Date: 2026-05-01T06:12:08+00:00

Actual source code: ipm.c

      1: #include <petsctaolinesearch.h>
      2: #include <../src/tao/constrained/impls/ipm/ipm.h>

      4: /*
      5:    x,d in R^n
      6:    f in R
      7:    nb = mi + nlb+nub
      8:    s in R^nb is slack vector CI(x) / x-XL / -x+XU
      9:    bin in R^mi (tao->constraints_inequality)
     10:    beq in R^me (tao->constraints_equality)
     11:    lambdai in R^nb (ipmP->lambdai)
     12:    lambdae in R^me (ipmP->lambdae)
     13:    Jeq in R^(me x n) (tao->jacobian_equality)
     14:    Jin in R^(mi x n) (tao->jacobian_inequality)
     15:    Ai in  R^(nb x n) (ipmP->Ai)
     16:    H in R^(n x n) (tao->hessian)
     17:    min f=(1/2)*x'*H*x + d'*x
     18:    s.t.  CE(x) == 0
     19:          CI(x) >= 0
     20:          x >= tao->XL
     21:          -x >= -tao->XU
     22: */

     24: static PetscErrorCode IPMComputeKKT(Tao tao);
     25: static PetscErrorCode IPMPushInitialPoint(Tao tao);
     26: static PetscErrorCode IPMEvaluate(Tao tao);
     27: static PetscErrorCode IPMUpdateK(Tao tao);
     28: static PetscErrorCode IPMUpdateAi(Tao tao);
     29: static PetscErrorCode IPMGatherRHS(Tao tao, Vec, Vec, Vec, Vec, Vec);
     30: static PetscErrorCode IPMScatterStep(Tao tao, Vec, Vec, Vec, Vec, Vec);
     31: static PetscErrorCode IPMInitializeBounds(Tao tao);

     33: static PetscErrorCode TaoSolve_IPM(Tao tao)
     34: {
     35:   TAO_IPM    *ipmP = (TAO_IPM *)tao->data;
     36:   PetscInt    its, i;
     37:   PetscScalar stepsize = 1.0;
     38:   PetscScalar step_s, step_l, alpha, tau, sigma, phi_target;

     40:   PetscFunctionBegin;
     41:   /* Push initial point away from bounds */
     42:   PetscCall(IPMInitializeBounds(tao));
     43:   PetscCall(IPMPushInitialPoint(tao));
     44:   PetscCall(VecCopy(tao->solution, ipmP->rhs_x));
     45:   PetscCall(IPMEvaluate(tao));
     46:   PetscCall(IPMComputeKKT(tao));

     48:   tao->reason = TAO_CONTINUE_ITERATING;
     49:   PetscCall(TaoLogConvergenceHistory(tao, ipmP->kkt_f, ipmP->phi, 0.0, tao->ksp_its));
     50:   PetscCall(TaoMonitor(tao, tao->niter, ipmP->kkt_f, ipmP->phi, 0.0, 1.0));
     51:   PetscUseTypeMethod(tao, convergencetest, tao->cnvP);

     53:   while (tao->reason == TAO_CONTINUE_ITERATING) {
     54:     /* Call general purpose update function */
     55:     PetscTryTypeMethod(tao, update, tao->niter, tao->user_update);

     57:     tao->ksp_its = 0;
     58:     PetscCall(IPMUpdateK(tao));
     59:     /*
     60:        rhs.x    = -rd
     61:        rhs.lame = -rpe
     62:        rhs.lami = -rpi
     63:        rhs.com  = -com
     64:     */

     66:     PetscCall(VecCopy(ipmP->rd, ipmP->rhs_x));
     67:     if (ipmP->me > 0) PetscCall(VecCopy(ipmP->rpe, ipmP->rhs_lambdae));
     68:     if (ipmP->nb > 0) {
     69:       PetscCall(VecCopy(ipmP->rpi, ipmP->rhs_lambdai));
     70:       PetscCall(VecCopy(ipmP->complementarity, ipmP->rhs_s));
     71:     }
     72:     PetscCall(IPMGatherRHS(tao, ipmP->bigrhs, ipmP->rhs_x, ipmP->rhs_lambdae, ipmP->rhs_lambdai, ipmP->rhs_s));
     73:     PetscCall(VecScale(ipmP->bigrhs, -1.0));

     75:     /* solve K * step = rhs */
     76:     PetscCall(KSPSetOperators(tao->ksp, ipmP->K, ipmP->K));
     77:     PetscCall(KSPSolve(tao->ksp, ipmP->bigrhs, ipmP->bigstep));

     79:     PetscCall(IPMScatterStep(tao, ipmP->bigstep, tao->stepdirection, ipmP->ds, ipmP->dlambdae, ipmP->dlambdai));
     80:     PetscCall(KSPGetIterationNumber(tao->ksp, &its));
     81:     tao->ksp_its += its;
     82:     tao->ksp_tot_its += its;
     83:     /* Find distance along step direction to closest bound */
     84:     if (ipmP->nb > 0) {
     85:       PetscCall(VecStepBoundInfo(ipmP->s, ipmP->ds, ipmP->Zero_nb, ipmP->Inf_nb, &step_s, NULL, NULL));
     86:       PetscCall(VecStepBoundInfo(ipmP->lambdai, ipmP->dlambdai, ipmP->Zero_nb, ipmP->Inf_nb, &step_l, NULL, NULL));
     87:       alpha        = PetscMin(step_s, step_l);
     88:       alpha        = PetscMin(alpha, 1.0);
     89:       ipmP->alpha1 = alpha;
     90:     } else {
     91:       ipmP->alpha1 = alpha = 1.0;
     92:     }

     94:     /* x_aff = x + alpha*d */
     95:     PetscCall(VecCopy(tao->solution, ipmP->save_x));
     96:     if (ipmP->me > 0) PetscCall(VecCopy(ipmP->lambdae, ipmP->save_lambdae));
     97:     if (ipmP->nb > 0) {
     98:       PetscCall(VecCopy(ipmP->lambdai, ipmP->save_lambdai));
     99:       PetscCall(VecCopy(ipmP->s, ipmP->save_s));
    100:     }

    102:     PetscCall(VecAXPY(tao->solution, alpha, tao->stepdirection));
    103:     if (ipmP->me > 0) PetscCall(VecAXPY(ipmP->lambdae, alpha, ipmP->dlambdae));
    104:     if (ipmP->nb > 0) {
    105:       PetscCall(VecAXPY(ipmP->lambdai, alpha, ipmP->dlambdai));
    106:       PetscCall(VecAXPY(ipmP->s, alpha, ipmP->ds));
    107:     }

    109:     /* Recompute kkt to find centering parameter sigma = (new_mu/old_mu)^3 */
    110:     if (ipmP->mu == 0.0) {
    111:       sigma = 0.0;
    112:     } else {
    113:       sigma = 1.0 / ipmP->mu;
    114:     }
    115:     PetscCall(IPMComputeKKT(tao));
    116:     sigma *= ipmP->mu;
    117:     sigma *= sigma * sigma;

    119:     /* revert kkt info */
    120:     PetscCall(VecCopy(ipmP->save_x, tao->solution));
    121:     if (ipmP->me > 0) PetscCall(VecCopy(ipmP->save_lambdae, ipmP->lambdae));
    122:     if (ipmP->nb > 0) {
    123:       PetscCall(VecCopy(ipmP->save_lambdai, ipmP->lambdai));
    124:       PetscCall(VecCopy(ipmP->save_s, ipmP->s));
    125:     }
    126:     PetscCall(IPMComputeKKT(tao));

    128:     /* update rhs with new complementarity vector */
    129:     if (ipmP->nb > 0) {
    130:       PetscCall(VecCopy(ipmP->complementarity, ipmP->rhs_s));
    131:       PetscCall(VecScale(ipmP->rhs_s, -1.0));
    132:       PetscCall(VecShift(ipmP->rhs_s, sigma * ipmP->mu));
    133:     }
    134:     PetscCall(IPMGatherRHS(tao, ipmP->bigrhs, NULL, NULL, NULL, ipmP->rhs_s));

