Date: 2022-08-02T03:15:00+00:00

Actual source code: ssp.c

      1: /*
      2:        Code for Timestepping with explicit SSP.
      3: */
      4: #include <petsc/private/tsimpl.h>

      6: PetscFunctionList TSSSPList = NULL;
      7: static PetscBool TSSSPPackageInitialized;

      9: typedef struct {
     10:   PetscErrorCode (*onestep)(TS,PetscReal,PetscReal,Vec);
     11:   char           *type_name;
     12:   PetscInt       nstages;
     13:   Vec            *work;
     14:   PetscInt       nwork;
     15:   PetscBool      workout;
     16: } TS_SSP;

     18: static PetscErrorCode TSSSPGetWorkVectors(TS ts,PetscInt n,Vec **work)
     19: {
     20:   TS_SSP         *ssp = (TS_SSP*)ts->data;

     23:   if (ssp->nwork < n) {
     24:     if (ssp->nwork > 0) {
     25:       VecDestroyVecs(ssp->nwork,&ssp->work);
     26:     }
     27:     VecDuplicateVecs(ts->vec_sol,n,&ssp->work);
     28:     ssp->nwork = n;
     29:   }
     30:   *work = ssp->work;
     31:   ssp->workout = PETSC_TRUE;
     32:   return 0;
     33: }

     35: static PetscErrorCode TSSSPRestoreWorkVectors(TS ts,PetscInt n,Vec **work)
     36: {
     37:   TS_SSP *ssp = (TS_SSP*)ts->data;

     41:   ssp->workout = PETSC_FALSE;
     42:   *work = NULL;
     43:   return 0;
     44: }

     46: /*MC
     47:    TSSSPRKS2 - Optimal second order SSP Runge-Kutta method, low-storage, c_eff=(s-1)/s

     49:    Pseudocode 2 of Ketcheson 2008

     51:    Level: beginner

     53: .seealso: TSSSP, TSSSPSetType(), TSSSPSetNumStages()
     54: M*/
     55: static PetscErrorCode TSSSPStep_RK_2(TS ts,PetscReal t0,PetscReal dt,Vec sol)
     56: {
     57:   TS_SSP         *ssp = (TS_SSP*)ts->data;
     58:   Vec            *work,F;
     59:   PetscInt       i,s;

     61:   s    = ssp->nstages;
     62:   TSSSPGetWorkVectors(ts,2,&work);
     63:   F    = work[1];
     64:   VecCopy(sol,work[0]);
     65:   for (i=0; i<s-1; i++) {
     66:     PetscReal stage_time = t0+dt*(i/(s-1.));
     67:     TSPreStage(ts,stage_time);
     68:     TSComputeRHSFunction(ts,stage_time,work[0],F);
     69:     VecAXPY(work[0],dt/(s-1.),F);
     70:   }
     71:   TSComputeRHSFunction(ts,t0+dt,work[0],F);
     72:   VecAXPBYPCZ(sol,(s-1.)/s,dt/s,1./s,work[0],F);
     73:   TSSSPRestoreWorkVectors(ts,2,&work);
     74:   return 0;
     75: }

     77: /*MC
     78:    TSSSPRKS3 - Optimal third order SSP Runge-Kutta, low-storage, c_eff=(PetscSqrtReal(s)-1)/PetscSqrtReal(s), where PetscSqrtReal(s) is an integer

     80:    Pseudocode 2 of Ketcheson 2008

     82:    Level: beginner

     84: .seealso: TSSSP, TSSSPSetType(), TSSSPSetNumStages()
     85: M*/
     86: static PetscErrorCode TSSSPStep_RK_3(TS ts,PetscReal t0,PetscReal dt,Vec sol)
     87: {
     88:   TS_SSP         *ssp = (TS_SSP*)ts->data;
     89:   Vec            *work,F;
     90:   PetscInt       i,s,n,r;
     91:   PetscReal      c,stage_time;

