ViennaCL - The Vienna Computing Library  1.6.1
Free open-source GPU-accelerated linear algebra and solver library.
iterative.cpp
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1 /* =========================================================================
2  Copyright (c) 2010-2014, Institute for Microelectronics,
3  Institute for Analysis and Scientific Computing,
4  TU Wien.
5  Portions of this software are copyright by UChicago Argonne, LLC.
6 
7  -----------------
8  ViennaCL - The Vienna Computing Library
9  -----------------
10 
11  Project Head: Karl Rupp rupp@iue.tuwien.ac.at
12 
13  (A list of authors and contributors can be found in the PDF manual)
14 
15  License: MIT (X11), see file LICENSE in the base directory
16 ============================================================================= */
17 
27 //
28 // include necessary system headers
29 //
30 #include <iostream>
31 
32 //
33 // Necessary to obtain a suitable performance in ublas
34 #ifndef NDEBUG
35  #define BOOST_UBLAS_NDEBUG
36 #endif
37 
38 //
39 // ublas includes
40 //
41 #include <boost/numeric/ublas/io.hpp>
42 #include <boost/numeric/ublas/triangular.hpp>
43 #include <boost/numeric/ublas/matrix_sparse.hpp>
44 #include <boost/numeric/ublas/matrix.hpp>
45 #include <boost/numeric/ublas/matrix_proxy.hpp>
46 #include <boost/numeric/ublas/operation.hpp>
47 #include <boost/numeric/ublas/operation_sparse.hpp>
48 #include <boost/numeric/ublas/io.hpp>
49 #include <boost/numeric/ublas/lu.hpp>
50 
51 // Must be set if you want to use ViennaCL algorithms on ublas objects
52 #define VIENNACL_WITH_UBLAS 1
53 
54 
55 //
56 // ViennaCL includes
57 //
58 #include "viennacl/scalar.hpp"
59 #include "viennacl/vector.hpp"
62 #include "viennacl/linalg/prod.hpp"
63 #include "viennacl/linalg/ilu.hpp"
65 #include "viennacl/linalg/cg.hpp"
69 
70 
71 // Some helper functions for this tutorial:
72 #include "Random.hpp"
73 #include "vector-io.hpp"
74 
78 using namespace boost::numeric;
79 
80 
86 int main()
87 {
88  typedef float ScalarType;
89 
93  ublas::vector<ScalarType> rhs;
94  ublas::vector<ScalarType> ref_result;
95  ublas::vector<ScalarType> result;
96  ublas::compressed_matrix<ScalarType> ublas_matrix;
97 
101  if (!viennacl::io::read_matrix_market_file(ublas_matrix, "../examples/testdata/mat65k.mtx"))
102  {
103  std::cout << "Error reading Matrix file" << std::endl;
104  return EXIT_FAILURE;
105  }
106 
107  if (!readVectorFromFile("../examples/testdata/rhs65025.txt", rhs))
108  {
109  std::cout << "Error reading RHS file" << std::endl;
110  return EXIT_FAILURE;
111  }
112 
113  if (!readVectorFromFile("../examples/testdata/result65025.txt", ref_result))
114  {
115  std::cout << "Error reading Result file" << std::endl;
116  return EXIT_FAILURE;
117  }
118 
122  std::size_t vcl_size = rhs.size();
123  viennacl::compressed_matrix<ScalarType> vcl_compressed_matrix;
124  viennacl::coordinate_matrix<ScalarType> vcl_coordinate_matrix;
125  viennacl::vector<ScalarType> vcl_rhs(vcl_size);
126  viennacl::vector<ScalarType> vcl_result(vcl_size);
127  viennacl::vector<ScalarType> vcl_ref_result(vcl_size);
128 
129  viennacl::copy(rhs.begin(), rhs.end(), vcl_rhs.begin());
130  viennacl::copy(ref_result.begin(), ref_result.end(), vcl_ref_result.begin());
131 
132 
136  viennacl::copy(ublas_matrix, vcl_compressed_matrix);
137 
144  std::vector< std::map< unsigned int, ScalarType> > stl_matrix(rhs.size());
145  for (ublas::compressed_matrix<ScalarType>::iterator1 iter1 = ublas_matrix.begin1();
146  iter1 != ublas_matrix.end1();
147  ++iter1)
148  {
149  for (ublas::compressed_matrix<ScalarType>::iterator2 iter2 = iter1.begin();
150  iter2 != iter1.end();
151  ++iter2)
152  stl_matrix[iter2.index1()][static_cast<unsigned int>(iter2.index2())] = *iter2;
153  }
154  viennacl::copy(stl_matrix, vcl_coordinate_matrix);
155  viennacl::copy(vcl_coordinate_matrix, stl_matrix);
156 
160  std::cout << "Setting up preconditioners for uBLAS-matrix..." << std::endl;
164  viennacl::linalg::ilu0_tag> ublas_block_ilu0(ublas_matrix, viennacl::linalg::ilu0_tag());
165 
166  std::cout << "Setting up preconditioners for ViennaCL-matrix..." << std::endl;
170  viennacl::linalg::ilu0_tag> vcl_block_ilu0(vcl_compressed_matrix, viennacl::linalg::ilu0_tag());
171 
177 
181  std::cout << "----- CG Method -----" << std::endl;
182 
188  result = viennacl::linalg::solve(ublas_matrix, rhs, viennacl::linalg::cg_tag());
189  result = viennacl::linalg::solve(ublas_matrix, rhs, viennacl::linalg::cg_tag(1e-6, 20), ublas_ilut);
190  result = viennacl::linalg::solve(ublas_matrix, rhs, viennacl::linalg::cg_tag(1e-6, 20), ublas_jacobi);
191 
192 
197  vcl_result = viennacl::linalg::solve(vcl_compressed_matrix, vcl_rhs, viennacl::linalg::cg_tag());