    136:     /* solve K * step = rhs */
    137:     PetscCall(KSPSetOperators(tao->ksp, ipmP->K, ipmP->K));
    138:     PetscCall(KSPSolve(tao->ksp, ipmP->bigrhs, ipmP->bigstep));

    140:     PetscCall(IPMScatterStep(tao, ipmP->bigstep, tao->stepdirection, ipmP->ds, ipmP->dlambdae, ipmP->dlambdai));
    141:     PetscCall(KSPGetIterationNumber(tao->ksp, &its));
    142:     tao->ksp_its += its;
    143:     tao->ksp_tot_its += its;
    144:     if (ipmP->nb > 0) {
    145:       /* Get max step size and apply frac-to-boundary */
    146:       tau = PetscMax(ipmP->taumin, 1.0 - ipmP->mu);
    147:       tau = PetscMin(tau, 1.0);
    148:       if (tau != 1.0) {
    149:         PetscCall(VecScale(ipmP->s, tau));
    150:         PetscCall(VecScale(ipmP->lambdai, tau));
    151:       }
    152:       PetscCall(VecStepBoundInfo(ipmP->s, ipmP->ds, ipmP->Zero_nb, ipmP->Inf_nb, &step_s, NULL, NULL));
    153:       PetscCall(VecStepBoundInfo(ipmP->lambdai, ipmP->dlambdai, ipmP->Zero_nb, ipmP->Inf_nb, &step_l, NULL, NULL));
    154:       if (tau != 1.0) {
    155:         PetscCall(VecCopy(ipmP->save_s, ipmP->s));
    156:         PetscCall(VecCopy(ipmP->save_lambdai, ipmP->lambdai));
    157:       }
    158:       alpha = PetscMin(step_s, step_l);
    159:       alpha = PetscMin(alpha, 1.0);
    160:     } else {
    161:       alpha = 1.0;
    162:     }
    163:     ipmP->alpha2 = alpha;
    164:     /* TODO make phi_target meaningful */
    165:     phi_target = ipmP->dec * ipmP->phi;
    166:     for (i = 0; i < 11; i++) {
    167:       PetscCall(VecAXPY(tao->solution, alpha, tao->stepdirection));
    168:       if (ipmP->nb > 0) {
    169:         PetscCall(VecAXPY(ipmP->s, alpha, ipmP->ds));
    170:         PetscCall(VecAXPY(ipmP->lambdai, alpha, ipmP->dlambdai));
    171:       }
    172:       if (ipmP->me > 0) PetscCall(VecAXPY(ipmP->lambdae, alpha, ipmP->dlambdae));

    174:       /* update dual variables */
    175:       if (ipmP->me > 0) PetscCall(VecCopy(ipmP->lambdae, tao->DE));

    177:       PetscCall(IPMEvaluate(tao));
    178:       PetscCall(IPMComputeKKT(tao));
    179:       if (ipmP->phi <= phi_target) break;
    180:       alpha /= 2.0;
    181:     }

    183:     PetscCall(TaoLogConvergenceHistory(tao, ipmP->kkt_f, ipmP->phi, 0.0, tao->ksp_its));
    184:     PetscCall(TaoMonitor(tao, tao->niter, ipmP->kkt_f, ipmP->phi, 0.0, stepsize));
    185:     PetscUseTypeMethod(tao, convergencetest, tao->cnvP);
    186:     tao->niter++;
    187:   }
    188:   PetscFunctionReturn(PETSC_SUCCESS);
    189: }

    191: static PetscErrorCode TaoSetup_IPM(Tao tao)
    192: {
    193:   TAO_IPM *ipmP = (TAO_IPM *)tao->data;

    195:   PetscFunctionBegin;
    196:   ipmP->nb = ipmP->mi = ipmP->me = 0;
    197:   ipmP->K                        = NULL;
    198:   PetscCall(VecGetSize(tao->solution, &ipmP->n));
    199:   if (!tao->gradient) PetscCall(VecDuplicate(tao->solution, &tao->gradient));
    200:   if (!tao->stepdirection) PetscCall(VecDuplicate(tao->solution, &tao->stepdirection));
    201:   if (!ipmP->rd) PetscCall(VecDuplicate(tao->solution, &ipmP->rd));
    202:   if (!ipmP->rhs_x) PetscCall(VecDuplicate(tao->solution, &ipmP->rhs_x));
    203:   if (!ipmP->work) PetscCall(VecDuplicate(tao->solution, &ipmP->work));
    204:   if (!ipmP->save_x) PetscCall(VecDuplicate(tao->solution, &ipmP->save_x));
    205:   if (tao->constraints_equality) {
    206:     PetscCall(VecGetSize(tao->constraints_equality, &ipmP->me));
    207:     PetscCall(VecDuplicate(tao->constraints_equality, &ipmP->lambdae));
    208:     PetscCall(VecDuplicate(tao->constraints_equality, &ipmP->dlambdae));
    209:     PetscCall(VecDuplicate(tao->constraints_equality, &ipmP->rhs_lambdae));
    210:     PetscCall(VecDuplicate(tao->constraints_equality, &ipmP->save_lambdae));
    211:     PetscCall(VecDuplicate(tao->constraints_equality, &ipmP->rpe));
    212:     PetscCall(VecDuplicate(tao->constraints_equality, &tao->DE));
    213:   }
    214:   if (tao->constraints_inequality) PetscCall(VecDuplicate(tao->constraints_inequality, &tao->DI));
    215:   PetscFunctionReturn(PETSC_SUCCESS);
    216: }

    218: static PetscErrorCode IPMInitializeBounds(Tao tao)
    219: {
    220:   TAO_IPM        *ipmP = (TAO_IPM *)tao->data;
    221:   Vec             xtmp;
    222:   PetscInt        xstart, xend;
    223:   PetscInt        ucstart, ucend;   /* user ci */
    224:   PetscInt        ucestart, uceend; /* user ce */
    225:   PetscInt        sstart = 0, send = 0;
    226:   PetscInt        bigsize;
    227:   PetscInt        i, counter, nloc;
    228:   PetscInt       *cind, *xind, *ucind, *uceind, *stepind;
    229:   VecType         vtype;
    230:   const PetscInt *xli, *xui;
    231:   PetscInt        xl_offset, xu_offset;
    232:   IS              bigxl, bigxu, isuc, isc, isx, sis, is1;
    233:   MPI_Comm        comm;

    235:   PetscFunctionBegin;
    236:   cind = xind = ucind = uceind = stepind = NULL;
    237:   ipmP->mi                               = 0;
    238:   ipmP->nxlb                             = 0;
    239:   ipmP->nxub                             = 0;
    240:   ipmP->nb                               = 0;
    241:   ipmP->nslack                           = 0;

    243:   PetscCall(VecDuplicate(tao->solution, &xtmp));
    244:   PetscCall(TaoComputeVariableBounds(tao));
    245:   if (tao->XL) {
    246:     PetscCall(VecSet(xtmp, PETSC_NINFINITY));
    247:     PetscCall(VecWhichGreaterThan(tao->XL, xtmp, &ipmP->isxl));
    248:     PetscCall(ISGetSize(ipmP->isxl, &ipmP->nxlb));
    249:   } else {
    250:     ipmP->nxlb = 0;
    251:   }
    252:   if (tao->XU) {
    253:     PetscCall(VecSet(xtmp, PETSC_INFINITY));
    254:     PetscCall(VecWhichLessThan(tao->XU, xtmp, &ipmP->isxu));
    255:     PetscCall(ISGetSize(ipmP->isxu, &ipmP->nxub));
    256:   } else {
    257:     ipmP->nxub = 0;
    258:   }
    259:   PetscCall(VecDestroy(&xtmp));
    260:   if (tao->constraints_inequality) {
    261:     PetscCall(VecGetSize(tao->constraints_inequality, &ipmP->mi));
    262:   } else {
    263:     ipmP->mi = 0;
    264:   }
    265:   ipmP->nb = ipmP->nxlb + ipmP->nxub + ipmP->mi;

