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<div class="title">svd.hpp</div> </div>
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<a href="svd_8hpp.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="preprocessor">#ifndef VIENNACL_LINALG_SVD_HPP</span></div>
<div class="line"><a name="l00002"></a><span class="lineno"> 2</span> <span class="preprocessor">#define VIENNACL_LINALG_SVD_HPP</span></div>
<div class="line"><a name="l00003"></a><span class="lineno"> 3</span> </div>
<div class="line"><a name="l00004"></a><span class="lineno"> 4</span> <span class="comment">/* =========================================================================</span></div>
<div class="line"><a name="l00005"></a><span class="lineno"> 5</span> <span class="comment"> Copyright (c) 2010-2016, Institute for Microelectronics,</span></div>
<div class="line"><a name="l00006"></a><span class="lineno"> 6</span> <span class="comment"> Institute for Analysis and Scientific Computing,</span></div>
<div class="line"><a name="l00007"></a><span class="lineno"> 7</span> <span class="comment"> TU Wien.</span></div>
<div class="line"><a name="l00008"></a><span class="lineno"> 8</span> <span class="comment"> Portions of this software are copyright by UChicago Argonne, LLC.</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"> ViennaCL - The Vienna Computing Library</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"></span></div>
<div class="line"><a name="l00014"></a><span class="lineno"> 14</span> <span class="comment"> Project Head: Karl Rupp rupp@iue.tuwien.ac.at</span></div>
<div class="line"><a name="l00015"></a><span class="lineno"> 15</span> <span class="comment"></span></div>
<div class="line"><a name="l00016"></a><span class="lineno"> 16</span> <span class="comment"> (A list of authors and contributors can be found in the manual)</span></div>
<div class="line"><a name="l00017"></a><span class="lineno"> 17</span> <span class="comment"></span></div>
<div class="line"><a name="l00018"></a><span class="lineno"> 18</span> <span class="comment"> License: MIT (X11), see file LICENSE in the base directory</span></div>
<div class="line"><a name="l00019"></a><span class="lineno"> 19</span> <span class="comment">============================================================================= */</span></div>
<div class="line"><a name="l00020"></a><span class="lineno"> 20</span> </div>
<div class="line"><a name="l00028"></a><span class="lineno"> 28</span> <span class="comment">// Note: Boost.uBLAS is required at the moment</span></div>
<div class="line"><a name="l00029"></a><span class="lineno"> 29</span> <span class="preprocessor">#include <boost/numeric/ublas/vector.hpp></span></div>
<div class="line"><a name="l00030"></a><span class="lineno"> 30</span> <span class="preprocessor">#include <boost/numeric/ublas/matrix.hpp></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> </div>
<div class="line"><a name="l00033"></a><span class="lineno"> 33</span> <span class="preprocessor">#include <cmath></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> <span class="preprocessor">#include "<a class="code" href="matrix_8hpp.html">viennacl/matrix.hpp</a>"</span></div>
<div class="line"><a name="l00036"></a><span class="lineno"> 36</span> <span class="preprocessor">#include "<a class="code" href="opencl_2kernels_2svd_8hpp.html">viennacl/linalg/opencl/kernels/svd.hpp</a>"</span></div>
<div class="line"><a name="l00037"></a><span class="lineno"> 37</span> <span class="preprocessor">#include "<a class="code" href="qr-method-common_8hpp.html">viennacl/linalg/qr-method-common.hpp</a>"</span></div>
<div class="line"><a name="l00038"></a><span class="lineno"> 38</span> </div>
<div class="line"><a name="l00039"></a><span class="lineno"> 39</span> <span class="keyword">namespace </span>viennacl</div>
<div class="line"><a name="l00040"></a><span class="lineno"> 40</span> {</div>
<div class="line"><a name="l00041"></a><span class="lineno"> 41</span>  <span class="keyword">namespace </span>linalg</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> </div>
<div class="line"><a name="l00044"></a><span class="lineno"> 44</span>  <span class="keyword">namespace </span>detail</div>
<div class="line"><a name="l00045"></a><span class="lineno"> 45</span>  {</div>
<div class="line"><a name="l00046"></a><span class="lineno"> 46</span> </div>
<div class="line"><a name="l00047"></a><span class="lineno"> 47</span>  <span class="keyword">template</span><<span class="keyword">typename</span> MatrixType, <span class="keyword">typename</span> VectorType></div>
<div class="line"><a name="l00048"></a><span class="lineno"><a class="line" href="namespaceviennacl_1_1linalg_1_1detail.html#a76be0f2fd292f0e457e364e20d512e17"> 48</a></span>  <span class="keywordtype">void</span> <a class="code" href="namespaceviennacl_1_1linalg_1_1detail.html#a76be0f2fd292f0e457e364e20d512e17">givens_prev</a>(MatrixType & <a class="code" href="classviennacl_1_1matrix.html">matrix</a>,</div>
<div class="line"><a name="l00049"></a><span class="lineno"> 49</span>  VectorType & tmp1,</div>
<div class="line"><a name="l00050"></a><span class="lineno"> 50</span>  VectorType & tmp2,</div>
<div class="line"><a name="l00051"></a><span class="lineno"> 51</span>  <span class="keywordtype">int</span> n,</div>
<div class="line"><a name="l00052"></a><span class="lineno"> 52</span>  <span class="keywordtype">int</span> l,</div>
<div class="line"><a name="l00053"></a><span class="lineno"> 53</span>  <span class="keywordtype">int</span> k</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>  {</div>
<div class="line"><a name="l00056"></a><span class="lineno"> 56</span>  <span class="keyword">typedef</span> <span class="keyword">typename</span> MatrixType::value_type <a class="code" href="fft__1d_8cpp.html#ad5c19ca4f47d3f8ec21232a5af2624e5">ScalarType</a>;</div>
<div class="line"><a name="l00057"></a><span class="lineno"> 57</span>  <span class="keyword">typedef</span> <span class="keyword">typename</span> <a class="code" href="structviennacl_1_1result__of_1_1cpu__value__type.html#aa015d93f419985879a7c13b09633c5c6">viennacl::result_of::cpu_value_type<ScalarType>::type</a> CPU_ScalarType;</div>
<div class="line"><a name="l00058"></a><span class="lineno"> 58</span> </div>
<div class="line"><a name="l00059"></a><span class="lineno"> 59</span>  <a class="code" href="classviennacl_1_1ocl_1_1context.html">viennacl::ocl::context</a> & ctx = <span class="keyword">const_cast<</span><a class="code" href="classviennacl_1_1ocl_1_1context.html">viennacl::ocl::context</a> &<span class="keyword">></span>(viennacl::traits::opencl_handle(matrix).context());</div>
<div class="line"><a name="l00060"></a><span class="lineno"> 60</span>  <a class="code" href="classviennacl_1_1ocl_1_1kernel.html">viennacl::ocl::kernel</a> & kernel = ctx.<a class="code" href="classviennacl_1_1ocl_1_1context.html#afe68ad8c2df449f40f45db6605038946">get_kernel</a>(<a class="code" href="structviennacl_1_1linalg_1_1opencl_1_1kernels_1_1svd.html">viennacl::linalg::opencl::kernels::svd<CPU_ScalarType>::program_name</a>(), <a class="code" href="namespaceviennacl_1_1linalg.html#a15bedacb51ec9b425baf52ee7f68bdba">SVD_GIVENS_PREV_KERNEL</a>);</div>
<div class="line"><a name="l00061"></a><span class="lineno"> 61</span> </div>
<div class="line"><a name="l00062"></a><span class="lineno"> 62</span>  kernel.<a class="code" href="classviennacl_1_1ocl_1_1kernel.html#a0144c18ae9f07722e5b5697335b7cff5">global_work_size</a>(0, viennacl::tools::align_to_multiple<vcl_size_t>(<a class="code" href="namespaceviennacl_1_1traits.html#aa756f5d6820722094cae0d8b9bb6d5e2">viennacl::traits::size1</a>(matrix), 256));</div>
<div class="line"><a name="l00063"></a><span class="lineno"> 63</span>  kernel.<a class="code" href="classviennacl_1_1ocl_1_1kernel.html#ae2b841c487f9ddbfcfb6297d648e2d7f">local_work_size</a>(0, 256);</div>
<div class="line"><a name="l00064"></a><span class="lineno"> 64</span> </div>
<div class="line"><a name="l00065"></a><span class="lineno"> 65</span>  <a class="code" href="namespaceviennacl_1_1ocl.html#a5f2022f653ea1cf364d20e3ff84dcada">viennacl::ocl::enqueue</a>(kernel(</div>
<div class="line"><a name="l00066"></a><span class="lineno"> 66</span>  matrix,</div>
<div class="line"><a name="l00067"></a><span class="lineno"> 67</span>  tmp1,</div>
<div class="line"><a name="l00068"></a><span class="lineno"> 68</span>  tmp2,</div>
<div class="line"><a name="l00069"></a><span class="lineno"> 69</span>  static_cast<cl_uint>(n),</div>
<div class="line"><a name="l00070"></a><span class="lineno"> 70</span>  static_cast<cl_uint>(matrix.internal_size1()),</div>
<div class="line"><a name="l00071"></a><span class="lineno"> 71</span>  static_cast<cl_uint>(l + 1),</div>
<div class="line"><a name="l00072"></a><span class="lineno"> 72</span>  <span class="keyword">static_cast<</span>cl_uint<span class="keyword">></span>(k + 1)</div>
<div class="line"><a name="l00073"></a><span class="lineno"> 73</span>  ));</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> </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>  <span class="keyword">template</span><<span class="keyword">typename</span> MatrixType, <span class="keyword">typename</span> VectorType></div>
<div class="line"><a name="l00078"></a><span class="lineno"><a class="line" href="namespaceviennacl_1_1linalg_1_1detail.html#a1f9130eb00ff2625dff55b18e0ac1553"> 78</a></span>  <span class="keywordtype">void</span> <a class="code" href="namespaceviennacl_1_1linalg_1_1detail.html#a1f9130eb00ff2625dff55b18e0ac1553">change_signs</a>(MatrixType& <a class="code" href="classviennacl_1_1matrix.html">matrix</a>, VectorType& signs, <span class="keywordtype">int</span> n)</div>
<div class="line"><a name="l00079"></a><span class="lineno"> 79</span>  {</div>
<div class="line"><a name="l00080"></a><span class="lineno"> 80</span>  <span class="keyword">typedef</span> <span class="keyword">typename</span> MatrixType::value_type <a class="code" href="fft__1d_8cpp.html#ad5c19ca4f47d3f8ec21232a5af2624e5">ScalarType</a>;</div>
<div class="line"><a name="l00081"></a><span class="lineno"> 81</span>  <span class="keyword">typedef</span> <span class="keyword">typename</span> <a class="code" href="structviennacl_1_1result__of_1_1cpu__value__type.html#aa015d93f419985879a7c13b09633c5c6">viennacl::result_of::cpu_value_type<ScalarType>::type</a> CPU_ScalarType;</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>  <a class="code" href="classviennacl_1_1ocl_1_1context.html">viennacl::ocl::context</a> & ctx = <span class="keyword">const_cast<</span><a class="code" href="classviennacl_1_1ocl_1_1context.html">viennacl::ocl::context</a> &<span class="keyword">></span>(viennacl::traits::opencl_handle(matrix).context());</div>
<div class="line"><a name="l00084"></a><span class="lineno"> 84</span>  <a class="code" href="classviennacl_1_1ocl_1_1kernel.html">viennacl::ocl::kernel</a> & kernel = ctx.<a class="code" href="classviennacl_1_1ocl_1_1context.html#afe68ad8c2df449f40f45db6605038946">get_kernel</a>(<a class="code" href="structviennacl_1_1linalg_1_1opencl_1_1kernels_1_1svd.html">viennacl::linalg::opencl::kernels::svd<CPU_ScalarType>::program_name</a>(), <a class="code" href="namespaceviennacl_1_1linalg.html#a05717ddd22894376e780b075d59616ed">SVD_INVERSE_SIGNS_KERNEL</a>);</div>
<div class="line"><a name="l00085"></a><span class="lineno"> 85</span> </div>
<div class="line"><a name="l00086"></a><span class="lineno"> 86</span>  kernel.<a class="code" href="classviennacl_1_1ocl_1_1kernel.html#a0144c18ae9f07722e5b5697335b7cff5">global_work_size</a>(0, viennacl::tools::align_to_multiple<vcl_size_t>(<a class="code" href="namespaceviennacl_1_1traits.html#aa756f5d6820722094cae0d8b9bb6d5e2">viennacl::traits::size1</a>(matrix), 16));</div>
