00001 /* @HEADER@ */ 00002 // ************************************************************************ 00003 // 00004 // Playa: Programmable Linear Algebra 00005 // Copyright 2012 Sandia Corporation 00006 // 00007 // Under the terms of Contract DE-AC04-94AL85000 with Sandia Corporation, 00008 // the U.S. Government retains certain rights in this software. 00009 // 00010 // Redistribution and use in source and binary forms, with or without 00011 // modification, are permitted provided that the following conditions are 00012 // met: 00013 // 00014 // 1. Redistributions of source code must retain the above copyright 00015 // notice, this list of conditions and the following disclaimer. 00016 // 00017 // 2. Redistributions in binary form must reproduce the above copyright 00018 // notice, this list of conditions and the following disclaimer in the 00019 // documentation and/or other materials provided with the distribution. 00020 // 00021 // 3. Neither the name of the Corporation nor the names of the 00022 // contributors may be used to endorse or promote products derived from 00023 // this software without specific prior written permission. 00024 // 00025 // THIS SOFTWARE IS PROVIDED BY SANDIA CORPORATION "AS IS" AND ANY 00026 // EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE 00027 // IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR 00028 // PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL SANDIA CORPORATION OR THE 00029 // CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, 00030 // EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, 00031 // PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR 00032 // PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF 00033 // LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING 00034 // NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS 00035 // SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE. 00036 // 00037 // Questions? Contact Kevin Long (kevin.long@ttu.edu) 00038 // 00039 00040 /* @HEADER@ */ 00041 00042 #ifndef PLAYA_VECTORTYPEBASE_HPP 00043 #define PLAYA_VECTORTYPEBASE_HPP 00044 00045 #include "PlayaHandle.hpp" 00046 #include "PlayaVectorSpaceDecl.hpp" 00047 #include "PlayaLinearOperatorDecl.hpp" 00048 #include "PlayaMatrixFactory.hpp" 00049 #include "PlayaGhostImporter.hpp" 00050 00051 namespace Playa 00052 { 00053 using namespace Teuchos; 00054 00055 /** 00056 * 00057 */ 00058 template <class Scalar> 00059 class VectorTypeBase 00060 { 00061 public: 00062 /** Virtual dtor */ 00063 virtual ~VectorTypeBase() {;} 00064 00065 /** create a distributed vector space. 00066 * @param dimension the dimension of the space 00067 * @param nLocal number of indices owned by the local processor 00068 * @param locallyOwnedIndices array of indices owned by this processor 00069 */ 00070 virtual RCP<const VectorSpaceBase<Scalar> > 00071 createSpace(int dimension, 00072 int nLocal, 00073 const int* locallyOwnedIndices, 00074 const MPIComm& comm) const = 0 ; 00075 00076 00077 /** Default implementation creates a vector space having 00078 * nLocal elements on each processor. Serial types should override this 00079 * to produce a replicated space. */ 00080 virtual VectorSpace<Scalar> 00081 createEvenlyPartitionedSpace(const MPIComm& comm, 00082 int nLocal) const ; 00083 00084 /** 00085 * Create an importer for accessing ghost elements. 00086 * @param space the distributed vector space on which ghost elements 00087 * are to be shared 00088 * @param nGhost number of ghost elements needed by this processor 00089 * @param ghostIndices read-only C array of off-processor indices needed 00090 * by this processor. 00091 * @return A RCP to a GhostImporter object. 00092 */ 00093 virtual RCP<GhostImporter<Scalar> > 00094 createGhostImporter(const VectorSpace<Scalar>& space, 00095 int nGhost, 00096 const int* ghostIndices) const = 0 ; 00097 00098 00099 /** 00100 * Create a matrix factory of type compatible with this vector type, 00101 * sized according to the given domain and range spaces. 00102 */ 00103 virtual RCP<MatrixFactory<Scalar> > 00104 createMatrixFactory(const VectorSpace<Scalar>& domain, 00105 const VectorSpace<Scalar>& range) const = 0 ; 00106 00107 00108 }; 00109 00110 00111 00112 /* Default implementation */ 00113 template <class Scalar> inline 00114 VectorSpace<Scalar> VectorTypeBase<Scalar> 00115 ::createEvenlyPartitionedSpace(const MPIComm& comm, 00116 int nLocal) const 00117 { 00118 int rank = comm.getRank(); 00119 int nProc = comm.getNProc(); 00120 int dimension = nLocal * nProc; 00121 Array<int> locallyOwnedIndices(nLocal); 00122 int lowestLocalRow = rank*nLocal; 00123 for (int i=0; i<nLocal; i++) 00124 { 00125 locallyOwnedIndices[i] = lowestLocalRow + i; 00126 } 00127 return this->createSpace(dimension, nLocal, &(locallyOwnedIndices[0]), comm); 00128 } 00129 00130 00131 } 00132 00133 #endif