Date: 2023-01-26T12:19:39+00:00

Actual source code: mfnexpokit.c
slepc-3.18.2 2023-01-26
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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:    SLEPc matrix function solver: "expokit"

     13:    Method: Arnoldi method tailored for the matrix exponential

     15:    Algorithm:

     17:        Uses Arnoldi relations to compute exp(t_step*A)*v_last for
     18:        several time steps.

     20:    References:

     22:        [1] R. Sidje, "Expokit: a software package for computing matrix
     23:            exponentials", ACM Trans. Math. Softw. 24(1):130-156, 1998.
     24: */

     26: #include <slepc/private/mfnimpl.h>

     28: PetscErrorCode MFNSetUp_Expokit(MFN mfn)
     29: {
     30:   PetscInt       N;
     31:   PetscBool      isexp;

     33:   MatGetSize(mfn->A,&N,NULL);
     34:   if (mfn->ncv==PETSC_DEFAULT) mfn->ncv = PetscMin(30,N);
     35:   if (mfn->max_it==PETSC_DEFAULT) mfn->max_it = 100;
     36:   MFNAllocateSolution(mfn,2);

     38:   PetscObjectTypeCompare((PetscObject)mfn->fn,FNEXP,&isexp);
     40:   return 0;
     41: }

     43: PetscErrorCode MFNSolve_Expokit(MFN mfn,Vec b,Vec x)
     44: {
     45:   PetscInt          mxstep,mxrej,m,mb,ld,i,j,ireject,mx,k1;
     46:   Vec               v,r;
     47:   Mat               H,M=NULL,K=NULL;
     48:   FN                fn;
     49:   PetscScalar       *Harray,*B,*F,*betaF,t,sgn,sfactor;
     50:   const PetscScalar *pK;
     51:   PetscReal         anorm,avnorm,tol,err_loc,rndoff,t_out,t_new,t_now,t_step;
     52:   PetscReal         xm,fact,s,p1,p2,beta,beta2,gamma,delta;
     53:   PetscBool         breakdown;

     55:   m   = mfn->ncv;
     56:   tol = mfn->tol;
     57:   mxstep = mfn->max_it;
     58:   mxrej = 10;
     59:   gamma = 0.9;
     60:   delta = 1.2;
     61:   mb    = m;
     62:   FNGetScale(mfn->fn,&t,&sfactor);
     63:   FNDuplicate(mfn->fn,PetscObjectComm((PetscObject)mfn->fn),&fn);
     64:   FNSetScale(fn,1.0,1.0);
     65:   t_out = PetscAbsScalar(t);
     66:   t_now = 0.0;
     67:   MatNorm(mfn->A,NORM_INFINITY,&anorm);
     68:   rndoff = anorm*PETSC_MACHINE_EPSILON;

     70:   k1 = 2;
     71:   xm = 1.0/(PetscReal)m;
     72:   beta = mfn->bnorm;
     73:   fact = PetscPowRealInt((m+1)/2.72,m+1)*PetscSqrtReal(2.0*PETSC_PI*(m+1));
     74:   t_new = (1.0/anorm)*PetscPowReal((fact*tol)/(4.0*beta*anorm),xm);
     75:   s = PetscPowReal(10.0,PetscFloorReal(PetscLog10Real(t_new))-1);
     76:   t_new = PetscCeilReal(t_new/s)*s;
     77:   sgn = t/PetscAbsScalar(t);

     79:   VecCopy(b,x);
     80:   ld = m+2;
     81:   PetscCalloc2(m+1,&betaF,ld*ld,&B);
     82:   MatCreateSeqDense(PETSC_COMM_SELF,ld,ld,NULL,&H);
     83:   MatDenseGetArray(H,&Harray);

     85:   while (mfn->reason == MFN_CONVERGED_ITERATING) {
     86:     mfn->its++;
     87:     if (PetscIsInfOrNanReal(t_new)) t_new = PETSC_MAX_REAL;
     88:     t_step = PetscMin(t_out-t_now,t_new);
     89:     BVInsertVec(mfn->V,0,x);
     90:     BVScaleColumn(mfn->V,0,1.0/beta);
     91:     BVMatArnoldi(mfn->V,mfn->transpose_solve?mfn->AT:mfn->A,H,0,&mb,&beta2,&breakdown);
     92:     if (breakdown) {
     93:       k1 = 0;
     94:       t_step = t_out-t_now;
     95:     }
     96:     if (k1!=0) {
     97:       Harray[m+1+ld*m] = 1.0;
     98:       BVGetColumn(mfn->V,m,&v);
     99:       BVGetColumn(mfn->V,m+1,&r);
    100:       MatMult(mfn->transpose_solve?mfn->AT:mfn->A,v,r);
    101:       BVRestoreColumn(mfn->V,m,&v);
    102:       BVRestoreColumn(mfn->V,m+1,&r);
    103:       BVNormColumn(mfn->V,m+1,NORM_2,&avnorm);
    104:     }
    105:     PetscArraycpy(B,Harray,ld*ld);

