Actual source code: chwirut2f.F90
petsc-3.9.4 2018-09-11
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: !!/*T
11: ! Concepts: TAO^Solving an unconstrained minimization problem
12: ! Routines: TaoCreate();
13: ! Routines: TaoSetType();
14: ! Routines: TaoSetSeparableObjectiveRoutine();
15: ! Routines: TaoSetInitialVector();
16: ! Routines: TaoSetFromOptions();
17: ! Routines: TaoSolve();
18: ! Routines: TaoDestroy();
19: ! Processors: n
20: !T*/
23: !
24: ! ----------------------------------------------------------------------
25: !
26: #include "chwirut2f.h"
28: ! - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
29: ! Variable declarations
30: ! - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
31: !
32: ! See additional variable declarations in the file chwirut2f.h
34: PetscErrorCode ierr ! used to check for functions returning nonzeros
35: Vec x ! solution vector
36: Vec f ! vector of functions
37: Tao tao ! Tao context
39: ! Note: Any user-defined Fortran routines (such as FormGradient)
40: ! MUST be declared as external.
42: external FormFunction
44: ! Initialize TAO and PETSc
45: call PetscInitialize(PETSC_NULL_CHARACTER,ierr)
46: if (ierr .ne. 0) then
47: print*,'Unable to initialize PETSc'
48: stop
49: endif
51: call MPI_Comm_size(PETSC_COMM_WORLD,size,ierr)
52: CHKERRA(ierr)
53: call MPI_Comm_rank(PETSC_COMM_WORLD,rank,ierr)
54: CHKERRA(ierr)
56: ! Initialize problem parameters
57: call InitializeData()
59: if (rank .eq. 0) then
60: ! Allocate vectors for the solution and gradient
61: call VecCreateSeq(PETSC_COMM_SELF,n,x,ierr)
62: CHKERRA(ierr)
63: call VecCreateSeq(PETSC_COMM_SELF,m,f,ierr)
64: CHKERRA(ierr)
67: ! The TAO code begins here
69: ! Create TAO solver
70: call TaoCreate(PETSC_COMM_SELF,tao,ierr)
71: CHKERRA(ierr)
72: call TaoSetType(tao,TAOPOUNDERS,ierr)
73: CHKERRA(ierr)
75: ! Set routines for function, gradient, and hessian evaluation
76: call TaoSetSeparableObjectiveRoutine(tao,f, &
77: & FormFunction,0,ierr)
78: CHKERRA(ierr)
80: ! Optional: Set initial guess
81: call FormStartingPoint(x)
82: call TaoSetInitialVector(tao, x, ierr)
83: CHKERRA(ierr)
86: ! Check for TAO command line options
87: call TaoSetFromOptions(tao,ierr)
88: CHKERRA(ierr)
89: ! SOLVE THE APPLICATION
90: call TaoSolve(tao,ierr)
91: CHKERRA(ierr)
93: ! Free TAO data structures
94: call TaoDestroy(tao,ierr)
95: CHKERRA(ierr)
97: ! Free PETSc data structures
98: call VecDestroy(x,ierr)
99: CHKERRA(ierr)
100: call VecDestroy(f,ierr)
101: CHKERRA(ierr)
102: call StopWorkers(ierr)
103: CHKERRA(ierr)
105: else
106: call TaskWorker(ierr)
107: CHKERRA(ierr)
108: endif
110: call PetscFinalize(ierr)
111: end
114: ! --------------------------------------------------------------------
115: ! FormFunction - Evaluates the function f(X) and gradient G(X)
116: !
117: ! Input Parameters:
118: ! tao - the Tao context
119: ! X - input vector
120: ! dummy - not used
121: !
122: ! Output Parameters:
123: ! f - function vector
125: subroutine FormFunction(tao, x, f, dummy, ierr)
126: #include "chwirut2f.h"
128: Tao tao
129: Vec x,f
130: PetscErrorCode ierr
131: PetscInt dummy
133: PetscInt i,checkedin
134: PetscInt finished_tasks
135: integer next_task,status(MPI_STATUS_SIZE),tag,source
137: ! PETSc's VecGetArray acts differently in Fortran than it does in C.
138: ! Calling VecGetArray((Vec) X, (PetscReal) x_array(0:1), (PetscOffset) x_index, ierr)
139: ! will return an array of doubles referenced by x_array offset by x_index.
140: ! i.e., to reference the kth element of X, use x_array(k + x_index).