198  vcl_result = viennacl::linalg::solve(vcl_compressed_matrix, vcl_rhs, viennacl::linalg::cg_tag(1e-6, 20), vcl_ilut);
199  vcl_result = viennacl::linalg::solve(vcl_compressed_matrix, vcl_rhs, viennacl::linalg::cg_tag(1e-6, 20), vcl_jacobi);
200 
204  std::cout << "----- BiCGStab Method -----" << std::endl;
205 
209  result = viennacl::linalg::solve(ublas_matrix, rhs, viennacl::linalg::bicgstab_tag()); //without preconditioner
210  result = viennacl::linalg::solve(ublas_matrix, rhs, viennacl::linalg::bicgstab_tag(1e-6, 20), ublas_ilut); //with preconditioner
211  result = viennacl::linalg::solve(ublas_matrix, rhs, viennacl::linalg::bicgstab_tag(1e-6, 20), ublas_jacobi); //with preconditioner
212 
213 
218  vcl_result = viennacl::linalg::solve(vcl_compressed_matrix, vcl_rhs, viennacl::linalg::bicgstab_tag()); //without preconditioner
219  vcl_result = viennacl::linalg::solve(vcl_compressed_matrix, vcl_rhs, viennacl::linalg::bicgstab_tag(1e-6, 20), vcl_ilut); //with preconditioner
220  vcl_result = viennacl::linalg::solve(vcl_compressed_matrix, vcl_rhs, viennacl::linalg::bicgstab_tag(1e-6, 20), vcl_jacobi); //with preconditioner
221 
225  std::cout << "----- GMRES Method -----" << std::endl;
226 
230  result = viennacl::linalg::solve(ublas_matrix, rhs, viennacl::linalg::gmres_tag()); //without preconditioner
231  result = viennacl::linalg::solve(ublas_matrix, rhs, viennacl::linalg::gmres_tag(1e-6, 20), ublas_ilut);//with preconditioner
232  result = viennacl::linalg::solve(ublas_matrix, rhs, viennacl::linalg::gmres_tag(1e-6, 20), ublas_jacobi);//with preconditioner
233 
238  vcl_result = viennacl::linalg::solve(vcl_compressed_matrix, vcl_rhs, viennacl::linalg::gmres_tag()); //without preconditioner
239  vcl_result = viennacl::linalg::solve(vcl_compressed_matrix, vcl_rhs, viennacl::linalg::gmres_tag(1e-6, 20), vcl_ilut);//with preconditioner
240  vcl_result = viennacl::linalg::solve(vcl_compressed_matrix, vcl_rhs, viennacl::linalg::gmres_tag(1e-6, 20), vcl_jacobi);//with preconditioner
241 
245  std::cout << "!!!! TUTORIAL COMPLETED SUCCESSFULLY !!!!" << std::endl;
246 
247  return EXIT_SUCCESS;
248 }
249 
A reader and writer for the matrix market format is implemented here.
ILU0 preconditioner class, can be supplied to solve()-routines.
Definition: ilu0.hpp:146
Jacobi preconditioner class, can be supplied to solve()-routines. Generic version for non-ViennaCL ma...
Generic interface for matrix-vector and matrix-matrix products. See viennacl/linalg/vector_operations...
int main()
Definition: bisect.cpp:160
A tag for incomplete LU factorization with static pattern (ILU0)
Definition: ilu0.hpp:58
The stabilized bi-conjugate gradient method is implemented here.
A tag for a jacobi preconditioner.
A block ILU preconditioner class, can be supplied to solve()-routines.
Definition: block_ilu.hpp:132
Implementation of a simple Jacobi preconditioner.
A tag for the solver GMRES. Used for supplying solver parameters and for dispatching the solve() func...
Definition: gmres.hpp:49
Implementation of the coordinate_matrix class.
Implementations of the generalized minimum residual method are in this file.
Implementations of incomplete factorization preconditioners. Convenience header file.
A tag for incomplete LU factorization with threshold (ILUT)
Definition: ilut.hpp:45
Implementation of the compressed_matrix class.
bool readVectorFromFile(const std::string &filename, VectorType &vec)
Definition: vector-io.hpp:104
ILUT preconditioner class, can be supplied to solve()-routines.
Definition: ilut.hpp:252
The conjugate gradient method is implemented here.
The vector type with operator-overloads and proxy classes is defined here. Linear algebra operations ...
void copy(std::vector< NumericT > &cpu_vec, circulant_matrix< NumericT, AlignmentV > &gpu_mat)
Copies a circulant matrix from the std::vector to the OpenCL device (either GPU or multi-core CPU) ...
float ScalarType
Definition: fft_1d.cpp:42
A tag for the conjugate gradient Used for supplying solver parameters and for dispatching the solve()...
Definition: cg.hpp:48
A sparse square matrix in compressed sparse rows format.
A tag for the stabilized Bi-conjugate gradient solver. Used for supplying solver parameters and for d...
Definition: bicgstab.hpp:47
long read_matrix_market_file(MatrixT &mat, const char *file, long index_base=1)
Reads a sparse matrix from a file (MatrixMarket format)
Implementation of the ViennaCL scalar class.
A sparse square matrix, where entries are stored as triplets (i,j, val), where i and j are the row an...
viennacl::vector< NumericT > solve(MatrixT const &A, viennacl::vector_base< NumericT > const &rhs, bicgstab_tag const &tag, viennacl::linalg::no_precond)
Implementation of a pipelined stabilized Bi-conjugate gradient solver.
Definition: bicgstab.hpp:88