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<div class="title">amg_operations.hpp</div> </div>
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<a href="cuda_2amg__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_AMG_OPERATIONS_HPP</span></div>
<div class="line"><a name="l00002"></a><span class="lineno"> 2</span> <span class="preprocessor">#define VIENNACL_LINALG_CUDA_AMG_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 PDF 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 <cstdlib></span></div>
<div class="line"><a name="l00026"></a><span class="lineno"> 26</span> <span class="preprocessor">#include <cmath></span></div>
<div class="line"><a name="l00027"></a><span class="lineno"> 27</span> <span class="preprocessor">#include "<a class="code" href="amg__base_8hpp.html">viennacl/linalg/detail/amg/amg_base.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="preprocessor">#include <map></span></div>
<div class="line"><a name="l00030"></a><span class="lineno"> 30</span> <span class="preprocessor">#include <set></span></div>
<div class="line"><a name="l00031"></a><span class="lineno"> 31</span> </div>
<div class="line"><a name="l00032"></a><span class="lineno"> 32</span> <span class="keyword">namespace </span>viennacl</div>
<div class="line"><a name="l00033"></a><span class="lineno"> 33</span> {</div>
<div class="line"><a name="l00034"></a><span class="lineno"> 34</span> <span class="keyword">namespace </span>linalg</div>
<div class="line"><a name="l00035"></a><span class="lineno"> 35</span> {</div>
<div class="line"><a name="l00036"></a><span class="lineno"> 36</span> <span class="keyword">namespace </span>cuda</div>
<div class="line"><a name="l00037"></a><span class="lineno"> 37</span> {</div>
<div class="line"><a name="l00038"></a><span class="lineno"><a class="line" href="namespaceviennacl_1_1linalg_1_1cuda_1_1amg.html"> 38</a></span> <span class="keyword">namespace </span>amg</div>
<div class="line"><a name="l00039"></a><span class="lineno"> 39</span> {</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> </div>
<div class="line"><a name="l00043"></a><span class="lineno"> 43</span> </div>
<div class="line"><a name="l00044"></a><span class="lineno"><a class="line" href="namespaceviennacl_1_1linalg_1_1cuda_1_1amg.html#a2d8aec3a05feaaff512af0bcf5e94ccd"> 44</a></span> __global__ <span class="keywordtype">void</span> <a class="code" href="namespaceviennacl_1_1linalg_1_1cuda_1_1amg.html#a2d8aec3a05feaaff512af0bcf5e94ccd">amg_influence_trivial_kernel</a>(</div>
<div class="line"><a name="l00045"></a><span class="lineno"> 45</span>  <span class="keyword">const</span> <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> * row_indices,</div>
<div class="line"><a name="l00046"></a><span class="lineno"> 46</span>  <span class="keyword">const</span> <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> * column_indices,</div>
<div class="line"><a name="l00047"></a><span class="lineno"> 47</span>  <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> <a class="code" href="namespaceviennacl_1_1traits.html#aa756f5d6820722094cae0d8b9bb6d5e2">size1</a>,</div>
<div class="line"><a name="l00048"></a><span class="lineno"> 48</span>  <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> nnz,</div>
<div class="line"><a name="l00049"></a><span class="lineno"> 49</span>  <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> *influences_row,</div>
<div class="line"><a name="l00050"></a><span class="lineno"> 50</span>  <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> *influences_id,</div>
<div class="line"><a name="l00051"></a><span class="lineno"> 51</span>  <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> *influences_values</div>
<div class="line"><a name="l00052"></a><span class="lineno"> 52</span>  )</div>
<div class="line"><a name="l00053"></a><span class="lineno"> 53</span> {</div>
<div class="line"><a name="l00054"></a><span class="lineno"> 54</span>  <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> global_id = blockDim.x * blockIdx.x + threadIdx.x;</div>
<div class="line"><a name="l00055"></a><span class="lineno"> 55</span>  <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> global_size = gridDim.x * blockDim.x;</div>
<div class="line"><a name="l00056"></a><span class="lineno"> 56</span> </div>
<div class="line"><a name="l00057"></a><span class="lineno"> 57</span>  <span class="keywordflow">for</span> (<span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> i = global_id; i < <a class="code" href="namespaceviennacl_1_1traits.html#aa756f5d6820722094cae0d8b9bb6d5e2">size1</a>; i += global_size)</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>  <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> tmp = row_indices[i];</div>
<div class="line"><a name="l00060"></a><span class="lineno"> 60</span>  influences_row[i] = tmp;</div>
<div class="line"><a name="l00061"></a><span class="lineno"> 61</span>  influences_values[i] = row_indices[i+1] - tmp;</div>
<div class="line"><a name="l00062"></a><span class="lineno"> 62</span>  }</div>
<div class="line"><a name="l00063"></a><span class="lineno"> 63</span> </div>
<div class="line"><a name="l00064"></a><span class="lineno"> 64</span>  <span class="keywordflow">for</span> (<span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> i = global_id; i < nnz; i += global_size)</div>
<div class="line"><a name="l00065"></a><span class="lineno"> 65</span>  influences_id[i] = column_indices[i];</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> (global_id == 0)</div>
<div class="line"><a name="l00068"></a><span class="lineno"> 68</span>  influences_row[<a class="code" href="namespaceviennacl_1_1traits.html#aa756f5d6820722094cae0d8b9bb6d5e2">size1</a>] = row_indices[<a class="code" href="namespaceviennacl_1_1traits.html#aa756f5d6820722094cae0d8b9bb6d5e2">size1</a>];</div>
<div class="line"><a name="l00069"></a><span class="lineno"> 69</span> }</div>
<div class="line"><a name="l00070"></a><span class="lineno"> 70</span> </div>
<div class="line"><a name="l00071"></a><span class="lineno"> 71</span> </div>
<div class="line"><a name="l00073"></a><span class="lineno"> 73</span> <span class="keyword">template</span><<span class="keyword">typename</span> NumericT></div>
<div class="line"><a name="l00074"></a><span class="lineno"><a class="line" href="namespaceviennacl_1_1linalg_1_1cuda_1_1amg.html#ac1b1f9a0666d83c46ee9b4c5e25cd2c6"> 74</a></span> <span class="keywordtype">void</span> <a class="code" href="namespaceviennacl_1_1linalg_1_1cuda_1_1amg.html#ac1b1f9a0666d83c46ee9b4c5e25cd2c6">amg_influence_trivial</a>(<a class="code" href="classviennacl_1_1compressed__matrix.html">compressed_matrix<NumericT></a> <span class="keyword">const</span> & A,</div>
<div class="line"><a name="l00075"></a><span class="lineno"> 75</span>  <a class="code" href="structviennacl_1_1linalg_1_1detail_1_1amg_1_1amg__level__context.html">viennacl::linalg::detail::amg::amg_level_context</a> & amg_context,</div>
<div class="line"><a name="l00076"></a><span class="lineno"> 76</span>  <a class="code" href="classviennacl_1_1linalg_1_1amg__tag.html">viennacl::linalg::amg_tag</a> & tag)</div>
<div class="line"><a name="l00077"></a><span class="lineno"> 77</span> {</div>
<div class="line"><a name="l00078"></a><span class="lineno"> 78</span>  (void)tag;</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>  amg_influence_trivial_kernel<<<128, 128>>>(viennacl::cuda_arg<unsigned int>(A.<a class="code" href="classviennacl_1_1compressed__matrix.html#af71dec61a70e8df4f78a527aa989a106">handle1</a>().cuda_handle()),</div>
<div class="line"><a name="l00081"></a><span class="lineno"> 81</span>  viennacl::cuda_arg<unsigned int>(A.<a class="code" href="classviennacl_1_1compressed__matrix.html#a91f5145351151a66f916bdc3901206f2">handle2</a>().cuda_handle()),</div>
<div class="line"><a name="l00082"></a><span class="lineno"> 82</span>  static_cast<unsigned int>(A.<a class="code" href="classviennacl_1_1compressed__matrix.html#a463cf1739f9cdd387aa185cb574db183">size1</a>()),</div>
<div class="line"><a name="l00083"></a><span class="lineno"> 83</span>  static_cast<unsigned int>(A.<a class="code" href="classviennacl_1_1compressed__matrix.html#ae69ca21ded644fdd0c7a5168011b13ed">nnz</a>()),</div>
<div class="line"><a name="l00084"></a><span class="lineno"> 84</span>  <a class="code" href="namespaceviennacl.html#ae7d5db0c2c91be75218db5b52c4d13da">viennacl::cuda_arg</a>(amg_context.<a class="code" href="structviennacl_1_1linalg_1_1detail_1_1amg_1_1amg__level__context.html#ad537babcb184069cc920bfb2140860de">influence_jumper_</a>),</div>
<div class="line"><a name="l00085"></a><span class="lineno"> 85</span>  <a class="code" href="namespaceviennacl.html#ae7d5db0c2c91be75218db5b52c4d13da">viennacl::cuda_arg</a>(amg_context.<a class="code" href="structviennacl_1_1linalg_1_1detail_1_1amg_1_1amg__level__context.html#a262b6f406db2b16b53936b8759f83d05">influence_ids_</a>),</div>
<div class="line"><a name="l00086"></a><span class="lineno"> 86</span>  <a class="code" href="namespaceviennacl.html#ae7d5db0c2c91be75218db5b52c4d13da">viennacl::cuda_arg</a>(amg_context.<a class="code" href="structviennacl_1_1linalg_1_1detail_1_1amg_1_1amg__level__context.html#a757fe2a72ed0d9eb3649ecda1c83129e">influence_values_</a>)</div>
<div class="line"><a name="l00087"></a><span class="lineno"> 87</span>  );</div>
<div class="line"><a name="l00088"></a><span class="lineno"> 88</span>  <a class="code" href="linalg_2cuda_2common_8hpp.html#acdb31f22f4d1e12f1c2a27d4c4aa6865">VIENNACL_CUDA_LAST_ERROR_CHECK</a>(<span class="stringliteral">"amg_influence_trivial_kernel"</span>);</div>
<div class="line"><a name="l00089"></a><span class="lineno"> 89</span> }</div>
<div class="line"><a name="l00090"></a><span class="lineno"> 90</span> </div>
<div class="line"><a name="l00091"></a><span class="lineno"> 91</span> </div>
<div class="line"><a name="l00093"></a><span class="lineno"> 93</span> <span class="keyword">template</span><<span class="keyword">typename</span> NumericT></div>
<div class="line"><a name="l00094"></a><span class="lineno"><a class="line" href="namespaceviennacl_1_1linalg_1_1cuda_1_1amg.html#ad251eca20f99e452229d76237d791a0e"> 94</a></span> <span class="keywordtype">void</span> <a class="code" href="namespaceviennacl_1_1linalg_1_1cuda_1_1amg.html#ad251eca20f99e452229d76237d791a0e">amg_influence_advanced</a>(<a class="code" href="classviennacl_1_1compressed__matrix.html">compressed_matrix<NumericT></a> <span class="keyword">const</span> & A,</div>
<div class="line"><a name="l00095"></a><span class="lineno"> 95</span>  <a class="code" href="structviennacl_1_1linalg_1_1detail_1_1amg_1_1amg__level__context.html">viennacl::linalg::detail::amg::amg_level_context</a> & amg_context,</div>
<div class="line"><a name="l00096"></a><span class="lineno"> 96</span>  <a class="code" href="classviennacl_1_1linalg_1_1amg__tag.html">viennacl::linalg::amg_tag</a> & tag)</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>  <span class="keywordflow">throw</span> std::runtime_error(<span class="stringliteral">"not implemented yet"</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> </div>
<div class="line"><a name="l00102"></a><span class="lineno"> 102</span> <span class="keyword">template</span><<span class="keyword">typename</span> NumericT></div>
<div class="line"><a name="l00103"></a><span class="lineno"><a class="line" href="namespaceviennacl_1_1linalg_1_1cuda_1_1amg.html#a28e3755d2f30432e39bb842732129098"> 103</a></span> <span class="keywordtype">void</span> <a class="code" href="namespaceviennacl_1_1linalg_1_1cuda_1_1amg.html#a28e3755d2f30432e39bb842732129098">amg_influence</a>(<a class="code" href="classviennacl_1_1compressed__matrix.html">compressed_matrix<NumericT></a> <span class="keyword">const</span> & A,</div>
<div class="line"><a name="l00104"></a><span class="lineno"> 104</span>  <a class="code" href="structviennacl_1_1linalg_1_1detail_1_1amg_1_1amg__level__context.html">viennacl::linalg::detail::amg::amg_level_context</a> & amg_context,</div>
<div class="line"><a name="l00105"></a><span class="lineno"> 105</span>  <a class="code" href="classviennacl_1_1linalg_1_1amg__tag.html">viennacl::linalg::amg_tag</a> & tag)</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>  <span class="comment">// TODO: dispatch based on influence tolerance provided</span></div>
<div class="line"><a name="l00108"></a><span class="lineno"> 108</span>  <a class="code" href="namespaceviennacl_1_1linalg_1_1cuda_1_1amg.html#ac1b1f9a0666d83c46ee9b4c5e25cd2c6">amg_influence_trivial</a>(A, amg_context, tag);</div>
<div class="line"><a name="l00109"></a><span class="lineno"> 109</span> }</div>
<div class="line"><a name="l00110"></a><span class="lineno"> 110</span> </div>
<div class="line"><a name="l00115"></a><span class="lineno"><a class="line" href="namespaceviennacl_1_1linalg_1_1cuda_1_1amg.html#a258c31de37f3c9831443b5f2ea5f4b19"> 115</a></span> <span class="keyword">inline</span> <span class="keywordtype">void</span> <a class="code" href="namespaceviennacl_1_1linalg_1_1cuda_1_1amg.html#a258c31de37f3c9831443b5f2ea5f4b19">enumerate_coarse_points</a>(<a class="code" href="structviennacl_1_1linalg_1_1detail_1_1amg_1_1amg__level__context.html">viennacl::linalg::detail::amg::amg_level_context</a> & amg_context)</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>  <a class="code" href="classviennacl_1_1backend_1_1typesafe__host__array.html">viennacl::backend::typesafe_host_array<unsigned int></a> point_types(amg_context.<a class="code" href="structviennacl_1_1linalg_1_1detail_1_1amg_1_1amg__level__context.html#a8856e6db54e88c12e2ac728b5fcbe1e4">point_types_</a>.<a class="code" href="classviennacl_1_1vector__base.html#a64e98aea5aa298ad63e3832a04c19648">handle</a>(), amg_context.<a class="code" href="structviennacl_1_1linalg_1_1detail_1_1amg_1_1amg__level__context.html#a8856e6db54e88c12e2ac728b5fcbe1e4">point_types_</a>.<a class="code" href="classviennacl_1_1vector__base.html#a15c47ae4326098aeaa4ed6b91fc6df9b">size</a>());</div>
<div class="line"><a name="l00118"></a><span class="lineno"> 118</span>  <a class="code" href="classviennacl_1_1backend_1_1typesafe__host__array.html">viennacl::backend::typesafe_host_array<unsigned int></a> coarse_ids(amg_context.<a class="code" href="structviennacl_1_1linalg_1_1detail_1_1amg_1_1amg__level__context.html#aa647069a4102267171e395fcfd10e7ac">coarse_id_</a>.<a class="code" href="classviennacl_1_1vector__base.html#a64e98aea5aa298ad63e3832a04c19648">handle</a>(), amg_context.<a class="code" href="structviennacl_1_1linalg_1_1detail_1_1amg_1_1amg__level__context.html#aa647069a4102267171e395fcfd10e7ac">coarse_id_</a>.<a class="code" href="classviennacl_1_1vector__base.html#a15c47ae4326098aeaa4ed6b91fc6df9b">size</a>());</div>
<div class="line"><a name="l00119"></a><span class="lineno"> 119</span>  <a class="code" href="namespaceviennacl_1_1backend.html#a62854cfd6f04404b274f8ede36f63e2d">viennacl::backend::memory_read</a>(amg_context.<a class="code" href="structviennacl_1_1linalg_1_1detail_1_1amg_1_1amg__level__context.html#a8856e6db54e88c12e2ac728b5fcbe1e4">point_types_</a>.<a class="code" href="classviennacl_1_1vector__base.html#a64e98aea5aa298ad63e3832a04c19648">handle</a>(), 0, point_types.<a class="code" href="classviennacl_1_1backend_1_1mem__handle.html#ac8373f0d899b89c843e14de4cb7a1c4a">raw_size</a>(), point_types.get());</div>
<div class="line"><a name="l00120"></a><span class="lineno"> 120</span>  <a class="code" href="namespaceviennacl_1_1backend.html#a62854cfd6f04404b274f8ede36f63e2d">viennacl::backend::memory_read</a>(amg_context.<a class="code" href="structviennacl_1_1linalg_1_1detail_1_1amg_1_1amg__level__context.html#aa647069a4102267171e395fcfd10e7ac">coarse_id_</a>.<a class="code" href="classviennacl_1_1vector__base.html#a64e98aea5aa298ad63e3832a04c19648">handle</a>(), 0, coarse_ids.<a class="code" href="classviennacl_1_1backend_1_1mem__handle.html#ac8373f0d899b89c843e14de4cb7a1c4a">raw_size</a>(), coarse_ids.get());</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="keywordtype">unsigned</span> <span class="keywordtype">int</span> coarse_id = 0;</div>
<div class="line"><a name="l00123"></a><span class="lineno"> 123</span>  <span class="keywordflow">for</span> (std::size_t i=0; i<amg_context.<a class="code" href="structviennacl_1_1linalg_1_1detail_1_1amg_1_1amg__level__context.html#a8856e6db54e88c12e2ac728b5fcbe1e4">point_types_</a>.<a class="code" href="classviennacl_1_1vector__base.html#a15c47ae4326098aeaa4ed6b91fc6df9b">size</a>(); ++i)</div>
<div class="line"><a name="l00124"></a><span class="lineno"> 124</span>  {</div>
<div class="line"><a name="l00125"></a><span class="lineno"> 125</span>  coarse_ids.set(i, coarse_id);</div>
<div class="line"><a name="l00126"></a><span class="lineno"> 126</span>  <span class="keywordflow">if</span> (point_types[i] == <a class="code" href="structviennacl_1_1linalg_1_1detail_1_1amg_1_1amg__level__context.html#aa97530b4793135fb8d5e71010c8ff637afbc2c39efc86491c26c2401d06f2cc8a">viennacl::linalg::detail::amg::amg_level_context::POINT_TYPE_COARSE</a>)</div>
<div class="line"><a name="l00127"></a><span class="lineno"> 127</span>  ++coarse_id;</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> </div>
<div class="line"><a name="l00130"></a><span class="lineno"> 130</span>  amg_context.<a class="code" href="structviennacl_1_1linalg_1_1detail_1_1amg_1_1amg__level__context.html#aac5a6ef480cf58fb8fa490760bb94e35">num_coarse_</a> = coarse_id;</div>
<div class="line"><a name="l00131"></a><span class="lineno"> 131</span> </div>
<div class="line"><a name="l00132"></a><span class="lineno"> 132</span>  <a class="code" href="namespaceviennacl_1_1backend.html#a06bdedb2bc72dc1922cada91e9bbbd61">viennacl::backend::memory_write</a>(amg_context.<a class="code" href="structviennacl_1_1linalg_1_1detail_1_1amg_1_1amg__level__context.html#aa647069a4102267171e395fcfd10e7ac">coarse_id_</a>.<a class="code" href="classviennacl_1_1vector__base.html#a64e98aea5aa298ad63e3832a04c19648">handle</a>(), 0, coarse_ids.<a class="code" href="classviennacl_1_1backend_1_1mem__handle.html#ac8373f0d899b89c843e14de4cb7a1c4a">raw_size</a>(), coarse_ids.get());</div>
