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<div class="title">nmf_operations.hpp</div> </div>
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<a href="cuda_2nmf__operations_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_CUDA_NMF_OPERATIONS_HPP_</span></div>
<div class="line"><a name="l00002"></a><span class="lineno"> 2</span> <span class="preprocessor">#define VIENNACL_LINALG_CUDA_NMF_OPERATIONS_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="l00025"></a><span class="lineno"> 25</span> <span class="preprocessor">#include "<a class="code" href="host__based_2nmf__operations_8hpp.html">viennacl/linalg/host_based/nmf_operations.hpp</a>"</span></div>
<div class="line"><a name="l00026"></a><span class="lineno"> 26</span> </div>
<div class="line"><a name="l00027"></a><span class="lineno"> 27</span> <span class="preprocessor">#include "<a class="code" href="linalg_2cuda_2common_8hpp.html">viennacl/linalg/cuda/common.hpp</a>"</span></div>
<div class="line"><a name="l00028"></a><span class="lineno"> 28</span> </div>
<div class="line"><a name="l00029"></a><span class="lineno"> 29</span> <span class="keyword">namespace </span>viennacl</div>
<div class="line"><a name="l00030"></a><span class="lineno"> 30</span> {</div>
<div class="line"><a name="l00031"></a><span class="lineno"> 31</span> <span class="keyword">namespace </span>linalg</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="keyword">namespace </span>cuda</div>
<div class="line"><a name="l00034"></a><span class="lineno"> 34</span> {</div>
<div class="line"><a name="l00035"></a><span class="lineno"> 35</span> </div>
<div class="line"><a name="l00037"></a><span class="lineno"> 37</span> <span class="keyword">template</span><<span class="keyword">typename</span> NumericT></div>
<div class="line"><a name="l00038"></a><span class="lineno"><a class="line" href="namespaceviennacl_1_1linalg_1_1cuda.html#a453ec252f6dc75aca7e04d13950ee33b"> 38</a></span> __global__ <span class="keywordtype">void</span> <a class="code" href="namespaceviennacl_1_1linalg_1_1cuda.html#a453ec252f6dc75aca7e04d13950ee33b">el_wise_mul_div</a>(<a class="code" href="tests_2src_2bisect_8cpp.html#a52b5d30a2d7b064678644a3bf49b7f6c">NumericT</a> * matrix1,</div>
<div class="line"><a name="l00039"></a><span class="lineno"> 39</span>  <a class="code" href="tests_2src_2bisect_8cpp.html#a52b5d30a2d7b064678644a3bf49b7f6c">NumericT</a> <span class="keyword">const</span> * matrix2,</div>
<div class="line"><a name="l00040"></a><span class="lineno"> 40</span>  <a class="code" href="tests_2src_2bisect_8cpp.html#a52b5d30a2d7b064678644a3bf49b7f6c">NumericT</a> <span class="keyword">const</span> * matrix3,</div>
<div class="line"><a name="l00041"></a><span class="lineno"> 41</span>  <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> <a class="code" href="namespaceviennacl_1_1traits.html#aa2344ea20469f55fbc15a8e9526494d0">size</a>)</div>
<div class="line"><a name="l00042"></a><span class="lineno"> 42</span> {</div>
<div class="line"><a name="l00043"></a><span class="lineno"> 43</span>  <span class="keywordflow">for</span> (<span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> i = blockIdx.x * blockDim.x + threadIdx.x; i < size; i +=gridDim.x * blockDim.x)</div>
<div class="line"><a name="l00044"></a><span class="lineno"> 44</span>  {</div>
<div class="line"><a name="l00045"></a><span class="lineno"> 45</span>  <a class="code" href="tests_2src_2bisect_8cpp.html#a52b5d30a2d7b064678644a3bf49b7f6c">NumericT</a> val = matrix1[i] * matrix2[i];</div>
<div class="line"><a name="l00046"></a><span class="lineno"> 46</span>  <a class="code" href="tests_2src_2bisect_8cpp.html#a52b5d30a2d7b064678644a3bf49b7f6c">NumericT</a> divisor = matrix3[i];</div>
<div class="line"><a name="l00047"></a><span class="lineno"> 47</span>  matrix1[i] = (divisor > (<a class="code" href="tests_2src_2bisect_8cpp.html#a52b5d30a2d7b064678644a3bf49b7f6c">NumericT</a>) 0.00001) ? (val / divisor) : <a class="code" href="tests_2src_2bisect_8cpp.html#a52b5d30a2d7b064678644a3bf49b7f6c">NumericT</a>(0);</div>
