Actual source code: symbrdn.c

      1: #include "symbrdn.h" /*I "petscksp.h" I*/
      2: #include <petscblaslapack.h>

      4: /* Compute the forward symmetric Broyden scaling parameter phi corresponding the already known value of the "bad"
      5:    symmetric Broyden scaling parameter psi */
      6: static inline PetscScalar PhiFromPsi(PetscScalar psi, PetscScalar yts, PetscScalar stBs, PetscScalar ytHy)
      7: {
      8:   PetscScalar numer = (1.0 - psi) * PetscRealPart(PetscConj(yts) * yts);
      9:   PetscScalar phi   = numer / (numer + psi * stBs * ytHy);
     10:   return phi;
     11: }

     13: /* The symmetric Broyden update can be written as

     15:                    [         |     ] [ a_k | b_k ] [ s_k^T B_k ]
     16:    B_{k+1} = B_k + [ B_k s_k | y_k ] [-----+-----] [-----------]
     17:                    [         |     ] [ b_k | c_k ] [    y_k^T  ]

     19:    We can unroll this as

     21:                           [         |     ] [ a_i | b_i ] [ s_i^T B_i ]
     22:    B_{k+1} = B_0 + \sum_i [ B_i s_i | y_i ] [-----+-----] [-----------]
     23:                           [         |     ] [ b_i | c_i ] [    y_i^T  ]

     25:    The a_i, b_i, and c_i values are stored in M00, M01, and M11, and are computed in
     26:    SymBroydenRecursiveBasisUpdate() below
     27:  */
     28: static PetscErrorCode SymBroydenKernel_Recursive_Inner(Mat B, MatLMVMMode mode, PetscInt oldest, PetscInt next, Vec X, Vec B0X)
     29: {
     30:   Mat_LMVM        *lmvm = (Mat_LMVM *)B->data;
     31:   Mat_SymBrdn     *lsb  = (Mat_SymBrdn *)lmvm->ctx;
     32:   MatLMVMBasisType Y_t  = LMVMModeMap(LMBASIS_Y, mode);
     33:   LMBasis          BkS  = lsb->basis[LMVMModeMap(SYMBROYDEN_BASIS_BKS, mode)];
     34:   LMProducts       M00  = lsb->products[LMVMModeMap(SYMBROYDEN_PRODUCTS_M00, mode)];
     35:   LMProducts       M01  = lsb->products[LMVMModeMap(SYMBROYDEN_PRODUCTS_M01, mode)];
     36:   LMProducts       M11  = lsb->products[LMVMModeMap(SYMBROYDEN_PRODUCTS_M11, mode)];
     37:   LMBasis          Y;
     38:   Vec              StBkX, YtX, U, V;

     40:   PetscFunctionBegin;
     41:   PetscCall(MatLMVMGetUpdatedBasis(B, Y_t, &Y, NULL, NULL));
     42:   PetscCall(MatLMVMGetWorkRow(B, &StBkX));
     43:   PetscCall(MatLMVMGetWorkRow(B, &YtX));
     44:   PetscCall(MatLMVMGetWorkRow(B, &U));
     45:   PetscCall(MatLMVMGetWorkRow(B, &V));
     46:   PetscCall(LMBasisGEMVH(BkS, oldest, next, 1.0, X, 0.0, StBkX));
     47:   PetscCall(LMBasisGEMVH(Y, oldest, next, 1.0, X, 0.0, YtX));
     48:   PetscCall(LMProductsMult(M00, oldest, next, 1.0, StBkX, 0.0, U, PETSC_FALSE));
     49:   PetscCall(LMProductsMult(M01, oldest, next, 1.0, YtX, 1.0, U, PETSC_FALSE));
     50:   PetscCall(LMProductsMult(M01, oldest, next, 1.0, StBkX, 0.0, V, PETSC_FALSE));
     51:   PetscCall(LMProductsMult(M11, oldest, next, 1.0, YtX, 1.0, V, PETSC_FALSE));
     52:   PetscCall(LMBasisGEMV(BkS, oldest, next, 1.0, U, 1.0, B0X));
     53:   PetscCall(LMBasisGEMV(Y, oldest, next, 1.0, V, 1.0, B0X));
     54:   PetscCall(MatLMVMRestoreWorkRow(B, &V));
     55:   PetscCall(MatLMVMRestoreWorkRow(B, &U));
     56:   PetscCall(MatLMVMRestoreWorkRow(B, &YtX));
     57:   PetscCall(MatLMVMRestoreWorkRow(B, &StBkX));
     58:   PetscFunctionReturn(PETSC_SUCCESS);
     59: }

     61: static PetscErrorCode MatLMVMSymBroydenGetConvexFactor(Mat B, SymBroydenProductsType Phi_t, LMProducts *Phi)
     62: {
     63:   Mat_LMVM    *lmvm = (Mat_LMVM *)B->data;
     64:   Mat_SymBrdn *lsb  = (Mat_SymBrdn *)lmvm->ctx;
     65:   PetscScalar  phi  = Phi_t == SYMBROYDEN_PRODUCTS_PHI ? lsb->phi_scalar : lsb->psi_scalar;

     67:   PetscFunctionBegin;
     68:   if (!lsb->products[Phi_t]) PetscCall(MatLMVMCreateProducts(B, LMBLOCK_DIAGONAL, &lsb->products[Phi_t]));
     69:   *Phi = lsb->products[Phi_t];
     70:   if (phi != PETSC_DETERMINE) {
     71:     PetscInt oldest, next, start;

     73:     PetscCall(MatLMVMGetRange(B, &oldest, &next));
     74:     start     = PetscMax((*Phi)->k, oldest);
     75:     (*Phi)->k = start;
     76:     for (PetscInt i = start; i < next; i++) PetscCall(LMProductsInsertNextDiagonalValue(*Phi, i, phi));
     77:   }
     78:   PetscFunctionReturn(PETSC_SUCCESS);
     79: }

     81: static PetscErrorCode SymBroydenRecursiveBasisUpdate(Mat B, MatLMVMMode mode, PetscBool update_phi_from_psi)
     82: {
     83:   Mat_LMVM              *lmvm    = (Mat_LMVM *)B->data;
     84:   Mat_SymBrdn           *lsb     = (Mat_SymBrdn *)lmvm->ctx;
     85:   MatLMVMBasisType       S_t     = LMVMModeMap(LMBASIS_S, mode);
     86:   MatLMVMBasisType       B0S_t   = LMVMModeMap(LMBASIS_B0S, mode);
     87:   SymBroydenProductsType Phi_t   = LMVMModeMap(SYMBROYDEN_PRODUCTS_PHI, mode);
     88:   SymBroydenProductsType Psi_t   = LMVMModeMap(SYMBROYDEN_PRODUCTS_PSI, mode);
     89:   SymBroydenProductsType StBkS_t = LMVMModeMap(SYMBROYDEN_PRODUCTS_STBKS, mode);
     90:   SymBroydenProductsType YtHkY_t = LMVMModeMap(SYMBROYDEN_PRODUCTS_YTHKY, mode);
     91:   SymBroydenProductsType M00_t   = LMVMModeMap(SYMBROYDEN_PRODUCTS_M00, mode);
     92:   SymBroydenProductsType M01_t   = LMVMModeMap(SYMBROYDEN_PRODUCTS_M01, mode);
     93:   SymBroydenProductsType M11_t   = LMVMModeMap(SYMBROYDEN_PRODUCTS_M11, mode);
     94:   SymBroydenProductsType M_t[3]  = {M00_t, M01_t, M11_t};
     95:   LMProducts             M[3];
     96:   LMProducts             Phi, Psi = NULL;
     97:   SymBroydenBasisType    BkS_t = LMVMModeMap(SYMBROYDEN_BASIS_BKS, mode);
     98:   LMBasis                BkS;
     99:   LMProducts             StBkS, YtHkY = NULL;
    100:   PetscInt               oldest, start, next;
    101:   PetscInt               products_oldest;
    102:   LMBasis                S;

    104:   PetscFunctionBegin;
    105:   PetscCall(MatLMVMGetRange(B, &oldest, &next));
    106:   for (PetscInt i = 0; i < 3; i++) {
    107:     if (lsb->products[M_t[i]] && lsb->products[M_t[i]]->block_type != LMBLOCK_DIAGONAL) PetscCall(LMProductsDestroy(&lsb->products[M_t[i]]));
    108:     if (!lsb->products[M_t[i]]) PetscCall(MatLMVMCreateProducts(B, LMBLOCK_DIAGONAL, &lsb->products[M_t[i]]));
    109:     M[i] = lsb->products[M_t[i]];
    110:   }
    111:   if (!lsb->basis[BkS_t]) PetscCall(LMBasisCreate(MatLMVMBasisSizeOf(B0S_t) == LMBASIS_S ? lmvm->Xprev : lmvm->Fprev, lmvm->m, &lsb->basis[BkS_t]));
    112:   BkS = lsb->basis[BkS_t];
    113:   PetscCall(MatLMVMSymBroydenGetConvexFactor(B, Phi_t, &Phi));
    114:   if (!lsb->products[StBkS_t]) PetscCall(MatLMVMCreateProducts(B, LMBLOCK_DIAGONAL, &lsb->products[StBkS_t]));
    115:   StBkS = lsb->products[StBkS_t];
    116:   PetscCall(LMProductsPrepare(StBkS, lmvm->J0, oldest, next));
    117:   products_oldest = PetscMax(0, StBkS->k - lmvm->m);
    118:   if (oldest > products_oldest) {
    119:     // recursion is starting from a different starting index, it must be recomputed
    120:     StBkS->k = oldest;
    121:   }
    122:   BkS->k = start = StBkS->k;
    123:   for (PetscInt i = 0; i < 3; i++) M[i]->k = start;
    124:   if (start == next) PetscFunctionReturn(PETSC_SUCCESS);

