Actual source code: chwirut2f.F90

  1: !  Program usage: mpiexec -n 1 chwirut1f [-help] [all TAO options]
  2: !
  3: !  Description:  This example demonstrates use of the TAO package to solve a
  4: !  nonlinear least-squares problem on a single processor.  We minimize the
  5: !  Chwirut function:
  6: !       sum_{i=0}^{n/2-1} ( alpha*(x_{2i+1}-x_{2i}^2)^2 + (1-x_{2i})^2)
  7: !
  8: !  The C version of this code is chwirut1.c
  9: !

 11: !
 12: ! ----------------------------------------------------------------------
 13: !
 14:       module chwirut2fmodule
 15:       use petscmpi              ! or mpi or mpi_f08
 16:       use petsctao
 17: #include <petsc/finclude/petsctao.h>
 18:       PetscReal t(0:213)
 19:       PetscReal y(0:213)
 20:       PetscInt  m,n
 21:       PetscMPIInt  nn
 22:       PetscMPIInt  rank
 23:       PetscMPIInt  size
 24:       PetscMPIInt  idle_tag, die_tag
 25:       PetscMPIInt  zero,one
 26:       parameter (m=214)
 27:       parameter (n=3)
 28:       parameter (nn=n)
 29:       parameter (idle_tag=2000)
 30:       parameter (die_tag=3000)
 31:       parameter (zero=0,one=1)
 32:       end module chwirut2fmodule

 34:       program main
 35:       use chwirut2fmodule

 37: ! - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
 38: !                   Variable declarations
 39: ! - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
 40: !
 41: !  See additional variable declarations in the file chwirut2f.h

 43:       PetscErrorCode   ierr    ! used to check for functions returning nonzeros
 44:       Vec              x       ! solution vector
 45:       Vec              f       ! vector of functions
 46:       Tao        tao     ! Tao context

 48: !  Note: Any user-defined Fortran routines (such as FormGradient)
 49: !  MUST be declared as external.

 51:       external FormFunction

 53: !  Initialize TAO and PETSc
 54:       PetscCallA(PetscInitialize(ierr))
 55:       PetscCallMPIA(MPI_Comm_size(PETSC_COMM_WORLD,size,ierr))
 56:       PetscCallMPIA(MPI_Comm_rank(PETSC_COMM_WORLD,rank,ierr))

 58: !  Initialize problem parameters
 59:       call InitializeData()

 61:       if (rank .eq. 0) then
 62: !  Allocate vectors for the solution and gradient
 63:          PetscCallA(VecCreateSeq(PETSC_COMM_SELF,n,x,ierr))
 64:          PetscCallA(VecCreateSeq(PETSC_COMM_SELF,m,f,ierr))

 66: !     The TAO code begins here

 68: !     Create TAO solver
 69:          PetscCallA(TaoCreate(PETSC_COMM_SELF,tao,ierr))
 70:          PetscCallA(TaoSetType(tao,TAOPOUNDERS,ierr))

 72: !     Set routines for function, gradient, and hessian evaluation
 73:          PetscCallA(TaoSetResidualRoutine(tao,f,FormFunction,0,ierr))

 75: !     Optional: Set initial guess
 76:          call FormStartingPoint(x)
 77:          PetscCallA(TaoSetSolution(tao, x, ierr))

 79: !     Check for TAO command line options
 80:          PetscCallA(TaoSetFromOptions(tao,ierr))
 81: !     SOLVE THE APPLICATION
 82:          PetscCallA(TaoSolve(tao,ierr))

 84: !     Free TAO data structures
 85:          PetscCallA(TaoDestroy(tao,ierr))

 87: !     Free PETSc data structures
 88:          PetscCallA(VecDestroy(x,ierr))
 89:          PetscCallA(VecDestroy(f,ierr))
 90:          PetscCallA(StopWorkers(ierr))