<div class="line"><a name="l00133"></a><span class="lineno"> 133</span> }</div>
<div class="line"><a name="l00134"></a><span class="lineno"> 134</span> </div>
<div class="line"><a name="l00136"></a><span class="lineno"> 136</span> </div>
<div class="line"><a name="l00138"></a><span class="lineno"> 138</span> <span class="keyword">template</span><<span class="keyword">typename</span> IndexT></div>
<div class="line"><a name="l00139"></a><span class="lineno"><a class="line" href="namespaceviennacl_1_1linalg_1_1cuda_1_1amg.html#ae34c65a23e53597faff3357364fc4c2d"> 139</a></span> __global__ <span class="keywordtype">void</span> <a class="code" href="namespaceviennacl_1_1linalg_1_1cuda_1_1amg.html#ae34c65a23e53597faff3357364fc4c2d">amg_pmis2_init_workdata</a>(IndexT *work_state,</div>
<div class="line"><a name="l00140"></a><span class="lineno"> 140</span>  IndexT *work_random,</div>
<div class="line"><a name="l00141"></a><span class="lineno"> 141</span>  IndexT *work_index,</div>
<div class="line"><a name="l00142"></a><span class="lineno"> 142</span>  IndexT <span class="keyword">const</span> *point_types,</div>
<div class="line"><a name="l00143"></a><span class="lineno"> 143</span>  IndexT <span class="keyword">const</span> *random_weights,</div>
<div class="line"><a name="l00144"></a><span class="lineno"> 144</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="l00145"></a><span class="lineno"> 145</span> {</div>
<div class="line"><a name="l00146"></a><span class="lineno"> 146</span>  <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> global_id = blockDim.x * blockIdx.x + threadIdx.x;</div>
<div class="line"><a name="l00147"></a><span class="lineno"> 147</span>  <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> global_size = gridDim.x * blockDim.x;</div>
<div class="line"><a name="l00148"></a><span class="lineno"> 148</span> </div>
<div class="line"><a name="l00149"></a><span class="lineno"> 149</span>  <span class="keywordflow">for</span> (<span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> i = global_id; i < <a class="code" href="namespaceviennacl_1_1traits.html#aa2344ea20469f55fbc15a8e9526494d0">size</a>; i += global_size)</div>
<div class="line"><a name="l00150"></a><span class="lineno"> 150</span>  {</div>
<div class="line"><a name="l00151"></a><span class="lineno"> 151</span>  <span class="keywordflow">switch</span> (point_types[i])</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="keywordflow">case</span> <a class="code" href="structviennacl_1_1linalg_1_1detail_1_1amg_1_1amg__level__context.html#aa97530b4793135fb8d5e71010c8ff637adf77f4d874aa905e58b1d01448d599b7">viennacl::linalg::detail::amg::amg_level_context::POINT_TYPE_UNDECIDED</a>: work_state[i] = 1; <span class="keywordflow">break</span>;</div>
<div class="line"><a name="l00154"></a><span class="lineno"> 154</span>  <span class="keywordflow">case</span> <a class="code" href="structviennacl_1_1linalg_1_1detail_1_1amg_1_1amg__level__context.html#aa97530b4793135fb8d5e71010c8ff637af803b8af4a6abdaf3d0fd08c18da6de6">viennacl::linalg::detail::amg::amg_level_context::POINT_TYPE_FINE</a>: work_state[i] = 0; <span class="keywordflow">break</span>;</div>
<div class="line"><a name="l00155"></a><span class="lineno"> 155</span>  <span class="keywordflow">case</span> <a class="code" href="structviennacl_1_1linalg_1_1detail_1_1amg_1_1amg__level__context.html#aa97530b4793135fb8d5e71010c8ff637afbc2c39efc86491c26c2401d06f2cc8a">viennacl::linalg::detail::amg::amg_level_context::POINT_TYPE_COARSE</a>: work_state[i] = 2; <span class="keywordflow">break</span>;</div>
<div class="line"><a name="l00156"></a><span class="lineno"> 156</span>  <span class="keywordflow">default</span>:</div>
<div class="line"><a name="l00157"></a><span class="lineno"> 157</span>  <span class="keywordflow">break</span>; <span class="comment">// do nothing</span></div>
<div class="line"><a name="l00158"></a><span class="lineno"> 158</span>  }</div>
<div class="line"><a name="l00159"></a><span class="lineno"> 159</span> </div>
<div class="line"><a name="l00160"></a><span class="lineno"> 160</span>  work_random[i] = random_weights[i];</div>
<div class="line"><a name="l00161"></a><span class="lineno"> 161</span>  work_index[i] = i;</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> }</div>
<div class="line"><a name="l00164"></a><span class="lineno"> 164</span> </div>
<div class="line"><a name="l00166"></a><span class="lineno"> 166</span> <span class="keyword">template</span><<span class="keyword">typename</span> IndexT></div>
<div class="line"><a name="l00167"></a><span class="lineno"><a class="line" href="namespaceviennacl_1_1linalg_1_1cuda_1_1amg.html#ac6522518fb686a2fe0bd3db0d34a3fcd"> 167</a></span> __global__ <span class="keywordtype">void</span> <a class="code" href="namespaceviennacl_1_1linalg_1_1cuda_1_1amg.html#ac6522518fb686a2fe0bd3db0d34a3fcd">amg_pmis2_max_neighborhood</a>(IndexT <span class="keyword">const</span> *work_state,</div>
<div class="line"><a name="l00168"></a><span class="lineno"> 168</span>  IndexT <span class="keyword">const</span> *work_random,</div>
<div class="line"><a name="l00169"></a><span class="lineno"> 169</span>  IndexT <span class="keyword">const</span> *work_index,</div>
<div class="line"><a name="l00170"></a><span class="lineno"> 170</span>  IndexT *work_state2,</div>
<div class="line"><a name="l00171"></a><span class="lineno"> 171</span>  IndexT *work_random2,</div>
<div class="line"><a name="l00172"></a><span class="lineno"> 172</span>  IndexT *work_index2,</div>
<div class="line"><a name="l00173"></a><span class="lineno"> 173</span>  IndexT <span class="keyword">const</span> *influences_row,</div>
<div class="line"><a name="l00174"></a><span class="lineno"> 174</span>  IndexT <span class="keyword">const</span> *influences_id,</div>
<div class="line"><a name="l00175"></a><span class="lineno"> 175</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="l00176"></a><span class="lineno"> 176</span> {</div>
<div class="line"><a name="l00177"></a><span class="lineno"> 177</span>  <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> global_id = blockDim.x * blockIdx.x + threadIdx.x;</div>
<div class="line"><a name="l00178"></a><span class="lineno"> 178</span>  <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> global_size = gridDim.x * blockDim.x;</div>
<div class="line"><a name="l00179"></a><span class="lineno"> 179</span> </div>
<div class="line"><a name="l00180"></a><span class="lineno"> 180</span>  <span class="keywordflow">for</span> (<span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> i = global_id; i < <a class="code" href="namespaceviennacl_1_1traits.html#aa2344ea20469f55fbc15a8e9526494d0">size</a>; i += global_size)</div>
<div class="line"><a name="l00181"></a><span class="lineno"> 181</span>  {</div>
<div class="line"><a name="l00182"></a><span class="lineno"> 182</span>  <span class="comment">// load</span></div>
<div class="line"><a name="l00183"></a><span class="lineno"> 183</span>  <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> state = work_state[i];</div>
<div class="line"><a name="l00184"></a><span class="lineno"> 184</span>  <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> random = work_random[i];</div>
<div class="line"><a name="l00185"></a><span class="lineno"> 185</span>  <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> index = work_index[i];</div>
<div class="line"><a name="l00186"></a><span class="lineno"> 186</span> </div>
<div class="line"><a name="l00187"></a><span class="lineno"> 187</span>  <span class="comment">// max</span></div>
<div class="line"><a name="l00188"></a><span class="lineno"> 188</span>  <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> j_stop = influences_row[i + 1];</div>
<div class="line"><a name="l00189"></a><span class="lineno"> 189</span>  <span class="keywordflow">for</span> (<span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> j = influences_row[i]; j < j_stop; ++j)</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>  <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> influenced_point_id = influences_id[j];</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="comment">// lexigraphical triple-max (not particularly pretty, but does the job):</span></div>
<div class="line"><a name="l00194"></a><span class="lineno"> 194</span>  <span class="keywordflow">if</span> (state < work_state[influenced_point_id])</div>
<div class="line"><a name="l00195"></a><span class="lineno"> 195</span>  {</div>
<div class="line"><a name="l00196"></a><span class="lineno"> 196</span>  state = work_state[influenced_point_id];</div>
<div class="line"><a name="l00197"></a><span class="lineno"> 197</span>  random = work_random[influenced_point_id];</div>
<div class="line"><a name="l00198"></a><span class="lineno"> 198</span>  index = work_index[influenced_point_id];</div>
<div class="line"><a name="l00199"></a><span class="lineno"> 199</span>  }</div>
<div class="line"><a name="l00200"></a><span class="lineno"> 200</span>  <span class="keywordflow">else</span> <span class="keywordflow">if</span> (state == work_state[influenced_point_id])</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">if</span> (random < work_random[influenced_point_id])</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>  state = work_state[influenced_point_id];</div>
<div class="line"><a name="l00205"></a><span class="lineno"> 205</span>  random = work_random[influenced_point_id];</div>
<div class="line"><a name="l00206"></a><span class="lineno"> 206</span>  index = work_index[influenced_point_id];</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>  <span class="keywordflow">else</span> <span class="keywordflow">if</span> (random == work_random[influenced_point_id])</div>
<div class="line"><a name="l00209"></a><span class="lineno"> 209</span>  {</div>
<div class="line"><a name="l00210"></a><span class="lineno"> 210</span>  <span class="keywordflow">if</span> (index < work_index[influenced_point_id])</div>
<div class="line"><a name="l00211"></a><span class="lineno"> 211</span>  {</div>
<div class="line"><a name="l00212"></a><span class="lineno"> 212</span>  state = work_state[influenced_point_id];</div>
<div class="line"><a name="l00213"></a><span class="lineno"> 213</span>  random = work_random[influenced_point_id];</div>
<div class="line"><a name="l00214"></a><span class="lineno"> 214</span>  index = work_index[influenced_point_id];</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="comment">// max(random)</span></div>
<div class="line"><a name="l00217"></a><span class="lineno"> 217</span>  } <span class="comment">// max(state)</span></div>
<div class="line"><a name="l00218"></a><span class="lineno"> 218</span>  } <span class="comment">// for</span></div>
<div class="line"><a name="l00219"></a><span class="lineno"> 219</span> </div>
<div class="line"><a name="l00220"></a><span class="lineno"> 220</span>  <span class="comment">// store</span></div>
<div class="line"><a name="l00221"></a><span class="lineno"> 221</span>  work_state2[i] = state;</div>
<div class="line"><a name="l00222"></a><span class="lineno"> 222</span>  work_random2[i] = random;</div>
<div class="line"><a name="l00223"></a><span class="lineno"> 223</span>  work_index2[i] = index;</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> }</div>
<div class="line"><a name="l00226"></a><span class="lineno"> 226</span> </div>
<div class="line"><a name="l00228"></a><span class="lineno"> 228</span> <span class="keyword">template</span><<span class="keyword">typename</span> IndexT></div>
<div class="line"><a name="l00229"></a><span class="lineno"><a class="line" href="namespaceviennacl_1_1linalg_1_1cuda_1_1amg.html#ad5ee409e7f7e64210c17025092da89cd"> 229</a></span> __global__ <span class="keywordtype">void</span> <a class="code" href="namespaceviennacl_1_1linalg_1_1cuda_1_1amg.html#ad5ee409e7f7e64210c17025092da89cd">amg_pmis2_mark_mis_nodes</a>(IndexT <span class="keyword">const</span> *work_state,</div>
<div class="line"><a name="l00230"></a><span class="lineno"> 230</span>  IndexT <span class="keyword">const</span> *work_index,</div>
<div class="line"><a name="l00231"></a><span class="lineno"> 231</span>  IndexT *point_types,</div>
<div class="line"><a name="l00232"></a><span class="lineno"> 232</span>  IndexT *undecided_buffer,</div>
<div class="line"><a name="l00233"></a><span class="lineno"> 233</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="l00234"></a><span class="lineno"> 234</span> {</div>
<div class="line"><a name="l00235"></a><span class="lineno"> 235</span>  <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> global_id = blockDim.x * blockIdx.x + threadIdx.x;</div>
<div class="line"><a name="l00236"></a><span class="lineno"> 236</span>  <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> global_size = gridDim.x * blockDim.x;</div>
<div class="line"><a name="l00237"></a><span class="lineno"> 237</span> </div>
<div class="line"><a name="l00238"></a><span class="lineno"> 238</span>  <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> num_undecided = 0;</div>
<div class="line"><a name="l00239"></a><span class="lineno"> 239</span>  <span class="keywordflow">for</span> (<span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> i = global_id; i < <a class="code" href="namespaceviennacl_1_1traits.html#aa2344ea20469f55fbc15a8e9526494d0">size</a>; i += global_size)</div>
<div class="line"><a name="l00240"></a><span class="lineno"> 240</span>  {</div>
<div class="line"><a name="l00241"></a><span class="lineno"> 241</span>  <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> max_state = work_state[i];</div>
<div class="line"><a name="l00242"></a><span class="lineno"> 242</span>  <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> max_index = work_index[i];</div>
<div class="line"><a name="l00243"></a><span class="lineno"> 243</span> </div>
<div class="line"><a name="l00244"></a><span class="lineno"> 244</span>  <span class="keywordflow">if</span> (point_types[i] == <a class="code" href="structviennacl_1_1linalg_1_1detail_1_1amg_1_1amg__level__context.html#aa97530b4793135fb8d5e71010c8ff637adf77f4d874aa905e58b1d01448d599b7">viennacl::linalg::detail::amg::amg_level_context::POINT_TYPE_UNDECIDED</a>)</div>
<div class="line"><a name="l00245"></a><span class="lineno"> 245</span>  {</div>
<div class="line"><a name="l00246"></a><span class="lineno"> 246</span>  <span class="keywordflow">if</span> (i == max_index) <span class="comment">// make this a MIS node</span></div>
<div class="line"><a name="l00247"></a><span class="lineno"> 247</span>  point_types[i] = <a class="code" href="structviennacl_1_1linalg_1_1detail_1_1amg_1_1amg__level__context.html#aa97530b4793135fb8d5e71010c8ff637afbc2c39efc86491c26c2401d06f2cc8a">viennacl::linalg::detail::amg::amg_level_context::POINT_TYPE_COARSE</a>;</div>
<div class="line"><a name="l00248"></a><span class="lineno"> 248</span>  <span class="keywordflow">else</span> <span class="keywordflow">if</span> (max_state == 2) <span class="comment">// mind the mapping of viennacl::linalg::detail::amg::amg_level_context::POINT_TYPE_COARSE above!</span></div>
<div class="line"><a name="l00249"></a><span class="lineno"> 249</span>  point_types[i] = <a class="code" href="structviennacl_1_1linalg_1_1detail_1_1amg_1_1amg__level__context.html#aa97530b4793135fb8d5e71010c8ff637af803b8af4a6abdaf3d0fd08c18da6de6">viennacl::linalg::detail::amg::amg_level_context::POINT_TYPE_FINE</a>;</div>
<div class="line"><a name="l00250"></a><span class="lineno"> 250</span>  <span class="keywordflow">else</span></div>
<div class="line"><a name="l00251"></a><span class="lineno"> 251</span>  num_undecided += 1;</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>  <span class="comment">// reduction of the number of undecided nodes:</span></div>
<div class="line"><a name="l00256"></a><span class="lineno"> 256</span>  __shared__ <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> shared_buffer[256];</div>
<div class="line"><a name="l00257"></a><span class="lineno"> 257</span>  shared_buffer[threadIdx.x] = num_undecided;</div>
<div class="line"><a name="l00258"></a><span class="lineno"> 258</span>  <span class="keywordflow">for</span> (<span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> <a class="code" href="namespaceviennacl_1_1traits.html#a09997870f4802fa5d4ac2c43cf4020d1">stride</a> = blockDim.x/2; <a class="code" href="namespaceviennacl_1_1traits.html#a09997870f4802fa5d4ac2c43cf4020d1">stride</a> > 0; <a class="code" href="namespaceviennacl_1_1traits.html#a09997870f4802fa5d4ac2c43cf4020d1">stride</a> /= 2)</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>  __syncthreads();</div>
<div class="line"><a name="l00261"></a><span class="lineno"> 261</span>  <span class="keywordflow">if</span> (threadIdx.x < <a class="code" href="namespaceviennacl_1_1traits.html#a09997870f4802fa5d4ac2c43cf4020d1">stride</a>)</div>
<div class="line"><a name="l00262"></a><span class="lineno"> 262</span>  shared_buffer[threadIdx.x] += shared_buffer[threadIdx.x+<a class="code" href="namespaceviennacl_1_1traits.html#a09997870f4802fa5d4ac2c43cf4020d1">stride</a>];</div>
<div class="line"><a name="l00263"></a><span class="lineno"> 263</span>  }</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>  <span class="keywordflow">if</span> (threadIdx.x == 0)</div>
<div class="line"><a name="l00266"></a><span class="lineno"> 266</span>  undecided_buffer[blockIdx.x] = shared_buffer[0];</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> }</div>
<div class="line"><a name="l00269"></a><span class="lineno"> 269</span> </div>
<div class="line"><a name="l00271"></a><span class="lineno"><a class="line" href="namespaceviennacl_1_1linalg_1_1cuda_1_1amg.html#a1c10960302d546fd274e68564f1409de"> 271</a></span> __global__ <span class="keywordtype">void</span> <a class="code" href="namespaceviennacl_1_1linalg_1_1cuda_1_1amg.html#a1c10960302d546fd274e68564f1409de">amg_pmis2_reset_state</a>(<span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> *point_types, <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="l00272"></a><span class="lineno"> 272</span> {</div>
