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<div class="title">eigen-with-viennacl.cpp</div> </div>
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<a href="eigen-with-viennacl_8cpp.html">Go to the documentation of this file.</a><div class="fragment"><div class="line"><a name="l00001"></a><span class="lineno"> 1</span> <span class="comment">/* =========================================================================</span></div>
<div class="line"><a name="l00002"></a><span class="lineno"> 2</span> <span class="comment"> Copyright (c) 2010-2016, Institute for Microelectronics,</span></div>
<div class="line"><a name="l00003"></a><span class="lineno"> 3</span> <span class="comment"> Institute for Analysis and Scientific Computing,</span></div>
<div class="line"><a name="l00004"></a><span class="lineno"> 4</span> <span class="comment"> TU Wien.</span></div>
<div class="line"><a name="l00005"></a><span class="lineno"> 5</span> <span class="comment"> Portions of this software are copyright by UChicago Argonne, LLC.</span></div>
<div class="line"><a name="l00006"></a><span class="lineno"> 6</span> <span class="comment"></span></div>
<div class="line"><a name="l00007"></a><span class="lineno"> 7</span> <span class="comment"> -----------------</span></div>
<div class="line"><a name="l00008"></a><span class="lineno"> 8</span> <span class="comment"> ViennaCL - The Vienna Computing Library</span></div>
<div class="line"><a name="l00009"></a><span class="lineno"> 9</span> <span class="comment"> -----------------</span></div>
<div class="line"><a name="l00010"></a><span class="lineno"> 10</span> <span class="comment"></span></div>
<div class="line"><a name="l00011"></a><span class="lineno"> 11</span> <span class="comment"> Project Head: Karl Rupp rupp@iue.tuwien.ac.at</span></div>
<div class="line"><a name="l00012"></a><span class="lineno"> 12</span> <span class="comment"></span></div>
<div class="line"><a name="l00013"></a><span class="lineno"> 13</span> <span class="comment"> (A list of authors and contributors can be found in the PDF manual)</span></div>
<div class="line"><a name="l00014"></a><span class="lineno"> 14</span> <span class="comment"></span></div>
<div class="line"><a name="l00015"></a><span class="lineno"> 15</span> <span class="comment"> License: MIT (X11), see file LICENSE in the base directory</span></div>
<div class="line"><a name="l00016"></a><span class="lineno"> 16</span> <span class="comment">============================================================================= */</span></div>
<div class="line"><a name="l00017"></a><span class="lineno"> 17</span> </div>
<div class="line"><a name="l00025"></a><span class="lineno"> 25</span> <span class="comment">// System headers</span></div>
<div class="line"><a name="l00026"></a><span class="lineno"> 26</span> <span class="preprocessor">#include <iostream></span></div>
<div class="line"><a name="l00027"></a><span class="lineno"> 27</span> </div>
<div class="line"><a name="l00028"></a><span class="lineno"> 28</span> <span class="comment">// Eigen headers</span></div>
<div class="line"><a name="l00029"></a><span class="lineno"> 29</span> <span class="preprocessor">#include <Eigen/Core></span></div>
<div class="line"><a name="l00030"></a><span class="lineno"> 30</span> <span class="preprocessor">#include <Eigen/Sparse></span></div>
<div class="line"><a name="l00031"></a><span class="lineno"> 31</span> </div>