    126:   if (update_phi_from_psi) {
    127:     Phi->k = start;
    128:     // we have to first make sure that the inverse data is up to date
    129:     PetscCall(SymBroydenRecursiveBasisUpdate(B, (MatLMVMMode)(mode ^ 1), PETSC_FALSE));
    130:     PetscCall(MatLMVMSymBroydenGetConvexFactor(B, Psi_t, &Psi));
    131:     YtHkY = lsb->products[YtHkY_t];
    132:   }
    133:   PetscCall(MatLMVMGetUpdatedBasis(B, S_t, &S, NULL, NULL));

    135:   for (PetscInt j = start; j < next; j++) {
    136:     Vec         p_j, s_j, B0s_j;
    137:     PetscScalar alpha, sjtbjsj;
    138:     PetscScalar m_00, m_01, m_11, yjtsj;
    139:     PetscScalar phi_j;

    141:     PetscCall(LMBasisGetWorkVec(BkS, &p_j));
    142:     // p_j starts as B_0 * s_j
    143:     PetscCall(MatLMVMBasisGetVecRead(B, B0S_t, j, &B0s_j, &alpha));
    144:     PetscCall(VecAXPBY(p_j, alpha, 0.0, B0s_j));
    145:     PetscCall(MatLMVMBasisRestoreVecRead(B, B0S_t, j, &B0s_j, &alpha));

    147:     // Use the matmult kernel to compute p_j = B_j * p_j
    148:     PetscCall(LMBasisGetVecRead(S, j, &s_j));
    149:     if (j > oldest) PetscCall(SymBroydenKernel_Recursive_Inner(B, mode, oldest, j, s_j, p_j));
    150:     PetscCall(VecDot(p_j, s_j, &sjtbjsj));
    151:     PetscCall(LMBasisRestoreVecRead(S, j, &s_j));
    152:     PetscCall(LMProductsInsertNextDiagonalValue(StBkS, j, sjtbjsj));
    153:     PetscCall(LMBasisSetNextVec(BkS, p_j));
    154:     PetscCall(LMBasisRestoreWorkVec(BkS, &p_j));

    156:     PetscCall(MatLMVMProductsGetDiagonalValue(B, LMBASIS_Y, LMBASIS_S, j, &yjtsj));
    157:     if (update_phi_from_psi) {
    158:       PetscScalar psi_j;
    159:       PetscScalar yjthjyj;

    161:       PetscCall(LMProductsGetDiagonalValue(YtHkY, j, &yjthjyj));
    162:       PetscCall(LMProductsGetDiagonalValue(Psi, j, &psi_j));

    164:       phi_j = PhiFromPsi(psi_j, yjtsj, sjtbjsj, yjthjyj);
    165:       PetscCall(LMProductsInsertNextDiagonalValue(Phi, j, phi_j));
    166:     } else PetscCall(LMProductsGetDiagonalValue(Phi, j, &phi_j));

    168:     /* The symmetric Broyden update can be represented as

    170:        [     |     ][ (phi - 1) / s_j^T p_j |              -phi / y_j^T s_j                 ][ p_j^T ]
    171:        [ p_j | y_j ][-----------------------+-----------------------------------------------][-------]
    172:        [     |     ][    -phi / y_j^T s_j   | (y_j^T s_j + phi * s_j^T p_j) / (y_j^T s_j)^2 ][ y_j^T ]

    174:        We store diagonal vectors with these values
    175:      */

    177:     m_00 = (phi_j - 1.0) / sjtbjsj;
    178:     m_01 = -phi_j / yjtsj;
    179:     m_11 = (yjtsj + phi_j * sjtbjsj) / (yjtsj * yjtsj);
    180:     PetscCall(LMProductsInsertNextDiagonalValue(M[0], j, m_00));
    181:     PetscCall(LMProductsInsertNextDiagonalValue(M[1], j, m_01));
    182:     PetscCall(LMProductsInsertNextDiagonalValue(M[2], j, m_11));
    183:   }
    184:   PetscFunctionReturn(PETSC_SUCCESS);
    185: }

    187: PETSC_INTERN PetscErrorCode SymBroydenKernel_Recursive(Mat B, MatLMVMMode mode, Vec X, Vec Y, PetscBool update_phi_from_psi)
    188: {
    189:   PetscInt oldest, next;

    191:   PetscFunctionBegin;
    192:   PetscCall(MatLMVMApplyJ0Mode(mode)(B, X, Y));
    193:   PetscCall(MatLMVMGetRange(B, &oldest, &next));
    194:   if (next > oldest) {
    195:     PetscCall(SymBroydenRecursiveBasisUpdate(B, mode, update_phi_from_psi));
    196:     PetscCall(SymBroydenKernel_Recursive_Inner(B, mode, oldest, next, X, Y));
    197:   }
    198:   PetscFunctionReturn(PETSC_SUCCESS);
    199: }

    201: static PetscErrorCode MatMult_LMVMSymBrdn_Recursive(Mat B, Vec X, Vec Y)
    202: {
    203:   Mat_LMVM    *lmvm = (Mat_LMVM *)B->data;
    204:   Mat_SymBrdn *lsb  = (Mat_SymBrdn *)lmvm->ctx;

    206:   PetscFunctionBegin;
    207:   PetscCheck(lsb->phi_scalar != PETSC_DETERMINE, PetscObjectComm((PetscObject)B), PETSC_ERR_ARG_WRONGSTATE, "Phi must first be set using MatLMVMSymBroydenSetPhi()");
    208:   if (lsb->phi_scalar == 0.0) {
    209:     PetscCall(BFGSKernel_Recursive(B, MATLMVM_MODE_PRIMAL, X, Y));
    210:   } else if (lsb->phi_scalar == 1.0) {
    211:     PetscCall(DFPKernel_Recursive(B, MATLMVM_MODE_PRIMAL, X, Y));
    212:   } else {
    213:     PetscCall(SymBroydenKernel_Recursive(B, MATLMVM_MODE_PRIMAL, X, Y, PETSC_FALSE));
    214:   }
    215:   PetscFunctionReturn(PETSC_SUCCESS);
    216: }

    218: static PetscErrorCode MatSolve_LMVMSymBrdn_Recursive(Mat B, Vec X, Vec Y)
    219: {
    220:   Mat_LMVM    *lmvm = (Mat_LMVM *)B->data;
    221:   Mat_SymBrdn *lsb  = (Mat_SymBrdn *)lmvm->ctx;

    223:   PetscFunctionBegin;
    224:   PetscCheck(lsb->phi_scalar != PETSC_DETERMINE, PetscObjectComm((PetscObject)B), PETSC_ERR_ARG_WRONGSTATE, "Phi must first be set using MatLMVMSymBroydenSetPhi()");
    225:   if (lsb->phi_scalar == 0.0) {
    226:     PetscCall(DFPKernel_Recursive(B, MATLMVM_MODE_DUAL, X, Y));
    227:   } else if (lsb->phi_scalar == 1.0) {
    228:     PetscCall(BFGSKernel_Recursive(B, MATLMVM_MODE_DUAL, X, Y));
    229:   } else {
    230:     PetscCall(SymBroydenKernel_Recursive(B, MATLMVM_MODE_DUAL, X, Y, PETSC_TRUE));
    231:   }
    232:   PetscFunctionReturn(PETSC_SUCCESS);
    233: }

    235: PetscBool  ErwayMarciaCite       = PETSC_FALSE;
    236: const char ErwayMarciaCitation[] = "@article{Erway2015,"
    237:                                    "  title = {On Efficiently Computing the Eigenvalues of Limited-Memory Quasi-Newton Matrices},"
    238:                                    "  volume = {36},"
    239:                                    "  ISSN = {1095-7162},"
    240:                                    "  url = {http://dx.doi.org/10.1137/140997737},"
    241:                                    "  DOI = {10.1137/140997737},"
    242:                                    "  number = {3},"
    243:                                    "  journal = {SIAM Journal on Matrix Analysis and Applications},"
    244:                                    "  publisher = {Society for Industrial & Applied Mathematics (SIAM)},"
    245:                                    "  author = {Erway,  Jennifer B. and Marcia,  Roummel F.},"
    246:                                    "  year = {2015},"
    247:                                    "  month = jan,"
    248:                                    "  pages = {1338-1359}"
    249:                                    "}\n";

    251: // TODO: on device (e.g. cuBLAS) implementation?
    252: static PetscErrorCode SymBroydenCompactDenseUpdateArrays(PetscBLASInt m, PetscBLASInt oldest, PetscBLASInt next, PetscScalar M00[], PetscBLASInt lda00, PetscScalar M01[], PetscBLASInt lda01, PetscScalar M11[], PetscBLASInt lda11, const PetscScalar StB0S[], PetscBLASInt ldasbs, const PetscScalar YtS[], PetscBLASInt ldays, const PetscScalar Phi[], PetscScalar p0[], PetscScalar p1[], const PetscScalar Psi[], const PetscScalar YtHkY[], PetscScalar StBkS[])
    253: {
    254:   PetscBLASInt i;
    255:   PetscScalar  alpha, beta, delta;
    256:   PetscBLASInt ione  = 1;
    257:   PetscScalar  sone  = 1.0;
    258:   PetscScalar  szero = 0.0;
    259:   PetscScalar  sBis;
    260:   PetscScalar  yts;
    261:   PetscScalar  phi;

    263:   PetscFunctionBegin;
    264:   if (next <= oldest || m <= 0) PetscFunctionReturn(PETSC_SUCCESS);

    266:   PetscCall(PetscCitationsRegister(ErwayMarciaCitation, &ErwayMarciaCite));

    268:   PetscCall(PetscArrayzero(M00, m * lda00));
    269:   PetscCall(PetscArrayzero(M01, m * lda01));
    270:   PetscCall(PetscArrayzero(M11, m * lda11));

    272:   i = oldest % m;