141: ! Notice that by declaring the arrays with range (0:1), we are using the C 0-indexing practice.
142: PetscReal f_v(0:1),x_v(0:1),fval
143: PetscOffset f_i,x_i
145: 0
147: ! Get pointers to vector data
148: call VecGetArray(x,x_v,x_i,ierr)
149: CHKERRQ(ierr)
150: call VecGetArray(f,f_v,f_i,ierr)
151: CHKERRQ(ierr)
154: ! Compute F(X)
155: if (size .eq. 1) then
156: ! Single processor
157: do i=0,m-1
158: call RunSimulation(x_v(x_i),i,f_v(i+f_i),ierr)
159: enddo
160: else
161: ! Multiprocessor master
162: next_task = 0
163: finished_tasks = 0
164: checkedin = 0
166: do while (finished_tasks .lt. m .or. checkedin .lt. size-1)
167: call MPI_Recv(fval,1,MPIU_SCALAR,MPI_ANY_SOURCE, &
168: & MPI_ANY_TAG,PETSC_COMM_WORLD,status,ierr)
169: tag = status(MPI_TAG)
170: source = status(MPI_SOURCE)
171: if (tag .eq. IDLE_TAG) then
172: checkedin = checkedin + 1
173: else
174: f_v(f_i+tag) = fval
175: finished_tasks = finished_tasks + 1
176: endif
177: if (next_task .lt. m) then
178: ! Send task to worker
179: call MPI_Send(x_v(x_i),n,MPIU_SCALAR,source,next_task, &
180: & PETSC_COMM_WORLD,ierr)
181: next_task = next_task + 1
182: else
183: ! Send idle message to worker
184: call MPI_Send(x_v(x_i),n,MPIU_SCALAR,source,IDLE_TAG, &
185: & PETSC_COMM_WORLD,ierr)
186: end if
187: enddo
188: endif
190: ! Restore vectors
191: call VecRestoreArray(x,x_v,x_i,ierr)
192: CHKERRQ(ierr)
193: call VecRestoreArray(F,f_v,f_i,ierr)
194: CHKERRQ(ierr)
195: return
196: end
198: subroutine FormStartingPoint(x)
199: #include "chwirut2f.h"
201: Vec x
202: PetscReal x_v(0:1)
203: PetscOffset x_i
204: PetscErrorCode ierr
206: call VecGetArray(x,x_v,x_i,ierr)
207: CHKERRQ(ierr)
208: x_v(x_i) = 0.15
209: x_v(x_i+1) = 0.008
210: x_v(x_i+2) = 0.01
211: call VecRestoreArray(x,x_v,x_i,ierr)
212: CHKERRQ(ierr)
213: return
214: end
217: subroutine InitializeData()
218: #include "chwirut2f.h"
220: PetscInt i
221: i=0
222: y(i) = 92.9000; t(i) = 0.5000; i=i+1
223: y(i) = 78.7000; t(i) = 0.6250; i=i+1
224: y(i) = 64.2000; t(i) = 0.7500; i=i+1
225: y(i) = 64.9000; t(i) = 0.8750; i=i+1
226: y(i) = 57.1000; t(i) = 1.0000; i=i+1
227: y(i) = 43.3000; t(i) = 1.2500; i=i+1
228: y(i) = 31.1000; t(i) = 1.7500; i=i+1
229: y(i) = 23.6000; t(i) = 2.2500; i=i+1
230: y(i) = 31.0500; t(i) = 1.7500; i=i+1
231: y(i) = 23.7750; t(i) = 2.2500; i=i+1
232: y(i) = 17.7375; t(i) = 2.7500; i=i+1
233: y(i) = 13.8000; t(i) = 3.2500; i=i+1
234: y(i) = 11.5875; t(i) = 3.7500; i=i+1
235: y(i) = 9.4125; t(i) = 4.2500; i=i+1
236: y(i) = 7.7250; t(i) = 4.7500; i=i+1
237: y(i) = 7.3500; t(i) = 5.2500; i=i+1
