Actual source code: cgne.c
1: #define PETSCKSP_DLL
3: /*
4: cgctx.h defines the simple data structured used to store information
5: related to the type of matrix (e.g. complex symmetric) being solved and
6: data used during the optional Lanczo process used to compute eigenvalues
7: */
8: #include src/ksp/ksp/impls/cg/cgctx.h
9: EXTERN PetscErrorCode KSPComputeExtremeSingularValues_CG(KSP,PetscReal *,PetscReal *);
10: EXTERN PetscErrorCode KSPComputeEigenvalues_CG(KSP,PetscInt,PetscReal *,PetscReal *,PetscInt *);
13: /*
14: KSPSetUp_CGNE - Sets up the workspace needed by the CGNE method.
16: IDENTICAL TO THE CG ONE EXCEPT for one extra work vector!
17: */
20: PetscErrorCode KSPSetUp_CGNE(KSP ksp)
21: {
22: KSP_CG *cgP = (KSP_CG*)ksp->data;
24: PetscInt maxit = ksp->max_it;
27: /*
28: This implementation of CGNE only handles left preconditioning
29: so generate an error otherwise.
30: */
31: if (ksp->pc_side == PC_RIGHT) {
32: SETERRQ(PETSC_ERR_SUP,"No right preconditioning for KSPCGNE");
33: } else if (ksp->pc_side == PC_SYMMETRIC) {
34: SETERRQ(PETSC_ERR_SUP,"No symmetric preconditioning for KSPCGNE");
35: }
37: /* get work vectors needed by CGNE */
38: KSPDefaultGetWork(ksp,4);
40: /*
41: If user requested computations of eigenvalues then allocate work
42: work space needed
43: */
44: if (ksp->calc_sings) {
45: /* get space to store tridiagonal matrix for Lanczos */
46: PetscMalloc(2*(maxit+1)*sizeof(PetscScalar),&cgP->e);
47: PetscLogObjectMemory(ksp,2*(maxit+1)*sizeof(PetscScalar));
48: cgP->d = cgP->e + maxit + 1;
49: PetscMalloc(2*(maxit+1)*sizeof(PetscReal),&cgP->ee);
50: PetscLogObjectMemory(ksp,2*(maxit+1)*sizeof(PetscScalar));
51: cgP->dd = cgP->ee + maxit + 1;
52: ksp->ops->computeextremesingularvalues = KSPComputeExtremeSingularValues_CG;
53: ksp->ops->computeeigenvalues = KSPComputeEigenvalues_CG;
54: }
55: return(0);
56: }
58: /*
59: KSPSolve_CGNE - This routine actually applies the conjugate gradient
60: method
62: Input Parameter:
63: . ksp - the Krylov space object that was set to use conjugate gradient, by, for
64: example, KSPCreate(MPI_Comm,KSP *ksp); KSPSetType(ksp,KSPCG);
66: Probably virtually identical to the KSPSolve_CG, would be nice if we could reuse the code
68: */
71: PetscErrorCode KSPSolve_CGNE(KSP ksp)
72: {
74: PetscInt i,stored_max_it,eigs;
75: PetscScalar dpi,a = 1.0,beta,betaold = 1.0,b = 0,*e = 0,*d = 0;
76: PetscReal dp = 0.0;
77: Vec X,B,Z,R,P,T;
78: KSP_CG *cg;
79: Mat Amat,Pmat;
80: MatStructure pflag;
81: PetscTruth diagonalscale,transpose_pc;
84: PCDiagonalScale(ksp->pc,&diagonalscale);
85: if (diagonalscale) SETERRQ1(PETSC_ERR_SUP,"Krylov method %s does not support diagonal scaling",ksp->type_name);
86: PCHasApplyTranspose(ksp->pc,&transpose_pc);
88: cg = (KSP_CG*)ksp->data;
89: eigs = ksp->calc_sings;
90: stored_max_it = ksp->max_it;
91: X = ksp->vec_sol;
92: B = ksp->vec_rhs;
93: R = ksp->work[0];
94: Z = ksp->work[1];
95: P = ksp->work[2];
96: T = ksp->work[3];
98: #if !defined(PETSC_USE_COMPLEX)
99: #define VecXDot(x,y,a) VecDot(x,y,a)
100: #else
101: #define VecXDot(x,y,a) (((cg->type) == (KSP_CG_HERMITIAN)) ? VecDot(x,y,a) : VecTDot(x,y,a))
102: #endif
104: if (eigs) {e = cg->e; d = cg->d; e[0] = 0.0; }
105: PCGetOperators(ksp->pc,&Amat,&Pmat,&pflag);
107: ksp->its = 0;
108: MatMultTranspose(Amat,B,T);
109: if (!ksp->guess_zero) {
110: KSP_MatMult(ksp,Amat,X,P);
111: KSP_MatMultTranspose(ksp,Amat,P,R);
112: VecAYPX(R,-1.0,T);
113: } else {
114: VecCopy(T,R); /* r <- b (x is 0) */
115: }
116: KSP_PCApply(ksp,R,T);
117: if (transpose_pc) {
118: KSP_PCApplyTranspose(ksp,T,Z);
119: } else {
120: KSP_PCApply(ksp,T,Z);
121: }
123: VecXDot(Z,R,&beta);
124: if (ksp->normtype == KSP_NORM_PRECONDITIONED) {
125: VecNorm(Z,NORM_2,&dp); /* dp <- z'*z */
126: } else if (ksp->normtype == KSP_NORM_UNPRECONDITIONED) {
127: VecNorm(R,NORM_2,&dp); /* dp <- r'*r */
128: } else if (ksp->normtype == KSP_NORM_NATURAL) {
129: dp = sqrt(PetscAbsScalar(beta));
130: } else dp = 0.0;
131: KSPLogResidualHistory(ksp,dp);
