Date: 2015-10-02T22:02:54+00:00

Actual source code: mpiviennacl.cxx
petsc-3.6.2 2015-10-02
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      2: /*
      3:    This file contains routines for Parallel vector operations.
      4:  */
      5: #include <petscconf.h>
      6: #include <../src/vec/vec/impls/mpi/pvecimpl.h>   /*I  "petscvec.h"   I*/
      7: #include <../src/vec/vec/impls/seq/seqviennacl/viennaclvecimpl.h>

     11: PetscErrorCode VecDestroy_MPIViennaCL(Vec v)
     12: {

     16:   try {
     17:     if (v->spptr) {
     18:       delete ((Vec_ViennaCL*)v->spptr)->GPUarray;
     19:       delete (Vec_ViennaCL*) v->spptr;
     20:     }
     21:   } catch(std::exception const & ex) {
     22:     SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_LIB,"ViennaCL error: %s", ex.what());
     23:   }
     24:   VecDestroy_MPI(v);
     25:   return(0);
     26: }

     30: PetscErrorCode VecNorm_MPIViennaCL(Vec xin,NormType type,PetscReal *z)
     31: {
     32:   PetscReal      sum,work = 0.0;

     36:   if (type == NORM_2 || type == NORM_FROBENIUS) {
     37:     VecNorm_SeqViennaCL(xin,NORM_2,&work);
     38:     work *= work;
     39:     MPI_Allreduce(&work,&sum,1,MPIU_REAL,MPIU_SUM,PetscObjectComm((PetscObject)xin));
     40:     *z    = PetscSqrtReal(sum);
     41:   } else if (type == NORM_1) {
     42:     /* Find the local part */
     43:     VecNorm_SeqViennaCL(xin,NORM_1,&work);
     44:     /* Find the global max */
     45:     MPI_Allreduce(&work,z,1,MPIU_REAL,MPIU_SUM,PetscObjectComm((PetscObject)xin));
     46:   } else if (type == NORM_INFINITY) {
     47:     /* Find the local max */
     48:     VecNorm_SeqViennaCL(xin,NORM_INFINITY,&work);
     49:     /* Find the global max */
     50:     MPI_Allreduce(&work,z,1,MPIU_REAL,MPIU_MAX,PetscObjectComm((PetscObject)xin));
     51:   } else if (type == NORM_1_AND_2) {
     52:     PetscReal temp[2];
     53:     VecNorm_SeqViennaCL(xin,NORM_1,temp);
     54:     VecNorm_SeqViennaCL(xin,NORM_2,temp+1);
     55:     temp[1] = temp[1]*temp[1];
     56:     MPI_Allreduce(temp,z,2,MPIU_REAL,MPIU_SUM,PetscObjectComm((PetscObject)xin));
     57:     z[1] = PetscSqrtReal(z[1]);
     58:   }
     59:   return(0);
     60: }

     64: PetscErrorCode VecDot_MPIViennaCL(Vec xin,Vec yin,PetscScalar *z)
     65: {
     66:   PetscScalar    sum,work;

     70:   VecDot_SeqViennaCL(xin,yin,&work);
     71:   MPI_Allreduce(&work,&sum,1,MPIU_SCALAR,MPIU_SUM,PetscObjectComm((PetscObject)xin));
     72:   *z   = sum;
     73:   return(0);
     74: }

     78: PetscErrorCode VecTDot_MPIViennaCL(Vec xin,Vec yin,PetscScalar *z)
     79: {
     80:   PetscScalar    sum,work;

     84:   VecTDot_SeqViennaCL(xin,yin,&work);
     85:   MPI_Allreduce(&work,&sum,1,MPIU_SCALAR,MPIU_SUM,PetscObjectComm((PetscObject)xin));
     86:   *z   = sum;
     87:   return(0);
     88: }

     92: PetscErrorCode VecMDot_MPIViennaCL(Vec xin,PetscInt nv,const Vec y[],PetscScalar *z)
     93: {
     94:   PetscScalar    awork[128],*work = awork;

     98:   if (nv > 128) {
     99:     PetscMalloc1(nv,&work);
    100:   }
    101:   VecMDot_SeqViennaCL(xin,nv,y,work);
    102:   MPI_Allreduce(work,z,nv,MPIU_SCALAR,MPIU_SUM,PetscObjectComm((PetscObject)xin));
    103:   if (nv > 128) {
    104:     PetscFree(work);
    105:   }
    106:   return(0);
    107: }

    109: /*MC
    110:    VECMPIVIENNACL - VECMPIVIENNACL = "mpiviennacl" - The basic parallel vector, modified to use ViennaCL

    112:    Options Database Keys:
    113: . -vec_type mpiviennacl - sets the vector type to VECMPIVIENNACL during a call to VecSetFromOptions()

    115:   Level: beginner

    117: .seealso: VecCreate(), VecSetType(), VecSetFromOptions(), VecCreateMpiWithArray(), VECMPI, VecType, VecCreateMPI(), VecCreateMpi()
    118: M*/

    123: PetscErrorCode VecDuplicate_MPIViennaCL(Vec win,Vec *v)
    124: {
    126:   Vec_MPI        *vw,*w = (Vec_MPI*)win->data;
    127:   PetscScalar    *array;

    130:   VecCreate(PetscObjectComm((PetscObject)win),v);
    131:   PetscLayoutReference(win->map,&(*v)->map);