    267:   PetscCall(PetscObjectGetComm((PetscObject)tao->solution, &comm));

    269:   bigsize = ipmP->n + 2 * ipmP->nb + ipmP->me;
    270:   PetscCall(PetscMalloc1(bigsize, &stepind));
    271:   PetscCall(PetscMalloc1(ipmP->n, &xind));
    272:   PetscCall(PetscMalloc1(ipmP->me, &uceind));
    273:   PetscCall(VecGetOwnershipRange(tao->solution, &xstart, &xend));

    275:   if (ipmP->nb > 0) {
    276:     PetscCall(VecCreate(comm, &ipmP->s));
    277:     PetscCall(VecSetSizes(ipmP->s, PETSC_DECIDE, ipmP->nb));
    278:     PetscCall(VecSetFromOptions(ipmP->s));
    279:     PetscCall(VecDuplicate(ipmP->s, &ipmP->ds));
    280:     PetscCall(VecDuplicate(ipmP->s, &ipmP->rhs_s));
    281:     PetscCall(VecDuplicate(ipmP->s, &ipmP->complementarity));
    282:     PetscCall(VecDuplicate(ipmP->s, &ipmP->ci));

    284:     PetscCall(VecDuplicate(ipmP->s, &ipmP->lambdai));
    285:     PetscCall(VecDuplicate(ipmP->s, &ipmP->dlambdai));
    286:     PetscCall(VecDuplicate(ipmP->s, &ipmP->rhs_lambdai));
    287:     PetscCall(VecDuplicate(ipmP->s, &ipmP->save_lambdai));

    289:     PetscCall(VecDuplicate(ipmP->s, &ipmP->save_s));
    290:     PetscCall(VecDuplicate(ipmP->s, &ipmP->rpi));
    291:     PetscCall(VecDuplicate(ipmP->s, &ipmP->Zero_nb));
    292:     PetscCall(VecSet(ipmP->Zero_nb, 0.0));
    293:     PetscCall(VecDuplicate(ipmP->s, &ipmP->One_nb));
    294:     PetscCall(VecSet(ipmP->One_nb, 1.0));
    295:     PetscCall(VecDuplicate(ipmP->s, &ipmP->Inf_nb));
    296:     PetscCall(VecSet(ipmP->Inf_nb, PETSC_INFINITY));

    298:     PetscCall(PetscMalloc1(ipmP->nb, &cind));
    299:     PetscCall(PetscMalloc1(ipmP->mi, &ucind));
    300:     PetscCall(VecGetOwnershipRange(ipmP->s, &sstart, &send));

    302:     if (ipmP->mi > 0) {
    303:       PetscCall(VecGetOwnershipRange(tao->constraints_inequality, &ucstart, &ucend));
    304:       counter = 0;
    305:       for (i = ucstart; i < ucend; i++) cind[counter++] = i;
    306:       PetscCall(ISCreateGeneral(comm, counter, cind, PETSC_COPY_VALUES, &isuc));
    307:       PetscCall(ISCreateGeneral(comm, counter, cind, PETSC_COPY_VALUES, &isc));
    308:       PetscCall(VecScatterCreate(tao->constraints_inequality, isuc, ipmP->ci, isc, &ipmP->ci_scat));

    310:       PetscCall(ISDestroy(&isuc));
    311:       PetscCall(ISDestroy(&isc));
    312:     }
    313:     /* need to know how may xbound indices are on each process */
    314:     /* TODO better way */
    315:     if (ipmP->nxlb) {
    316:       PetscCall(ISAllGather(ipmP->isxl, &bigxl));
    317:       PetscCall(ISGetIndices(bigxl, &xli));
    318:       /* find offsets for this processor */
    319:       xl_offset = ipmP->mi;
    320:       for (i = 0; i < ipmP->nxlb; i++) {
    321:         if (xli[i] < xstart) {
    322:           xl_offset++;
    323:         } else break;
    324:       }
    325:       PetscCall(ISRestoreIndices(bigxl, &xli));

    327:       PetscCall(ISGetIndices(ipmP->isxl, &xli));
    328:       PetscCall(ISGetLocalSize(ipmP->isxl, &nloc));
    329:       for (i = 0; i < nloc; i++) {
    330:         xind[i] = xli[i];
    331:         cind[i] = xl_offset + i;
    332:       }

    334:       PetscCall(ISCreateGeneral(comm, nloc, xind, PETSC_COPY_VALUES, &isx));
    335:       PetscCall(ISCreateGeneral(comm, nloc, cind, PETSC_COPY_VALUES, &isc));
    336:       PetscCall(VecScatterCreate(tao->XL, isx, ipmP->ci, isc, &ipmP->xl_scat));
    337:       PetscCall(ISDestroy(&isx));
    338:       PetscCall(ISDestroy(&isc));
    339:       PetscCall(ISDestroy(&bigxl));
    340:     }

    342:     if (ipmP->nxub) {
    343:       PetscCall(ISAllGather(ipmP->isxu, &bigxu));
    344:       PetscCall(ISGetIndices(bigxu, &xui));
    345:       /* find offsets for this processor */
    346:       xu_offset = ipmP->mi + ipmP->nxlb;
    347:       for (i = 0; i < ipmP->nxub; i++) {
    348:         if (xui[i] < xstart) {
    349:           xu_offset++;
    350:         } else break;
    351:       }
    352:       PetscCall(ISRestoreIndices(bigxu, &xui));

    354:       PetscCall(ISGetIndices(ipmP->isxu, &xui));
    355:       PetscCall(ISGetLocalSize(ipmP->isxu, &nloc));
    356:       for (i = 0; i < nloc; i++) {
    357:         xind[i] = xui[i];
    358:         cind[i] = xu_offset + i;
    359:       }

    361:       PetscCall(ISCreateGeneral(comm, nloc, xind, PETSC_COPY_VALUES, &isx));
    362:       PetscCall(ISCreateGeneral(comm, nloc, cind, PETSC_COPY_VALUES, &isc));
    363:       PetscCall(VecScatterCreate(tao->XU, isx, ipmP->ci, isc, &ipmP->xu_scat));
    364:       PetscCall(ISDestroy(&isx));
    365:       PetscCall(ISDestroy(&isc));
    366:       PetscCall(ISDestroy(&bigxu));
    367:     }
    368:   }
    369:   PetscCall(VecCreate(comm, &ipmP->bigrhs));
    370:   PetscCall(VecGetType(tao->solution, &vtype));
    371:   PetscCall(VecSetType(ipmP->bigrhs, vtype));
    372:   PetscCall(VecSetSizes(ipmP->bigrhs, PETSC_DECIDE, bigsize));
    373:   PetscCall(VecSetFromOptions(ipmP->bigrhs));
    374:   PetscCall(VecDuplicate(ipmP->bigrhs, &ipmP->bigstep));

    376:   /* create scatters for step->x and x->rhs */
    377:   for (i = xstart; i < xend; i++) {
    378:     stepind[i - xstart] = i;
    379:     xind[i - xstart]    = i;
    380:   }
    381:   PetscCall(ISCreateGeneral(comm, xend - xstart, stepind, PETSC_COPY_VALUES, &sis));
    382:   PetscCall(ISCreateGeneral(comm, xend - xstart, xind, PETSC_COPY_VALUES, &is1));
    383:   PetscCall(VecScatterCreate(ipmP->bigstep, sis, tao->solution, is1, &ipmP->step1));
    384:   PetscCall(VecScatterCreate(tao->solution, is1, ipmP->bigrhs, sis, &ipmP->rhs1));
    385:   PetscCall(ISDestroy(&sis));
    386:   PetscCall(ISDestroy(&is1));