 92:       else
 93:          PetscCallA(TaskWorker(ierr))
 94:       endif

 96:       PetscCallA(PetscFinalize(ierr))
 97:       end

 99: ! --------------------------------------------------------------------
100: !  FormFunction - Evaluates the function f(X) and gradient G(X)
101: !
102: !  Input Parameters:
103: !  tao - the Tao context
104: !  X   - input vector
105: !  dummy - not used
106: !
107: !  Output Parameters:
108: !  f - function vector

110:       subroutine FormFunction(tao, x, f, dummy, ierr)
111:       use chwirut2fmodule

113:       Tao        tao
114:       Vec              x,f
115:       PetscErrorCode   ierr

117:       PetscInt         i,checkedin
118:       PetscInt         finished_tasks
119:       PetscMPIInt      next_task
120:       PetscMPIInt      status(MPI_STATUS_SIZE),tag,source
121:       PetscInt         dummy

123: ! PETSc's VecGetArray acts differently in Fortran than it does in C.
124: ! Calling VecGetArray((Vec) X, (PetscReal) x_array(0:1), (PetscOffset) x_index, ierr))
125: ! will return an array of doubles referenced by x_array offset by x_index.
126: !  i.e.,  to reference the kth element of X, use x_array(k + x_index).
127: ! Notice that by declaring the arrays with range (0:1), we are using the C 0-indexing practice.
128:       PetscReal        f_v(0:1),x_v(0:1),fval(1)
129:       PetscOffset      f_i,x_i

131:       0

133: !     Get pointers to vector data
134:       PetscCall(VecGetArray(x,x_v,x_i,ierr))
135:       PetscCall(VecGetArray(f,f_v,f_i,ierr))

137: !     Compute F(X)
138:       if (size .eq. 1) then
139:          ! Single processor
140:          do i=0,m-1
141:             PetscCall(RunSimulation(x_v(x_i),i,f_v(i+f_i),ierr))
142:          enddo
143:       else
144:          ! Multiprocessor main
145:          next_task = zero
146:          finished_tasks = 0
147:          checkedin = 0

149:          do while (finished_tasks .lt. m .or. checkedin .lt. size-1)
150:             PetscCallMPI(MPI_Recv(fval,one,MPIU_SCALAR,MPI_ANY_SOURCE,MPI_ANY_TAG,PETSC_COMM_WORLD,status,ierr))
151:             tag = status(MPI_TAG)
152:             source = status(MPI_SOURCE)
153:             if (tag .eq. IDLE_TAG) then
154:                checkedin = checkedin + 1
155:             else
156:                f_v(f_i+tag) = fval(1)
157:                finished_tasks = finished_tasks + 1
158:             endif
159:             if (next_task .lt. m) then
160:                ! Send task to worker
161:                PetscCallMPI(MPI_Send(x_v(x_i),nn,MPIU_SCALAR,source,next_task,PETSC_COMM_WORLD,ierr))
162:                next_task = next_task + one
163:             else
164:                ! Send idle message to worker
165:                PetscCallMPI(MPI_Send(x_v(x_i),nn,MPIU_SCALAR,source,IDLE_TAG,PETSC_COMM_WORLD,ierr))
166:             end if
167:          enddo
168:       endif

170: !     Restore vectors
171:       PetscCall(VecRestoreArray(x,x_v,x_i,ierr))
172:       PetscCall(VecRestoreArray(F,f_v,f_i,ierr))
173:       return
174:       end

176:       subroutine FormStartingPoint(x)
177:       use chwirut2fmodule

179:       Vec             x
180:       PetscReal       x_v(0:1)
181:       PetscOffset     x_i
182:       PetscErrorCode  ierr

184:       PetscCall(VecGetArray(x,x_v,x_i,ierr))
185:       x_v(x_i) = 0.15
186:       x_v(x_i+1) = 0.008
187:       x_v(x_i+2) = 0.01
188:       PetscCall(VecRestoreArray(x,x_v,x_i,ierr))
189:       return
190:       end