<div class="line"><a name="l00087"></a><span class="lineno"> 87</span>  kernel.<a class="code" href="classviennacl_1_1ocl_1_1kernel.html#a0144c18ae9f07722e5b5697335b7cff5">global_work_size</a>(1, viennacl::tools::align_to_multiple<vcl_size_t>(<a class="code" href="namespaceviennacl_1_1traits.html#a3658e7c29ac0f60a20cb5871f5b5fd98">viennacl::traits::size2</a>(matrix), 16));</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>  kernel.<a class="code" href="classviennacl_1_1ocl_1_1kernel.html#ae2b841c487f9ddbfcfb6297d648e2d7f">local_work_size</a>(0, 16);</div>
<div class="line"><a name="l00090"></a><span class="lineno"> 90</span>  kernel.<a class="code" href="classviennacl_1_1ocl_1_1kernel.html#ae2b841c487f9ddbfcfb6297d648e2d7f">local_work_size</a>(1, 16);</div>
<div class="line"><a name="l00091"></a><span class="lineno"> 91</span> </div>
<div class="line"><a name="l00092"></a><span class="lineno"> 92</span>  <a class="code" href="namespaceviennacl_1_1ocl.html#a5f2022f653ea1cf364d20e3ff84dcada">viennacl::ocl::enqueue</a>(kernel(</div>
<div class="line"><a name="l00093"></a><span class="lineno"> 93</span>  matrix,</div>
<div class="line"><a name="l00094"></a><span class="lineno"> 94</span>  signs,</div>
<div class="line"><a name="l00095"></a><span class="lineno"> 95</span>  static_cast<cl_uint>(n),</div>
<div class="line"><a name="l00096"></a><span class="lineno"> 96</span>  static_cast<cl_uint>(matrix.internal_size1())</div>
<div class="line"><a name="l00097"></a><span class="lineno"> 97</span>  ));</div>
<div class="line"><a name="l00098"></a><span class="lineno"> 98</span>  }</div>
<div class="line"><a name="l00099"></a><span class="lineno"> 99</span> </div>
<div class="line"><a name="l00100"></a><span class="lineno"> 100</span>  <span class="keyword">template</span><<span class="keyword">typename</span> MatrixType, <span class="keyword">typename</span> CPU_VectorType></div>
<div class="line"><a name="l00101"></a><span class="lineno"><a class="line" href="namespaceviennacl_1_1linalg_1_1detail.html#a38fd7b41df5895671a4beb943cc35bc3"> 101</a></span>  <span class="keywordtype">void</span> <a class="code" href="namespaceviennacl_1_1linalg_1_1detail.html#a38fd7b41df5895671a4beb943cc35bc3">svd_qr_shift</a>(MatrixType & vcl_u,</div>
<div class="line"><a name="l00102"></a><span class="lineno"> 102</span>  MatrixType & vcl_v,</div>
<div class="line"><a name="l00103"></a><span class="lineno"> 103</span>  CPU_VectorType & q,</div>
<div class="line"><a name="l00104"></a><span class="lineno"> 104</span>  CPU_VectorType & e)</div>
<div class="line"><a name="l00105"></a><span class="lineno"> 105</span>  {</div>
<div class="line"><a name="l00106"></a><span class="lineno"> 106</span>  <span class="keyword">typedef</span> <span class="keyword">typename</span> MatrixType::value_type <a class="code" href="fft__1d_8cpp.html#ad5c19ca4f47d3f8ec21232a5af2624e5">ScalarType</a>;</div>
<div class="line"><a name="l00107"></a><span class="lineno"> 107</span>  <span class="keyword">typedef</span> <span class="keyword">typename</span> <a class="code" href="structviennacl_1_1result__of_1_1cpu__value__type.html#aa015d93f419985879a7c13b09633c5c6">viennacl::result_of::cpu_value_type<ScalarType>::type</a> CPU_ScalarType;</div>
<div class="line"><a name="l00108"></a><span class="lineno"> 108</span> </div>
<div class="line"><a name="l00109"></a><span class="lineno"> 109</span>  <a class="code" href="namespaceviennacl.html#a98a0afcc513111ffa0bd138f891930df">vcl_size_t</a> n = q.size();</div>
<div class="line"><a name="l00110"></a><span class="lineno"> 110</span>  <span class="keywordtype">int</span> m = <span class="keyword">static_cast<</span><span class="keywordtype">int</span><span class="keyword">></span>(vcl_u.size1());</div>
<div class="line"><a name="l00111"></a><span class="lineno"> 111</span> </div>
<div class="line"><a name="l00112"></a><span class="lineno"> 112</span>  <a class="code" href="namespaceviennacl_1_1linalg_1_1detail.html#aad4cd2951549618c93f74ff26444675f">detail::transpose</a>(vcl_u);</div>
<div class="line"><a name="l00113"></a><span class="lineno"> 113</span>  <a class="code" href="namespaceviennacl_1_1linalg_1_1detail.html#aad4cd2951549618c93f74ff26444675f">detail::transpose</a>(vcl_v);</div>
<div class="line"><a name="l00114"></a><span class="lineno"> 114</span> </div>
<div class="line"><a name="l00115"></a><span class="lineno"> 115</span>  std::vector<CPU_ScalarType> signs_v(n, 1);</div>
<div class="line"><a name="l00116"></a><span class="lineno"> 116</span>  std::vector<CPU_ScalarType> cs1(n), ss1(n), cs2(n), ss2(n);</div>
<div class="line"><a name="l00117"></a><span class="lineno"> 117</span> </div>
<div class="line"><a name="l00118"></a><span class="lineno"> 118</span>  <a class="code" href="classviennacl_1_1vector.html">viennacl::vector<CPU_ScalarType></a> tmp1(n, <a class="code" href="namespaceviennacl_1_1traits.html#a6707f5dab8f482170d2046a605f46ef8">viennacl::traits::context</a>(vcl_u)), tmp2(n, <a class="code" href="namespaceviennacl_1_1traits.html#a6707f5dab8f482170d2046a605f46ef8">viennacl::traits::context</a>(vcl_u));</div>
<div class="line"><a name="l00119"></a><span class="lineno"> 119</span> </div>
<div class="line"><a name="l00120"></a><span class="lineno"> 120</span>  <span class="keywordtype">bool</span> goto_test_conv = <span class="keyword">false</span>;</div>
<div class="line"><a name="l00121"></a><span class="lineno"> 121</span> </div>
<div class="line"><a name="l00122"></a><span class="lineno"> 122</span>  <span class="keywordflow">for</span> (<span class="keywordtype">int</span> k = static_cast<int>(n) - 1; k >= 0; k--)</div>
<div class="line"><a name="l00123"></a><span class="lineno"> 123</span>  {</div>
<div class="line"><a name="l00124"></a><span class="lineno"> 124</span>  <span class="comment">// std::cout << "K = " << k << std::endl;</span></div>
<div class="line"><a name="l00125"></a><span class="lineno"> 125</span> </div>
<div class="line"><a name="l00126"></a><span class="lineno"> 126</span>  <a class="code" href="namespaceviennacl.html#a98a0afcc513111ffa0bd138f891930df">vcl_size_t</a> iter = 0;</div>
<div class="line"><a name="l00127"></a><span class="lineno"> 127</span>  <span class="keywordflow">for</span> (iter = 0; iter < detail::ITER_MAX; iter++)</div>
<div class="line"><a name="l00128"></a><span class="lineno"> 128</span>  {</div>
<div class="line"><a name="l00129"></a><span class="lineno"> 129</span>  <span class="comment">// test for split</span></div>
<div class="line"><a name="l00130"></a><span class="lineno"> 130</span>  <span class="keywordtype">int</span> l;</div>
<div class="line"><a name="l00131"></a><span class="lineno"> 131</span>  <span class="keywordflow">for</span> (l = k; l >= 0; l--)</div>
<div class="line"><a name="l00132"></a><span class="lineno"> 132</span>  {</div>
<div class="line"><a name="l00133"></a><span class="lineno"> 133</span>  goto_test_conv = <span class="keyword">false</span>;</div>
<div class="line"><a name="l00134"></a><span class="lineno"> 134</span>  <span class="keywordflow">if</span> (std::fabs(e[<a class="code" href="namespaceviennacl.html#a98a0afcc513111ffa0bd138f891930df">vcl_size_t</a>(l)]) <= detail::EPS)</div>
<div class="line"><a name="l00135"></a><span class="lineno"> 135</span>  {</div>
<div class="line"><a name="l00136"></a><span class="lineno"> 136</span>  <span class="comment">// set it</span></div>
<div class="line"><a name="l00137"></a><span class="lineno"> 137</span>  goto_test_conv = <span class="keyword">true</span>;</div>
<div class="line"><a name="l00138"></a><span class="lineno"> 138</span>  <span class="keywordflow">break</span>;</div>
<div class="line"><a name="l00139"></a><span class="lineno"> 139</span>  }</div>
<div class="line"><a name="l00140"></a><span class="lineno"> 140</span> </div>
<div class="line"><a name="l00141"></a><span class="lineno"> 141</span>  <span class="keywordflow">if</span> (std::fabs(q[<a class="code" href="namespaceviennacl.html#a98a0afcc513111ffa0bd138f891930df">vcl_size_t</a>(l) - 1]) <= detail::EPS)</div>
<div class="line"><a name="l00142"></a><span class="lineno"> 142</span>  {</div>
<div class="line"><a name="l00143"></a><span class="lineno"> 143</span>  <span class="comment">// goto</span></div>
<div class="line"><a name="l00144"></a><span class="lineno"> 144</span>  <span class="keywordflow">break</span>;</div>
<div class="line"><a name="l00145"></a><span class="lineno"> 145</span>  }</div>
<div class="line"><a name="l00146"></a><span class="lineno"> 146</span>  }</div>
<div class="line"><a name="l00147"></a><span class="lineno"> 147</span> </div>
<div class="line"><a name="l00148"></a><span class="lineno"> 148</span>  <span class="keywordflow">if</span> (!goto_test_conv)</div>
<div class="line"><a name="l00149"></a><span class="lineno"> 149</span>  {</div>
<div class="line"><a name="l00150"></a><span class="lineno"> 150</span>  CPU_ScalarType c = 0.0;</div>
<div class="line"><a name="l00151"></a><span class="lineno"> 151</span>  CPU_ScalarType s = 1.0;</div>
<div class="line"><a name="l00152"></a><span class="lineno"> 152</span> </div>
<div class="line"><a name="l00153"></a><span class="lineno"> 153</span>  <span class="comment">//int l1 = l - 1;</span></div>
<div class="line"><a name="l00154"></a><span class="lineno"> 154</span>  <span class="comment">//int l2 = k;</span></div>
<div class="line"><a name="l00155"></a><span class="lineno"> 155</span> </div>
<div class="line"><a name="l00156"></a><span class="lineno"> 156</span>  <span class="keywordflow">for</span> (<span class="keywordtype">int</span> i = l; i <= k; i++)</div>
<div class="line"><a name="l00157"></a><span class="lineno"> 157</span>  {</div>
<div class="line"><a name="l00158"></a><span class="lineno"> 158</span>  CPU_ScalarType f = s * e[<a class="code" href="namespaceviennacl.html#a98a0afcc513111ffa0bd138f891930df">vcl_size_t</a>(i)];</div>
<div class="line"><a name="l00159"></a><span class="lineno"> 159</span>  e[<a class="code" href="namespaceviennacl.html#a98a0afcc513111ffa0bd138f891930df">vcl_size_t</a>(i)] = c * e[<a class="code" href="namespaceviennacl.html#a98a0afcc513111ffa0bd138f891930df">vcl_size_t</a>(i)];</div>
<div class="line"><a name="l00160"></a><span class="lineno"> 160</span> </div>
<div class="line"><a name="l00161"></a><span class="lineno"> 161</span>  <span class="keywordflow">if</span> (std::fabs(f) <= detail::EPS)</div>
<div class="line"><a name="l00162"></a><span class="lineno"> 162</span>  {</div>
<div class="line"><a name="l00163"></a><span class="lineno"> 163</span>  <span class="comment">//l2 = i - 1;</span></div>
<div class="line"><a name="l00164"></a><span class="lineno"> 164</span>  <span class="keywordflow">break</span>;</div>
<div class="line"><a name="l00165"></a><span class="lineno"> 165</span>  }</div>
<div class="line"><a name="l00166"></a><span class="lineno"> 166</span> </div>
<div class="line"><a name="l00167"></a><span class="lineno"> 167</span>  CPU_ScalarType g = q[<a class="code" href="namespaceviennacl.html#a98a0afcc513111ffa0bd138f891930df">vcl_size_t</a>(i)];</div>
<div class="line"><a name="l00168"></a><span class="lineno"> 168</span>  CPU_ScalarType h = <a class="code" href="namespaceviennacl_1_1linalg_1_1detail.html#a0737c94fac817b0d0c8444463be7ceb7">detail::pythag</a>(f, g);</div>
<div class="line"><a name="l00169"></a><span class="lineno"> 169</span>  q[<a class="code" href="namespaceviennacl.html#a98a0afcc513111ffa0bd138f891930df">vcl_size_t</a>(i)] = h;</div>
<div class="line"><a name="l00170"></a><span class="lineno"> 170</span>  c = g / h;</div>
<div class="line"><a name="l00171"></a><span class="lineno"> 171</span>  s = -f / h;</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>  cs1[<a class="code" href="namespaceviennacl.html#a98a0afcc513111ffa0bd138f891930df">vcl_size_t</a>(i)] = c;</div>
