Date: 2023-11-27T17:19:32+00:00

Actual source code: dlaed3m.c
slepc-3.20.1 2023-11-27
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      1: /*
      2:    - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
      3:    SLEPc - Scalable Library for Eigenvalue Problem Computations
      4:    Copyright (c) 2002-, Universitat Politecnica de Valencia, Spain

      6:    This file is part of SLEPc.
      7:    SLEPc is distributed under a 2-clause BSD license (see LICENSE).
      8:    - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
      9: */
     10: /*
     11:    BDC - Block-divide and conquer (see description in README file)
     12: */

     14: #include <slepc/private/dsimpl.h>
     15: #include <slepcblaslapack.h>

     17: PetscErrorCode BDC_dlaed3m_(const char *jobz,const char *defl,PetscBLASInt k,PetscBLASInt n,
     18:         PetscBLASInt n1,PetscReal *d,PetscReal *q,PetscBLASInt ldq,
     19:         PetscReal rho,PetscReal *dlamda,PetscReal *q2,PetscBLASInt *indx,
     20:         PetscBLASInt *ctot,PetscReal *w,PetscReal *s,PetscBLASInt *info,
     21:         PetscBLASInt jobz_len,PetscBLASInt defl_len)
     22: {
     23: /*  -- Routine written in LAPACK version 3.0 style -- */
     24: /* *************************************************** */
     25: /*     Written by */
     26: /*     Michael Moldaschl and Wilfried Gansterer */
     27: /*     University of Vienna */
     28: /*     last modification: March 16, 2014 */

     30: /*     Small adaptations of original code written by */
     31: /*     Wilfried Gansterer and Bob Ward, */
     32: /*     Department of Computer Science, University of Tennessee */
     33: /*     see https://doi.org/10.1137/S1064827501399432 */
     34: /* *************************************************** */

     36: /*  Purpose */
     37: /*  ======= */

     39: /*  DLAED3M finds the roots of the secular equation, as defined by the */
     40: /*  values in D, W, and RHO, between 1 and K.  It makes the */
     41: /*  appropriate calls to DLAED4 and then updates the eigenvectors by */
     42: /*  multiplying the matrix of eigenvectors of the pair of eigensystems */
     43: /*  being combined by the matrix of eigenvectors of the K-by-K system */
     44: /*  which is solved here. */

     46: /*  This code makes very mild assumptions about floating point */
     47: /*  arithmetic. It will work on machines with a guard digit in */
     48: /*  add/subtract, or on those binary machines without guard digits */
     49: /*  which subtract like the Cray X-MP, Cray Y-MP, Cray C-90, or Cray-2. */
     50: /*  It could conceivably fail on hexadecimal or decimal machines */
     51: /*  without guard digits, but we know of none. */

     53: /*  Arguments */
     54: /*  ========= */

     56: /*  JOBZ    (input) CHARACTER*1 */
     57: /*          = 'N':  Do not accumulate eigenvectors (not implemented); */
     58: /*          = 'D':  Do accumulate eigenvectors in the divide-and-conquer */
     59: /*                  process. */

     61: /*  DEFL    (input) CHARACTER*1 */
     62: /*          = '0':  No deflation happened in DSRTDF */
     63: /*          = '1':  Some deflation happened in DSRTDF (and therefore some */
     64: /*                  Givens rotations need to be applied to the computed */
     65: /*                  eigenvector matrix Q) */

     67: /*  K       (input) INTEGER */
     68: /*          The number of terms in the rational function to be solved by */
     69: /*          DLAED4. 0 <= K <= N. */

     71: /*  N       (input) INTEGER */
     72: /*          The number of rows and columns in the Q matrix. */
     73: /*          N >= K (deflation may result in N>K). */

     75: /*  N1      (input) INTEGER */
     76: /*          The location of the last eigenvalue in the leading submatrix. */
     77: /*          min(1,N) <= N1 <= max(1,N-1). */