<div class="line"><a name="l00032"></a><span class="lineno"> 32</span> <span class="comment">// IMPORTANT: Must be set prior to any ViennaCL includes if you want to use ViennaCL algorithms on Eigen objects</span></div>
<div class="line"><a name="l00033"></a><span class="lineno"> 33</span> <span class="preprocessor">#define VIENNACL_WITH_EIGEN 1</span></div>
<div class="line"><a name="l00034"></a><span class="lineno"> 34</span> </div>
<div class="line"><a name="l00035"></a><span class="lineno"> 35</span> </div>
<div class="line"><a name="l00036"></a><span class="lineno"> 36</span> <span class="comment">// ViennaCL includes</span></div>
<div class="line"><a name="l00037"></a><span class="lineno"> 37</span> <span class="preprocessor">#include "<a class="code" href="vector_8hpp.html">viennacl/vector.hpp</a>"</span></div>
<div class="line"><a name="l00038"></a><span class="lineno"> 38</span> <span class="preprocessor">#include "<a class="code" href="matrix_8hpp.html">viennacl/matrix.hpp</a>"</span></div>
<div class="line"><a name="l00039"></a><span class="lineno"> 39</span> <span class="preprocessor">#include "<a class="code" href="compressed__matrix_8hpp.html">viennacl/compressed_matrix.hpp</a>"</span></div>
<div class="line"><a name="l00040"></a><span class="lineno"> 40</span> <span class="preprocessor">#include "<a class="code" href="prod_8hpp.html">viennacl/linalg/prod.hpp</a>"</span></div>
<div class="line"><a name="l00041"></a><span class="lineno"> 41</span> </div>
<div class="line"><a name="l00042"></a><span class="lineno"> 42</span> </div>
<div class="line"><a name="l00043"></a><span class="lineno"> 43</span> <span class="comment">// Helper functions for this tutorial:</span></div>
<div class="line"><a name="l00044"></a><span class="lineno"> 44</span> <span class="preprocessor">#include "<a class="code" href="vector-io_8hpp.html">vector-io.hpp</a>"</span></div>
<div class="line"><a name="l00045"></a><span class="lineno"> 45</span> </div>
<div class="line"><a name="l00051"></a><span class="lineno"> 51</span> <span class="comment">//dense matrix:</span></div>
<div class="line"><a name="l00052"></a><span class="lineno"> 52</span> <span class="keyword">template</span><<span class="keyword">typename</span> T></div>
<div class="line"><a name="l00053"></a><span class="lineno"> 53</span> <span class="keyword">struct </span>Eigen_dense_matrix</div>
<div class="line"><a name="l00054"></a><span class="lineno"> 54</span> {</div>
<div class="line"><a name="l00055"></a><span class="lineno"> 55</span>  <span class="keyword">typedef</span> <span class="keyword">typename</span> T::ERROR_NO_EIGEN_TYPE_AVAILABLE error_type;</div>
<div class="line"><a name="l00056"></a><span class="lineno"> 56</span> };</div>
<div class="line"><a name="l00057"></a><span class="lineno"> 57</span> </div>
<div class="line"><a name="l00058"></a><span class="lineno"> 58</span> <span class="keyword">template</span><></div>
<div class="line"><a name="l00059"></a><span class="lineno"> 59</span> <span class="keyword">struct </span>Eigen_dense_matrix<float></div>
<div class="line"><a name="l00060"></a><span class="lineno"> 60</span> {</div>
<div class="line"><a name="l00061"></a><span class="lineno"> 61</span>  <span class="keyword">typedef</span> Eigen::MatrixXf type;</div>
<div class="line"><a name="l00062"></a><span class="lineno"> 62</span> };</div>
<div class="line"><a name="l00063"></a><span class="lineno"> 63</span> </div>
<div class="line"><a name="l00064"></a><span class="lineno"> 64</span> <span class="keyword">template</span><></div>