<div class="line"><a name="l00174"></a><span class="lineno"> 174</span>  ss1[<a class="code" href="namespaceviennacl.html#a98a0afcc513111ffa0bd138f891930df">vcl_size_t</a>(i)] = s;</div>
<div class="line"><a name="l00175"></a><span class="lineno"> 175</span>  }</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>  <span class="comment">// std::cout << "Hitted!" << l1 << " " << l2 << "\n";</span></div>
<div class="line"><a name="l00178"></a><span class="lineno"> 178</span> </div>
<div class="line"><a name="l00179"></a><span class="lineno"> 179</span>  <span class="comment">// for (int i = l; i <= l2; i++)</span></div>
<div class="line"><a name="l00180"></a><span class="lineno"> 180</span>  <span class="comment">// {</span></div>
<div class="line"><a name="l00181"></a><span class="lineno"> 181</span>  <span class="comment">// for (int j = 0; j < m; j++)</span></div>
<div class="line"><a name="l00182"></a><span class="lineno"> 182</span>  <span class="comment">// {</span></div>
<div class="line"><a name="l00183"></a><span class="lineno"> 183</span>  <span class="comment">// CPU_ScalarType y = u(j, l1);</span></div>
<div class="line"><a name="l00184"></a><span class="lineno"> 184</span>  <span class="comment">// CPU_ScalarType z = u(j, i);</span></div>
<div class="line"><a name="l00185"></a><span class="lineno"> 185</span>  <span class="comment">// u(j, l1) = y * cs1[i] + z * ss1[i];</span></div>
<div class="line"><a name="l00186"></a><span class="lineno"> 186</span>  <span class="comment">// u(j, i) = -y * ss1[i] + z * cs1[i];</span></div>
<div class="line"><a name="l00187"></a><span class="lineno"> 187</span>  <span class="comment">// }</span></div>
<div class="line"><a name="l00188"></a><span class="lineno"> 188</span>  <span class="comment">// }</span></div>
<div class="line"><a name="l00189"></a><span class="lineno"> 189</span>  }</div>
<div class="line"><a name="l00190"></a><span class="lineno"> 190</span> </div>
<div class="line"><a name="l00191"></a><span class="lineno"> 191</span>  CPU_ScalarType z = q[<a class="code" href="namespaceviennacl.html#a98a0afcc513111ffa0bd138f891930df">vcl_size_t</a>(k)];</div>
<div class="line"><a name="l00192"></a><span class="lineno"> 192</span> </div>
<div class="line"><a name="l00193"></a><span class="lineno"> 193</span>  <span class="keywordflow">if</span> (l == k)</div>
<div class="line"><a name="l00194"></a><span class="lineno"> 194</span>  {</div>
<div class="line"><a name="l00195"></a><span class="lineno"> 195</span>  <span class="keywordflow">if</span> (z < 0)</div>
<div class="line"><a name="l00196"></a><span class="lineno"> 196</span>  {</div>
<div class="line"><a name="l00197"></a><span class="lineno"> 197</span>  q[<a class="code" href="namespaceviennacl.html#a98a0afcc513111ffa0bd138f891930df">vcl_size_t</a>(k)] = -z;</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>  signs_v[<a class="code" href="namespaceviennacl.html#a98a0afcc513111ffa0bd138f891930df">vcl_size_t</a>(k)] *= -1;</div>
<div class="line"><a name="l00200"></a><span class="lineno"> 200</span>  }</div>
<div class="line"><a name="l00201"></a><span class="lineno"> 201</span> </div>
<div class="line"><a name="l00202"></a><span class="lineno"> 202</span>  <span class="keywordflow">break</span>;</div>
<div class="line"><a name="l00203"></a><span class="lineno"> 203</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>  <span class="keywordflow">if</span> (iter >= detail::ITER_MAX - 1)</div>
<div class="line"><a name="l00206"></a><span class="lineno"> 206</span>  <span class="keywordflow">break</span>;</div>
<div class="line"><a name="l00207"></a><span class="lineno"> 207</span> </div>
<div class="line"><a name="l00208"></a><span class="lineno"> 208</span>  CPU_ScalarType x = q[<a class="code" href="namespaceviennacl.html#a98a0afcc513111ffa0bd138f891930df">vcl_size_t</a>(l)];</div>
<div class="line"><a name="l00209"></a><span class="lineno"> 209</span>  CPU_ScalarType y = q[<a class="code" href="namespaceviennacl.html#a98a0afcc513111ffa0bd138f891930df">vcl_size_t</a>(k) - 1];</div>
<div class="line"><a name="l00210"></a><span class="lineno"> 210</span>  CPU_ScalarType g = e[<a class="code" href="namespaceviennacl.html#a98a0afcc513111ffa0bd138f891930df">vcl_size_t</a>(k) - 1];</div>
<div class="line"><a name="l00211"></a><span class="lineno"> 211</span>  CPU_ScalarType h = e[<a class="code" href="namespaceviennacl.html#a98a0afcc513111ffa0bd138f891930df">vcl_size_t</a>(k)];</div>
<div class="line"><a name="l00212"></a><span class="lineno"> 212</span>  CPU_ScalarType f = ((y - z) * (y + z) + (g - h) * (g + h)) / (2 * h * y);</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>  g = detail::pythag<CPU_ScalarType>(f, 1);</div>
<div class="line"><a name="l00215"></a><span class="lineno"> 215</span> </div>
<div class="line"><a name="l00216"></a><span class="lineno"> 216</span>  <span class="keywordflow">if</span> (f < 0) {</div>
<div class="line"><a name="l00217"></a><span class="lineno"> 217</span>  f = ((x - z) * (x + z) + h * (y / (f - g) - h)) / x;</div>
<div class="line"><a name="l00218"></a><span class="lineno"> 218</span>  } <span class="keywordflow">else</span> {</div>
<div class="line"><a name="l00219"></a><span class="lineno"> 219</span>  f = ((x - z) * (x + z) + h * (y / (f + g) - h)) / x;</div>
<div class="line"><a name="l00220"></a><span class="lineno"> 220</span>  }</div>
<div class="line"><a name="l00221"></a><span class="lineno"> 221</span> </div>
<div class="line"><a name="l00222"></a><span class="lineno"> 222</span>  CPU_ScalarType c = 1;</div>
<div class="line"><a name="l00223"></a><span class="lineno"> 223</span>  CPU_ScalarType s = 1;</div>
<div class="line"><a name="l00224"></a><span class="lineno"> 224</span> </div>
<div class="line"><a name="l00225"></a><span class="lineno"> 225</span>  <span class="keywordflow">for</span> (<a class="code" href="namespaceviennacl.html#a98a0afcc513111ffa0bd138f891930df">vcl_size_t</a> i = static_cast<vcl_size_t>(l) + 1; i <= static_cast<vcl_size_t>(k); i++)</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>  g = e[i];</div>
<div class="line"><a name="l00228"></a><span class="lineno"> 228</span>  y = q[i];</div>
<div class="line"><a name="l00229"></a><span class="lineno"> 229</span>  h = s * g;</div>
<div class="line"><a name="l00230"></a><span class="lineno"> 230</span>  g = c * g;</div>
<div class="line"><a name="l00231"></a><span class="lineno"> 231</span>  CPU_ScalarType z2 = <a class="code" href="namespaceviennacl_1_1linalg_1_1detail.html#a0737c94fac817b0d0c8444463be7ceb7">detail::pythag</a>(f, h);</div>
<div class="line"><a name="l00232"></a><span class="lineno"> 232</span>  e[i - 1] = z2;</div>
<div class="line"><a name="l00233"></a><span class="lineno"> 233</span>  c = f / z2;</div>
<div class="line"><a name="l00234"></a><span class="lineno"> 234</span>  s = h / z2;</div>
<div class="line"><a name="l00235"></a><span class="lineno"> 235</span>  f = x * c + g * s;</div>
<div class="line"><a name="l00236"></a><span class="lineno"> 236</span>  g = -x * s + g * c;</div>
<div class="line"><a name="l00237"></a><span class="lineno"> 237</span>  h = y * s;</div>
<div class="line"><a name="l00238"></a><span class="lineno"> 238</span>  y = y * c;</div>
<div class="line"><a name="l00239"></a><span class="lineno"> 239</span> </div>
<div class="line"><a name="l00240"></a><span class="lineno"> 240</span>  cs1[i] = c;</div>
<div class="line"><a name="l00241"></a><span class="lineno"> 241</span>  ss1[i] = s;</div>
<div class="line"><a name="l00242"></a><span class="lineno"> 242</span> </div>
<div class="line"><a name="l00243"></a><span class="lineno"> 243</span>  z2 = <a class="code" href="namespaceviennacl_1_1linalg_1_1detail.html#a0737c94fac817b0d0c8444463be7ceb7">detail::pythag</a>(f, h);</div>
<div class="line"><a name="l00244"></a><span class="lineno"> 244</span>  q[i - 1] = z2;</div>
<div class="line"><a name="l00245"></a><span class="lineno"> 245</span>  c = f / z2;</div>
<div class="line"><a name="l00246"></a><span class="lineno"> 246</span>  s = h / z2;</div>
<div class="line"><a name="l00247"></a><span class="lineno"> 247</span>  f = c * g + s * y;</div>
<div class="line"><a name="l00248"></a><span class="lineno"> 248</span>  x = -s * g + c * y;</div>
<div class="line"><a name="l00249"></a><span class="lineno"> 249</span> </div>
<div class="line"><a name="l00250"></a><span class="lineno"> 250</span>  cs2[i] = c;</div>
<div class="line"><a name="l00251"></a><span class="lineno"> 251</span>  ss2[i] = s;</div>
<div class="line"><a name="l00252"></a><span class="lineno"> 252</span>  }</div>
<div class="line"><a name="l00253"></a><span class="lineno"> 253</span> </div>
<div class="line"><a name="l00254"></a><span class="lineno"> 254</span>  {</div>
<div class="line"><a name="l00255"></a><span class="lineno"> 255</span>  <a class="code" href="namespaceviennacl.html#a10b7f8cf6b8864a7aa196d670481a453">viennacl::copy</a>(cs1, tmp1);</div>
<div class="line"><a name="l00256"></a><span class="lineno"> 256</span>  <a class="code" href="namespaceviennacl.html#a10b7f8cf6b8864a7aa196d670481a453">viennacl::copy</a>(ss1, tmp2);</div>
<div class="line"><a name="l00257"></a><span class="lineno"> 257</span> </div>
<div class="line"><a name="l00258"></a><span class="lineno"> 258</span>  <a class="code" href="namespaceviennacl_1_1linalg_1_1detail.html#a76be0f2fd292f0e457e364e20d512e17">givens_prev</a>(vcl_v, tmp1, tmp2, static_cast<int>(n), l, k);</div>
<div class="line"><a name="l00259"></a><span class="lineno"> 259</span>  }</div>
<div class="line"><a name="l00260"></a><span class="lineno"> 260</span> </div>
<div class="line"><a name="l00261"></a><span class="lineno"> 261</span>  {</div>
<div class="line"><a name="l00262"></a><span class="lineno"> 262</span>  <a class="code" href="namespaceviennacl.html#a10b7f8cf6b8864a7aa196d670481a453">viennacl::copy</a>(cs2, tmp1);</div>
<div class="line"><a name="l00263"></a><span class="lineno"> 263</span>  <a class="code" href="namespaceviennacl.html#a10b7f8cf6b8864a7aa196d670481a453">viennacl::copy</a>(ss2, tmp2);</div>
<div class="line"><a name="l00264"></a><span class="lineno"> 264</span> </div>
<div class="line"><a name="l00265"></a><span class="lineno"> 265</span>  <a class="code" href="namespaceviennacl_1_1linalg_1_1detail.html#a76be0f2fd292f0e457e364e20d512e17">givens_prev</a>(vcl_u, tmp1, tmp2, m, l, k);</div>
<div class="line"><a name="l00266"></a><span class="lineno"> 266</span>  }</div>
<div class="line"><a name="l00267"></a><span class="lineno"> 267</span> </div>
<div class="line"><a name="l00268"></a><span class="lineno"> 268</span>  e[<a class="code" href="namespaceviennacl.html#a98a0afcc513111ffa0bd138f891930df">vcl_size_t</a>(l)] = 0.0;</div>
<div class="line"><a name="l00269"></a><span class="lineno"> 269</span>  e[<a class="code" href="namespaceviennacl.html#a98a0afcc513111ffa0bd138f891930df">vcl_size_t</a>(k)] = f;</div>
<div class="line"><a name="l00270"></a><span class="lineno"> 270</span>  q[<a class="code" href="namespaceviennacl.html#a98a0afcc513111ffa0bd138f891930df">vcl_size_t</a>(k)] = x;</div>
<div class="line"><a name="l00271"></a><span class="lineno"> 271</span>  }</div>
<div class="line"><a name="l00272"></a><span class="lineno"> 272</span> </div>
<div class="line"><a name="l00273"></a><span class="lineno"> 273</span>  }</div>
<div class="line"><a name="l00274"></a><span class="lineno"> 274</span> </div>
<div class="line"><a name="l00275"></a><span class="lineno"> 275</span> </div>
<div class="line"><a name="l00276"></a><span class="lineno"> 276</span>  <a class="code" href="namespaceviennacl.html#a10b7f8cf6b8864a7aa196d670481a453">viennacl::copy</a>(signs_v, tmp1);</div>
<div class="line"><a name="l00277"></a><span class="lineno"> 277</span>  <a class="code" href="namespaceviennacl_1_1linalg_1_1detail.html#a1f9130eb00ff2625dff55b18e0ac1553">change_signs</a>(vcl_v, tmp1, static_cast<int>(n));</div>
