Actual source code: groppcg.c
1: #include <petsc/private/kspimpl.h>
3: /*
4: KSPSetUp_GROPPCG - Sets up the workspace needed by the GROPPCG method.
6: This is called once, usually automatically by KSPSolve() or KSPSetUp()
7: but can be called directly by KSPSetUp()
8: */
9: static PetscErrorCode KSPSetUp_GROPPCG(KSP ksp)
10: {
11: PetscFunctionBegin;
12: PetscCall(KSPSetWorkVecs(ksp, 6));
13: PetscFunctionReturn(PETSC_SUCCESS);
14: }
16: /*
17: KSPSolve_GROPPCG
19: Input Parameter:
20: . ksp - the Krylov space object that was set to use conjugate gradient, by, for
21: example, KSPCreate(MPI_Comm,KSP *ksp); KSPSetType(ksp,KSPCG);
22: */
23: static PetscErrorCode KSPSolve_GROPPCG(KSP ksp)
24: {
25: PetscInt i;
26: PetscScalar alpha, beta = 0.0, gamma, gammaNew, t;
27: PetscReal dp = 0.0;
28: Vec x, b, r, p, s, S, z, Z;
29: Mat Amat, Pmat;
31: PetscFunctionBegin;
32: x = ksp->vec_sol;
33: b = ksp->vec_rhs;
34: r = ksp->work[0];
35: p = ksp->work[1];
36: s = ksp->work[2];
37: S = ksp->work[3];
38: z = ksp->work[4];
39: Z = ksp->work[5];
41: PetscCall(PCGetOperators(ksp->pc, &Amat, &Pmat));
43: ksp->its = 0;
44: if (!ksp->guess_zero) {
45: PetscCall(KSP_MatMult(ksp, Amat, x, r)); /* r <- b - Ax */
46: PetscCall(VecAYPX(r, -1.0, b));
47: } else {
48: PetscCall(VecCopy(b, r)); /* r <- b (x is 0) */
49: }
51: PetscCall(KSP_PCApply(ksp, r, z)); /* z <- Br */
52: PetscCall(VecCopy(z, p)); /* p <- z */
53: PetscCall(VecDotBegin(r, z, &gamma)); /* gamma <- z'*r */
54: PetscCall(PetscCommSplitReductionBegin(PetscObjectComm((PetscObject)r)));
55: PetscCall(KSP_MatMult(ksp, Amat, p, s)); /* s <- Ap */
56: PetscCall(VecDotEnd(r, z, &gamma)); /* gamma <- z'*r */
58: switch (ksp->normtype) {
59: case KSP_NORM_PRECONDITIONED:
60: /* This could be merged with the computation of gamma above */
61: PetscCall(VecNorm(z, NORM_2, &dp)); /* dp <- z'*z = e'*A'*B'*B*A'*e' */
62: break;
63: case KSP_NORM_UNPRECONDITIONED:
64: /* This could be merged with the computation of gamma above */
65: PetscCall(VecNorm(r, NORM_2, &dp)); /* dp <- r'*r = e'*A'*A*e */
66: break;
67: case KSP_NORM_NATURAL:
68: KSPCheckDot(ksp, gamma);
69: dp = PetscSqrtReal(PetscAbsScalar(gamma)); /* dp <- r'*z = r'*B*r = e'*A'*B*A*e */
70: break;
71: case KSP_NORM_NONE:
72: dp = 0.0;
73: break;
74: default:
75: SETERRQ(PetscObjectComm((PetscObject)ksp), PETSC_ERR_SUP, "%s", KSPNormTypes[ksp->normtype]);
76: }
77: PetscCall(KSPLogResidualHistory(ksp, dp));
78: PetscCall(KSPMonitor(ksp, 0, dp));
79: ksp->rnorm = dp;
80: PetscCall((*ksp->converged)(ksp, 0, dp, &ksp->reason, ksp->cnvP)); /* test for convergence */
81: if (ksp->reason) PetscFunctionReturn(PETSC_SUCCESS);
83: i = 0;
84: do {
85: ksp->its = i + 1;
86: i++;
88: PetscCall(VecDotBegin(p, s, &t));
89: PetscCall(PetscCommSplitReductionBegin(PetscObjectComm((PetscObject)p)));
91: PetscCall(KSP_PCApply(ksp, s, S)); /* S <- Bs */
93: PetscCall(VecDotEnd(p, s, &t));
95: alpha = gamma / t;
96: PetscCall(VecAXPY(x, alpha, p)); /* x <- x + alpha * p */
97: PetscCall(VecAXPY(r, -alpha, s)); /* r <- r - alpha * s */
98: PetscCall(VecAXPY(z, -alpha, S)); /* z <- z - alpha * S */
100: if (ksp->normtype == KSP_NORM_UNPRECONDITIONED) {