    388:   if (ipmP->nb > 0) {
    389:     for (i = sstart; i < send; i++) {
    390:       stepind[i - sstart] = i + ipmP->n;
    391:       cind[i - sstart]    = i;
    392:     }
    393:     PetscCall(ISCreateGeneral(comm, send - sstart, stepind, PETSC_COPY_VALUES, &sis));
    394:     PetscCall(ISCreateGeneral(comm, send - sstart, cind, PETSC_COPY_VALUES, &is1));
    395:     PetscCall(VecScatterCreate(ipmP->bigstep, sis, ipmP->s, is1, &ipmP->step2));
    396:     PetscCall(ISDestroy(&sis));

    398:     for (i = sstart; i < send; i++) {
    399:       stepind[i - sstart] = i + ipmP->n + ipmP->me;
    400:       cind[i - sstart]    = i;
    401:     }
    402:     PetscCall(ISCreateGeneral(comm, send - sstart, stepind, PETSC_COPY_VALUES, &sis));
    403:     PetscCall(VecScatterCreate(ipmP->s, is1, ipmP->bigrhs, sis, &ipmP->rhs3));
    404:     PetscCall(ISDestroy(&sis));
    405:     PetscCall(ISDestroy(&is1));
    406:   }

    408:   if (ipmP->me > 0) {
    409:     PetscCall(VecGetOwnershipRange(tao->constraints_equality, &ucestart, &uceend));
    410:     for (i = ucestart; i < uceend; i++) {
    411:       stepind[i - ucestart] = i + ipmP->n + ipmP->nb;
    412:       uceind[i - ucestart]  = i;
    413:     }

    415:     PetscCall(ISCreateGeneral(comm, uceend - ucestart, stepind, PETSC_COPY_VALUES, &sis));
    416:     PetscCall(ISCreateGeneral(comm, uceend - ucestart, uceind, PETSC_COPY_VALUES, &is1));
    417:     PetscCall(VecScatterCreate(ipmP->bigstep, sis, tao->constraints_equality, is1, &ipmP->step3));
    418:     PetscCall(ISDestroy(&sis));

    420:     for (i = ucestart; i < uceend; i++) stepind[i - ucestart] = i + ipmP->n;

    422:     PetscCall(ISCreateGeneral(comm, uceend - ucestart, stepind, PETSC_COPY_VALUES, &sis));
    423:     PetscCall(VecScatterCreate(tao->constraints_equality, is1, ipmP->bigrhs, sis, &ipmP->rhs2));
    424:     PetscCall(ISDestroy(&sis));
    425:     PetscCall(ISDestroy(&is1));
    426:   }

    428:   if (ipmP->nb > 0) {
    429:     for (i = sstart; i < send; i++) {
    430:       stepind[i - sstart] = i + ipmP->n + ipmP->nb + ipmP->me;
    431:       cind[i - sstart]    = i;
    432:     }
    433:     PetscCall(ISCreateGeneral(comm, send - sstart, cind, PETSC_COPY_VALUES, &is1));
    434:     PetscCall(ISCreateGeneral(comm, send - sstart, stepind, PETSC_COPY_VALUES, &sis));
    435:     PetscCall(VecScatterCreate(ipmP->bigstep, sis, ipmP->s, is1, &ipmP->step4));
    436:     PetscCall(VecScatterCreate(ipmP->s, is1, ipmP->bigrhs, sis, &ipmP->rhs4));
    437:     PetscCall(ISDestroy(&sis));
    438:     PetscCall(ISDestroy(&is1));
    439:   }

    441:   PetscCall(PetscFree(stepind));
    442:   PetscCall(PetscFree(cind));
    443:   PetscCall(PetscFree(ucind));
    444:   PetscCall(PetscFree(uceind));
    445:   PetscCall(PetscFree(xind));
    446:   PetscFunctionReturn(PETSC_SUCCESS);
    447: }

    449: static PetscErrorCode TaoDestroy_IPM(Tao tao)
    450: {
    451:   TAO_IPM *ipmP = (TAO_IPM *)tao->data;

    453:   PetscFunctionBegin;
    454:   PetscCall(VecDestroy(&ipmP->rd));
    455:   PetscCall(VecDestroy(&ipmP->rpe));
    456:   PetscCall(VecDestroy(&ipmP->rpi));
    457:   PetscCall(VecDestroy(&ipmP->work));
    458:   PetscCall(VecDestroy(&ipmP->lambdae));
    459:   PetscCall(VecDestroy(&ipmP->lambdai));
    460:   PetscCall(VecDestroy(&ipmP->s));
    461:   PetscCall(VecDestroy(&ipmP->ds));
    462:   PetscCall(VecDestroy(&ipmP->ci));

    464:   PetscCall(VecDestroy(&ipmP->rhs_x));
    465:   PetscCall(VecDestroy(&ipmP->rhs_lambdae));
    466:   PetscCall(VecDestroy(&ipmP->rhs_lambdai));
    467:   PetscCall(VecDestroy(&ipmP->rhs_s));

    469:   PetscCall(VecDestroy(&ipmP->save_x));
    470:   PetscCall(VecDestroy(&ipmP->save_lambdae));
    471:   PetscCall(VecDestroy(&ipmP->save_lambdai));
    472:   PetscCall(VecDestroy(&ipmP->save_s));

    474:   PetscCall(VecScatterDestroy(&ipmP->step1));
    475:   PetscCall(VecScatterDestroy(&ipmP->step2));
    476:   PetscCall(VecScatterDestroy(&ipmP->step3));
    477:   PetscCall(VecScatterDestroy(&ipmP->step4));

    479:   PetscCall(VecScatterDestroy(&ipmP->rhs1));
    480:   PetscCall(VecScatterDestroy(&ipmP->rhs2));
    481:   PetscCall(VecScatterDestroy(&ipmP->rhs3));
    482:   PetscCall(VecScatterDestroy(&ipmP->rhs4));

    484:   PetscCall(VecScatterDestroy(&ipmP->ci_scat));
    485:   PetscCall(VecScatterDestroy(&ipmP->xl_scat));
    486:   PetscCall(VecScatterDestroy(&ipmP->xu_scat));

    488:   PetscCall(VecDestroy(&ipmP->dlambdai));
    489:   PetscCall(VecDestroy(&ipmP->dlambdae));
    490:   PetscCall(VecDestroy(&ipmP->Zero_nb));
    491:   PetscCall(VecDestroy(&ipmP->One_nb));
    492:   PetscCall(VecDestroy(&ipmP->Inf_nb));
    493:   PetscCall(VecDestroy(&ipmP->complementarity));

    495:   PetscCall(VecDestroy(&ipmP->bigrhs));
    496:   PetscCall(VecDestroy(&ipmP->bigstep));
    497:   PetscCall(MatDestroy(&ipmP->Ai));
    498:   PetscCall(MatDestroy(&ipmP->K));
    499:   PetscCall(ISDestroy(&ipmP->isxu));
    500:   PetscCall(ISDestroy(&ipmP->isxl));
    501:   PetscCall(KSPDestroy(&tao->ksp));
    502:   PetscCall(PetscFree(tao->data));
    503:   PetscFunctionReturn(PETSC_SUCCESS);
    504: }

    506: static PetscErrorCode TaoSetFromOptions_IPM(Tao tao, PetscOptionItems PetscOptionsObject)
    507: {
    508:   TAO_IPM *ipmP = (TAO_IPM *)tao->data;