    274:   // Base case entries
    275:   sBis = StB0S[i + i * ldasbs];
    276:   if (StBkS) StBkS[i] = sBis;
    277:   yts = YtS[i + i * ldays];
    278:   if (Psi) {
    279:     phi = PhiFromPsi(Psi[i], yts, sBis, YtHkY[i]);
    280:   } else {
    281:     phi = Phi[i];
    282:   }
    283:   alpha              = PetscRealPart(-(1.0 - phi) / sBis);
    284:   beta               = -phi / yts;
    285:   delta              = (1.0 + phi * sBis / yts) / yts;
    286:   M00[i + i * lda00] = alpha;
    287:   M01[i + i * lda01] = beta;
    288:   M11[i + i * lda11] = delta;
    289:   for (PetscBLASInt i_ = oldest + 1; i_ < next; i_++) {
    290:     const PetscScalar *q0, *q1;
    291:     PetscScalar        qp;

    293:     i  = i_ % m;
    294:     q0 = &StB0S[0 + i * ldasbs];
    295:     q1 = &YtS[0 + i * ldays];

    297:     // p_i <- M_{i-1} q_i

    299:     PetscCallBLAS("BLASgemv", BLASgemv_("N", &m, &m, &sone, M00, &lda00, q0, &ione, &szero, p0, &ione));
    300:     PetscCallBLAS("BLASgemv", BLASgemv_("N", &m, &m, &sone, M01, &lda01, q1, &ione, &sone, p0, &ione));
    301:     PetscCallBLAS("BLASgemv", BLASgemv_("C", &m, &m, &sone, M01, &lda01, q0, &ione, &szero, p1, &ione));
    302:     PetscCallBLAS("BLASgemv", BLASgemv_("N", &m, &m, &sone, M11, &lda11, q1, &ione, &sone, p1, &ione));

    304:     // q'p
    305:     PetscCallBLAS("BLASdot", qp = BLASdot_(&m, q0, &ione, p0, &ione));
    306:     PetscCallBLAS("BLASdot", qp += BLASdot_(&m, q1, &ione, p1, &ione));

    308:     sBis = StB0S[i + i * ldasbs] + qp;
    309:     if (StBkS) StBkS[i] = sBis;
    310:     yts = YtS[i + i * ldays];
    311:     if (Psi) {
    312:       phi = PhiFromPsi(Psi[i], yts, sBis, YtHkY[i]);
    313:     } else {
    314:       phi = Phi[i];
    315:     }

    317:     alpha = PetscRealPart(-(1.0 - phi) / sBis);
    318:     beta  = -phi / yts;
    319:     delta = (1.0 + phi * sBis / yts) / yts;

    321:     PetscCallBLAS("LAPACKgerc", LAPACKgerc_(&m, &m, &alpha, p0, &ione, p0, &ione, M00, &lda00));
    322:     for (PetscInt j = 0; j < m; j++) M00[j + i * lda00] = alpha * p0[j];
    323:     for (PetscInt j = 0; j < m; j++) M00[i + j * lda00] = PetscConj(alpha * p0[j]);
    324:     M00[i + i * lda00] = alpha;

    326:     PetscCallBLAS("LAPACKgerc", LAPACKgerc_(&m, &m, &alpha, p0, &ione, p1, &ione, M01, &lda01));
    327:     for (PetscBLASInt j = 0; j < m; j++) M01[j + i * lda01] = beta * p0[j];
    328:     for (PetscBLASInt j = 0; j < m; j++) M01[i + j * lda01] = PetscConj(alpha * p1[j]);
    329:     M01[i + i * lda01] = beta;

    331:     PetscCallBLAS("LAPACKgerc", LAPACKgerc_(&m, &m, &alpha, p1, &ione, p1, &ione, M11, &lda11));
    332:     for (PetscInt j = 0; j < m; j++) M11[j + i * lda11] = beta * p1[j];
    333:     for (PetscInt j = 0; j < m; j++) M11[i + j * lda11] = PetscConj(beta * p1[j]);
    334:     M11[i + i * lda11] = delta;
    335:   }
    336:   PetscFunctionReturn(PETSC_SUCCESS);
    337: }

    339: static PetscErrorCode SymBroydenCompactProductsUpdate(Mat B, MatLMVMMode mode, PetscBool update_phi_from_psi)
    340: {
    341:   Mat_LMVM              *lmvm = (Mat_LMVM *)B->data;
    342:   Mat_SymBrdn           *lsb  = (Mat_SymBrdn *)lmvm->ctx;
    343:   PetscInt               oldest, next;
    344:   MatLMVMBasisType       S_t     = LMVMModeMap(LMBASIS_S, mode);
    345:   MatLMVMBasisType       B0S_t   = LMVMModeMap(LMBASIS_B0S, mode);
    346:   MatLMVMBasisType       Y_t     = LMVMModeMap(LMBASIS_Y, mode);
    347:   SymBroydenProductsType Phi_t   = LMVMModeMap(SYMBROYDEN_PRODUCTS_PHI, mode);
    348:   SymBroydenProductsType Psi_t   = LMVMModeMap(SYMBROYDEN_PRODUCTS_PSI, mode);
    349:   SymBroydenProductsType StBkS_t = LMVMModeMap(SYMBROYDEN_PRODUCTS_STBKS, mode);
    350:   SymBroydenProductsType YtHkY_t = LMVMModeMap(SYMBROYDEN_PRODUCTS_YTHKY, mode);
    351:   SymBroydenProductsType M00_t   = LMVMModeMap(SYMBROYDEN_PRODUCTS_M00, mode);
    352:   SymBroydenProductsType M01_t   = LMVMModeMap(SYMBROYDEN_PRODUCTS_M01, mode);
    353:   SymBroydenProductsType M11_t   = LMVMModeMap(SYMBROYDEN_PRODUCTS_M11, mode);
    354:   SymBroydenProductsType M_t[3]  = {M00_t, M01_t, M11_t};
    355:   Mat                    M_local[3];
    356:   LMProducts             M[3], Phi, Psi, YtS, StB0S, StBkS, YtHkY;
    357:   PetscInt               products_oldest, k;
    358:   PetscBool              local_is_nonempty;

    360:   PetscFunctionBegin;
    361:   PetscCall(MatLMVMGetRange(B, &oldest, &next));
    362:   for (PetscInt i = 0; i < 3; i++) {
    363:     if (lsb->products[M_t[i]] && lsb->products[M_t[i]]->block_type != LMBLOCK_FULL) PetscCall(LMProductsDestroy(&lsb->products[M_t[i]]));
    364:     if (!lsb->products[M_t[i]]) PetscCall(MatLMVMCreateProducts(B, LMBLOCK_FULL, &lsb->products[M_t[i]]));
    365:     M[i] = lsb->products[M_t[i]];
    366:   }
    367:   PetscCall(MatLMVMSymBroydenGetConvexFactor(B, Phi_t, &Phi));
    368:   PetscCall(MatLMVMSymBroydenGetConvexFactor(B, Psi_t, &Psi));
    369:   if (!lsb->products[StBkS_t]) PetscCall(MatLMVMCreateProducts(B, LMBLOCK_DIAGONAL, &lsb->products[StBkS_t]));
    370:   StBkS = lsb->products[StBkS_t];
    371:   if (!lsb->products[YtHkY_t]) PetscCall(MatLMVMCreateProducts(B, LMBLOCK_DIAGONAL, &lsb->products[YtHkY_t]));
    372:   YtHkY = lsb->products[YtHkY_t];
    373:   PetscCall(LMProductsPrepare(M[0], lmvm->J0, oldest, next));
    374:   PetscCall(LMProductsGetLocalMatrix(M[0], &M_local[0], &k, &local_is_nonempty));
    375:   products_oldest = PetscMax(0, k - lmvm->m);
    376:   if (products_oldest < oldest) k = oldest;
    377:   if (k < next) {
    378:     Mat StB0S_local, YtS_local;
    379:     Vec Psi_local = NULL, Phi_local = NULL, YtHkY_local = NULL, StBkS_local = NULL;

    381:     PetscCall(MatLMVMGetUpdatedProducts(B, Y_t, S_t, LMBLOCK_UPPER_TRIANGLE, &YtS));
    382:     PetscCall(MatLMVMGetUpdatedProducts(B, S_t, B0S_t, LMBLOCK_UPPER_TRIANGLE, &StB0S));
    383:     PetscCall(LMProductsGetLocalMatrix(StB0S, &StB0S_local, NULL, NULL));
    384:     PetscCall(LMProductsGetLocalMatrix(YtS, &YtS_local, NULL, NULL));
    385:     PetscCall(LMProductsGetLocalMatrix(M[1], &M_local[1], NULL, NULL));
    386:     PetscCall(LMProductsGetLocalMatrix(M[2], &M_local[2], NULL, NULL));
    387:     if (update_phi_from_psi) {
    388:       PetscCall(LMProductsGetLocalDiagonal(Psi, &Psi_local));
    389:       PetscCall(LMProductsGetLocalDiagonal(YtHkY, &YtHkY_local));
    390:     } else {
    391:       PetscCall(LMProductsGetLocalDiagonal(Phi, &Phi_local));
    392:       PetscCall(LMProductsGetLocalDiagonal(StBkS, &StBkS_local));
    393:     }
    394:     if (local_is_nonempty) {
    395:       PetscInt           lda;
    396:       PetscBLASInt       M_lda[3], StB0S_lda, YtS_lda, m_blas, oldest_blas, next_blas;
    397:       const PetscScalar *StB0S_;
    398:       const PetscScalar *YtS_;
    399:       PetscScalar       *M_[3];
    400:       const PetscScalar *Phi_   = NULL;
    401:       const PetscScalar *Psi_   = NULL;
    402:       const PetscScalar *YtHkY_ = NULL;
    403:       PetscScalar       *StBkS_ = NULL;
    404:       PetscScalar       *p0, *p1;

    406:       for (PetscInt i = 0; i < 3; i++) {
    407:         PetscCall(MatDenseGetLDA(M_local[i], &lda));
    408:         PetscCall(PetscBLASIntCast(lda, &M_lda[i]));
    409:         PetscCall(MatDenseGetArrayWrite(M_local[i], &M_[i]));
    410:       }

    412:       PetscCall(MatDenseGetArrayRead(StB0S_local, &StB0S_));
    413:       PetscCall(MatDenseGetLDA(StB0S_local, &lda));
    414:       PetscCall(PetscBLASIntCast(lda, &StB0S_lda));