192:       subroutine InitializeData()
193:       use chwirut2fmodule

195:       PetscInt i
196:       i=0
197:       y(i) =    92.9000;  t(i) =  0.5000; i=i+1
198:       y(i) =    78.7000;  t(i) =   0.6250; i=i+1
199:       y(i) =    64.2000;  t(i) =   0.7500; i=i+1
200:       y(i) =    64.9000;  t(i) =   0.8750; i=i+1
201:       y(i) =    57.1000;  t(i) =   1.0000; i=i+1
202:       y(i) =    43.3000;  t(i) =   1.2500; i=i+1
203:       y(i) =    31.1000;  t(i) =  1.7500; i=i+1
204:       y(i) =    23.6000;  t(i) =  2.2500; i=i+1
205:       y(i) =    31.0500;  t(i) =  1.7500; i=i+1
206:       y(i) =    23.7750;  t(i) =  2.2500; i=i+1
207:       y(i) =    17.7375;  t(i) =  2.7500; i=i+1
208:       y(i) =    13.8000;  t(i) =  3.2500; i=i+1
209:       y(i) =    11.5875;  t(i) =  3.7500; i=i+1
210:       y(i) =     9.4125;  t(i) =  4.2500; i=i+1
211:       y(i) =     7.7250;  t(i) =  4.7500; i=i+1
212:       y(i) =     7.3500;  t(i) =  5.2500; i=i+1
213:       y(i) =     8.0250;  t(i) =  5.7500; i=i+1
214:       y(i) =    90.6000;  t(i) =  0.5000; i=i+1
215:       y(i) =    76.9000;  t(i) =  0.6250; i=i+1
216:       y(i) =    71.6000;  t(i) = 0.7500; i=i+1
217:       y(i) =    63.6000;  t(i) =  0.8750; i=i+1
218:       y(i) =    54.0000;  t(i) =  1.0000; i=i+1
219:       y(i) =    39.2000;  t(i) =  1.2500; i=i+1
220:       y(i) =    29.3000;  t(i) = 1.7500; i=i+1
221:       y(i) =    21.4000;  t(i) =  2.2500; i=i+1
222:       y(i) =    29.1750;  t(i) =  1.7500; i=i+1
223:       y(i) =    22.1250;  t(i) =  2.2500; i=i+1
224:       y(i) =    17.5125;  t(i) =  2.7500; i=i+1
225:       y(i) =    14.2500;  t(i) =  3.2500; i=i+1
226:       y(i) =     9.4500;  t(i) =  3.7500; i=i+1
227:       y(i) =     9.1500;  t(i) =  4.2500; i=i+1
228:       y(i) =     7.9125;  t(i) =  4.7500; i=i+1
229:       y(i) =     8.4750;  t(i) =  5.2500; i=i+1
230:       y(i) =     6.1125;  t(i) =  5.7500; i=i+1
231:       y(i) =    80.0000;  t(i) =  0.5000; i=i+1
232:       y(i) =    79.0000;  t(i) =  0.6250; i=i+1
233:       y(i) =    63.8000;  t(i) =  0.7500; i=i+1
234:       y(i) =    57.2000;  t(i) =  0.8750; i=i+1
235:       y(i) =    53.2000;  t(i) =  1.0000; i=i+1
236:       y(i) =    42.5000;  t(i) =  1.2500; i=i+1
237:       y(i) =    26.8000;  t(i) =  1.7500; i=i+1
238:       y(i) =    20.4000;  t(i) =  2.2500; i=i+1
239:       y(i) =    26.8500;  t(i) =   1.7500; i=i+1
240:       y(i) =    21.0000;  t(i) =   2.2500; i=i+1
241:       y(i) =    16.4625;  t(i) =   2.7500; i=i+1
242:       y(i) =    12.5250;  t(i) =   3.2500; i=i+1
243:       y(i) =    10.5375;  t(i) =   3.7500; i=i+1
244:       y(i) =     8.5875;  t(i) =   4.2500; i=i+1
245:       y(i) =     7.1250;  t(i) =   4.7500; i=i+1
246:       y(i) =     6.1125;  t(i) =   5.2500; i=i+1
247:       y(i) =     5.9625;  t(i) =   5.7500; i=i+1
248:       y(i) =    74.1000;  t(i) =   0.5000; i=i+1
249:       y(i) =    67.3000;  t(i) =   0.6250; i=i+1