     93:   s = ssp->nstages;
     94:   n = (PetscInt)(PetscSqrtReal((PetscReal)s)+0.001);
     95:   r = s-n;
     97:   TSSSPGetWorkVectors(ts,3,&work);
     98:   F    = work[2];
     99:   VecCopy(sol,work[0]);
    100:   for (i=0; i<(n-1)*(n-2)/2; i++) {
    101:     c          = (i<n*(n+1)/2) ? 1.*i/(s-n) : (1.*i-n)/(s-n);
    102:     stage_time = t0+c*dt;
    103:     TSPreStage(ts,stage_time);
    104:     TSComputeRHSFunction(ts,stage_time,work[0],F);
    105:     VecAXPY(work[0],dt/r,F);
    106:   }
    107:   VecCopy(work[0],work[1]);
    108:   for (; i<n*(n+1)/2-1; i++) {
    109:     c          = (i<n*(n+1)/2) ? 1.*i/(s-n) : (1.*i-n)/(s-n);
    110:     stage_time = t0+c*dt;
    111:     TSPreStage(ts,stage_time);
    112:     TSComputeRHSFunction(ts,stage_time,work[0],F);
    113:     VecAXPY(work[0],dt/r,F);
    114:   }
    115:   {
    116:     c          = (i<n*(n+1)/2) ? 1.*i/(s-n) : (1.*i-n)/(s-n);
    117:     stage_time = t0+c*dt;
    118:     TSPreStage(ts,stage_time);
    119:     TSComputeRHSFunction(ts,stage_time,work[0],F);
    120:     VecAXPBYPCZ(work[0],1.*n/(2*n-1.),(n-1.)*dt/(r*(2*n-1)),(n-1.)/(2*n-1.),work[1],F);
    121:     i++;
    122:   }
    123:   for (; i<s; i++) {
    124:     c          = (i<n*(n+1)/2) ? 1.*i/(s-n) : (1.*i-n)/(s-n);
    125:     stage_time = t0+c*dt;
    126:     TSPreStage(ts,stage_time);
    127:     TSComputeRHSFunction(ts,stage_time,work[0],F);
    128:     VecAXPY(work[0],dt/r,F);
    129:   }
    130:   VecCopy(work[0],sol);
    131:   TSSSPRestoreWorkVectors(ts,3,&work);
    132:   return 0;
    133: }

    135: /*MC
    136:    TSSSPRKS104 - Optimal fourth order SSP Runge-Kutta, low-storage (2N), c_eff=0.6

    138:    SSPRK(10,4), Pseudocode 3 of Ketcheson 2008

    140:    Level: beginner

    142: .seealso: TSSSP, TSSSPSetType()
    143: M*/
    144: static PetscErrorCode TSSSPStep_RK_10_4(TS ts,PetscReal t0,PetscReal dt,Vec sol)
    145: {
    146:   const PetscReal c[10] = {0, 1./6, 2./6, 3./6, 4./6, 2./6, 3./6, 4./6, 5./6, 1};
    147:   Vec             *work,F;
    148:   PetscInt        i;
    149:   PetscReal       stage_time;

    151:   TSSSPGetWorkVectors(ts,3,&work);
    152:   F    = work[2];
    153:   VecCopy(sol,work[0]);
    154:   for (i=0; i<5; i++) {
    155:     stage_time = t0+c[i]*dt;
    156:     TSPreStage(ts,stage_time);
    157:     TSComputeRHSFunction(ts,stage_time,work[0],F);
    158:     VecAXPY(work[0],dt/6,F);
    159:   }
    160:   VecAXPBYPCZ(work[1],1./25,9./25,0,sol,work[0]);
    161:   VecAXPBY(work[0],15,-5,work[1]);
    162:   for (; i<9; i++) {
    163:     stage_time = t0+c[i]*dt;
    164:     TSPreStage(ts,stage_time);
    165:     TSComputeRHSFunction(ts,stage_time,work[0],F);
    166:     VecAXPY(work[0],dt/6,F);
    167:   }
    168:   stage_time = t0+dt;
    169:   TSPreStage(ts,stage_time);
    170:   TSComputeRHSFunction(ts,stage_time,work[0],F);
    171:   VecAXPBYPCZ(work[1],3./5,dt/10,1,work[0],F);
    172:   VecCopy(work[1],sol);
    173:   TSSSPRestoreWorkVectors(ts,3,&work);
    174:   return 0;
    175: }

    177: static PetscErrorCode TSSetUp_SSP(TS ts)
    178: {
    179:   TSCheckImplicitTerm(ts);
    180:   TSGetAdapt(ts,&ts->adapt);
    181:   TSAdaptCandidatesClear(ts->adapt);
    182:   return 0;
    183: }

    185: static PetscErrorCode TSStep_SSP(TS ts)
    186: {
    187:   TS_SSP         *ssp = (TS_SSP*)ts->data;
    188:   Vec            sol  = ts->vec_sol;
    189:   PetscBool      stageok,accept = PETSC_TRUE;
    190:   PetscReal      next_time_step = ts->time_step;