    416:       PetscCall(MatDenseGetArrayRead(YtS_local, &YtS_));
    417:       PetscCall(MatDenseGetLDA(YtS_local, &lda));
    418:       PetscCall(PetscBLASIntCast(lda, &YtS_lda));

    420:       PetscCall(PetscBLASIntCast(lmvm->m, &m_blas));
    421:       PetscCall(PetscBLASIntCast(oldest, &oldest_blas));
    422:       PetscCall(PetscBLASIntCast(next, &next_blas));

    424:       if (update_phi_from_psi) {
    425:         PetscCall(VecGetArrayRead(Psi_local, &Psi_));
    426:         PetscCall(VecGetArrayRead(YtHkY_local, &YtHkY_));
    427:       } else {
    428:         PetscCall(VecGetArrayRead(Phi_local, &Phi_));
    429:         PetscCall(VecGetArrayWrite(StBkS_local, &StBkS_));
    430:       }

    432:       PetscCall(PetscMalloc2(lmvm->m, &p0, lmvm->m, &p1));
    433:       PetscCall(SymBroydenCompactDenseUpdateArrays(m_blas, oldest_blas, next_blas, M_[0], M_lda[0], M_[1], M_lda[1], M_[2], M_lda[2], StB0S_, StB0S_lda, YtS_, YtS_lda, Phi_, p0, p1, Psi_, YtHkY_, StBkS_));
    434:       PetscCall(PetscFree2(p0, p1));

    436:       if (update_phi_from_psi) {
    437:         PetscCall(VecRestoreArrayRead(YtHkY_local, &YtHkY_));
    438:         PetscCall(VecRestoreArrayRead(Psi_local, &Psi_));
    439:       } else {
    440:         PetscCall(VecRestoreArrayWrite(StBkS_local, &StBkS_));
    441:         PetscCall(VecRestoreArrayRead(Phi_local, &Phi_));
    442:       }

    444:       for (PetscInt i = 0; i < 3; i++) PetscCall(MatDenseRestoreArrayWrite(M_local[i], &M_[i]));
    445:       PetscCall(MatDenseRestoreArrayRead(YtS_local, &YtS_));
    446:       PetscCall(MatDenseRestoreArrayRead(StB0S_local, &StB0S_));
    447:     }
    448:     if (update_phi_from_psi) {
    449:       PetscCall(LMProductsRestoreLocalDiagonal(YtHkY, &YtHkY_local));
    450:       PetscCall(LMProductsRestoreLocalDiagonal(Psi, &Psi_local));
    451:     } else {
    452:       PetscCall(LMProductsRestoreLocalDiagonal(StBkS, &StBkS_local));
    453:       PetscCall(LMProductsRestoreLocalDiagonal(Phi, &Phi_local));
    454:     }
    455:     PetscCall(LMProductsRestoreLocalMatrix(M[2], &M_local[2], &next));
    456:     PetscCall(LMProductsRestoreLocalMatrix(M[1], &M_local[1], &next));
    457:     PetscCall(LMProductsRestoreLocalMatrix(YtS, &YtS_local, NULL));
    458:     PetscCall(LMProductsRestoreLocalMatrix(StB0S, &StB0S_local, NULL));
    459:   }
    460:   PetscCall(LMProductsRestoreLocalMatrix(M[0], &M_local[0], &next));
    461:   PetscFunctionReturn(PETSC_SUCCESS);
    462: }

    464: PETSC_INTERN PetscErrorCode SymBroydenCompactDenseKernelUseB0S(Mat B, MatLMVMMode mode, Vec X, PetscBool *use_B0S)
    465: {
    466:   Mat_LMVM        *lmvm = (Mat_LMVM *)B->data;
    467:   PetscBool        is_scalar;
    468:   PetscScalar      J0_scale;
    469:   LMBasis          B0S;
    470:   Mat              J0 = lmvm->J0;
    471:   PetscObjectId    id;
    472:   PetscObjectState state;

    474:   /*
    475:      The one time where we would want to compute S^T B_0 X as (B_0 S)^T X instead of S^T (B_0 X)
    476:      is if (B_0 S)^T X is cached.
    477:    */
    478:   PetscFunctionBegin;
    479:   *use_B0S = PETSC_FALSE;
    480:   PetscCall(MatLMVMGetJ0Scalar(B, &is_scalar, &J0_scale));
    481:   B0S = lmvm->basis[is_scalar ? LMVMModeMap(LMBASIS_S, mode) : LMVMModeMap(LMBASIS_B0S, mode)];
    482:   if ((B0S->k < lmvm->k) || (B0S->cached_product == NULL)) PetscFunctionReturn(PETSC_SUCCESS);
    483:   if (!is_scalar) {
    484:     PetscCall(PetscObjectGetId((PetscObject)J0, &id));
    485:     PetscCall(PetscObjectStateGet((PetscObject)J0, &state));
    486:     if (id != B0S->operator_id || state != B0S->operator_state) PetscFunctionReturn(PETSC_SUCCESS);
    487:   }
    488:   PetscCall(PetscObjectGetId((PetscObject)X, &id));
    489:   PetscCall(PetscObjectStateGet((PetscObject)X, &state));
    490:   if (id == B0S->cached_vec_id && state == B0S->cached_vec_state) *use_B0S = PETSC_TRUE;
    491:   PetscFunctionReturn(PETSC_SUCCESS);
    492: }

    494: PETSC_INTERN PetscErrorCode SymBroydenKernel_CompactDense(Mat B, MatLMVMMode mode, Vec X, Vec BX, PetscBool update_phi_from_psi)
    495: {
    496:   PetscInt oldest, next;

    498:   PetscFunctionBegin;
    499:   PetscCall(MatLMVMApplyJ0Mode(mode)(B, X, BX));
    500:   PetscCall(MatLMVMGetRange(B, &oldest, &next));
    501:   if (next > oldest) {
    502:     Mat_LMVM              *lmvm = (Mat_LMVM *)B->data;
    503:     Mat_SymBrdn           *lsb  = (Mat_SymBrdn *)lmvm->ctx;
    504:     Vec                    StB0X, YtX, u, v;
    505:     MatLMVMBasisType       S_t   = LMVMModeMap(LMBASIS_S, mode);
    506:     MatLMVMBasisType       Y_t   = LMVMModeMap(LMBASIS_Y, mode);
    507:     MatLMVMBasisType       B0S_t = LMVMModeMap(LMBASIS_B0S, mode);
    508:     SymBroydenProductsType M00_t = LMVMModeMap(SYMBROYDEN_PRODUCTS_M00, mode);
    509:     SymBroydenProductsType M01_t = LMVMModeMap(SYMBROYDEN_PRODUCTS_M01, mode);
    510:     SymBroydenProductsType M11_t = LMVMModeMap(SYMBROYDEN_PRODUCTS_M11, mode);
    511:     LMProducts             M00, M01, M11;
    512:     LMBasis                S, Y;
    513:     PetscBool              use_B0S;

    515:     if (update_phi_from_psi) PetscCall(SymBroydenCompactProductsUpdate(B, (MatLMVMMode)(mode ^ 1), PETSC_FALSE));
    516:     PetscCall(SymBroydenCompactProductsUpdate(B, mode, update_phi_from_psi));
    517:     M00 = lsb->products[M00_t];
    518:     M01 = lsb->products[M01_t];
    519:     M11 = lsb->products[M11_t];

    521:     PetscCall(MatLMVMGetUpdatedBasis(B, S_t, &S, NULL, NULL));
    522:     PetscCall(MatLMVMGetUpdatedBasis(B, Y_t, &Y, NULL, NULL));

    524:     PetscCall(MatLMVMGetWorkRow(B, &StB0X));
    525:     PetscCall(MatLMVMGetWorkRow(B, &YtX));
    526:     PetscCall(MatLMVMGetWorkRow(B, &u));
    527:     PetscCall(MatLMVMGetWorkRow(B, &v));

    529:     PetscCall(SymBroydenCompactDenseKernelUseB0S(B, mode, X, &use_B0S));
    530:     if (use_B0S) PetscCall(MatLMVMBasisGEMVH(B, B0S_t, oldest, next, 1.0, X, 0.0, StB0X));
    531:     else PetscCall(LMBasisGEMVH(S, oldest, next, 1.0, BX, 0.0, StB0X));

    533:     PetscCall(LMBasisGEMVH(Y, oldest, next, 1.0, X, 0.0, YtX));

    535:     PetscCall(LMProductsMult(M00, oldest, next, 1.0, StB0X, 0.0, u, PETSC_FALSE));
    536:     PetscCall(LMProductsMult(M01, oldest, next, 1.0, YtX, 1.0, u, PETSC_FALSE));
    537:     PetscCall(LMProductsMult(M01, oldest, next, 1.0, StB0X, 0.0, v, PETSC_TRUE));
    538:     PetscCall(LMProductsMult(M11, oldest, next, 1.0, YtX, 1.0, v, PETSC_FALSE));

    540:     PetscCall(LMBasisGEMV(Y, oldest, next, 1.0, v, 1.0, BX));
    541:     PetscCall(MatLMVMBasisGEMV(B, B0S_t, oldest, next, 1.0, u, 1.0, BX));

    543:     PetscCall(MatLMVMRestoreWorkRow(B, &v));
    544:     PetscCall(MatLMVMRestoreWorkRow(B, &u));
    545:     PetscCall(MatLMVMRestoreWorkRow(B, &YtX));
    546:     PetscCall(MatLMVMRestoreWorkRow(B, &StB0X));
    547:   }
    548:   PetscFunctionReturn(PETSC_SUCCESS);
    549: }

    551: static PetscErrorCode MatMult_LMVMSymBrdn_CompactDense(Mat B, Vec X, Vec BX)
    552: {
    553:   Mat_LMVM    *lmvm = (Mat_LMVM *)B->data;
    554:   Mat_SymBrdn *lsb  = (Mat_SymBrdn *)lmvm->ctx;