<div class="line"><a name="l00048"></a><span class="lineno"> 48</span>  }</div>
<div class="line"><a name="l00049"></a><span class="lineno"> 49</span> }</div>
<div class="line"><a name="l00050"></a><span class="lineno"> 50</span> </div>
<div class="line"><a name="l00058"></a><span class="lineno"> 58</span> <span class="keyword">template</span><<span class="keyword">typename</span> NumericT></div>
<div class="line"><a name="l00059"></a><span class="lineno"><a class="line" href="namespaceviennacl_1_1linalg_1_1cuda.html#ad9b529eaaf42d91af16200a3def8971c"> 59</a></span> <span class="keywordtype">void</span> <a class="code" href="namespaceviennacl_1_1linalg_1_1cuda.html#ad9b529eaaf42d91af16200a3def8971c">nmf</a>(<a class="code" href="classviennacl_1_1matrix__base.html">viennacl::matrix_base<NumericT></a> <span class="keyword">const</span> & V,</div>
<div class="line"><a name="l00060"></a><span class="lineno"> 60</span>  <a class="code" href="classviennacl_1_1matrix__base.html">viennacl::matrix_base<NumericT></a> & W,</div>
<div class="line"><a name="l00061"></a><span class="lineno"> 61</span>  <a class="code" href="classviennacl_1_1matrix__base.html">viennacl::matrix_base<NumericT></a> & H,</div>
<div class="line"><a name="l00062"></a><span class="lineno"> 62</span>  <a class="code" href="classviennacl_1_1linalg_1_1nmf__config.html">viennacl::linalg::nmf_config</a> <span class="keyword">const</span> & conf)</div>
<div class="line"><a name="l00063"></a><span class="lineno"> 63</span> {</div>
<div class="line"><a name="l00064"></a><span class="lineno"> 64</span>  <a class="code" href="namespaceviennacl.html#a98a0afcc513111ffa0bd138f891930df">vcl_size_t</a> k = W.<a class="code" href="classviennacl_1_1matrix__base.html#a4348766b3b9cb049f7acd6a795272dbe">size2</a>();</div>
<div class="line"><a name="l00065"></a><span class="lineno"> 65</span>  conf.<a class="code" href="classviennacl_1_1linalg_1_1nmf__config.html#a031a7591b5f6de300749037b39ad5db7">iters_</a> = 0;</div>
<div class="line"><a name="l00066"></a><span class="lineno"> 66</span> </div>
<div class="line"><a name="l00067"></a><span class="lineno"> 67</span>  <span class="keywordflow">if</span> (!<a class="code" href="namespaceviennacl_1_1linalg.html#a67813d48ed274df9fc19e6aad99fc761">viennacl::linalg::norm_frobenius</a>(W))</div>
<div class="line"><a name="l00068"></a><span class="lineno"> 68</span>  W = <a class="code" href="classviennacl_1_1scalar__matrix.html">viennacl::scalar_matrix<NumericT></a>(W.<a class="code" href="classviennacl_1_1matrix__base.html#a24e4f5fa27a1af5ad47e52a97c065d68">size1</a>(), W.<a class="code" href="classviennacl_1_1matrix__base.html#a4348766b3b9cb049f7acd6a795272dbe">size2</a>(), <a class="code" href="tests_2src_2bisect_8cpp.html#a52b5d30a2d7b064678644a3bf49b7f6c">NumericT</a>(1.0));</div>
<div class="line"><a name="l00069"></a><span class="lineno"> 69</span> </div>
<div class="line"><a name="l00070"></a><span class="lineno"> 70</span>  <span class="keywordflow">if</span> (!<a class="code" href="namespaceviennacl_1_1linalg.html#a67813d48ed274df9fc19e6aad99fc761">viennacl::linalg::norm_frobenius</a>(H))</div>
<div class="line"><a name="l00071"></a><span class="lineno"> 71</span>  H = <a class="code" href="classviennacl_1_1scalar__matrix.html">viennacl::scalar_matrix<NumericT></a>(H.<a class="code" href="classviennacl_1_1matrix__base.html#a24e4f5fa27a1af5ad47e52a97c065d68">size1</a>(), H.<a class="code" href="classviennacl_1_1matrix__base.html#a4348766b3b9cb049f7acd6a795272dbe">size2</a>(), <a class="code" href="tests_2src_2bisect_8cpp.html#a52b5d30a2d7b064678644a3bf49b7f6c">NumericT</a>(1.0));</div>
<div class="line"><a name="l00072"></a><span class="lineno"> 72</span> </div>
<div class="line"><a name="l00073"></a><span class="lineno"> 73</span>  <a class="code" href="classviennacl_1_1matrix__base.html">viennacl::matrix_base<NumericT></a> wn(V.<a class="code" href="classviennacl_1_1matrix__base.html#a24e4f5fa27a1af5ad47e52a97c065d68">size1</a>(), k, W.<a class="code" href="classviennacl_1_1matrix__base.html#a15ec879f9e85a6fc209454b0bf137084">row_major</a>());</div>
