Actual source code: gpcg.c
petsc-dev 2014-02-02
1: #include <petsc-private/kspimpl.h>
2: #include <../src/tao/bound/impls/gpcg/gpcg.h> /*I "gpcg.h" I*/
5: static PetscErrorCode GPCGGradProjections(Tao tao);
6: static PetscErrorCode GPCGObjectiveAndGradient(TaoLineSearch,Vec,PetscReal*,Vec,void*);
8: /*------------------------------------------------------------*/
11: static PetscErrorCode TaoDestroy_GPCG(Tao tao)
12: {
13: TAO_GPCG *gpcg = (TAO_GPCG *)tao->data;
16: /* Free allocated memory in GPCG structure */
18: VecDestroy(&gpcg->B);
19: VecDestroy(&gpcg->Work);
20: VecDestroy(&gpcg->X_New);
21: VecDestroy(&gpcg->G_New);
22: VecDestroy(&gpcg->DXFree);
23: VecDestroy(&gpcg->R);
24: VecDestroy(&gpcg->PG);
25: MatDestroy(&gpcg->Hsub);
26: MatDestroy(&gpcg->Hsub_pre);
27: ISDestroy(&gpcg->Free_Local);
28: PetscFree(tao->data);
29: tao->data = NULL;
30: return(0);
31: }
33: /*------------------------------------------------------------*/
36: static PetscErrorCode TaoSetFromOptions_GPCG(Tao tao)
37: {
38: TAO_GPCG *gpcg = (TAO_GPCG *)tao->data;
40: PetscBool flg;
43: PetscOptionsHead("Gradient Projection, Conjugate Gradient method for bound constrained optimization");
44: ierr=PetscOptionsInt("-gpcg_maxpgits","maximum number of gradient projections per GPCG iterate",0,gpcg->maxgpits,&gpcg->maxgpits,&flg);
45: PetscOptionsTail();
46: TaoLineSearchSetFromOptions(tao->linesearch);
47: return(0);
48: }
50: /*------------------------------------------------------------*/
53: static PetscErrorCode TaoView_GPCG(Tao tao, PetscViewer viewer)
54: {
55: TAO_GPCG *gpcg = (TAO_GPCG *)tao->data;
56: PetscBool isascii;
60: PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERASCII,&isascii);
61: if (isascii) {
62: PetscViewerASCIIPushTab(viewer);
63: PetscViewerASCIIPrintf(viewer,"Total PG its: %D,",gpcg->total_gp_its);
64: PetscViewerASCIIPrintf(viewer,"PG tolerance: %g \n",(double)gpcg->pg_ftol);
65: PetscViewerASCIIPopTab(viewer);
66: }
67: TaoLineSearchView(tao->linesearch,viewer);
68: return(0);
69: }
71: /* GPCGObjectiveAndGradient()
72: Compute f=0.5 * x'Hx + b'x + c
73: g=Hx + b
74: */
77: static PetscErrorCode GPCGObjectiveAndGradient(TaoLineSearch ls, Vec X, PetscReal *f, Vec G, void*tptr)
78: {
79: Tao tao = (Tao)tptr;
80: TAO_GPCG *gpcg = (TAO_GPCG*)tao->data;
82: PetscReal f1,f2;
85: MatMult(tao->hessian,X,G);
86: VecDot(G,X,&f1);
87: VecDot(gpcg->B,X,&f2);
88: VecAXPY(G,1.0,gpcg->B);
89: *f=f1/2.0 + f2 + gpcg->c;
90: return(0);
91: }
93: /* ---------------------------------------------------------- */
96: static PetscErrorCode TaoSetup_GPCG(Tao tao)
97: {
99: TAO_GPCG *gpcg = (TAO_GPCG *)tao->data;
102: /* Allocate some arrays */
103: if (!tao->gradient) {
104: VecDuplicate(tao->solution, &tao->gradient);