238: y(i) = 8.0250; t(i) = 5.7500; i=i+1
239: y(i) = 90.6000; t(i) = 0.5000; i=i+1
240: y(i) = 76.9000; t(i) = 0.6250; i=i+1
241: y(i) = 71.6000; t(i) = 0.7500; i=i+1
242: y(i) = 63.6000; t(i) = 0.8750; i=i+1
243: y(i) = 54.0000; t(i) = 1.0000; i=i+1
244: y(i) = 39.2000; t(i) = 1.2500; i=i+1
245: y(i) = 29.3000; t(i) = 1.7500; i=i+1
246: y(i) = 21.4000; t(i) = 2.2500; i=i+1
247: y(i) = 29.1750; t(i) = 1.7500; i=i+1
248: y(i) = 22.1250; t(i) = 2.2500; i=i+1
249: y(i) = 17.5125; t(i) = 2.7500; i=i+1
250: y(i) = 14.2500; t(i) = 3.2500; i=i+1
251: y(i) = 9.4500; t(i) = 3.7500; i=i+1
252: y(i) = 9.1500; t(i) = 4.2500; i=i+1
253: y(i) = 7.9125; t(i) = 4.7500; i=i+1
254: y(i) = 8.4750; t(i) = 5.2500; i=i+1
255: y(i) = 6.1125; t(i) = 5.7500; i=i+1
256: y(i) = 80.0000; t(i) = 0.5000; i=i+1
257: y(i) = 79.0000; t(i) = 0.6250; i=i+1
258: y(i) = 63.8000; t(i) = 0.7500; i=i+1
259: y(i) = 57.2000; t(i) = 0.8750; i=i+1
260: y(i) = 53.2000; t(i) = 1.0000; i=i+1
261: y(i) = 42.5000; t(i) = 1.2500; i=i+1
262: y(i) = 26.8000; t(i) = 1.7500; i=i+1
263: y(i) = 20.4000; t(i) = 2.2500; i=i+1
264: y(i) = 26.8500; t(i) = 1.7500; i=i+1
265: y(i) = 21.0000; t(i) = 2.2500; i=i+1
266: y(i) = 16.4625; t(i) = 2.7500; i=i+1
267: y(i) = 12.5250; t(i) = 3.2500; i=i+1
268: y(i) = 10.5375; t(i) = 3.7500; i=i+1
269: y(i) = 8.5875; t(i) = 4.2500; i=i+1
270: y(i) = 7.1250; t(i) = 4.7500; i=i+1
271: y(i) = 6.1125; t(i) = 5.2500; i=i+1
272: y(i) = 5.9625; t(i) = 5.7500; i=i+1
273: y(i) = 74.1000; t(i) = 0.5000; i=i+1
274: y(i) = 67.3000; t(i) = 0.6250; i=i+1
275: y(i) = 60.8000; t(i) = 0.7500; i=i+1
276: y(i) = 55.5000; t(i) = 0.8750; i=i+1
277: y(i) = 50.3000; t(i) = 1.0000; i=i+1
278: y(i) = 41.0000; t(i) = 1.2500; i=i+1
279: y(i) = 29.4000; t(i) = 1.7500; i=i+1
280: y(i) = 20.4000; t(i) = 2.2500; i=i+1
281: y(i) = 29.3625; t(i) = 1.7500; i=i+1
282: y(i) = 21.1500; t(i) = 2.2500; i=i+1
283: y(i) = 16.7625; t(i) = 2.7500; i=i+1
284: y(i) = 13.2000; t(i) = 3.2500; i=i+1
285: y(i) = 10.8750; t(i) = 3.7500; i=i+1
286: y(i) = 8.1750; t(i) = 4.2500; i=i+1
287: y(i) = 7.3500; t(i) = 4.7500; i=i+1
288: y(i) = 5.9625; t(i) = 5.2500; i=i+1
289: y(i) = 5.6250; t(i) = 5.7500; i=i+1
290: y(i) = 81.5000; t(i) = .5000; i=i+1
291: y(i) = 62.4000; t(i) = .7500; i=i+1
292: y(i) = 32.5000; t(i) = 1.5000; i=i+1
293: y(i) = 12.4100; t(i) = 3.0000; i=i+1
294: y(i) = 13.1200; t(i) = 3.0000; i=i+1
295: y(i) = 15.5600; t(i) = 3.0000; i=i+1
296: y(i) = 5.6300; t(i) = 6.0000; i=i+1
297: y(i) = 78.0000; t(i) = .5000; i=i+1
298: y(i) = 59.9000; t(i) = .7500; i=i+1
299: y(i) = 33.2000; t(i) = 1.5000; i=i+1