<div class="line"><a name="l00074"></a><span class="lineno"> 74</span>  <a class="code" href="classviennacl_1_1matrix__base.html">viennacl::matrix_base<NumericT></a> wd(V.<a class="code" href="classviennacl_1_1matrix__base.html#a24e4f5fa27a1af5ad47e52a97c065d68">size1</a>(), k, W.<a class="code" href="classviennacl_1_1matrix__base.html#a15ec879f9e85a6fc209454b0bf137084">row_major</a>());</div>
<div class="line"><a name="l00075"></a><span class="lineno"> 75</span>  <a class="code" href="classviennacl_1_1matrix__base.html">viennacl::matrix_base<NumericT></a> wtmp(V.<a class="code" href="classviennacl_1_1matrix__base.html#a24e4f5fa27a1af5ad47e52a97c065d68">size1</a>(), V.<a class="code" href="classviennacl_1_1matrix__base.html#a4348766b3b9cb049f7acd6a795272dbe">size2</a>(), W.<a class="code" href="classviennacl_1_1matrix__base.html#a15ec879f9e85a6fc209454b0bf137084">row_major</a>());</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>  <a class="code" href="classviennacl_1_1matrix__base.html">viennacl::matrix_base<NumericT></a> hn(k, V.<a class="code" href="classviennacl_1_1matrix__base.html#a4348766b3b9cb049f7acd6a795272dbe">size2</a>(), H.<a class="code" href="classviennacl_1_1matrix__base.html#a15ec879f9e85a6fc209454b0bf137084">row_major</a>());</div>
<div class="line"><a name="l00078"></a><span class="lineno"> 78</span>  <a class="code" href="classviennacl_1_1matrix__base.html">viennacl::matrix_base<NumericT></a> hd(k, V.<a class="code" href="classviennacl_1_1matrix__base.html#a4348766b3b9cb049f7acd6a795272dbe">size2</a>(), H.<a class="code" href="classviennacl_1_1matrix__base.html#a15ec879f9e85a6fc209454b0bf137084">row_major</a>());</div>
<div class="line"><a name="l00079"></a><span class="lineno"> 79</span>  <a class="code" href="classviennacl_1_1matrix__base.html">viennacl::matrix_base<NumericT></a> htmp(k, k, H.<a class="code" href="classviennacl_1_1matrix__base.html#a15ec879f9e85a6fc209454b0bf137084">row_major</a>());</div>
<div class="line"><a name="l00080"></a><span class="lineno"> 80</span> </div>
<div class="line"><a name="l00081"></a><span class="lineno"> 81</span>  <a class="code" href="classviennacl_1_1matrix__base.html">viennacl::matrix_base<NumericT></a> appr(V.<a class="code" href="classviennacl_1_1matrix__base.html#a24e4f5fa27a1af5ad47e52a97c065d68">size1</a>(), V.<a class="code" href="classviennacl_1_1matrix__base.html#a4348766b3b9cb049f7acd6a795272dbe">size2</a>(), V.<a class="code" href="classviennacl_1_1matrix__base.html#a15ec879f9e85a6fc209454b0bf137084">row_major</a>());</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_1vector.html">viennacl::vector<NumericT></a> <a class="code" href="blas3__solve_8cpp.html#afebc249681af56fdd45860b32ed34b4e">diff</a>(V.<a class="code" href="classviennacl_1_1matrix__base.html#a24e4f5fa27a1af5ad47e52a97c065d68">size1</a>() * V.<a class="code" href="classviennacl_1_1matrix__base.html#a4348766b3b9cb049f7acd6a795272dbe">size2</a>());</div>
<div class="line"><a name="l00084"></a><span class="lineno"> 84</span> </div>
<div class="line"><a name="l00085"></a><span class="lineno"> 85</span>  <a class="code" href="tests_2src_2bisect_8cpp.html#a52b5d30a2d7b064678644a3bf49b7f6c">NumericT</a> last_diff = 0;</div>
<div class="line"><a name="l00086"></a><span class="lineno"> 86</span>  <a class="code" href="tests_2src_2bisect_8cpp.html#a52b5d30a2d7b064678644a3bf49b7f6c">NumericT</a> diff_init = 0;</div>
<div class="line"><a name="l00087"></a><span class="lineno"> 87</span>  <span class="keywordtype">bool</span> stagnation_flag = <span class="keyword">false</span>;</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>  <span class="keywordflow">for</span> (<a class="code" href="namespaceviennacl.html#a98a0afcc513111ffa0bd138f891930df">vcl_size_t</a> i = 0; i < conf.<a class="code" href="classviennacl_1_1linalg_1_1nmf__config.html#a494899ccb2fed620eb7fb69da5fc46c0">max_iterations</a>(); i++)</div>