250:       y(i) =    60.8000;  t(i) =   0.7500; i=i+1
251:       y(i) =    55.5000;  t(i) =   0.8750; i=i+1
252:       y(i) =    50.3000;  t(i) =   1.0000; i=i+1
253:       y(i) =    41.0000;  t(i) =   1.2500; i=i+1
254:       y(i) =    29.4000;  t(i) =   1.7500; i=i+1
255:       y(i) =    20.4000;  t(i) =   2.2500; i=i+1
256:       y(i) =    29.3625;  t(i) =   1.7500; i=i+1
257:       y(i) =    21.1500;  t(i) =   2.2500; i=i+1
258:       y(i) =    16.7625;  t(i) =   2.7500; i=i+1
259:       y(i) =    13.2000;  t(i) =   3.2500; i=i+1
260:       y(i) =    10.8750;  t(i) =   3.7500; i=i+1
261:       y(i) =     8.1750;  t(i) =   4.2500; i=i+1
262:       y(i) =     7.3500;  t(i) =   4.7500; i=i+1
263:       y(i) =     5.9625;  t(i) =  5.2500; i=i+1
264:       y(i) =     5.6250;  t(i) =   5.7500; i=i+1
265:       y(i) =    81.5000;  t(i) =    .5000; i=i+1
266:       y(i) =    62.4000;  t(i) =    .7500; i=i+1
267:       y(i) =    32.5000;  t(i) =   1.5000; i=i+1
268:       y(i) =    12.4100;  t(i) =   3.0000; i=i+1
269:       y(i) =    13.1200;  t(i) =   3.0000; i=i+1
270:       y(i) =    15.5600;  t(i) =   3.0000; i=i+1
271:       y(i) =     5.6300;  t(i) =   6.0000; i=i+1
272:       y(i) =    78.0000;  t(i) =   .5000; i=i+1
273:       y(i) =    59.9000;  t(i) =    .7500; i=i+1
274:       y(i) =    33.2000;  t(i) =   1.5000; i=i+1
275:       y(i) =    13.8400;  t(i) =   3.0000; i=i+1
276:       y(i) =    12.7500;  t(i) =   3.0000; i=i+1
277:       y(i) =    14.6200;  t(i) =   3.0000; i=i+1
278:       y(i) =     3.9400;  t(i) =   6.0000; i=i+1
279:       y(i) =    76.8000;  t(i) =    .5000; i=i+1
280:       y(i) =    61.0000;  t(i) =    .7500; i=i+1
281:       y(i) =    32.9000;  t(i) =   1.5000; i=i+1
282:       y(i) =    13.8700;  t(i) = 3.0000; i=i+1
283:       y(i) =    11.8100;  t(i) =   3.0000; i=i+1
284:       y(i) =    13.3100;  t(i) =   3.0000; i=i+1
285:       y(i) =     5.4400;  t(i) =   6.0000; i=i+1
286:       y(i) =    78.0000;  t(i) =    .5000; i=i+1
287:       y(i) =    63.5000;  t(i) =    .7500; i=i+1
288:       y(i) =    33.8000;  t(i) =   1.5000; i=i+1
289:       y(i) =    12.5600;  t(i) =   3.0000; i=i+1
290:       y(i) =     5.6300;  t(i) =   6.0000; i=i+1
291:       y(i) =    12.7500;  t(i) =   3.0000; i=i+1
292:       y(i) =    13.1200;  t(i) =   3.0000; i=i+1
293:       y(i) =     5.4400;  t(i) =   6.0000; i=i+1
294:       y(i) =    76.8000;  t(i) =    .5000; i=i+1
295:       y(i) =    60.0000;  t(i) =    .7500; i=i+1
296:       y(i) =    47.8000;  t(i) =   1.0000; i=i+1
297:       y(i) =    32.0000;  t(i) =   1.5000; i=i+1
298:       y(i) =    22.2000;  t(i) =   2.0000; i=i+1
299:       y(i) =    22.5700;  t(i) =   2.0000; i=i+1
300:       y(i) =    18.8200;  t(i) =   2.5000; i=i+1
301:       y(i) =    13.9500;  t(i) =   3.0000; i=i+1
302:       y(i) =    11.2500;  t(i) =   4.0000; i=i+1