105: }
106: if (!tao->stepdirection) {
107: VecDuplicate(tao->solution, &tao->stepdirection);
108: }
109: if (!tao->XL) {
110: VecDuplicate(tao->solution,&tao->XL);
111: VecSet(tao->XL,PETSC_NINFINITY);
112: }
113: if (!tao->XU) {
114: VecDuplicate(tao->solution,&tao->XU);
115: VecSet(tao->XU,PETSC_INFINITY);
116: }
118: ierr=VecDuplicate(tao->solution,&gpcg->B);
119: ierr=VecDuplicate(tao->solution,&gpcg->Work);
120: ierr=VecDuplicate(tao->solution,&gpcg->X_New);
121: ierr=VecDuplicate(tao->solution,&gpcg->G_New);
122: ierr=VecDuplicate(tao->solution,&gpcg->DXFree);
123: ierr=VecDuplicate(tao->solution,&gpcg->R);
124: ierr=VecDuplicate(tao->solution,&gpcg->PG);
125: KSPCreate(((PetscObject)tao)->comm, &tao->ksp);
126: KSPSetType(tao->ksp,KSPNASH);
127: KSPSetFromOptions(tao->ksp);
128: /*
129: if (gpcg->ksp_type == GPCG_KSP_NASH) {
130: KSPSetType(tao->ksp,KSPNASH);
131: } else if (gpcg->ksp_type == GPCG_KSP_STCG) {
132: KSPSetType(tao->ksp,KSPSTCG);
133: } else {
134: KSPSetType(tao->ksp,KSPGLTR);
135: }
136: if (tao->ksp->ops->setfromoptions) {
137: (*tao->ksp->ops->setfromoptions)(tao->ksp);
138: }
140: }
141: */
142: return(0);
143: }
147: static PetscErrorCode TaoSolve_GPCG(Tao tao)
148: {
149: TAO_GPCG *gpcg = (TAO_GPCG *)tao->data;
150: PetscErrorCode ierr;
151: PetscInt iter=0,its;
152: PetscReal actred,f,f_new,gnorm,gdx,stepsize,xtb;
153: PetscReal xtHx;
154: MatStructure structure;
155: TaoTerminationReason reason = TAO_CONTINUE_ITERATING;
156: TaoLineSearchTerminationReason ls_status = TAOLINESEARCH_CONTINUE_ITERATING;
159: gpcg->Hsub=NULL;
160: gpcg->Hsub_pre=NULL;
162: TaoComputeVariableBounds(tao);
163: VecMedian(tao->XL,tao->solution,tao->XU,tao->solution);
164: TaoLineSearchSetVariableBounds(tao->linesearch,tao->XL,tao->XU);
166: /* Using f = .5*x'Hx + x'b + c and g=Hx + b, compute b,c */
167: TaoComputeHessian(tao,tao->solution,&tao->hessian, &tao->hessian_pre,&structure);
168: TaoComputeObjectiveAndGradient(tao,tao->solution,&f,tao->gradient);
169: VecCopy(tao->gradient, gpcg->B);
170: MatMult(tao->hessian,tao->solution,gpcg->Work);
171: VecDot(gpcg->Work, tao->solution, &xtHx);
172: VecAXPY(gpcg->B,-1.0,gpcg->Work);
173: VecDot(gpcg->B,tao->solution,&xtb);
174: gpcg->c=f-xtHx/2.0-xtb;
175: if (gpcg->Free_Local) {
176: ISDestroy(&gpcg->Free_Local);
177: }
178: VecWhichBetween(tao->XL,tao->solution,tao->XU,&gpcg->Free_Local);
180: /* Project the gradient and calculate the norm */
181: VecCopy(tao->gradient,gpcg->G_New);
182: VecBoundGradientProjection(tao->gradient,tao->solution,tao->XL,tao->XU,gpcg->PG);
183: VecNorm(gpcg->PG,NORM_2,&gpcg->gnorm);
184: tao->step=1.0;
185: gpcg->f = f;
187: /* Check Stopping Condition */