<div class="line"><a name="l00065"></a><span class="lineno"> 65</span> <span class="keyword">struct </span>Eigen_dense_matrix<double></div>
<div class="line"><a name="l00066"></a><span class="lineno"> 66</span> {</div>
<div class="line"><a name="l00067"></a><span class="lineno"> 67</span>  <span class="keyword">typedef</span> Eigen::MatrixXd type;</div>
<div class="line"><a name="l00068"></a><span class="lineno"> 68</span> };</div>
<div class="line"><a name="l00069"></a><span class="lineno"> 69</span> </div>
<div class="line"><a name="l00070"></a><span class="lineno"> 70</span> </div>
<div class="line"><a name="l00071"></a><span class="lineno"> 71</span> <span class="comment">//sparse matrix</span></div>
<div class="line"><a name="l00072"></a><span class="lineno"> 72</span> <span class="keyword">template</span><<span class="keyword">typename</span> T></div>
<div class="line"><a name="l00073"></a><span class="lineno"> 73</span> <span class="keyword">struct </span>Eigen_vector</div>
<div class="line"><a name="l00074"></a><span class="lineno"> 74</span> {</div>
<div class="line"><a name="l00075"></a><span class="lineno"> 75</span>  <span class="keyword">typedef</span> <span class="keyword">typename</span> T::ERROR_NO_EIGEN_TYPE_AVAILABLE error_type;</div>
<div class="line"><a name="l00076"></a><span class="lineno"> 76</span> };</div>
<div class="line"><a name="l00077"></a><span class="lineno"> 77</span> </div>
<div class="line"><a name="l00078"></a><span class="lineno"> 78</span> <span class="keyword">template</span><></div>
<div class="line"><a name="l00079"></a><span class="lineno"> 79</span> <span class="keyword">struct </span>Eigen_vector<float></div>
<div class="line"><a name="l00080"></a><span class="lineno"> 80</span> {</div>
<div class="line"><a name="l00081"></a><span class="lineno"> 81</span>  <span class="keyword">typedef</span> Eigen::VectorXf type;</div>
<div class="line"><a name="l00082"></a><span class="lineno"> 82</span> };</div>
<div class="line"><a name="l00083"></a><span class="lineno"> 83</span> </div>
<div class="line"><a name="l00084"></a><span class="lineno"> 84</span> <span class="keyword">template</span><></div>
<div class="line"><a name="l00085"></a><span class="lineno"> 85</span> <span class="keyword">struct </span>Eigen_vector<double></div>
<div class="line"><a name="l00086"></a><span class="lineno"> 86</span> {</div>
<div class="line"><a name="l00087"></a><span class="lineno"> 87</span>  <span class="keyword">typedef</span> Eigen::VectorXd type;</div>
<div class="line"><a name="l00088"></a><span class="lineno"> 88</span> };</div>
<div class="line"><a name="l00089"></a><span class="lineno"> 89</span> </div>
<div class="line"><a name="l00090"></a><span class="lineno"> 90</span> </div>
<div class="line"><a name="l00091"></a><span class="lineno"> 91</span> </div>
<div class="line"><a name="l00102"></a><span class="lineno"> 102</span> <span class="keyword">template</span><<span class="keyword">typename</span> ScalarType></div>
<div class="line"><a name="l00103"></a><span class="lineno"> 103</span> <span class="keywordtype">void</span> run_tutorial()</div>
<div class="line"><a name="l00104"></a><span class="lineno"> 104</span> {</div>
<div class="line"><a name="l00109"></a><span class="lineno"> 109</span>  <span class="keyword">typedef</span> <span class="keyword">typename</span> Eigen_dense_matrix<ScalarType>::type EigenMatrix;</div>
<div class="line"><a name="l00110"></a><span class="lineno"> 110</span>  <span class="keyword">typedef</span> <span class="keyword">typename</span> Eigen_vector<ScalarType>::type EigenVector;</div>
