xref: /petsc/src/tao/leastsquares/tutorials/chwirut2f.F90 (revision 7e1a0bbe36d2be40a00a95404ece00db4857f70d) 
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!
10#include <petsc/finclude/petsctao.h>
11module chwirut2fmodule
12  use petscmpi              ! or mpi or mpi_f08
13  use petsctao
14  implicit none
15  PetscReal t(0:213)
16  PetscReal y(0:213)
17  PetscInt, parameter :: m = 214, n = 3
18  PetscMPIInt, parameter :: nn = n
19  PetscMPIInt rank
20  PetscMPIInt size
21  PetscMPIInt, parameter :: idle_tag = 2000, die_tag = 3000
22  PetscMPIInt, parameter :: zero = 0, one = 1
23
24contains
25  subroutine InitializeData()
26
27    PetscInt i
28    i = 0
29    y(i) = 92.9000; t(i) = 0.5000; i = i + 1
30    y(i) = 78.7000; t(i) = 0.6250; i = i + 1
31    y(i) = 64.2000; t(i) = 0.7500; i = i + 1
32    y(i) = 64.9000; t(i) = 0.8750; i = i + 1
33    y(i) = 57.1000; t(i) = 1.0000; i = i + 1
34    y(i) = 43.3000; t(i) = 1.2500; i = i + 1
35    y(i) = 31.1000; t(i) = 1.7500; i = i + 1
36    y(i) = 23.6000; t(i) = 2.2500; i = i + 1
37    y(i) = 31.0500; t(i) = 1.7500; i = i + 1
38    y(i) = 23.7750; t(i) = 2.2500; i = i + 1
39    y(i) = 17.7375; t(i) = 2.7500; i = i + 1
40    y(i) = 13.8000; t(i) = 3.2500; i = i + 1
41    y(i) = 11.5875; t(i) = 3.7500; i = i + 1
42    y(i) = 9.4125; t(i) = 4.2500; i = i + 1
43    y(i) = 7.7250; t(i) = 4.7500; i = i + 1
44    y(i) = 7.3500; t(i) = 5.2500; i = i + 1
45    y(i) = 8.0250; t(i) = 5.7500; i = i + 1
46    y(i) = 90.6000; t(i) = 0.5000; i = i + 1
47    y(i) = 76.9000; t(i) = 0.6250; i = i + 1
48    y(i) = 71.6000; t(i) = 0.7500; i = i + 1
49    y(i) = 63.6000; t(i) = 0.8750; i = i + 1
50    y(i) = 54.0000; t(i) = 1.0000; i = i + 1
51    y(i) = 39.2000; t(i) = 1.2500; i = i + 1
52    y(i) = 29.3000; t(i) = 1.7500; i = i + 1
53    y(i) = 21.4000; t(i) = 2.2500; i = i + 1
54    y(i) = 29.1750; t(i) = 1.7500; i = i + 1
55    y(i) = 22.1250; t(i) = 2.2500; i = i + 1
56    y(i) = 17.5125; t(i) = 2.7500; i = i + 1
57    y(i) = 14.2500; t(i) = 3.2500; i = i + 1
58    y(i) = 9.4500; t(i) = 3.7500; i = i + 1
59    y(i) = 9.1500; t(i) = 4.2500; i = i + 1
60    y(i) = 7.9125; t(i) = 4.7500; i = i + 1
61    y(i) = 8.4750; t(i) = 5.2500; i = i + 1
62    y(i) = 6.1125; t(i) = 5.7500; i = i + 1
63    y(i) = 80.0000; t(i) = 0.5000; i = i + 1
64    y(i) = 79.0000; t(i) = 0.6250; i = i + 1
65    y(i) = 63.8000; t(i) = 0.7500; i = i + 1
66    y(i) = 57.2000; t(i) = 0.8750; i = i + 1
67    y(i) = 53.2000; t(i) = 1.0000; i = i + 1
68    y(i) = 42.5000; t(i) = 1.2500; i = i + 1
69    y(i) = 26.8000; t(i) = 1.7500; i = i + 1