     79: /*  D       (output) DOUBLE PRECISION array, dimension (N) */
     80: /*          D(I) contains the updated eigenvalues for */
     81: /*          1 <= I <= K. */

     83: /*  Q       (output) DOUBLE PRECISION array, dimension (LDQ,N) */
     84: /*          Initially the first K columns are used as workspace. */
     85: /*          On output the columns 1 to K contain */
     86: /*          the updated eigenvectors. */

     88: /*  LDQ     (input) INTEGER */
     89: /*          The leading dimension of the array Q.  LDQ >= max(1,N). */

     91: /*  RHO     (input) DOUBLE PRECISION */
     92: /*          The value of the parameter in the rank one update equation. */
     93: /*          RHO >= 0 required. */

     95: /*  DLAMDA  (input/output) DOUBLE PRECISION array, dimension (K) */
     96: /*          The first K elements of this array contain the old roots */
     97: /*          of the deflated updating problem.  These are the poles */
     98: /*          of the secular equation. May be changed on output by */
     99: /*          having lowest order bit set to zero on Cray X-MP, Cray Y-MP, */
    100: /*          Cray-2, or Cray C-90, as described above. */

    102: /*  Q2      (input) DOUBLE PRECISION array, dimension (LDQ2, N) */
    103: /*          The first K columns of this matrix contain the non-deflated */
    104: /*          eigenvectors for the split problem. */

    106: /*  INDX    (input) INTEGER array, dimension (N) */
    107: /*          The permutation used to arrange the columns of the deflated */
    108: /*          Q matrix into three groups (see DLAED2). */
    109: /*          The rows of the eigenvectors found by DLAED4 must be likewise */
    110: /*          permuted before the matrix multiply can take place. */

    112: /*  CTOT    (input) INTEGER array, dimension (4) */
    113: /*          A count of the total number of the various types of columns */
    114: /*          in Q, as described in INDX.  The fourth column type is any */
    115: /*          column which has been deflated. */

    117: /*  W       (input/output) DOUBLE PRECISION array, dimension (K) */
    118: /*          The first K elements of this array contain the components */
    119: /*          of the deflation-adjusted updating vector. Destroyed on */
    120: /*          output. */

    122: /*  S       (workspace) DOUBLE PRECISION array, dimension */
    123: /*          (MAX(CTOT(1)+CTOT(2),CTOT(2)+CTOT(3)) + 1)*K */
    124: /*          Will contain parts of the eigenvectors of the repaired matrix */
    125: /*          which will be multiplied by the previously accumulated */
    126: /*          eigenvectors to update the system. This array is a major */
    127: /*          source of workspace requirements ! */

    129: /*  INFO    (output) INTEGER */
    130: /*          = 0:  successful exit. */
    131: /*          < 0:  if INFO = -i, the i-th argument had an illegal value. */
    132: /*          > 0:  if INFO = i, eigenpair i was not computed successfully */

    134: /*  Further Details */
    135: /*  =============== */

    137: /*  Based on code written by */
    138: /*     Wilfried Gansterer and Bob Ward, */
    139: /*     Department of Computer Science, University of Tennessee */
    140: /*  Based on the design of the LAPACK code DLAED3 with small modifications */
    141: /*  (Note that in contrast to the original DLAED3, this routine */
    142: /*  DOES NOT require that N1 <= N/2) */

    144: /*  Based on contributions by */
    145: /*     Jeff Rutter, Computer Science Division, University of California */
    146: /*     at Berkeley, USA */
    147: /*  Modified by Francoise Tisseur, University of Tennessee. */

    149: /*  ===================================================================== */

    151:   PetscReal    temp, done = 1.0, dzero = 0.0;
    152:   PetscBLASInt i, j, n2, n12, ii, n23, iq2, i1, one=1;

    154:   PetscFunctionBegin;
    155:   *info = 0;