300: y(i) = 13.8400; t(i) = 3.0000; i=i+1
301: y(i) = 12.7500; t(i) = 3.0000; i=i+1
302: y(i) = 14.6200; t(i) = 3.0000; i=i+1
303: y(i) = 3.9400; t(i) = 6.0000; i=i+1
304: y(i) = 76.8000; t(i) = .5000; i=i+1
305: y(i) = 61.0000; t(i) = .7500; i=i+1
306: y(i) = 32.9000; t(i) = 1.5000; i=i+1
307: y(i) = 13.8700; t(i) = 3.0000; i=i+1
308: y(i) = 11.8100; t(i) = 3.0000; i=i+1
309: y(i) = 13.3100; t(i) = 3.0000; i=i+1
310: y(i) = 5.4400; t(i) = 6.0000; i=i+1
311: y(i) = 78.0000; t(i) = .5000; i=i+1
312: y(i) = 63.5000; t(i) = .7500; i=i+1
313: y(i) = 33.8000; t(i) = 1.5000; i=i+1
314: y(i) = 12.5600; t(i) = 3.0000; i=i+1
315: y(i) = 5.6300; t(i) = 6.0000; i=i+1
316: y(i) = 12.7500; t(i) = 3.0000; i=i+1
317: y(i) = 13.1200; t(i) = 3.0000; i=i+1
318: y(i) = 5.4400; t(i) = 6.0000; i=i+1
319: y(i) = 76.8000; t(i) = .5000; i=i+1
320: y(i) = 60.0000; t(i) = .7500; i=i+1
321: y(i) = 47.8000; t(i) = 1.0000; i=i+1
322: y(i) = 32.0000; t(i) = 1.5000; i=i+1
323: y(i) = 22.2000; t(i) = 2.0000; i=i+1
324: y(i) = 22.5700; t(i) = 2.0000; i=i+1
325: y(i) = 18.8200; t(i) = 2.5000; i=i+1
326: y(i) = 13.9500; t(i) = 3.0000; i=i+1
327: y(i) = 11.2500; t(i) = 4.0000; i=i+1
328: y(i) = 9.0000; t(i) = 5.0000; i=i+1
329: y(i) = 6.6700; t(i) = 6.0000; i=i+1
330: y(i) = 75.8000; t(i) = .5000; i=i+1
331: y(i) = 62.0000; t(i) = .7500; i=i+1
332: y(i) = 48.8000; t(i) = 1.0000; i=i+1
333: y(i) = 35.2000; t(i) = 1.5000; i=i+1
334: y(i) = 20.0000; t(i) = 2.0000; i=i+1
335: y(i) = 20.3200; t(i) = 2.0000; i=i+1
336: y(i) = 19.3100; t(i) = 2.5000; i=i+1
337: y(i) = 12.7500; t(i) = 3.0000; i=i+1
338: y(i) = 10.4200; t(i) = 4.0000; i=i+1
339: y(i) = 7.3100; t(i) = 5.0000; i=i+1
340: y(i) = 7.4200; t(i) = 6.0000; i=i+1
341: y(i) = 70.5000; t(i) = .5000; i=i+1
342: y(i) = 59.5000; t(i) = .7500; i=i+1
343: y(i) = 48.5000; t(i) = 1.0000; i=i+1
344: y(i) = 35.8000; t(i) = 1.5000; i=i+1
345: y(i) = 21.0000; t(i) = 2.0000; i=i+1
346: y(i) = 21.6700; t(i) = 2.0000; i=i+1
347: y(i) = 21.0000; t(i) = 2.5000; i=i+1
348: y(i) = 15.6400; t(i) = 3.0000; i=i+1
349: y(i) = 8.1700; t(i) = 4.0000; i=i+1
350: y(i) = 8.5500; t(i) = 5.0000; i=i+1
351: y(i) = 10.1200; t(i) = 6.0000; i=i+1
352: y(i) = 78.0000; t(i) = .5000; i=i+1
353: y(i) = 66.0000; t(i) = .6250; i=i+1
354: y(i) = 62.0000; t(i) = .7500; i=i+1
355: y(i) = 58.0000; t(i) = .8750; i=i+1
356: y(i) = 47.7000; t(i) = 1.0000; i=i+1
357: y(i) = 37.8000; t(i) = 1.2500; i=i+1
358: y(i) = 20.2000; t(i) = 2.2500; i=i+1
359: y(i) = 21.0700; t(i) = 2.2500; i=i+1
360: y(i) = 13.8700; t(i) = 2.7500; i=i+1
361: y(i) = 9.6700; t(i) = 3.2500; i=i+1