70    y(i) = 20.4000; t(i) = 2.2500; i = i + 1
71    y(i) = 26.8500; t(i) = 1.7500; i = i + 1
72    y(i) = 21.0000; t(i) = 2.2500; i = i + 1
73    y(i) = 16.4625; t(i) = 2.7500; i = i + 1
74    y(i) = 12.5250; t(i) = 3.2500; i = i + 1
75    y(i) = 10.5375; t(i) = 3.7500; i = i + 1
76    y(i) = 8.5875; t(i) = 4.2500; i = i + 1
77    y(i) = 7.1250; t(i) = 4.7500; i = i + 1
78    y(i) = 6.1125; t(i) = 5.2500; i = i + 1
79    y(i) = 5.9625; t(i) = 5.7500; i = i + 1
80    y(i) = 74.1000; t(i) = 0.5000; i = i + 1
81    y(i) = 67.3000; t(i) = 0.6250; i = i + 1
82    y(i) = 60.8000; t(i) = 0.7500; i = i + 1
83    y(i) = 55.5000; t(i) = 0.8750; i = i + 1
84    y(i) = 50.3000; t(i) = 1.0000; i = i + 1
85    y(i) = 41.0000; t(i) = 1.2500; i = i + 1
86    y(i) = 29.4000; t(i) = 1.7500; i = i + 1
87    y(i) = 20.4000; t(i) = 2.2500; i = i + 1
88    y(i) = 29.3625; t(i) = 1.7500; i = i + 1
89    y(i) = 21.1500; t(i) = 2.2500; i = i + 1
90    y(i) = 16.7625; t(i) = 2.7500; i = i + 1
91    y(i) = 13.2000; t(i) = 3.2500; i = i + 1
92    y(i) = 10.8750; t(i) = 3.7500; i = i + 1
93    y(i) = 8.1750; t(i) = 4.2500; i = i + 1
94    y(i) = 7.3500; t(i) = 4.7500; i = i + 1
95    y(i) = 5.9625; t(i) = 5.2500; i = i + 1
96    y(i) = 5.6250; t(i) = 5.7500; i = i + 1
97    y(i) = 81.5000; t(i) = .5000; i = i + 1
98    y(i) = 62.4000; t(i) = .7500; i = i + 1
99    y(i) = 32.5000; t(i) = 1.5000; i = i + 1
100    y(i) = 12.4100; t(i) = 3.0000; i = i + 1
101    y(i) = 13.1200; t(i) = 3.0000; i = i + 1
102    y(i) = 15.5600; t(i) = 3.0000; i = i + 1
103    y(i) = 5.6300; t(i) = 6.0000; i = i + 1
104    y(i) = 78.0000; t(i) = .5000; i = i + 1
105    y(i) = 59.9000; t(i) = .7500; i = i + 1
106    y(i) = 33.2000; t(i) = 1.5000; i = i + 1
107    y(i) = 13.8400; t(i) = 3.0000; i = i + 1
108    y(i) = 12.7500; t(i) = 3.0000; i = i + 1
109    y(i) = 14.6200; t(i) = 3.0000; i = i + 1
110    y(i) = 3.9400; t(i) = 6.0000; i = i + 1
111    y(i) = 76.8000; t(i) = .5000; i = i + 1
112    y(i) = 61.0000; t(i) = .7500; i = i + 1
113    y(i) = 32.9000; t(i) = 1.5000; i = i + 1
114    y(i) = 13.8700; t(i) = 3.0000; i = i + 1
115    y(i) = 11.8100; t(i) = 3.0000; i = i + 1
116    y(i) = 13.3100; t(i) = 3.0000; i = i + 1
117    y(i) = 5.4400; t(i) = 6.0000; i = i + 1
118    y(i) = 78.0000; t(i) = .5000; i = i + 1
119    y(i) = 63.5000; t(i) = .7500; i = i + 1
120    y(i) = 33.8000; t(i) = 1.5000; i = i + 1
121    y(i) = 12.5600; t(i) = 3.0000; i = i + 1
122    y(i) = 5.6300; t(i) = 6.0000; i = i + 1
123    y(i) = 12.7500; t(i) = 3.0000; i = i + 1
124    y(i) = 13.1200; t(i) = 3.0000; i = i + 1