<div class="line"><a name="l00278"></a><span class="lineno"> 278</span> </div>
<div class="line"><a name="l00279"></a><span class="lineno"> 279</span>  <span class="comment">// transpose singular matrices again</span></div>
<div class="line"><a name="l00280"></a><span class="lineno"> 280</span>  <a class="code" href="namespaceviennacl_1_1linalg_1_1detail.html#aad4cd2951549618c93f74ff26444675f">detail::transpose</a>(vcl_u);</div>
<div class="line"><a name="l00281"></a><span class="lineno"> 281</span>  <a class="code" href="namespaceviennacl_1_1linalg_1_1detail.html#aad4cd2951549618c93f74ff26444675f">detail::transpose</a>(vcl_v);</div>
<div class="line"><a name="l00282"></a><span class="lineno"> 282</span>  }</div>
<div class="line"><a name="l00283"></a><span class="lineno"> 283</span> </div>
<div class="line"><a name="l00284"></a><span class="lineno"> 284</span> </div>
<div class="line"><a name="l00285"></a><span class="lineno"> 285</span>  <span class="comment">/*template<typename SCALARTYPE, unsigned int ALIGNMENT></span></div>
<div class="line"><a name="l00286"></a><span class="lineno"> 286</span> <span class="comment"> bool householder_c(viennacl::matrix<SCALARTYPE, row_major, ALIGNMENT> & A,</span></div>
<div class="line"><a name="l00287"></a><span class="lineno"> 287</span> <span class="comment"> viennacl::matrix<SCALARTYPE, row_major, ALIGNMENT> & Q,</span></div>
<div class="line"><a name="l00288"></a><span class="lineno"> 288</span> <span class="comment"> viennacl::vector<SCALARTYPE, ALIGNMENT> & D,</span></div>
<div class="line"><a name="l00289"></a><span class="lineno"> 289</span> <span class="comment"> vcl_size_t start)</span></div>
<div class="line"><a name="l00290"></a><span class="lineno"> 290</span> <span class="comment"> {</span></div>
<div class="line"><a name="l00291"></a><span class="lineno"> 291</span> <span class="comment"></span></div>
<div class="line"><a name="l00292"></a><span class="lineno"> 292</span> <span class="comment"> vcl_size_t row_start = start;</span></div>
<div class="line"><a name="l00293"></a><span class="lineno"> 293</span> <span class="comment"> vcl_size_t col_start = start;</span></div>
<div class="line"><a name="l00294"></a><span class="lineno"> 294</span> <span class="comment"></span></div>
<div class="line"><a name="l00295"></a><span class="lineno"> 295</span> <span class="comment"> if (row_start + 1 >= A.size1())</span></div>
<div class="line"><a name="l00296"></a><span class="lineno"> 296</span> <span class="comment"> return false;</span></div>
<div class="line"><a name="l00297"></a><span class="lineno"> 297</span> <span class="comment"></span></div>
<div class="line"><a name="l00298"></a><span class="lineno"> 298</span> <span class="comment"> std::vector<SCALARTYPE> tmp(A.size1(), 0);</span></div>
<div class="line"><a name="l00299"></a><span class="lineno"> 299</span> <span class="comment"></span></div>
<div class="line"><a name="l00300"></a><span class="lineno"> 300</span> <span class="comment"> copy_vec(A, D, row_start, col_start, true);</span></div>
<div class="line"><a name="l00301"></a><span class="lineno"> 301</span> <span class="comment"> fast_copy(D.begin(), D.begin() + (A.size1() - row_start), tmp.begin() + row_start);</span></div>
<div class="line"><a name="l00302"></a><span class="lineno"> 302</span> <span class="comment"></span></div>
<div class="line"><a name="l00303"></a><span class="lineno"> 303</span> <span class="comment"> detail::householder_vector(tmp, row_start);</span></div>
<div class="line"><a name="l00304"></a><span class="lineno"> 304</span> <span class="comment"></span></div>
<div class="line"><a name="l00305"></a><span class="lineno"> 305</span> <span class="comment"> fast_copy(tmp, D);</span></div>
<div class="line"><a name="l00306"></a><span class="lineno"> 306</span> <span class="comment"></span></div>
<div class="line"><a name="l00307"></a><span class="lineno"> 307</span> <span class="comment"> viennacl::ocl::kernel & kernel = viennacl::ocl::get_kernel(viennacl::linalg::opencl::kernels::svd<SCALARTYPE>::program_name(), SVD_HOUSEHOLDER_COL_KERNEL);</span></div>
<div class="line"><a name="l00308"></a><span class="lineno"> 308</span> <span class="comment"></span></div>
<div class="line"><a name="l00309"></a><span class="lineno"> 309</span> <span class="comment"> //kernel.global_work_size(0, A.size1() << 1);</span></div>
<div class="line"><a name="l00310"></a><span class="lineno"> 310</span> <span class="comment"></span></div>
<div class="line"><a name="l00311"></a><span class="lineno"> 311</span> <span class="comment"> viennacl::ocl::enqueue(kernel(</span></div>
<div class="line"><a name="l00312"></a><span class="lineno"> 312</span> <span class="comment"> A,</span></div>
<div class="line"><a name="l00313"></a><span class="lineno"> 313</span> <span class="comment"> Q,</span></div>
<div class="line"><a name="l00314"></a><span class="lineno"> 314</span> <span class="comment"> D,</span></div>
<div class="line"><a name="l00315"></a><span class="lineno"> 315</span> <span class="comment"> static_cast<cl_uint>(row_start),</span></div>
<div class="line"><a name="l00316"></a><span class="lineno"> 316</span> <span class="comment"> static_cast<cl_uint>(col_start),</span></div>
<div class="line"><a name="l00317"></a><span class="lineno"> 317</span> <span class="comment"> static_cast<cl_uint>(A.size1()),</span></div>
<div class="line"><a name="l00318"></a><span class="lineno"> 318</span> <span class="comment"> static_cast<cl_uint>(A.size2()),</span></div>
<div class="line"><a name="l00319"></a><span class="lineno"> 319</span> <span class="comment"> static_cast<cl_uint>(A.internal_size2()),</span></div>
<div class="line"><a name="l00320"></a><span class="lineno"> 320</span> <span class="comment"> static_cast<cl_uint>(Q.internal_size2()),</span></div>
<div class="line"><a name="l00321"></a><span class="lineno"> 321</span> <span class="comment"> viennacl::ocl::local_mem(static_cast<cl_uint>(128 * sizeof(SCALARTYPE)))</span></div>
<div class="line"><a name="l00322"></a><span class="lineno"> 322</span> <span class="comment"> ));</span></div>
<div class="line"><a name="l00323"></a><span class="lineno"> 323</span> <span class="comment"></span></div>
<div class="line"><a name="l00324"></a><span class="lineno"> 324</span> <span class="comment"> return true;</span></div>
<div class="line"><a name="l00325"></a><span class="lineno"> 325</span> <span class="comment"> }*/</span></div>
<div class="line"><a name="l00326"></a><span class="lineno"> 326</span> </div>
<div class="line"><a name="l00327"></a><span class="lineno"> 327</span>  <span class="keyword">template</span><<span class="keyword">typename</span> SCALARTYPE, <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> ALIGNMENT></div>
<div class="line"><a name="l00328"></a><span class="lineno"><a class="line" href="namespaceviennacl_1_1linalg_1_1detail.html#aabaaa377c989dddc5ab35faf8541b8f8"> 328</a></span>  <span class="keywordtype">bool</span> <a class="code" href="namespaceviennacl_1_1linalg_1_1detail.html#aabaaa377c989dddc5ab35faf8541b8f8">householder_c</a>(<a class="code" href="classviennacl_1_1matrix.html">viennacl::matrix<SCALARTYPE, row_major, ALIGNMENT></a>& A,</div>
<div class="line"><a name="l00329"></a><span class="lineno"> 329</span>  <a class="code" href="classviennacl_1_1matrix.html">viennacl::matrix<SCALARTYPE, row_major, ALIGNMENT></a>& Q,</div>
<div class="line"><a name="l00330"></a><span class="lineno"> 330</span>  <a class="code" href="classviennacl_1_1vector.html">viennacl::vector<SCALARTYPE, ALIGNMENT></a>& D,</div>
<div class="line"><a name="l00331"></a><span class="lineno"> 331</span>  <a class="code" href="namespaceviennacl.html#a98a0afcc513111ffa0bd138f891930df">vcl_size_t</a> row_start, <a class="code" href="namespaceviennacl.html#a98a0afcc513111ffa0bd138f891930df">vcl_size_t</a> col_start)</div>
<div class="line"><a name="l00332"></a><span class="lineno"> 332</span>  {</div>
<div class="line"><a name="l00333"></a><span class="lineno"> 333</span>  <a class="code" href="classviennacl_1_1ocl_1_1context.html">viennacl::ocl::context</a> & ctx = <span class="keyword">const_cast<</span><a class="code" href="classviennacl_1_1ocl_1_1context.html">viennacl::ocl::context</a> &<span class="keyword">></span>(viennacl::traits::opencl_handle(A).context());</div>
<div class="line"><a name="l00334"></a><span class="lineno"> 334</span> </div>
<div class="line"><a name="l00335"></a><span class="lineno"> 335</span>  <span class="keywordflow">if</span> (row_start + 1 >= A.<a class="code" href="classviennacl_1_1matrix__base.html#a24e4f5fa27a1af5ad47e52a97c065d68">size1</a>())</div>
<div class="line"><a name="l00336"></a><span class="lineno"> 336</span>  <span class="keywordflow">return</span> <span class="keyword">false</span>;</div>
<div class="line"><a name="l00337"></a><span class="lineno"> 337</span> </div>
<div class="line"><a name="l00338"></a><span class="lineno"> 338</span>  <a class="code" href="namespaceviennacl_1_1linalg_1_1detail.html#a5852aa7527c0599681f1b0fbc753d357">prepare_householder_vector</a>(A, D, A.<a class="code" href="classviennacl_1_1matrix__base.html#a24e4f5fa27a1af5ad47e52a97c065d68">size1</a>(), row_start, col_start, row_start, <span class="keyword">true</span>);</div>
<div class="line"><a name="l00339"></a><span class="lineno"> 339</span> </div>
<div class="line"><a name="l00340"></a><span class="lineno"> 340</span>  {</div>
<div class="line"><a name="l00341"></a><span class="lineno"> 341</span>  <a class="code" href="classviennacl_1_1ocl_1_1kernel.html">viennacl::ocl::kernel</a>& kernel = ctx.<a class="code" href="classviennacl_1_1ocl_1_1context.html#afe68ad8c2df449f40f45db6605038946">get_kernel</a>(<a class="code" href="structviennacl_1_1linalg_1_1opencl_1_1kernels_1_1svd.html">viennacl::linalg::opencl::kernels::svd<SCALARTYPE>::program_name</a>(), <a class="code" href="namespaceviennacl_1_1linalg.html#a8e62fa452895c889f7bad9700300994d">SVD_HOUSEHOLDER_UPDATE_A_LEFT_KERNEL</a>);</div>
<div class="line"><a name="l00342"></a><span class="lineno"> 342</span> </div>
<div class="line"><a name="l00343"></a><span class="lineno"> 343</span>  <a class="code" href="namespaceviennacl_1_1ocl.html#a5f2022f653ea1cf364d20e3ff84dcada">viennacl::ocl::enqueue</a>(kernel(</div>
<div class="line"><a name="l00344"></a><span class="lineno"> 344</span>  A,</div>
<div class="line"><a name="l00345"></a><span class="lineno"> 345</span>  D,</div>
<div class="line"><a name="l00346"></a><span class="lineno"> 346</span>  static_cast<cl_uint>(row_start),</div>
<div class="line"><a name="l00347"></a><span class="lineno"> 347</span>  static_cast<cl_uint>(col_start),</div>
<div class="line"><a name="l00348"></a><span class="lineno"> 348</span>  static_cast<cl_uint>(A.<a class="code" href="classviennacl_1_1matrix__base.html#a24e4f5fa27a1af5ad47e52a97c065d68">size1</a>()),</div>
<div class="line"><a name="l00349"></a><span class="lineno"> 349</span>  static_cast<cl_uint>(A.<a class="code" href="classviennacl_1_1matrix__base.html#a4348766b3b9cb049f7acd6a795272dbe">size2</a>()),</div>
<div class="line"><a name="l00350"></a><span class="lineno"> 350</span>  static_cast<cl_uint>(A.<a class="code" href="classviennacl_1_1matrix__base.html#a00e30fdc61081a73995b54175a91d220">internal_size2</a>()),</div>
<div class="line"><a name="l00351"></a><span class="lineno"> 351</span>  <a class="code" href="classviennacl_1_1ocl_1_1local__mem.html">viennacl::ocl::local_mem</a>(static_cast<cl_uint>(128 * <span class="keyword">sizeof</span>(SCALARTYPE)))</div>
<div class="line"><a name="l00352"></a><span class="lineno"> 352</span>  ));</div>
<div class="line"><a name="l00353"></a><span class="lineno"> 353</span> </div>
<div class="line"><a name="l00354"></a><span class="lineno"> 354</span>  }</div>