<div class="line"><a name="l00111"></a><span class="lineno"> 111</span> </div>
<div class="line"><a name="l00115"></a><span class="lineno"> 115</span>  EigenMatrix eigen_densemat(6, 5);</div>
<div class="line"><a name="l00116"></a><span class="lineno"> 116</span>  EigenMatrix eigen_densemat2(6, 5);</div>
<div class="line"><a name="l00117"></a><span class="lineno"> 117</span>  eigen_densemat(0,0) = 2.0; eigen_densemat(0,1) = -1.0;</div>
<div class="line"><a name="l00118"></a><span class="lineno"> 118</span>  eigen_densemat(1,0) = -1.0; eigen_densemat(1,1) = 2.0; eigen_densemat(1,2) = -1.0;</div>
<div class="line"><a name="l00119"></a><span class="lineno"> 119</span>  eigen_densemat(2,1) = -1.0; eigen_densemat(2,2) = -1.0; eigen_densemat(2,3) = -1.0;</div>
<div class="line"><a name="l00120"></a><span class="lineno"> 120</span>  eigen_densemat(3,2) = -1.0; eigen_densemat(3,3) = 2.0; eigen_densemat(3,4) = -1.0;</div>
<div class="line"><a name="l00121"></a><span class="lineno"> 121</span>  eigen_densemat(5,4) = -1.0; eigen_densemat(4,4) = -1.0;</div>
<div class="line"><a name="l00122"></a><span class="lineno"> 122</span>  Eigen::Map<EigenMatrix> eigen_densemat_map(eigen_densemat.data(), 6, 5); <span class="comment">// same as eigen_densemat, but emulating user-provided buffer</span></div>
<div class="line"><a name="l00123"></a><span class="lineno"> 123</span> </div>
<div class="line"><a name="l00127"></a><span class="lineno"> 127</span>  Eigen::SparseMatrix<ScalarType, Eigen::RowMajor> eigen_sparsemat(6, 5);</div>
<div class="line"><a name="l00128"></a><span class="lineno"> 128</span>  Eigen::SparseMatrix<ScalarType, Eigen::RowMajor> eigen_sparsemat2(6, 5);</div>
<div class="line"><a name="l00129"></a><span class="lineno"> 129</span>  eigen_sparsemat.reserve(5*2);</div>
<div class="line"><a name="l00130"></a><span class="lineno"> 130</span>  eigen_sparsemat.insert(0,0) = 2.0; eigen_sparsemat.insert(0,1) = -1.0;</div>
<div class="line"><a name="l00131"></a><span class="lineno"> 131</span>  eigen_sparsemat.insert(1,1) = 2.0; eigen_sparsemat.insert(1,2) = -1.0;</div>
<div class="line"><a name="l00132"></a><span class="lineno"> 132</span>  eigen_sparsemat.insert(2,2) = -1.0; eigen_sparsemat.insert(2,3) = -1.0;</div>
<div class="line"><a name="l00133"></a><span class="lineno"> 133</span>  eigen_sparsemat.insert(3,3) = 2.0; eigen_sparsemat.insert(3,4) = -1.0;</div>
<div class="line"><a name="l00134"></a><span class="lineno"> 134</span>  eigen_sparsemat.insert(5,4) = -1.0;</div>
<div class="line"><a name="l00135"></a><span class="lineno"> 135</span>  <span class="comment">//eigen_sparsemat.endFill();</span></div>
<div class="line"><a name="l00136"></a><span class="lineno"> 136</span> </div>
<div class="line"><a name="l00140"></a><span class="lineno"> 140</span>  EigenVector eigen_rhs(5);</div>
<div class="line"><a name="l00141"></a><span class="lineno"> 141</span>  Eigen::Map<EigenVector> eigen_rhs_map(eigen_rhs.data(), 5);</div>
<div class="line"><a name="l00142"></a><span class="lineno"> 142</span>  EigenVector eigen_result(6);</div>
<div class="line"><a name="l00143"></a><span class="lineno"> 143</span>  EigenVector eigen_temp(6);</div>
<div class="line"><a name="l00144"></a><span class="lineno"> 144</span> </div>
<div class="line"><a name="l00145"></a><span class="lineno"> 145</span>  eigen_rhs(0) = 10.0;</div>
<div class="line"><a name="l00146"></a><span class="lineno"> 146</span>  eigen_rhs(1) = 11.0;</div>