    556:   PetscFunctionBegin;
    557:   PetscCheck(lsb->phi_scalar != PETSC_DETERMINE, PetscObjectComm((PetscObject)B), PETSC_ERR_ARG_WRONGSTATE, "Phi must first be set using MatLMVMSymBroydenSetPhi()");
    558:   if (lsb->phi_scalar == 0.0) {
    559:     PetscCall(BFGSKernel_CompactDense(B, MATLMVM_MODE_PRIMAL, X, BX));
    560:   } else if (lsb->phi_scalar == 1.0) {
    561:     PetscCall(DFPKernel_CompactDense(B, MATLMVM_MODE_PRIMAL, X, BX));
    562:   } else {
    563:     PetscCall(SymBroydenKernel_CompactDense(B, MATLMVM_MODE_PRIMAL, X, BX, PETSC_FALSE));
    564:   }
    565:   PetscFunctionReturn(PETSC_SUCCESS);
    566: }

    568: static PetscErrorCode MatSolve_LMVMSymBrdn_CompactDense(Mat B, Vec X, Vec HX)
    569: {
    570:   Mat_LMVM    *lmvm = (Mat_LMVM *)B->data;
    571:   Mat_SymBrdn *lsb  = (Mat_SymBrdn *)lmvm->ctx;

    573:   PetscFunctionBegin;
    574:   PetscCheck(lsb->phi_scalar != PETSC_DETERMINE, PetscObjectComm((PetscObject)B), PETSC_ERR_ARG_WRONGSTATE, "Phi must first be set using MatLMVMSymBroydenSetPhi()");
    575:   if (lsb->phi_scalar == 0.0) {
    576:     PetscCall(DFPKernel_CompactDense(B, MATLMVM_MODE_DUAL, X, HX));
    577:   } else if (lsb->phi_scalar == 1.0) {
    578:     PetscCall(BFGSKernel_CompactDense(B, MATLMVM_MODE_DUAL, X, HX));
    579:   } else {
    580:     PetscCall(SymBroydenKernel_CompactDense(B, MATLMVM_MODE_DUAL, X, HX, PETSC_TRUE));
    581:   }
    582:   PetscFunctionReturn(PETSC_SUCCESS);
    583: }

    585: static PetscErrorCode MatUpdate_LMVMSymBrdn(Mat B, Vec X, Vec F)
    586: {
    587:   Mat_LMVM        *lmvm = (Mat_LMVM *)B->data;
    588:   Mat_SymBrdn     *lsb  = (Mat_SymBrdn *)lmvm->ctx;
    589:   PetscReal        curvtol;
    590:   PetscScalar      curvature, ststmp;
    591:   PetscInt         oldest, next;
    592:   PetscBool        cache_StFprev   = (lmvm->mult_alg != MAT_LMVM_MULT_RECURSIVE) ? lmvm->cache_gradient_products : PETSC_FALSE;
    593:   PetscBool        cache_YtH0Fprev = cache_StFprev;
    594:   LMBasis          S = NULL, H0Y = NULL;
    595:   PetscScalar      H0_alpha = 1.0;
    596:   MatLMVMBasisType H0Y_t    = LMBASIS_H0Y;

    598:   PetscFunctionBegin;
    599:   if (!lmvm->m) PetscFunctionReturn(PETSC_SUCCESS);
    600:   // BFGS using the dense algorithm does not need to cache YtH0F products
    601:   if (lsb->phi_scalar == 0.0 && lmvm->mult_alg == MAT_LMVM_MULT_DENSE) cache_YtH0Fprev = PETSC_FALSE;
    602:   // Caching is no use if we are diagonally updating
    603:   if (lsb->rescale->scale_type == MAT_LMVM_SYMBROYDEN_SCALE_DIAGONAL) cache_YtH0Fprev = PETSC_FALSE;
    604:   PetscCall(MatLMVMGetRange(B, &oldest, &next));
    605:   if (lmvm->prev_set) {
    606:     LMBasis Y         = NULL;
    607:     Vec     Fprev_old = NULL;

    609:     if (cache_StFprev || cache_YtH0Fprev) {
    610:       PetscCall(MatLMVMGetUpdatedBasis(B, LMBASIS_Y, &Y, NULL, NULL));
    611:       PetscCall(LMBasisGetWorkVec(Y, &Fprev_old));
    612:       PetscCall(VecCopy(lmvm->Fprev, Fprev_old));
    613:     }

    615:     /* Compute the new (S = X - Xprev) and (Y = F - Fprev) vectors */
    616:     PetscCall(VecAYPX(lmvm->Xprev, -1.0, X));
    617:     PetscCall(VecAYPX(lmvm->Fprev, -1.0, F));

    619:     /* Test if the updates can be accepted */
    620:     {
    621:       Vec         sy[2] = {lmvm->Xprev, lmvm->Fprev};
    622:       PetscScalar stsy[2];

    624:       PetscCall(VecMDot(lmvm->Xprev, 2, sy, stsy));
    625:       ststmp    = stsy[0];
    626:       curvature = stsy[1];
    627:     }
    628:     curvtol = lmvm->eps * PetscRealPart(ststmp);

    630:     if (PetscRealPart(curvature) > curvtol) { /* Update is good, accept it */
    631:       LMProducts StY           = NULL;
    632:       LMProducts YtH0Y         = NULL;
    633:       Vec        StFprev_old   = NULL;
    634:       Vec        YtH0Fprev_old = NULL;
    635:       PetscInt   oldest_new, next_new;

    637:       lsb->watchdog = 0;
    638:       if (cache_StFprev) {
    639:         PetscCall(MatLMVMGetUpdatedBasis(B, LMBASIS_S, &S, NULL, NULL));
    640:         if (!lsb->StFprev) PetscCall(LMBasisCreateRow(S, &lsb->StFprev));
    641:         PetscCall(MatLMVMGetUpdatedProducts(B, LMBASIS_S, LMBASIS_Y, LMBLOCK_UPPER_TRIANGLE, &StY));
    642:         PetscCall(LMProductsGetNextColumn(StY, &StFprev_old));
    643:         PetscCall(VecCopy(lsb->StFprev, StFprev_old));
    644:       }
    645:       if (cache_YtH0Fprev) {
    646:         PetscCall(MatLMVMGetUpdatedBasis(B, LMBASIS_H0Y, &H0Y, &H0Y_t, &H0_alpha));
    647:         if (!lsb->YtH0Fprev) PetscCall(LMBasisCreateRow(H0Y, &lsb->YtH0Fprev));
    648:         PetscCall(MatLMVMGetUpdatedProducts(B, LMBASIS_Y, H0Y_t, LMBLOCK_UPPER_TRIANGLE, &YtH0Y));
    649:         PetscCall(LMProductsGetNextColumn(YtH0Y, &YtH0Fprev_old));
    650:         if (lsb->YtH0Fprev == H0Y->cached_product) {
    651:           PetscCall(VecCopy(lsb->YtH0Fprev, YtH0Fprev_old));
    652:         } else {
    653:           if (next > oldest) {
    654:             // need to recalculate
    655:             PetscCall(LMBasisGEMVH(H0Y, oldest, next, 1.0, Fprev_old, 0.0, YtH0Fprev_old));
    656:           } else {
    657:             PetscCall(VecZeroEntries(YtH0Fprev_old));
    658:           }
    659:         }
    660:       }

    662:       PetscCall(MatUpdateKernel_LMVM(B, lmvm->Xprev, lmvm->Fprev));
    663:       PetscCall(MatLMVMGetRange(B, &oldest_new, &next_new));
    664:       if (cache_StFprev) {
    665:         // compute the one new s_i^T F_old value
    666:         PetscCall(LMBasisGEMVH(S, next, next_new, 1.0, Fprev_old, 0.0, StFprev_old));
    667:         PetscCall(LMBasisGEMVH(S, oldest_new, next_new, 1.0, F, 0.0, lsb->StFprev));
    668:         PetscCall(LMBasisSetCachedProduct(S, F, lsb->StFprev));
    669:         PetscCall(VecAXPBY(StFprev_old, 1.0, -1.0, lsb->StFprev));
    670:         PetscCall(LMProductsRestoreNextColumn(StY, &StFprev_old));
    671:       }
    672:       if (cache_YtH0Fprev) {
    673:         PetscCall(MatLMVMGetUpdatedBasis(B, LMBASIS_H0Y, &H0Y, &H0Y_t, &H0_alpha));
    674:         // compute the one new (H_0 y_i)^T F_old value
    675:         PetscCall(LMBasisGEMVH(H0Y, next, next_new, 1.0, Fprev_old, 0.0, YtH0Fprev_old));
    676:         PetscCall(LMBasisGEMVH(H0Y, oldest_new, next_new, 1.0, F, 0.0, lsb->YtH0Fprev));
    677:         PetscCall(LMBasisSetCachedProduct(H0Y, F, lsb->YtH0Fprev));
    678:         PetscCall(VecAXPBY(YtH0Fprev_old, 1.0, -1.0, lsb->YtH0Fprev));
    679:         PetscCall(LMProductsRestoreNextColumn(YtH0Y, &YtH0Fprev_old));
    680:       }