<div class="line"><a name="l00273"></a><span class="lineno"> 273</span>  <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> global_id = blockDim.x * blockIdx.x + threadIdx.x;</div>
<div class="line"><a name="l00274"></a><span class="lineno"> 274</span>  <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> global_size = gridDim.x * blockDim.x;</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>  <span class="keywordflow">for</span> (<span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> i = global_id; i < <a class="code" href="namespaceviennacl_1_1traits.html#aa2344ea20469f55fbc15a8e9526494d0">size</a>; i += global_size)</div>
<div class="line"><a name="l00277"></a><span class="lineno"> 277</span>  {</div>
<div class="line"><a name="l00278"></a><span class="lineno"> 278</span>  <span class="keywordflow">if</span> (point_types[i] != <a class="code" href="structviennacl_1_1linalg_1_1detail_1_1amg_1_1amg__level__context.html#aa97530b4793135fb8d5e71010c8ff637afbc2c39efc86491c26c2401d06f2cc8a">viennacl::linalg::detail::amg::amg_level_context::POINT_TYPE_COARSE</a>)</div>
<div class="line"><a name="l00279"></a><span class="lineno"> 279</span>  point_types[i] = <a class="code" href="structviennacl_1_1linalg_1_1detail_1_1amg_1_1amg__level__context.html#aa97530b4793135fb8d5e71010c8ff637adf77f4d874aa905e58b1d01448d599b7">viennacl::linalg::detail::amg::amg_level_context::POINT_TYPE_UNDECIDED</a>;</div>
<div class="line"><a name="l00280"></a><span class="lineno"> 280</span>  }</div>
<div class="line"><a name="l00281"></a><span class="lineno"> 281</span> }</div>
<div class="line"><a name="l00282"></a><span class="lineno"> 282</span> </div>
<div class="line"><a name="l00289"></a><span class="lineno"> 289</span> <span class="keyword">template</span><<span class="keyword">typename</span> NumericT></div>
<div class="line"><a name="l00290"></a><span class="lineno"><a class="line" href="namespaceviennacl_1_1linalg_1_1cuda_1_1amg.html#a24916ce5eec2c7fa4b4542a4c082e75e"> 290</a></span> <span class="keywordtype">void</span> <a class="code" href="namespaceviennacl_1_1linalg_1_1cuda_1_1amg.html#a24916ce5eec2c7fa4b4542a4c082e75e">amg_coarse_ag_stage1_mis2</a>(<a class="code" href="classviennacl_1_1compressed__matrix.html">compressed_matrix<NumericT></a> <span class="keyword">const</span> & A,</div>
<div class="line"><a name="l00291"></a><span class="lineno"> 291</span>  <a class="code" href="structviennacl_1_1linalg_1_1detail_1_1amg_1_1amg__level__context.html">viennacl::linalg::detail::amg::amg_level_context</a> & amg_context,</div>
<div class="line"><a name="l00292"></a><span class="lineno"> 292</span>  <a class="code" href="classviennacl_1_1linalg_1_1amg__tag.html">viennacl::linalg::amg_tag</a> & tag)</div>
<div class="line"><a name="l00293"></a><span class="lineno"> 293</span> {</div>
<div class="line"><a name="l00294"></a><span class="lineno"> 294</span>  <a class="code" href="classviennacl_1_1vector.html">viennacl::vector<unsigned int></a> random_weights(A.<a class="code" href="classviennacl_1_1compressed__matrix.html#a463cf1739f9cdd387aa185cb574db183">size1</a>(), <a class="code" href="namespaceviennacl_1_1traits.html#a6707f5dab8f482170d2046a605f46ef8">viennacl::context</a>(<a class="code" href="namespaceviennacl.html#a00b40450b6b2fd87aad3527d9b2084b8a427356f0fb1b8d32b28f37e36b272df4">viennacl::MAIN_MEMORY</a>));</div>
<div class="line"><a name="l00295"></a><span class="lineno"> 295</span>  <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> *random_weights_ptr = viennacl::linalg::host_based::detail::extract_raw_pointer<unsigned int>(random_weights.handle());</div>
<div class="line"><a name="l00296"></a><span class="lineno"> 296</span>  <span class="keywordflow">for</span> (std::size_t i=0; i<random_weights.size(); ++i)</div>
<div class="line"><a name="l00297"></a><span class="lineno"> 297</span>  random_weights_ptr[i] = static_cast<unsigned int>(rand()) % static_cast<unsigned int>(A.<a class="code" href="classviennacl_1_1compressed__matrix.html#a463cf1739f9cdd387aa185cb574db183">size1</a>());</div>
<div class="line"><a name="l00298"></a><span class="lineno"> 298</span>  random_weights.<a class="code" href="classviennacl_1_1vector.html#a59f2ec43f298cc04d2f2bbbeee239bfe">switch_memory_context</a>(<a class="code" href="namespaceviennacl_1_1traits.html#a6707f5dab8f482170d2046a605f46ef8">viennacl::traits::context</a>(A));</div>
<div class="line"><a name="l00299"></a><span class="lineno"> 299</span> </div>
<div class="line"><a name="l00300"></a><span class="lineno"> 300</span>  <span class="comment">// work vectors:</span></div>
<div class="line"><a name="l00301"></a><span class="lineno"> 301</span>  <a class="code" href="classviennacl_1_1vector.html">viennacl::vector<unsigned int></a> work_state(A.<a class="code" href="classviennacl_1_1compressed__matrix.html#a463cf1739f9cdd387aa185cb574db183">size1</a>(), <a class="code" href="namespaceviennacl_1_1traits.html#a6707f5dab8f482170d2046a605f46ef8">viennacl::traits::context</a>(A));</div>
<div class="line"><a name="l00302"></a><span class="lineno"> 302</span>  <a class="code" href="classviennacl_1_1vector.html">viennacl::vector<unsigned int></a> work_random(A.<a class="code" href="classviennacl_1_1compressed__matrix.html#a463cf1739f9cdd387aa185cb574db183">size1</a>(), <a class="code" href="namespaceviennacl_1_1traits.html#a6707f5dab8f482170d2046a605f46ef8">viennacl::traits::context</a>(A));</div>
<div class="line"><a name="l00303"></a><span class="lineno"> 303</span>  <a class="code" href="classviennacl_1_1vector.html">viennacl::vector<unsigned int></a> work_index(A.<a class="code" href="classviennacl_1_1compressed__matrix.html#a463cf1739f9cdd387aa185cb574db183">size1</a>(), <a class="code" href="namespaceviennacl_1_1traits.html#a6707f5dab8f482170d2046a605f46ef8">viennacl::traits::context</a>(A));</div>
<div class="line"><a name="l00304"></a><span class="lineno"> 304</span> </div>
<div class="line"><a name="l00305"></a><span class="lineno"> 305</span>  <a class="code" href="classviennacl_1_1vector.html">viennacl::vector<unsigned int></a> work_state2(A.<a class="code" href="classviennacl_1_1compressed__matrix.html#a463cf1739f9cdd387aa185cb574db183">size1</a>(), <a class="code" href="namespaceviennacl_1_1traits.html#a6707f5dab8f482170d2046a605f46ef8">viennacl::traits::context</a>(A));</div>
<div class="line"><a name="l00306"></a><span class="lineno"> 306</span>  <a class="code" href="classviennacl_1_1vector.html">viennacl::vector<unsigned int></a> work_random2(A.<a class="code" href="classviennacl_1_1compressed__matrix.html#a463cf1739f9cdd387aa185cb574db183">size1</a>(), <a class="code" href="namespaceviennacl_1_1traits.html#a6707f5dab8f482170d2046a605f46ef8">viennacl::traits::context</a>(A));</div>
<div class="line"><a name="l00307"></a><span class="lineno"> 307</span>  <a class="code" href="classviennacl_1_1vector.html">viennacl::vector<unsigned int></a> work_index2(A.<a class="code" href="classviennacl_1_1compressed__matrix.html#a463cf1739f9cdd387aa185cb574db183">size1</a>(), <a class="code" href="namespaceviennacl_1_1traits.html#a6707f5dab8f482170d2046a605f46ef8">viennacl::traits::context</a>(A));</div>
<div class="line"><a name="l00308"></a><span class="lineno"> 308</span> </div>
<div class="line"><a name="l00309"></a><span class="lineno"> 309</span>  <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> num_undecided = <span class="keyword">static_cast<</span><span class="keywordtype">unsigned</span> <span class="keywordtype">int</span><span class="keyword">></span>(A.<a class="code" href="classviennacl_1_1compressed__matrix.html#a463cf1739f9cdd387aa185cb574db183">size1</a>());</div>
<div class="line"><a name="l00310"></a><span class="lineno"> 310</span>  <a class="code" href="classviennacl_1_1vector.html">viennacl::vector<unsigned int></a> undecided_buffer(256, <a class="code" href="namespaceviennacl_1_1traits.html#a6707f5dab8f482170d2046a605f46ef8">viennacl::traits::context</a>(A));</div>
<div class="line"><a name="l00311"></a><span class="lineno"> 311</span>  <a class="code" href="classviennacl_1_1backend_1_1typesafe__host__array.html">viennacl::backend::typesafe_host_array<unsigned int></a> undecided_buffer_host(undecided_buffer.<a class="code" href="classviennacl_1_1vector__base.html#a64e98aea5aa298ad63e3832a04c19648">handle</a>(), undecided_buffer.<a class="code" href="classviennacl_1_1vector__base.html#a15c47ae4326098aeaa4ed6b91fc6df9b">size</a>());</div>
<div class="line"><a name="l00312"></a><span class="lineno"> 312</span> </div>
<div class="line"><a name="l00313"></a><span class="lineno"> 313</span>  <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> pmis_iters = 0;</div>
<div class="line"><a name="l00314"></a><span class="lineno"> 314</span>  <span class="keywordflow">while</span> (num_undecided > 0)</div>
<div class="line"><a name="l00315"></a><span class="lineno"> 315</span>  {</div>
<div class="line"><a name="l00316"></a><span class="lineno"> 316</span>  ++pmis_iters;</div>
<div class="line"><a name="l00317"></a><span class="lineno"> 317</span> </div>
<div class="line"><a name="l00318"></a><span class="lineno"> 318</span>  <span class="comment">//</span></div>
<div class="line"><a name="l00319"></a><span class="lineno"> 319</span>  <span class="comment">// init temporary work data:</span></div>
<div class="line"><a name="l00320"></a><span class="lineno"> 320</span>  <span class="comment">//</span></div>
<div class="line"><a name="l00321"></a><span class="lineno"> 321</span>  amg_pmis2_init_workdata<<<128, 128>>>(<a class="code" href="namespaceviennacl.html#ae7d5db0c2c91be75218db5b52c4d13da">viennacl::cuda_arg</a>(work_state),</div>
<div class="line"><a name="l00322"></a><span class="lineno"> 322</span>  <a class="code" href="namespaceviennacl.html#ae7d5db0c2c91be75218db5b52c4d13da">viennacl::cuda_arg</a>(work_random),</div>
<div class="line"><a name="l00323"></a><span class="lineno"> 323</span>  <a class="code" href="namespaceviennacl.html#ae7d5db0c2c91be75218db5b52c4d13da">viennacl::cuda_arg</a>(work_index),</div>
<div class="line"><a name="l00324"></a><span class="lineno"> 324</span>  <a class="code" href="namespaceviennacl.html#ae7d5db0c2c91be75218db5b52c4d13da">viennacl::cuda_arg</a>(amg_context.<a class="code" href="structviennacl_1_1linalg_1_1detail_1_1amg_1_1amg__level__context.html#a8856e6db54e88c12e2ac728b5fcbe1e4">point_types_</a>),</div>
<div class="line"><a name="l00325"></a><span class="lineno"> 325</span>  <a class="code" href="namespaceviennacl.html#ae7d5db0c2c91be75218db5b52c4d13da">viennacl::cuda_arg</a>(random_weights),</div>
<div class="line"><a name="l00326"></a><span class="lineno"> 326</span>  <span class="keyword">static_cast<</span><span class="keywordtype">unsigned</span> <span class="keywordtype">int</span><span class="keyword">></span>(A.<a class="code" href="classviennacl_1_1compressed__matrix.html#a463cf1739f9cdd387aa185cb574db183">size1</a>())</div>
<div class="line"><a name="l00327"></a><span class="lineno"> 327</span>  );</div>
<div class="line"><a name="l00328"></a><span class="lineno"> 328</span>  <a class="code" href="linalg_2cuda_2common_8hpp.html#acdb31f22f4d1e12f1c2a27d4c4aa6865">VIENNACL_CUDA_LAST_ERROR_CHECK</a>(<span class="stringliteral">"amg_pmis2_reset_state"</span>);</div>
<div class="line"><a name="l00329"></a><span class="lineno"> 329</span> </div>
<div class="line"><a name="l00330"></a><span class="lineno"> 330</span> </div>
<div class="line"><a name="l00331"></a><span class="lineno"> 331</span>  <span class="comment">//</span></div>
<div class="line"><a name="l00332"></a><span class="lineno"> 332</span>  <span class="comment">// Propagate maximum tuple twice</span></div>
<div class="line"><a name="l00333"></a><span class="lineno"> 333</span>  <span class="comment">//</span></div>
<div class="line"><a name="l00334"></a><span class="lineno"> 334</span>  <span class="keywordflow">for</span> (<span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> r = 0; r < 2; ++r)</div>
<div class="line"><a name="l00335"></a><span class="lineno"> 335</span>  {</div>
<div class="line"><a name="l00336"></a><span class="lineno"> 336</span>  <span class="comment">// max operation over neighborhood</span></div>
<div class="line"><a name="l00337"></a><span class="lineno"> 337</span>  amg_pmis2_max_neighborhood<<<128, 128>>>(<a class="code" href="namespaceviennacl.html#ae7d5db0c2c91be75218db5b52c4d13da">viennacl::cuda_arg</a>(work_state),</div>
<div class="line"><a name="l00338"></a><span class="lineno"> 338</span>  <a class="code" href="namespaceviennacl.html#ae7d5db0c2c91be75218db5b52c4d13da">viennacl::cuda_arg</a>(work_random),</div>
<div class="line"><a name="l00339"></a><span class="lineno"> 339</span>  <a class="code" href="namespaceviennacl.html#ae7d5db0c2c91be75218db5b52c4d13da">viennacl::cuda_arg</a>(work_index),</div>
<div class="line"><a name="l00340"></a><span class="lineno"> 340</span>  <a class="code" href="namespaceviennacl.html#ae7d5db0c2c91be75218db5b52c4d13da">viennacl::cuda_arg</a>(work_state2),</div>
<div class="line"><a name="l00341"></a><span class="lineno"> 341</span>  <a class="code" href="namespaceviennacl.html#ae7d5db0c2c91be75218db5b52c4d13da">viennacl::cuda_arg</a>(work_random2),</div>
<div class="line"><a name="l00342"></a><span class="lineno"> 342</span>  <a class="code" href="namespaceviennacl.html#ae7d5db0c2c91be75218db5b52c4d13da">viennacl::cuda_arg</a>(work_index2),</div>
<div class="line"><a name="l00343"></a><span class="lineno"> 343</span>  <a class="code" href="namespaceviennacl.html#ae7d5db0c2c91be75218db5b52c4d13da">viennacl::cuda_arg</a>(amg_context.<a class="code" href="structviennacl_1_1linalg_1_1detail_1_1amg_1_1amg__level__context.html#ad537babcb184069cc920bfb2140860de">influence_jumper_</a>),</div>
<div class="line"><a name="l00344"></a><span class="lineno"> 344</span>  <a class="code" href="namespaceviennacl.html#ae7d5db0c2c91be75218db5b52c4d13da">viennacl::cuda_arg</a>(amg_context.<a class="code" href="structviennacl_1_1linalg_1_1detail_1_1amg_1_1amg__level__context.html#a262b6f406db2b16b53936b8759f83d05">influence_ids_</a>),</div>
<div class="line"><a name="l00345"></a><span class="lineno"> 345</span>  <span class="keyword">static_cast<</span><span class="keywordtype">unsigned</span> <span class="keywordtype">int</span><span class="keyword">></span>(A.<a class="code" href="classviennacl_1_1compressed__matrix.html#a463cf1739f9cdd387aa185cb574db183">size1</a>())</div>
<div class="line"><a name="l00346"></a><span class="lineno"> 346</span>  );</div>
<div class="line"><a name="l00347"></a><span class="lineno"> 347</span>  <a class="code" href="linalg_2cuda_2common_8hpp.html#acdb31f22f4d1e12f1c2a27d4c4aa6865">VIENNACL_CUDA_LAST_ERROR_CHECK</a>(<span class="stringliteral">"amg_pmis2_max_neighborhood"</span>);</div>
<div class="line"><a name="l00348"></a><span class="lineno"> 348</span> </div>
<div class="line"><a name="l00349"></a><span class="lineno"> 349</span>  <span class="comment">// copy work array (can be fused into a single kernel if needed. Previous kernel is in most cases sufficiently heavy)</span></div>
<div class="line"><a name="l00350"></a><span class="lineno"> 350</span>  work_state = work_state2;</div>
<div class="line"><a name="l00351"></a><span class="lineno"> 351</span>  work_random = work_random2;</div>
<div class="line"><a name="l00352"></a><span class="lineno"> 352</span>  work_index = work_index2;</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>  <span class="comment">//</span></div>
<div class="line"><a name="l00356"></a><span class="lineno"> 356</span>  <span class="comment">// mark MIS and non-MIS nodes:</span></div>
<div class="line"><a name="l00357"></a><span class="lineno"> 357</span>  <span class="comment">//</span></div>
<div class="line"><a name="l00358"></a><span class="lineno"> 358</span>  amg_pmis2_mark_mis_nodes<<<128, 128>>>(<a class="code" href="namespaceviennacl.html#ae7d5db0c2c91be75218db5b52c4d13da">viennacl::cuda_arg</a>(work_state),</div>
<div class="line"><a name="l00359"></a><span class="lineno"> 359</span>  <a class="code" href="namespaceviennacl.html#ae7d5db0c2c91be75218db5b52c4d13da">viennacl::cuda_arg</a>(work_index),</div>
<div class="line"><a name="l00360"></a><span class="lineno"> 360</span>  <a class="code" href="namespaceviennacl.html#ae7d5db0c2c91be75218db5b52c4d13da">viennacl::cuda_arg</a>(amg_context.<a class="code" href="structviennacl_1_1linalg_1_1detail_1_1amg_1_1amg__level__context.html#a8856e6db54e88c12e2ac728b5fcbe1e4">point_types_</a>),</div>
<div class="line"><a name="l00361"></a><span class="lineno"> 361</span>  <a class="code" href="namespaceviennacl.html#ae7d5db0c2c91be75218db5b52c4d13da">viennacl::cuda_arg</a>(undecided_buffer),</div>
<div class="line"><a name="l00362"></a><span class="lineno"> 362</span>  <span class="keyword">static_cast<</span><span class="keywordtype">unsigned</span> <span class="keywordtype">int</span><span class="keyword">></span>(A.<a class="code" href="classviennacl_1_1compressed__matrix.html#a463cf1739f9cdd387aa185cb574db183">size1</a>())</div>
<div class="line"><a name="l00363"></a><span class="lineno"> 363</span>  );</div>
<div class="line"><a name="l00364"></a><span class="lineno"> 364</span>  <a class="code" href="linalg_2cuda_2common_8hpp.html#acdb31f22f4d1e12f1c2a27d4c4aa6865">VIENNACL_CUDA_LAST_ERROR_CHECK</a>(<span class="stringliteral">"amg_pmis2_reset_state"</span>);</div>
<div class="line"><a name="l00365"></a><span class="lineno"> 365</span> </div>
<div class="line"><a name="l00366"></a><span class="lineno"> 366</span>  <span class="comment">// get number of undecided points on host:</span></div>
<div class="line"><a name="l00367"></a><span class="lineno"> 367</span>  <a class="code" href="namespaceviennacl_1_1backend.html#a62854cfd6f04404b274f8ede36f63e2d">viennacl::backend::memory_read</a>(undecided_buffer.<a class="code" href="classviennacl_1_1vector__base.html#a64e98aea5aa298ad63e3832a04c19648">handle</a>(), 0, undecided_buffer_host.<a class="code" href="classviennacl_1_1backend_1_1mem__handle.html#ac8373f0d899b89c843e14de4cb7a1c4a">raw_size</a>(), undecided_buffer_host.get());</div>