<div class="line"><a name="l00147"></a><span class="lineno"> 147</span>  eigen_rhs(2) = 12.0;</div>
<div class="line"><a name="l00148"></a><span class="lineno"> 148</span>  eigen_rhs(3) = 13.0;</div>
<div class="line"><a name="l00149"></a><span class="lineno"> 149</span>  eigen_rhs(4) = 14.0;</div>
<div class="line"><a name="l00150"></a><span class="lineno"> 150</span> </div>
<div class="line"><a name="l00151"></a><span class="lineno"> 151</span> </div>
<div class="line"><a name="l00155"></a><span class="lineno"> 155</span>  <a class="code" href="classviennacl_1_1vector.html">viennacl::vector<ScalarType></a> vcl_rhs(5);</div>
<div class="line"><a name="l00156"></a><span class="lineno"> 156</span>  <a class="code" href="classviennacl_1_1vector.html">viennacl::vector<ScalarType></a> vcl_result(6);</div>
<div class="line"><a name="l00157"></a><span class="lineno"> 157</span>  <a class="code" href="classviennacl_1_1matrix.html">viennacl::matrix<ScalarType></a> vcl_densemat(6, 5);</div>
<div class="line"><a name="l00158"></a><span class="lineno"> 158</span>  <a class="code" href="classviennacl_1_1compressed__matrix.html">viennacl::compressed_matrix<ScalarType></a> vcl_sparsemat(6, 5);</div>
<div class="line"><a name="l00159"></a><span class="lineno"> 159</span> </div>
<div class="line"><a name="l00160"></a><span class="lineno"> 160</span> </div>
<div class="line"><a name="l00164"></a><span class="lineno"> 164</span>  <a class="code" href="namespaceviennacl.html#a10b7f8cf6b8864a7aa196d670481a453">viennacl::copy</a>(&(eigen_rhs[0]), &(eigen_rhs[0]) + 5, vcl_rhs.begin()); <span class="comment">// Method 1: via iterator interface (cf. std::copy())</span></div>
<div class="line"><a name="l00165"></a><span class="lineno"> 165</span>  <a class="code" href="namespaceviennacl.html#a10b7f8cf6b8864a7aa196d670481a453">viennacl::copy</a>(eigen_rhs, vcl_rhs); <span class="comment">// Method 2: via built-in wrappers (convenience layer)</span></div>
<div class="line"><a name="l00166"></a><span class="lineno"> 166</span>  <a class="code" href="namespaceviennacl.html#a10b7f8cf6b8864a7aa196d670481a453">viennacl::copy</a>(eigen_rhs_map, vcl_rhs); <span class="comment">// Same as method 2, but for a mapped vector</span></div>
<div class="line"><a name="l00167"></a><span class="lineno"> 167</span> </div>
<div class="line"><a name="l00168"></a><span class="lineno"> 168</span>  <a class="code" href="namespaceviennacl.html#a10b7f8cf6b8864a7aa196d670481a453">viennacl::copy</a>(eigen_densemat, vcl_densemat);</div>
<div class="line"><a name="l00169"></a><span class="lineno"> 169</span>  <a class="code" href="namespaceviennacl.html#a10b7f8cf6b8864a7aa196d670481a453">viennacl::copy</a>(eigen_densemat_map, vcl_densemat); <span class="comment">//same as above, using mapped matrix</span></div>
<div class="line"><a name="l00170"></a><span class="lineno"> 170</span>  <a class="code" href="namespaceviennacl.html#a10b7f8cf6b8864a7aa196d670481a453">viennacl::copy</a>(eigen_sparsemat, vcl_sparsemat);</div>
<div class="line"><a name="l00171"></a><span class="lineno"> 171</span>  std::cout << <span class="stringliteral">"VCL sparsematrix dimensions: "</span> << vcl_sparsemat.size1() << <span class="stringliteral">", "</span> << vcl_sparsemat.size2() << std::endl;</div>
<div class="line"><a name="l00172"></a><span class="lineno"> 172</span> </div>
<div class="line"><a name="l00173"></a><span class="lineno"> 173</span>  <span class="comment">// For completeness: Copy matrices from ViennaCL back to Eigen:</span></div>
