Actual source code: ex74.c
petsc-3.13.6 2020-09-29
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      1: static char help[] = "Solves the constant-coefficient 1D heat equation \n\
      2: with an Implicit Runge-Kutta method using MatKAIJ.                  \n\
      3:                                                                     \n\
      4:     du      d^2 u                                                   \n\
      5:     --  = a ----- ; 0 <= x <= 1;                                    \n\
      6:     dt      dx^2                                                    \n\
      7:                                                                     \n\
      8:   with periodic boundary conditions                                 \n\
      9:                                                                     \n\
     10: 2nd order central discretization in space:                          \n\
     11:                                                                     \n\
     12:    [ d^2 u ]     u_{i+1} - 2u_i + u_{i-1}                           \n\
     13:    [ ----- ]  =  ------------------------                           \n\
     14:    [ dx^2  ]i              h^2                                      \n\
     15:                                                                     \n\
     16:     i = grid index;    h = x_{i+1}-x_i (Uniform)                    \n\
     17:     0 <= i < n         h = 1.0/n                                    \n\
     18:                                                                     \n\
     19: Thus,                                                               \n\
     20:                                                                     \n\
     21:    du                                                               \n\
     22:    --  = Ju;  J = (a/h^2) tridiagonal(1,-2,1)_n                     \n\
     23:    dt                                                               \n\
     24:                                                                     \n\
     25: Implicit Runge-Kutta method:                                        \n\
     26:                                                                     \n\
     27:   U^(k)   = u^n + dt \\sum_i a_{ki} JU^{i}                          \n\
     28:   u^{n+1} = u^n + dt \\sum_i b_i JU^{i}                             \n\
     29:                                                                     \n\
     30:   i = 1,...,s (s -> number of stages)                               \n\
     31:                                                                     \n\
     32: At each time step, we solve                                         \n\
     33:                                                                     \n\
     34:  [  1                                  ]     1                      \n\
     35:  [ -- I \\otimes A^{-1} - J \\otimes I ] U = -- u^n \\otimes A^{-1} \n\
     36:  [ dt                                  ]     dt                     \n\
     37:                                                                     \n\
     38:   where A is the Butcher tableaux of the implicit                   \n\
     39:   Runge-Kutta method,                                               \n\
     40:                                                                     \n\
     41: with MATKAIJ and KSP.                                               \n\
     42:                                                                     \n\
     43: Available IRK Methods:                                              \n\
     44:   gauss       n-stage Gauss method                                  \n\
     45:                                                                     \n";

     47: /*T
     48:   Concepts: MATKAIJ
     49:   Concepts: MAT
     50:   Concepts: KSP
     51: T*/

     53: /*
     54:   Include "petscksp.h" so that we can use KSP solvers.  Note that this file
     55:   automatically includes:
     56:   petscsys.h      - base PETSc routines
     57:   petscvec.h      - vectors
     58:   petscmat.h      - matrices
     59:   petscis.h       - index sets
     60:   petscviewer.h   - viewers
     61:   petscpc.h       - preconditioners
     62: */
     63:  #include <petscksp.h>
     64:  #include <petscdt.h>

     66: /* define the IRK methods available */
     67: #define IRKGAUSS      "gauss"

     69: typedef enum {
     70:   PHYSICS_DIFFUSION,
     71:   PHYSICS_ADVECTION
     72: } PhysicsType;
     73: const char *const PhysicsTypes[] = {"DIFFUSION","ADVECTION","PhysicsType","PHYSICS_",NULL};

     75: typedef struct __context__ {
     76:   PetscReal     a;              /* diffusion coefficient      */
     77:   PetscReal     xmin,xmax;      /* domain bounds              */
     78:   PetscInt      imax;           /* number of grid points      */
     79:   PetscInt      niter;          /* number of time iterations  */
     80:   PetscReal     dt;             /* time step size             */
     81:   PhysicsType   physics_type;
     82: } UserContext;

     84: static PetscErrorCode ExactSolution(Vec,void*,PetscReal);
     85: static PetscErrorCode RKCreate_Gauss(PetscInt,PetscScalar**,PetscScalar**,PetscReal**);
     86: static PetscErrorCode Assemble_AdvDiff(MPI_Comm,UserContext*,Mat*);