    682:       PetscCall(MatLMVMProductsInsertDiagonalValue(B, LMBASIS_Y, LMBASIS_S, next, PetscRealPart(curvature)));
    683:       PetscCall(MatLMVMProductsInsertDiagonalValue(B, LMBASIS_S, LMBASIS_Y, next, PetscRealPart(curvature)));
    684:       PetscCall(MatLMVMProductsInsertDiagonalValue(B, LMBASIS_S, LMBASIS_S, next, ststmp));
    685:       PetscCall(SymBroydenRescaleUpdate(B, lsb->rescale));
    686:     } else {
    687:       /* Update is bad, skip it */
    688:       PetscCall(PetscInfo(B, "Rejecting update: curvature %g, ||s||^2 %g\n", (double)PetscRealPart(curvature), (double)PetscRealPart(ststmp)));
    689:       lmvm->nrejects++;
    690:       lsb->watchdog++;
    691:       if (cache_StFprev) {
    692:         // we still need to update the cached product
    693:         PetscCall(MatLMVMGetUpdatedBasis(B, LMBASIS_S, &S, NULL, NULL));
    694:         PetscCall(LMBasisGEMVH(S, oldest, next, 1.0, F, 0.0, lsb->StFprev));
    695:         PetscCall(LMBasisSetCachedProduct(S, F, lsb->StFprev));
    696:       }
    697:       if (cache_YtH0Fprev) {
    698:         // we still need to update the cached product
    699:         PetscCall(MatLMVMGetUpdatedBasis(B, LMBASIS_H0Y, &H0Y, &H0Y_t, &H0_alpha));
    700:         PetscCall(LMBasisGEMVH(H0Y, oldest, next, 1.0, F, 0.0, lsb->YtH0Fprev));
    701:         PetscCall(LMBasisSetCachedProduct(H0Y, F, lsb->StFprev));
    702:       }
    703:     }
    704:     if (cache_StFprev || cache_YtH0Fprev) PetscCall(LMBasisRestoreWorkVec(Y, &Fprev_old));
    705:   } else {
    706:     if (cache_StFprev) {
    707:       PetscCall(MatLMVMGetUpdatedBasis(B, LMBASIS_S, &S, NULL, NULL));
    708:       if (!lsb->StFprev) PetscCall(LMBasisCreateRow(S, &lsb->StFprev));
    709:     }
    710:     if (cache_YtH0Fprev) {
    711:       MatLMVMBasisType H0Y_t;
    712:       PetscScalar      H0_alpha;

    714:       PetscCall(MatLMVMGetUpdatedBasis(B, LMBASIS_H0Y, &H0Y, &H0Y_t, &H0_alpha));
    715:       if (!lsb->YtH0Fprev) PetscCall(LMBasisCreateRow(H0Y, &lsb->YtH0Fprev));
    716:     }
    717:   }

    719:   if (lsb->watchdog > lsb->max_seq_rejects) PetscCall(MatLMVMReset(B, PETSC_FALSE));

    721:   /* Save the solution and function to be used in the next update */
    722:   PetscCall(VecCopy(X, lmvm->Xprev));
    723:   PetscCall(VecCopy(F, lmvm->Fprev));
    724:   lmvm->prev_set = PETSC_TRUE;
    725:   PetscFunctionReturn(PETSC_SUCCESS);
    726: }

    728: static PetscErrorCode MatCopy_LMVMSymBrdn(Mat B, Mat M, MatStructure str)
    729: {
    730:   Mat_LMVM    *bdata = (Mat_LMVM *)B->data;
    731:   Mat_SymBrdn *blsb  = (Mat_SymBrdn *)bdata->ctx;
    732:   Mat_LMVM    *mdata = (Mat_LMVM *)M->data;
    733:   Mat_SymBrdn *mlsb  = (Mat_SymBrdn *)mdata->ctx;

    735:   PetscFunctionBegin;
    736:   mlsb->phi_scalar      = blsb->phi_scalar;
    737:   mlsb->psi_scalar      = blsb->psi_scalar;
    738:   mlsb->watchdog        = blsb->watchdog;
    739:   mlsb->max_seq_rejects = blsb->max_seq_rejects;
    740:   PetscCall(SymBroydenRescaleCopy(blsb->rescale, mlsb->rescale));
    741:   PetscFunctionReturn(PETSC_SUCCESS);
    742: }

    744: static PetscErrorCode MatReset_LMVMSymBrdn_Internal(Mat B, MatLMVMResetMode mode)
    745: {
    746:   Mat_LMVM    *lmvm = (Mat_LMVM *)B->data;
    747:   Mat_SymBrdn *lsb  = (Mat_SymBrdn *)lmvm->ctx;

    749:   PetscFunctionBegin;
    750:   if (MatLMVMResetClearsBases(mode)) {
    751:     for (PetscInt i = 0; i < SYMBROYDEN_BASIS_COUNT; i++) PetscCall(LMBasisDestroy(&lsb->basis[i]));
    752:     for (PetscInt i = 0; i < SYMBROYDEN_PRODUCTS_COUNT; i++) PetscCall(LMProductsDestroy(&lsb->products[i]));
    753:     PetscCall(VecDestroy(&lsb->StFprev));
    754:     PetscCall(VecDestroy(&lsb->YtH0Fprev));
    755:   } else {
    756:     for (PetscInt i = 0; i < SYMBROYDEN_BASIS_COUNT; i++) PetscCall(LMBasisReset(lsb->basis[i]));
    757:     for (PetscInt i = 0; i < SYMBROYDEN_PRODUCTS_COUNT; i++) PetscCall(LMProductsReset(lsb->products[i]));
    758:     if (lsb->StFprev) PetscCall(VecZeroEntries(lsb->StFprev));
    759:     if (lsb->YtH0Fprev) PetscCall(VecZeroEntries(lsb->YtH0Fprev));
    760:   }
    761:   PetscFunctionReturn(PETSC_SUCCESS);
    762: }

    764: static PetscErrorCode MatReset_LMVMSymBrdn(Mat B, MatLMVMResetMode mode)
    765: {
    766:   Mat_LMVM    *lmvm = (Mat_LMVM *)B->data;
    767:   Mat_SymBrdn *lsb  = (Mat_SymBrdn *)lmvm->ctx;

    769:   PetscFunctionBegin;
    770:   lsb->watchdog = 0;
    771:   PetscCall(SymBroydenRescaleReset(B, lsb->rescale, mode));
    772:   PetscCall(MatReset_LMVMSymBrdn_Internal(B, mode));
    773:   PetscFunctionReturn(PETSC_SUCCESS);
    774: }

    776: static PetscErrorCode MatDestroy_LMVMSymBrdn(Mat B)
    777: {
    778:   Mat_LMVM    *lmvm = (Mat_LMVM *)B->data;
    779:   Mat_SymBrdn *lsb  = (Mat_SymBrdn *)lmvm->ctx;

    781:   PetscFunctionBegin;
    782:   PetscCall(PetscObjectComposeFunction((PetscObject)B, "MatLMVMSymBroydenGetPhi_C", NULL));
    783:   PetscCall(PetscObjectComposeFunction((PetscObject)B, "MatLMVMSymBroydenSetPhi_C", NULL));
    784:   PetscCall(PetscObjectComposeFunction((PetscObject)B, "MatLMVMSymBadBroydenGetPsi_C", NULL));
    785:   PetscCall(PetscObjectComposeFunction((PetscObject)B, "MatLMVMSymBadBroydenSetPsi_C", NULL));
    786:   PetscCall(PetscObjectComposeFunction((PetscObject)B, "MatLMVMSymBroydenSetDelta_C", NULL));
    787:   PetscCall(SymBroydenRescaleDestroy(&lsb->rescale));
    788:   PetscCall(MatReset_LMVMSymBrdn_Internal(B, MAT_LMVM_RESET_ALL));
    789:   PetscCall(PetscFree(lmvm->ctx));
    790:   PetscCall(MatDestroy_LMVM(B));
    791:   PetscFunctionReturn(PETSC_SUCCESS);
    792: }

    794: static PetscErrorCode MatSetUp_LMVMSymBrdn(Mat B)
    795: {
    796:   Mat_LMVM    *lmvm = (Mat_LMVM *)B->data;
    797:   Mat_SymBrdn *lsb  = (Mat_SymBrdn *)lmvm->ctx;

    799:   PetscFunctionBegin;
    800:   PetscCall(MatSetUp_LMVM(B));
    801:   PetscCall(SymBroydenRescaleInitializeJ0(B, lsb->rescale));
    802:   PetscFunctionReturn(PETSC_SUCCESS);
    803: }

    805: static PetscErrorCode MatView_LMVMSymBrdn(Mat B, PetscViewer pv)
    806: {
    807:   Mat_LMVM    *lmvm = (Mat_LMVM *)B->data;
    808:   Mat_SymBrdn *lsb  = (Mat_SymBrdn *)lmvm->ctx;
    809:   PetscBool    isascii;

    811:   PetscFunctionBegin;
    812:   PetscCall(MatView_LMVM(B, pv));
    813:   PetscCall(PetscObjectTypeCompare((PetscObject)pv, PETSCVIEWERASCII, &isascii));
    814:   if (isascii) {
    815:     PetscBool is_other;

    817:     PetscCall(PetscObjectTypeCompareAny((PetscObject)B, &is_other, MATLMVMBFGS, MATLMVMDFP, ""));
    818:     if (!is_other) {
    819:       if (lsb->phi_scalar != PETSC_DETERMINE) PetscCall(PetscViewerASCIIPrintf(pv, "Convex factor phi = %g\n", (double)lsb->phi_scalar));
    820:       if (lsb->psi_scalar != PETSC_DETERMINE) PetscCall(PetscViewerASCIIPrintf(pv, "Dual convex factor psi = %g\n", (double)lsb->psi_scalar));
    821:     }
    822:   }
    823:   PetscCall(SymBroydenRescaleView(lsb->rescale, pv));
    824:   PetscFunctionReturn(PETSC_SUCCESS);
    825: }

    827: static PetscErrorCode MatLMVMSetMultAlgorithm_SymBrdn(Mat B)
    828: {
    829:   Mat_LMVM *lmvm = (Mat_LMVM *)B->data;

    831:   PetscFunctionBegin;
    832:   switch (lmvm->mult_alg) {
    833:   case MAT_LMVM_MULT_RECURSIVE:
    834:     lmvm->ops->mult  = MatMult_LMVMSymBrdn_Recursive;
    835:     lmvm->ops->solve = MatSolve_LMVMSymBrdn_Recursive;
    836:     break;
    837:   case MAT_LMVM_MULT_DENSE:
    838:   case MAT_LMVM_MULT_COMPACT_DENSE:
    839:     lmvm->ops->mult  = MatMult_LMVMSymBrdn_CompactDense;
    840:     lmvm->ops->solve = MatSolve_LMVMSymBrdn_CompactDense;
    841:     break;
    842:   }
    843:   lmvm->ops->multht  = lmvm->ops->mult;
    844:   lmvm->ops->solveht = lmvm->ops->solve;
    845:   PetscFunctionReturn(PETSC_SUCCESS);
    846: }