<div class="line"><a name="l00174"></a><span class="lineno"> 174</span>  <a class="code" href="namespaceviennacl.html#a10b7f8cf6b8864a7aa196d670481a453">viennacl::copy</a>(vcl_densemat, eigen_densemat2);</div>
<div class="line"><a name="l00175"></a><span class="lineno"> 175</span>  <a class="code" href="namespaceviennacl.html#a10b7f8cf6b8864a7aa196d670481a453">viennacl::copy</a>(vcl_sparsemat, eigen_sparsemat2);</div>
<div class="line"><a name="l00176"></a><span class="lineno"> 176</span> </div>
<div class="line"><a name="l00177"></a><span class="lineno"> 177</span> </div>
<div class="line"><a name="l00181"></a><span class="lineno"> 181</span>  eigen_result = eigen_densemat * eigen_rhs;</div>
<div class="line"><a name="l00182"></a><span class="lineno"> 182</span>  vcl_result = <a class="code" href="namespaceviennacl_1_1linalg.html#aa18d10f8a90e38bd9ff43c650fc670ef">viennacl::linalg::prod</a>(vcl_densemat, vcl_rhs);</div>
<div class="line"><a name="l00183"></a><span class="lineno"> 183</span>  <a class="code" href="namespaceviennacl.html#a10b7f8cf6b8864a7aa196d670481a453">viennacl::copy</a>(vcl_result, eigen_temp);</div>
<div class="line"><a name="l00184"></a><span class="lineno"> 184</span>  std::cout << <span class="stringliteral">"Difference for dense matrix-vector product: "</span> << (eigen_result - eigen_temp).norm() << std::endl;</div>
<div class="line"><a name="l00185"></a><span class="lineno"> 185</span>  std::cout << <span class="stringliteral">"Difference for dense matrix-vector product (Eigen->ViennaCL->Eigen): "</span></div>
<div class="line"><a name="l00186"></a><span class="lineno"> 186</span>  << (eigen_densemat2 * eigen_rhs - eigen_temp).norm() << std::endl;</div>
<div class="line"><a name="l00187"></a><span class="lineno"> 187</span> </div>
<div class="line"><a name="l00191"></a><span class="lineno"> 191</span>  eigen_result = eigen_sparsemat * eigen_rhs;</div>
<div class="line"><a name="l00192"></a><span class="lineno"> 192</span>  vcl_result = <a class="code" href="namespaceviennacl_1_1linalg.html#aa18d10f8a90e38bd9ff43c650fc670ef">viennacl::linalg::prod</a>(vcl_sparsemat, vcl_rhs);</div>
<div class="line"><a name="l00193"></a><span class="lineno"> 193</span>  <a class="code" href="namespaceviennacl.html#a10b7f8cf6b8864a7aa196d670481a453">viennacl::copy</a>(vcl_result, eigen_temp);</div>
<div class="line"><a name="l00194"></a><span class="lineno"> 194</span>  std::cout << <span class="stringliteral">"Difference for sparse matrix-vector product: "</span> << (eigen_result - eigen_temp).norm() << std::endl;</div>
<div class="line"><a name="l00195"></a><span class="lineno"> 195</span>  std::cout << <span class="stringliteral">"Difference for sparse matrix-vector product (Eigen->ViennaCL->Eigen): "</span></div>
<div class="line"><a name="l00196"></a><span class="lineno"> 196</span>  << (eigen_sparsemat2 * eigen_rhs - eigen_temp).norm() << std::endl;</div>
<div class="line"><a name="l00197"></a><span class="lineno"> 197</span> }</div>
<div class="line"><a name="l00198"></a><span class="lineno"> 198</span> </div>
<div class="line"><a name="l00199"></a><span class="lineno"> 199</span> </div>
<div class="line"><a name="l00203"></a><span class="lineno"> 203</span> <span class="keywordtype">int</span> <a class="code" href="tests_2src_2bisect_8cpp.html#ae66f6b31b5ad750f1fe042a706a4e3d4">main</a>(<span class="keywordtype">int</span>, <span class="keywordtype">char</span> *[])</div>
<div class="line"><a name="l00204"></a><span class="lineno"> 204</span> {</div>