<div class="line"><a name="l00090"></a><span class="lineno"> 90</span>  {</div>
<div class="line"><a name="l00091"></a><span class="lineno"> 91</span>  conf.<a class="code" href="classviennacl_1_1linalg_1_1nmf__config.html#a031a7591b5f6de300749037b39ad5db7">iters_</a> = i + 1;</div>
<div class="line"><a name="l00092"></a><span class="lineno"> 92</span> </div>
<div class="line"><a name="l00093"></a><span class="lineno"> 93</span>  hn = <a class="code" href="namespaceviennacl_1_1linalg.html#aa18d10f8a90e38bd9ff43c650fc670ef">viennacl::linalg::prod</a>(<a class="code" href="namespaceviennacl_1_1linalg_1_1cuda.html#a99fff33c3afdc3c6b49816f86357c084">trans</a>(W), V);</div>
<div class="line"><a name="l00094"></a><span class="lineno"> 94</span>  htmp = <a class="code" href="namespaceviennacl_1_1linalg.html#aa18d10f8a90e38bd9ff43c650fc670ef">viennacl::linalg::prod</a>(<a class="code" href="namespaceviennacl_1_1linalg_1_1cuda.html#a99fff33c3afdc3c6b49816f86357c084">trans</a>(W), W);</div>
<div class="line"><a name="l00095"></a><span class="lineno"> 95</span>  hd = <a class="code" href="namespaceviennacl_1_1linalg.html#aa18d10f8a90e38bd9ff43c650fc670ef">viennacl::linalg::prod</a>(htmp, H);</div>
<div class="line"><a name="l00096"></a><span class="lineno"> 96</span> </div>
<div class="line"><a name="l00097"></a><span class="lineno"> 97</span>  el_wise_mul_div<<<128, 128>>>(viennacl::cuda_arg<NumericT>(H),</div>
<div class="line"><a name="l00098"></a><span class="lineno"> 98</span>  viennacl::cuda_arg<NumericT>(hn),</div>
<div class="line"><a name="l00099"></a><span class="lineno"> 99</span>  viennacl::cuda_arg<NumericT>(hd),</div>
<div class="line"><a name="l00100"></a><span class="lineno"> 100</span>  static_cast<unsigned int>(H.<a class="code" href="classviennacl_1_1matrix__base.html#a82018b4e169973bdfb9d3be68ceb5be0">internal_size1</a>() * H.<a class="code" href="classviennacl_1_1matrix__base.html#a00e30fdc61081a73995b54175a91d220">internal_size2</a>()));</div>
<div class="line"><a name="l00101"></a><span class="lineno"> 101</span>  <a class="code" href="linalg_2cuda_2common_8hpp.html#acdb31f22f4d1e12f1c2a27d4c4aa6865">VIENNACL_CUDA_LAST_ERROR_CHECK</a>(<span class="stringliteral">"el_wise_mul_div"</span>);</div>
<div class="line"><a name="l00102"></a><span class="lineno"> 102</span> </div>
<div class="line"><a name="l00103"></a><span class="lineno"> 103</span>  wn = <a class="code" href="namespaceviennacl_1_1linalg.html#aa18d10f8a90e38bd9ff43c650fc670ef">viennacl::linalg::prod</a>(V, <a class="code" href="namespaceviennacl_1_1linalg_1_1cuda.html#a99fff33c3afdc3c6b49816f86357c084">trans</a>(H));</div>
<div class="line"><a name="l00104"></a><span class="lineno"> 104</span>  wtmp = <a class="code" href="namespaceviennacl_1_1linalg.html#aa18d10f8a90e38bd9ff43c650fc670ef">viennacl::linalg::prod</a>(W, H);</div>
<div class="line"><a name="l00105"></a><span class="lineno"> 105</span>  wd = <a class="code" href="namespaceviennacl_1_1linalg.html#aa18d10f8a90e38bd9ff43c650fc670ef">viennacl::linalg::prod</a>(wtmp, <a class="code" href="namespaceviennacl_1_1linalg_1_1cuda.html#a99fff33c3afdc3c6b49816f86357c084">trans</a>(H));</div>
<div class="line"><a name="l00106"></a><span class="lineno"> 106</span> </div>
<div class="line"><a name="l00107"></a><span class="lineno"> 107</span>  el_wise_mul_div<<<128, 128>>>(viennacl::cuda_arg<NumericT>(W),</div>
<div class="line"><a name="l00108"></a><span class="lineno"> 108</span>  viennacl::cuda_arg<NumericT>(wn),</div>
<div class="line"><a name="l00109"></a><span class="lineno"> 109</span>  viennacl::cuda_arg<NumericT>(wd),</div>
<div class="line"><a name="l00110"></a><span class="lineno"> 110</span>  static_cast<unsigned int>( W.<a class="code" href="classviennacl_1_1matrix__base.html#a82018b4e169973bdfb9d3be68ceb5be0">internal_size1</a>() * W.<a class="code" href="classviennacl_1_1matrix__base.html#a00e30fdc61081a73995b54175a91d220">internal_size2</a>()));</div>
