Actual source code: lsc.c

petsc-3.5.4 2015-05-23
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  2: #include <petsc-private/pcimpl.h>   /*I "petscpc.h" I*/

  4: typedef struct {
  5:   PetscBool allocated;
  6:   PetscBool scalediag;
  7:   KSP       kspL;
  8:   Vec       scale;
  9:   Vec       x0,y0,x1;
 10:   Mat       L;             /* keep a copy to reuse when obtained with L = A10*A01 */
 11: } PC_LSC;

 15: static PetscErrorCode PCLSCAllocate_Private(PC pc)
 16: {
 17:   PC_LSC         *lsc = (PC_LSC*)pc->data;
 18:   Mat            A;

 22:   if (lsc->allocated) return(0);
 23:   KSPCreate(PetscObjectComm((PetscObject)pc),&lsc->kspL);
 24:   PetscObjectIncrementTabLevel((PetscObject)lsc->kspL,(PetscObject)pc,1);
 25:   KSPSetType(lsc->kspL,KSPPREONLY);
 26:   KSPSetOptionsPrefix(lsc->kspL,((PetscObject)pc)->prefix);
 27:   KSPAppendOptionsPrefix(lsc->kspL,"lsc_");
 28:   KSPSetFromOptions(lsc->kspL);
 29:   MatSchurComplementGetSubMatrices(pc->mat,&A,NULL,NULL,NULL,NULL);
 30:   MatGetVecs(A,&lsc->x0,&lsc->y0);
 31:   MatGetVecs(pc->pmat,&lsc->x1,NULL);
 32:   if (lsc->scalediag) {
 33:     VecDuplicate(lsc->x0,&lsc->scale);
 34:   }
 35:   lsc->allocated = PETSC_TRUE;
 36:   return(0);
 37: }

 41: static PetscErrorCode PCSetUp_LSC(PC pc)
 42: {
 43:   PC_LSC         *lsc = (PC_LSC*)pc->data;
 44:   Mat            L,Lp,B,C;

 48:   PCLSCAllocate_Private(pc);
 49:   PetscObjectQuery((PetscObject)pc->mat,"LSC_L",(PetscObject*)&L);
 50:   if (!L) {PetscObjectQuery((PetscObject)pc->pmat,"LSC_L",(PetscObject*)&L);}
 51:   PetscObjectQuery((PetscObject)pc->pmat,"LSC_Lp",(PetscObject*)&Lp);
 52:   if (!Lp) {PetscObjectQuery((PetscObject)pc->mat,"LSC_Lp",(PetscObject*)&Lp);}
 53:   if (!L) {
 54:     MatSchurComplementGetSubMatrices(pc->mat,NULL,NULL,&B,&C,NULL);
 55:     if (!lsc->L) {
 56:       MatMatMult(C,B,MAT_INITIAL_MATRIX,PETSC_DEFAULT,&lsc->L);
 57:     } else {
 58:       MatMatMult(C,B,MAT_REUSE_MATRIX,PETSC_DEFAULT,&lsc->L);
 59:     }
 60:     Lp = L = lsc->L;
 61:   }
 62:   if (lsc->scale) {
 63:     Mat Ap;
 64:     MatSchurComplementGetSubMatrices(pc->mat,NULL,&Ap,NULL,NULL,NULL);
 65:     MatGetDiagonal(Ap,lsc->scale); /* Should be the mass matrix, but we don't have plumbing for that yet */
 66:     VecReciprocal(lsc->scale);
 67:   }
 68:   KSPSetOperators(lsc->kspL,L,Lp);
 69:   return(0);
 70: }

 74: static PetscErrorCode PCApply_LSC(PC pc,Vec x,Vec y)
 75: {
 76:   PC_LSC         *lsc = (PC_LSC*)pc->data;
 77:   Mat            A,B,C;

 81:   MatSchurComplementGetSubMatrices(pc->mat,&A,NULL,&B,&C,NULL);
 82:   KSPSolve(lsc->kspL,x,lsc->x1);
 83:   MatMult(B,lsc->x1,lsc->x0);
 84:   if (lsc->scale) {
 85:     VecPointwiseMult(lsc->x0,lsc->x0,lsc->scale);
 86:   }
 87:   MatMult(A,lsc->x0,lsc->y0);
 88:   if (lsc->scale) {
 89:     VecPointwiseMult(lsc->y0,lsc->y0,lsc->scale);
 90:   }
 91:   MatMult(C,lsc->y0,lsc->x1);
 92:   KSPSolve(lsc->kspL,lsc->x1,y);
 93:   return(0);
 94: }

 98: static PetscErrorCode PCReset_LSC(PC pc)
 99: {
100:   PC_LSC         *lsc = (PC_LSC*)pc->data;

104:   VecDestroy(&lsc->x0);
105:   VecDestroy(&lsc->y0);
106:   VecDestroy(&lsc->x1);
107:   VecDestroy(&lsc->scale);
108:   KSPDestroy(&lsc->kspL);
109:   MatDestroy(&lsc->L);
110:   return(0);
111: }

