Date: 2023-11-27T17:18:17+00:00

Actual source code: fnimpl.h
slepc-3.20.1 2023-11-27
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      1: /*
      2:    - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
      3:    SLEPc - Scalable Library for Eigenvalue Problem Computations
      4:    Copyright (c) 2002-, Universitat Politecnica de Valencia, Spain

      6:    This file is part of SLEPc.
      7:    SLEPc is distributed under a 2-clause BSD license (see LICENSE).
      8:    - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
      9: */

     11: #pragma once

     13: #include <slepcfn.h>
     14: #include <slepc/private/slepcimpl.h>

     16: /* SUBMANSEC = FN */

     18: SLEPC_EXTERN PetscBool FNRegisterAllCalled;
     19: SLEPC_EXTERN PetscErrorCode FNRegisterAll(void);
     20: SLEPC_EXTERN PetscLogEvent FN_Evaluate;

     22: typedef struct _FNOps *FNOps;

     24: struct _FNOps {
     25:   PetscErrorCode (*evaluatefunction)(FN,PetscScalar,PetscScalar*);
     26:   PetscErrorCode (*evaluatederivative)(FN,PetscScalar,PetscScalar*);
     27:   PetscErrorCode (*evaluatefunctionmat[FN_MAX_SOLVE])(FN,Mat,Mat);
     28:   PetscErrorCode (*evaluatefunctionmatcuda[FN_MAX_SOLVE])(FN,Mat,Mat);
     29:   PetscErrorCode (*evaluatefunctionmatvec[FN_MAX_SOLVE])(FN,Mat,Vec);
     30:   PetscErrorCode (*evaluatefunctionmatveccuda[FN_MAX_SOLVE])(FN,Mat,Vec);
     31:   PetscErrorCode (*setfromoptions)(FN,PetscOptionItems*);
     32:   PetscErrorCode (*view)(FN,PetscViewer);
     33:   PetscErrorCode (*duplicate)(FN,MPI_Comm,FN*);
     34:   PetscErrorCode (*destroy)(FN);
     35: };

     37: #define FN_MAX_W 6

     39: struct _p_FN {
     40:   PETSCHEADER(struct _FNOps);
     41:   /*------------------------- User parameters --------------------------*/
     42:   PetscScalar    alpha;          /* inner scaling (argument) */
     43:   PetscScalar    beta;           /* outer scaling (result) */
     44:   PetscInt       method;         /* the method to compute matrix functions */
     45:   FNParallelType pmode;          /* parallel mode (redundant or synchronized) */

     47:   /*---------------------- Cached data and workspace -------------------*/
     48:   Mat            W[FN_MAX_W];    /* workspace matrices */
     49:   PetscInt       nw;             /* number of allocated W matrices */
     50:   PetscInt       cw;             /* current W matrix */
     51:   void           *data;
     52: };

     54: /*
     55:   FN_AllocateWorkMat - Allocate a work Mat of the same dimension of A and copy
     56:   its contents. The work matrix is returned in M and should be freed with
     57:   FN_FreeWorkMat().
     58: */
     59: static inline PetscErrorCode FN_AllocateWorkMat(FN fn,Mat A,Mat *M)
     60: {
     61:   PetscInt       n,na;
     62:   PetscBool      create=PETSC_FALSE;

     64:   PetscFunctionBegin;
     65:   *M = NULL;
     66:   PetscCheck(fn->cw<FN_MAX_W,PETSC_COMM_SELF,PETSC_ERR_SUP,"Too many requested work matrices %" PetscInt_FMT,fn->cw);
     67:   if (fn->nw<=fn->cw) {
     68:     create=PETSC_TRUE;
     69:     fn->nw++;
     70:   } else {
     71:     PetscCall(MatGetSize(fn->W[fn->cw],&n,NULL));
     72:     PetscCall(MatGetSize(A,&na,NULL));
     73:     if (n!=na) {
     74:       PetscCall(MatDestroy(&fn->W[fn->cw]));
     75:       create=PETSC_TRUE;
     76:     }
     77:   }
     78:   if (create) PetscCall(MatDuplicate(A,MAT_COPY_VALUES,&fn->W[fn->cw]));
     79:   else PetscCall(MatCopy(A,fn->W[fn->cw],SAME_NONZERO_PATTERN));
     80:   *M = fn->W[fn->cw];
     81:   fn->cw++;
     82:   PetscFunctionReturn(PETSC_SUCCESS);
     83: }

     85: /*
     86:   FN_FreeWorkMat - Release a work matrix created with FN_AllocateWorkMat().
     87: */
     88: static inline PetscErrorCode FN_FreeWorkMat(FN fn,Mat *M)
     89: {
     90:   PetscFunctionBegin;
     91:   PetscCheck(fn->cw,PETSC_COMM_SELF,PETSC_ERR_ARG_WRONG,"There are no work matrices");
     92:   fn->cw--;
     93:   PetscCheck(fn->W[fn->cw]==*M,PETSC_COMM_SELF,PETSC_ERR_ARG_WRONG,"Work matrices must be freed in the reverse order of their creation");
     94:   *M = NULL;
     95:   PetscFunctionReturn(PETSC_SUCCESS);
     96: }

     98: SLEPC_INTERN PetscErrorCode FNSqrtmSchur(FN,PetscBLASInt,PetscScalar*,PetscBLASInt,PetscBool);
     99: SLEPC_INTERN PetscErrorCode FNSqrtmDenmanBeavers(FN,PetscBLASInt,PetscScalar*,PetscBLASInt,PetscBool);
    100: SLEPC_INTERN PetscErrorCode FNSqrtmNewtonSchulz(FN,PetscBLASInt,PetscScalar*,PetscBLASInt,PetscBool);
    101: SLEPC_INTERN PetscErrorCode FNSqrtmSadeghi(FN,PetscBLASInt,PetscScalar*,PetscBLASInt);
    102: SLEPC_INTERN PetscErrorCode SlepcNormAm(PetscBLASInt,PetscScalar*,PetscInt,PetscScalar*,PetscRandom,PetscReal*);
    103: SLEPC_INTERN PetscErrorCode FNEvaluateFunctionMat_Private(FN,Mat,Mat,PetscBool);
    104: SLEPC_INTERN PetscErrorCode FNEvaluateFunctionMatVec_Private(FN,Mat,Vec,PetscBool);
    105: SLEPC_INTERN PetscErrorCode FNEvaluateFunctionMat_Exp_Higham(FN,Mat,Mat); /* used in FNPHI */
    106: #if defined(PETSC_HAVE_CUDA)
    107: SLEPC_INTERN PetscErrorCode FNSqrtmDenmanBeavers_CUDAm(FN,PetscBLASInt,PetscScalar*,PetscBLASInt,PetscBool);
    108: SLEPC_INTERN PetscErrorCode FNSqrtmNewtonSchulz_CUDA(FN,PetscBLASInt,PetscScalar*,PetscBLASInt,PetscBool);
    109: SLEPC_INTERN PetscErrorCode FNSqrtmSadeghi_CUDAm(FN,PetscBLASInt,PetscScalar*,PetscBLASInt);
    110: #endif