    510:   PetscFunctionBegin;
    511:   PetscOptionsHeadBegin(PetscOptionsObject, "IPM method for constrained optimization");
    512:   PetscCall(PetscOptionsBool("-tao_ipm_monitorkkt", "monitor kkt status", NULL, ipmP->monitorkkt, &ipmP->monitorkkt, NULL));
    513:   PetscCall(PetscOptionsReal("-tao_ipm_pushs", "parameter to push initial slack variables away from bounds", NULL, ipmP->pushs, &ipmP->pushs, NULL));
    514:   PetscCall(PetscOptionsReal("-tao_ipm_pushnu", "parameter to push initial (inequality) dual variables away from bounds", NULL, ipmP->pushnu, &ipmP->pushnu, NULL));
    515:   PetscOptionsHeadEnd();
    516:   PetscCall(KSPSetFromOptions(tao->ksp));
    517:   PetscFunctionReturn(PETSC_SUCCESS);
    518: }

    520: static PetscErrorCode TaoView_IPM(Tao tao, PetscViewer viewer)
    521: {
    522:   return PETSC_SUCCESS;
    523: }

    525: /* IPMObjectiveAndGradient()
    526:    f = d'x + 0.5 * x' * H * x
    527:    rd = H*x + d + Ae'*lame - Ai'*lami
    528:    rpe = Ae*x - be
    529:    rpi = Ai*x - yi - bi
    530:    mu = yi' * lami/mi;
    531:    com = yi.*lami

    533:    phi = ||rd|| + ||rpe|| + ||rpi|| + ||com||
    534: */
    535: /*
    536: static PetscErrorCode IPMObjective(TaoLineSearch ls, Vec X, PetscReal *f, void *tptr)
    537: {
    538:   Tao tao = (Tao)tptr;
    539:   TAO_IPM *ipmP = (TAO_IPM*)tao->data;

    541:   PetscFunctionBegin;
    542:   PetscCall(IPMComputeKKT(tao));
    543:   *f = ipmP->phi;
    544:   PetscFunctionReturn(PETSC_SUCCESS);
    545: }
    546: */

    548: /*
    549:    f = d'x + 0.5 * x' * H * x
    550:    rd = H*x + d + Ae'*lame - Ai'*lami
    551:        Ai =   jac_ineq
    552:                I (w/lb)
    553:               -I (w/ub)

    555:    rpe = ce
    556:    rpi = ci - s;
    557:    com = s.*lami
    558:    mu = yi' * lami/mi;

    560:    phi = ||rd|| + ||rpe|| + ||rpi|| + ||com||
    561: */
    562: static PetscErrorCode IPMComputeKKT(Tao tao)
    563: {
    564:   TAO_IPM    *ipmP = (TAO_IPM *)tao->data;
    565:   PetscScalar norm;

    567:   PetscFunctionBegin;
    568:   PetscCall(VecCopy(tao->gradient, ipmP->rd));

    570:   if (ipmP->me > 0) {
    571:     /* rd = gradient + Ae'*lambdae */
    572:     PetscCall(MatMultTranspose(tao->jacobian_equality, ipmP->lambdae, ipmP->work));
    573:     PetscCall(VecAXPY(ipmP->rd, 1.0, ipmP->work));

    575:     /* rpe = ce(x) */
    576:     PetscCall(VecCopy(tao->constraints_equality, ipmP->rpe));
    577:   }
    578:   if (ipmP->nb > 0) {
    579:     /* rd = rd - Ai'*lambdai */
    580:     PetscCall(MatMultTranspose(ipmP->Ai, ipmP->lambdai, ipmP->work));
    581:     PetscCall(VecAXPY(ipmP->rd, -1.0, ipmP->work));

    583:     /* rpi = cin - s */
    584:     PetscCall(VecCopy(ipmP->ci, ipmP->rpi));
    585:     PetscCall(VecAXPY(ipmP->rpi, -1.0, ipmP->s));

    587:     /* com = s .* lami */
    588:     PetscCall(VecPointwiseMult(ipmP->complementarity, ipmP->s, ipmP->lambdai));
    589:   }
    590:   /* phi = ||rd; rpe; rpi; com|| */
    591:   PetscCall(VecDot(ipmP->rd, ipmP->rd, &norm));
    592:   ipmP->phi = norm;
    593:   if (ipmP->me > 0) {
    594:     PetscCall(VecDot(ipmP->rpe, ipmP->rpe, &norm));
    595:     ipmP->phi += norm;
    596:   }
    597:   if (ipmP->nb > 0) {
    598:     PetscCall(VecDot(ipmP->rpi, ipmP->rpi, &norm));
    599:     ipmP->phi += norm;
    600:     PetscCall(VecDot(ipmP->complementarity, ipmP->complementarity, &norm));
    601:     ipmP->phi += norm;
    602:     /* mu = s'*lami/nb */
    603:     PetscCall(VecDot(ipmP->s, ipmP->lambdai, &ipmP->mu));
    604:     ipmP->mu /= ipmP->nb;
    605:   } else {
    606:     ipmP->mu = 1.0;
    607:   }

    609:   ipmP->phi = PetscSqrtScalar(ipmP->phi);
    610:   PetscFunctionReturn(PETSC_SUCCESS);
    611: }

    613: /* evaluate user info at current point */
    614: static PetscErrorCode IPMEvaluate(Tao tao)
    615: {
    616:   TAO_IPM *ipmP = (TAO_IPM *)tao->data;

    618:   PetscFunctionBegin;
    619:   PetscCall(TaoComputeObjectiveAndGradient(tao, tao->solution, &ipmP->kkt_f, tao->gradient));
    620:   PetscCall(TaoComputeHessian(tao, tao->solution, tao->hessian, tao->hessian_pre));
    621:   if (ipmP->me > 0) {
    622:     PetscCall(TaoComputeEqualityConstraints(tao, tao->solution, tao->constraints_equality));
    623:     PetscCall(TaoComputeJacobianEquality(tao, tao->solution, tao->jacobian_equality, tao->jacobian_equality_pre));
    624:   }
    625:   if (ipmP->mi > 0) {
    626:     PetscCall(TaoComputeInequalityConstraints(tao, tao->solution, tao->constraints_inequality));
    627:     PetscCall(TaoComputeJacobianInequality(tao, tao->solution, tao->jacobian_inequality, tao->jacobian_inequality_pre));
    628:   }
    629:   if (ipmP->nb > 0) {
    630:     /* Ai' =   jac_ineq | I (w/lb) | -I (w/ub)  */
    631:     PetscCall(IPMUpdateAi(tao));
    632:   }
    633:   PetscFunctionReturn(PETSC_SUCCESS);
    634: }

    636: /* Push initial point away from bounds */
    637: static PetscErrorCode IPMPushInitialPoint(Tao tao)
    638: {
    639:   TAO_IPM *ipmP = (TAO_IPM *)tao->data;

    641:   PetscFunctionBegin;
    642:   PetscCall(TaoComputeVariableBounds(tao));
    643:   PetscCall(VecMedian(tao->XL, tao->solution, tao->XU, tao->solution));
    644:   if (ipmP->nb > 0) {
    645:     PetscCall(VecSet(ipmP->s, ipmP->pushs));
    646:     PetscCall(VecSet(ipmP->lambdai, ipmP->pushnu));
    647:     if (ipmP->mi > 0) PetscCall(VecSet(tao->DI, ipmP->pushnu));
    648:   }
    649:   if (ipmP->me > 0) {
    650:     PetscCall(VecSet(tao->DE, 1.0));
    651:     PetscCall(VecSet(ipmP->lambdae, 1.0));
    652:   }
    653:   PetscFunctionReturn(PETSC_SUCCESS);
    654: }

    656: static PetscErrorCode IPMUpdateAi(Tao tao)
    657: {
    658:   /* Ai =     Ji
    659:               I (w/lb)
    660:              -I (w/ub) */

    662:   /* Ci =    user->ci
    663:              Xi - lb (w/lb)
    664:              -Xi + ub (w/ub)  */