188: ierr=TaoMonitor(tao,iter,f,gpcg->gnorm,0.0,tao->step,&reason);
190: while (reason == TAO_CONTINUE_ITERATING){
192: GPCGGradProjections(tao);
193: ISGetSize(gpcg->Free_Local,&gpcg->n_free);
195: f=gpcg->f; gnorm=gpcg->gnorm;
197: KSPReset(tao->ksp);
199: if (gpcg->n_free > 0){
200: /* Create a reduced linear system */
201: VecDestroy(&gpcg->R);
202: VecDestroy(&gpcg->DXFree);
203: VecGetSubVec(tao->gradient,gpcg->Free_Local, tao->subset_type, 0.0, &gpcg->R);
204: VecScale(gpcg->R, -1.0);
205: VecGetSubVec(tao->stepdirection,gpcg->Free_Local,tao->subset_type, 0.0, &gpcg->DXFree);
206: VecSet(gpcg->DXFree,0.0);
208: MatGetSubMat(tao->hessian, gpcg->Free_Local, gpcg->Work, tao->subset_type, &gpcg->Hsub);
210: if (tao->hessian_pre == tao->hessian) {
211: MatDestroy(&gpcg->Hsub_pre);
212: PetscObjectReference((PetscObject)gpcg->Hsub);
213: gpcg->Hsub_pre = gpcg->Hsub;
214: } else {
215: MatGetSubMat(tao->hessian, gpcg->Free_Local, gpcg->Work, tao->subset_type, &gpcg->Hsub_pre);
216: }
218: KSPReset(tao->ksp);
219: KSPSetOperators(tao->ksp,gpcg->Hsub,gpcg->Hsub_pre,DIFFERENT_NONZERO_PATTERN);
221: KSPSolve(tao->ksp,gpcg->R,gpcg->DXFree);
222: KSPGetIterationNumber(tao->ksp,&its);
223: tao->ksp_its+=its;
225: VecSet(tao->stepdirection,0.0);
226: VecISAXPY(tao->stepdirection,gpcg->Free_Local,1.0,gpcg->DXFree);
228: VecDot(tao->stepdirection,tao->gradient,&gdx);
229: TaoLineSearchSetInitialStepLength(tao->linesearch,1.0);
230: f_new=f;
231: TaoLineSearchApply(tao->linesearch,tao->solution,&f_new,tao->gradient,tao->stepdirection,&stepsize,&ls_status);
233: actred = f_new - f;
235: /* Evaluate the function and gradient at the new point */
236: VecBoundGradientProjection(tao->gradient,tao->solution,tao->XL,tao->XU, gpcg->PG);
237: VecNorm(gpcg->PG, NORM_2, &gnorm);
238: f=f_new;
239: ISDestroy(&gpcg->Free_Local);
240: VecWhichBetween(tao->XL,tao->solution,tao->XU,&gpcg->Free_Local);
241: } else {
242: actred = 0; gpcg->step=1.0;
243: /* if there were no free variables, no cg method */
244: }
246: iter++;
247: TaoMonitor(tao,iter,f,gnorm,0.0,gpcg->step,&reason);
248: gpcg->f=f;gpcg->gnorm=gnorm; gpcg->actred=actred;
249: if (reason!=TAO_CONTINUE_ITERATING) break;
250: } /* END MAIN LOOP */
252: return(0);
253: }
257: static PetscErrorCode GPCGGradProjections(Tao tao)
258: {
259: PetscErrorCode ierr;
260: TAO_GPCG *gpcg = (TAO_GPCG *)tao->data;
261: PetscInt i;
262: PetscReal actred=-1.0,actred_max=0.0, gAg,gtg=gpcg->gnorm,alpha;
263: PetscReal f_new,gdx,stepsize;
264: Vec DX=tao->stepdirection,XL=tao->XL,XU=tao->XU,Work=gpcg->Work;
265: Vec X=tao->solution,G=tao->gradient;
266: TaoLineSearchTerminationReason lsflag=TAOLINESEARCH_CONTINUE_ITERATING;
268: /*
269: The free, active, and binding variables should be already identified