<div class="line"><a name="l00368"></a><span class="lineno"> 368</span>  num_undecided = 0;</div>
<div class="line"><a name="l00369"></a><span class="lineno"> 369</span>  <span class="keywordflow">for</span> (std::size_t i=0; i<undecided_buffer.<a class="code" href="classviennacl_1_1vector__base.html#a15c47ae4326098aeaa4ed6b91fc6df9b">size</a>(); ++i)</div>
<div class="line"><a name="l00370"></a><span class="lineno"> 370</span>  num_undecided += undecided_buffer_host[i];</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>  } <span class="comment">//while</span></div>
<div class="line"><a name="l00373"></a><span class="lineno"> 373</span> </div>
<div class="line"><a name="l00374"></a><span class="lineno"> 374</span>  <span class="comment">// consistency with sequential MIS: reset state for non-coarse points, so that coarse indices are correctly picked up later</span></div>
<div class="line"><a name="l00375"></a><span class="lineno"> 375</span>  amg_pmis2_reset_state<<<128, 128>>>(<a class="code" href="namespaceviennacl.html#ae7d5db0c2c91be75218db5b52c4d13da">viennacl::cuda_arg</a>(amg_context.<a class="code" href="structviennacl_1_1linalg_1_1detail_1_1amg_1_1amg__level__context.html#a8856e6db54e88c12e2ac728b5fcbe1e4">point_types_</a>),</div>
<div class="line"><a name="l00376"></a><span class="lineno"> 376</span>  <span class="keyword">static_cast<</span><span class="keywordtype">unsigned</span> <span class="keywordtype">int</span><span class="keyword">></span>(amg_context.<a class="code" href="structviennacl_1_1linalg_1_1detail_1_1amg_1_1amg__level__context.html#a8856e6db54e88c12e2ac728b5fcbe1e4">point_types_</a>.<a class="code" href="classviennacl_1_1vector__base.html#a15c47ae4326098aeaa4ed6b91fc6df9b">size</a>())</div>
<div class="line"><a name="l00377"></a><span class="lineno"> 377</span>  );</div>
<div class="line"><a name="l00378"></a><span class="lineno"> 378</span>  <a class="code" href="linalg_2cuda_2common_8hpp.html#acdb31f22f4d1e12f1c2a27d4c4aa6865">VIENNACL_CUDA_LAST_ERROR_CHECK</a>(<span class="stringliteral">"amg_pmis2_reset_state"</span>);</div>
<div class="line"><a name="l00379"></a><span class="lineno"> 379</span> }</div>
<div class="line"><a name="l00380"></a><span class="lineno"> 380</span> </div>
<div class="line"><a name="l00381"></a><span class="lineno"> 381</span> </div>
<div class="line"><a name="l00382"></a><span class="lineno"> 382</span> </div>
<div class="line"><a name="l00383"></a><span class="lineno"> 383</span> </div>
<div class="line"><a name="l00384"></a><span class="lineno"> 384</span> </div>
<div class="line"><a name="l00385"></a><span class="lineno"> 385</span> <span class="keyword">template</span><<span class="keyword">typename</span> IndexT></div>
<div class="line"><a name="l00386"></a><span class="lineno"><a class="line" href="namespaceviennacl_1_1linalg_1_1cuda_1_1amg.html#a72f36c48c3a517297e28ec9b87aea14f"> 386</a></span> __global__ <span class="keywordtype">void</span> <a class="code" href="namespaceviennacl_1_1linalg_1_1cuda_1_1amg.html#a72f36c48c3a517297e28ec9b87aea14f">amg_agg_propagate_coarse_indices</a>(IndexT *point_types,</div>
<div class="line"><a name="l00387"></a><span class="lineno"> 387</span>  IndexT *coarse_ids,</div>
<div class="line"><a name="l00388"></a><span class="lineno"> 388</span>  IndexT <span class="keyword">const</span> *influences_row,</div>
<div class="line"><a name="l00389"></a><span class="lineno"> 389</span>  IndexT <span class="keyword">const</span> *influences_id,</div>
<div class="line"><a name="l00390"></a><span class="lineno"> 390</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="l00391"></a><span class="lineno"> 391</span> {</div>
<div class="line"><a name="l00392"></a><span class="lineno"> 392</span>  <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> global_id = blockDim.x * blockIdx.x + threadIdx.x;</div>
<div class="line"><a name="l00393"></a><span class="lineno"> 393</span>  <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> global_size = gridDim.x * blockDim.x;</div>
<div class="line"><a name="l00394"></a><span class="lineno"> 394</span> </div>
<div class="line"><a name="l00395"></a><span class="lineno"> 395</span>  <span class="keywordflow">for</span> (<span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> i = global_id; i < <a class="code" href="namespaceviennacl_1_1traits.html#aa2344ea20469f55fbc15a8e9526494d0">size</a>; i += global_size)</div>
<div class="line"><a name="l00396"></a><span class="lineno"> 396</span>  {</div>
<div class="line"><a name="l00397"></a><span class="lineno"> 397</span>  <span class="keywordflow">if</span> (point_types[i] == <a class="code" href="structviennacl_1_1linalg_1_1detail_1_1amg_1_1amg__level__context.html#aa97530b4793135fb8d5e71010c8ff637afbc2c39efc86491c26c2401d06f2cc8a">viennacl::linalg::detail::amg::amg_level_context::POINT_TYPE_COARSE</a>)</div>
<div class="line"><a name="l00398"></a><span class="lineno"> 398</span>  {</div>
<div class="line"><a name="l00399"></a><span class="lineno"> 399</span>  <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> coarse_index = coarse_ids[i];</div>
<div class="line"><a name="l00400"></a><span class="lineno"> 400</span> </div>
<div class="line"><a name="l00401"></a><span class="lineno"> 401</span>  <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> j_stop = influences_row[i + 1];</div>
<div class="line"><a name="l00402"></a><span class="lineno"> 402</span>  <span class="keywordflow">for</span> (<span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> j = influences_row[i]; j < j_stop; ++j)</div>
<div class="line"><a name="l00403"></a><span class="lineno"> 403</span>  {</div>
<div class="line"><a name="l00404"></a><span class="lineno"> 404</span>  <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> influenced_point_id = influences_id[j];</div>
<div class="line"><a name="l00405"></a><span class="lineno"> 405</span>  coarse_ids[influenced_point_id] = coarse_index; <span class="comment">// Set aggregate index for fine point</span></div>
<div class="line"><a name="l00406"></a><span class="lineno"> 406</span> </div>
<div class="line"><a name="l00407"></a><span class="lineno"> 407</span>  <span class="keywordflow">if</span> (influenced_point_id != i) <span class="comment">// Note: Any write races between threads are harmless here</span></div>
<div class="line"><a name="l00408"></a><span class="lineno"> 408</span>  point_types[influenced_point_id] = <a class="code" href="structviennacl_1_1linalg_1_1detail_1_1amg_1_1amg__level__context.html#aa97530b4793135fb8d5e71010c8ff637af803b8af4a6abdaf3d0fd08c18da6de6">viennacl::linalg::detail::amg::amg_level_context::POINT_TYPE_FINE</a>;</div>
<div class="line"><a name="l00409"></a><span class="lineno"> 409</span>  }</div>
<div class="line"><a name="l00410"></a><span class="lineno"> 410</span>  }</div>
<div class="line"><a name="l00411"></a><span class="lineno"> 411</span>  }</div>
<div class="line"><a name="l00412"></a><span class="lineno"> 412</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> </div>
<div class="line"><a name="l00415"></a><span class="lineno"> 415</span> <span class="keyword">template</span><<span class="keyword">typename</span> IndexT></div>
<div class="line"><a name="l00416"></a><span class="lineno"><a class="line" href="namespaceviennacl_1_1linalg_1_1cuda_1_1amg.html#affaef0634b3cfec5a940b278051cb21d"> 416</a></span> __global__ <span class="keywordtype">void</span> <a class="code" href="namespaceviennacl_1_1linalg_1_1cuda_1_1amg.html#affaef0634b3cfec5a940b278051cb21d">amg_agg_merge_undecided</a>(IndexT *point_types,</div>
<div class="line"><a name="l00417"></a><span class="lineno"> 417</span>  IndexT *coarse_ids,</div>
<div class="line"><a name="l00418"></a><span class="lineno"> 418</span>  IndexT <span class="keyword">const</span> *influences_row,</div>
<div class="line"><a name="l00419"></a><span class="lineno"> 419</span>  IndexT <span class="keyword">const</span> *influences_id,</div>
<div class="line"><a name="l00420"></a><span class="lineno"> 420</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="l00421"></a><span class="lineno"> 421</span> {</div>
<div class="line"><a name="l00422"></a><span class="lineno"> 422</span>  <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> global_id = blockDim.x * blockIdx.x + threadIdx.x;</div>
<div class="line"><a name="l00423"></a><span class="lineno"> 423</span>  <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> global_size = gridDim.x * blockDim.x;</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>  <span class="keywordflow">for</span> (<span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> i = global_id; i < <a class="code" href="namespaceviennacl_1_1traits.html#aa2344ea20469f55fbc15a8e9526494d0">size</a>; i += global_size)</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>  <span class="keywordflow">if</span> (point_types[i] == <a class="code" href="structviennacl_1_1linalg_1_1detail_1_1amg_1_1amg__level__context.html#aa97530b4793135fb8d5e71010c8ff637adf77f4d874aa905e58b1d01448d599b7">viennacl::linalg::detail::amg::amg_level_context::POINT_TYPE_UNDECIDED</a>)</div>
<div class="line"><a name="l00428"></a><span class="lineno"> 428</span>  {</div>
<div class="line"><a name="l00429"></a><span class="lineno"> 429</span>  <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> j_stop = influences_row[i + 1];</div>
<div class="line"><a name="l00430"></a><span class="lineno"> 430</span>  <span class="keywordflow">for</span> (<span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> j = influences_row[i]; j < j_stop; ++j)</div>
<div class="line"><a name="l00431"></a><span class="lineno"> 431</span>  {</div>
<div class="line"><a name="l00432"></a><span class="lineno"> 432</span>  <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> influenced_point_id = influences_id[j];</div>
<div class="line"><a name="l00433"></a><span class="lineno"> 433</span>  <span class="keywordflow">if</span> (point_types[influenced_point_id] != <a class="code" href="structviennacl_1_1linalg_1_1detail_1_1amg_1_1amg__level__context.html#aa97530b4793135fb8d5e71010c8ff637adf77f4d874aa905e58b1d01448d599b7">viennacl::linalg::detail::amg::amg_level_context::POINT_TYPE_UNDECIDED</a>) <span class="comment">// either coarse or fine point</span></div>
<div class="line"><a name="l00434"></a><span class="lineno"> 434</span>  {</div>
<div class="line"><a name="l00435"></a><span class="lineno"> 435</span>  <span class="comment">//std::cout << "Setting fine node " << i << " to be aggregated with node " << *influence_iter << "/" << pointvector.get_coarse_index(*influence_iter) << std::endl;</span></div>
<div class="line"><a name="l00436"></a><span class="lineno"> 436</span>  coarse_ids[i] = coarse_ids[influenced_point_id];</div>
<div class="line"><a name="l00437"></a><span class="lineno"> 437</span>  <span class="keywordflow">break</span>;</div>
<div class="line"><a name="l00438"></a><span class="lineno"> 438</span>  }</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> </div>
<div class="line"><a name="l00444"></a><span class="lineno"> 444</span> </div>
<div class="line"><a name="l00445"></a><span class="lineno"><a class="line" href="namespaceviennacl_1_1linalg_1_1cuda_1_1amg.html#a4a60d31dadc06e04523a474fe067589f"> 445</a></span> __global__ <span class="keywordtype">void</span> <a class="code" href="namespaceviennacl_1_1linalg_1_1cuda_1_1amg.html#a4a60d31dadc06e04523a474fe067589f">amg_agg_merge_undecided_2</a>(<span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> *point_types,</div>
<div class="line"><a name="l00446"></a><span class="lineno"> 446</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="l00447"></a><span class="lineno"> 447</span> {</div>
<div class="line"><a name="l00448"></a><span class="lineno"> 448</span>  <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> global_id = blockDim.x * blockIdx.x + threadIdx.x;</div>
<div class="line"><a name="l00449"></a><span class="lineno"> 449</span>  <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> global_size = gridDim.x * blockDim.x;</div>
<div class="line"><a name="l00450"></a><span class="lineno"> 450</span> </div>
<div class="line"><a name="l00451"></a><span class="lineno"> 451</span>  <span class="keywordflow">for</span> (<span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> i = global_id; i < <a class="code" href="namespaceviennacl_1_1traits.html#aa2344ea20469f55fbc15a8e9526494d0">size</a>; i += global_size)</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>  <span class="keywordflow">if</span> (point_types[i] == <a class="code" href="structviennacl_1_1linalg_1_1detail_1_1amg_1_1amg__level__context.html#aa97530b4793135fb8d5e71010c8ff637adf77f4d874aa905e58b1d01448d599b7">viennacl::linalg::detail::amg::amg_level_context::POINT_TYPE_UNDECIDED</a>)</div>
<div class="line"><a name="l00454"></a><span class="lineno"> 454</span>  point_types[i] = <a class="code" href="structviennacl_1_1linalg_1_1detail_1_1amg_1_1amg__level__context.html#aa97530b4793135fb8d5e71010c8ff637af803b8af4a6abdaf3d0fd08c18da6de6">viennacl::linalg::detail::amg::amg_level_context::POINT_TYPE_FINE</a>;</div>
<div class="line"><a name="l00455"></a><span class="lineno"> 455</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> </div>
<div class="line"><a name="l00465"></a><span class="lineno"> 465</span> <span class="keyword">template</span><<span class="keyword">typename</span> NumericT></div>
<div class="line"><a name="l00466"></a><span class="lineno"><a class="line" href="namespaceviennacl_1_1linalg_1_1cuda_1_1amg.html#ac4a8f8869f8ba360558b53e40059dacb"> 466</a></span> <span class="keywordtype">void</span> <a class="code" href="namespaceviennacl_1_1linalg_1_1cuda_1_1amg.html#ac4a8f8869f8ba360558b53e40059dacb">amg_coarse_ag</a>(<a class="code" href="classviennacl_1_1compressed__matrix.html">compressed_matrix<NumericT></a> <span class="keyword">const</span> & A,</div>
<div class="line"><a name="l00467"></a><span class="lineno"> 467</span>  <a class="code" href="structviennacl_1_1linalg_1_1detail_1_1amg_1_1amg__level__context.html">viennacl::linalg::detail::amg::amg_level_context</a> & amg_context,</div>
<div class="line"><a name="l00468"></a><span class="lineno"> 468</span>  <a class="code" href="classviennacl_1_1linalg_1_1amg__tag.html">viennacl::linalg::amg_tag</a> & tag)</div>
<div class="line"><a name="l00469"></a><span class="lineno"> 469</span> {</div>
<div class="line"><a name="l00470"></a><span class="lineno"> 470</span> </div>
<div class="line"><a name="l00471"></a><span class="lineno"> 471</span>  <a class="code" href="namespaceviennacl_1_1linalg_1_1cuda_1_1amg.html#ac1b1f9a0666d83c46ee9b4c5e25cd2c6">amg_influence_trivial</a>(A, amg_context, tag);</div>
<div class="line"><a name="l00472"></a><span class="lineno"> 472</span> </div>
<div class="line"><a name="l00473"></a><span class="lineno"> 473</span>  <span class="comment">//</span></div>
<div class="line"><a name="l00474"></a><span class="lineno"> 474</span>  <span class="comment">// Stage 1: Build aggregates:</span></div>
<div class="line"><a name="l00475"></a><span class="lineno"> 475</span>  <span class="comment">//</span></div>
<div class="line"><a name="l00476"></a><span class="lineno"> 476</span>  <span class="keywordflow">if</span> (tag.<a class="code" href="classviennacl_1_1linalg_1_1amg__tag.html#a37cf475ac353f457a3b14879a1140e14">get_coarsening_method</a>() == <a class="code" href="namespaceviennacl_1_1linalg.html#a3ba810acdca541a5eada4560982a645ca0d4c883a9aa8a8514fb260ac404e3c8b">viennacl::linalg::AMG_COARSENING_METHOD_MIS2_AGGREGATION</a>)</div>
<div class="line"><a name="l00477"></a><span class="lineno"> 477</span>  <a class="code" href="namespaceviennacl_1_1linalg_1_1cuda_1_1amg.html#a24916ce5eec2c7fa4b4542a4c082e75e">amg_coarse_ag_stage1_mis2</a>(A, amg_context, tag);</div>
<div class="line"><a name="l00478"></a><span class="lineno"> 478</span>  <span class="keywordflow">else</span></div>
<div class="line"><a name="l00479"></a><span class="lineno"> 479</span>  <span class="keywordflow">throw</span> std::runtime_error(<span class="stringliteral">"Only MIS2 coarsening implemented. Selected coarsening not available with CUDA backend!"</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>  <a class="code" href="namespaceviennacl_1_1linalg_1_1cuda_1_1amg.html#a258c31de37f3c9831443b5f2ea5f4b19">viennacl::linalg::cuda::amg::enumerate_coarse_points</a>(amg_context);</div>
<div class="line"><a name="l00482"></a><span class="lineno"> 482</span> </div>
<div class="line"><a name="l00483"></a><span class="lineno"> 483</span>  <span class="comment">//</span></div>
<div class="line"><a name="l00484"></a><span class="lineno"> 484</span>  <span class="comment">// Stage 2: Propagate coarse aggregate indices to neighbors:</span></div>
<div class="line"><a name="l00485"></a><span class="lineno"> 485</span>  <span class="comment">//</span></div>
<div class="line"><a name="l00486"></a><span class="lineno"> 486</span>  amg_agg_propagate_coarse_indices<<<128, 128>>>(<a class="code" href="namespaceviennacl.html#ae7d5db0c2c91be75218db5b52c4d13da">viennacl::cuda_arg</a>(amg_context.<a class="code" href="structviennacl_1_1linalg_1_1detail_1_1amg_1_1amg__level__context.html#a8856e6db54e88c12e2ac728b5fcbe1e4">point_types_</a>),</div>
<div class="line"><a name="l00487"></a><span class="lineno"> 487</span>  <a class="code" href="namespaceviennacl.html#ae7d5db0c2c91be75218db5b52c4d13da">viennacl::cuda_arg</a>(amg_context.<a class="code" href="structviennacl_1_1linalg_1_1detail_1_1amg_1_1amg__level__context.html#aa647069a4102267171e395fcfd10e7ac">coarse_id_</a>),</div>
<div class="line"><a name="l00488"></a><span class="lineno"> 488</span>  <a class="code" href="namespaceviennacl.html#ae7d5db0c2c91be75218db5b52c4d13da">viennacl::cuda_arg</a>(amg_context.<a class="code" href="structviennacl_1_1linalg_1_1detail_1_1amg_1_1amg__level__context.html#ad537babcb184069cc920bfb2140860de">influence_jumper_</a>),</div>