303:       y(i) =     9.0000;  t(i) =   5.0000; i=i+1
304:       y(i) =     6.6700;  t(i) =   6.0000; i=i+1
305:       y(i) =    75.8000;  t(i) =    .5000; i=i+1
306:       y(i) =    62.0000;  t(i) =    .7500; i=i+1
307:       y(i) =    48.8000;  t(i) =   1.0000; i=i+1
308:       y(i) =    35.2000;  t(i) =   1.5000; i=i+1
309:       y(i) =    20.0000;  t(i) =   2.0000; i=i+1
310:       y(i) =    20.3200;  t(i) =   2.0000; i=i+1
311:       y(i) =    19.3100;  t(i) =   2.5000; i=i+1
312:       y(i) =    12.7500;  t(i) =   3.0000; i=i+1
313:       y(i) =    10.4200;  t(i) =   4.0000; i=i+1
314:       y(i) =     7.3100;  t(i) =   5.0000; i=i+1
315:       y(i) =     7.4200;  t(i) =   6.0000; i=i+1
316:       y(i) =    70.5000;  t(i) =    .5000; i=i+1
317:       y(i) =    59.5000;  t(i) =    .7500; i=i+1
318:       y(i) =    48.5000;  t(i) =   1.0000; i=i+1
319:       y(i) =    35.8000;  t(i) =   1.5000; i=i+1
320:       y(i) =    21.0000;  t(i) =   2.0000; i=i+1
321:       y(i) =    21.6700;  t(i) =   2.0000; i=i+1
322:       y(i) =    21.0000;  t(i) =   2.5000; i=i+1
323:       y(i) =    15.6400;  t(i) =   3.0000; i=i+1
324:       y(i) =     8.1700;  t(i) =   4.0000; i=i+1
325:       y(i) =     8.5500;  t(i) =   5.0000; i=i+1
326:       y(i) =    10.1200;  t(i) =   6.0000; i=i+1
327:       y(i) =    78.0000;  t(i) =    .5000; i=i+1
328:       y(i) =    66.0000;  t(i) =    .6250; i=i+1
329:       y(i) =    62.0000;  t(i) =    .7500; i=i+1
330:       y(i) =    58.0000;  t(i) =    .8750; i=i+1
331:       y(i) =    47.7000;  t(i) =   1.0000; i=i+1
332:       y(i) =    37.8000;  t(i) =   1.2500; i=i+1
333:       y(i) =    20.2000;  t(i) =   2.2500; i=i+1
334:       y(i) =    21.0700;  t(i) =   2.2500; i=i+1
335:       y(i) =    13.8700;  t(i) =   2.7500; i=i+1
336:       y(i) =     9.6700;  t(i) =   3.2500; i=i+1
337:       y(i) =     7.7600;  t(i) =   3.7500; i=i+1
338:       y(i) =     5.4400;  t(i) =  4.2500; i=i+1
339:       y(i) =     4.8700;  t(i) =  4.7500; i=i+1
340:       y(i) =     4.0100;  t(i) =   5.2500; i=i+1
341:       y(i) =     3.7500;  t(i) =   5.7500; i=i+1
342:       y(i) =    24.1900;  t(i) =   3.0000; i=i+1
343:       y(i) =    25.7600;  t(i) =   3.0000; i=i+1
344:       y(i) =    18.0700;  t(i) =   3.0000; i=i+1
345:       y(i) =    11.8100;  t(i) =   3.0000; i=i+1
346:       y(i) =    12.0700;  t(i) =   3.0000; i=i+1
347:       y(i) =    16.1200;  t(i) =   3.0000; i=i+1
348:       y(i) =    70.8000;  t(i) =    .5000; i=i+1
349:       y(i) =    54.7000;  t(i) =    .7500; i=i+1
350:       y(i) =    48.0000;  t(i) =   1.0000; i=i+1
351:       y(i) =    39.8000;  t(i) =   1.5000; i=i+1
352:       y(i) =    29.8000;  t(i) =   2.0000; i=i+1
353:       y(i) =    23.7000;  t(i) =   2.5000; i=i+1
354:       y(i) =    29.6200;  t(i) =   2.0000; i=i+1
355:       y(i) =    23.8100;  t(i) =   2.5000; i=i+1
356:       y(i) =    17.7000;  t(i) =   3.0000; i=i+1