115: static PetscErrorCode PCDestroy_LSC(PC pc)
116: {

120:   PCReset_LSC(pc);
121:   PetscFree(pc->data);
122:   return(0);
123: }

127: static PetscErrorCode PCSetFromOptions_LSC(PC pc)
128: {
129:   PC_LSC         *lsc = (PC_LSC*)pc->data;

133:   PetscOptionsHead("LSC options");
134:   {
135:     PetscOptionsBool("-pc_lsc_scale_diag","Use diagonal of velocity block (A) for scaling","None",lsc->scalediag,&lsc->scalediag,NULL);
136:   }
137:   PetscOptionsTail();
138:   return(0);
139: }

143: static PetscErrorCode PCView_LSC(PC pc,PetscViewer viewer)
144: {
145:   PC_LSC         *jac = (PC_LSC*)pc->data;
147:   PetscBool      iascii;

150:   PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERASCII,&iascii);
151:   if (iascii) {
152:     PetscViewerASCIIPushTab(viewer);
153:     KSPView(jac->kspL,viewer);
154:     PetscViewerASCIIPopTab(viewer);
155:   }
156:   return(0);
157: }

159: /*MC
160:      PCLSC - Preconditioning for Schur complements, based on Least Squares Commutators

162:    Options Database Key:
163: .    -pc_lsc_scale_diag - Use the diagonal of A for scaling

165:    Level: intermediate

167:    Notes:
168:    This preconditioner will normally be used with PCFieldSplit to precondition the Schur complement, but
169:    it can be used for any Schur complement system.  Consider the Schur complement

171: .vb
172:    S = A11 - A10 inv(A00) A01
173: .ve

175:    PCLSC currently doesn't do anything with A11, so let's assume it is 0.  The idea is that a good approximation to
176:    inv(S) is given by

178: .vb
179:    inv(A10 A01) A10 A00 A01 inv(A10 A01)
180: .ve

182:    The product A10 A01 can be computed for you, but you can provide it (this is
183:    usually more efficient anyway).  In the case of incompressible flow, A10 A10 is a Laplacian, call it L.  The current
184:    interface is to hang L and a preconditioning matrix Lp on the preconditioning matrix.

186:    If you had called KSPSetOperators(ksp,S,Sp), S should have type MATSCHURCOMPLEMENT and Sp can be any type you
187:    like (PCLSC doesn't use it directly) but should have matrices composed with it, under the names "LSC_L" and "LSC_Lp".
188:    For example, you might have setup code like this

190: .vb
191:    PetscObjectCompose((PetscObject)Sp,"LSC_L",(PetscObject)L);
192:    PetscObjectCompose((PetscObject)Sp,"LSC_Lp",(PetscObject)Lp);
193: .ve

195:    And then your Jacobian assembly would look like

197: .vb
198:    PetscObjectQuery((PetscObject)Sp,"LSC_L",(PetscObject*)&L);
199:    PetscObjectQuery((PetscObject)Sp,"LSC_Lp",(PetscObject*)&Lp);
200:    if (L) { assembly L }
201:    if (Lp) { assemble Lp }
202: .ve

204:    With this, you should be able to choose LSC preconditioning, using e.g. ML's algebraic multigrid to solve with L

206: .vb
207:    -fieldsplit_1_pc_type lsc -fieldsplit_1_lsc_pc_type ml
208: .ve

210:    Since we do not use the values in Sp, you can still put an assembled matrix there to use normal preconditioners.

212:    References:
213: +  Elman, Howle, Shadid, Shuttleworth, and Tuminaro, Block preconditioners based on approximate commutators, 2006.
214: -  Silvester, Elman, Kay, Wathen, Efficient preconditioning of the linearized Navier-Stokes equations for incompressible flow, 2001.

216:    Concepts: physics based preconditioners, block preconditioners

218: .seealso:  PCCreate(), PCSetType(), PCType (for list of available types), PC, Block_Preconditioners, PCFIELDSPLIT,
219:            PCFieldSplitGetSubKSP(), PCFieldSplitSetFields(), PCFieldSplitSetType(), PCFieldSplitSetIS(), PCFieldSplitSetSchurPre(),
220:            MatCreateSchurComplement()
221: M*/

225: PETSC_EXTERN PetscErrorCode PCCreate_LSC(PC pc)
226: {
227:   PC_LSC         *lsc;

231:   PetscNewLog(pc,&lsc);
232:   pc->data = (void*)lsc;

234:   pc->ops->apply           = PCApply_LSC;
235:   pc->ops->applytranspose  = 0;
236:   pc->ops->setup           = PCSetUp_LSC;
237:   pc->ops->reset           = PCReset_LSC;
238:   pc->ops->destroy         = PCDestroy_LSC;
239:   pc->ops->setfromoptions  = PCSetFromOptions_LSC;
240:   pc->ops->view            = PCView_LSC;
241:   pc->ops->applyrichardson = 0;
242:   return(0);
243: }