     88:  #include <petsc/private/kernels/blockinvert.h>

     90: int main(int argc, char **argv)
     91: {
     92:   PetscErrorCode    ierr;
     93:   Vec               u,uex,rhs,z;
     94:   UserContext       ctxt;
     95:   PetscInt          nstages,is,ie,matis,matie,*ix,*ix2;
     96:   PetscInt          n,i,s,t,total_its;
     97:   PetscScalar       *A,*B,*At,*b,*zvals,one = 1.0;
     98:   PetscReal         *c,err,time;
     99:   Mat               Identity,J,TA,SC,R;
    100:   KSP               ksp;
    101:   PetscFunctionList IRKList = NULL;
    102:   char              irktype[256] = IRKGAUSS;

    104:   PetscInitialize(&argc,&argv,(char*)0,help);if (ierr) return ierr;
    105:   PetscFunctionListAdd(&IRKList,IRKGAUSS,RKCreate_Gauss);

    107:   /* default value */
    108:   ctxt.a       = 1.0;
    109:   ctxt.xmin    = 0.0;
    110:   ctxt.xmax    = 1.0;
    111:   ctxt.imax    = 20;
    112:   ctxt.niter   = 0;
    113:   ctxt.dt      = 0.0;
    114:   ctxt.physics_type = PHYSICS_DIFFUSION;

    116:   PetscOptionsBegin(PETSC_COMM_WORLD,NULL,"IRK options","");
    117:   PetscOptionsReal("-a","diffusion coefficient","<1.0>",ctxt.a,&ctxt.a,NULL);
    118:   PetscOptionsInt ("-imax","grid size","<20>",ctxt.imax,&ctxt.imax,NULL);
    119:   PetscOptionsReal("-xmin","xmin","<0.0>",ctxt.xmin,&ctxt.xmin,NULL);
    120:   PetscOptionsReal("-xmax","xmax","<1.0>",ctxt.xmax,&ctxt.xmax,NULL);
    121:   PetscOptionsInt ("-niter","number of time steps","<0>",ctxt.niter,&ctxt.niter,NULL);
    122:   PetscOptionsReal("-dt","time step size","<0.0>",ctxt.dt,&ctxt.dt,NULL);
    123:   PetscOptionsFList("-irk_type","IRK method family","",IRKList,irktype,irktype,sizeof(irktype),NULL);
    124:   nstages = 2;
    125:   PetscOptionsInt ("-irk_nstages","Number of stages in IRK method","",nstages,&nstages,NULL);
    126:   PetscOptionsEnum("-physics_type","Type of process to discretize","",PhysicsTypes,(PetscEnum)ctxt.physics_type,(PetscEnum*)&ctxt.physics_type,NULL);
    127:   PetscOptionsEnd();

    129:   /* allocate and initialize solution vector and exact solution */
    130:   VecCreate(PETSC_COMM_WORLD,&u);
    131:   VecSetSizes(u,PETSC_DECIDE,ctxt.imax);
    132:   VecSetFromOptions(u);
    133:   VecDuplicate(u,&uex);
    134:   /* initial solution */
    135:   ExactSolution(u  ,&ctxt,0.0);
    136:   /* exact   solution */
    137:   ExactSolution(uex,&ctxt,ctxt.dt*ctxt.niter);

