Actual source code: cgtype.c

petsc-3.8.3 2017-12-09
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  2:  #include <../src/ksp/ksp/impls/cg/cgimpl.h>

  4: /*@
  5:     KSPCGSetType - Sets the variant of the conjugate gradient method to
  6:     use for solving a linear system with a complex coefficient matrix.
  7:     This option is irrelevant when solving a real system.

  9:     Logically Collective on KSP

 11:     Input Parameters:
 12: +   ksp - the iterative context
 13: -   type - the variant of CG to use, one of
 14: .vb
 15:       KSP_CG_HERMITIAN - complex, Hermitian matrix (default)
 16:       KSP_CG_SYMMETRIC - complex, symmetric matrix
 17: .ve

 19:     Level: intermediate

 21:     Options Database Keys:
 22: +   -ksp_cg_Hermitian - Indicates Hermitian matrix
 23: -   -ksp_cg_symmetric - Indicates symmetric matrix

 25:     Note:
 26:     By default, the matrix is assumed to be complex, Hermitian.

 28: .keywords: CG, conjugate gradient, Hermitian, symmetric, set, type
 29: @*/
 30: PetscErrorCode  KSPCGSetType(KSP ksp,KSPCGType type)
 31: {

 36:   PetscTryMethod(ksp,"KSPCGSetType_C",(KSP,KSPCGType),(ksp,type));
 37:   return(0);
 38: }

 40: /*@
 41:     KSPCGUseSingleReduction - Merge the two inner products needed in CG into a single MPI_Allreduce() call.

 43:     Logically Collective on KSP

 45:     Input Parameters:
 46: +   ksp - the iterative context
 47: -   flg - turn on or off the single reduction

 49:     Options Database:
 50: .   -ksp_cg_single_reduction

 52:     Level: intermediate

 54:      The algorithm used in this case is described as Method 1 in Lapack Working Note 56, "Conjugate Gradient Algorithms with Reduced Synchronization Overhead
 55:      Distributed Memory Multiprocessors", by E. F. D'Azevedo, V. L. Eijkhout, and C. H. Romine, December 3, 1999. V. Eijkhout creates the algorithm
 56:      initially to Chronopoulos and Gear.

 58:      It requires two extra work vectors than the conventional implementation in PETSc.

 60:      See also KSPPIPECG, KSPPIPECR, and KSPGROPPCG that use non-blocking reductions.

 62: .keywords: CG, conjugate gradient, Hermitian, symmetric, set, type, KSPPGMRES
 63: @*/
 64: PetscErrorCode  KSPCGUseSingleReduction(KSP ksp,PetscBool flg)
 65: {

 71:   PetscTryMethod(ksp,"KSPCGUseSingleReduction_C",(KSP,PetscBool),(ksp,flg));
 72:   return(0);
 73: }

 75: /*@
 76:     KSPCGSetRadius - Sets the radius of the trust region.

 78:     Logically Collective on KSP

 80:     Input Parameters:
 81: +   ksp    - the iterative context
 82: -   radius - the trust region radius (Infinity is the default)

 84:     Level: advanced

 86: .keywords: KSP, NASH, STCG, GLTR, set, trust region radius
 87: @*/
 88: PetscErrorCode  KSPCGSetRadius(KSP ksp, PetscReal radius)
 89: {

 94:   if (radius < 0.0) SETERRQ(PetscObjectComm((PetscObject)ksp),PETSC_ERR_ARG_OUTOFRANGE, "Radius negative");
 96:   PetscTryMethod(ksp,"KSPCGSetRadius_C",(KSP,PetscReal),(ksp,radius));
 97:   return(0);
 98: }

100: /*@
101:     KSPCGGetNormD - Got norm of the direction.

103:     Collective on KSP

105:     Input Parameters:
106: +   ksp    - the iterative context
107: -   norm_d - the norm of the direction

109:     Level: advanced

111: .keywords: KSP, NASH, STCG, GLTR, get, norm direction
112: @*/
113: PetscErrorCode  KSPCGGetNormD(KSP ksp, PetscReal *norm_d)
114: {

119:   PetscUseMethod(ksp,"KSPCGGetNormD_C",(KSP,PetscReal*),(ksp,norm_d));
120:   return(0);
121: }

123: /*@
124:     KSPCGGetObjFcn - Get objective function value.

126:     Collective on KSP

128:     Input Parameters:
129: +   ksp   - the iterative context
130: -   o_fcn - the objective function value

132:     Level: advanced

134: .keywords: KSP, NASH, STCG, GLTR, get, objective function
135: @*/
136: PetscErrorCode  KSPCGGetObjFcn(KSP ksp, PetscReal *o_fcn)
137: {

142:   PetscUseMethod(ksp,"KSPCGGetObjFcn_C",(KSP,PetscReal*),(ksp,o_fcn));
143:   return(0);
144: }