    157:   if (k < 0) *info = -3;
    158:   else if (n < k) *info = -4;
    159:   else if (n1 < PetscMin(1,n) || n1 > PetscMax(1,n)) *info = -5;
    160:   else if (ldq < PetscMax(1,n)) *info = -8;
    161:   else if (rho < 0.) *info = -9;
    162:   PetscCheck(!*info,PETSC_COMM_SELF,PETSC_ERR_ARG_WRONG,"Wrong argument %" PetscBLASInt_FMT " in DLAED3M",-(*info));

    164:   /* Quick return if possible */

    166:   if (k == 0) PetscFunctionReturn(PETSC_SUCCESS);

    168:   /* Modify values DLAMDA(i) to make sure all DLAMDA(i)-DLAMDA(j) can */
    169:   /* be computed with high relative accuracy (barring over/underflow). */
    170:   /* This is a problem on machines without a guard digit in */
    171:   /* add/subtract (Cray XMP, Cray YMP, Cray C 90 and Cray 2). */
    172:   /* The following code replaces DLAMDA(I) by 2*DLAMDA(I)-DLAMDA(I), */
    173:   /* which on any of these machines zeros out the bottommost */
    174:   /* bit of DLAMDA(I) if it is 1; this makes the subsequent */
    175:   /* subtractions DLAMDA(I)-DLAMDA(J) unproblematic when cancellation */
    176:   /* occurs. On binary machines with a guard digit (almost all */
    177:   /* machines) it does not change DLAMDA(I) at all. On hexadecimal */
    178:   /* and decimal machines with a guard digit, it slightly */
    179:   /* changes the bottommost bits of DLAMDA(I). It does not account */
    180:   /* for hexadecimal or decimal machines without guard digits */
    181:   /* (we know of none). We use a subroutine call to compute */
    182:   /* 2*DLAMBDA(I) to prevent optimizing compilers from eliminating */
    183:   /* this code. */

    185:   for (i = 0; i < k; ++i) {
    186:     dlamda[i] = LAPACKlamc3_(&dlamda[i], &dlamda[i]) - dlamda[i];
    187:   }

    189:   for (j = 1; j <= k; ++j) {

    191:     /* ....calling DLAED4 for eigenpair J.... */

    193:     PetscCallBLAS("LAPACKlaed4",LAPACKlaed4_(&k, &j, dlamda, w, &q[(j-1)*ldq], &rho, &d[j-1], info));
    194:     SlepcCheckLapackInfo("laed4",*info);

    196:     if (j < k) {

    198:       /* If the zero finder terminated properly, but the computed */
    199:       /* eigenvalues are not ordered, issue an error statement */
    200:       /* but continue computation. */

    202:       PetscCheck(dlamda[j-1]<dlamda[j],PETSC_COMM_SELF,PETSC_ERR_FP,"DLAMDA(%" PetscBLASInt_FMT ") is greater or equal than DLAMDA(%" PetscBLASInt_FMT ")", j, j+1);
    203:       PetscCheck(d[j-1]>=dlamda[j-1] && d[j-1]<=dlamda[j],PETSC_COMM_SELF,PETSC_ERR_FP,"DLAMDA(%" PetscBLASInt_FMT ") = %g D(%" PetscBLASInt_FMT ") = %g DLAMDA(%" PetscBLASInt_FMT ") = %g", j, (double)dlamda[j-1], j, (double)d[j-1], j+1, (double)dlamda[j]);
    204:     }
    205:   }

    207:   if (k == 1) goto L110;

    209:   if (k == 2) {

    211:     /* permute the components of Q(:,J) (the information returned by DLAED4 */
    212:     /* necessary to construct the eigenvectors) according to the permutation */
    213:     /* stored in INDX, resulting from deflation */

    215:     for (j = 0; j < k; ++j) {
    216:       w[0] = q[0+j*ldq];
    217:       w[1] = q[1+j*ldq];
    218:       ii = indx[0];
    219:       q[0+j*ldq] = w[ii-1];
    220:       ii = indx[1];
    221:       q[1+j*ldq] = w[ii-1];
    222:     }
    223:     goto L110;
    224:   }