362: y(i) = 7.7600; t(i) = 3.7500; i=i+1
363: y(i) = 5.4400; t(i) = 4.2500; i=i+1
364: y(i) = 4.8700; t(i) = 4.7500; i=i+1
365: y(i) = 4.0100; t(i) = 5.2500; i=i+1
366: y(i) = 3.7500; t(i) = 5.7500; i=i+1
367: y(i) = 24.1900; t(i) = 3.0000; i=i+1
368: y(i) = 25.7600; t(i) = 3.0000; i=i+1
369: y(i) = 18.0700; t(i) = 3.0000; i=i+1
370: y(i) = 11.8100; t(i) = 3.0000; i=i+1
371: y(i) = 12.0700; t(i) = 3.0000; i=i+1
372: y(i) = 16.1200; t(i) = 3.0000; i=i+1
373: y(i) = 70.8000; t(i) = .5000; i=i+1
374: y(i) = 54.7000; t(i) = .7500; i=i+1
375: y(i) = 48.0000; t(i) = 1.0000; i=i+1
376: y(i) = 39.8000; t(i) = 1.5000; i=i+1
377: y(i) = 29.8000; t(i) = 2.0000; i=i+1
378: y(i) = 23.7000; t(i) = 2.5000; i=i+1
379: y(i) = 29.6200; t(i) = 2.0000; i=i+1
380: y(i) = 23.8100; t(i) = 2.5000; i=i+1
381: y(i) = 17.7000; t(i) = 3.0000; i=i+1
382: y(i) = 11.5500; t(i) = 4.0000; i=i+1
383: y(i) = 12.0700; t(i) = 5.0000; i=i+1
384: y(i) = 8.7400; t(i) = 6.0000; i=i+1
385: y(i) = 80.7000; t(i) = .5000; i=i+1
386: y(i) = 61.3000; t(i) = .7500; i=i+1
387: y(i) = 47.5000; t(i) = 1.0000; i=i+1
388: y(i) = 29.0000; t(i) = 1.5000; i=i+1
389: y(i) = 24.0000; t(i) = 2.0000; i=i+1
390: y(i) = 17.7000; t(i) = 2.5000; i=i+1
391: y(i) = 24.5600; t(i) = 2.0000; i=i+1
392: y(i) = 18.6700; t(i) = 2.5000; i=i+1
393: y(i) = 16.2400; t(i) = 3.0000; i=i+1
394: y(i) = 8.7400; t(i) = 4.0000; i=i+1
395: y(i) = 7.8700; t(i) = 5.0000; i=i+1
396: y(i) = 8.5100; t(i) = 6.0000; i=i+1
397: y(i) = 66.7000; t(i) = .5000; i=i+1
398: y(i) = 59.2000; t(i) = .7500; i=i+1
399: y(i) = 40.8000; t(i) = 1.0000; i=i+1
400: y(i) = 30.7000; t(i) = 1.5000; i=i+1
401: y(i) = 25.7000; t(i) = 2.0000; i=i+1
402: y(i) = 16.3000; t(i) = 2.5000; i=i+1
403: y(i) = 25.9900; t(i) = 2.0000; i=i+1
404: y(i) = 16.9500; t(i) = 2.5000; i=i+1
405: y(i) = 13.3500; t(i) = 3.0000; i=i+1
406: y(i) = 8.6200; t(i) = 4.0000; i=i+1
407: y(i) = 7.2000; t(i) = 5.0000; i=i+1
408: y(i) = 6.6400; t(i) = 6.0000; i=i+1
409: y(i) = 13.6900; t(i) = 3.0000; i=i+1
410: y(i) = 81.0000; t(i) = .5000; i=i+1
411: y(i) = 64.5000; t(i) = .7500; i=i+1
412: y(i) = 35.5000; t(i) = 1.5000; i=i+1
413: y(i) = 13.3100; t(i) = 3.0000; i=i+1
414: y(i) = 4.8700; t(i) = 6.0000; i=i+1
415: y(i) = 12.9400; t(i) = 3.0000; i=i+1
416: y(i) = 5.0600; t(i) = 6.0000; i=i+1
417: y(i) = 15.1900; t(i) = 3.0000; i=i+1
418: y(i) = 14.6200; t(i) = 3.0000; i=i+1
419: y(i) = 15.6400; t(i) = 3.0000; i=i+1
420: y(i) = 25.5000; t(i) = 1.7500; i=i+1
421: y(i) = 25.9500; t(i) = 1.7500; i=i+1
422: y(i) = 81.7000; t(i) = .5000; i=i+1
423: y(i) = 61.6000; t(i) = .7500; i=i+1
424: y(i) = 29.8000; t(i) = 1.7500; i=i+1