    666:   TAO_IPM           *ipmP = (TAO_IPM *)tao->data;
    667:   MPI_Comm           comm;
    668:   PetscInt           i;
    669:   PetscScalar        newval;
    670:   PetscInt           newrow, newcol, ncols;
    671:   const PetscScalar *vals;
    672:   const PetscInt    *cols;
    673:   PetscInt           astart, aend, jstart, jend;
    674:   PetscInt          *nonzeros;
    675:   PetscInt           r2, r3, r4;
    676:   PetscMPIInt        size;
    677:   Vec                solu;
    678:   PetscInt           nloc;

    680:   PetscFunctionBegin;
    681:   r2 = ipmP->mi;
    682:   r3 = r2 + ipmP->nxlb;
    683:   r4 = r3 + ipmP->nxub;

    685:   if (!ipmP->nb) PetscFunctionReturn(PETSC_SUCCESS);

    687:   /* Create Ai matrix if it doesn't exist yet */
    688:   if (!ipmP->Ai) {
    689:     comm = ((PetscObject)tao->solution)->comm;
    690:     PetscCallMPI(MPI_Comm_size(comm, &size));
    691:     if (size == 1) {
    692:       PetscCall(PetscMalloc1(ipmP->nb, &nonzeros));
    693:       for (i = 0; i < ipmP->mi; i++) {
    694:         PetscCall(MatGetRow(tao->jacobian_inequality, i, &ncols, NULL, NULL));
    695:         nonzeros[i] = ncols;
    696:         PetscCall(MatRestoreRow(tao->jacobian_inequality, i, &ncols, NULL, NULL));
    697:       }
    698:       for (i = r2; i < r4; i++) nonzeros[i] = 1;
    699:     }
    700:     PetscCall(MatCreate(comm, &ipmP->Ai));
    701:     PetscCall(MatSetType(ipmP->Ai, MATAIJ));

    703:     PetscCall(TaoGetSolution(tao, &solu));
    704:     PetscCall(VecGetLocalSize(solu, &nloc));
    705:     PetscCall(MatSetSizes(ipmP->Ai, PETSC_DECIDE, nloc, ipmP->nb, PETSC_DECIDE));
    706:     PetscCall(MatSetFromOptions(ipmP->Ai));
    707:     PetscCall(MatMPIAIJSetPreallocation(ipmP->Ai, ipmP->nb, NULL, ipmP->nb, NULL));
    708:     PetscCall(MatSeqAIJSetPreallocation(ipmP->Ai, PETSC_DEFAULT, nonzeros));
    709:     if (size == 1) PetscCall(PetscFree(nonzeros));
    710:   }

    712:   /* Copy values from user jacobian to Ai */
    713:   PetscCall(MatGetOwnershipRange(ipmP->Ai, &astart, &aend));

    715:   /* Ai w/lb */
    716:   if (ipmP->mi) {
    717:     PetscCall(MatZeroEntries(ipmP->Ai));
    718:     PetscCall(MatGetOwnershipRange(tao->jacobian_inequality, &jstart, &jend));
    719:     for (i = jstart; i < jend; i++) {
    720:       PetscCall(MatGetRow(tao->jacobian_inequality, i, &ncols, &cols, &vals));
    721:       newrow = i;
    722:       PetscCall(MatSetValues(ipmP->Ai, 1, &newrow, ncols, cols, vals, INSERT_VALUES));
    723:       PetscCall(MatRestoreRow(tao->jacobian_inequality, i, &ncols, &cols, &vals));
    724:     }
    725:   }

    727:   /* I w/ xlb */
    728:   if (ipmP->nxlb) {
    729:     for (i = 0; i < ipmP->nxlb; i++) {
    730:       if (i >= astart && i < aend) {
    731:         newrow = i + r2;
    732:         newcol = i;
    733:         newval = 1.0;
    734:         PetscCall(MatSetValues(ipmP->Ai, 1, &newrow, 1, &newcol, &newval, INSERT_VALUES));
    735:       }
    736:     }
    737:   }
    738:   if (ipmP->nxub) {
    739:     /* I w/ xub */
    740:     for (i = 0; i < ipmP->nxub; i++) {
    741:       if (i >= astart && i < aend) {
    742:         newrow = i + r3;
    743:         newcol = i;
    744:         newval = -1.0;
    745:         PetscCall(MatSetValues(ipmP->Ai, 1, &newrow, 1, &newcol, &newval, INSERT_VALUES));
    746:       }
    747:     }
    748:   }

    750:   PetscCall(MatAssemblyBegin(ipmP->Ai, MAT_FINAL_ASSEMBLY));
    751:   PetscCall(MatAssemblyEnd(ipmP->Ai, MAT_FINAL_ASSEMBLY));
    752:   CHKMEMQ;

    754:   PetscCall(VecSet(ipmP->ci, 0.0));

    756:   /* user ci */
    757:   if (ipmP->mi > 0) {
    758:     PetscCall(VecScatterBegin(ipmP->ci_scat, tao->constraints_inequality, ipmP->ci, INSERT_VALUES, SCATTER_FORWARD));
    759:     PetscCall(VecScatterEnd(ipmP->ci_scat, tao->constraints_inequality, ipmP->ci, INSERT_VALUES, SCATTER_FORWARD));
    760:   }
    761:   if (!ipmP->work) PetscCall(VecDuplicate(tao->solution, &ipmP->work));
    762:   PetscCall(VecCopy(tao->solution, ipmP->work));
    763:   if (tao->XL) {
    764:     PetscCall(VecAXPY(ipmP->work, -1.0, tao->XL));

    766:     /* lower bounds on variables */
    767:     if (ipmP->nxlb > 0) {
    768:       PetscCall(VecScatterBegin(ipmP->xl_scat, ipmP->work, ipmP->ci, INSERT_VALUES, SCATTER_FORWARD));
    769:       PetscCall(VecScatterEnd(ipmP->xl_scat, ipmP->work, ipmP->ci, INSERT_VALUES, SCATTER_FORWARD));
    770:     }
    771:   }
    772:   if (tao->XU) {
    773:     /* upper bounds on variables */
    774:     PetscCall(VecCopy(tao->solution, ipmP->work));
    775:     PetscCall(VecScale(ipmP->work, -1.0));
    776:     PetscCall(VecAXPY(ipmP->work, 1.0, tao->XU));
    777:     if (ipmP->nxub > 0) {
    778:       PetscCall(VecScatterBegin(ipmP->xu_scat, ipmP->work, ipmP->ci, INSERT_VALUES, SCATTER_FORWARD));
    779:       PetscCall(VecScatterEnd(ipmP->xu_scat, ipmP->work, ipmP->ci, INSERT_VALUES, SCATTER_FORWARD));
    780:     }
    781:   }
    782:   PetscFunctionReturn(PETSC_SUCCESS);
    783: }

    785: /* create K = [ Hlag , 0 , Ae', -Ai'];
    786:               [Ae , 0,   0  , 0];
    787:               [Ai ,-I,   0 ,  0];
    788:               [ 0 , S ,  0,   Y ];  */
    789: static PetscErrorCode IPMUpdateK(Tao tao)
    790: {
    791:   TAO_IPM         *ipmP = (TAO_IPM *)tao->data;
    792:   MPI_Comm         comm;
    793:   PetscMPIInt      size;
    794:   PetscInt         i, j, row;
    795:   PetscInt         ncols, newcol, newcols[2], newrow;
    796:   const PetscInt  *cols;
    797:   const PetscReal *vals;
    798:   const PetscReal *l, *y;
    799:   PetscReal       *newvals;
    800:   PetscReal        newval;
    801:   PetscInt         subsize;
    802:   const PetscInt  *indices;
    803:   PetscInt        *nonzeros, *d_nonzeros, *o_nonzeros;
    804:   PetscInt         bigsize;
    805:   PetscInt         r1, r2, r3;
    806:   PetscInt         c1, c2, c3;
    807:   PetscInt         klocalsize;
    808:   PetscInt         hstart, hend, kstart, kend;
    809:   PetscInt         aistart, aiend, aestart, aeend;
    810:   PetscInt         sstart, send;