    192:   (*ssp->onestep)(ts,ts->ptime,ts->time_step,sol);
    193:   TSPostStage(ts,ts->ptime,0,&sol);
    194:   TSAdaptCheckStage(ts->adapt,ts,ts->ptime+ts->time_step,sol,&stageok);
    195:   if (!stageok) {ts->reason = TS_DIVERGED_STEP_REJECTED; return 0;}

    197:   TSAdaptChoose(ts->adapt,ts,ts->time_step,NULL,&next_time_step,&accept);
    198:   if (!accept) {ts->reason = TS_DIVERGED_STEP_REJECTED; return 0;}

    200:   ts->ptime += ts->time_step;
    201:   ts->time_step = next_time_step;
    202:   return 0;
    203: }
    204: /*------------------------------------------------------------*/

    206: static PetscErrorCode TSReset_SSP(TS ts)
    207: {
    208:   TS_SSP         *ssp = (TS_SSP*)ts->data;

    210:   if (ssp->work) VecDestroyVecs(ssp->nwork,&ssp->work);
    211:   ssp->nwork   = 0;
    212:   ssp->workout = PETSC_FALSE;
    213:   return 0;
    214: }

    216: static PetscErrorCode TSDestroy_SSP(TS ts)
    217: {
    218:   TS_SSP         *ssp = (TS_SSP*)ts->data;

    220:   TSReset_SSP(ts);
    221:   PetscFree(ssp->type_name);
    222:   PetscFree(ts->data);
    223:   PetscObjectComposeFunction((PetscObject)ts,"TSSSPGetType_C",NULL);
    224:   PetscObjectComposeFunction((PetscObject)ts,"TSSSPSetType_C",NULL);
    225:   PetscObjectComposeFunction((PetscObject)ts,"TSSSPGetNumStages_C",NULL);
    226:   PetscObjectComposeFunction((PetscObject)ts,"TSSSPSetNumStages_C",NULL);
    227:   return 0;
    228: }
    229: /*------------------------------------------------------------*/

    231: /*@C
    232:    TSSSPSetType - set the SSP time integration scheme to use

    234:    Logically Collective

    236:    Input Parameters:
    237: +  ts - time stepping object
    238: -  ssptype - type of scheme to use

    240:    Options Database Keys:
    241:    -ts_ssp_type <rks2>: Type of SSP method (one of) rks2 rks3 rk104
    242:    -ts_ssp_nstages <5>: Number of stages

    244:    Level: beginner

    246: .seealso: TSSSP, TSSSPGetType(), TSSSPSetNumStages(), TSSSPRKS2, TSSSPRKS3, TSSSPRK104
    247: @*/
    248: PetscErrorCode TSSSPSetType(TS ts,TSSSPType ssptype)
    249: {
    252:   PetscTryMethod(ts,"TSSSPSetType_C",(TS,TSSSPType),(ts,ssptype));
    253:   return 0;
    254: }

    256: /*@C
    257:    TSSSPGetType - get the SSP time integration scheme

    259:    Logically Collective

    261:    Input Parameter:
    262: .  ts - time stepping object

    264:    Output Parameter:
    265: .  type - type of scheme being used

    267:    Level: beginner

    269: .seealso: TSSSP, TSSSPSettype(), TSSSPSetNumStages(), TSSSPRKS2, TSSSPRKS3, TSSSPRK104
    270: @*/
    271: PetscErrorCode TSSSPGetType(TS ts,TSSSPType *type)
    272: {
    274:   PetscUseMethod(ts,"TSSSPGetType_C",(TS,TSSSPType*),(ts,type));
    275:   return 0;
    276: }

    278: /*@
    279:    TSSSPSetNumStages - set the number of stages to use with the SSP method

    281:    Logically Collective

    283:    Input Parameters:
    284: +  ts - time stepping object
    285: -  nstages - number of stages

    287:    Options Database Keys:
    288:    -ts_ssp_type <rks2>: NumStages of SSP method (one of) rks2 rks3 rk104
    289:    -ts_ssp_nstages <5>: Number of stages

    291:    Level: beginner

    293: .seealso: TSSSP, TSSSPGetNumStages(), TSSSPSetNumStages(), TSSSPRKS2, TSSSPRKS3, TSSSPRK104
    294: @*/
    295: PetscErrorCode TSSSPSetNumStages(TS ts,PetscInt nstages)
    296: {
    298:   PetscTryMethod(ts,"TSSSPSetNumStages_C",(TS,PetscInt),(ts,nstages));
    299:   return 0;
    300: }