<div class="line"><a name="l00205"></a><span class="lineno"> 205</span>  std::cout << <span class="stringliteral">"----------------------------------------------"</span> << std::endl;</div>
<div class="line"><a name="l00206"></a><span class="lineno"> 206</span>  std::cout << <span class="stringliteral">"## Single precision"</span> << std::endl;</div>
<div class="line"><a name="l00207"></a><span class="lineno"> 207</span>  std::cout << <span class="stringliteral">"----------------------------------------------"</span> << std::endl;</div>
<div class="line"><a name="l00208"></a><span class="lineno"> 208</span>  run_tutorial<float>();</div>
<div class="line"><a name="l00209"></a><span class="lineno"> 209</span> </div>
<div class="line"><a name="l00210"></a><span class="lineno"> 210</span> <span class="preprocessor">#ifdef VIENNACL_HAVE_OPENCL</span></div>
<div class="line"><a name="l00211"></a><span class="lineno"> 211</span>  <span class="keywordflow">if</span> ( <a class="code" href="namespaceviennacl_1_1ocl.html#ac54d59a74deaccec81f64e738b856348">viennacl::ocl::current_device</a>().<a class="code" href="classviennacl_1_1ocl_1_1device.html#a5182025f56c76de6770e26b14165b00a">double_support</a>() )</div>
<div class="line"><a name="l00212"></a><span class="lineno"> 212</span> #endif</div>
<div class="line"><a name="l00213"></a><span class="lineno"> 213</span>  {</div>
<div class="line"><a name="l00214"></a><span class="lineno"> 214</span>  std::cout << <span class="stringliteral">"----------------------------------------------"</span> << std::endl;</div>
<div class="line"><a name="l00215"></a><span class="lineno"> 215</span>  std::cout << <span class="stringliteral">"## Double precision"</span> << std::endl;</div>
<div class="line"><a name="l00216"></a><span class="lineno"> 216</span>  std::cout << <span class="stringliteral">"----------------------------------------------"</span> << std::endl;</div>
<div class="line"><a name="l00217"></a><span class="lineno"> 217</span>  run_tutorial<double>();</div>
<div class="line"><a name="l00218"></a><span class="lineno"> 218</span>  }</div>
<div class="line"><a name="l00219"></a><span class="lineno"> 219</span> </div>
<div class="line"><a name="l00223"></a><span class="lineno"> 223</span>  std::cout << std::endl;</div>
<div class="line"><a name="l00224"></a><span class="lineno"> 224</span>  std::cout << <span class="stringliteral">"!!!! TUTORIAL COMPLETED SUCCESSFULLY !!!!"</span> << std::endl;</div>
<div class="line"><a name="l00225"></a><span class="lineno"> 225</span>  std::cout << std::endl;</div>
<div class="line"><a name="l00226"></a><span class="lineno"> 226</span> </div>
<div class="line"><a name="l00227"></a><span class="lineno"> 227</span> }</div>
<div class="ttc" id="prod_8hpp_html"><div class="ttname"><a href="prod_8hpp.html">prod.hpp</a></div><div class="ttdoc">Generic interface for matrix-vector and matrix-matrix products. See viennacl/linalg/vector_operations...</div></div>
<div class="ttc" id="matrix_8hpp_html"><div class="ttname"><a href="matrix_8hpp.html">matrix.hpp</a></div><div class="ttdoc">Implementation of the dense matrix class. </div></div>
<div class="ttc" id="tests_2src_2bisect_8cpp_html_ae66f6b31b5ad750f1fe042a706a4e3d4"><div class="ttname"><a href="tests_2src_2bisect_8cpp.html#ae66f6b31b5ad750f1fe042a706a4e3d4">main</a></div><div class="ttdeci">int main()</div><div class="ttdef"><b>Definition:</b> <a href="tests_2src_2bisect_8cpp_source.html#l00091">bisect.cpp:91</a></div></div>