    139:   {                             /* Create A,b,c */
    140:     PetscErrorCode (*irkcreate)(PetscInt,PetscScalar**,PetscScalar**,PetscReal**);
    141:     PetscFunctionListFind(IRKList,irktype,&irkcreate);
    142:     (*irkcreate)(nstages,&A,&b,&c);
    143:   }
    144:   {                             /* Invert A */
    145:     /* PETSc does not provide a routine to calculate the inverse of a general matrix.
    146:      * To get the inverse of A, we form a sequential BAIJ matrix from it, consisting of a single block with block size
    147:      * equal to the dimension of A, and then use MatInvertBlockDiagonal(). */
    148:     Mat               A_baij;
    149:     PetscInt          idxm[1]={0},idxn[1]={0};
    150:     const PetscScalar *A_inv;
    151:     MatCreateSeqBAIJ(PETSC_COMM_SELF,nstages,nstages,nstages,1,NULL,&A_baij);
    152:     MatSetOption(A_baij,MAT_ROW_ORIENTED,PETSC_FALSE);
    153:     MatSetValuesBlocked(A_baij,1,idxm,1,idxn,A,INSERT_VALUES);
    154:     MatAssemblyBegin(A_baij,MAT_FINAL_ASSEMBLY);
    155:     MatAssemblyEnd(A_baij,MAT_FINAL_ASSEMBLY);
    156:     MatInvertBlockDiagonal(A_baij,&A_inv);
    157:     PetscMemcpy(A,A_inv,nstages*nstages*sizeof(PetscScalar));
    158:     MatDestroy(&A_baij);
    159:   }
    160:   /* Scale (1/dt)*A^{-1} and (1/dt)*b */
    161:   for (s=0; s<nstages*nstages; s++) A[s] *= 1.0/ctxt.dt;
    162:   for (s=0; s<nstages; s++) b[s] *= (-ctxt.dt);

    164:   /* Compute row sums At and identity B */
    165:   PetscMalloc2(nstages,&At,PetscSqr(nstages),&B);
    166:   for (s=0; s<nstages; s++) {
    167:     At[s] = 0;
    168:     for (t=0; t<nstages; t++) {
    169:       At[s] += A[s+nstages*t];      /* Row sums of  */
    170:       B[s+nstages*t] = 1.*(s == t); /* identity */
    171:     }
    172:   }

    174:   /* allocate and calculate the (-J) matrix */
    175:   switch (ctxt.physics_type) {
    176:   case PHYSICS_ADVECTION:
    177:   case PHYSICS_DIFFUSION:
    178:     Assemble_AdvDiff(PETSC_COMM_WORLD,&ctxt,&J);
    179:   }
    180:   MatCreate(PETSC_COMM_WORLD,&Identity);
    181:   MatSetType(Identity,MATAIJ);
    182:   MatGetOwnershipRange(J,&matis,&matie);
    183:   MatSetSizes(Identity,matie-matis,matie-matis,ctxt.imax,ctxt.imax);
    184:   MatSetUp(Identity);
    185:   for (i=matis; i<matie; i++) {
    186:     MatSetValues(Identity,1,&i,1,&i,&one,INSERT_VALUES);
    187:   }
    188:   MatAssemblyBegin(Identity,MAT_FINAL_ASSEMBLY);
    189:   MatAssemblyEnd  (Identity,MAT_FINAL_ASSEMBLY);

    191:   /* Create the KAIJ matrix for solving the stages */
    192:   MatCreateKAIJ(J,nstages,nstages,A,B,&TA);

    194:   /* Create the KAIJ matrix for step completion */
    195:   MatCreateKAIJ(J,1,nstages,NULL,b,&SC);

    197:   /* Create the KAIJ matrix to create the R for solving the stages */
    198:   MatCreateKAIJ(Identity,nstages,1,NULL,At,&R);

    200:   /* Create and set options for KSP */
    201:   KSPCreate(PETSC_COMM_WORLD,&ksp);
    202:   KSPSetOperators(ksp,TA,TA);
    203:   KSPSetFromOptions(ksp);

    205:   /* Allocate work and right-hand-side vectors */
    206:   VecCreate(PETSC_COMM_WORLD,&z);
    207:   VecSetFromOptions(z);
    208:   VecSetSizes(z,PETSC_DECIDE,ctxt.imax*nstages);
    209:   VecDuplicate(z,&rhs);

    211:   VecGetOwnershipRange(u,&is,&ie);
    212:   PetscMalloc3(nstages,&ix,nstages,&zvals,ie-is,&ix2);
    213:   /* iterate in time */
    214:   for (n=0,time=0.,total_its=0; n<ctxt.niter; n++) {
    215:     PetscInt its;

    217:     /* compute and set the right hand side */
    218:     MatMult(R,u,rhs);

    220:     /* Solve the system */
    221:     KSPSolve(ksp,rhs,z);
    222:     KSPGetIterationNumber(ksp,&its);
    223:     total_its += its;