    302: /*@
    303:    TSSSPGetNumStages - get the number of stages in the SSP time integration scheme

    305:    Logically Collective

    307:    Input Parameter:
    308: .  ts - time stepping object

    310:    Output Parameter:
    311: .  nstages - number of stages

    313:    Level: beginner

    315: .seealso: TSSSP, TSSSPGetType(), TSSSPSetNumStages(), TSSSPRKS2, TSSSPRKS3, TSSSPRK104
    316: @*/
    317: PetscErrorCode TSSSPGetNumStages(TS ts,PetscInt *nstages)
    318: {
    320:   PetscUseMethod(ts,"TSSSPGetNumStages_C",(TS,PetscInt*),(ts,nstages));
    321:   return 0;
    322: }

    324: static PetscErrorCode TSSSPSetType_SSP(TS ts,TSSSPType type)
    325: {
    326:   TS_SSP         *ssp = (TS_SSP*)ts->data;
    327:   PetscErrorCode (*r)(TS,PetscReal,PetscReal,Vec);

    329:   PetscFunctionListFind(TSSSPList,type,&r);
    331:   ssp->onestep = r;
    332:   PetscFree(ssp->type_name);
    333:   PetscStrallocpy(type,&ssp->type_name);
    334:   ts->default_adapt_type = TSADAPTNONE;
    335:   return 0;
    336: }
    337: static PetscErrorCode TSSSPGetType_SSP(TS ts,TSSSPType *type)
    338: {
    339:   TS_SSP *ssp = (TS_SSP*)ts->data;

    341:   *type = ssp->type_name;
    342:   return 0;
    343: }
    344: static PetscErrorCode TSSSPSetNumStages_SSP(TS ts,PetscInt nstages)
    345: {
    346:   TS_SSP *ssp = (TS_SSP*)ts->data;

    348:   ssp->nstages = nstages;
    349:   return 0;
    350: }
    351: static PetscErrorCode TSSSPGetNumStages_SSP(TS ts,PetscInt *nstages)
    352: {
    353:   TS_SSP *ssp = (TS_SSP*)ts->data;

    355:   *nstages = ssp->nstages;
    356:   return 0;
    357: }

    359: static PetscErrorCode TSSetFromOptions_SSP(PetscOptionItems *PetscOptionsObject,TS ts)
    360: {
    361:   char           tname[256] = TSSSPRKS2;
    362:   TS_SSP         *ssp       = (TS_SSP*)ts->data;
    363:   PetscBool      flg;

    365:   PetscOptionsHead(PetscOptionsObject,"SSP ODE solver options");
    366:   {
    367:     PetscOptionsFList("-ts_ssp_type","Type of SSP method","TSSSPSetType",TSSSPList,tname,tname,sizeof(tname),&flg);
    368:     if (flg) {
    369:       TSSSPSetType(ts,tname);
    370:     }
    371:     PetscOptionsInt("-ts_ssp_nstages","Number of stages","TSSSPSetNumStages",ssp->nstages,&ssp->nstages,NULL);
    372:   }
    373:   PetscOptionsTail();
    374:   return 0;
    375: }

    377: static PetscErrorCode TSView_SSP(TS ts,PetscViewer viewer)
    378: {
    379:   TS_SSP         *ssp = (TS_SSP*)ts->data;
    380:   PetscBool      ascii;

    382:   PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERASCII,&ascii);
    383:   if (ascii) PetscViewerASCIIPrintf(viewer,"  Scheme: %s\n",ssp->type_name);
    384:   return 0;
    385: }

    387: /* ------------------------------------------------------------ */

    389: /*MC
    390:       TSSSP - Explicit strong stability preserving ODE solver

    392:   Most hyperbolic conservation laws have exact solutions that are total variation diminishing (TVD) or total variation
    393:   bounded (TVB) although these solutions often contain discontinuities.  Spatial discretizations such as Godunov's
    394:   scheme and high-resolution finite volume methods (TVD limiters, ENO/WENO) are designed to preserve these properties,
    395:   but they are usually formulated using a forward Euler time discretization or by coupling the space and time
    396:   discretization as in the classical Lax-Wendroff scheme.  When the space and time discretization is coupled, it is very
    397:   difficult to produce schemes with high temporal accuracy while preserving TVD properties.  An alternative is the
    398:   semidiscrete formulation where we choose a spatial discretization that is TVD with forward Euler and then choose a
    399:   time discretization that preserves the TVD property.  Such integrators are called strong stability preserving (SSP).