    226:   /* ....K.GE.3.... */
    227:   /* Compute updated W (used for computing the eigenvectors corresponding */
    228:   /* to the previously computed eigenvalues). */

    230:   PetscCallBLAS("BLAScopy",BLAScopy_(&k, w, &one, s, &one));

    232:   /* Initialize W(I) = Q(I,I) */

    234:   i1 = ldq + 1;
    235:   PetscCallBLAS("BLAScopy",BLAScopy_(&k, q, &i1, w, &one));
    236:   for (j = 0; j < k; ++j) {
    237:     for (i = 0; i < j; ++i) {
    238:       w[i] *= q[i+j*ldq] / (dlamda[i] - dlamda[j]);
    239:     }
    240:     for (i = j + 1; i < k; ++i) {
    241:       w[i] *= q[i+j*ldq] / (dlamda[i] - dlamda[j]);
    242:     }
    243:   }
    244:   for (i = 0; i < k; ++i) {
    245:     temp = PetscSqrtReal(-w[i]);
    246:     if (temp<0) temp = -temp;
    247:     w[i] =  (s[i] >= 0) ? temp : -temp;
    248:   }

    250:   /* Compute eigenvectors of the modified rank-1 modification (using the */
    251:   /* vector W). */

    253:   for (j = 0; j < k; ++j) {
    254:     for (i = 0; i < k; ++i) {
    255:       s[i] = w[i] / q[i+j*ldq];
    256:     }
    257:     temp = BLASnrm2_(&k, s, &one);
    258:     for (i = 0; i < k; ++i) {

    260:       /* apply the permutation resulting from deflation as stored */
    261:       /* in INDX */

    263:       ii = indx[i];
    264:       q[i+j*ldq] = s[ii-1] / temp;
    265:     }
    266:   }

    268: /* ************************************************************************** */

    270:   /* ....updating the eigenvectors.... */

    272: L110:

    274:   n2 = n - n1;
    275:   n12 = ctot[0] + ctot[1];
    276:   n23 = ctot[1] + ctot[2];
    277:   if (*(unsigned char *)jobz == 'D') {

    279:     /* Compute the updated eigenvectors. (NOTE that every call of */
    280:     /* DGEMM requires three DISTINCT arrays) */

    282:     /* copy Q(CTOT(1)+1:K,1:K) to S */

    284:     for (j=0;j<k;j++) for (i=0;i<n23;i++) s[i+j*n23] = q[ctot[0]+i+j*ldq];
    285:     iq2 = n1 * n12 + 1;

    287:     if (n23 != 0) {

    289:       /* multiply the second part of Q2 (the eigenvectors of the */
    290:       /* lower block) with S and write the result into the lower part of */
    291:       /* Q, i.e., Q(N1+1:N,1:K) */

    293:       PetscCallBLAS("BLASgemm",BLASgemm_("N", "N", &n2, &k, &n23, &done,
    294:                   &q2[iq2-1], &n2, s, &n23, &dzero, &q[n1], &ldq));
    295:     } else {
    296:       for (j=0;j<k;j++) for (i=0;i<n2;i++) q[n1+i+j*ldq] = 0.0;
    297:     }

    299:     /* copy Q(1:CTOT(1)+CTOT(2),1:K) to S */

    301:     for (j=0;j<k;j++) for (i=0;i<n12;i++) s[i+j*n12] = q[i+j*ldq];

    303:     if (n12 != 0) {

    305:       /* multiply the first part of Q2 (the eigenvectors of the */
    306:       /* upper block) with S and write the result into the upper part of */
    307:       /* Q, i.e., Q(1:N1,1:K) */

    309:       PetscCallBLAS("BLASgemm",BLASgemm_("N", "N", &n1, &k, &n12, &done,
    310:                   q2, &n1, s, &n12, &dzero, q, &ldq));
    311:     } else {
    312:       for (j=0;j<k;j++) for (i=0;i<n1;i++) q[i+j*ldq] = 0.0;
    313:     }
    314:   }
    315:   PetscFunctionReturn(PETSC_SUCCESS);
    316: }