125    y(i) = 5.4400; t(i) = 6.0000; i = i + 1
126    y(i) = 76.8000; t(i) = .5000; i = i + 1
127    y(i) = 60.0000; t(i) = .7500; i = i + 1
128    y(i) = 47.8000; t(i) = 1.0000; i = i + 1
129    y(i) = 32.0000; t(i) = 1.5000; i = i + 1
130    y(i) = 22.2000; t(i) = 2.0000; i = i + 1
131    y(i) = 22.5700; t(i) = 2.0000; i = i + 1
132    y(i) = 18.8200; t(i) = 2.5000; i = i + 1
133    y(i) = 13.9500; t(i) = 3.0000; i = i + 1
134    y(i) = 11.2500; t(i) = 4.0000; i = i + 1
135    y(i) = 9.0000; t(i) = 5.0000; i = i + 1
136    y(i) = 6.6700; t(i) = 6.0000; i = i + 1
137    y(i) = 75.8000; t(i) = .5000; i = i + 1
138    y(i) = 62.0000; t(i) = .7500; i = i + 1
139    y(i) = 48.8000; t(i) = 1.0000; i = i + 1
140    y(i) = 35.2000; t(i) = 1.5000; i = i + 1
141    y(i) = 20.0000; t(i) = 2.0000; i = i + 1
142    y(i) = 20.3200; t(i) = 2.0000; i = i + 1
143    y(i) = 19.3100; t(i) = 2.5000; i = i + 1
144    y(i) = 12.7500; t(i) = 3.0000; i = i + 1
145    y(i) = 10.4200; t(i) = 4.0000; i = i + 1
146    y(i) = 7.3100; t(i) = 5.0000; i = i + 1
147    y(i) = 7.4200; t(i) = 6.0000; i = i + 1
148    y(i) = 70.5000; t(i) = .5000; i = i + 1
149    y(i) = 59.5000; t(i) = .7500; i = i + 1
150    y(i) = 48.5000; t(i) = 1.0000; i = i + 1
151    y(i) = 35.8000; t(i) = 1.5000; i = i + 1
152    y(i) = 21.0000; t(i) = 2.0000; i = i + 1
153    y(i) = 21.6700; t(i) = 2.0000; i = i + 1
154    y(i) = 21.0000; t(i) = 2.5000; i = i + 1
155    y(i) = 15.6400; t(i) = 3.0000; i = i + 1
156    y(i) = 8.1700; t(i) = 4.0000; i = i + 1
157    y(i) = 8.5500; t(i) = 5.0000; i = i + 1
158    y(i) = 10.1200; t(i) = 6.0000; i = i + 1
159    y(i) = 78.0000; t(i) = .5000; i = i + 1
160    y(i) = 66.0000; t(i) = .6250; i = i + 1
161    y(i) = 62.0000; t(i) = .7500; i = i + 1
162    y(i) = 58.0000; t(i) = .8750; i = i + 1
163    y(i) = 47.7000; t(i) = 1.0000; i = i + 1
164    y(i) = 37.8000; t(i) = 1.2500; i = i + 1
165    y(i) = 20.2000; t(i) = 2.2500; i = i + 1
166    y(i) = 21.0700; t(i) = 2.2500; i = i + 1
167    y(i) = 13.8700; t(i) = 2.7500; i = i + 1
168    y(i) = 9.6700; t(i) = 3.2500; i = i + 1
169    y(i) = 7.7600; t(i) = 3.7500; i = i + 1
170    y(i) = 5.4400; t(i) = 4.2500; i = i + 1
171    y(i) = 4.8700; t(i) = 4.7500; i = i + 1
172    y(i) = 4.0100; t(i) = 5.2500; i = i + 1
173    y(i) = 3.7500; t(i) = 5.7500; i = i + 1
174    y(i) = 24.1900; t(i) = 3.0000; i = i + 1
175    y(i) = 25.7600; t(i) = 3.0000; i = i + 1
176    y(i) = 18.0700; t(i) = 3.0000; i = i + 1
177    y(i) = 11.8100; t(i) = 3.0000; i = i + 1
178    y(i) = 12.0700; t(i) = 3.0000; i = i + 1