<div class="line"><a name="l00489"></a><span class="lineno"> 489</span>  <a class="code" href="namespaceviennacl.html#ae7d5db0c2c91be75218db5b52c4d13da">viennacl::cuda_arg</a>(amg_context.<a class="code" href="structviennacl_1_1linalg_1_1detail_1_1amg_1_1amg__level__context.html#a262b6f406db2b16b53936b8759f83d05">influence_ids_</a>),</div>
<div class="line"><a name="l00490"></a><span class="lineno"> 490</span>  <span class="keyword">static_cast<</span><span class="keywordtype">unsigned</span> <span class="keywordtype">int</span><span class="keyword">></span>(A.<a class="code" href="classviennacl_1_1compressed__matrix.html#a463cf1739f9cdd387aa185cb574db183">size1</a>())</div>
<div class="line"><a name="l00491"></a><span class="lineno"> 491</span>  );</div>
<div class="line"><a name="l00492"></a><span class="lineno"> 492</span>  <a class="code" href="linalg_2cuda_2common_8hpp.html#acdb31f22f4d1e12f1c2a27d4c4aa6865">VIENNACL_CUDA_LAST_ERROR_CHECK</a>(<span class="stringliteral">"amg_agg_propagate_coarse_indices"</span>);</div>
<div class="line"><a name="l00493"></a><span class="lineno"> 493</span> </div>
<div class="line"><a name="l00494"></a><span class="lineno"> 494</span> </div>
<div class="line"><a name="l00495"></a><span class="lineno"> 495</span>  <span class="comment">//</span></div>
<div class="line"><a name="l00496"></a><span class="lineno"> 496</span>  <span class="comment">// Stage 3: Merge remaining undecided points (merging to first aggregate found when cycling over the hierarchy</span></div>
<div class="line"><a name="l00497"></a><span class="lineno"> 497</span>  <span class="comment">//</span></div>
<div class="line"><a name="l00498"></a><span class="lineno"> 498</span>  amg_agg_merge_undecided<<<128, 128>>>(<a class="code" href="namespaceviennacl.html#ae7d5db0c2c91be75218db5b52c4d13da">viennacl::cuda_arg</a>(amg_context.<a class="code" href="structviennacl_1_1linalg_1_1detail_1_1amg_1_1amg__level__context.html#a8856e6db54e88c12e2ac728b5fcbe1e4">point_types_</a>),</div>
<div class="line"><a name="l00499"></a><span class="lineno"> 499</span>  <a class="code" href="namespaceviennacl.html#ae7d5db0c2c91be75218db5b52c4d13da">viennacl::cuda_arg</a>(amg_context.<a class="code" href="structviennacl_1_1linalg_1_1detail_1_1amg_1_1amg__level__context.html#aa647069a4102267171e395fcfd10e7ac">coarse_id_</a>),</div>
<div class="line"><a name="l00500"></a><span class="lineno"> 500</span>  <a class="code" href="namespaceviennacl.html#ae7d5db0c2c91be75218db5b52c4d13da">viennacl::cuda_arg</a>(amg_context.<a class="code" href="structviennacl_1_1linalg_1_1detail_1_1amg_1_1amg__level__context.html#ad537babcb184069cc920bfb2140860de">influence_jumper_</a>),</div>
<div class="line"><a name="l00501"></a><span class="lineno"> 501</span>  <a class="code" href="namespaceviennacl.html#ae7d5db0c2c91be75218db5b52c4d13da">viennacl::cuda_arg</a>(amg_context.<a class="code" href="structviennacl_1_1linalg_1_1detail_1_1amg_1_1amg__level__context.html#a262b6f406db2b16b53936b8759f83d05">influence_ids_</a>),</div>
<div class="line"><a name="l00502"></a><span class="lineno"> 502</span>  <span class="keyword">static_cast<</span><span class="keywordtype">unsigned</span> <span class="keywordtype">int</span><span class="keyword">></span>(A.<a class="code" href="classviennacl_1_1compressed__matrix.html#a463cf1739f9cdd387aa185cb574db183">size1</a>())</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>  <a class="code" href="linalg_2cuda_2common_8hpp.html#acdb31f22f4d1e12f1c2a27d4c4aa6865">VIENNACL_CUDA_LAST_ERROR_CHECK</a>(<span class="stringliteral">"amg_agg_merge_undecided"</span>);</div>
<div class="line"><a name="l00505"></a><span class="lineno"> 505</span> </div>
<div class="line"><a name="l00506"></a><span class="lineno"> 506</span>  <span class="comment">//</span></div>
<div class="line"><a name="l00507"></a><span class="lineno"> 507</span>  <span class="comment">// Stage 4: Set undecided points to fine points (coarse ID already set in Stage 3)</span></div>
<div class="line"><a name="l00508"></a><span class="lineno"> 508</span>  <span class="comment">// Note: Stage 3 and Stage 4 were initially fused, but are now split in order to avoid race conditions (or a fallback to sequential execution).</span></div>
<div class="line"><a name="l00509"></a><span class="lineno"> 509</span>  <span class="comment">//</span></div>
<div class="line"><a name="l00510"></a><span class="lineno"> 510</span>  amg_agg_merge_undecided_2<<<128, 128>>>(<a class="code" href="namespaceviennacl.html#ae7d5db0c2c91be75218db5b52c4d13da">viennacl::cuda_arg</a>(amg_context.<a class="code" href="structviennacl_1_1linalg_1_1detail_1_1amg_1_1amg__level__context.html#a8856e6db54e88c12e2ac728b5fcbe1e4">point_types_</a>),</div>
<div class="line"><a name="l00511"></a><span class="lineno"> 511</span>  <span class="keyword">static_cast<</span><span class="keywordtype">unsigned</span> <span class="keywordtype">int</span><span class="keyword">></span>(A.<a class="code" href="classviennacl_1_1compressed__matrix.html#a463cf1739f9cdd387aa185cb574db183">size1</a>())</div>
<div class="line"><a name="l00512"></a><span class="lineno"> 512</span>  );</div>
<div class="line"><a name="l00513"></a><span class="lineno"> 513</span>  <a class="code" href="linalg_2cuda_2common_8hpp.html#acdb31f22f4d1e12f1c2a27d4c4aa6865">VIENNACL_CUDA_LAST_ERROR_CHECK</a>(<span class="stringliteral">"amg_agg_merge_undecided_2"</span>);</div>
<div class="line"><a name="l00514"></a><span class="lineno"> 514</span> }</div>
<div class="line"><a name="l00515"></a><span class="lineno"> 515</span> </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> </div>
<div class="line"><a name="l00525"></a><span class="lineno"> 525</span> <span class="keyword">template</span><<span class="keyword">typename</span> InternalT1></div>
<div class="line"><a name="l00526"></a><span class="lineno"><a class="line" href="namespaceviennacl_1_1linalg_1_1cuda_1_1amg.html#a0397785aabbeaa292cf3fbfe0d758dc1"> 526</a></span> <span class="keywordtype">void</span> <a class="code" href="namespaceviennacl_1_1linalg_1_1cuda_1_1amg.html#a0397785aabbeaa292cf3fbfe0d758dc1">amg_coarse</a>(InternalT1 & A,</div>
<div class="line"><a name="l00527"></a><span class="lineno"> 527</span>  <a class="code" href="structviennacl_1_1linalg_1_1detail_1_1amg_1_1amg__level__context.html">viennacl::linalg::detail::amg::amg_level_context</a> & amg_context,</div>
<div class="line"><a name="l00528"></a><span class="lineno"> 528</span>  <a class="code" href="classviennacl_1_1linalg_1_1amg__tag.html">viennacl::linalg::amg_tag</a> & tag)</div>
<div class="line"><a name="l00529"></a><span class="lineno"> 529</span> {</div>
<div class="line"><a name="l00530"></a><span class="lineno"> 530</span>  <span class="keywordflow">switch</span> (tag.<a class="code" href="classviennacl_1_1linalg_1_1amg__tag.html#a37cf475ac353f457a3b14879a1140e14">get_coarsening_method</a>())</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>  <span class="keywordflow">case</span> <a class="code" href="namespaceviennacl_1_1linalg.html#a3ba810acdca541a5eada4560982a645ca0d4c883a9aa8a8514fb260ac404e3c8b">viennacl::linalg::AMG_COARSENING_METHOD_MIS2_AGGREGATION</a>: <a class="code" href="namespaceviennacl_1_1linalg_1_1cuda_1_1amg.html#ac4a8f8869f8ba360558b53e40059dacb">amg_coarse_ag</a>(A, amg_context, tag); <span class="keywordflow">break</span>;</div>
<div class="line"><a name="l00533"></a><span class="lineno"> 533</span>  <span class="keywordflow">default</span>: <span class="keywordflow">throw</span> std::runtime_error(<span class="stringliteral">"not implemented yet"</span>);</div>
<div class="line"><a name="l00534"></a><span class="lineno"> 534</span>  }</div>
<div class="line"><a name="l00535"></a><span class="lineno"> 535</span> }</div>
<div class="line"><a name="l00536"></a><span class="lineno"> 536</span> </div>
<div class="line"><a name="l00537"></a><span class="lineno"> 537</span> </div>
<div class="line"><a name="l00538"></a><span class="lineno"> 538</span> </div>
<div class="line"><a name="l00539"></a><span class="lineno"> 539</span> </div>
<div class="line"><a name="l00541"></a><span class="lineno"> 541</span> </div>
<div class="line"><a name="l00542"></a><span class="lineno"> 542</span> <span class="keyword">template</span><<span class="keyword">typename</span> NumericT></div>
<div class="line"><a name="l00543"></a><span class="lineno"><a class="line" href="namespaceviennacl_1_1linalg_1_1cuda_1_1amg.html#a696559c185d8b0ff86edc633f6cbc643"> 543</a></span> __global__ <span class="keywordtype">void</span> <a class="code" href="namespaceviennacl_1_1linalg_1_1cuda_1_1amg.html#a696559c185d8b0ff86edc633f6cbc643">amg_interpol_ag_kernel</a>(<span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> *P_row_buffer,</div>
<div class="line"><a name="l00544"></a><span class="lineno"> 544</span>  <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> *P_col_buffer,</div>
<div class="line"><a name="l00545"></a><span class="lineno"> 545</span>  <a class="code" href="tests_2src_2bisect_8cpp.html#a52b5d30a2d7b064678644a3bf49b7f6c">NumericT</a> *P_elements,</div>
<div class="line"><a name="l00546"></a><span class="lineno"> 546</span>  <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> *coarse_ids,</div>
<div class="line"><a name="l00547"></a><span class="lineno"> 547</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="l00548"></a><span class="lineno"> 548</span> {</div>
<div class="line"><a name="l00549"></a><span class="lineno"> 549</span>  <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> global_id = blockDim.x * blockIdx.x + threadIdx.x;</div>
<div class="line"><a name="l00550"></a><span class="lineno"> 550</span>  <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> global_size = gridDim.x * blockDim.x;</div>
<div class="line"><a name="l00551"></a><span class="lineno"> 551</span> </div>
<div class="line"><a name="l00552"></a><span class="lineno"> 552</span>  <span class="keywordflow">for</span> (<span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> i = global_id; i < <a class="code" href="namespaceviennacl_1_1traits.html#aa2344ea20469f55fbc15a8e9526494d0">size</a>; i += global_size)</div>
<div class="line"><a name="l00553"></a><span class="lineno"> 553</span>  {</div>
<div class="line"><a name="l00554"></a><span class="lineno"> 554</span>  P_row_buffer[i] = i;</div>
<div class="line"><a name="l00555"></a><span class="lineno"> 555</span>  P_col_buffer[i] = coarse_ids[i];</div>
<div class="line"><a name="l00556"></a><span class="lineno"> 556</span>  P_elements[i] = <a class="code" href="tests_2src_2bisect_8cpp.html#a52b5d30a2d7b064678644a3bf49b7f6c">NumericT</a>(1);</div>
<div class="line"><a name="l00557"></a><span class="lineno"> 557</span>  }</div>
<div class="line"><a name="l00558"></a><span class="lineno"> 558</span> </div>
<div class="line"><a name="l00559"></a><span class="lineno"> 559</span>  <span class="comment">// set last entry as well:</span></div>
<div class="line"><a name="l00560"></a><span class="lineno"> 560</span>  <span class="keywordflow">if</span> (global_id == 0)</div>
<div class="line"><a name="l00561"></a><span class="lineno"> 561</span>  P_row_buffer[<a class="code" href="namespaceviennacl_1_1traits.html#aa2344ea20469f55fbc15a8e9526494d0">size</a>] = <a class="code" href="namespaceviennacl_1_1traits.html#aa2344ea20469f55fbc15a8e9526494d0">size</a>;</div>
<div class="line"><a name="l00562"></a><span class="lineno"> 562</span> }</div>
<div class="line"><a name="l00563"></a><span class="lineno"> 563</span> </div>
<div class="line"><a name="l00571"></a><span class="lineno"> 571</span> <span class="keyword">template</span><<span class="keyword">typename</span> NumericT></div>
<div class="line"><a name="l00572"></a><span class="lineno"><a class="line" href="namespaceviennacl_1_1linalg_1_1cuda_1_1amg.html#a9cb19def4af89cc7d5e58b7599d5c2d6"> 572</a></span> <span class="keywordtype">void</span> <a class="code" href="namespaceviennacl_1_1linalg_1_1cuda_1_1amg.html#a9cb19def4af89cc7d5e58b7599d5c2d6">amg_interpol_ag</a>(<a class="code" href="classviennacl_1_1compressed__matrix.html">compressed_matrix<NumericT></a> <span class="keyword">const</span> & A,</div>
<div class="line"><a name="l00573"></a><span class="lineno"> 573</span>  <a class="code" href="classviennacl_1_1compressed__matrix.html">compressed_matrix<NumericT></a> & P,</div>
<div class="line"><a name="l00574"></a><span class="lineno"> 574</span>  <a class="code" href="structviennacl_1_1linalg_1_1detail_1_1amg_1_1amg__level__context.html">viennacl::linalg::detail::amg::amg_level_context</a> & amg_context,</div>
<div class="line"><a name="l00575"></a><span class="lineno"> 575</span>  <a class="code" href="classviennacl_1_1linalg_1_1amg__tag.html">viennacl::linalg::amg_tag</a> & tag)</div>
<div class="line"><a name="l00576"></a><span class="lineno"> 576</span> {</div>
<div class="line"><a name="l00577"></a><span class="lineno"> 577</span>  (void)tag;</div>
<div class="line"><a name="l00578"></a><span class="lineno"> 578</span>  P = <a class="code" href="classviennacl_1_1compressed__matrix.html">compressed_matrix<NumericT></a>(A.<a class="code" href="classviennacl_1_1compressed__matrix.html#a463cf1739f9cdd387aa185cb574db183">size1</a>(), amg_context.<a class="code" href="structviennacl_1_1linalg_1_1detail_1_1amg_1_1amg__level__context.html#aac5a6ef480cf58fb8fa490760bb94e35">num_coarse_</a>, A.<a class="code" href="classviennacl_1_1compressed__matrix.html#a463cf1739f9cdd387aa185cb574db183">size1</a>(), <a class="code" href="namespaceviennacl_1_1traits.html#a6707f5dab8f482170d2046a605f46ef8">viennacl::traits::context</a>(A));</div>
<div class="line"><a name="l00579"></a><span class="lineno"> 579</span> </div>
<div class="line"><a name="l00580"></a><span class="lineno"> 580</span>  amg_interpol_ag_kernel<<<128, 128>>>(viennacl::cuda_arg<unsigned int>(P.<a class="code" href="classviennacl_1_1compressed__matrix.html#af71dec61a70e8df4f78a527aa989a106">handle1</a>().cuda_handle()),</div>
<div class="line"><a name="l00581"></a><span class="lineno"> 581</span>  viennacl::cuda_arg<unsigned int>(P.<a class="code" href="classviennacl_1_1compressed__matrix.html#a91f5145351151a66f916bdc3901206f2">handle2</a>().cuda_handle()),</div>
<div class="line"><a name="l00582"></a><span class="lineno"> 582</span>  viennacl::cuda_arg<NumericT>(P.<a class="code" href="classviennacl_1_1compressed__matrix.html#a87a0ad5f26983b1c2d24ee302d886562">handle</a>().cuda_handle()),</div>
<div class="line"><a name="l00583"></a><span class="lineno"> 583</span>  <a class="code" href="namespaceviennacl.html#ae7d5db0c2c91be75218db5b52c4d13da">viennacl::cuda_arg</a>(amg_context.<a class="code" href="structviennacl_1_1linalg_1_1detail_1_1amg_1_1amg__level__context.html#aa647069a4102267171e395fcfd10e7ac">coarse_id_</a>),</div>
<div class="line"><a name="l00584"></a><span class="lineno"> 584</span>  <span class="keyword">static_cast<</span><span class="keywordtype">unsigned</span> <span class="keywordtype">int</span><span class="keyword">></span>(A.<a class="code" href="classviennacl_1_1compressed__matrix.html#a463cf1739f9cdd387aa185cb574db183">size1</a>())</div>
<div class="line"><a name="l00585"></a><span class="lineno"> 585</span>  );</div>
<div class="line"><a name="l00586"></a><span class="lineno"> 586</span>  <a class="code" href="linalg_2cuda_2common_8hpp.html#acdb31f22f4d1e12f1c2a27d4c4aa6865">VIENNACL_CUDA_LAST_ERROR_CHECK</a>(<span class="stringliteral">"amg_interpol_ag_kernel"</span>);</div>
<div class="line"><a name="l00587"></a><span class="lineno"> 587</span> </div>
<div class="line"><a name="l00588"></a><span class="lineno"> 588</span>  P.<a class="code" href="classviennacl_1_1compressed__matrix.html#ab5922a97b73b869fbeeb6a2fa40e3b06">generate_row_block_information</a>();</div>
<div class="line"><a name="l00589"></a><span class="lineno"> 589</span> }</div>
<div class="line"><a name="l00590"></a><span class="lineno"> 590</span> </div>
<div class="line"><a name="l00591"></a><span class="lineno"> 591</span> </div>
<div class="line"><a name="l00592"></a><span class="lineno"> 592</span> </div>
<div class="line"><a name="l00593"></a><span class="lineno"> 593</span> <span class="keyword">template</span><<span class="keyword">typename</span> NumericT></div>
<div class="line"><a name="l00594"></a><span class="lineno"><a class="line" href="namespaceviennacl_1_1linalg_1_1cuda_1_1amg.html#a88cc74771dab339b07e06d16500dccb1"> 594</a></span> __global__ <span class="keywordtype">void</span> <a class="code" href="namespaceviennacl_1_1linalg_1_1cuda_1_1amg.html#a88cc74771dab339b07e06d16500dccb1">amg_interpol_sa_kernel</a>(</div>
<div class="line"><a name="l00595"></a><span class="lineno"> 595</span>  <span class="keyword">const</span> <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> *A_row_indices,</div>
<div class="line"><a name="l00596"></a><span class="lineno"> 596</span>  <span class="keyword">const</span> <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> *A_col_indices,</div>
<div class="line"><a name="l00597"></a><span class="lineno"> 597</span>  <span class="keyword">const</span> <a class="code" href="tests_2src_2bisect_8cpp.html#a52b5d30a2d7b064678644a3bf49b7f6c">NumericT</a> *A_elements,</div>
<div class="line"><a name="l00598"></a><span class="lineno"> 598</span>  <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> A_size1,</div>
<div class="line"><a name="l00599"></a><span class="lineno"> 599</span>  <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> A_nnz,</div>
<div class="line"><a name="l00600"></a><span class="lineno"> 600</span>  <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> *Jacobi_row_indices,</div>
<div class="line"><a name="l00601"></a><span class="lineno"> 601</span>  <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> *Jacobi_col_indices,</div>
<div class="line"><a name="l00602"></a><span class="lineno"> 602</span>  <a class="code" href="tests_2src_2bisect_8cpp.html#a52b5d30a2d7b064678644a3bf49b7f6c">NumericT</a> *Jacobi_elements,</div>
<div class="line"><a name="l00603"></a><span class="lineno"> 603</span>  <a class="code" href="tests_2src_2bisect_8cpp.html#a52b5d30a2d7b064678644a3bf49b7f6c">NumericT</a> omega</div>