132: KSPMonitor(ksp,0,dp); /* call any registered monitor routines */
133: ksp->rnorm = dp;
134: (*ksp->converged)(ksp,0,dp,&ksp->reason,ksp->cnvP); /* test for convergence */
135: if (ksp->reason) return(0);
137: i = 0;
138: do {
139: ksp->its = i+1;
140: VecXDot(Z,R,&beta); /* beta <- r'z */
141: if (beta == 0.0) {
142: ksp->reason = KSP_CONVERGED_ATOL;
143: PetscInfo(ksp,"converged due to beta = 0\n");
144: break;
145: #if !defined(PETSC_USE_COMPLEX)
146: } else if (beta < 0.0) {
147: ksp->reason = KSP_DIVERGED_INDEFINITE_PC;
148: PetscInfo(ksp,"diverging due to indefinite preconditioner\n");
149: break;
150: #endif
151: }
152: if (!i) {
153: VecCopy(Z,P); /* p <- z */
154: b = 0.0;
155: } else {
156: b = beta/betaold;
157: if (eigs) {
158: if (ksp->max_it != stored_max_it) {
159: SETERRQ(PETSC_ERR_SUP,"Can not change maxit AND calculate eigenvalues");
160: }
161: e[i] = sqrt(PetscAbsScalar(b))/a;
162: }
163: VecAYPX(P,b,Z); /* p <- z + b* p */
164: }
165: betaold = beta;
166: MatMult(Amat,P,T);
167: MatMultTranspose(Amat,T,Z);
168: VecXDot(P,Z,&dpi); /* dpi <- z'p */
169: a = beta/dpi; /* a = beta/p'z */
170: if (eigs) {
171: d[i] = sqrt(PetscAbsScalar(b))*e[i] + 1.0/a;
172: }
173: VecAXPY(X,a,P); /* x <- x + ap */
174: VecAXPY(R,-a,Z); /* r <- r - az */
175: if (ksp->normtype == KSP_NORM_PRECONDITIONED) {
176: KSP_PCApply(ksp,R,T);
177: if (transpose_pc) {
178: KSP_PCApplyTranspose(ksp,T,Z);
179: } else {
180: KSP_PCApply(ksp,T,Z);
181: }
182: VecNorm(Z,NORM_2,&dp); /* dp <- z'*z */
183: } else if (ksp->normtype == KSP_NORM_UNPRECONDITIONED) {
184: VecNorm(R,NORM_2,&dp);
185: } else if (ksp->normtype == KSP_NORM_NATURAL) {
186: dp = sqrt(PetscAbsScalar(beta));
187: } else {
188: dp = 0.0;
189: }
190: ksp->rnorm = dp;
191: KSPLogResidualHistory(ksp,dp);
192: KSPMonitor(ksp,i+1,dp);
193: (*ksp->converged)(ksp,i+1,dp,&ksp->reason,ksp->cnvP);
194: if (ksp->reason) break;
195: if (ksp->normtype != KSP_NORM_PRECONDITIONED) {
196: KSP_PCApply(ksp,R,Z); /* z <- Br */
197: }
198: i++;
199: } while (i<ksp->max_it);
200: if (i >= ksp->max_it) {
201: ksp->reason = KSP_DIVERGED_ITS;
202: }
203: return(0);
204: }
206: /*
207: KSPCreate_CGNE - Creates the data structure for the Krylov method CGNE and sets the
208: function pointers for all the routines it needs to call (KSPSolve_CGNE() etc)
211: */
213: /*MC
214: KSPCGNE - Applies the preconditioned conjugate gradient method to the normal equations
215: without explicitly forming A^t*A
217: Options Database Keys:
218: . -ksp_cg_type <Hermitian or symmetric - (for complex matrices only) indicates the matrix is Hermitian or symmetric
221: Level: beginner
223: Notes: eigenvalue computation routines will return information about the
224: spectrum of A^tA, rather than A.
226: This object is subclassed off of KSPCG
228: .seealso: KSPCreate(), KSPSetType(), KSPType (for list of available types), KSP,
229: KSPCGSetType()
231: M*/
243: PetscErrorCode KSPCreate_CGNE(KSP ksp)
244: {
246: KSP_CG *cg;
249: PetscNew(KSP_CG,&cg);
250: PetscLogObjectMemory(ksp,sizeof(KSP_CG));
251: #if !defined(PETSC_USE_COMPLEX)
252: cg->type = KSP_CG_SYMMETRIC;
253: #else
254: cg->type = KSP_CG_HERMITIAN;
255: #endif
256: ksp->data = (void*)cg;
257: ksp->pc_side = PC_LEFT;
259: /*
260: Sets the functions that are associated with this data structure
261: (in C++ this is the same as defining virtual functions)
262: */
263: ksp->ops->setup = KSPSetUp_CGNE;
264: ksp->ops->solve = KSPSolve_CGNE;
265: ksp->ops->destroy = KSPDestroy_CG;
266: ksp->ops->view = KSPView_CG;
267: ksp->ops->setfromoptions = KSPSetFromOptions_CG;
268: ksp->ops->buildsolution = KSPDefaultBuildSolution;
269: ksp->ops->buildresidual = KSPDefaultBuildResidual;
271: /*
272: Attach the function KSPCGSetType_CGNE() to this object. The routine
273: KSPCGSetType() checks for this attached function and calls it if it finds
274: it. (Sort of like a dynamic member function that can be added at run time
275: */
276: PetscObjectComposeFunctionDynamic((PetscObject)ksp,"KSPCGSetType_C","KSPCGSetType_CG",KSPCGSetType_CG);
277: return(0);
278: }