<div class="line"><a name="l00355"></a><span class="lineno"> 355</span> </div>
<div class="line"><a name="l00356"></a><span class="lineno"> 356</span>  {</div>
<div class="line"><a name="l00357"></a><span class="lineno"> 357</span>  <a class="code" href="classviennacl_1_1ocl_1_1kernel.html">viennacl::ocl::kernel</a>& kernel = ctx.<a class="code" href="classviennacl_1_1ocl_1_1context.html#afe68ad8c2df449f40f45db6605038946">get_kernel</a>(<a class="code" href="structviennacl_1_1linalg_1_1opencl_1_1kernels_1_1svd.html">viennacl::linalg::opencl::kernels::svd<SCALARTYPE>::program_name</a>(), <a class="code" href="namespaceviennacl_1_1linalg.html#a04a5ce1f7230502c9d1ee87dcc24c8b4">SVD_HOUSEHOLDER_UPDATE_QL_KERNEL</a>);</div>
<div class="line"><a name="l00358"></a><span class="lineno"> 358</span> </div>
<div class="line"><a name="l00359"></a><span class="lineno"> 359</span>  <a class="code" href="namespaceviennacl_1_1ocl.html#a5f2022f653ea1cf364d20e3ff84dcada">viennacl::ocl::enqueue</a>(kernel(</div>
<div class="line"><a name="l00360"></a><span class="lineno"> 360</span>  Q,</div>
<div class="line"><a name="l00361"></a><span class="lineno"> 361</span>  D,</div>
<div class="line"><a name="l00362"></a><span class="lineno"> 362</span>  static_cast<cl_uint>(A.<a class="code" href="classviennacl_1_1matrix__base.html#a24e4f5fa27a1af5ad47e52a97c065d68">size1</a>()),</div>
<div class="line"><a name="l00363"></a><span class="lineno"> 363</span>  <span class="comment">// static_cast<cl_uint>(A.size2()),</span></div>
<div class="line"><a name="l00364"></a><span class="lineno"> 364</span>  static_cast<cl_uint>(Q.<a class="code" href="classviennacl_1_1matrix__base.html#a00e30fdc61081a73995b54175a91d220">internal_size2</a>()),</div>
<div class="line"><a name="l00365"></a><span class="lineno"> 365</span>  <a class="code" href="classviennacl_1_1ocl_1_1local__mem.html">viennacl::ocl::local_mem</a>(static_cast<cl_uint>(128 * <span class="keyword">sizeof</span>(SCALARTYPE)))</div>
<div class="line"><a name="l00366"></a><span class="lineno"> 366</span>  ));</div>
<div class="line"><a name="l00367"></a><span class="lineno"> 367</span> </div>
<div class="line"><a name="l00368"></a><span class="lineno"> 368</span>  }</div>
<div class="line"><a name="l00369"></a><span class="lineno"> 369</span> </div>
<div class="line"><a name="l00370"></a><span class="lineno"> 370</span>  <span class="keywordflow">return</span> <span class="keyword">true</span>;</div>
<div class="line"><a name="l00371"></a><span class="lineno"> 371</span>  }</div>
<div class="line"><a name="l00372"></a><span class="lineno"> 372</span> </div>
<div class="line"><a name="l00373"></a><span class="lineno"> 373</span>  <span class="comment">/*</span></div>
<div class="line"><a name="l00374"></a><span class="lineno"> 374</span> <span class="comment"> template<typename SCALARTYPE, unsigned int ALIGNMENT></span></div>
<div class="line"><a name="l00375"></a><span class="lineno"> 375</span> <span class="comment"> bool householder_r(viennacl::matrix<SCALARTYPE, row_major, ALIGNMENT>& A,</span></div>
<div class="line"><a name="l00376"></a><span class="lineno"> 376</span> <span class="comment"> viennacl::matrix<SCALARTYPE, row_major, ALIGNMENT>& Q,</span></div>
<div class="line"><a name="l00377"></a><span class="lineno"> 377</span> <span class="comment"> viennacl::vector<SCALARTYPE, ALIGNMENT>& S,</span></div>
<div class="line"><a name="l00378"></a><span class="lineno"> 378</span> <span class="comment"> vcl_size_t start)</span></div>
<div class="line"><a name="l00379"></a><span class="lineno"> 379</span> <span class="comment"> {</span></div>
<div class="line"><a name="l00380"></a><span class="lineno"> 380</span> <span class="comment"></span></div>
<div class="line"><a name="l00381"></a><span class="lineno"> 381</span> <span class="comment"> vcl_size_t row_start = start;</span></div>
<div class="line"><a name="l00382"></a><span class="lineno"> 382</span> <span class="comment"> vcl_size_t col_start = start + 1;</span></div>
<div class="line"><a name="l00383"></a><span class="lineno"> 383</span> <span class="comment"></span></div>
<div class="line"><a name="l00384"></a><span class="lineno"> 384</span> <span class="comment"> if (col_start + 1 >= A.size2())</span></div>
<div class="line"><a name="l00385"></a><span class="lineno"> 385</span> <span class="comment"> return false;</span></div>
<div class="line"><a name="l00386"></a><span class="lineno"> 386</span> <span class="comment"></span></div>
<div class="line"><a name="l00387"></a><span class="lineno"> 387</span> <span class="comment"> std::vector<SCALARTYPE> tmp(A.size2(), 0);</span></div>
<div class="line"><a name="l00388"></a><span class="lineno"> 388</span> <span class="comment"></span></div>
<div class="line"><a name="l00389"></a><span class="lineno"> 389</span> <span class="comment"> copy_vec(A, S, row_start, col_start, false);</span></div>
<div class="line"><a name="l00390"></a><span class="lineno"> 390</span> <span class="comment"> fast_copy(S.begin(),</span></div>
<div class="line"><a name="l00391"></a><span class="lineno"> 391</span> <span class="comment"> S.begin() + (A.size2() - col_start),</span></div>
<div class="line"><a name="l00392"></a><span class="lineno"> 392</span> <span class="comment"> tmp.begin() + col_start);</span></div>
<div class="line"><a name="l00393"></a><span class="lineno"> 393</span> <span class="comment"></span></div>
<div class="line"><a name="l00394"></a><span class="lineno"> 394</span> <span class="comment"> detail::householder_vector(tmp, col_start);</span></div>
<div class="line"><a name="l00395"></a><span class="lineno"> 395</span> <span class="comment"> fast_copy(tmp, S);</span></div>
<div class="line"><a name="l00396"></a><span class="lineno"> 396</span> <span class="comment"></span></div>
<div class="line"><a name="l00397"></a><span class="lineno"> 397</span> <span class="comment"> viennacl::ocl::kernel& kernel = viennacl::ocl::get_kernel(viennacl::linalg::opencl::kernels::svd<SCALARTYPE>::program_name(), SVD_HOUSEHOLDER_ROW_KERNEL);</span></div>
<div class="line"><a name="l00398"></a><span class="lineno"> 398</span> <span class="comment"></span></div>
<div class="line"><a name="l00399"></a><span class="lineno"> 399</span> <span class="comment"> viennacl::ocl::enqueue(kernel(</span></div>
<div class="line"><a name="l00400"></a><span class="lineno"> 400</span> <span class="comment"> A,</span></div>
<div class="line"><a name="l00401"></a><span class="lineno"> 401</span> <span class="comment"> Q,</span></div>
<div class="line"><a name="l00402"></a><span class="lineno"> 402</span> <span class="comment"> S,</span></div>
<div class="line"><a name="l00403"></a><span class="lineno"> 403</span> <span class="comment"> static_cast<cl_uint>(row_start),</span></div>
<div class="line"><a name="l00404"></a><span class="lineno"> 404</span> <span class="comment"> static_cast<cl_uint>(col_start),</span></div>
<div class="line"><a name="l00405"></a><span class="lineno"> 405</span> <span class="comment"> static_cast<cl_uint>(A.size1()),</span></div>
<div class="line"><a name="l00406"></a><span class="lineno"> 406</span> <span class="comment"> static_cast<cl_uint>(A.size2()),</span></div>
<div class="line"><a name="l00407"></a><span class="lineno"> 407</span> <span class="comment"> static_cast<cl_uint>(A.internal_size2()),</span></div>
<div class="line"><a name="l00408"></a><span class="lineno"> 408</span> <span class="comment"> static_cast<cl_uint>(Q.internal_size2()),</span></div>
<div class="line"><a name="l00409"></a><span class="lineno"> 409</span> <span class="comment"> viennacl::ocl::local_mem(static_cast<cl_uint>(128 * sizeof(SCALARTYPE)))</span></div>
<div class="line"><a name="l00410"></a><span class="lineno"> 410</span> <span class="comment"> ));</span></div>
<div class="line"><a name="l00411"></a><span class="lineno"> 411</span> <span class="comment"> return true;</span></div>
<div class="line"><a name="l00412"></a><span class="lineno"> 412</span> <span class="comment"> } */</span></div>
<div class="line"><a name="l00413"></a><span class="lineno"> 413</span> </div>
<div class="line"><a name="l00414"></a><span class="lineno"> 414</span>  <span class="keyword">template</span><<span class="keyword">typename</span> SCALARTYPE, <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> ALIGNMENT></div>
<div class="line"><a name="l00415"></a><span class="lineno"><a class="line" href="namespaceviennacl_1_1linalg_1_1detail.html#af8b53df1b5fb63b53073889589646dc5"> 415</a></span>  <span class="keywordtype">bool</span> <a class="code" href="namespaceviennacl_1_1linalg_1_1detail.html#af8b53df1b5fb63b53073889589646dc5">householder_r</a>(<a class="code" href="classviennacl_1_1matrix.html">viennacl::matrix<SCALARTYPE, row_major, ALIGNMENT></a> & A,</div>
<div class="line"><a name="l00416"></a><span class="lineno"> 416</span>  <a class="code" href="classviennacl_1_1matrix.html">viennacl::matrix<SCALARTYPE, row_major, ALIGNMENT></a> & Q,</div>
<div class="line"><a name="l00417"></a><span class="lineno"> 417</span>  <a class="code" href="classviennacl_1_1vector.html">viennacl::vector<SCALARTYPE, ALIGNMENT></a>& D,</div>
<div class="line"><a name="l00418"></a><span class="lineno"> 418</span>  <a class="code" href="namespaceviennacl.html#a98a0afcc513111ffa0bd138f891930df">vcl_size_t</a> row_start, <a class="code" href="namespaceviennacl.html#a98a0afcc513111ffa0bd138f891930df">vcl_size_t</a> col_start)</div>
<div class="line"><a name="l00419"></a><span class="lineno"> 419</span>  {</div>
<div class="line"><a name="l00420"></a><span class="lineno"> 420</span>  <a class="code" href="classviennacl_1_1ocl_1_1context.html">viennacl::ocl::context</a> & ctx = <span class="keyword">const_cast<</span><a class="code" href="classviennacl_1_1ocl_1_1context.html">viennacl::ocl::context</a> &<span class="keyword">></span>(viennacl::traits::opencl_handle(A).context());</div>
<div class="line"><a name="l00421"></a><span class="lineno"> 421</span> </div>
<div class="line"><a name="l00422"></a><span class="lineno"> 422</span>  <span class="keywordflow">if</span> (col_start + 1 >= A.<a class="code" href="classviennacl_1_1matrix__base.html#a4348766b3b9cb049f7acd6a795272dbe">size2</a>())</div>
<div class="line"><a name="l00423"></a><span class="lineno"> 423</span>  <span class="keywordflow">return</span> <span class="keyword">false</span>;</div>
<div class="line"><a name="l00424"></a><span class="lineno"> 424</span> </div>
<div class="line"><a name="l00425"></a><span class="lineno"> 425</span>  <a class="code" href="namespaceviennacl_1_1linalg_1_1detail.html#a5852aa7527c0599681f1b0fbc753d357">prepare_householder_vector</a>(A, D, A.<a class="code" href="classviennacl_1_1matrix__base.html#a4348766b3b9cb049f7acd6a795272dbe">size2</a>(), row_start, col_start, col_start, <span class="keyword">false</span>);</div>
<div class="line"><a name="l00426"></a><span class="lineno"> 426</span> </div>
<div class="line"><a name="l00427"></a><span class="lineno"> 427</span>  {</div>
<div class="line"><a name="l00428"></a><span class="lineno"> 428</span>  <a class="code" href="classviennacl_1_1ocl_1_1kernel.html">viennacl::ocl::kernel</a>& kernel = ctx.<a class="code" href="classviennacl_1_1ocl_1_1context.html#afe68ad8c2df449f40f45db6605038946">get_kernel</a>(<a class="code" href="structviennacl_1_1linalg_1_1opencl_1_1kernels_1_1svd.html">viennacl::linalg::opencl::kernels::svd<SCALARTYPE>::program_name</a>(), <a class="code" href="namespaceviennacl_1_1linalg.html#ace85ea4095e9e7404b6f77b767ac000f">SVD_HOUSEHOLDER_UPDATE_A_RIGHT_KERNEL</a>);</div>
<div class="line"><a name="l00429"></a><span class="lineno"> 429</span> </div>
<div class="line"><a name="l00430"></a><span class="lineno"> 430</span>  <a class="code" href="namespaceviennacl_1_1ocl.html#a5f2022f653ea1cf364d20e3ff84dcada">viennacl::ocl::enqueue</a>(kernel(</div>