    133:   VecCreate_MPI_Private(*v,PETSC_FALSE,w->nghost,0);
    134:   vw   = (Vec_MPI*)(*v)->data;
    135:   PetscMemcpy((*v)->ops,win->ops,sizeof(struct _VecOps));

    137:   /* save local representation of the parallel vector (and scatter) if it exists */
    138:   if (w->localrep) {
    139:     VecGetArray(*v,&array);
    140:     VecCreateSeqWithArray(PETSC_COMM_SELF,1,win->map->n+w->nghost,array,&vw->localrep);
    141:     PetscMemcpy(vw->localrep->ops,w->localrep->ops,sizeof(struct _VecOps));
    142:     VecRestoreArray(*v,&array);
    143:     PetscLogObjectParent((PetscObject)*v,(PetscObject)vw->localrep);
    144:     vw->localupdate = w->localupdate;
    145:     if (vw->localupdate) {
    146:       PetscObjectReference((PetscObject)vw->localupdate);
    147:     }
    148:   }

    150:   /* New vector should inherit stashing property of parent */
    151:   (*v)->stash.donotstash   = win->stash.donotstash;
    152:   (*v)->stash.ignorenegidx = win->stash.ignorenegidx;

    154:   /* change type_name appropriately */
    155:   PetscObjectChangeTypeName((PetscObject)(*v),VECMPIVIENNACL);

    157:   PetscObjectListDuplicate(((PetscObject)win)->olist,&((PetscObject)(*v))->olist);
    158:   PetscFunctionListDuplicate(((PetscObject)win)->qlist,&((PetscObject)(*v))->qlist);
    159:   (*v)->map->bs   = PetscAbs(win->map->bs);
    160:   (*v)->bstash.bs = win->bstash.bs;
    161:   return(0);
    162: }

    166: PetscErrorCode VecDotNorm2_MPIViennaCL(Vec s,Vec t,PetscScalar *dp,PetscScalar *nm)
    167: {
    169:   PetscScalar    work[2],sum[2];

    172:   VecDotNorm2_SeqViennaCL(s,t,work,work+1);
    173:   MPI_Allreduce((void*)&work,(void*)&sum,2,MPIU_SCALAR,MPIU_SUM,PetscObjectComm((PetscObject)s));
    174:   *dp  = sum[0];
    175:   *nm  = sum[1];
    176:   return(0);
    177: }

    181: PETSC_EXTERN PetscErrorCode VecCreate_MPIViennaCL(Vec vv)
    182: {

    186:   VecCreate_MPI_Private(vv,PETSC_FALSE,0,0);
    187:   PetscObjectChangeTypeName((PetscObject)vv,VECMPIVIENNACL);

    189:   vv->ops->dotnorm2        = VecDotNorm2_MPIViennaCL;
    190:   vv->ops->waxpy           = VecWAXPY_SeqViennaCL;
    191:   vv->ops->duplicate       = VecDuplicate_MPIViennaCL;
    192:   vv->ops->dot             = VecDot_MPIViennaCL;
    193:   vv->ops->mdot            = VecMDot_MPIViennaCL;
    194:   vv->ops->tdot            = VecTDot_MPIViennaCL;
    195:   vv->ops->norm            = VecNorm_MPIViennaCL;
    196:   vv->ops->scale           = VecScale_SeqViennaCL;
    197:   vv->ops->copy            = VecCopy_SeqViennaCL;
    198:   vv->ops->set             = VecSet_SeqViennaCL;
    199:   vv->ops->swap            = VecSwap_SeqViennaCL;
    200:   vv->ops->axpy            = VecAXPY_SeqViennaCL;
    201:   vv->ops->axpby           = VecAXPBY_SeqViennaCL;
    202:   vv->ops->maxpy           = VecMAXPY_SeqViennaCL;
    203:   vv->ops->aypx            = VecAYPX_SeqViennaCL;
    204:   vv->ops->axpbypcz        = VecAXPBYPCZ_SeqViennaCL;
    205:   vv->ops->pointwisemult   = VecPointwiseMult_SeqViennaCL;
    206:   vv->ops->setrandom       = VecSetRandom_SeqViennaCL;
    207:   vv->ops->replacearray    = VecReplaceArray_SeqViennaCL;
    208:   vv->ops->dot_local       = VecDot_SeqViennaCL;
    209:   vv->ops->tdot_local      = VecTDot_SeqViennaCL;
    210:   vv->ops->norm_local      = VecNorm_SeqViennaCL;
    211:   vv->ops->mdot_local      = VecMDot_SeqViennaCL;
    212:   vv->ops->destroy         = VecDestroy_MPIViennaCL;
    213:   vv->ops->pointwisedivide = VecPointwiseDivide_SeqViennaCL;
    214:   /* place array?
    215:      reset array?
    216:      get values?
    217:   */
    218:   VecViennaCLAllocateCheck(vv);
    219:   vv->valid_GPU_array      = PETSC_VIENNACL_GPU;
    220:   VecSet(vv,0.0);
    221:   return(0);
    222: }

    227: PETSC_EXTERN PetscErrorCode VecCreate_ViennaCL(Vec v)
    228: {
    230:   PetscMPIInt    size;

    233:   MPI_Comm_size(PetscObjectComm((PetscObject)v),&size);
    234:   if (size == 1) {
    235:     VecSetType(v,VECSEQVIENNACL);
    236:   } else {
    237:     VecSetType(v,VECMPIVIENNACL);
    238:   }
    239:   return(0);
    240: }