    225:     /* Update the solution */
    226:     MatMultAdd(SC,z,u,u);

    228:     /* time step complete */
    229:     time += ctxt.dt;
    230:   }
    231:   PetscFree3(ix,ix2,zvals);

    233:   /* Deallocate work and right-hand-side vectors */
    234:   VecDestroy(&z);
    235:   VecDestroy(&rhs);

    237:   /* Calculate error in final solution */
    238:   VecAYPX(uex,-1.0,u);
    239:   VecNorm(uex,NORM_2,&err);
    240:   err  = PetscSqrtReal(err*err/((PetscReal)ctxt.imax));
    241:   PetscPrintf(PETSC_COMM_WORLD,"L2 norm of the numerical error = %g (time=%g)\n",(double)err,(double)time);
    242:   PetscPrintf(PETSC_COMM_WORLD,"Number of time steps: %D (%D Krylov iterations)\n",ctxt.niter,total_its);

    244:   /* Free up memory */
    245:   KSPDestroy(&ksp);
    246:   MatDestroy(&TA);
    247:   MatDestroy(&SC);
    248:   MatDestroy(&R);
    249:   MatDestroy(&J);
    250:   MatDestroy(&Identity);
    251:   PetscFree3(A,b,c);
    252:   PetscFree2(At,B);
    253:   VecDestroy(&uex);
    254:   VecDestroy(&u);
    255:   PetscFunctionListDestroy(&IRKList);

    257:   PetscFinalize();
    258:   return ierr;
    259: }

    261: PetscErrorCode ExactSolution(Vec u,void *c,PetscReal t)
    262: {
    263:   UserContext     *ctxt = (UserContext*) c;
    264:   PetscErrorCode  ierr;
    265:   PetscInt        i,is,ie;
    266:   PetscScalar     *uarr;
    267:   PetscReal       x,dx,a=ctxt->a,pi=PETSC_PI;

    270:   dx = (ctxt->xmax - ctxt->xmin)/((PetscReal) ctxt->imax);
    271:   VecGetOwnershipRange(u,&is,&ie);
    272:   VecGetArray(u,&uarr);
    273:   for(i=is; i<ie; i++) {
    274:     x          = i * dx;
    275:     switch (ctxt->physics_type) {
    276:     case PHYSICS_DIFFUSION:
    277:       uarr[i-is] = PetscExpScalar(-4.0*pi*pi*a*t)*PetscSinScalar(2*pi*x);
    278:       break;
    279:     case PHYSICS_ADVECTION:
    280:       uarr[i-is] = PetscSinScalar(2*pi*(x - a*t));
    281:       break;
    282:     default: SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_SUP,"No support for physics type %s",PhysicsTypes[ctxt->physics_type]);
    283:     }
    284:   }
    285:   VecRestoreArray(u,&uarr);
    286:   return(0);
    287: }

    289: /* Arrays should be freed with PetscFree3(A,b,c) */
    290: static PetscErrorCode RKCreate_Gauss(PetscInt nstages,PetscScalar **gauss_A,PetscScalar **gauss_b,PetscReal **gauss_c)
    291: {
    292:   PetscErrorCode    ierr;
    293:   PetscScalar       *A,*G0,*G1;
    294:   PetscReal         *b,*c;
    295:   PetscInt          i,j;
    296:   Mat               G0mat,G1mat,Amat;

    299:   PetscMalloc3(PetscSqr(nstages),&A,nstages,gauss_b,nstages,&c);
    300:   PetscMalloc3(nstages,&b,PetscSqr(nstages),&G0,PetscSqr(nstages),&G1);
    301:   PetscDTGaussQuadrature(nstages,0.,1.,c,b);
    302:   for (i=0; i<nstages; i++) (*gauss_b)[i] = b[i]; /* copy to possibly-complex array */