357:       y(i) =    11.5500;  t(i) =   4.0000; i=i+1
358:       y(i) =    12.0700;  t(i) =   5.0000; i=i+1
359:       y(i) =     8.7400;  t(i) =   6.0000; i=i+1
360:       y(i) =    80.7000;  t(i) =    .5000; i=i+1
361:       y(i) =    61.3000;  t(i) =    .7500; i=i+1
362:       y(i) =    47.5000;  t(i) =   1.0000; i=i+1
363:       y(i) =    29.0000;  t(i) =   1.5000; i=i+1
364:       y(i) =    24.0000;  t(i) =   2.0000; i=i+1
365:       y(i) =    17.7000;  t(i) =   2.5000; i=i+1
366:       y(i) =    24.5600;  t(i) =   2.0000; i=i+1
367:       y(i) =    18.6700;  t(i) =   2.5000; i=i+1
368:       y(i) =    16.2400;  t(i) =   3.0000; i=i+1
369:       y(i) =     8.7400;  t(i) =   4.0000; i=i+1
370:       y(i) =     7.8700;  t(i) =   5.0000; i=i+1
371:       y(i) =     8.5100;  t(i) =   6.0000; i=i+1
372:       y(i) =    66.7000;  t(i) =    .5000; i=i+1
373:       y(i) =    59.2000;  t(i) =    .7500; i=i+1
374:       y(i) =    40.8000;  t(i) =   1.0000; i=i+1
375:       y(i) =    30.7000;  t(i) =   1.5000; i=i+1
376:       y(i) =    25.7000;  t(i) =   2.0000; i=i+1
377:       y(i) =    16.3000;  t(i) =   2.5000; i=i+1
378:       y(i) =    25.9900;  t(i) =   2.0000; i=i+1
379:       y(i) =    16.9500;  t(i) =   2.5000; i=i+1
380:       y(i) =    13.3500;  t(i) =   3.0000; i=i+1
381:       y(i) =     8.6200;  t(i) =   4.0000; i=i+1
382:       y(i) =     7.2000;  t(i) =   5.0000; i=i+1
383:       y(i) =     6.6400;  t(i) =   6.0000; i=i+1
384:       y(i) =    13.6900;  t(i) =   3.0000; i=i+1
385:       y(i) =    81.0000;  t(i) =    .5000; i=i+1
386:       y(i) =    64.5000;  t(i) =    .7500; i=i+1
387:       y(i) =    35.5000;  t(i) =   1.5000; i=i+1
388:       y(i) =    13.3100;  t(i) =   3.0000; i=i+1
389:       y(i) =     4.8700;  t(i) =   6.0000; i=i+1
390:       y(i) =    12.9400;  t(i) =   3.0000; i=i+1
391:       y(i) =     5.0600;  t(i) =   6.0000; i=i+1
392:       y(i) =    15.1900;  t(i) =   3.0000; i=i+1
393:       y(i) =    14.6200;  t(i) =   3.0000; i=i+1
394:       y(i) =    15.6400;  t(i) =   3.0000; i=i+1
395:       y(i) =    25.5000;  t(i) =   1.7500; i=i+1
396:       y(i) =    25.9500;  t(i) =   1.7500; i=i+1
397:       y(i) =    81.7000;  t(i) =    .5000; i=i+1
398:       y(i) =    61.6000;  t(i) =    .7500; i=i+1
399:       y(i) =    29.8000;  t(i) =   1.7500; i=i+1
400:       y(i) =    29.8100;  t(i) =   1.7500; i=i+1
401:       y(i) =    17.1700;  t(i) =   2.7500; i=i+1
402:       y(i) =    10.3900;  t(i) =   3.7500; i=i+1
403:       y(i) =    28.4000;  t(i) =   1.7500; i=i+1
404:       y(i) =    28.6900;  t(i) =   1.7500; i=i+1
405:       y(i) =    81.3000;  t(i) =    .5000; i=i+1
406:       y(i) =    60.9000;  t(i) =    .7500; i=i+1
407:       y(i) =    16.6500;  t(i) =   2.7500; i=i+1
408:       y(i) =    10.0500;  t(i) =   3.7500; i=i+1
409:       y(i) =    28.9000;  t(i) =   1.7500; i=i+1
410:       y(i) =    28.9500;  t(i) =   1.7500; i=i+1