<div class="ttc" id="vector-io_8hpp_html"><div class="ttname"><a href="vector-io_8hpp.html">vector-io.hpp</a></div></div>
<div class="ttc" id="classviennacl_1_1matrix_html"><div class="ttname"><a href="classviennacl_1_1matrix.html">viennacl::matrix</a></div><div class="ttdoc">A dense matrix class. </div><div class="ttdef"><b>Definition:</b> <a href="forwards_8h_source.html#l00375">forwards.h:375</a></div></div>
<div class="ttc" id="namespaceviennacl_1_1ocl_html_ac54d59a74deaccec81f64e738b856348"><div class="ttname"><a href="namespaceviennacl_1_1ocl.html#ac54d59a74deaccec81f64e738b856348">viennacl::ocl::current_device</a></div><div class="ttdeci">viennacl::ocl::device const & current_device()</div><div class="ttdoc">Convenience function for returning the active device in the current context. </div><div class="ttdef"><b>Definition:</b> <a href="backend_8hpp_source.html#l00351">backend.hpp:351</a></div></div>
<div class="ttc" id="namespaceviennacl_1_1linalg_html_aa18d10f8a90e38bd9ff43c650fc670ef"><div class="ttname"><a href="namespaceviennacl_1_1linalg.html#aa18d10f8a90e38bd9ff43c650fc670ef">viennacl::linalg::prod</a></div><div class="ttdeci">VectorT prod(std::vector< std::vector< T, A1 >, A2 > const &matrix, VectorT const &vector)</div><div class="ttdef"><b>Definition:</b> <a href="prod_8hpp_source.html#l00102">prod.hpp:102</a></div></div>
<div class="ttc" id="compressed__matrix_8hpp_html"><div class="ttname"><a href="compressed__matrix_8hpp.html">compressed_matrix.hpp</a></div><div class="ttdoc">Implementation of the compressed_matrix class. </div></div>
<div class="ttc" id="classviennacl_1_1ocl_1_1device_html_a5182025f56c76de6770e26b14165b00a"><div class="ttname"><a href="classviennacl_1_1ocl_1_1device.html#a5182025f56c76de6770e26b14165b00a">viennacl::ocl::device::double_support</a></div><div class="ttdeci">bool double_support() const </div><div class="ttdoc">ViennaCL convenience function: Returns true if the device supports double precision. </div><div class="ttdef"><b>Definition:</b> <a href="device_8hpp_source.html#l00956">device.hpp:956</a></div></div>
<div class="ttc" id="classviennacl_1_1vector_html"><div class="ttname"><a href="classviennacl_1_1vector.html">viennacl::vector< ScalarType ></a></div></div>
<div class="ttc" id="vector_8hpp_html"><div class="ttname"><a href="vector_8hpp.html">vector.hpp</a></div><div class="ttdoc">The vector type with operator-overloads and proxy classes is defined here. Linear algebra operations ...</div></div>
<div class="ttc" id="namespaceviennacl_html_a10b7f8cf6b8864a7aa196d670481a453"><div class="ttname"><a href="namespaceviennacl.html#a10b7f8cf6b8864a7aa196d670481a453">viennacl::copy</a></div><div class="ttdeci">void copy(std::vector< NumericT > &cpu_vec, circulant_matrix< NumericT, AlignmentV > &gpu_mat)</div><div class="ttdoc">Copies a circulant matrix from the std::vector to the OpenCL device (either GPU or multi-core CPU) ...</div><div class="ttdef"><b>Definition:</b> <a href="circulant__matrix_8hpp_source.html#l00150">circulant_matrix.hpp:150</a></div></div>
<div class="ttc" id="classviennacl_1_1compressed__matrix_html"><div class="ttname"><a href="classviennacl_1_1compressed__matrix.html">viennacl::compressed_matrix</a></div><div class="ttdoc">A sparse square matrix in compressed sparse rows format. </div><div class="ttdef"><b>Definition:</b> <a href="compressed__matrix_8hpp_source.html#l00559">compressed_matrix.hpp:559</a></div></div>
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