    848: static PetscErrorCode MatSetFromOptions_LMVMSymBrdn(Mat B, PetscOptionItems PetscOptionsObject)
    849: {
    850:   Mat_LMVM    *lmvm = (Mat_LMVM *)B->data;
    851:   Mat_SymBrdn *lsb  = (Mat_SymBrdn *)lmvm->ctx;

    853:   PetscFunctionBegin;
    854:   PetscCall(MatSetFromOptions_LMVM(B, PetscOptionsObject));
    855:   PetscOptionsHeadBegin(PetscOptionsObject, "Restricted/Symmetric Broyden method for approximating SPD Jacobian actions (MATLMVMSYMBRDN)");
    856:   PetscCall(PetscOptionsReal("-mat_lmvm_phi", "convex ratio between BFGS and DFP components of the update", "", lsb->phi_scalar, &lsb->phi_scalar, NULL));
    857:   PetscCheck(lsb->phi_scalar >= 0.0 && lsb->phi_scalar <= 1.0, PetscObjectComm((PetscObject)B), PETSC_ERR_ARG_OUTOFRANGE, "convex ratio for the update formula cannot be outside the range of [0, 1]");
    858:   PetscCall(SymBroydenRescaleSetFromOptions(B, lsb->rescale, PetscOptionsObject));
    859:   PetscOptionsHeadEnd();
    860:   PetscFunctionReturn(PETSC_SUCCESS);
    861: }

    863: /*@
    864:   MatLMVMSymBroydenGetPhi - Get the phi parameter for a Broyden class quasi-Newton update matrix

    866:   Input Parameter:
    867: . B - The matrix

    869:   Output Parameter:
    870: . phi - a number defining an update that is an affine combination of the BFGS update (phi = 0) and DFP update (phi = 1)

    872:   Level: advanced

    874:   Note:
    875:   If `B` does not have a constant value of `phi` for all iterations this will
    876:   return `phi` = `PETSC_DETERMINE` = -1, a negative value that `phi` cannot
    877:   attain for a valid general Broyden update.
    878:   This is the case if `B` is a `MATLMVMSYMBADBROYDEN`, where `phi`'s dual value
    879:   `psi` is constant and `phi` changes from iteration to iteration.

    881: .seealso: [](ch_ksp),
    882:           `MATLMVMSYMBROYDEN`, `MATLMVMSYMBADBROYDEN`,
    883:           `MATLMVMDFP`, `MATLMVMBFGS`,
    884:           `MatLMVMSymBroydenSetPhi()`,
    885:           `MatLMVMSymBadBroydenGetPsi()`, `MatLMVMSymBadBroydenSetPsi()`
    886: @*/
    887: PetscErrorCode MatLMVMSymBroydenGetPhi(Mat B, PetscReal *phi)
    888: {
    889:   PetscFunctionBegin;
    890:   *phi = PETSC_DETERMINE;
    891:   PetscUseMethod(B, "MatLMVMSymBroydenGetPhi_C", (Mat, PetscReal *), (B, phi));
    892:   PetscFunctionReturn(PETSC_SUCCESS);
    893: }

    895: static PetscErrorCode MatLMVMSymBroydenGetPhi_SymBrdn(Mat B, PetscReal *phi)
    896: {
    897:   Mat_LMVM    *lmvm = (Mat_LMVM *)B->data;
    898:   Mat_SymBrdn *lsb  = (Mat_SymBrdn *)lmvm->ctx;

    900:   PetscFunctionBegin;
    901:   *phi = lsb->phi_scalar;
    902:   PetscFunctionReturn(PETSC_SUCCESS);
    903: }

    905: /*@
    906:   MatLMVMSymBroydenSetPhi - Get the phi parameter for a Broyden class quasi-Newton update matrix

    908:   Input Parameters:
    909: + B   - The matrix
    910: - phi - a number defining an update that is a convex combination of the BFGS update (phi = 0) and DFP update (phi = 1)

    912:   Level: advanced

    914:   Note:
    915:   If `B` cannot have a constant value of `phi` for all iterations this will be ignored.
    916:   This is the case if `B` is a `MATLMVMSYMBADBROYDEN`, where `phi`'s dual value
    917:   `psi` is constant and `phi` changes from iteration to iteration.

    919: .seealso: [](ch_ksp),
    920:           `MATLMVMSYMBROYDEN`, `MATLMVMSYMBADBROYDEN`,
    921:           `MATLMVMDFP`, `MATLMVMBFGS`,
    922:           `MatLMVMSymBroydenGetPhi()`,
    923:           `MatLMVMSymBadBroydenGetPsi()`, `MatLMVMSymBadBroydenSetPsi()`
    924: @*/
    925: PetscErrorCode MatLMVMSymBroydenSetPhi(Mat B, PetscReal phi)
    926: {
    927:   PetscFunctionBegin;
    928:   PetscTryMethod(B, "MatLMVMSymBroydenSetPhi_C", (Mat, PetscReal), (B, phi));
    929:   PetscFunctionReturn(PETSC_SUCCESS);
    930: }

    932: static PetscErrorCode MatLMVMSymBroydenSetPhi_SymBrdn(Mat B, PetscReal phi)
    933: {
    934:   Mat_LMVM    *lmvm = (Mat_LMVM *)B->data;
    935:   Mat_SymBrdn *lsb  = (Mat_SymBrdn *)lmvm->ctx;

    937:   PetscFunctionBegin;
    938:   lsb->phi_scalar = phi;
    939:   PetscFunctionReturn(PETSC_SUCCESS);
    940: }

    942: /*@
    943:   MatLMVMSymBadBroydenGetPsi - Get the psi parameter for a Broyden class quasi-Newton update matrix

    945:   Input Parameter:
    946: . B - The matrix

    948:   Output Parameter:
    949: . psi - a number defining an update that is an affine combination of the BFGS update (psi = 1) and DFP update (psi = 0)

    951:   Level: advanced

    953:   Note:
    954:   If B does not have a constant value of `psi` for all iterations this  will
    955:   return `psi` = `PETSC_DETERMINE` = -1, a negative value that `psi` cannot
    956:   attain for a valid general Broyden update.
    957:   This is the case if `B` is a `MATLMVMSYMBROYDEN`, where `psi`'s dual value
    958:   `phi` is constant and `psi` changes from iteration to iteration.

    960: .seealso: [](ch_ksp),
    961:           `MATLMVMSYMBROYDEN`, `MATLMVMSYMBADBROYDEN`,
    962:           `MATLMVMDFP`, `MATLMVMBFGS`,
    963:           `MatLMVMSymBadBroydenSetPsi()`,
    964:           `MatLMVMSymBroydenGetPhi()`, `MatLMVMSymBroydenSetPhi()`
    965: @*/
    966: PetscErrorCode MatLMVMSymBadBroydenGetPsi(Mat B, PetscReal *psi)
    967: {
    968:   PetscFunctionBegin;
    969:   *psi = PETSC_DETERMINE;
    970:   PetscTryMethod(B, "MatLMVMSymBadBroydenGetPsi_C", (Mat, PetscReal *), (B, psi));
    971:   PetscFunctionReturn(PETSC_SUCCESS);
    972: }

    974: static PetscErrorCode MatLMVMSymBadBroydenGetPsi_SymBrdn(Mat B, PetscReal *psi)
    975: {
    976:   Mat_LMVM    *lmvm = (Mat_LMVM *)B->data;
    977:   Mat_SymBrdn *lsb  = (Mat_SymBrdn *)lmvm->ctx;

    979:   PetscFunctionBegin;
    980:   *psi = lsb->psi_scalar;
    981:   PetscFunctionReturn(PETSC_SUCCESS);
    982: }

    984: /*@
    985:   MatLMVMSymBadBroydenSetPsi - Get the psi parameter for a Broyden class quasi-Newton update matrix

    987:   Input Parameters:
    988: + B   - The matrix
    989: - psi - a number defining an update that is a convex combination of the BFGS update (psi = 1) and DFP update (psi = 0)

    991:   Level: developer

    993:   Note:
    994:   If `B` cannot have a constant value of `psi` for all iterations this will
    995:   be ignored.
    996:   This is the case if `B` is a `MATLMVMSYMBROYDEN`, where `psi`'s dual value
    997:   `phi` is constant and `psi` changes from iteration to iteration.

    999: .seealso: [](ch_ksp),
    1000:           `MATLMVMSYMBROYDEN`, `MATLMVMSYMBADBROYDEN`,
    1001:           `MATLMVMDFP`, `MATLMVMBFGS`,
    1002:           `MatLMVMSymBadBroydenGetPsi()`,
    1003:           `MatLMVMSymBroydenGetPhi()`, `MatLMVMSymBroydenSetPhi()`
    1004: @*/
    1005: PetscErrorCode MatLMVMSymBadBroydenSetPsi(Mat B, PetscReal psi)
    1006: {
    1007:   PetscFunctionBegin;
    1008:   PetscTryMethod(B, "MatLMVMSymBadBroydenSetPsi_C", (Mat, PetscReal), (B, psi));
    1009:   PetscFunctionReturn(PETSC_SUCCESS);
    1010: }

    1012: static PetscErrorCode MatLMVMSymBadBroydenSetPsi_SymBrdn(Mat B, PetscReal psi)
    1013: {
    1014:   Mat_LMVM    *lmvm = (Mat_LMVM *)B->data;
    1015:   Mat_SymBrdn *lsb  = (Mat_SymBrdn *)lmvm->ctx;

    1017:   PetscFunctionBegin;
    1018:   lsb->psi_scalar = psi;
    1019:   PetscFunctionReturn(PETSC_SUCCESS);
    1020: }

    1022: static PetscErrorCode MatLMVMSymBroydenSetDelta_SymBrdn(Mat B, PetscScalar delta)
    1023: {
    1024:   Mat_LMVM    *lmvm = (Mat_LMVM *)B->data;
    1025:   Mat_SymBrdn *lsb  = (Mat_SymBrdn *)lmvm->ctx;