<div class="line"><a name="l00604"></a><span class="lineno"> 604</span>  )</div>
<div class="line"><a name="l00605"></a><span class="lineno"> 605</span> {</div>
<div class="line"><a name="l00606"></a><span class="lineno"> 606</span>  <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> global_id = blockDim.x * blockIdx.x + threadIdx.x;</div>
<div class="line"><a name="l00607"></a><span class="lineno"> 607</span>  <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> global_size = gridDim.x * blockDim.x;</div>
<div class="line"><a name="l00608"></a><span class="lineno"> 608</span> </div>
<div class="line"><a name="l00609"></a><span class="lineno"> 609</span>  <span class="keywordflow">for</span> (<span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> <a class="code" href="namespaceviennacl.html#a0a574e6cd04ca0e42298b4ab845700e4">row</a> = global_id; <a class="code" href="namespaceviennacl.html#a0a574e6cd04ca0e42298b4ab845700e4">row</a> < A_size1; <a class="code" href="namespaceviennacl.html#a0a574e6cd04ca0e42298b4ab845700e4">row</a> += global_size)</div>
<div class="line"><a name="l00610"></a><span class="lineno"> 610</span>  {</div>
<div class="line"><a name="l00611"></a><span class="lineno"> 611</span>  <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> row_begin = A_row_indices[<a class="code" href="namespaceviennacl.html#a0a574e6cd04ca0e42298b4ab845700e4">row</a>];</div>
<div class="line"><a name="l00612"></a><span class="lineno"> 612</span>  <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> row_end = A_row_indices[<a class="code" href="namespaceviennacl.html#a0a574e6cd04ca0e42298b4ab845700e4">row</a>+1];</div>
<div class="line"><a name="l00613"></a><span class="lineno"> 613</span> </div>
<div class="line"><a name="l00614"></a><span class="lineno"> 614</span>  Jacobi_row_indices[<a class="code" href="namespaceviennacl.html#a0a574e6cd04ca0e42298b4ab845700e4">row</a>] = row_begin;</div>
<div class="line"><a name="l00615"></a><span class="lineno"> 615</span> </div>
<div class="line"><a name="l00616"></a><span class="lineno"> 616</span>  <span class="comment">// Step 1: Extract diagonal:</span></div>
<div class="line"><a name="l00617"></a><span class="lineno"> 617</span>  <a class="code" href="tests_2src_2bisect_8cpp.html#a52b5d30a2d7b064678644a3bf49b7f6c">NumericT</a> <a class="code" href="namespaceviennacl.html#a507d2ac469c79997f2bb6e82b37b7483">diag</a> = 0;</div>
<div class="line"><a name="l00618"></a><span class="lineno"> 618</span>  <span class="keywordflow">for</span> (<span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> j = row_begin; j < row_end; ++j)</div>
<div class="line"><a name="l00619"></a><span class="lineno"> 619</span>  {</div>
<div class="line"><a name="l00620"></a><span class="lineno"> 620</span>  <span class="keywordflow">if</span> (A_col_indices[j] == <a class="code" href="namespaceviennacl.html#a0a574e6cd04ca0e42298b4ab845700e4">row</a>)</div>
<div class="line"><a name="l00621"></a><span class="lineno"> 621</span>  {</div>
<div class="line"><a name="l00622"></a><span class="lineno"> 622</span>  diag = A_elements[j];</div>
<div class="line"><a name="l00623"></a><span class="lineno"> 623</span>  <span class="keywordflow">break</span>;</div>
<div class="line"><a name="l00624"></a><span class="lineno"> 624</span>  }</div>
<div class="line"><a name="l00625"></a><span class="lineno"> 625</span>  }</div>
<div class="line"><a name="l00626"></a><span class="lineno"> 626</span> </div>
<div class="line"><a name="l00627"></a><span class="lineno"> 627</span>  <span class="comment">// Step 2: Write entries:</span></div>
<div class="line"><a name="l00628"></a><span class="lineno"> 628</span>  <span class="keywordflow">for</span> (<span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> j = row_begin; j < row_end; ++j)</div>
<div class="line"><a name="l00629"></a><span class="lineno"> 629</span>  {</div>
<div class="line"><a name="l00630"></a><span class="lineno"> 630</span>  <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> col_index = A_col_indices[j];</div>
<div class="line"><a name="l00631"></a><span class="lineno"> 631</span>  Jacobi_col_indices[j] = col_index;</div>
<div class="line"><a name="l00632"></a><span class="lineno"> 632</span> </div>
<div class="line"><a name="l00633"></a><span class="lineno"> 633</span>  <span class="keywordflow">if</span> (col_index == <a class="code" href="namespaceviennacl.html#a0a574e6cd04ca0e42298b4ab845700e4">row</a>)</div>
<div class="line"><a name="l00634"></a><span class="lineno"> 634</span>  Jacobi_elements[j] = <a class="code" href="tests_2src_2bisect_8cpp.html#a52b5d30a2d7b064678644a3bf49b7f6c">NumericT</a>(1) - omega;</div>
<div class="line"><a name="l00635"></a><span class="lineno"> 635</span>  <span class="keywordflow">else</span></div>
<div class="line"><a name="l00636"></a><span class="lineno"> 636</span>  Jacobi_elements[j] = - omega * A_elements[j] / <a class="code" href="namespaceviennacl.html#a507d2ac469c79997f2bb6e82b37b7483">diag</a>;</div>
<div class="line"><a name="l00637"></a><span class="lineno"> 637</span>  }</div>
<div class="line"><a name="l00638"></a><span class="lineno"> 638</span>  }</div>
<div class="line"><a name="l00639"></a><span class="lineno"> 639</span> </div>
<div class="line"><a name="l00640"></a><span class="lineno"> 640</span>  <span class="keywordflow">if</span> (global_id == 0)</div>
<div class="line"><a name="l00641"></a><span class="lineno"> 641</span>  Jacobi_row_indices[A_size1] = A_nnz; <span class="comment">// don't forget finalizer</span></div>
<div class="line"><a name="l00642"></a><span class="lineno"> 642</span> }</div>
<div class="line"><a name="l00643"></a><span class="lineno"> 643</span> </div>
<div class="line"><a name="l00644"></a><span class="lineno"> 644</span> </div>
<div class="line"><a name="l00645"></a><span class="lineno"> 645</span> </div>
<div class="line"><a name="l00653"></a><span class="lineno"> 653</span> <span class="keyword">template</span><<span class="keyword">typename</span> NumericT></div>
<div class="line"><a name="l00654"></a><span class="lineno"><a class="line" href="namespaceviennacl_1_1linalg_1_1cuda_1_1amg.html#a9cc8c1d739430a807751738aa5559a32"> 654</a></span> <span class="keywordtype">void</span> <a class="code" href="namespaceviennacl_1_1linalg_1_1cuda_1_1amg.html#a9cc8c1d739430a807751738aa5559a32">amg_interpol_sa</a>(<a class="code" href="classviennacl_1_1compressed__matrix.html">compressed_matrix<NumericT></a> <span class="keyword">const</span> & A,</div>
<div class="line"><a name="l00655"></a><span class="lineno"> 655</span>  <a class="code" href="classviennacl_1_1compressed__matrix.html">compressed_matrix<NumericT></a> & P,</div>
<div class="line"><a name="l00656"></a><span class="lineno"> 656</span>  <a class="code" href="structviennacl_1_1linalg_1_1detail_1_1amg_1_1amg__level__context.html">viennacl::linalg::detail::amg::amg_level_context</a> & amg_context,</div>
<div class="line"><a name="l00657"></a><span class="lineno"> 657</span>  <a class="code" href="classviennacl_1_1linalg_1_1amg__tag.html">viennacl::linalg::amg_tag</a> & tag)</div>
<div class="line"><a name="l00658"></a><span class="lineno"> 658</span> {</div>
<div class="line"><a name="l00659"></a><span class="lineno"> 659</span>  (void)tag;</div>
<div class="line"><a name="l00660"></a><span class="lineno"> 660</span>  <a class="code" href="classviennacl_1_1compressed__matrix.html">viennacl::compressed_matrix<NumericT></a> P_tentative(A.<a class="code" href="classviennacl_1_1compressed__matrix.html#a463cf1739f9cdd387aa185cb574db183">size1</a>(), amg_context.<a class="code" href="structviennacl_1_1linalg_1_1detail_1_1amg_1_1amg__level__context.html#aac5a6ef480cf58fb8fa490760bb94e35">num_coarse_</a>, A.<a class="code" href="classviennacl_1_1compressed__matrix.html#a463cf1739f9cdd387aa185cb574db183">size1</a>(), <a class="code" href="namespaceviennacl_1_1traits.html#a6707f5dab8f482170d2046a605f46ef8">viennacl::traits::context</a>(A));</div>
<div class="line"><a name="l00661"></a><span class="lineno"> 661</span> </div>
<div class="line"><a name="l00662"></a><span class="lineno"> 662</span>  <span class="comment">// form tentative operator:</span></div>
<div class="line"><a name="l00663"></a><span class="lineno"> 663</span>  <a class="code" href="namespaceviennacl_1_1linalg_1_1cuda_1_1amg.html#a9cb19def4af89cc7d5e58b7599d5c2d6">amg_interpol_ag</a>(A, P_tentative, amg_context, tag);</div>
<div class="line"><a name="l00664"></a><span class="lineno"> 664</span> </div>
<div class="line"><a name="l00665"></a><span class="lineno"> 665</span>  <a class="code" href="classviennacl_1_1compressed__matrix.html">viennacl::compressed_matrix<NumericT></a> Jacobi(A.<a class="code" href="classviennacl_1_1compressed__matrix.html#a463cf1739f9cdd387aa185cb574db183">size1</a>(), A.<a class="code" href="classviennacl_1_1compressed__matrix.html#a463cf1739f9cdd387aa185cb574db183">size1</a>(), A.<a class="code" href="classviennacl_1_1compressed__matrix.html#ae69ca21ded644fdd0c7a5168011b13ed">nnz</a>(), <a class="code" href="namespaceviennacl_1_1traits.html#a6707f5dab8f482170d2046a605f46ef8">viennacl::traits::context</a>(A));</div>
<div class="line"><a name="l00666"></a><span class="lineno"> 666</span> </div>
<div class="line"><a name="l00667"></a><span class="lineno"> 667</span>  amg_interpol_sa_kernel<<<128, 128>>>(viennacl::cuda_arg<unsigned int>(A.<a class="code" href="classviennacl_1_1compressed__matrix.html#af71dec61a70e8df4f78a527aa989a106">handle1</a>().cuda_handle()),</div>
<div class="line"><a name="l00668"></a><span class="lineno"> 668</span>  viennacl::cuda_arg<unsigned int>(A.<a class="code" href="classviennacl_1_1compressed__matrix.html#a91f5145351151a66f916bdc3901206f2">handle2</a>().cuda_handle()),</div>
<div class="line"><a name="l00669"></a><span class="lineno"> 669</span>  viennacl::cuda_arg<NumericT>(A.<a class="code" href="classviennacl_1_1compressed__matrix.html#a87a0ad5f26983b1c2d24ee302d886562">handle</a>().cuda_handle()),</div>
<div class="line"><a name="l00670"></a><span class="lineno"> 670</span>  static_cast<unsigned int>(A.<a class="code" href="classviennacl_1_1compressed__matrix.html#a463cf1739f9cdd387aa185cb574db183">size1</a>()),</div>
<div class="line"><a name="l00671"></a><span class="lineno"> 671</span>  static_cast<unsigned int>(A.<a class="code" href="classviennacl_1_1compressed__matrix.html#ae69ca21ded644fdd0c7a5168011b13ed">nnz</a>()),</div>
<div class="line"><a name="l00672"></a><span class="lineno"> 672</span>  viennacl::cuda_arg<unsigned int>(Jacobi.handle1().cuda_handle()),</div>
<div class="line"><a name="l00673"></a><span class="lineno"> 673</span>  viennacl::cuda_arg<unsigned int>(Jacobi.handle2().cuda_handle()),</div>
<div class="line"><a name="l00674"></a><span class="lineno"> 674</span>  viennacl::cuda_arg<NumericT>(Jacobi.handle().cuda_handle()),</div>
<div class="line"><a name="l00675"></a><span class="lineno"> 675</span>  <a class="code" href="tests_2src_2bisect_8cpp.html#a52b5d30a2d7b064678644a3bf49b7f6c">NumericT</a>(tag.<a class="code" href="classviennacl_1_1linalg_1_1amg__tag.html#ac040fe4a5f3a3ac02bcc951d6a72837b">get_jacobi_weight</a>())</div>
<div class="line"><a name="l00676"></a><span class="lineno"> 676</span>  );</div>
<div class="line"><a name="l00677"></a><span class="lineno"> 677</span>  <a class="code" href="linalg_2cuda_2common_8hpp.html#acdb31f22f4d1e12f1c2a27d4c4aa6865">VIENNACL_CUDA_LAST_ERROR_CHECK</a>(<span class="stringliteral">"amg_interpol_sa_kernel"</span>);</div>
<div class="line"><a name="l00678"></a><span class="lineno"> 678</span> </div>
<div class="line"><a name="l00679"></a><span class="lineno"> 679</span>  P = <a class="code" href="namespaceviennacl_1_1linalg.html#aa18d10f8a90e38bd9ff43c650fc670ef">viennacl::linalg::prod</a>(Jacobi, P_tentative);</div>
<div class="line"><a name="l00680"></a><span class="lineno"> 680</span> </div>
<div class="line"><a name="l00681"></a><span class="lineno"> 681</span>  P.<a class="code" href="classviennacl_1_1compressed__matrix.html#ab5922a97b73b869fbeeb6a2fa40e3b06">generate_row_block_information</a>();</div>
<div class="line"><a name="l00682"></a><span class="lineno"> 682</span> }</div>
<div class="line"><a name="l00683"></a><span class="lineno"> 683</span> </div>
<div class="line"><a name="l00684"></a><span class="lineno"> 684</span> </div>
<div class="line"><a name="l00692"></a><span class="lineno"> 692</span> <span class="keyword">template</span><<span class="keyword">typename</span> MatrixT></div>
<div class="line"><a name="l00693"></a><span class="lineno"><a class="line" href="namespaceviennacl_1_1linalg_1_1cuda_1_1amg.html#a9fce75799e03103c73d005c09ac361e2"> 693</a></span> <span class="keywordtype">void</span> <a class="code" href="namespaceviennacl_1_1linalg_1_1cuda_1_1amg.html#a9fce75799e03103c73d005c09ac361e2">amg_interpol</a>(MatrixT <span class="keyword">const</span> & A,</div>
<div class="line"><a name="l00694"></a><span class="lineno"> 694</span>  MatrixT & P,</div>
<div class="line"><a name="l00695"></a><span class="lineno"> 695</span>  <a class="code" href="structviennacl_1_1linalg_1_1detail_1_1amg_1_1amg__level__context.html">viennacl::linalg::detail::amg::amg_level_context</a> & amg_context,</div>
<div class="line"><a name="l00696"></a><span class="lineno"> 696</span>  <a class="code" href="classviennacl_1_1linalg_1_1amg__tag.html">viennacl::linalg::amg_tag</a> & tag)</div>
<div class="line"><a name="l00697"></a><span class="lineno"> 697</span> {</div>
<div class="line"><a name="l00698"></a><span class="lineno"> 698</span>  <span class="keywordflow">switch</span> (tag.<a class="code" href="classviennacl_1_1linalg_1_1amg__tag.html#afb4b14cf0b9e99161fa8c1da4647ad0d">get_interpolation_method</a>())</div>
<div class="line"><a name="l00699"></a><span class="lineno"> 699</span>  {</div>
<div class="line"><a name="l00700"></a><span class="lineno"> 700</span>  <span class="keywordflow">case</span> <a class="code" href="namespaceviennacl_1_1linalg.html#a9933216144a64dbd433ec02c95bbfdd7a31dbd459c3ba8068280a6ec1bca00482">viennacl::linalg::AMG_INTERPOLATION_METHOD_AGGREGATION</a>: <a class="code" href="namespaceviennacl_1_1linalg_1_1cuda_1_1amg.html#a9cb19def4af89cc7d5e58b7599d5c2d6">amg_interpol_ag</a> (A, P, amg_context, tag); <span class="keywordflow">break</span>;</div>
<div class="line"><a name="l00701"></a><span class="lineno"> 701</span>  <span class="keywordflow">case</span> <a class="code" href="namespaceviennacl_1_1linalg.html#a9933216144a64dbd433ec02c95bbfdd7afcffee5ed6e7ad032a9ffebe615b5932">viennacl::linalg::AMG_INTERPOLATION_METHOD_SMOOTHED_AGGREGATION</a>: <a class="code" href="namespaceviennacl_1_1linalg_1_1cuda_1_1amg.html#a9cc8c1d739430a807751738aa5559a32">amg_interpol_sa</a> (A, P, amg_context, tag); <span class="keywordflow">break</span>;</div>
<div class="line"><a name="l00702"></a><span class="lineno"> 702</span>  <span class="keywordflow">default</span>: <span class="keywordflow">throw</span> std::runtime_error(<span class="stringliteral">"Not implemented yet!"</span>);</div>
<div class="line"><a name="l00703"></a><span class="lineno"> 703</span>  }</div>
<div class="line"><a name="l00704"></a><span class="lineno"> 704</span> }</div>
<div class="line"><a name="l00705"></a><span class="lineno"> 705</span> </div>
<div class="line"><a name="l00706"></a><span class="lineno"> 706</span> </div>
<div class="line"><a name="l00707"></a><span class="lineno"> 707</span> <span class="keyword">template</span><<span class="keyword">typename</span> NumericT></div>
<div class="line"><a name="l00708"></a><span class="lineno"><a class="line" href="namespaceviennacl_1_1linalg_1_1cuda_1_1amg.html#a644a8509ef334ceb151a8ffa6d8f6111"> 708</a></span> __global__ <span class="keywordtype">void</span> <a class="code" href="namespaceviennacl_1_1linalg_1_1cuda_1_1amg.html#a644a8509ef334ceb151a8ffa6d8f6111">compressed_matrix_assign_to_dense</a>(</div>
<div class="line"><a name="l00709"></a><span class="lineno"> 709</span>  <span class="keyword">const</span> <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> * row_indices,</div>
<div class="line"><a name="l00710"></a><span class="lineno"> 710</span>  <span class="keyword">const</span> <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> * column_indices,</div>
<div class="line"><a name="l00711"></a><span class="lineno"> 711</span>  <span class="keyword">const</span> <a class="code" href="tests_2src_2bisect_8cpp.html#a52b5d30a2d7b064678644a3bf49b7f6c">NumericT</a> * elements,</div>
<div class="line"><a name="l00712"></a><span class="lineno"> 712</span>  <a class="code" href="tests_2src_2bisect_8cpp.html#a52b5d30a2d7b064678644a3bf49b7f6c">NumericT</a> *B,</div>
<div class="line"><a name="l00713"></a><span class="lineno"> 713</span>  <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> B_row_start, <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> B_col_start,</div>
<div class="line"><a name="l00714"></a><span class="lineno"> 714</span>  <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> B_row_inc, <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> B_col_inc,</div>
<div class="line"><a name="l00715"></a><span class="lineno"> 715</span>  <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> B_row_size, <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> B_col_size,</div>
<div class="line"><a name="l00716"></a><span class="lineno"> 716</span>  <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> B_internal_rows, <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> B_internal_cols)</div>
<div class="line"><a name="l00717"></a><span class="lineno"> 717</span> {</div>
<div class="line"><a name="l00718"></a><span class="lineno"> 718</span>  <span class="keywordflow">for</span> (<span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> <a class="code" href="namespaceviennacl.html#a0a574e6cd04ca0e42298b4ab845700e4">row</a> = blockDim.x * blockIdx.x + threadIdx.x;</div>
<div class="line"><a name="l00719"></a><span class="lineno"> 719</span>  <a class="code" href="namespaceviennacl.html#a0a574e6cd04ca0e42298b4ab845700e4">row</a> < B_row_size;</div>
