35 #include <boost/numeric/ublas/io.hpp> 
   36 #include <boost/numeric/ublas/triangular.hpp> 
   37 #include <boost/numeric/ublas/matrix_sparse.hpp> 
   38 #include <boost/numeric/ublas/matrix.hpp> 
   39 #include <boost/numeric/ublas/matrix_proxy.hpp> 
   40 #include <boost/numeric/ublas/lu.hpp> 
   41 #include <boost/numeric/ublas/io.hpp> 
   45 #define VIENNACL_WITH_UBLAS 1 
   56 #define BLAS3_MATRIX_SIZE   400 
   58 using namespace boost::numeric;
 
   65 #ifndef VIENNACL_WITH_OPENCL 
   68     std::size_t 
size()
 const { 
return 1; }
 
   92   for (
unsigned int i = 0; i < ublas_A.size1(); ++i)
 
   93     for (
unsigned int j = 0; j < ublas_A.size2(); ++j)
 
   94       ublas_A(i,j) = randomNumber();
 
   96   for (
unsigned int i = 0; i < ublas_B.size1(); ++i)
 
   97     for (
unsigned int j = 0; j < ublas_B.size2(); ++j)
 
   98       ublas_B(i,j) = randomNumber();
 
  113   std::cout << 
"--- Computing matrix-matrix product using ublas ---" << std::endl;
 
  116   exec_time = timer.
get();
 
  117   std::cout << 
" - Execution time: " << exec_time << std::endl;
 
  123   std::cout << std::endl << 
"--- Computing matrix-matrix product on each available compute device using ViennaCL ---" << std::endl;
 
  124 #ifdef VIENNACL_WITH_OPENCL 
  130   for (std::size_t device_id=0; device_id<devices.size(); ++device_id)
 
  132 #ifdef VIENNACL_WITH_OPENCL 
  147     exec_time = timer.
get();
 
  148     std::cout << 
" - Execution time on device (no setup time included): " << exec_time << std::endl;
 
  155     std::cout << 
" - Checking result... ";
 
  156     bool check_ok = 
true;
 
  157     for (std::size_t i = 0; i < ublas_A.size1(); ++i)
 
  159       for (std::size_t j = 0; j < ublas_A.size2(); ++j)
 
  161         if ( std::fabs(ublas_C1(i,j) - ublas_C(i,j)) / ublas_C(i,j) > 1e-4 )
 
  171       std::cout << 
"[OK]" << std::endl << std::endl;
 
  173       std::cout << 
"[FAILED]" << std::endl << std::endl;
 
  180   std::cout << 
"!!!! TUTORIAL COMPLETED SUCCESSFULLY !!!!" << std::endl;
 
void switch_device(vcl_size_t i)
Switches the current device to the i-th device in this context. 
Generic interface for matrix-vector and matrix-matrix products. See viennacl/linalg/vector_operations...
Implementation of the dense matrix class. 
viennacl::ocl::context & current_context()
Convenience function for returning the current context. 
void finish()
Synchronizes the execution. finish() will only return after all compute kernels (CUDA, OpenCL) have completed. 
viennacl::ocl::device const & current_device()
Convenience function for returning the active device in the current context. 
VectorT prod(std::vector< std::vector< T, A1 >, A2 > const &matrix, VectorT const &vector)
vcl_size_t size(VectorType const &vec)
Generic routine for obtaining the size of a vector (ViennaCL, uBLAS, etc.) 
std::string name() const 
Device name string. 
#define BLAS3_MATRIX_SIZE
A simple, yet (mostly) sufficiently accurate timer for benchmarking and profiling. 
void prod(std::vector< std::map< IndexT, NumericT > > const &stl_A, std::vector< std::map< IndexT, NumericT > > const &stl_B, std::vector< std::map< IndexT, NumericT > > &stl_C)
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) ...
A small collection of sequential random number generators. 
std::vector< viennacl::ocl::device > const & devices() const 
Returns a vector with all devices in this context. 
Implementation of the ViennaCL scalar class.