<div class="line"><a name="l00111"></a><span class="lineno"> 111</span>  <a class="code" href="linalg_2cuda_2common_8hpp.html#acdb31f22f4d1e12f1c2a27d4c4aa6865">VIENNACL_CUDA_LAST_ERROR_CHECK</a>(<span class="stringliteral">"el_wise_mul_div"</span>);</div>
<div class="line"><a name="l00112"></a><span class="lineno"> 112</span> </div>
<div class="line"><a name="l00113"></a><span class="lineno"> 113</span>  <span class="keywordflow">if</span> (i % conf.<a class="code" href="classviennacl_1_1linalg_1_1nmf__config.html#a875e5f082abe21568f75b36cc7b590b2">check_after_steps</a>() == 0) <span class="comment">//check for convergence</span></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>  appr = <a class="code" href="namespaceviennacl_1_1linalg.html#aa18d10f8a90e38bd9ff43c650fc670ef">viennacl::linalg::prod</a>(W, H);</div>
<div class="line"><a name="l00116"></a><span class="lineno"> 116</span> </div>
<div class="line"><a name="l00117"></a><span class="lineno"> 117</span>  appr -= V;</div>
<div class="line"><a name="l00118"></a><span class="lineno"> 118</span>  <a class="code" href="tests_2src_2bisect_8cpp.html#a52b5d30a2d7b064678644a3bf49b7f6c">NumericT</a> diff_val = <a class="code" href="namespaceviennacl_1_1linalg.html#a67813d48ed274df9fc19e6aad99fc761">viennacl::linalg::norm_frobenius</a>(appr);</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="keywordflow">if</span> (i == 0)</div>
<div class="line"><a name="l00121"></a><span class="lineno"> 121</span>  diff_init = diff_val;</div>
<div class="line"><a name="l00122"></a><span class="lineno"> 122</span> </div>
<div class="line"><a name="l00123"></a><span class="lineno"> 123</span>  <span class="keywordflow">if</span> (conf.<a class="code" href="classviennacl_1_1linalg_1_1nmf__config.html#ab948223929be79e20a1050146210ec6d">print_relative_error</a>())</div>
<div class="line"><a name="l00124"></a><span class="lineno"> 124</span>  std::cout << diff_val / diff_init << std::endl;</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>  <span class="comment">// Approximation check</span></div>
<div class="line"><a name="l00127"></a><span class="lineno"> 127</span>  <span class="keywordflow">if</span> (diff_val / diff_init < conf.<a class="code" href="classviennacl_1_1linalg_1_1nmf__config.html#a36fe78d7d2e80e41e4e7546f01511840">tolerance</a>())</div>
<div class="line"><a name="l00128"></a><span class="lineno"> 128</span>  <span class="keywordflow">break</span>;</div>
<div class="line"><a name="l00129"></a><span class="lineno"> 129</span> </div>
<div class="line"><a name="l00130"></a><span class="lineno"> 130</span>  <span class="comment">// Stagnation check</span></div>
<div class="line"><a name="l00131"></a><span class="lineno"> 131</span>  <span class="keywordflow">if</span> (std::fabs(diff_val - last_diff) / (diff_val * conf.<a class="code" href="classviennacl_1_1linalg_1_1nmf__config.html#a875e5f082abe21568f75b36cc7b590b2">check_after_steps</a>()) < conf.<a class="code" href="classviennacl_1_1linalg_1_1nmf__config.html#a992720e64934be9f6e0e940ee5bbdfca">stagnation_tolerance</a>()) <span class="comment">//avoid situations where convergence stagnates</span></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>  <span class="keywordflow">if</span> (stagnation_flag) <span class="comment">// iteration stagnates (two iterates with no notable progress)</span></div>
<div class="line"><a name="l00134"></a><span class="lineno"> 134</span>  <span class="keywordflow">break</span>;</div>
<div class="line"><a name="l00135"></a><span class="lineno"> 135</span>  <span class="keywordflow">else</span></div>
<div class="line"><a name="l00136"></a><span class="lineno"> 136</span>  <span class="comment">// record stagnation in this iteration</span></div>
<div class="line"><a name="l00137"></a><span class="lineno"> 137</span>  stagnation_flag = <span class="keyword">true</span>;</div>