    401:   Let c_eff be the minimum number of function evaluations required to step as far as one step of forward Euler while
    402:   still being SSP.  Some theoretical bounds

    404:   1. There are no explicit methods with c_eff > 1.

    406:   2. There are no explicit methods beyond order 4 (for nonlinear problems) and c_eff > 0.

    408:   3. There are no implicit methods with order greater than 1 and c_eff > 2.

    410:   This integrator provides Runge-Kutta methods of order 2, 3, and 4 with maximal values of c_eff.  More stages allows
    411:   for larger values of c_eff which improves efficiency.  These implementations are low-memory and only use 2 or 3 work
    412:   vectors regardless of the total number of stages, so e.g. 25-stage 3rd order methods may be an excellent choice.

    414:   Methods can be chosen with -ts_ssp_type {rks2,rks3,rk104}

    416:   rks2: Second order methods with any number s>1 of stages.  c_eff = (s-1)/s

    418:   rks3: Third order methods with s=n^2 stages, n>1.  c_eff = (s-n)/s

    420:   rk104: A 10-stage fourth order method.  c_eff = 0.6

    422:   Level: beginner

    424:   References:
    425: +  * - Ketcheson, Highly efficient strong stability preserving Runge Kutta methods with low storage implementations, SISC, 2008.
    426: -  * - Gottlieb, Ketcheson, and Shu, High order strong stability preserving time discretizations, J Scientific Computing, 2009.

    428: .seealso:  TSCreate(), TS, TSSetType()

    430: M*/
    431: PETSC_EXTERN PetscErrorCode TSCreate_SSP(TS ts)
    432: {
    433:   TS_SSP         *ssp;

    435:   TSSSPInitializePackage();

    437:   ts->ops->setup          = TSSetUp_SSP;
    438:   ts->ops->step           = TSStep_SSP;
    439:   ts->ops->reset          = TSReset_SSP;
    440:   ts->ops->destroy        = TSDestroy_SSP;
    441:   ts->ops->setfromoptions = TSSetFromOptions_SSP;
    442:   ts->ops->view           = TSView_SSP;

    444:   PetscNewLog(ts,&ssp);
    445:   ts->data = (void*)ssp;

    447:   PetscObjectComposeFunction((PetscObject)ts,"TSSSPGetType_C",TSSSPGetType_SSP);
    448:   PetscObjectComposeFunction((PetscObject)ts,"TSSSPSetType_C",TSSSPSetType_SSP);
    449:   PetscObjectComposeFunction((PetscObject)ts,"TSSSPGetNumStages_C",TSSSPGetNumStages_SSP);
    450:   PetscObjectComposeFunction((PetscObject)ts,"TSSSPSetNumStages_C",TSSSPSetNumStages_SSP);

    452:   TSSSPSetType(ts,TSSSPRKS2);
    453:   ssp->nstages = 5;
    454:   return 0;
    455: }

    457: /*@C
    458:   TSSSPInitializePackage - This function initializes everything in the TSSSP package. It is called
    459:   from TSInitializePackage().

    461:   Level: developer

    463: .seealso: PetscInitialize()
    464: @*/
    465: PetscErrorCode TSSSPInitializePackage(void)
    466: {
    467:   if (TSSSPPackageInitialized) return 0;
    468:   TSSSPPackageInitialized = PETSC_TRUE;
    469:   PetscFunctionListAdd(&TSSSPList,TSSSPRKS2, TSSSPStep_RK_2);
    470:   PetscFunctionListAdd(&TSSSPList,TSSSPRKS3, TSSSPStep_RK_3);
    471:   PetscFunctionListAdd(&TSSSPList,TSSSPRK104,TSSSPStep_RK_10_4);
    472:   PetscRegisterFinalize(TSSSPFinalizePackage);
    473:   return 0;
    474: }

    476: /*@C
    477:   TSSSPFinalizePackage - This function destroys everything in the TSSSP package. It is
    478:   called from PetscFinalize().

    480:   Level: developer

    482: .seealso: PetscFinalize()
    483: @*/
    484: PetscErrorCode TSSSPFinalizePackage(void)
    485: {
    486:   TSSSPPackageInitialized = PETSC_FALSE;
    487:   PetscFunctionListDestroy(&TSSSPList);
    488:   return 0;
    489: }