412:       return
413:       end

415:       subroutine TaskWorker(ierr)
416:       use chwirut2fmodule

418:       PetscErrorCode ierr
419:       PetscReal x(n),f(1)
420:       PetscMPIInt tag
421:       PetscInt index
422:       PetscMPIInt status(MPI_STATUS_SIZE)

424:       tag = IDLE_TAG
425:       f   = 0.0
426:       ! Send check-in message to rank-0
427:       PetscCallMPI(MPI_Send(f,one,MPIU_SCALAR,zero,IDLE_TAG,PETSC_COMM_WORLD,ierr))
428:       do while (tag .ne. DIE_TAG)
429:          PetscCallMPI(MPI_Recv(x,nn,MPIU_SCALAR,zero,MPI_ANY_TAG,PETSC_COMM_WORLD,status,ierr))
430:          tag = status(MPI_TAG)
431:          if (tag .eq. IDLE_TAG) then
432:             PetscCallMPI(MPI_Send(f,one,MPIU_SCALAR,zero,IDLE_TAG,PETSC_COMM_WORLD,ierr))
433:          else if (tag .ne. DIE_TAG) then
434:             index = tag
435:             ! Compute local part of residual
436:             PetscCall(RunSimulation(x,index,f(1),ierr))

438:             ! Return residual to rank-0
439:             PetscCallMPI(MPI_Send(f,one,MPIU_SCALAR,zero,tag,PETSC_COMM_WORLD,ierr))
440:          end if
441:       enddo
442:       0
443:       return
444:       end

446:       subroutine RunSimulation(x,i,f,ierr)
447:       use chwirut2fmodule

449:       PetscReal x(n),f
450:       PetscInt i
451:       PetscErrorCode ierr
452:       f = y(i) - exp(-x(1)*t(i))/(x(2)+x(3)*t(i))
453:       0
454:       return
455:       end

457:       subroutine StopWorkers(ierr)
458:       use chwirut2fmodule

460:       integer checkedin
461:       PetscMPIInt status(MPI_STATUS_SIZE)
462:       PetscMPIInt source
463:       PetscReal f(1),x(n)
464:       PetscErrorCode ierr
465:       PetscInt i

467:       checkedin=0
468:       do while (checkedin .lt. size-1)
469:          PetscCallMPI(MPI_Recv(f,one,MPIU_SCALAR,MPI_ANY_SOURCE,MPI_ANY_TAG,PETSC_COMM_WORLD,status,ierr))
470:          checkedin=checkedin+1
471:          source = status(MPI_SOURCE)
472:          do i=1,n
473:            x(i) = 0.0
474:          enddo
475:          PetscCallMPI(MPI_Send(x,nn,MPIU_SCALAR,source,DIE_TAG,PETSC_COMM_WORLD,ierr))
476:       enddo
477:       0
478:       return
479:       end

481: !/*TEST
482: !
483: !   build:
484: !      requires: !complex
485: !
486: !   test:
487: !      nsize: 3
488: !      args: -tao_smonitor -tao_max_it 100 -tao_type pounders -tao_gatol 1.e-5
489: !      requires: !single
490: !
491: !
492: !TEST*/