<div class="line"><a name="l00431"></a><span class="lineno"> 431</span>  A,</div>
<div class="line"><a name="l00432"></a><span class="lineno"> 432</span>  D,</div>
<div class="line"><a name="l00433"></a><span class="lineno"> 433</span>  static_cast<cl_uint>(row_start),</div>
<div class="line"><a name="l00434"></a><span class="lineno"> 434</span>  static_cast<cl_uint>(col_start),</div>
<div class="line"><a name="l00435"></a><span class="lineno"> 435</span>  static_cast<cl_uint>(A.<a class="code" href="classviennacl_1_1matrix__base.html#a24e4f5fa27a1af5ad47e52a97c065d68">size1</a>()),</div>
<div class="line"><a name="l00436"></a><span class="lineno"> 436</span>  static_cast<cl_uint>(A.<a class="code" href="classviennacl_1_1matrix__base.html#a4348766b3b9cb049f7acd6a795272dbe">size2</a>()),</div>
<div class="line"><a name="l00437"></a><span class="lineno"> 437</span>  static_cast<cl_uint>(A.<a class="code" href="classviennacl_1_1matrix__base.html#a00e30fdc61081a73995b54175a91d220">internal_size2</a>()),</div>
<div class="line"><a name="l00438"></a><span class="lineno"> 438</span>  <a class="code" href="classviennacl_1_1ocl_1_1local__mem.html">viennacl::ocl::local_mem</a>(static_cast<cl_uint>(128 * <span class="keyword">sizeof</span>(SCALARTYPE)))</div>
<div class="line"><a name="l00439"></a><span class="lineno"> 439</span>  ));</div>
<div class="line"><a name="l00440"></a><span class="lineno"> 440</span>  }</div>
<div class="line"><a name="l00441"></a><span class="lineno"> 441</span> </div>
<div class="line"><a name="l00442"></a><span class="lineno"> 442</span>  {</div>
<div class="line"><a name="l00443"></a><span class="lineno"> 443</span>  <a class="code" href="classviennacl_1_1ocl_1_1kernel.html">viennacl::ocl::kernel</a>& kernel = ctx.<a class="code" href="classviennacl_1_1ocl_1_1context.html#afe68ad8c2df449f40f45db6605038946">get_kernel</a>(<a class="code" href="structviennacl_1_1linalg_1_1opencl_1_1kernels_1_1svd.html">viennacl::linalg::opencl::kernels::svd<SCALARTYPE>::program_name</a>(), <a class="code" href="namespaceviennacl_1_1linalg.html#a5b5cb81b46208cae772a5e0813f02517">SVD_HOUSEHOLDER_UPDATE_QR_KERNEL</a>);</div>
<div class="line"><a name="l00444"></a><span class="lineno"> 444</span> </div>
<div class="line"><a name="l00445"></a><span class="lineno"> 445</span>  <a class="code" href="namespaceviennacl_1_1ocl.html#a5f2022f653ea1cf364d20e3ff84dcada">viennacl::ocl::enqueue</a>(kernel(</div>
<div class="line"><a name="l00446"></a><span class="lineno"> 446</span>  Q,</div>
<div class="line"><a name="l00447"></a><span class="lineno"> 447</span>  D,</div>
<div class="line"><a name="l00448"></a><span class="lineno"> 448</span>  static_cast<cl_uint>(A.<a class="code" href="classviennacl_1_1matrix__base.html#a24e4f5fa27a1af5ad47e52a97c065d68">size1</a>()),</div>
<div class="line"><a name="l00449"></a><span class="lineno"> 449</span>  static_cast<cl_uint>(A.<a class="code" href="classviennacl_1_1matrix__base.html#a4348766b3b9cb049f7acd6a795272dbe">size2</a>()),</div>
<div class="line"><a name="l00450"></a><span class="lineno"> 450</span>  static_cast<cl_uint>(Q.<a class="code" href="classviennacl_1_1matrix__base.html#a00e30fdc61081a73995b54175a91d220">internal_size2</a>()),</div>
<div class="line"><a name="l00451"></a><span class="lineno"> 451</span>  <a class="code" href="classviennacl_1_1ocl_1_1local__mem.html">viennacl::ocl::local_mem</a>(static_cast<cl_uint>(128 * <span class="keyword">sizeof</span>(SCALARTYPE)))</div>
<div class="line"><a name="l00452"></a><span class="lineno"> 452</span>  ));</div>
<div class="line"><a name="l00453"></a><span class="lineno"> 453</span>  }</div>
<div class="line"><a name="l00454"></a><span class="lineno"> 454</span> </div>
<div class="line"><a name="l00455"></a><span class="lineno"> 455</span>  <span class="keywordflow">return</span> <span class="keyword">true</span>;</div>
<div class="line"><a name="l00456"></a><span class="lineno"> 456</span>  }</div>
<div class="line"><a name="l00457"></a><span class="lineno"> 457</span> </div>
<div class="line"><a name="l00458"></a><span class="lineno"> 458</span>  <span class="keyword">template</span><<span class="keyword">typename</span> SCALARTYPE, <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> ALIGNMENT></div>
<div class="line"><a name="l00459"></a><span class="lineno"><a class="line" href="namespaceviennacl_1_1linalg_1_1detail.html#aedc8c34c5978a76a894890bf6d86010f"> 459</a></span>  <span class="keywordtype">void</span> <a class="code" href="namespaceviennacl_1_1linalg_1_1detail.html#aedc8c34c5978a76a894890bf6d86010f">bidiag</a>(<a class="code" href="classviennacl_1_1matrix.html">viennacl::matrix<SCALARTYPE, row_major, ALIGNMENT></a> & Ai,</div>
<div class="line"><a name="l00460"></a><span class="lineno"> 460</span>  <a class="code" href="classviennacl_1_1matrix.html">viennacl::matrix<SCALARTYPE, row_major, ALIGNMENT></a> & QL,</div>
<div class="line"><a name="l00461"></a><span class="lineno"> 461</span>  <a class="code" href="classviennacl_1_1matrix.html">viennacl::matrix<SCALARTYPE, row_major, ALIGNMENT></a> & QR)</div>
<div class="line"><a name="l00462"></a><span class="lineno"> 462</span>  {</div>
<div class="line"><a name="l00463"></a><span class="lineno"> 463</span>  <a class="code" href="namespaceviennacl.html#a98a0afcc513111ffa0bd138f891930df">vcl_size_t</a> row_num = Ai.<a class="code" href="classviennacl_1_1matrix__base.html#a24e4f5fa27a1af5ad47e52a97c065d68">size1</a>();</div>
<div class="line"><a name="l00464"></a><span class="lineno"> 464</span>  <a class="code" href="namespaceviennacl.html#a98a0afcc513111ffa0bd138f891930df">vcl_size_t</a> col_num = Ai.<a class="code" href="classviennacl_1_1matrix__base.html#a4348766b3b9cb049f7acd6a795272dbe">size2</a>();</div>
<div class="line"><a name="l00465"></a><span class="lineno"> 465</span> </div>
<div class="line"><a name="l00466"></a><span class="lineno"> 466</span>  <a class="code" href="namespaceviennacl.html#a98a0afcc513111ffa0bd138f891930df">vcl_size_t</a> to = <a class="code" href="namespaceviennacl_1_1linalg_1_1detail.html#aef015779a92be597e546c3491cebf6c1">std::min</a>(row_num, col_num);</div>
<div class="line"><a name="l00467"></a><span class="lineno"> 467</span>  <a class="code" href="namespaceviennacl.html#a98a0afcc513111ffa0bd138f891930df">vcl_size_t</a> big_to = <a class="code" href="namespaceviennacl_1_1linalg_1_1detail.html#a5d46fe9558b0e462f10fd44942ad4fc6">std::max</a>(row_num, col_num);</div>
<div class="line"><a name="l00468"></a><span class="lineno"> 468</span> </div>
<div class="line"><a name="l00469"></a><span class="lineno"> 469</span>  <span class="comment">//for storing householder vector</span></div>
<div class="line"><a name="l00470"></a><span class="lineno"> 470</span>  <a class="code" href="classviennacl_1_1vector.html">viennacl::vector<SCALARTYPE, ALIGNMENT></a> hh_vector(big_to, <a class="code" href="namespaceviennacl_1_1traits.html#a6707f5dab8f482170d2046a605f46ef8">viennacl::traits::context</a>(Ai));</div>
<div class="line"><a name="l00471"></a><span class="lineno"> 471</span> </div>
<div class="line"><a name="l00472"></a><span class="lineno"> 472</span>  QL = <a class="code" href="classviennacl_1_1identity__matrix.html">viennacl::identity_matrix<SCALARTYPE></a>(QL.<a class="code" href="classviennacl_1_1matrix__base.html#a24e4f5fa27a1af5ad47e52a97c065d68">size1</a>(), <a class="code" href="namespaceviennacl_1_1traits.html#a6707f5dab8f482170d2046a605f46ef8">viennacl::traits::context</a>(QL));</div>
<div class="line"><a name="l00473"></a><span class="lineno"> 473</span>  QR = <a class="code" href="classviennacl_1_1identity__matrix.html">viennacl::identity_matrix<SCALARTYPE></a>(QR.<a class="code" href="classviennacl_1_1implicit__matrix__base.html#adb2478453dc7af39d89e8140abd53c7f">size1</a>(), <a class="code" href="namespaceviennacl_1_1traits.html#a6707f5dab8f482170d2046a605f46ef8">viennacl::traits::context</a>(QR));</div>
<div class="line"><a name="l00474"></a><span class="lineno"> 474</span> </div>
<div class="line"><a name="l00475"></a><span class="lineno"> 475</span>  <span class="keywordflow">for</span> (<a class="code" href="namespaceviennacl.html#a98a0afcc513111ffa0bd138f891930df">vcl_size_t</a> i = 0; i < to; i++)</div>
<div class="line"><a name="l00476"></a><span class="lineno"> 476</span>  {</div>
<div class="line"><a name="l00477"></a><span class="lineno"> 477</span>  <a class="code" href="namespaceviennacl_1_1linalg_1_1detail.html#aabaaa377c989dddc5ab35faf8541b8f8">householder_c</a>(Ai, QL, hh_vector, i, i);</div>
<div class="line"><a name="l00478"></a><span class="lineno"> 478</span>  <a class="code" href="namespaceviennacl_1_1linalg_1_1detail.html#af8b53df1b5fb63b53073889589646dc5">householder_r</a>(Ai, QR, hh_vector, i, i+1);</div>
<div class="line"><a name="l00479"></a><span class="lineno"> 479</span>  }</div>
<div class="line"><a name="l00480"></a><span class="lineno"> 480</span>  }</div>
<div class="line"><a name="l00481"></a><span class="lineno"> 481</span> </div>
<div class="line"><a name="l00482"></a><span class="lineno"> 482</span>  } <span class="comment">// namespace detail</span></div>
<div class="line"><a name="l00483"></a><span class="lineno"> 483</span> </div>
<div class="line"><a name="l00484"></a><span class="lineno"> 484</span> </div>
<div class="line"><a name="l00491"></a><span class="lineno"> 491</span>  <span class="keyword">template</span><<span class="keyword">typename</span> SCALARTYPE, <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> ALIGNMENT></div>
<div class="line"><a name="l00492"></a><span class="lineno"><a class="line" href="namespaceviennacl_1_1linalg.html#a7dd4119fc5dfef5c067af3b46bd86191"> 492</a></span>  <span class="keywordtype">void</span> <a class="code" href="namespaceviennacl_1_1linalg.html#a7dd4119fc5dfef5c067af3b46bd86191">svd</a>(<a class="code" href="classviennacl_1_1matrix.html">viennacl::matrix<SCALARTYPE, row_major, ALIGNMENT></a> & A,</div>
<div class="line"><a name="l00493"></a><span class="lineno"> 493</span>  <a class="code" href="classviennacl_1_1matrix.html">viennacl::matrix<SCALARTYPE, row_major, ALIGNMENT></a> & QL,</div>
<div class="line"><a name="l00494"></a><span class="lineno"> 494</span>  <a class="code" href="classviennacl_1_1matrix.html">viennacl::matrix<SCALARTYPE, row_major, ALIGNMENT></a> & QR)</div>
<div class="line"><a name="l00495"></a><span class="lineno"> 495</span>  {</div>
<div class="line"><a name="l00496"></a><span class="lineno"> 496</span>  <a class="code" href="classviennacl_1_1ocl_1_1context.html">viennacl::ocl::context</a> & ctx = <span class="keyword">const_cast<</span><a class="code" href="classviennacl_1_1ocl_1_1context.html">viennacl::ocl::context</a> &<span class="keyword">></span>(viennacl::traits::opencl_handle(A).context());</div>
<div class="line"><a name="l00497"></a><span class="lineno"> 497</span>  <a class="code" href="structviennacl_1_1linalg_1_1opencl_1_1kernels_1_1svd.html#ab9e831dbb989de8ddc771c949658b514">viennacl::linalg::opencl::kernels::svd<SCALARTYPE>::init</a>(ctx);</div>
<div class="line"><a name="l00498"></a><span class="lineno"> 498</span> </div>
<div class="line"><a name="l00499"></a><span class="lineno"> 499</span>  <a class="code" href="namespaceviennacl.html#a98a0afcc513111ffa0bd138f891930df">vcl_size_t</a> row_num = A.<a class="code" href="classviennacl_1_1matrix__base.html#a24e4f5fa27a1af5ad47e52a97c065d68">size1</a>();</div>
<div class="line"><a name="l00500"></a><span class="lineno"> 500</span>  <a class="code" href="namespaceviennacl.html#a98a0afcc513111ffa0bd138f891930df">vcl_size_t</a> col_num = A.<a class="code" href="classviennacl_1_1matrix__base.html#a4348766b3b9cb049f7acd6a795272dbe">size2</a>();</div>
<div class="line"><a name="l00501"></a><span class="lineno"> 501</span> </div>