    812:   PetscFunctionBegin;
    813:   comm = ((PetscObject)tao->solution)->comm;
    814:   PetscCallMPI(MPI_Comm_size(comm, &size));
    815:   PetscCall(IPMUpdateAi(tao));

    817:   /* allocate workspace */
    818:   subsize = PetscMax(ipmP->n, ipmP->nb);
    819:   subsize = PetscMax(ipmP->me, subsize);
    820:   subsize = PetscMax(2, subsize);
    821:   PetscCall(PetscMalloc1(subsize, &indices));
    822:   PetscCall(PetscMalloc1(subsize, &newvals));

    824:   r1 = c1 = ipmP->n;
    825:   r2      = r1 + ipmP->me;
    826:   c2      = c1 + ipmP->nb;
    827:   r3 = c3 = r2 + ipmP->nb;

    829:   bigsize = ipmP->n + 2 * ipmP->nb + ipmP->me;
    830:   PetscCall(VecGetOwnershipRange(ipmP->bigrhs, &kstart, &kend));
    831:   PetscCall(MatGetOwnershipRange(tao->hessian, &hstart, &hend));
    832:   klocalsize = kend - kstart;
    833:   if (!ipmP->K) {
    834:     if (size == 1) {
    835:       PetscCall(PetscMalloc1(kend - kstart, &nonzeros));
    836:       for (i = 0; i < bigsize; i++) {
    837:         if (i < r1) {
    838:           PetscCall(MatGetRow(tao->hessian, i, &ncols, NULL, NULL));
    839:           nonzeros[i] = ncols;
    840:           PetscCall(MatRestoreRow(tao->hessian, i, &ncols, NULL, NULL));
    841:           nonzeros[i] += ipmP->me + ipmP->nb;
    842:         } else if (i < r2) {
    843:           nonzeros[i - kstart] = ipmP->n;
    844:         } else if (i < r3) {
    845:           nonzeros[i - kstart] = ipmP->n + 1;
    846:         } else if (i < bigsize) {
    847:           nonzeros[i - kstart] = 2;
    848:         }
    849:       }
    850:       PetscCall(MatCreate(comm, &ipmP->K));
    851:       PetscCall(MatSetType(ipmP->K, MATSEQAIJ));
    852:       PetscCall(MatSetSizes(ipmP->K, klocalsize, klocalsize, PETSC_DETERMINE, PETSC_DETERMINE));
    853:       PetscCall(MatSeqAIJSetPreallocation(ipmP->K, 0, nonzeros));
    854:       PetscCall(MatSetFromOptions(ipmP->K));
    855:       PetscCall(PetscFree(nonzeros));
    856:     } else {
    857:       PetscCall(PetscMalloc1(kend - kstart, &d_nonzeros));
    858:       PetscCall(PetscMalloc1(kend - kstart, &o_nonzeros));
    859:       for (i = kstart; i < kend; i++) {
    860:         if (i < r1) {
    861:           /* TODO fix preallocation for mpi mats */
    862:           d_nonzeros[i - kstart] = PetscMin(ipmP->n + ipmP->me + ipmP->nb, kend - kstart);
    863:           o_nonzeros[i - kstart] = PetscMin(ipmP->n + ipmP->me + ipmP->nb, bigsize - (kend - kstart));
    864:         } else if (i < r2) {
    865:           d_nonzeros[i - kstart] = PetscMin(ipmP->n, kend - kstart);
    866:           o_nonzeros[i - kstart] = PetscMin(ipmP->n, bigsize - (kend - kstart));
    867:         } else if (i < r3) {
    868:           d_nonzeros[i - kstart] = PetscMin(ipmP->n + 2, kend - kstart);
    869:           o_nonzeros[i - kstart] = PetscMin(ipmP->n + 2, bigsize - (kend - kstart));
    870:         } else {
    871:           d_nonzeros[i - kstart] = PetscMin(2, kend - kstart);
    872:           o_nonzeros[i - kstart] = PetscMin(2, bigsize - (kend - kstart));
    873:         }
    874:       }
    875:       PetscCall(MatCreate(comm, &ipmP->K));
    876:       PetscCall(MatSetType(ipmP->K, MATMPIAIJ));
    877:       PetscCall(MatSetSizes(ipmP->K, klocalsize, klocalsize, PETSC_DETERMINE, PETSC_DETERMINE));
    878:       PetscCall(MatMPIAIJSetPreallocation(ipmP->K, 0, d_nonzeros, 0, o_nonzeros));
    879:       PetscCall(PetscFree(d_nonzeros));
    880:       PetscCall(PetscFree(o_nonzeros));
    881:       PetscCall(MatSetFromOptions(ipmP->K));
    882:     }
    883:   }

    885:   PetscCall(MatZeroEntries(ipmP->K));
    886:   /* Copy H */
    887:   for (i = hstart; i < hend; i++) {
    888:     PetscCall(MatGetRow(tao->hessian, i, &ncols, &cols, &vals));
    889:     if (ncols > 0) PetscCall(MatSetValues(ipmP->K, 1, &i, ncols, cols, vals, INSERT_VALUES));
    890:     PetscCall(MatRestoreRow(tao->hessian, i, &ncols, &cols, &vals));
    891:   }

    893:   /* Copy Ae and Ae' */
    894:   if (ipmP->me > 0) {
    895:     PetscCall(MatGetOwnershipRange(tao->jacobian_equality, &aestart, &aeend));
    896:     for (i = aestart; i < aeend; i++) {
    897:       PetscCall(MatGetRow(tao->jacobian_equality, i, &ncols, &cols, &vals));
    898:       if (ncols > 0) {
    899:         /*Ae*/
    900:         row = i + r1;
    901:         PetscCall(MatSetValues(ipmP->K, 1, &row, ncols, cols, vals, INSERT_VALUES));
    902:         /*Ae'*/
    903:         for (j = 0; j < ncols; j++) {
    904:           newcol = i + c2;
    905:           newrow = cols[j];
    906:           newval = vals[j];
    907:           PetscCall(MatSetValues(ipmP->K, 1, &newrow, 1, &newcol, &newval, INSERT_VALUES));
    908:         }
    909:       }
    910:       PetscCall(MatRestoreRow(tao->jacobian_equality, i, &ncols, &cols, &vals));
    911:     }
    912:   }

    914:   if (ipmP->nb > 0) {
    915:     PetscCall(MatGetOwnershipRange(ipmP->Ai, &aistart, &aiend));
    916:     /* Copy Ai,and Ai' */
    917:     for (i = aistart; i < aiend; i++) {
    918:       row = i + r2;
    919:       PetscCall(MatGetRow(ipmP->Ai, i, &ncols, &cols, &vals));
    920:       if (ncols > 0) {
    921:         /*Ai*/
    922:         PetscCall(MatSetValues(ipmP->K, 1, &row, ncols, cols, vals, INSERT_VALUES));
    923:         /*-Ai'*/
    924:         for (j = 0; j < ncols; j++) {
    925:           newcol = i + c3;
    926:           newrow = cols[j];
    927:           newval = -vals[j];
    928:           PetscCall(MatSetValues(ipmP->K, 1, &newrow, 1, &newcol, &newval, INSERT_VALUES));
    929:         }
    930:       }
    931:       PetscCall(MatRestoreRow(ipmP->Ai, i, &ncols, &cols, &vals));
    932:     }

    934:     /* -I */
    935:     for (i = kstart; i < kend; i++) {
    936:       if (i >= r2 && i < r3) {
    937:         newrow = i;
    938:         newcol = i - r2 + c1;
    939:         newval = -1.0;
    940:         PetscCall(MatSetValues(ipmP->K, 1, &newrow, 1, &newcol, &newval, INSERT_VALUES));
    941:       }
    942:     }