    1027:   PetscFunctionBegin;
    1028:   PetscCall(SymBroydenRescaleSetDelta(B, lsb->rescale, PetscAbsReal(PetscRealPart(delta))));
    1029:   PetscFunctionReturn(PETSC_SUCCESS);
    1030: }

    1032: PetscErrorCode MatCreate_LMVMSymBrdn(Mat B)
    1033: {
    1034:   Mat_LMVM    *lmvm;
    1035:   Mat_SymBrdn *lsb;

    1037:   PetscFunctionBegin;
    1038:   PetscCall(MatCreate_LMVM(B));
    1039:   PetscCall(PetscObjectChangeTypeName((PetscObject)B, MATLMVMSYMBROYDEN));
    1040:   PetscCall(MatSetOption(B, MAT_HERMITIAN, PETSC_TRUE));
    1041:   PetscCall(MatSetOption(B, MAT_SPD, PETSC_TRUE)); // TODO: change to HPD when available
    1042:   PetscCall(MatSetOption(B, MAT_SPD_ETERNAL, PETSC_TRUE));
    1043:   B->ops->view           = MatView_LMVMSymBrdn;
    1044:   B->ops->setfromoptions = MatSetFromOptions_LMVMSymBrdn;
    1045:   B->ops->setup          = MatSetUp_LMVMSymBrdn;
    1046:   B->ops->destroy        = MatDestroy_LMVMSymBrdn;

    1048:   lmvm                          = (Mat_LMVM *)B->data;
    1049:   lmvm->ops->reset              = MatReset_LMVMSymBrdn;
    1050:   lmvm->ops->update             = MatUpdate_LMVMSymBrdn;
    1051:   lmvm->ops->copy               = MatCopy_LMVMSymBrdn;
    1052:   lmvm->ops->setmultalgorithm   = MatLMVMSetMultAlgorithm_SymBrdn;
    1053:   lmvm->cache_gradient_products = PETSC_TRUE;
    1054:   PetscCall(MatLMVMSetMultAlgorithm_SymBrdn(B));

    1056:   PetscCall(PetscNew(&lsb));
    1057:   lmvm->ctx            = (void *)lsb;
    1058:   lsb->phi_scalar      = 0.125;
    1059:   lsb->psi_scalar      = PETSC_DETERMINE;
    1060:   lsb->watchdog        = 0;
    1061:   lsb->max_seq_rejects = lmvm->m / 2;

    1063:   PetscCall(SymBroydenRescaleCreate(&lsb->rescale));
    1064:   lsb->rescale->theta = lsb->phi_scalar;
    1065:   PetscCall(PetscObjectComposeFunction((PetscObject)B, "MatLMVMSymBroydenGetPhi_C", MatLMVMSymBroydenGetPhi_SymBrdn));
    1066:   PetscCall(PetscObjectComposeFunction((PetscObject)B, "MatLMVMSymBroydenSetPhi_C", MatLMVMSymBroydenSetPhi_SymBrdn));
    1067:   PetscCall(PetscObjectComposeFunction((PetscObject)B, "MatLMVMSymBadBroydenGetPsi_C", MatLMVMSymBadBroydenGetPsi_SymBrdn));
    1068:   PetscCall(PetscObjectComposeFunction((PetscObject)B, "MatLMVMSymBadBroydenSetPsi_C", MatLMVMSymBadBroydenSetPsi_SymBrdn));
    1069:   PetscCall(PetscObjectComposeFunction((PetscObject)B, "MatLMVMSymBroydenSetDelta_C", MatLMVMSymBroydenSetDelta_SymBrdn));
    1070:   PetscFunctionReturn(PETSC_SUCCESS);
    1071: }

    1073: /*@
    1074:   MatLMVMSymBroydenSetDelta - Sets the starting value for the diagonal scaling vector computed
    1075:   in the SymBrdn approximations (also works for BFGS and DFP).

    1077:   Input Parameters:
    1078: + B     - `MATLMVM` matrix
    1079: - delta - initial value for diagonal scaling

    1081:   Level: intermediate

    1083: .seealso: [](ch_ksp), `MATLMVMSYMBROYDEN`
    1084: @*/
    1085: PetscErrorCode MatLMVMSymBroydenSetDelta(Mat B, PetscScalar delta)
    1086: {
    1087:   PetscFunctionBegin;
    1089:   PetscTryMethod(B, "MatLMVMSymBroydenSetDelta_C", (Mat, PetscScalar), (B, delta));
    1090:   PetscFunctionReturn(PETSC_SUCCESS);
    1091: }

    1093: /*@
    1094:   MatLMVMSymBroydenSetScaleType - Sets the scale type for symmetric Broyden-type updates.

    1096:   Input Parameters:
    1097: + B     - the `MATLMVM` matrix
    1098: - stype - scale type, see `MatLMVMSymBroydenScaleType`

    1100:   Options Database Key:
    1101: . -mat_lmvm_scale_type <none,scalar,diagonal> - set the scaling type

    1103:   Level: intermediate

    1105:   MatLMVMSymBrdnScaleTypes\:
    1106: +   `MAT_LMVM_SYMBROYDEN_SCALE_NONE`     - use whatever initial Hessian is already there (will be the identity if the user does nothing)
    1107: .   `MAT_LMVM_SYMBROYDEN_SCALE_SCALAR`   - use the Shanno scalar as the initial Hessian
    1108: .   `MAT_LMVM_SYMBROYDEN_SCALE_DIAGONAL` - use a diagonalized BFGS update as the initial Hessian
    1109: .   `MAT_LMVM_SYMBROYDEN_SCALE_USER`     - same as `MAT_LMVM_SYMBROYDEN_NONE`
    1110: -   `MAT_LMVM_SYMBROYDEN_SCALE_DECIDE`   - let PETSc decide

    1112: .seealso: [](ch_ksp), `MATLMVMSYMBROYDEN`, `MatCreateLMVMSymBroyden()`, `MatLMVMSymBroydenScaleType`
    1113: @*/
    1114: PetscErrorCode MatLMVMSymBroydenSetScaleType(Mat B, MatLMVMSymBroydenScaleType stype)
    1115: {
    1116:   Mat_LMVM    *lmvm = (Mat_LMVM *)B->data;
    1117:   Mat_SymBrdn *lsb  = (Mat_SymBrdn *)lmvm->ctx;

    1119:   PetscFunctionBegin;
    1121:   PetscCall(SymBroydenRescaleSetType(lsb->rescale, stype));
    1122:   PetscFunctionReturn(PETSC_SUCCESS);
    1123: }

    1125: /*@
    1126:   MatCreateLMVMSymBroyden - Creates a limited-memory Symmetric Broyden-type matrix used
    1127:   for approximating Jacobians.

    1129:   Collective

    1131:   Input Parameters:
    1132: + comm - MPI communicator, set to `PETSC_COMM_SELF`
    1133: . n    - number of local rows for storage vectors
    1134: - N    - global size of the storage vectors

    1136:   Output Parameter:
    1137: . B - the matrix

    1139:   Options Database Keys:
    1140: + -mat_lmvm_hist_size         - the number of history vectors to keep
    1141: . -mat_lmvm_phi               - convex ratio between BFGS and DFP components of the update
    1142: . -mat_lmvm_scale_type        - type of scaling applied to J0 (none, scalar, diagonal)
    1143: . -mat_lmvm_mult_algorithm    - the algorithm to use for multiplication (recursive, dense, compact_dense)
    1144: . -mat_lmvm_cache_J0_products - whether products between the base Jacobian J0 and history vectors should be cached or recomputed
    1145: . -mat_lmvm_eps               - (developer) numerical zero tolerance for testing when an update should be skipped
    1146: . -mat_lmvm_debug             - (developer) perform internal debugging checks
    1147: . -mat_lmvm_theta             - (developer) convex ratio between BFGS and DFP components of the diagonal J0 scaling
    1148: . -mat_lmvm_rho               - (developer) update limiter for the J0 scaling
    1149: . -mat_lmvm_alpha             - (developer) coefficient factor for the quadratic subproblem in J0 scaling
    1150: . -mat_lmvm_beta              - (developer) exponential factor for the diagonal J0 scaling
    1151: - -mat_lmvm_sigma_hist        - (developer) number of past updates to use in J0 scaling

    1153:   Level: intermediate

    1155:   Notes:
    1156:   It is recommended that one use the `MatCreate()`, `MatSetType()` and/or `MatSetFromOptions()` paradigm instead of this
    1157:   routine directly.

    1159:   L-SymBrdn is a convex combination of L-DFP and L-BFGS such that $B = (1 - \phi)B_{\text{BFGS}} + \phi B_{\text{DFP}}$.
    1160:   The combination factor $\phi$ is restricted to the range $[0, 1]$, where the L-SymBrdn matrix is guaranteed to be
    1161:   symmetric positive-definite.

    1163:   To use the L-SymBrdn matrix with other vector types, the matrix must be created using `MatCreate()` and `MatSetType()`,
    1164:   followed by `MatLMVMAllocate()`.  This ensures that the internal storage and work vectors are duplicated from the
    1165:   correct type of vector.

    1167: .seealso: [](ch_ksp), `MatCreate()`, `MATLMVM`, `MATLMVMSYMBROYDEN`, `MatCreateLMVMDFP()`, `MatCreateLMVMSR1()`,
    1168:           `MatCreateLMVMBFGS()`, `MatCreateLMVMBroyden()`, `MatCreateLMVMBadBroyden()`
    1169: @*/
    1170: PetscErrorCode MatCreateLMVMSymBroyden(MPI_Comm comm, PetscInt n, PetscInt N, Mat *B)
    1171: {
    1172:   PetscFunctionBegin;
    1173:   PetscCall(KSPInitializePackage());
    1174:   PetscCall(MatCreate(comm, B));
    1175:   PetscCall(MatSetSizes(*B, n, n, N, N));
    1176:   PetscCall(MatSetType(*B, MATLMVMSYMBROYDEN));
    1177:   PetscCall(MatSetUp(*B));
    1178:   PetscFunctionReturn(PETSC_SUCCESS);
    1179: }