<div class="line"><a name="l00502"></a><span class="lineno"> 502</span>  <a class="code" href="namespaceviennacl.html#a98a0afcc513111ffa0bd138f891930df">vcl_size_t</a> to = <a class="code" href="namespaceviennacl_1_1linalg_1_1detail.html#aef015779a92be597e546c3491cebf6c1">std::min</a>(row_num, col_num);</div>
<div class="line"><a name="l00503"></a><span class="lineno"> 503</span> </div>
<div class="line"><a name="l00504"></a><span class="lineno"> 504</span> </div>
<div class="line"><a name="l00505"></a><span class="lineno"> 505</span>  <span class="comment">//viennacl::vector<SCALARTYPE, ALIGNMENT> d(to);</span></div>
<div class="line"><a name="l00506"></a><span class="lineno"> 506</span>  <span class="comment">//viennacl::vector<SCALARTYPE, ALIGNMENT> s(to + 1);</span></div>
<div class="line"><a name="l00507"></a><span class="lineno"> 507</span> </div>
<div class="line"><a name="l00508"></a><span class="lineno"> 508</span>  <span class="comment">// first stage</span></div>
<div class="line"><a name="l00509"></a><span class="lineno"> 509</span>  <a class="code" href="namespaceviennacl_1_1linalg_1_1detail.html#aedc8c34c5978a76a894890bf6d86010f">detail::bidiag</a>(A, QL, QR);</div>
<div class="line"><a name="l00510"></a><span class="lineno"> 510</span> </div>
<div class="line"><a name="l00511"></a><span class="lineno"> 511</span>  <span class="comment">// second stage</span></div>
<div class="line"><a name="l00512"></a><span class="lineno"> 512</span>  <span class="comment">//std::vector<SCALARTYPE> dh(to, 0);</span></div>
<div class="line"><a name="l00513"></a><span class="lineno"> 513</span>  <span class="comment">//std::vector<SCALARTYPE> sh(to + 1, 0);</span></div>
<div class="line"><a name="l00514"></a><span class="lineno"> 514</span>  boost::numeric::ublas::vector<SCALARTYPE> dh = boost::numeric::ublas::scalar_vector<SCALARTYPE>(to, 0);</div>
<div class="line"><a name="l00515"></a><span class="lineno"> 515</span>  boost::numeric::ublas::vector<SCALARTYPE> sh = boost::numeric::ublas::scalar_vector<SCALARTYPE>(to + 1, 0);</div>
<div class="line"><a name="l00516"></a><span class="lineno"> 516</span> </div>
<div class="line"><a name="l00517"></a><span class="lineno"> 517</span> </div>
<div class="line"><a name="l00518"></a><span class="lineno"> 518</span>  <a class="code" href="namespaceviennacl_1_1linalg_1_1opencl.html#ae9e45a4202d75a28076b78d133ba9379">viennacl::linalg::opencl::bidiag_pack_svd</a>(A, dh, sh);</div>
<div class="line"><a name="l00519"></a><span class="lineno"> 519</span> </div>
<div class="line"><a name="l00520"></a><span class="lineno"> 520</span>  <a class="code" href="namespaceviennacl_1_1linalg_1_1detail.html#a38fd7b41df5895671a4beb943cc35bc3">detail::svd_qr_shift</a>( QL, QR, dh, sh);</div>
<div class="line"><a name="l00521"></a><span class="lineno"> 521</span> </div>
<div class="line"><a name="l00522"></a><span class="lineno"> 522</span>  <span class="comment">// Write resulting diagonal matrix with singular values to A:</span></div>
<div class="line"><a name="l00523"></a><span class="lineno"> 523</span>  boost::numeric::ublas::matrix<SCALARTYPE> h_Sigma(row_num, col_num);</div>
<div class="line"><a name="l00524"></a><span class="lineno"> 524</span>  h_Sigma.clear();</div>
<div class="line"><a name="l00525"></a><span class="lineno"> 525</span> </div>
<div class="line"><a name="l00526"></a><span class="lineno"> 526</span>  <span class="keywordflow">for</span> (<a class="code" href="namespaceviennacl.html#a98a0afcc513111ffa0bd138f891930df">vcl_size_t</a> i = 0; i < to; i++)</div>
<div class="line"><a name="l00527"></a><span class="lineno"> 527</span>  h_Sigma(i, i) = dh[i];</div>
<div class="line"><a name="l00528"></a><span class="lineno"> 528</span> </div>
<div class="line"><a name="l00529"></a><span class="lineno"> 529</span>  <a class="code" href="namespaceviennacl.html#a10b7f8cf6b8864a7aa196d670481a453">copy</a>(h_Sigma, A);</div>
<div class="line"><a name="l00530"></a><span class="lineno"> 530</span>  }</div>
<div class="line"><a name="l00531"></a><span class="lineno"> 531</span>  }</div>
<div class="line"><a name="l00532"></a><span class="lineno"> 532</span> }</div>
<div class="line"><a name="l00533"></a><span class="lineno"> 533</span> <span class="preprocessor">#endif</span></div>
<div class="ttc" id="namespaceviennacl_1_1linalg_1_1detail_html_a1f9130eb00ff2625dff55b18e0ac1553"><div class="ttname"><a href="namespaceviennacl_1_1linalg_1_1detail.html#a1f9130eb00ff2625dff55b18e0ac1553">viennacl::linalg::detail::change_signs</a></div><div class="ttdeci">void change_signs(MatrixType &matrix, VectorType &signs, int n)</div><div class="ttdef"><b>Definition:</b> <a href="svd_8hpp_source.html#l00078">svd.hpp:78</a></div></div>
<div class="ttc" id="namespaceviennacl_1_1linalg_html_a05717ddd22894376e780b075d59616ed"><div class="ttname"><a href="namespaceviennacl_1_1linalg.html#a05717ddd22894376e780b075d59616ed">viennacl::linalg::SVD_INVERSE_SIGNS_KERNEL</a></div><div class="ttdeci">const std::string SVD_INVERSE_SIGNS_KERNEL</div><div class="ttdef"><b>Definition:</b> <a href="qr-method-common_8hpp_source.html#l00051">qr-method-common.hpp:51</a></div></div>
<div class="ttc" id="classviennacl_1_1ocl_1_1kernel_html"><div class="ttname"><a href="classviennacl_1_1ocl_1_1kernel.html">viennacl::ocl::kernel</a></div><div class="ttdoc">Represents an OpenCL kernel within ViennaCL. </div><div class="ttdef"><b>Definition:</b> <a href="kernel_8hpp_source.html#l00058">kernel.hpp:58</a></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="classviennacl_1_1ocl_1_1kernel_html_ae2b841c487f9ddbfcfb6297d648e2d7f"><div class="ttname"><a href="classviennacl_1_1ocl_1_1kernel.html#ae2b841c487f9ddbfcfb6297d648e2d7f">viennacl::ocl::kernel::local_work_size</a></div><div class="ttdeci">size_type local_work_size(int index=0) const </div><div class="ttdoc">Returns the local work size at the respective dimension. </div><div class="ttdef"><b>Definition:</b> <a href="kernel_8hpp_source.html#l00742">kernel.hpp:742</a></div></div>
<div class="ttc" id="namespaceviennacl_1_1traits_html_aa756f5d6820722094cae0d8b9bb6d5e2"><div class="ttname"><a href="namespaceviennacl_1_1traits.html#aa756f5d6820722094cae0d8b9bb6d5e2">viennacl::traits::size1</a></div><div class="ttdeci">vcl_size_t size1(MatrixType const &mat)</div><div class="ttdoc">Generic routine for obtaining the number of rows of a matrix (ViennaCL, uBLAS, etc.) </div><div class="ttdef"><b>Definition:</b> <a href="size_8hpp_source.html#l00163">size.hpp:163</a></div></div>
<div class="ttc" id="classviennacl_1_1ocl_1_1context_html"><div class="ttname"><a href="classviennacl_1_1ocl_1_1context.html">viennacl::ocl::context</a></div><div class="ttdoc">Manages an OpenCL context and provides the respective convenience functions for creating buffers...</div><div class="ttdef"><b>Definition:</b> <a href="ocl_2context_8hpp_source.html#l00055">context.hpp:55</a></div></div>
<div class="ttc" id="namespaceviennacl_1_1linalg_html_ace85ea4095e9e7404b6f77b767ac000f"><div class="ttname"><a href="namespaceviennacl_1_1linalg.html#ace85ea4095e9e7404b6f77b767ac000f">viennacl::linalg::SVD_HOUSEHOLDER_UPDATE_A_RIGHT_KERNEL</a></div><div class="ttdeci">const std::string SVD_HOUSEHOLDER_UPDATE_A_RIGHT_KERNEL</div><div class="ttdef"><b>Definition:</b> <a href="qr-method-common_8hpp_source.html#l00056">qr-method-common.hpp:56</a></div></div>
<div class="ttc" id="namespaceviennacl_1_1linalg_html_a5b5cb81b46208cae772a5e0813f02517"><div class="ttname"><a href="namespaceviennacl_1_1linalg.html#a5b5cb81b46208cae772a5e0813f02517">viennacl::linalg::SVD_HOUSEHOLDER_UPDATE_QR_KERNEL</a></div><div class="ttdeci">const std::string SVD_HOUSEHOLDER_UPDATE_QR_KERNEL</div><div class="ttdef"><b>Definition:</b> <a href="qr-method-common_8hpp_source.html#l00049">qr-method-common.hpp:49</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_1linalg_1_1detail_html_aad4cd2951549618c93f74ff26444675f"><div class="ttname"><a href="namespaceviennacl_1_1linalg_1_1detail.html#aad4cd2951549618c93f74ff26444675f">viennacl::linalg::detail::transpose</a></div><div class="ttdeci">void transpose(matrix_base< SCALARTYPE > &A)</div><div class="ttdef"><b>Definition:</b> <a href="qr-method-common_8hpp_source.html#l00107">qr-method-common.hpp:107</a></div></div>
<div class="ttc" id="structviennacl_1_1linalg_1_1opencl_1_1kernels_1_1svd_html_ab9e831dbb989de8ddc771c949658b514"><div class="ttname"><a href="structviennacl_1_1linalg_1_1opencl_1_1kernels_1_1svd.html#ab9e831dbb989de8ddc771c949658b514">viennacl::linalg::opencl::kernels::svd::init</a></div><div class="ttdeci">static void init(viennacl::ocl::context &ctx)</div><div class="ttdef"><b>Definition:</b> <a href="opencl_2kernels_2svd_8hpp_source.html#l00652">svd.hpp:652</a></div></div>
<div class="ttc" id="classviennacl_1_1identity__matrix_html"><div class="ttname"><a href="classviennacl_1_1identity__matrix.html">viennacl::identity_matrix</a></div><div class="ttdoc">Represents a vector consisting of 1 at a given index and zeros otherwise. To be used as an initialize...</div><div class="ttdef"><b>Definition:</b> <a href="matrix__def_8hpp_source.html#l00069">matrix_def.hpp:69</a></div></div>
<div class="ttc" id="namespaceviennacl_1_1linalg_1_1detail_html_a5d46fe9558b0e462f10fd44942ad4fc6"><div class="ttname"><a href="namespaceviennacl_1_1linalg_1_1detail.html#a5d46fe9558b0e462f10fd44942ad4fc6">viennacl::linalg::detail::max</a></div><div class="ttdeci">T max(const T &lhs, const T &rhs)</div><div class="ttdoc">Maximum. </div><div class="ttdef"><b>Definition:</b> <a href="linalg_2detail_2bisect_2util_8hpp_source.html#l00059">util.hpp:59</a></div></div>
<div class="ttc" id="namespaceviennacl_1_1linalg_1_1detail_html_a5852aa7527c0599681f1b0fbc753d357"><div class="ttname"><a href="namespaceviennacl_1_1linalg_1_1detail.html#a5852aa7527c0599681f1b0fbc753d357">viennacl::linalg::detail::prepare_householder_vector</a></div><div class="ttdeci">void prepare_householder_vector(matrix_base< SCALARTYPE > &A, vector_base< SCALARTYPE > &D, vcl_size_t size, vcl_size_t row_start, vcl_size_t col_start, vcl_size_t start, bool is_column)</div><div class="ttdef"><b>Definition:</b> <a href="qr-method-common_8hpp_source.html#l00165">qr-method-common.hpp:165</a></div></div>
<div class="ttc" id="namespaceviennacl_1_1linalg_html_a7dd4119fc5dfef5c067af3b46bd86191"><div class="ttname"><a href="namespaceviennacl_1_1linalg.html#a7dd4119fc5dfef5c067af3b46bd86191">viennacl::linalg::svd</a></div><div class="ttdeci">void svd(viennacl::matrix< SCALARTYPE, row_major, ALIGNMENT > &A, viennacl::matrix< SCALARTYPE, row_major, ALIGNMENT > &QL, viennacl::matrix< SCALARTYPE, row_major, ALIGNMENT > &QR)</div><div class="ttdoc">Computes the singular value decomposition of a matrix A. Experimental in 1.3.x. </div><div class="ttdef"><b>Definition:</b> <a href="svd_8hpp_source.html#l00492">svd.hpp:492</a></div></div>
<div class="ttc" id="namespaceviennacl_1_1traits_html_a3658e7c29ac0f60a20cb5871f5b5fd98"><div class="ttname"><a href="namespaceviennacl_1_1traits.html#a3658e7c29ac0f60a20cb5871f5b5fd98">viennacl::traits::size2</a></div><div class="ttdeci">result_of::size_type< MatrixType >::type size2(MatrixType const &mat)</div><div class="ttdoc">Generic routine for obtaining the number of columns of a matrix (ViennaCL, uBLAS, etc...</div><div class="ttdef"><b>Definition:</b> <a href="size_8hpp_source.html#l00201">size.hpp:201</a></div></div>
<div class="ttc" id="opencl_2kernels_2svd_8hpp_html"><div class="ttname"><a href="opencl_2kernels_2svd_8hpp.html">svd.hpp</a></div><div class="ttdoc">OpenCL kernel file for singular value decomposition. </div></div>
