\(\newcommand{\W}[1]{ \; #1 \; }\) \(\newcommand{\R}[1]{ {\rm #1} }\) \(\newcommand{\B}[1]{ {\bf #1} }\) \(\newcommand{\D}[2]{ \frac{\partial #1}{\partial #2} }\) \(\newcommand{\DD}[3]{ \frac{\partial^2 #1}{\partial #2 \partial #3} }\) \(\newcommand{\Dpow}[2]{ \frac{\partial^{#1}}{\partial {#2}^{#1}} }\) \(\newcommand{\dpow}[2]{ \frac{ {\rm d}^{#1}}{{\rm d}\, {#2}^{#1}} }\)

double_mat_mul.cpp

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Double Speed: Matrix Multiplication

Specifications

See link_mat_mul .

Implementation

# include <cppad/cppad.hpp>
# include <cppad/speed/mat_sum_sq.hpp>
# include <cppad/speed/uniform_01.hpp>

// Note that CppAD uses global_option["memory"] at the main program level
# include <map>
extern std::map<std::string, bool> global_option;

bool link_mat_mul(
   size_t                           size     ,
   size_t                           repeat   ,
   CppAD::vector<double>&           x        ,
   CppAD::vector<double>&           z        ,
   CppAD::vector<double>&           dz
)
{
   if(global_option["onetape"]||global_option["atomic"]||global_option["optimize"])
      return false;
   // -----------------------------------------------------
   size_t n = size * size; // number of independent variables
   CppAD::vector<double> y(n);

   while(repeat--)
   {  // get the next matrix
      CppAD::uniform_01(n, x);

      // do computation
      mat_sum_sq(size, x, y, z);

   }
   return true;
}