<div class="line"><a name="l00720"></a><span class="lineno"> 720</span>  <a class="code" href="namespaceviennacl.html#a0a574e6cd04ca0e42298b4ab845700e4">row</a> += gridDim.x * blockDim.x)</div>
<div class="line"><a name="l00721"></a><span class="lineno"> 721</span>  {</div>
<div class="line"><a name="l00722"></a><span class="lineno"> 722</span>  <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> row_end = row_indices[<a class="code" href="namespaceviennacl.html#a0a574e6cd04ca0e42298b4ab845700e4">row</a>+1];</div>
<div class="line"><a name="l00723"></a><span class="lineno"> 723</span>  <span class="keywordflow">for</span> (<span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> j = row_indices[<a class="code" href="namespaceviennacl.html#a0a574e6cd04ca0e42298b4ab845700e4">row</a>]; j<row_end; j++)</div>
<div class="line"><a name="l00724"></a><span class="lineno"> 724</span>  B[(B_row_start + <a class="code" href="namespaceviennacl.html#a0a574e6cd04ca0e42298b4ab845700e4">row</a> * B_row_inc) * B_internal_cols + B_col_start + column_indices[j] * B_col_inc] = elements[j];</div>
<div class="line"><a name="l00725"></a><span class="lineno"> 725</span>  }</div>
<div class="line"><a name="l00726"></a><span class="lineno"> 726</span> }</div>
<div class="line"><a name="l00727"></a><span class="lineno"> 727</span> </div>
<div class="line"><a name="l00728"></a><span class="lineno"> 728</span> </div>
<div class="line"><a name="l00729"></a><span class="lineno"> 729</span> <span class="keyword">template</span><<span class="keyword">typename</span> NumericT, <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> AlignmentV></div>
<div class="line"><a name="l00730"></a><span class="lineno"><a class="line" href="namespaceviennacl_1_1linalg_1_1cuda_1_1amg.html#ac6c4463d335fc3dd604639b87ed6229d"> 730</a></span> <span class="keywordtype">void</span> <a class="code" href="namespaceviennacl_1_1linalg_1_1cuda_1_1amg.html#ac6c4463d335fc3dd604639b87ed6229d">assign_to_dense</a>(<a class="code" href="classviennacl_1_1compressed__matrix.html">viennacl::compressed_matrix<NumericT, AlignmentV></a> <span class="keyword">const</span> & A,</div>
<div class="line"><a name="l00731"></a><span class="lineno"> 731</span>  <a class="code" href="classviennacl_1_1matrix__base.html">viennacl::matrix_base<NumericT></a> & B)</div>
<div class="line"><a name="l00732"></a><span class="lineno"> 732</span> {</div>
<div class="line"><a name="l00733"></a><span class="lineno"> 733</span>  compressed_matrix_assign_to_dense<<<128, 128>>>(viennacl::cuda_arg<unsigned int>(A.<a class="code" href="classviennacl_1_1compressed__matrix.html#af71dec61a70e8df4f78a527aa989a106">handle1</a>().cuda_handle()),</div>
<div class="line"><a name="l00734"></a><span class="lineno"> 734</span>  viennacl::cuda_arg<unsigned int>(A.<a class="code" href="classviennacl_1_1compressed__matrix.html#a91f5145351151a66f916bdc3901206f2">handle2</a>().cuda_handle()),</div>
<div class="line"><a name="l00735"></a><span class="lineno"> 735</span>  viennacl::cuda_arg<NumericT>(A.<a class="code" href="classviennacl_1_1compressed__matrix.html#a87a0ad5f26983b1c2d24ee302d886562">handle</a>().cuda_handle()),</div>
<div class="line"><a name="l00736"></a><span class="lineno"> 736</span>  viennacl::cuda_arg<NumericT>(B),</div>
<div class="line"><a name="l00737"></a><span class="lineno"> 737</span>  <span class="keyword">static_cast<</span><span class="keywordtype">unsigned</span> <span class="keywordtype">int</span><span class="keyword">></span>(<a class="code" href="namespaceviennacl_1_1traits.html#ae601425decc5f1a8763ab5272e9e492f">viennacl::traits::start1</a>(B)), static_cast<unsigned int>(<a class="code" href="namespaceviennacl_1_1traits.html#ac53fc8cc9836953dc87aaaaa56f382c2">viennacl::traits::start2</a>(B)),</div>
<div class="line"><a name="l00738"></a><span class="lineno"> 738</span>  static_cast<unsigned int>(<a class="code" href="namespaceviennacl_1_1traits.html#a53a39f11907d9098e6f144c87998fe5e">viennacl::traits::stride1</a>(B)), static_cast<unsigned int>(<a class="code" href="namespaceviennacl_1_1traits.html#ace596004f16c075adbfcd329e6c60e91">viennacl::traits::stride2</a>(B)),</div>
<div class="line"><a name="l00739"></a><span class="lineno"> 739</span>  static_cast<unsigned int>(<a class="code" href="namespaceviennacl_1_1traits.html#aa756f5d6820722094cae0d8b9bb6d5e2">viennacl::traits::size1</a>(B)), static_cast<unsigned int>(<a class="code" href="namespaceviennacl_1_1traits.html#a3658e7c29ac0f60a20cb5871f5b5fd98">viennacl::traits::size2</a>(B)),</div>
<div class="line"><a name="l00740"></a><span class="lineno"> 740</span>  static_cast<unsigned int>(<a class="code" href="namespaceviennacl_1_1traits.html#aedc426f055f1b4c5d00111cc8a46e50d">viennacl::traits::internal_size1</a>(B)), static_cast<unsigned int>(<a class="code" href="namespaceviennacl_1_1traits.html#a2cd7269b5d00b5ebadab1c4b5a94a7c1">viennacl::traits::internal_size2</a>(B))</div>
<div class="line"><a name="l00741"></a><span class="lineno"> 741</span>  );</div>
<div class="line"><a name="l00742"></a><span class="lineno"> 742</span>  <a class="code" href="linalg_2cuda_2common_8hpp.html#acdb31f22f4d1e12f1c2a27d4c4aa6865">VIENNACL_CUDA_LAST_ERROR_CHECK</a>(<span class="stringliteral">"compressed_matrix_assign_to_dense"</span>);</div>
<div class="line"><a name="l00743"></a><span class="lineno"> 743</span> }</div>
<div class="line"><a name="l00744"></a><span class="lineno"> 744</span> </div>
<div class="line"><a name="l00745"></a><span class="lineno"> 745</span> </div>
<div class="line"><a name="l00746"></a><span class="lineno"> 746</span> </div>
<div class="line"><a name="l00747"></a><span class="lineno"> 747</span> </div>
<div class="line"><a name="l00748"></a><span class="lineno"> 748</span> <span class="keyword">template</span><<span class="keyword">typename</span> NumericT></div>
<div class="line"><a name="l00749"></a><span class="lineno"><a class="line" href="namespaceviennacl_1_1linalg_1_1cuda_1_1amg.html#acff2449ac77ddd8c483db7f168b54ca6"> 749</a></span> __global__ <span class="keywordtype">void</span> <a class="code" href="namespaceviennacl_1_1linalg_1_1cuda_1_1amg.html#acff2449ac77ddd8c483db7f168b54ca6">compressed_matrix_smooth_jacobi_kernel</a>(</div>
<div class="line"><a name="l00750"></a><span class="lineno"> 750</span>  <span class="keyword">const</span> <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> * row_indices,</div>
<div class="line"><a name="l00751"></a><span class="lineno"> 751</span>  <span class="keyword">const</span> <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> * column_indices,</div>
<div class="line"><a name="l00752"></a><span class="lineno"> 752</span>  <span class="keyword">const</span> <a class="code" href="tests_2src_2bisect_8cpp.html#a52b5d30a2d7b064678644a3bf49b7f6c">NumericT</a> * elements,</div>
<div class="line"><a name="l00753"></a><span class="lineno"> 753</span>  <a class="code" href="tests_2src_2bisect_8cpp.html#a52b5d30a2d7b064678644a3bf49b7f6c">NumericT</a> weight,</div>
<div class="line"><a name="l00754"></a><span class="lineno"> 754</span>  <span class="keyword">const</span> <a class="code" href="tests_2src_2bisect_8cpp.html#a52b5d30a2d7b064678644a3bf49b7f6c">NumericT</a> * x_old,</div>
<div class="line"><a name="l00755"></a><span class="lineno"> 755</span>  <a class="code" href="tests_2src_2bisect_8cpp.html#a52b5d30a2d7b064678644a3bf49b7f6c">NumericT</a> * x_new,</div>
<div class="line"><a name="l00756"></a><span class="lineno"> 756</span>  <span class="keyword">const</span> <a class="code" href="tests_2src_2bisect_8cpp.html#a52b5d30a2d7b064678644a3bf49b7f6c">NumericT</a> * rhs,</div>
<div class="line"><a name="l00757"></a><span class="lineno"> 757</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="l00758"></a><span class="lineno"> 758</span> {</div>
<div class="line"><a name="l00759"></a><span class="lineno"> 759</span>  <span class="keywordflow">for</span> (<span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> <a class="code" href="namespaceviennacl.html#a0a574e6cd04ca0e42298b4ab845700e4">row</a> = blockDim.x * blockIdx.x + threadIdx.x;</div>
<div class="line"><a name="l00760"></a><span class="lineno"> 760</span>  <a class="code" href="namespaceviennacl.html#a0a574e6cd04ca0e42298b4ab845700e4">row</a> < size;</div>
<div class="line"><a name="l00761"></a><span class="lineno"> 761</span>  <a class="code" href="namespaceviennacl.html#a0a574e6cd04ca0e42298b4ab845700e4">row</a> += gridDim.x * blockDim.x)</div>
<div class="line"><a name="l00762"></a><span class="lineno"> 762</span>  {</div>
<div class="line"><a name="l00763"></a><span class="lineno"> 763</span>  <a class="code" href="tests_2src_2bisect_8cpp.html#a52b5d30a2d7b064678644a3bf49b7f6c">NumericT</a> <a class="code" href="namespaceviennacl_1_1linalg.html#a4117795095db49147ba7305d3e0a1af5">sum</a> = <a class="code" href="tests_2src_2bisect_8cpp.html#a52b5d30a2d7b064678644a3bf49b7f6c">NumericT</a>(0);</div>
<div class="line"><a name="l00764"></a><span class="lineno"> 764</span>  <a class="code" href="tests_2src_2bisect_8cpp.html#a52b5d30a2d7b064678644a3bf49b7f6c">NumericT</a> <a class="code" href="namespaceviennacl.html#a507d2ac469c79997f2bb6e82b37b7483">diag</a> = <a class="code" href="tests_2src_2bisect_8cpp.html#a52b5d30a2d7b064678644a3bf49b7f6c">NumericT</a>(1);</div>
<div class="line"><a name="l00765"></a><span class="lineno"> 765</span>  <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> row_end = row_indices[<a class="code" href="namespaceviennacl.html#a0a574e6cd04ca0e42298b4ab845700e4">row</a>+1];</div>
<div class="line"><a name="l00766"></a><span class="lineno"> 766</span>  <span class="keywordflow">for</span> (<span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> j = row_indices[<a class="code" href="namespaceviennacl.html#a0a574e6cd04ca0e42298b4ab845700e4">row</a>]; j < row_end; ++j)</div>
<div class="line"><a name="l00767"></a><span class="lineno"> 767</span>  {</div>
<div class="line"><a name="l00768"></a><span class="lineno"> 768</span>  <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> col = column_indices[j];</div>
<div class="line"><a name="l00769"></a><span class="lineno"> 769</span>  <span class="keywordflow">if</span> (col == <a class="code" href="namespaceviennacl.html#a0a574e6cd04ca0e42298b4ab845700e4">row</a>)</div>
<div class="line"><a name="l00770"></a><span class="lineno"> 770</span>  diag = elements[j];</div>
<div class="line"><a name="l00771"></a><span class="lineno"> 771</span>  <span class="keywordflow">else</span></div>
<div class="line"><a name="l00772"></a><span class="lineno"> 772</span>  sum += elements[j] * x_old[col];</div>
<div class="line"><a name="l00773"></a><span class="lineno"> 773</span>  }</div>
<div class="line"><a name="l00774"></a><span class="lineno"> 774</span>  x_new[<a class="code" href="namespaceviennacl.html#a0a574e6cd04ca0e42298b4ab845700e4">row</a>] = weight * (rhs[<a class="code" href="namespaceviennacl.html#a0a574e6cd04ca0e42298b4ab845700e4">row</a>] - <a class="code" href="namespaceviennacl_1_1linalg.html#a4117795095db49147ba7305d3e0a1af5">sum</a>) / diag + (<a class="code" href="tests_2src_2bisect_8cpp.html#a52b5d30a2d7b064678644a3bf49b7f6c">NumericT</a>(1) - weight) * x_old[<a class="code" href="namespaceviennacl.html#a0a574e6cd04ca0e42298b4ab845700e4">row</a>];</div>
<div class="line"><a name="l00775"></a><span class="lineno"> 775</span>  }</div>
<div class="line"><a name="l00776"></a><span class="lineno"> 776</span> }</div>
<div class="line"><a name="l00777"></a><span class="lineno"> 777</span> </div>
<div class="line"><a name="l00778"></a><span class="lineno"> 778</span> </div>
<div class="line"><a name="l00779"></a><span class="lineno"> 779</span> </div>
<div class="line"><a name="l00780"></a><span class="lineno"> 780</span> </div>
<div class="line"><a name="l00790"></a><span class="lineno"> 790</span> <span class="keyword">template</span><<span class="keyword">typename</span> NumericT></div>
<div class="line"><a name="l00791"></a><span class="lineno"><a class="line" href="namespaceviennacl_1_1linalg_1_1cuda_1_1amg.html#aed74cfedec05f6e080eee9abdd60f123"> 791</a></span> <span class="keywordtype">void</span> <a class="code" href="namespaceviennacl_1_1linalg_1_1cuda_1_1amg.html#aed74cfedec05f6e080eee9abdd60f123">smooth_jacobi</a>(<span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> iterations,</div>
<div class="line"><a name="l00792"></a><span class="lineno"> 792</span>  <a class="code" href="classviennacl_1_1compressed__matrix.html">compressed_matrix<NumericT></a> <span class="keyword">const</span> & A,</div>
<div class="line"><a name="l00793"></a><span class="lineno"> 793</span>  <a class="code" href="classviennacl_1_1vector.html">vector<NumericT></a> & x,</div>
<div class="line"><a name="l00794"></a><span class="lineno"> 794</span>  <a class="code" href="classviennacl_1_1vector.html">vector<NumericT></a> & x_backup,</div>
<div class="line"><a name="l00795"></a><span class="lineno"> 795</span>  <a class="code" href="classviennacl_1_1vector.html">vector<NumericT></a> <span class="keyword">const</span> & rhs_smooth,</div>
<div class="line"><a name="l00796"></a><span class="lineno"> 796</span>  <a class="code" href="tests_2src_2bisect_8cpp.html#a52b5d30a2d7b064678644a3bf49b7f6c">NumericT</a> weight)</div>
<div class="line"><a name="l00797"></a><span class="lineno"> 797</span> {</div>
<div class="line"><a name="l00798"></a><span class="lineno"> 798</span>  <span class="keywordflow">for</span> (<span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> i=0; i<iterations; ++i)</div>
<div class="line"><a name="l00799"></a><span class="lineno"> 799</span>  {</div>
<div class="line"><a name="l00800"></a><span class="lineno"> 800</span>  x_backup = x;</div>
<div class="line"><a name="l00801"></a><span class="lineno"> 801</span> </div>
<div class="line"><a name="l00802"></a><span class="lineno"> 802</span>  compressed_matrix_smooth_jacobi_kernel<<<128, 128>>>(viennacl::cuda_arg<unsigned int>(A.<a class="code" href="classviennacl_1_1compressed__matrix.html#af71dec61a70e8df4f78a527aa989a106">handle1</a>().cuda_handle()),</div>
<div class="line"><a name="l00803"></a><span class="lineno"> 803</span>  viennacl::cuda_arg<unsigned int>(A.<a class="code" href="classviennacl_1_1compressed__matrix.html#a91f5145351151a66f916bdc3901206f2">handle2</a>().cuda_handle()),</div>
<div class="line"><a name="l00804"></a><span class="lineno"> 804</span>  viennacl::cuda_arg<NumericT>(A.<a class="code" href="classviennacl_1_1compressed__matrix.html#a87a0ad5f26983b1c2d24ee302d886562">handle</a>().cuda_handle()),</div>
<div class="line"><a name="l00805"></a><span class="lineno"> 805</span>  static_cast<NumericT>(weight),</div>
<div class="line"><a name="l00806"></a><span class="lineno"> 806</span>  <a class="code" href="namespaceviennacl.html#ae7d5db0c2c91be75218db5b52c4d13da">viennacl::cuda_arg</a>(x_backup),</div>
<div class="line"><a name="l00807"></a><span class="lineno"> 807</span>  <a class="code" href="namespaceviennacl.html#ae7d5db0c2c91be75218db5b52c4d13da">viennacl::cuda_arg</a>(x),</div>
<div class="line"><a name="l00808"></a><span class="lineno"> 808</span>  <a class="code" href="namespaceviennacl.html#ae7d5db0c2c91be75218db5b52c4d13da">viennacl::cuda_arg</a>(rhs_smooth),</div>
<div class="line"><a name="l00809"></a><span class="lineno"> 809</span>  <span class="keyword">static_cast<</span><span class="keywordtype">unsigned</span> <span class="keywordtype">int</span><span class="keyword">></span>(rhs_smooth.<a class="code" href="classviennacl_1_1vector__base.html#a15c47ae4326098aeaa4ed6b91fc6df9b">size</a>())</div>
<div class="line"><a name="l00810"></a><span class="lineno"> 810</span>  );</div>
<div class="line"><a name="l00811"></a><span class="lineno"> 811</span>  <a class="code" href="linalg_2cuda_2common_8hpp.html#acdb31f22f4d1e12f1c2a27d4c4aa6865">VIENNACL_CUDA_LAST_ERROR_CHECK</a>(<span class="stringliteral">"compressed_matrix_smooth_jacobi_kernel"</span>);</div>
<div class="line"><a name="l00812"></a><span class="lineno"> 812</span>  }</div>
<div class="line"><a name="l00813"></a><span class="lineno"> 813</span> }</div>
<div class="line"><a name="l00814"></a><span class="lineno"> 814</span> </div>
<div class="line"><a name="l00815"></a><span class="lineno"> 815</span> </div>
<div class="line"><a name="l00816"></a><span class="lineno"> 816</span> } <span class="comment">//namespace amg</span></div>
<div class="line"><a name="l00817"></a><span class="lineno"> 817</span> } <span class="comment">//namespace host_based</span></div>
<div class="line"><a name="l00818"></a><span class="lineno"> 818</span> } <span class="comment">//namespace linalg</span></div>
<div class="line"><a name="l00819"></a><span class="lineno"> 819</span> } <span class="comment">//namespace viennacl</span></div>
<div class="line"><a name="l00820"></a><span class="lineno"> 820</span> </div>
<div class="line"><a name="l00821"></a><span class="lineno"> 821</span> <span class="preprocessor">#endif</span></div>
<div class="ttc" id="namespaceviennacl_1_1linalg_1_1cuda_1_1amg_html_ac1b1f9a0666d83c46ee9b4c5e25cd2c6"><div class="ttname"><a href="namespaceviennacl_1_1linalg_1_1cuda_1_1amg.html#ac1b1f9a0666d83c46ee9b4c5e25cd2c6">viennacl::linalg::cuda::amg::amg_influence_trivial</a></div><div class="ttdeci">void amg_influence_trivial(compressed_matrix< NumericT > const &A, viennacl::linalg::detail::amg::amg_level_context &amg_context, viennacl::linalg::amg_tag &tag)</div><div class="ttdoc">Routine for taking all connections in the matrix as strong. </div><div class="ttdef"><b>Definition:</b> <a href="cuda_2amg__operations_8hpp_source.html#l00074">amg_operations.hpp:74</a></div></div>
<div class="ttc" id="namespaceviennacl_1_1linalg_1_1cuda_1_1amg_html_a258c31de37f3c9831443b5f2ea5f4b19"><div class="ttname"><a href="namespaceviennacl_1_1linalg_1_1cuda_1_1amg.html#a258c31de37f3c9831443b5f2ea5f4b19">viennacl::linalg::cuda::amg::enumerate_coarse_points</a></div><div class="ttdeci">void enumerate_coarse_points(viennacl::linalg::detail::amg::amg_level_context &amg_context)</div><div class="ttdoc">Assign IDs to coarse points. </div><div class="ttdef"><b>Definition:</b> <a href="cuda_2amg__operations_8hpp_source.html#l00115">amg_operations.hpp:115</a></div></div>