179    y(i) = 16.1200; t(i) = 3.0000; i = i + 1
180    y(i) = 70.8000; t(i) = .5000; i = i + 1
181    y(i) = 54.7000; t(i) = .7500; i = i + 1
182    y(i) = 48.0000; t(i) = 1.0000; i = i + 1
183    y(i) = 39.8000; t(i) = 1.5000; i = i + 1
184    y(i) = 29.8000; t(i) = 2.0000; i = i + 1
185    y(i) = 23.7000; t(i) = 2.5000; i = i + 1
186    y(i) = 29.6200; t(i) = 2.0000; i = i + 1
187    y(i) = 23.8100; t(i) = 2.5000; i = i + 1
188    y(i) = 17.7000; t(i) = 3.0000; i = i + 1
189    y(i) = 11.5500; t(i) = 4.0000; i = i + 1
190    y(i) = 12.0700; t(i) = 5.0000; i = i + 1
191    y(i) = 8.7400; t(i) = 6.0000; i = i + 1
192    y(i) = 80.7000; t(i) = .5000; i = i + 1
193    y(i) = 61.3000; t(i) = .7500; i = i + 1
194    y(i) = 47.5000; t(i) = 1.0000; i = i + 1
195    y(i) = 29.0000; t(i) = 1.5000; i = i + 1
196    y(i) = 24.0000; t(i) = 2.0000; i = i + 1
197    y(i) = 17.7000; t(i) = 2.5000; i = i + 1
198    y(i) = 24.5600; t(i) = 2.0000; i = i + 1
199    y(i) = 18.6700; t(i) = 2.5000; i = i + 1
200    y(i) = 16.2400; t(i) = 3.0000; i = i + 1
201    y(i) = 8.7400; t(i) = 4.0000; i = i + 1
202    y(i) = 7.8700; t(i) = 5.0000; i = i + 1
203    y(i) = 8.5100; t(i) = 6.0000; i = i + 1
204    y(i) = 66.7000; t(i) = .5000; i = i + 1
205    y(i) = 59.2000; t(i) = .7500; i = i + 1
206    y(i) = 40.8000; t(i) = 1.0000; i = i + 1
207    y(i) = 30.7000; t(i) = 1.5000; i = i + 1
208    y(i) = 25.7000; t(i) = 2.0000; i = i + 1
209    y(i) = 16.3000; t(i) = 2.5000; i = i + 1
210    y(i) = 25.9900; t(i) = 2.0000; i = i + 1
211    y(i) = 16.9500; t(i) = 2.5000; i = i + 1
212    y(i) = 13.3500; t(i) = 3.0000; i = i + 1
213    y(i) = 8.6200; t(i) = 4.0000; i = i + 1
214    y(i) = 7.2000; t(i) = 5.0000; i = i + 1
215    y(i) = 6.6400; t(i) = 6.0000; i = i + 1
216    y(i) = 13.6900; t(i) = 3.0000; i = i + 1
217    y(i) = 81.0000; t(i) = .5000; i = i + 1
218    y(i) = 64.5000; t(i) = .7500; i = i + 1
219    y(i) = 35.5000; t(i) = 1.5000; i = i + 1
220    y(i) = 13.3100; t(i) = 3.0000; i = i + 1
221    y(i) = 4.8700; t(i) = 6.0000; i = i + 1
222    y(i) = 12.9400; t(i) = 3.0000; i = i + 1
223    y(i) = 5.0600; t(i) = 6.0000; i = i + 1
224    y(i) = 15.1900; t(i) = 3.0000; i = i + 1
225    y(i) = 14.6200; t(i) = 3.0000; i = i + 1
226    y(i) = 15.6400; t(i) = 3.0000; i = i + 1
227    y(i) = 25.5000; t(i) = 1.7500; i = i + 1
228    y(i) = 25.9500; t(i) = 1.7500; i = i + 1
229    y(i) = 81.7000; t(i) = .5000; i = i + 1
230    y(i) = 61.6000; t(i) = .7500; i = i + 1
231    y(i) = 29.8000; t(i) = 1.7500; i = i + 1
232    y(i) = 29.8100; t(i) = 1.7500; i = i + 1