    304:   /* A^T = G0^{-1} G1 */
    305:   for (i=0; i<nstages; i++) {
    306:     for (j=0; j<nstages; j++) {
    307:       G0[i*nstages+j] = PetscPowRealInt(c[i],j);
    308:       G1[i*nstages+j] = PetscPowRealInt(c[i],j+1)/(j+1);
    309:     }
    310:   }
    311:   /* The arrays above are row-aligned, but we create dense matrices as the transpose */
    312:   MatCreateSeqDense(PETSC_COMM_SELF,nstages,nstages,G0,&G0mat);
    313:   MatCreateSeqDense(PETSC_COMM_SELF,nstages,nstages,G1,&G1mat);
    314:   MatCreateSeqDense(PETSC_COMM_SELF,nstages,nstages,A,&Amat);
    315:   MatLUFactor(G0mat,NULL,NULL,NULL);
    316:   MatMatSolve(G0mat,G1mat,Amat);
    317:   MatTranspose(Amat,MAT_INPLACE_MATRIX,&Amat);

    319:   MatDestroy(&G0mat);
    320:   MatDestroy(&G1mat);
    321:   MatDestroy(&Amat);
    322:   PetscFree3(b,G0,G1);
    323:   *gauss_A = A;
    324:   *gauss_c = c;
    325:   return(0);
    326: }

    328: static PetscErrorCode Assemble_AdvDiff(MPI_Comm comm,UserContext *user,Mat *J)
    329: {
    331:   PetscInt       matis,matie,i;
    332:   PetscReal      dx,dx2;

    335:   dx = (user->xmax - user->xmin)/((PetscReal)user->imax); dx2 = dx*dx;
    336:   MatCreate(comm,J);
    337:   MatSetType(*J,MATAIJ);
    338:   MatSetSizes(*J,PETSC_DECIDE,PETSC_DECIDE,user->imax,user->imax);
    339:   MatSetUp(*J);
    340:   MatGetOwnershipRange(*J,&matis,&matie);
    341:   for (i=matis; i<matie; i++) {
    342:     PetscScalar values[3];
    343:     PetscInt    col[3];
    344:     switch (user->physics_type) {
    345:     case PHYSICS_DIFFUSION:
    346:       values[0] = -user->a*1.0/dx2;
    347:       values[1] = user->a*2.0/dx2;
    348:       values[2] = -user->a*1.0/dx2;
    349:       break;
    350:     case PHYSICS_ADVECTION:
    351:       values[0] = -user->a*.5/dx;
    352:       values[1] = 0.;
    353:       values[2] = user->a*.5/dx;
    354:       break;
    355:     default: SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_SUP,"No support for physics type %s",PhysicsTypes[user->physics_type]);
    356:     }
    357:     /* periodic boundaries */
    358:     if (i == 0) {
    359:       col[0] = user->imax-1;
    360:       col[1] = i;
    361:       col[2] = i+1;
    362:     } else if (i == user->imax-1) {
    363:       col[0] = i-1;
    364:       col[1] = i;
    365:       col[2] = 0;
    366:     } else {
    367:       col[0] = i-1;
    368:       col[1] = i;
    369:       col[2] = i+1;
    370:     }
    371:     MatSetValues(*J,1,&i,3,col,values,INSERT_VALUES);
    372:   }
    373:   MatAssemblyBegin(*J,MAT_FINAL_ASSEMBLY);
    374:   MatAssemblyEnd  (*J,MAT_FINAL_ASSEMBLY);
    375:   return(0);
    376: }

    378: /*TEST
    379:  test:
    380:    suffix: 1
    381:    args: -a 0.1 -dt .125 -niter 5 -imax 40 -ksp_monitor_short -pc_type pbjacobi -ksp_atol 1e-6 -irk_type gauss -irk_nstages 2
    382:  test:
    383:    suffix: 2
    384:    args: -a 0.1 -dt .125 -niter 5 -imax 40 -ksp_monitor_short -pc_type pbjacobi -ksp_atol 1e-6 -irk_type gauss -irk_nstages 4 -ksp_gmres_restart 100
    385:  test:
    386:    suffix: 3
    387:    requires: !single
    388:    args: -a 1 -dt .33 -niter 3 -imax 40 -ksp_monitor_short -pc_type pbjacobi -ksp_atol 1e-6 -irk_type gauss -irk_nstages 4 -ksp_gmres_restart 100 -physics_type advection

    390: TEST*/