425: y(i) = 29.8100; t(i) = 1.7500; i=i+1
426: y(i) = 17.1700; t(i) = 2.7500; i=i+1
427: y(i) = 10.3900; t(i) = 3.7500; i=i+1
428: y(i) = 28.4000; t(i) = 1.7500; i=i+1
429: y(i) = 28.6900; t(i) = 1.7500; i=i+1
430: y(i) = 81.3000; t(i) = .5000; i=i+1
431: y(i) = 60.9000; t(i) = .7500; i=i+1
432: y(i) = 16.6500; t(i) = 2.7500; i=i+1
433: y(i) = 10.0500; t(i) = 3.7500; i=i+1
434: y(i) = 28.9000; t(i) = 1.7500; i=i+1
435: y(i) = 28.9500; t(i) = 1.7500; i=i+1
437: return
438: end
442: subroutine TaskWorker(ierr)
443: #include "chwirut2f.h"
445: PetscErrorCode ierr
446: PetscReal x(n),f
447: integer tag
448: PetscInt index
449: integer status(MPI_STATUS_SIZE)
451: tag = IDLE_TAG
452: f = 0.0
453: ! Send check-in message to master
454: call MPI_Send(f,1,MPIU_SCALAR,0,IDLE_TAG,PETSC_COMM_WORLD,ierr)
455: CHKERRQ(ierr)
456: do while (tag .ne. DIE_TAG)
457: call MPI_Recv(x,n,MPIU_SCALAR,0,MPI_ANY_TAG,PETSC_COMM_WORLD, &
458: & status,ierr)
459: CHKERRQ(ierr)
460: tag = status(MPI_TAG)
461: if (tag .eq. IDLE_TAG) then
462: call MPI_Send(f,1,MPIU_SCALAR,0,IDLE_TAG,PETSC_COMM_WORLD, &
463: & ierr)
464: CHKERRQ(ierr)
465: else if (tag .ne. DIE_TAG) then
466: index = tag
467: ! Compute local part of residual
468: call RunSimulation(x,index,f,ierr)
469: CHKERRQ(ierr)
471: ! Return residual to master
472: call MPI_Send(f,1,MPIU_SCALAR,0,tag,PETSC_COMM_WORLD,ierr)
473: CHKERRQ(ierr)
474: end if
475: enddo
476: 0
477: return
478: end
482: subroutine RunSimulation(x,i,f,ierr)
483: #include "chwirut2f.h"
485: PetscReal x(n),f
486: PetscInt i
487: PetscErrorCode ierr
488: f = y(i) - exp(-x(1)*t(i))/(x(2)+x(3)*t(i))
489: 0
490: return
491: end
493: subroutine StopWorkers(ierr)
494: #include "chwirut2f.h"
496: integer checkedin
497: integer status(MPI_STATUS_SIZE)
498: integer source
499: PetscReal f,x(n)
500: PetscErrorCode ierr
501: PetscInt i
503: checkedin=0
504: do while (checkedin .lt. size-1)
505: call MPI_Recv(f,1,MPIU_SCALAR,MPI_ANY_SOURCE,MPI_ANY_TAG, &
506: & PETSC_COMM_WORLD,status,ierr)
507: CHKERRQ(ierr)
508: checkedin=checkedin+1
509: source = status(MPI_SOURCE)
510: do i=1,n
511: x(i) = 0.0
512: enddo
513: call MPI_Send(x,n,MPIU_SCALAR,source,DIE_TAG,PETSC_COMM_WORLD, &
514: & ierr)
515: CHKERRQ(ierr)
516: enddo
517: ierr=0
518: return
519: end
521: !/*TEST
522: !
523: ! build:
524: ! requires: !complex
525: !
526: ! test:
527: ! nsize: 3
528: ! args: -tao_smonitor -tao_max_it 100 -tao_type pounders
529: ! requires: !single
530: ! TODO: produces too many inconsistent results across machines/OS/compilers
531: !
532: !
533: !TEST*/