233    y(i) = 17.1700; t(i) = 2.7500; i = i + 1
234    y(i) = 10.3900; t(i) = 3.7500; i = i + 1
235    y(i) = 28.4000; t(i) = 1.7500; i = i + 1
236    y(i) = 28.6900; t(i) = 1.7500; i = i + 1
237    y(i) = 81.3000; t(i) = .5000; i = i + 1
238    y(i) = 60.9000; t(i) = .7500; i = i + 1
239    y(i) = 16.6500; t(i) = 2.7500; i = i + 1
240    y(i) = 10.0500; t(i) = 3.7500; i = i + 1
241    y(i) = 28.9000; t(i) = 1.7500; i = i + 1
242    y(i) = 28.9500; t(i) = 1.7500; i = i + 1
243
244  end
245
246  subroutine TaskWorker(ierr)
247
248    PetscErrorCode ierr
249    PetscReal x(n), f(1)
250    PetscMPIInt tag
251    PetscInt index
252    PetscMPIInt status(MPI_STATUS_SIZE)
253
254    tag = IDLE_TAG
255    f = 0.0
256    ! Send check-in message to rank-0
257    PetscCallMPI(MPI_Send(f, one, MPIU_SCALAR, zero, IDLE_TAG, PETSC_COMM_WORLD, ierr))
258    do while (tag /= DIE_TAG)
259      PetscCallMPI(MPI_Recv(x, nn, MPIU_SCALAR, zero, MPI_ANY_TAG, PETSC_COMM_WORLD, status, ierr))
260      tag = status(MPI_TAG)
261      if (tag == IDLE_TAG) then
262        PetscCallMPI(MPI_Send(f, one, MPIU_SCALAR, zero, IDLE_TAG, PETSC_COMM_WORLD, ierr))
263      else if (tag /= DIE_TAG) then
264        index = tag
265        ! Compute local part of residual
266        PetscCall(RunSimulation(x, index, f(1), ierr))
267
268        ! Return residual to rank-0
269        PetscCallMPI(MPI_Send(f, one, MPIU_SCALAR, zero, tag, PETSC_COMM_WORLD, ierr))
270      end if
271    end do
272    ierr = 0
273  end
274
275  subroutine RunSimulation(x, i, f, ierr)
276
277    PetscReal x(n), f
278    PetscInt i
279    PetscErrorCode ierr
280    f = y(i) - exp(-x(1)*t(i))/(x(2) + x(3)*t(i))
281    ierr = 0
282  end
283
284  subroutine StopWorkers(ierr)
285
286    integer checkedin
287    PetscMPIInt status(MPI_STATUS_SIZE)
288    PetscMPIInt source
289    PetscReal f(1), x(n)
290    PetscErrorCode ierr
291    PetscInt i
292
293    checkedin = 0
294    do while (checkedin < size - 1)
295      PetscCallMPI(MPI_Recv(f, one, MPIU_SCALAR, MPI_ANY_SOURCE, MPI_ANY_TAG, PETSC_COMM_WORLD, status, ierr))
296      checkedin = checkedin + 1
297      source = status(MPI_SOURCE)
298      do i = 1, n
299        x(i) = 0.0
300      end do
301      PetscCallMPI(MPI_Send(x, nn, MPIU_SCALAR, source, DIE_TAG, PETSC_COMM_WORLD, ierr))
302    end do
303    ierr = 0
304  end
305
306! --------------------------------------------------------------------
307!  FormFunction - Evaluates the function f(X) and gradient G(X)
308!
309!  Input Parameters:
310!  tao - the Tao context
311!  X   - input vector
312!  dummy - not used
313!