<div class="line"><a name="l00138"></a><span class="lineno"> 138</span>  } <span class="keywordflow">else</span></div>
<div class="line"><a name="l00139"></a><span class="lineno"> 139</span>  <span class="comment">// good progress in this iteration, so unset stagnation flag</span></div>
<div class="line"><a name="l00140"></a><span class="lineno"> 140</span>  stagnation_flag = <span class="keyword">false</span>;</div>
<div class="line"><a name="l00141"></a><span class="lineno"> 141</span> </div>
<div class="line"><a name="l00142"></a><span class="lineno"> 142</span>  <span class="comment">// prepare for next iterate:</span></div>
<div class="line"><a name="l00143"></a><span class="lineno"> 143</span>  last_diff = diff_val;</div>
<div class="line"><a name="l00144"></a><span class="lineno"> 144</span>  }</div>
<div class="line"><a name="l00145"></a><span class="lineno"> 145</span>  }</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="comment">//namespace cuda</span></div>
<div class="line"><a name="l00149"></a><span class="lineno"> 149</span> } <span class="comment">//namespace linalg</span></div>
<div class="line"><a name="l00150"></a><span class="lineno"> 150</span> } <span class="comment">//namespace viennacl</span></div>
<div class="line"><a name="l00151"></a><span class="lineno"> 151</span> </div>
<div class="line"><a name="l00152"></a><span class="lineno"> 152</span> <span class="preprocessor">#endif </span><span class="comment">/* VIENNACL_LINALG_CUDA_NMF_OPERATIONS_HPP_ */</span><span class="preprocessor"></span></div>
<div class="ttc" id="namespaceviennacl_1_1linalg_1_1cuda_html_ad9b529eaaf42d91af16200a3def8971c"><div class="ttname"><a href="namespaceviennacl_1_1linalg_1_1cuda.html#ad9b529eaaf42d91af16200a3def8971c">viennacl::linalg::cuda::nmf</a></div><div class="ttdeci">void nmf(viennacl::matrix_base< NumericT > const &V, viennacl::matrix_base< NumericT > &W, viennacl::matrix_base< NumericT > &H, viennacl::linalg::nmf_config const &conf)</div><div class="ttdoc">The nonnegative matrix factorization (approximation) algorithm as suggested by Lee and Seung...</div><div class="ttdef"><b>Definition:</b> <a href="cuda_2nmf__operations_8hpp_source.html#l00059">nmf_operations.hpp:59</a></div></div>
<div class="ttc" id="namespaceviennacl_1_1linalg_1_1cuda_html_a99fff33c3afdc3c6b49816f86357c084"><div class="ttname"><a href="namespaceviennacl_1_1linalg_1_1cuda.html#a99fff33c3afdc3c6b49816f86357c084">viennacl::linalg::cuda::trans</a></div><div class="ttdeci">void trans(matrix_expression< const matrix_base< NumericT, SizeT, DistanceT >, const matrix_base< NumericT, SizeT, DistanceT >, op_trans > const &proxy, matrix_base< NumericT > &temp_trans)</div><div class="ttdef"><b>Definition:</b> <a href="cuda_2matrix__operations_8hpp_source.html#l00094">matrix_operations.hpp:94</a></div></div>
<div class="ttc" id="host__based_2nmf__operations_8hpp_html"><div class="ttname"><a href="host__based_2nmf__operations_8hpp.html">nmf_operations.hpp</a></div></div>
<div class="ttc" id="classviennacl_1_1linalg_1_1nmf__config_html_a875e5f082abe21568f75b36cc7b590b2"><div class="ttname"><a href="classviennacl_1_1linalg_1_1nmf__config.html#a875e5f082abe21568f75b36cc7b590b2">viennacl::linalg::nmf_config::check_after_steps</a></div><div class="ttdeci">vcl_size_t check_after_steps() const </div><div class="ttdoc">Number of steps after which the convergence of NMF should be checked (again) </div><div class="ttdef"><b>Definition:</b> <a href="host__based_2nmf__operations_8hpp_source.html#l00091">nmf_operations.hpp:91</a></div></div>
<div class="ttc" id="classviennacl_1_1matrix__base_html"><div class="ttname"><a href="classviennacl_1_1matrix__base.html">viennacl::matrix_base< NumericT ></a></div></div>
<div class="ttc" id="classviennacl_1_1linalg_1_1nmf__config_html"><div class="ttname"><a href="classviennacl_1_1linalg_1_1nmf__config.html">viennacl::linalg::nmf_config</a></div><div class="ttdoc">Configuration class for the nonnegative-matrix-factorization algorithm. Specify tolerances, maximum iteration counts, etc., here. </div><div class="ttdef"><b>Definition:</b> <a href="host__based_2nmf__operations_8hpp_source.html#l00039">nmf_operations.hpp:39</a></div></div>