    107:     ireject = 0;
    108:     while (ireject <= mxrej) {
    109:       mx = mb + k1;
    110:       for (i=0;i<mx;i++) {
    111:         for (j=0;j<mx;j++) {
    112:           Harray[i+j*ld] = sgn*B[i+j*ld]*t_step;
    113:         }
    114:       }
    115:       MFN_CreateDenseMat(mx,&M);
    116:       MFN_CreateDenseMat(mx,&K);
    117:       MatDenseGetArray(M,&F);
    118:       for (j=0;j<mx;j++) PetscArraycpy(F+j*mx,Harray+j*ld,mx);
    119:       MatDenseRestoreArray(M,&F);
    120:       FNEvaluateFunctionMat(fn,M,K);

    122:       if (k1==0) {
    123:         err_loc = tol;
    124:         break;
    125:       } else {
    126:         MatDenseGetArrayRead(K,&pK);
    127:         p1 = PetscAbsScalar(beta*pK[m]);
    128:         p2 = PetscAbsScalar(beta*pK[m+1]*avnorm);
    129:         MatDenseRestoreArrayRead(K,&pK);
    130:         if (p1 > 10*p2) {
    131:           err_loc = p2;
    132:           xm = 1.0/(PetscReal)m;
    133:         } else if (p1 > p2) {
    134:           err_loc = (p1*p2)/(p1-p2);
    135:           xm = 1.0/(PetscReal)m;
    136:         } else {
    137:           err_loc = p1;
    138:           xm = 1.0/(PetscReal)(m-1);
    139:         }
    140:       }
    141:       if (err_loc <= delta*t_step*tol) break;
    142:       else {
    143:         t_step = gamma*t_step*PetscPowReal(t_step*tol/err_loc,xm);
    144:         s = PetscPowReal(10.0,PetscFloorReal(PetscLog10Real(t_step))-1);
    145:         t_step = PetscCeilReal(t_step/s)*s;
    146:         ireject = ireject+1;
    147:       }
    148:     }

    150:     mx = mb + PetscMax(0,k1-1);
    151:     MatDenseGetArrayRead(K,&pK);
    152:     for (j=0;j<mx;j++) betaF[j] = beta*pK[j];
    153:     MatDenseRestoreArrayRead(K,&pK);
    154:     BVSetActiveColumns(mfn->V,0,mx);
    155:     BVMultVec(mfn->V,1.0,0.0,x,betaF);
    156:     VecNorm(x,NORM_2,&beta);

    158:     t_now = t_now+t_step;
    159:     if (t_now>=t_out) mfn->reason = MFN_CONVERGED_TOL;
    160:     else {
    161:       t_new = gamma*t_step*PetscPowReal((t_step*tol)/err_loc,xm);
    162:       s = PetscPowReal(10.0,PetscFloorReal(PetscLog10Real(t_new))-1);
    163:       t_new = PetscCeilReal(t_new/s)*s;
    164:     }
    165:     err_loc = PetscMax(err_loc,rndoff);
    166:     if (mfn->its==mxstep) mfn->reason = MFN_DIVERGED_ITS;
    167:     MFNMonitor(mfn,mfn->its,err_loc);
    168:   }
    169:   VecScale(x,sfactor);

    171:   MatDestroy(&M);
    172:   MatDestroy(&K);
    173:   FNDestroy(&fn);
    174:   MatDenseRestoreArray(H,&Harray);
    175:   MatDestroy(&H);
    176:   PetscFree2(betaF,B);
    177:   return 0;
    178: }

    180: SLEPC_EXTERN PetscErrorCode MFNCreate_Expokit(MFN mfn)
    181: {
    182:   mfn->ops->solve          = MFNSolve_Expokit;
    183:   mfn->ops->setup          = MFNSetUp_Expokit;
    184:   return 0;
    185: }