    944:     /* Copy L,Y */
    945:     PetscCall(VecGetOwnershipRange(ipmP->s, &sstart, &send));
    946:     PetscCall(VecGetArrayRead(ipmP->lambdai, &l));
    947:     PetscCall(VecGetArrayRead(ipmP->s, &y));

    949:     for (i = sstart; i < send; i++) {
    950:       newcols[0] = c1 + i;
    951:       newcols[1] = c3 + i;
    952:       newvals[0] = l[i - sstart];
    953:       newvals[1] = y[i - sstart];
    954:       newrow     = r3 + i;
    955:       PetscCall(MatSetValues(ipmP->K, 1, &newrow, 2, newcols, newvals, INSERT_VALUES));
    956:     }

    958:     PetscCall(VecRestoreArrayRead(ipmP->lambdai, &l));
    959:     PetscCall(VecRestoreArrayRead(ipmP->s, &y));
    960:   }

    962:   PetscCall(PetscFree(indices));
    963:   PetscCall(PetscFree(newvals));
    964:   PetscCall(MatAssemblyBegin(ipmP->K, MAT_FINAL_ASSEMBLY));
    965:   PetscCall(MatAssemblyEnd(ipmP->K, MAT_FINAL_ASSEMBLY));
    966:   PetscFunctionReturn(PETSC_SUCCESS);
    967: }

    969: static PetscErrorCode IPMGatherRHS(Tao tao, Vec RHS, Vec X1, Vec X2, Vec X3, Vec X4)
    970: {
    971:   TAO_IPM *ipmP = (TAO_IPM *)tao->data;

    973:   PetscFunctionBegin;
    974:   /* rhs = [x1      (n)
    975:             x2     (me)
    976:             x3     (nb)
    977:             x4     (nb)] */
    978:   if (X1) {
    979:     PetscCall(VecScatterBegin(ipmP->rhs1, X1, RHS, INSERT_VALUES, SCATTER_FORWARD));
    980:     PetscCall(VecScatterEnd(ipmP->rhs1, X1, RHS, INSERT_VALUES, SCATTER_FORWARD));
    981:   }
    982:   if (ipmP->me > 0 && X2) {
    983:     PetscCall(VecScatterBegin(ipmP->rhs2, X2, RHS, INSERT_VALUES, SCATTER_FORWARD));
    984:     PetscCall(VecScatterEnd(ipmP->rhs2, X2, RHS, INSERT_VALUES, SCATTER_FORWARD));
    985:   }
    986:   if (ipmP->nb > 0) {
    987:     if (X3) {
    988:       PetscCall(VecScatterBegin(ipmP->rhs3, X3, RHS, INSERT_VALUES, SCATTER_FORWARD));
    989:       PetscCall(VecScatterEnd(ipmP->rhs3, X3, RHS, INSERT_VALUES, SCATTER_FORWARD));
    990:     }
    991:     if (X4) {
    992:       PetscCall(VecScatterBegin(ipmP->rhs4, X4, RHS, INSERT_VALUES, SCATTER_FORWARD));
    993:       PetscCall(VecScatterEnd(ipmP->rhs4, X4, RHS, INSERT_VALUES, SCATTER_FORWARD));
    994:     }
    995:   }
    996:   PetscFunctionReturn(PETSC_SUCCESS);
    997: }

    999: static PetscErrorCode IPMScatterStep(Tao tao, Vec STEP, Vec X1, Vec X2, Vec X3, Vec X4)
    1000: {
    1001:   TAO_IPM *ipmP = (TAO_IPM *)tao->data;

    1003:   PetscFunctionBegin;
    1004:   CHKMEMQ;
    1005:   /*        [x1    (n)
    1006:              x2    (nb) may be 0
    1007:              x3    (me) may be 0
    1008:              x4    (nb) may be 0 */
    1009:   if (X1) {
    1010:     PetscCall(VecScatterBegin(ipmP->step1, STEP, X1, INSERT_VALUES, SCATTER_FORWARD));
    1011:     PetscCall(VecScatterEnd(ipmP->step1, STEP, X1, INSERT_VALUES, SCATTER_FORWARD));
    1012:   }
    1013:   if (X2 && ipmP->nb > 0) {
    1014:     PetscCall(VecScatterBegin(ipmP->step2, STEP, X2, INSERT_VALUES, SCATTER_FORWARD));
    1015:     PetscCall(VecScatterEnd(ipmP->step2, STEP, X2, INSERT_VALUES, SCATTER_FORWARD));
    1016:   }
    1017:   if (X3 && ipmP->me > 0) {
    1018:     PetscCall(VecScatterBegin(ipmP->step3, STEP, X3, INSERT_VALUES, SCATTER_FORWARD));
    1019:     PetscCall(VecScatterEnd(ipmP->step3, STEP, X3, INSERT_VALUES, SCATTER_FORWARD));
    1020:   }
    1021:   if (X4 && ipmP->nb > 0) {
    1022:     PetscCall(VecScatterBegin(ipmP->step4, STEP, X4, INSERT_VALUES, SCATTER_FORWARD));
    1023:     PetscCall(VecScatterEnd(ipmP->step4, STEP, X4, INSERT_VALUES, SCATTER_FORWARD));
    1024:   }
    1025:   CHKMEMQ;
    1026:   PetscFunctionReturn(PETSC_SUCCESS);
    1027: }

    1029: /*MC
    1030:   TAOIPM - Interior point algorithm for generally constrained optimization.

    1032:   Options Database Keys:
    1033: +   -tao_ipm_pushnu - parameter to push initial dual variables away from bounds
    1034: -   -tao_ipm_pushs  - parameter to push initial slack variables away from bounds

    1036:   Notes:
    1037:     This algorithm is more of a place-holder for future constrained optimization algorithms and should not yet be used for large problems or production code.
    1038:   Level: beginner

    1040: .seealso: `Tao`, `TAOPDIPM`, `TaoType`
    1041: M*/

    1043: PETSC_EXTERN PetscErrorCode TaoCreate_IPM(Tao tao)
    1044: {
    1045:   TAO_IPM *ipmP;

    1047:   PetscFunctionBegin;
    1048:   tao->ops->setup            = TaoSetup_IPM;
    1049:   tao->ops->solve            = TaoSolve_IPM;
    1050:   tao->ops->view             = TaoView_IPM;
    1051:   tao->ops->setfromoptions   = TaoSetFromOptions_IPM;
    1052:   tao->ops->destroy          = TaoDestroy_IPM;
    1053:   tao->uses_gradient         = PETSC_TRUE;
    1054:   tao->uses_hessian_matrices = PETSC_TRUE;
    1055:   /* tao->ops->computedual = TaoComputeDual_IPM; */

    1057:   PetscCall(PetscNew(&ipmP));
    1058:   tao->data = (void *)ipmP;

    1060:   /* Override default settings (unless already changed) */
    1061:   PetscCall(TaoParametersInitialize(tao));
    1062:   PetscObjectParameterSetDefault(tao, max_it, 200);
    1063:   PetscObjectParameterSetDefault(tao, max_funcs, 500);

    1065:   ipmP->dec        = 10000; /* line search criteria */
    1066:   ipmP->taumin     = 0.995;
    1067:   ipmP->monitorkkt = PETSC_FALSE;
    1068:   ipmP->pushs      = 100;
    1069:   ipmP->pushnu     = 100;
    1070:   PetscCall(KSPCreate(((PetscObject)tao)->comm, &tao->ksp));
    1071:   PetscCall(PetscObjectIncrementTabLevel((PetscObject)tao->ksp, (PetscObject)tao, 1));
    1072:   PetscCall(KSPSetOptionsPrefix(tao->ksp, tao->hdr.prefix));
    1073:   PetscFunctionReturn(PETSC_SUCCESS);
    1074: }