314!  Output Parameters:
315!  f - function vector
316
317  subroutine FormFunction(ta, x, f, dummy, ierr)
318
319    Tao ta
320    Vec x, f
321    PetscErrorCode ierr
322
323    PetscInt i, checkedin
324    PetscInt finished_tasks
325    PetscMPIInt next_task
326    PetscMPIInt status(MPI_STATUS_SIZE), tag, source
327    PetscInt dummy
328
329    PetscReal, pointer :: f_v(:), x_v(:)
330    PetscReal fval(1)
331
332    ierr = 0
333
334!     Get pointers to vector data
335    PetscCall(VecGetArrayRead(x, x_v, ierr))
336    PetscCall(VecGetArray(f, f_v, ierr))
337
338!     Compute F(X)
339    if (size == 1) then
340      ! Single processor
341      do i = 1, m
342        PetscCall(RunSimulation(x_v, i, f_v(i), ierr))
343      end do
344    else
345      ! Multiprocessor main
346      next_task = zero
347      finished_tasks = 0
348      checkedin = 0
349
350      do while (finished_tasks < m .or. checkedin < size - 1)
351        PetscCallMPI(MPI_Recv(fval, one, MPIU_SCALAR, MPI_ANY_SOURCE, MPI_ANY_TAG, PETSC_COMM_WORLD, status, ierr))
352        tag = status(MPI_TAG)
353        source = status(MPI_SOURCE)
354        if (tag == IDLE_TAG) then
355          checkedin = checkedin + 1
356        else
357          f_v(tag + 1) = fval(1)
358          finished_tasks = finished_tasks + 1
359        end if
360        if (next_task < m) then
361          ! Send task to worker
362          PetscCallMPI(MPI_Send(x_v, nn, MPIU_SCALAR, source, next_task, PETSC_COMM_WORLD, ierr))
363          next_task = next_task + one
364        else
365          ! Send idle message to worker
366          PetscCallMPI(MPI_Send(x_v, nn, MPIU_SCALAR, source, IDLE_TAG, PETSC_COMM_WORLD, ierr))
367        end if
368      end do
369    end if
370
371!     Restore vectors
372    PetscCall(VecRestoreArrayRead(x, x_v, ierr))
373    PetscCall(VecRestoreArray(F, f_v, ierr))
374  end
375
376  subroutine FormStartingPoint(x)
377
378    Vec x
379    PetscReal, pointer :: x_v(:)
380    PetscErrorCode ierr
381
382    PetscCall(VecGetArray(x, x_v, ierr))
383    x_v(1) = 0.15
384    x_v(2) = 0.008
385    x_v(3) = 0.01
386    PetscCall(VecRestoreArray(x, x_v, ierr))
387  end
388end module chwirut2fmodule
389
390program main
391  use chwirut2fmodule
392  implicit none
393! - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
394!                   Variable declarations
395! - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
396!
397!  See additional variable declarations in the file chwirut2f.h
398
399  PetscErrorCode ierr    ! used to check for functions returning nonzeros
400  Vec x       ! solution vector
401  Vec f       ! vector of functions
402  Tao ta     ! Tao context
403
404!  Initialize TAO and PETSc
405  PetscCallA(PetscInitialize(ierr))
406  PetscCallMPIA(MPI_Comm_size(PETSC_COMM_WORLD, size, ierr))
407  PetscCallMPIA(MPI_Comm_rank(PETSC_COMM_WORLD, rank, ierr))
408
409!  Initialize problem parameters
410  call InitializeData()
411
412  if (rank == 0) then
413!  Allocate vectors for the solution and gradient
414    PetscCallA(VecCreateSeq(PETSC_COMM_SELF, n, x, ierr))
415    PetscCallA(VecCreateSeq(PETSC_COMM_SELF, m, f, ierr))
416
417!     The TAO code begins here
418
419!     Create TAO solver
420    PetscCallA(TaoCreate(PETSC_COMM_SELF, ta, ierr))
421    PetscCallA(TaoSetType(ta, TAOPOUNDERS, ierr))
422
423!     Set routines for function, gradient, and hessian evaluation
424    PetscCallA(TaoSetResidualRoutine(ta, f, FormFunction, 0, ierr))
425
426!     Optional: Set initial guess
427    call FormStartingPoint(x)
428    PetscCallA(TaoSetSolution(ta, x, ierr))
429
430!     Check for TAO command line options
431    PetscCallA(TaoSetFromOptions(ta, ierr))
432!     SOLVE THE APPLICATION
433    PetscCallA(TaoSolve(ta, ierr))
434
435!     Free TAO data structures
436    PetscCallA(TaoDestroy(ta, ierr))
437
438!     Free PETSc data structures
439    PetscCallA(VecDestroy(x, ierr))
440    PetscCallA(VecDestroy(f, ierr))
441    PetscCallA(StopWorkers(ierr))
442
443  else
444    PetscCallA(TaskWorker(ierr))
445  end if
446
447  PetscCallA(PetscFinalize(ierr))
448end
449!/*TEST
450!
451!   build:
452!      requires: !complex
453!
454!   test:
455!      nsize: 3
456!      args: -tao_monitor_short -tao_max_it 100 -tao_type pounders -tao_gatol 1.e-5
457!      requires: !single
458!
459!
460!TEST*/
461