101: PetscCall(VecNormBegin(r, NORM_2, &dp));
102: } else if (ksp->normtype == KSP_NORM_PRECONDITIONED) {
103: PetscCall(VecNormBegin(z, NORM_2, &dp));
104: }
105: PetscCall(VecDotBegin(r, z, &gammaNew));
106: PetscCall(PetscCommSplitReductionBegin(PetscObjectComm((PetscObject)r)));
108: PetscCall(KSP_MatMult(ksp, Amat, z, Z)); /* Z <- Az */
110: if (ksp->normtype == KSP_NORM_UNPRECONDITIONED) {
111: PetscCall(VecNormEnd(r, NORM_2, &dp));
112: } else if (ksp->normtype == KSP_NORM_PRECONDITIONED) {
113: PetscCall(VecNormEnd(z, NORM_2, &dp));
114: }
115: PetscCall(VecDotEnd(r, z, &gammaNew));
117: if (ksp->normtype == KSP_NORM_NATURAL) {
118: KSPCheckDot(ksp, gammaNew);
119: dp = PetscSqrtReal(PetscAbsScalar(gammaNew)); /* dp <- r'*z = r'*B*r = e'*A'*B*A*e */
120: } else if (ksp->normtype == KSP_NORM_NONE) {
121: dp = 0.0;
122: }
123: ksp->rnorm = dp;
124: PetscCall(KSPLogResidualHistory(ksp, dp));
125: PetscCall(KSPMonitor(ksp, i, dp));
126: PetscCall((*ksp->converged)(ksp, i, dp, &ksp->reason, ksp->cnvP));
127: if (ksp->reason) PetscFunctionReturn(PETSC_SUCCESS);
129: beta = gammaNew / gamma;
130: gamma = gammaNew;
131: PetscCall(VecAYPX(p, beta, z)); /* p <- z + beta * p */
132: PetscCall(VecAYPX(s, beta, Z)); /* s <- Z + beta * s */
134: } while (i < ksp->max_it);
136: if (i >= ksp->max_it) ksp->reason = KSP_DIVERGED_ITS;
137: PetscFunctionReturn(PETSC_SUCCESS);
138: }
140: PETSC_INTERN PetscErrorCode KSPBuildResidual_CG(KSP, Vec, Vec, Vec *);
142: /*MC
143: KSPGROPPCG - A pipelined conjugate gradient method developed by Bill Gropp {cite}`eller2016scalable`. [](sec_pipelineksp)
145: Level: intermediate
147: Notes:
148: This method has two reductions, one of which is overlapped with the matrix-vector product and one of which is
149: overlapped with the preconditioner.
151: See also `KSPPIPECG`, which has only a single reduction that overlaps both the matrix-vector product and the preconditioner.
153: MPI configuration may be necessary for reductions to make asynchronous progress, which is important for performance of pipelined methods.
154: See [](doc_faq_pipelined)
156: Contributed by:
157: Pieter Ghysels, Universiteit Antwerpen, Intel Exascience lab Flanders
159: .seealso: [](ch_ksp), [](sec_pipelineksp), [](doc_faq_pipelined), `KSPCreate()`, `KSPPIPECG2()`, `KSPSetType()`, `KSPPIPECG`, `KSPPIPECR`, `KSPPGMRES`, `KSPCG`, `KSPCGUseSingleReduction()`
160: M*/
162: PETSC_EXTERN PetscErrorCode KSPCreate_GROPPCG(KSP ksp)
163: {
164: PetscFunctionBegin;
165: PetscCall(KSPSetSupportedNorm(ksp, KSP_NORM_UNPRECONDITIONED, PC_LEFT, 2));
166: PetscCall(KSPSetSupportedNorm(ksp, KSP_NORM_PRECONDITIONED, PC_LEFT, 2));
167: PetscCall(KSPSetSupportedNorm(ksp, KSP_NORM_NATURAL, PC_LEFT, 2));
168: PetscCall(KSPSetSupportedNorm(ksp, KSP_NORM_NONE, PC_LEFT, 1));
170: ksp->ops->setup = KSPSetUp_GROPPCG;
171: ksp->ops->solve = KSPSolve_GROPPCG;
172: ksp->ops->destroy = KSPDestroyDefault;
173: ksp->ops->view = NULL;
174: ksp->ops->setfromoptions = NULL;
175: ksp->ops->buildsolution = KSPBuildSolutionDefault;
176: ksp->ops->buildresidual = KSPBuildResidual_CG;
177: PetscFunctionReturn(PETSC_SUCCESS);
178: }