,&rowsDM);
529: for (j=xs; j<xs+xn; j++) {
530: for (l=0; l<appctx->param.N; l++) {
531: rowsDM[l] = 1+(j-xs)*(appctx->param.N-1)+l;
532: }
533: MatSetValuesLocal(A,appctx->param.N,rowsDM,appctx->param.N,rowsDM,&temp[0][0],ADD_VALUES);
534: }
535: PetscFree(rowsDM);
536: MatAssemblyBegin(A,MAT_FINAL_ASSEMBLY);
537: MatAssemblyEnd(A,MAT_FINAL_ASSEMBLY);
539: VecReciprocal(appctx->SEMop.mass);
540: MatDiagonalScale(A,appctx->SEMop.mass,0);
541: VecReciprocal(appctx->SEMop.mass);
543: PetscGaussLobattoLegendreElementAdvectionDestroy(appctx->SEMop.gll.n,appctx->SEMop.gll.nodes,appctx->SEMop.gll.weights,&temp);
544: } else {
545: MatSetType(A,MATSHELL);
546: MatSetUp(A);
547: MatShellSetContext(A,appctx);
548: MatShellSetOperation(A,MATOP_MULT,(void (*)(void))MatMult_Advection);
549: }
550: return 0;
551: }
553: /*TEST
555: build:
556: requires: !complex
558: test:
559: suffix: 1
560: requires: !single
562: test:
563: suffix: 2
564: nsize: 5
565: requires: !single
567: test:
568: suffix: 3
569: requires: !single
570: args: -ts_view -ts_type beuler -gll_mf -pc_type none -ts_max_steps 5 -ts_monitor_error
572: test:
573: suffix: 4
574: requires: !single
575: args: -ts_view -ts_type beuler -pc_type none -ts_max_steps 5 -ts_monitor_error
577: TEST*/