<div class="ttc" id="tests_2src_2bisect_8cpp_html_a52b5d30a2d7b064678644a3bf49b7f6c"><div class="ttname"><a href="tests_2src_2bisect_8cpp.html#a52b5d30a2d7b064678644a3bf49b7f6c">NumericT</a></div><div class="ttdeci">float NumericT</div><div class="ttdef"><b>Definition:</b> <a href="tests_2src_2bisect_8cpp_source.html#l00040">bisect.cpp:40</a></div></div>
<div class="ttc" id="classviennacl_1_1linalg_1_1nmf__config_html_a031a7591b5f6de300749037b39ad5db7"><div class="ttname"><a href="classviennacl_1_1linalg_1_1nmf__config.html#a031a7591b5f6de300749037b39ad5db7">viennacl::linalg::nmf_config::iters_</a></div><div class="ttdeci">vcl_size_t iters_</div><div class="ttdef"><b>Definition:</b> <a href="host__based_2nmf__operations_8hpp_source.html#l00125">nmf_operations.hpp:125</a></div></div>
<div class="ttc" id="namespaceviennacl_1_1linalg_html_aa18d10f8a90e38bd9ff43c650fc670ef"><div class="ttname"><a href="namespaceviennacl_1_1linalg.html#aa18d10f8a90e38bd9ff43c650fc670ef">viennacl::linalg::prod</a></div><div class="ttdeci">VectorT prod(std::vector< std::vector< T, A1 >, A2 > const &matrix, VectorT const &vector)</div><div class="ttdef"><b>Definition:</b> <a href="prod_8hpp_source.html#l00102">prod.hpp:102</a></div></div>
<div class="ttc" id="namespaceviennacl_1_1traits_html_aa2344ea20469f55fbc15a8e9526494d0"><div class="ttname"><a href="namespaceviennacl_1_1traits.html#aa2344ea20469f55fbc15a8e9526494d0">viennacl::traits::size</a></div><div class="ttdeci">vcl_size_t size(VectorType const &vec)</div><div class="ttdoc">Generic routine for obtaining the size of a vector (ViennaCL, uBLAS, etc.) </div><div class="ttdef"><b>Definition:</b> <a href="size_8hpp_source.html#l00239">size.hpp:239</a></div></div>
<div class="ttc" id="namespaceviennacl_1_1linalg_1_1cuda_html_a453ec252f6dc75aca7e04d13950ee33b"><div class="ttname"><a href="namespaceviennacl_1_1linalg_1_1cuda.html#a453ec252f6dc75aca7e04d13950ee33b">viennacl::linalg::cuda::el_wise_mul_div</a></div><div class="ttdeci">__global__ void el_wise_mul_div(NumericT *matrix1, NumericT const *matrix2, NumericT const *matrix3, unsigned int size)</div><div class="ttdoc">Main CUDA kernel for nonnegative matrix factorization of a dense matrices. </div><div class="ttdef"><b>Definition:</b> <a href="cuda_2nmf__operations_8hpp_source.html#l00038">nmf_operations.hpp:38</a></div></div>
<div class="ttc" id="classviennacl_1_1linalg_1_1nmf__config_html_a494899ccb2fed620eb7fb69da5fc46c0"><div class="ttname"><a href="classviennacl_1_1linalg_1_1nmf__config.html#a494899ccb2fed620eb7fb69da5fc46c0">viennacl::linalg::nmf_config::max_iterations</a></div><div class="ttdeci">vcl_size_t max_iterations() const </div><div class="ttdoc">Returns the maximum number of iterations for the NMF algorithm. </div><div class="ttdef"><b>Definition:</b> <a href="host__based_2nmf__operations_8hpp_source.html#l00074">nmf_operations.hpp:74</a></div></div>
<div class="ttc" id="classviennacl_1_1scalar__matrix_html"><div class="ttname"><a href="classviennacl_1_1scalar__matrix.html">viennacl::scalar_matrix</a></div><div class="ttdoc">Represents a vector consisting of scalars 's' only, i.e. v[i] = s for all i. To be used as an initial...</div><div class="ttdef"><b>Definition:</b> <a href="matrix__def_8hpp_source.html#l00093">matrix_def.hpp:93</a></div></div>