270: */
272: for (i=0;i<gpcg->maxgpits;i++){
273: if ( -actred <= (gpcg->pg_ftol)*actred_max) break;
274: VecBoundGradientProjection(G,X,XL,XU,DX);
275: VecScale(DX,-1.0);
276: VecDot(DX,G,&gdx);
278: MatMult(tao->hessian,DX,Work);
279: VecDot(DX,Work,&gAg);
281: gpcg->gp_iterates++;
282: gpcg->total_gp_its++;
284: gtg=-gdx;
285: alpha = PetscAbsReal(gtg/gAg);
286: TaoLineSearchSetInitialStepLength(tao->linesearch,alpha);
287: f_new=gpcg->f;
288: TaoLineSearchApply(tao->linesearch,X,&f_new,G,DX,&stepsize,&lsflag);
290: /* Update the iterate */
291: actred = f_new - gpcg->f;
292: actred_max = PetscMax(actred_max,-(f_new - gpcg->f));
293: gpcg->f = f_new;
294: ISDestroy(&gpcg->Free_Local);
295: VecWhichBetween(XL,X,XU,&gpcg->Free_Local);
296: }
298: gpcg->gnorm=gtg;
299: return(0);
300: } /* End gradient projections */
304: static PetscErrorCode TaoComputeDual_GPCG(Tao tao, Vec DXL, Vec DXU)
305: {
306: TAO_GPCG *gpcg = (TAO_GPCG *)tao->data;
310: VecBoundGradientProjection(tao->gradient, tao->solution, tao->XL, tao->XU, gpcg->Work);
311: VecCopy(gpcg->Work, DXL);
312: VecAXPY(DXL,-1.0,tao->gradient);
313: VecSet(DXU,0.0);
314: VecPointwiseMax(DXL,DXL,DXU);
316: VecCopy(tao->gradient,DXU);
317: VecAXPY(DXU,-1.0,gpcg->Work);
318: VecSet(gpcg->Work,0.0);
319: VecPointwiseMin(DXU,gpcg->Work,DXU);
320: return(0);
321: }
323: /*------------------------------------------------------------*/
324: EXTERN_C_BEGIN
327: PetscErrorCode TaoCreate_GPCG(Tao tao)
328: {
329: TAO_GPCG *gpcg;
333: tao->ops->setup = TaoSetup_GPCG;
334: tao->ops->solve = TaoSolve_GPCG;
335: tao->ops->view = TaoView_GPCG;
336: tao->ops->setfromoptions = TaoSetFromOptions_GPCG;
337: tao->ops->destroy = TaoDestroy_GPCG;
338: tao->ops->computedual = TaoComputeDual_GPCG;
340: PetscNewLog(tao,&gpcg);
341: tao->data = (void*)gpcg;
343: tao->max_it = 500;
344: tao->max_funcs = 100000;
346: #if defined(PETSC_USE_REAL_SINGLE)
347: tao->fatol = 1e-6;
348: tao->frtol = 1e-6;
349: #else
350: tao->fatol = 1e-12;
351: tao->frtol = 1e-12;
352: #endif
354: /* Initialize pointers and variables */
355: gpcg->n=0;
356: gpcg->maxgpits = 8;
357: gpcg->pg_ftol = 0.1;
359: gpcg->gp_iterates=0; /* Cumulative number */
360: gpcg->total_gp_its = 0;
362: /* Initialize pointers and variables */
363: gpcg->n_bind=0;
364: gpcg->n_free = 0;
365: gpcg->n_upper=0;
366: gpcg->n_lower=0;
367: gpcg->subset_type = TAO_SUBSET_MASK;
368: /* gpcg->ksp_type = GPCG_KSP_STCG; */
370: TaoLineSearchCreate(((PetscObject)tao)->comm, &tao->linesearch);
371: TaoLineSearchSetType(tao->linesearch, TAOLINESEARCH_GPCG);
372: TaoLineSearchSetObjectiveAndGradientRoutine(tao->linesearch, GPCGObjectiveAndGradient, tao);
373: return(0);
374: }
375: EXTERN_C_END