<div class="ttc" id="namespaceviennacl_1_1linalg_1_1detail_html_af8b53df1b5fb63b53073889589646dc5"><div class="ttname"><a href="namespaceviennacl_1_1linalg_1_1detail.html#af8b53df1b5fb63b53073889589646dc5">viennacl::linalg::detail::householder_r</a></div><div class="ttdeci">bool householder_r(viennacl::matrix< SCALARTYPE, row_major, ALIGNMENT > &A, viennacl::matrix< SCALARTYPE, row_major, ALIGNMENT > &Q, viennacl::vector< SCALARTYPE, ALIGNMENT > &D, vcl_size_t row_start, vcl_size_t col_start)</div><div class="ttdef"><b>Definition:</b> <a href="svd_8hpp_source.html#l00415">svd.hpp:415</a></div></div>
<div class="ttc" id="qr-method-common_8hpp_html"><div class="ttname"><a href="qr-method-common_8hpp.html">qr-method-common.hpp</a></div><div class="ttdoc">Common routines used for the QR method and SVD. Experimental. </div></div>
<div class="ttc" id="classviennacl_1_1ocl_1_1local__mem_html"><div class="ttname"><a href="classviennacl_1_1ocl_1_1local__mem.html">viennacl::ocl::local_mem</a></div><div class="ttdoc">A class representing local (shared) OpenCL memory. Typically used as kernel argument. </div><div class="ttdef"><b>Definition:</b> <a href="local__mem_8hpp_source.html#l00033">local_mem.hpp:33</a></div></div>
<div class="ttc" id="structviennacl_1_1linalg_1_1opencl_1_1kernels_1_1svd_html"><div class="ttname"><a href="structviennacl_1_1linalg_1_1opencl_1_1kernels_1_1svd.html">viennacl::linalg::opencl::kernels::svd</a></div><div class="ttdoc">Main kernel class for generating OpenCL kernels for singular value decomposition of dense matrices...</div><div class="ttdef"><b>Definition:</b> <a href="opencl_2kernels_2svd_8hpp_source.html#l00644">svd.hpp:644</a></div></div>
<div class="ttc" id="classviennacl_1_1ocl_1_1context_html_afe68ad8c2df449f40f45db6605038946"><div class="ttname"><a href="classviennacl_1_1ocl_1_1context.html#afe68ad8c2df449f40f45db6605038946">viennacl::ocl::context::get_kernel</a></div><div class="ttdeci">viennacl::ocl::kernel & get_kernel(std::string const &program_name, std::string const &kernel_name)</div><div class="ttdoc">Convenience function for retrieving the kernel of a program directly from the context. </div><div class="ttdef"><b>Definition:</b> <a href="ocl_2context_8hpp_source.html#l00605">context.hpp:605</a></div></div>
<div class="ttc" id="classviennacl_1_1implicit__matrix__base_html_adb2478453dc7af39d89e8140abd53c7f"><div class="ttname"><a href="classviennacl_1_1implicit__matrix__base.html#adb2478453dc7af39d89e8140abd53c7f">viennacl::implicit_matrix_base::size1</a></div><div class="ttdeci">size_type size1() const </div><div class="ttdef"><b>Definition:</b> <a href="matrix__def_8hpp_source.html#l00044">matrix_def.hpp:44</a></div></div>
<div class="ttc" id="namespaceviennacl_1_1linalg_1_1detail_html_aabaaa377c989dddc5ab35faf8541b8f8"><div class="ttname"><a href="namespaceviennacl_1_1linalg_1_1detail.html#aabaaa377c989dddc5ab35faf8541b8f8">viennacl::linalg::detail::householder_c</a></div><div class="ttdeci">bool householder_c(viennacl::matrix< SCALARTYPE, row_major, ALIGNMENT > &A, viennacl::matrix< SCALARTYPE, row_major, ALIGNMENT > &Q, viennacl::vector< SCALARTYPE, ALIGNMENT > &D, vcl_size_t row_start, vcl_size_t col_start)</div><div class="ttdef"><b>Definition:</b> <a href="svd_8hpp_source.html#l00328">svd.hpp:328</a></div></div>
<div class="ttc" id="namespaceviennacl_1_1linalg_html_a8e62fa452895c889f7bad9700300994d"><div class="ttname"><a href="namespaceviennacl_1_1linalg.html#a8e62fa452895c889f7bad9700300994d">viennacl::linalg::SVD_HOUSEHOLDER_UPDATE_A_LEFT_KERNEL</a></div><div class="ttdeci">const std::string SVD_HOUSEHOLDER_UPDATE_A_LEFT_KERNEL</div><div class="ttdef"><b>Definition:</b> <a href="qr-method-common_8hpp_source.html#l00055">qr-method-common.hpp:55</a></div></div>
<div class="ttc" id="namespaceviennacl_html_a98a0afcc513111ffa0bd138f891930df"><div class="ttname"><a href="namespaceviennacl.html#a98a0afcc513111ffa0bd138f891930df">viennacl::vcl_size_t</a></div><div class="ttdeci">std::size_t vcl_size_t</div><div class="ttdef"><b>Definition:</b> <a href="forwards_8h_source.html#l00075">forwards.h:75</a></div></div>
<div class="ttc" id="classviennacl_1_1matrix__base_html_a4348766b3b9cb049f7acd6a795272dbe"><div class="ttname"><a href="classviennacl_1_1matrix__base.html#a4348766b3b9cb049f7acd6a795272dbe">viennacl::matrix_base< NumericT >::size2</a></div><div class="ttdeci">size_type size2() const</div><div class="ttdoc">Returns the number of columns. </div><div class="ttdef"><b>Definition:</b> <a href="matrix__def_8hpp_source.html#l00226">matrix_def.hpp:226</a></div></div>
<div class="ttc" id="namespaceviennacl_1_1linalg_1_1opencl_html_ae9e45a4202d75a28076b78d133ba9379"><div class="ttname"><a href="namespaceviennacl_1_1linalg_1_1opencl.html#ae9e45a4202d75a28076b78d133ba9379">viennacl::linalg::opencl::bidiag_pack_svd</a></div><div class="ttdeci">void bidiag_pack_svd(viennacl::matrix< SCALARTYPE > &A, VectorType &dh, VectorType &sh)</div><div class="ttdef"><b>Definition:</b> <a href="opencl_2matrix__operations_8hpp_source.html#l00732">matrix_operations.hpp:732</a></div></div>
<div class="ttc" id="classviennacl_1_1vector_html"><div class="ttname"><a href="classviennacl_1_1vector.html">viennacl::vector</a></div><div class="ttdef"><b>Definition:</b> <a href="forwards_8h_source.html#l00266">forwards.h:266</a></div></div>
<div class="ttc" id="namespaceviennacl_1_1linalg_1_1detail_html_aedc8c34c5978a76a894890bf6d86010f"><div class="ttname"><a href="namespaceviennacl_1_1linalg_1_1detail.html#aedc8c34c5978a76a894890bf6d86010f">viennacl::linalg::detail::bidiag</a></div><div class="ttdeci">void bidiag(viennacl::matrix< SCALARTYPE, row_major, ALIGNMENT > &Ai, viennacl::matrix< SCALARTYPE, row_major, ALIGNMENT > &QL, viennacl::matrix< SCALARTYPE, row_major, ALIGNMENT > &QR)</div><div class="ttdef"><b>Definition:</b> <a href="svd_8hpp_source.html#l00459">svd.hpp:459</a></div></div>
<div class="ttc" id="namespaceviennacl_1_1linalg_1_1detail_html_a0737c94fac817b0d0c8444463be7ceb7"><div class="ttname"><a href="namespaceviennacl_1_1linalg_1_1detail.html#a0737c94fac817b0d0c8444463be7ceb7">viennacl::linalg::detail::pythag</a></div><div class="ttdeci">SCALARTYPE pythag(SCALARTYPE a, SCALARTYPE b)</div><div class="ttdef"><b>Definition:</b> <a href="qr-method-common_8hpp_source.html#l00065">qr-method-common.hpp:65</a></div></div>
<div class="ttc" id="structviennacl_1_1result__of_1_1cpu__value__type_html_aa015d93f419985879a7c13b09633c5c6"><div class="ttname"><a href="structviennacl_1_1result__of_1_1cpu__value__type.html#aa015d93f419985879a7c13b09633c5c6">viennacl::result_of::cpu_value_type::type</a></div><div class="ttdeci">T::ERROR_CANNOT_DEDUCE_CPU_SCALAR_TYPE_FOR_T type</div><div class="ttdef"><b>Definition:</b> <a href="result__of_8hpp_source.html#l00271">result_of.hpp:271</a></div></div>
<div class="ttc" id="classviennacl_1_1matrix__base_html_a24e4f5fa27a1af5ad47e52a97c065d68"><div class="ttname"><a href="classviennacl_1_1matrix__base.html#a24e4f5fa27a1af5ad47e52a97c065d68">viennacl::matrix_base< NumericT >::size1</a></div><div class="ttdeci">size_type size1() const</div><div class="ttdoc">Returns the number of rows. </div><div class="ttdef"><b>Definition:</b> <a href="matrix__def_8hpp_source.html#l00224">matrix_def.hpp:224</a></div></div>
<div class="ttc" id="namespaceviennacl_1_1linalg_1_1detail_html_a76be0f2fd292f0e457e364e20d512e17"><div class="ttname"><a href="namespaceviennacl_1_1linalg_1_1detail.html#a76be0f2fd292f0e457e364e20d512e17">viennacl::linalg::detail::givens_prev</a></div><div class="ttdeci">void givens_prev(MatrixType &matrix, VectorType &tmp1, VectorType &tmp2, int n, int l, int k)</div><div class="ttdef"><b>Definition:</b> <a href="svd_8hpp_source.html#l00048">svd.hpp:48</a></div></div>
<div class="ttc" id="namespaceviennacl_1_1traits_html_a6707f5dab8f482170d2046a605f46ef8"><div class="ttname"><a href="namespaceviennacl_1_1traits.html#a6707f5dab8f482170d2046a605f46ef8">viennacl::traits::context</a></div><div class="ttdeci">viennacl::context context(T const &t)</div><div class="ttdoc">Returns an ID for the currently active memory domain of an object. </div><div class="ttdef"><b>Definition:</b> <a href="traits_2context_8hpp_source.html#l00040">context.hpp:40</a></div></div>
<div class="ttc" id="namespaceviennacl_1_1ocl_html_a5f2022f653ea1cf364d20e3ff84dcada"><div class="ttname"><a href="namespaceviennacl_1_1ocl.html#a5f2022f653ea1cf364d20e3ff84dcada">viennacl::ocl::enqueue</a></div><div class="ttdeci">void enqueue(KernelType &k, viennacl::ocl::command_queue const &queue)</div><div class="ttdoc">Enqueues a kernel in the provided queue. </div><div class="ttdef"><b>Definition:</b> <a href="enqueue_8hpp_source.html#l00050">enqueue.hpp:50</a></div></div>
<div class="ttc" id="namespaceviennacl_1_1linalg_html_a04a5ce1f7230502c9d1ee87dcc24c8b4"><div class="ttname"><a href="namespaceviennacl_1_1linalg.html#a04a5ce1f7230502c9d1ee87dcc24c8b4">viennacl::linalg::SVD_HOUSEHOLDER_UPDATE_QL_KERNEL</a></div><div class="ttdeci">const std::string SVD_HOUSEHOLDER_UPDATE_QL_KERNEL</div><div class="ttdef"><b>Definition:</b> <a href="qr-method-common_8hpp_source.html#l00057">qr-method-common.hpp:57</a></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="fft__1d_8cpp_html_ad5c19ca4f47d3f8ec21232a5af2624e5"><div class="ttname"><a href="fft__1d_8cpp.html#ad5c19ca4f47d3f8ec21232a5af2624e5">ScalarType</a></div><div class="ttdeci">float ScalarType</div><div class="ttdef"><b>Definition:</b> <a href="fft__1d_8cpp_source.html#l00042">fft_1d.cpp:42</a></div></div>
<div class="ttc" id="classviennacl_1_1ocl_1_1kernel_html_a0144c18ae9f07722e5b5697335b7cff5"><div class="ttname"><a href="classviennacl_1_1ocl_1_1kernel.html#a0144c18ae9f07722e5b5697335b7cff5">viennacl::ocl::kernel::global_work_size</a></div><div class="ttdeci">size_type global_work_size(int index=0) const </div><div class="ttdoc">Returns the global work size at the respective dimension. </div><div class="ttdef"><b>Definition:</b> <a href="kernel_8hpp_source.html#l00751">kernel.hpp:751</a></div></div>
<div class="ttc" id="classviennacl_1_1matrix__base_html_a00e30fdc61081a73995b54175a91d220"><div class="ttname"><a href="classviennacl_1_1matrix__base.html#a00e30fdc61081a73995b54175a91d220">viennacl::matrix_base< NumericT >::internal_size2</a></div><div class="ttdeci">size_type internal_size2() const</div><div class="ttdoc">Returns the internal number of columns. Usually required for launching OpenCL kernels only...</div><div class="ttdef"><b>Definition:</b> <a href="matrix__def_8hpp_source.html#l00240">matrix_def.hpp:240</a></div></div>
<div class="ttc" id="namespaceviennacl_1_1linalg_1_1detail_html_a38fd7b41df5895671a4beb943cc35bc3"><div class="ttname"><a href="namespaceviennacl_1_1linalg_1_1detail.html#a38fd7b41df5895671a4beb943cc35bc3">viennacl::linalg::detail::svd_qr_shift</a></div><div class="ttdeci">void svd_qr_shift(MatrixType &vcl_u, MatrixType &vcl_v, CPU_VectorType &q, CPU_VectorType &e)</div><div class="ttdef"><b>Definition:</b> <a href="svd_8hpp_source.html#l00101">svd.hpp:101</a></div></div>
<div class="ttc" id="namespaceviennacl_1_1linalg_1_1detail_html_aef015779a92be597e546c3491cebf6c1"><div class="ttname"><a href="namespaceviennacl_1_1linalg_1_1detail.html#aef015779a92be597e546c3491cebf6c1">viennacl::linalg::detail::min</a></div><div class="ttdeci">T min(const T &lhs, const T &rhs)</div><div class="ttdoc">Minimum. </div><div class="ttdef"><b>Definition:</b> <a href="linalg_2detail_2bisect_2util_8hpp_source.html#l00045">util.hpp:45</a></div></div>
<div class="ttc" id="namespaceviennacl_1_1linalg_html_a15bedacb51ec9b425baf52ee7f68bdba"><div class="ttname"><a href="namespaceviennacl_1_1linalg.html#a15bedacb51ec9b425baf52ee7f68bdba">viennacl::linalg::SVD_GIVENS_PREV_KERNEL</a></div><div class="ttdeci">const std::string SVD_GIVENS_PREV_KERNEL</div><div class="ttdef"><b>Definition:</b> <a href="qr-method-common_8hpp_source.html#l00052">qr-method-common.hpp:52</a></div></div>
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