<div class="ttc" id="classviennacl_1_1linalg_1_1nmf__config_html_a36fe78d7d2e80e41e4e7546f01511840"><div class="ttname"><a href="classviennacl_1_1linalg_1_1nmf__config.html#a36fe78d7d2e80e41e4e7546f01511840">viennacl::linalg::nmf_config::tolerance</a></div><div class="ttdeci">double tolerance() const </div><div class="ttdoc">Returns the relative tolerance for convergence. </div><div class="ttdef"><b>Definition:</b> <a href="host__based_2nmf__operations_8hpp_source.html#l00050">nmf_operations.hpp:50</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::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="classviennacl_1_1vector_html"><div class="ttname"><a href="classviennacl_1_1vector.html">viennacl::vector< NumericT ></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::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="classviennacl_1_1linalg_1_1nmf__config_html_a992720e64934be9f6e0e940ee5bbdfca"><div class="ttname"><a href="classviennacl_1_1linalg_1_1nmf__config.html#a992720e64934be9f6e0e940ee5bbdfca">viennacl::linalg::nmf_config::stagnation_tolerance</a></div><div class="ttdeci">double stagnation_tolerance() const </div><div class="ttdoc">Relative tolerance for the stagnation check. </div><div class="ttdef"><b>Definition:</b> <a href="host__based_2nmf__operations_8hpp_source.html#l00062">nmf_operations.hpp:62</a></div></div>
<div class="ttc" id="linalg_2cuda_2common_8hpp_html"><div class="ttname"><a href="linalg_2cuda_2common_8hpp.html">common.hpp</a></div><div class="ttdoc">Common routines for CUDA execution. </div></div>
<div class="ttc" id="classviennacl_1_1matrix__base_html_a15ec879f9e85a6fc209454b0bf137084"><div class="ttname"><a href="classviennacl_1_1matrix__base.html#a15ec879f9e85a6fc209454b0bf137084">viennacl::matrix_base::row_major</a></div><div class="ttdeci">bool row_major() const </div><div class="ttdef"><b>Definition:</b> <a href="matrix__def_8hpp_source.html#l00248">matrix_def.hpp:248</a></div></div>
<div class="ttc" id="namespaceviennacl_1_1linalg_html_a67813d48ed274df9fc19e6aad99fc761"><div class="ttname"><a href="namespaceviennacl_1_1linalg.html#a67813d48ed274df9fc19e6aad99fc761">viennacl::linalg::norm_frobenius</a></div><div class="ttdeci">scalar_expression< const matrix_base< NumericT >, const matrix_base< NumericT >, op_norm_frobenius > norm_frobenius(const matrix_base< NumericT > &A)</div><div class="ttdef"><b>Definition:</b> <a href="norm__frobenius_8hpp_source.html#l00061">norm_frobenius.hpp:61</a></div></div>
<div class="ttc" id="linalg_2cuda_2common_8hpp_html_acdb31f22f4d1e12f1c2a27d4c4aa6865"><div class="ttname"><a href="linalg_2cuda_2common_8hpp.html#acdb31f22f4d1e12f1c2a27d4c4aa6865">VIENNACL_CUDA_LAST_ERROR_CHECK</a></div><div class="ttdeci">#define VIENNACL_CUDA_LAST_ERROR_CHECK(message)</div><div class="ttdef"><b>Definition:</b> <a href="linalg_2cuda_2common_8hpp_source.html#l00030">common.hpp:30</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::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="classviennacl_1_1matrix__base_html_a82018b4e169973bdfb9d3be68ceb5be0"><div class="ttname"><a href="classviennacl_1_1matrix__base.html#a82018b4e169973bdfb9d3be68ceb5be0">viennacl::matrix_base::internal_size1</a></div><div class="ttdeci">size_type internal_size1() const </div><div class="ttdoc">Returns the internal number of rows. Usually required for launching OpenCL kernels only...</div><div class="ttdef"><b>Definition:</b> <a href="matrix__def_8hpp_source.html#l00238">matrix_def.hpp:238</a></div></div>
<div class="ttc" id="blas3__solve_8cpp_html_afebc249681af56fdd45860b32ed34b4e"><div class="ttname"><a href="blas3__solve_8cpp.html#afebc249681af56fdd45860b32ed34b4e">diff</a></div><div class="ttdeci">ScalarType diff(ScalarType &s1, viennacl::scalar< ScalarType > &s2)</div><div class="ttdef"><b>Definition:</b> <a href="blas3__solve_8cpp_source.html#l00050">blas3_solve.cpp:50</a></div></div>
<div class="ttc" id="classviennacl_1_1linalg_1_1nmf__config_html_ab948223929be79e20a1050146210ec6d"><div class="ttname"><a href="classviennacl_1_1linalg_1_1nmf__config.html#ab948223929be79e20a1050146210ec6d">viennacl::linalg::nmf_config::print_relative_error</a></div><div class="ttdeci">bool print_relative_error() const </div><div class="ttdoc">Returns the flag specifying whether the relative tolerance should be printed in each iteration...</div><div class="ttdef"><b>Definition:</b> <a href="host__based_2nmf__operations_8hpp_source.html#l00103">nmf_operations.hpp:103</a></div></div>
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