<div class="ttc" id="classviennacl_1_1backend_1_1typesafe__host__array_html"><div class="ttname"><a href="classviennacl_1_1backend_1_1typesafe__host__array.html">viennacl::backend::typesafe_host_array</a></div><div class="ttdoc">Helper class implementing an array on the host. Default case: No conversion necessary. </div><div class="ttdef"><b>Definition:</b> <a href="backend_2util_8hpp_source.html#l00092">util.hpp:92</a></div></div>
<div class="ttc" id="namespaceviennacl_1_1linalg_1_1cuda_1_1amg_html_a4a60d31dadc06e04523a474fe067589f"><div class="ttname"><a href="namespaceviennacl_1_1linalg_1_1cuda_1_1amg.html#a4a60d31dadc06e04523a474fe067589f">viennacl::linalg::cuda::amg::amg_agg_merge_undecided_2</a></div><div class="ttdeci">__global__ void amg_agg_merge_undecided_2(unsigned int *point_types, unsigned int size)</div><div class="ttdef"><b>Definition:</b> <a href="cuda_2amg__operations_8hpp_source.html#l00445">amg_operations.hpp:445</a></div></div>
<div class="ttc" id="classviennacl_1_1linalg_1_1amg__tag_html_a37cf475ac353f457a3b14879a1140e14"><div class="ttname"><a href="classviennacl_1_1linalg_1_1amg__tag.html#a37cf475ac353f457a3b14879a1140e14">viennacl::linalg::amg_tag::get_coarsening_method</a></div><div class="ttdeci">amg_coarsening_method get_coarsening_method() const </div><div class="ttdoc">Returns the current coarsening strategy. </div><div class="ttdef"><b>Definition:</b> <a href="amg__base_8hpp_source.html#l00088">amg_base.hpp:88</a></div></div>
<div class="ttc" id="namespaceviennacl_1_1backend_html_a06bdedb2bc72dc1922cada91e9bbbd61"><div class="ttname"><a href="namespaceviennacl_1_1backend.html#a06bdedb2bc72dc1922cada91e9bbbd61">viennacl::backend::memory_write</a></div><div class="ttdeci">void memory_write(mem_handle &dst_buffer, vcl_size_t dst_offset, vcl_size_t bytes_to_write, const void *ptr, bool async=false)</div><div class="ttdoc">Writes data from main RAM identified by 'ptr' to the buffer identified by 'dst_buffer'. </div><div class="ttdef"><b>Definition:</b> <a href="memory_8hpp_source.html#l00220">memory.hpp:220</a></div></div>
<div class="ttc" id="namespaceviennacl_1_1traits_html_a53a39f11907d9098e6f144c87998fe5e"><div class="ttname"><a href="namespaceviennacl_1_1traits.html#a53a39f11907d9098e6f144c87998fe5e">viennacl::traits::stride1</a></div><div class="ttdeci">result_of::size_type< matrix_base< NumericT > >::type stride1(matrix_base< NumericT > const &s)</div><div class="ttdef"><b>Definition:</b> <a href="stride_8hpp_source.html#l00055">stride.hpp:55</a></div></div>
<div class="ttc" id="namespaceviennacl_1_1linalg_html_a4117795095db49147ba7305d3e0a1af5"><div class="ttname"><a href="namespaceviennacl_1_1linalg.html#a4117795095db49147ba7305d3e0a1af5">viennacl::linalg::sum</a></div><div class="ttdeci">viennacl::scalar_expression< const viennacl::vector_base< NumericT >, const viennacl::vector_base< NumericT >, viennacl::op_sum > sum(viennacl::vector_base< NumericT > const &x)</div><div class="ttdoc">User interface function for computing the sum of all elements of a vector. </div><div class="ttdef"><b>Definition:</b> <a href="sum_8hpp_source.html#l00045">sum.hpp:45</a></div></div>
<div class="ttc" id="namespaceviennacl_1_1linalg_1_1cuda_1_1amg_html_acff2449ac77ddd8c483db7f168b54ca6"><div class="ttname"><a href="namespaceviennacl_1_1linalg_1_1cuda_1_1amg.html#acff2449ac77ddd8c483db7f168b54ca6">viennacl::linalg::cuda::amg::compressed_matrix_smooth_jacobi_kernel</a></div><div class="ttdeci">__global__ void compressed_matrix_smooth_jacobi_kernel(const unsigned int *row_indices, const unsigned int *column_indices, const NumericT *elements, NumericT weight, const NumericT *x_old, NumericT *x_new, const NumericT *rhs, unsigned int size)</div><div class="ttdef"><b>Definition:</b> <a href="cuda_2amg__operations_8hpp_source.html#l00749">amg_operations.hpp:749</a></div></div>
<div class="ttc" id="structviennacl_1_1linalg_1_1detail_1_1amg_1_1amg__level__context_html"><div class="ttname"><a href="structviennacl_1_1linalg_1_1detail_1_1amg_1_1amg__level__context.html">viennacl::linalg::detail::amg::amg_level_context</a></div><div class="ttdef"><b>Definition:</b> <a href="amg__base_8hpp_source.html#l00167">amg_base.hpp:167</a></div></div>
<div class="ttc" id="namespaceviennacl_1_1linalg_1_1cuda_1_1amg_html_ad251eca20f99e452229d76237d791a0e"><div class="ttname"><a href="namespaceviennacl_1_1linalg_1_1cuda_1_1amg.html#ad251eca20f99e452229d76237d791a0e">viennacl::linalg::cuda::amg::amg_influence_advanced</a></div><div class="ttdeci">void amg_influence_advanced(compressed_matrix< NumericT > const &A, viennacl::linalg::detail::amg::amg_level_context &amg_context, viennacl::linalg::amg_tag &tag)</div><div class="ttdoc">Routine for extracting strongly connected points considering a user-provided threshold value...</div><div class="ttdef"><b>Definition:</b> <a href="cuda_2amg__operations_8hpp_source.html#l00094">amg_operations.hpp:94</a></div></div>
<div class="ttc" id="classviennacl_1_1compressed__matrix_html_a463cf1739f9cdd387aa185cb574db183"><div class="ttname"><a href="classviennacl_1_1compressed__matrix.html#a463cf1739f9cdd387aa185cb574db183">viennacl::compressed_matrix::size1</a></div><div class="ttdeci">const vcl_size_t & size1() const </div><div class="ttdoc">Returns the number of rows. </div><div class="ttdef"><b>Definition:</b> <a href="compressed__matrix_8hpp_source.html#l00927">compressed_matrix.hpp:927</a></div></div>
<div class="ttc" id="namespaceviennacl_1_1linalg_1_1cuda_1_1amg_html_ad5ee409e7f7e64210c17025092da89cd"><div class="ttname"><a href="namespaceviennacl_1_1linalg_1_1cuda_1_1amg.html#ad5ee409e7f7e64210c17025092da89cd">viennacl::linalg::cuda::amg::amg_pmis2_mark_mis_nodes</a></div><div class="ttdeci">__global__ void amg_pmis2_mark_mis_nodes(IndexT const *work_state, IndexT const *work_index, IndexT *point_types, IndexT *undecided_buffer, unsigned int size)</div><div class="ttdoc">CUDA kernel for marking MIS and non-MIS nodes. </div><div class="ttdef"><b>Definition:</b> <a href="cuda_2amg__operations_8hpp_source.html#l00229">amg_operations.hpp:229</a></div></div>
<div class="ttc" id="namespaceviennacl_1_1traits_html_aedc426f055f1b4c5d00111cc8a46e50d"><div class="ttname"><a href="namespaceviennacl_1_1traits.html#aedc426f055f1b4c5d00111cc8a46e50d">viennacl::traits::internal_size1</a></div><div class="ttdeci">vcl_size_t internal_size1(matrix_base< NumericT > const &mat)</div><div class="ttdoc">Helper routine for obtaining the internal number of entries per row of a ViennaCL matrix...</div><div class="ttdef"><b>Definition:</b> <a href="size_8hpp_source.html#l00386">size.hpp:386</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="namespaceviennacl_1_1linalg_1_1cuda_1_1amg_html_ae34c65a23e53597faff3357364fc4c2d"><div class="ttname"><a href="namespaceviennacl_1_1linalg_1_1cuda_1_1amg.html#ae34c65a23e53597faff3357364fc4c2d">viennacl::linalg::cuda::amg::amg_pmis2_init_workdata</a></div><div class="ttdeci">__global__ void amg_pmis2_init_workdata(IndexT *work_state, IndexT *work_random, IndexT *work_index, IndexT const *point_types, IndexT const *random_weights, unsigned int size)</div><div class="ttdoc">CUDA kernel initializing the work vectors at each PMIS iteration. </div><div class="ttdef"><b>Definition:</b> <a href="cuda_2amg__operations_8hpp_source.html#l00139">amg_operations.hpp:139</a></div></div>
<div class="ttc" id="classviennacl_1_1linalg_1_1amg__tag_html_ac040fe4a5f3a3ac02bcc951d6a72837b"><div class="ttname"><a href="classviennacl_1_1linalg_1_1amg__tag.html#ac040fe4a5f3a3ac02bcc951d6a72837b">viennacl::linalg::amg_tag::get_jacobi_weight</a></div><div class="ttdeci">double get_jacobi_weight() const </div><div class="ttdoc">Returns the Jacobi smoother weight (damping). </div><div class="ttdef"><b>Definition:</b> <a href="amg__base_8hpp_source.html#l00113">amg_base.hpp:113</a></div></div>
<div class="ttc" id="namespaceviennacl_1_1traits_html_a2cd7269b5d00b5ebadab1c4b5a94a7c1"><div class="ttname"><a href="namespaceviennacl_1_1traits.html#a2cd7269b5d00b5ebadab1c4b5a94a7c1">viennacl::traits::internal_size2</a></div><div class="ttdeci">vcl_size_t internal_size2(matrix_base< NumericT > const &mat)</div><div class="ttdoc">Helper routine for obtaining the internal number of entries per column of a ViennaCL matrix...</div><div class="ttdef"><b>Definition:</b> <a href="size_8hpp_source.html#l00394">size.hpp:394</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="namespaceviennacl_1_1traits_html_a09997870f4802fa5d4ac2c43cf4020d1"><div class="ttname"><a href="namespaceviennacl_1_1traits.html#a09997870f4802fa5d4ac2c43cf4020d1">viennacl::traits::stride</a></div><div class="ttdeci">result_of::size_type< viennacl::vector_base< T > >::type stride(viennacl::vector_base< T > const &s)</div><div class="ttdef"><b>Definition:</b> <a href="stride_8hpp_source.html#l00045">stride.hpp:45</a></div></div>
<div class="ttc" id="namespaceviennacl_1_1traits_html_ae601425decc5f1a8763ab5272e9e492f"><div class="ttname"><a href="namespaceviennacl_1_1traits.html#ae601425decc5f1a8763ab5272e9e492f">viennacl::traits::start1</a></div><div class="ttdeci">result_of::size_type< T >::type start1(T const &obj)</div><div class="ttdef"><b>Definition:</b> <a href="start_8hpp_source.html#l00065">start.hpp:65</a></div></div>
<div class="ttc" id="namespaceviennacl_1_1linalg_1_1cuda_1_1amg_html_a9cb19def4af89cc7d5e58b7599d5c2d6"><div class="ttname"><a href="namespaceviennacl_1_1linalg_1_1cuda_1_1amg.html#a9cb19def4af89cc7d5e58b7599d5c2d6">viennacl::linalg::cuda::amg::amg_interpol_ag</a></div><div class="ttdeci">void amg_interpol_ag(compressed_matrix< NumericT > const &A, compressed_matrix< NumericT > &P, viennacl::linalg::detail::amg::amg_level_context &amg_context, viennacl::linalg::amg_tag &tag)</div><div class="ttdoc">AG (aggregation based) interpolation. Multi-Threaded! (VIENNACL_INTERPOL_SA) </div><div class="ttdef"><b>Definition:</b> <a href="cuda_2amg__operations_8hpp_source.html#l00572">amg_operations.hpp:572</a></div></div>
<div class="ttc" id="namespaceviennacl_1_1backend_html_a62854cfd6f04404b274f8ede36f63e2d"><div class="ttname"><a href="namespaceviennacl_1_1backend.html#a62854cfd6f04404b274f8ede36f63e2d">viennacl::backend::memory_read</a></div><div class="ttdeci">void memory_read(mem_handle const &src_buffer, vcl_size_t src_offset, vcl_size_t bytes_to_read, void *ptr, bool async=false)</div><div class="ttdoc">Reads data from a buffer back to main RAM. </div><div class="ttdef"><b>Definition:</b> <a href="memory_8hpp_source.html#l00261">memory.hpp:261</a></div></div>
<div class="ttc" id="namespaceviennacl_1_1linalg_html_a9933216144a64dbd433ec02c95bbfdd7a31dbd459c3ba8068280a6ec1bca00482"><div class="ttname"><a href="namespaceviennacl_1_1linalg.html#a9933216144a64dbd433ec02c95bbfdd7a31dbd459c3ba8068280a6ec1bca00482">viennacl::linalg::AMG_INTERPOLATION_METHOD_AGGREGATION</a></div><div class="ttdef"><b>Definition:</b> <a href="amg__base_8hpp_source.html#l00057">amg_base.hpp:57</a></div></div>
<div class="ttc" id="namespaceviennacl_1_1linalg_1_1cuda_1_1amg_html_a0397785aabbeaa292cf3fbfe0d758dc1"><div class="ttname"><a href="namespaceviennacl_1_1linalg_1_1cuda_1_1amg.html#a0397785aabbeaa292cf3fbfe0d758dc1">viennacl::linalg::cuda::amg::amg_coarse</a></div><div class="ttdeci">void amg_coarse(InternalT1 &A, viennacl::linalg::detail::amg::amg_level_context &amg_context, viennacl::linalg::amg_tag &tag)</div><div class="ttdoc">Calls the right coarsening procedure. </div><div class="ttdef"><b>Definition:</b> <a href="cuda_2amg__operations_8hpp_source.html#l00526">amg_operations.hpp:526</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="namespaceviennacl_1_1linalg_1_1cuda_1_1amg_html_affaef0634b3cfec5a940b278051cb21d"><div class="ttname"><a href="namespaceviennacl_1_1linalg_1_1cuda_1_1amg.html#affaef0634b3cfec5a940b278051cb21d">viennacl::linalg::cuda::amg::amg_agg_merge_undecided</a></div><div class="ttdeci">__global__ void amg_agg_merge_undecided(IndexT *point_types, IndexT *coarse_ids, IndexT const *influences_row, IndexT const *influences_id, unsigned int size)</div><div class="ttdef"><b>Definition:</b> <a href="cuda_2amg__operations_8hpp_source.html#l00416">amg_operations.hpp:416</a></div></div>
<div class="ttc" id="classviennacl_1_1compressed__matrix_html_a87a0ad5f26983b1c2d24ee302d886562"><div class="ttname"><a href="classviennacl_1_1compressed__matrix.html#a87a0ad5f26983b1c2d24ee302d886562">viennacl::compressed_matrix::handle</a></div><div class="ttdeci">const handle_type & handle() const </div><div class="ttdoc">Returns the OpenCL handle to the matrix entry array. </div><div class="ttdef"><b>Definition:</b> <a href="compressed__matrix_8hpp_source.html#l00942">compressed_matrix.hpp:942</a></div></div>
<div class="ttc" id="classviennacl_1_1compressed__matrix_html_af71dec61a70e8df4f78a527aa989a106"><div class="ttname"><a href="classviennacl_1_1compressed__matrix.html#af71dec61a70e8df4f78a527aa989a106">viennacl::compressed_matrix::handle1</a></div><div class="ttdeci">const handle_type & handle1() const </div><div class="ttdoc">Returns the OpenCL handle to the row index array. </div><div class="ttdef"><b>Definition:</b> <a href="compressed__matrix_8hpp_source.html#l00936">compressed_matrix.hpp:936</a></div></div>
<div class="ttc" id="namespaceviennacl_1_1linalg_html_a3ba810acdca541a5eada4560982a645ca0d4c883a9aa8a8514fb260ac404e3c8b"><div class="ttname"><a href="namespaceviennacl_1_1linalg.html#a3ba810acdca541a5eada4560982a645ca0d4c883a9aa8a8514fb260ac404e3c8b">viennacl::linalg::AMG_COARSENING_METHOD_MIS2_AGGREGATION</a></div><div class="ttdef"><b>Definition:</b> <a href="amg__base_8hpp_source.html#l00050">amg_base.hpp:50</a></div></div>
<div class="ttc" id="classviennacl_1_1compressed__matrix_html_ae69ca21ded644fdd0c7a5168011b13ed"><div class="ttname"><a href="classviennacl_1_1compressed__matrix.html#ae69ca21ded644fdd0c7a5168011b13ed">viennacl::compressed_matrix::nnz</a></div><div class="ttdeci">const vcl_size_t & nnz() const </div><div class="ttdoc">Returns the number of nonzero entries. </div><div class="ttdef"><b>Definition:</b> <a href="compressed__matrix_8hpp_source.html#l00931">compressed_matrix.hpp:931</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="namespaceviennacl_1_1linalg_1_1cuda_1_1amg_html_a2d8aec3a05feaaff512af0bcf5e94ccd"><div class="ttname"><a href="namespaceviennacl_1_1linalg_1_1cuda_1_1amg.html#a2d8aec3a05feaaff512af0bcf5e94ccd">viennacl::linalg::cuda::amg::amg_influence_trivial_kernel</a></div><div class="ttdeci">__global__ void amg_influence_trivial_kernel(const unsigned int *row_indices, const unsigned int *column_indices, unsigned int size1, unsigned int nnz, unsigned int *influences_row, unsigned int *influences_id, unsigned int *influences_values)</div><div class="ttdef"><b>Definition:</b> <a href="cuda_2amg__operations_8hpp_source.html#l00044">amg_operations.hpp:44</a></div></div>
<div class="ttc" id="namespaceviennacl_1_1linalg_1_1cuda_1_1amg_html_a9fce75799e03103c73d005c09ac361e2"><div class="ttname"><a href="namespaceviennacl_1_1linalg_1_1cuda_1_1amg.html#a9fce75799e03103c73d005c09ac361e2">viennacl::linalg::cuda::amg::amg_interpol</a></div><div class="ttdeci">void amg_interpol(MatrixT const &A, MatrixT &P, viennacl::linalg::detail::amg::amg_level_context &amg_context, viennacl::linalg::amg_tag &tag)</div><div class="ttdoc">Dispatcher for building the interpolation matrix. </div><div class="ttdef"><b>Definition:</b> <a href="cuda_2amg__operations_8hpp_source.html#l00693">amg_operations.hpp:693</a></div></div>
<div class="ttc" id="namespaceviennacl_1_1linalg_1_1cuda_1_1amg_html_a88cc74771dab339b07e06d16500dccb1"><div class="ttname"><a href="namespaceviennacl_1_1linalg_1_1cuda_1_1amg.html#a88cc74771dab339b07e06d16500dccb1">viennacl::linalg::cuda::amg::amg_interpol_sa_kernel</a></div><div class="ttdeci">__global__ void amg_interpol_sa_kernel(const unsigned int *A_row_indices, const unsigned int *A_col_indices, const NumericT *A_elements, unsigned int A_size1, unsigned int A_nnz, unsigned int *Jacobi_row_indices, unsigned int *Jacobi_col_indices, NumericT *Jacobi_elements, NumericT omega)</div><div class="ttdef"><b>Definition:</b> <a href="cuda_2amg__operations_8hpp_source.html#l00594">amg_operations.hpp:594</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="classviennacl_1_1compressed__matrix_html_ab5922a97b73b869fbeeb6a2fa40e3b06"><div class="ttname"><a href="classviennacl_1_1compressed__matrix.html#ab5922a97b73b869fbeeb6a2fa40e3b06">viennacl::compressed_matrix::generate_row_block_information</a></div><div class="ttdeci">void generate_row_block_information()</div><div class="ttdoc">Builds the row block information needed for fast sparse matrix-vector multiplications. </div><div class="ttdef"><b>Definition:</b> <a href="compressed__matrix_8hpp_source.html#l00999">compressed_matrix.hpp:999</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_1traits_html_ac53fc8cc9836953dc87aaaaa56f382c2"><div class="ttname"><a href="namespaceviennacl_1_1traits.html#ac53fc8cc9836953dc87aaaaa56f382c2">viennacl::traits::start2</a></div><div class="ttdeci">result_of::size_type< T >::type start2(T const &obj)</div><div class="ttdef"><b>Definition:</b> <a href="start_8hpp_source.html#l00084">start.hpp:84</a></div></div>
<div class="ttc" id="namespaceviennacl_1_1linalg_html_a9933216144a64dbd433ec02c95bbfdd7afcffee5ed6e7ad032a9ffebe615b5932"><div class="ttname"><a href="namespaceviennacl_1_1linalg.html#a9933216144a64dbd433ec02c95bbfdd7afcffee5ed6e7ad032a9ffebe615b5932">viennacl::linalg::AMG_INTERPOLATION_METHOD_SMOOTHED_AGGREGATION</a></div><div class="ttdef"><b>Definition:</b> <a href="amg__base_8hpp_source.html#l00058">amg_base.hpp:58</a></div></div>
<div class="ttc" id="structviennacl_1_1linalg_1_1detail_1_1amg_1_1amg__level__context_html_aac5a6ef480cf58fb8fa490760bb94e35"><div class="ttname"><a href="structviennacl_1_1linalg_1_1detail_1_1amg_1_1amg__level__context.html#aac5a6ef480cf58fb8fa490760bb94e35">viennacl::linalg::detail::amg::amg_level_context::num_coarse_</a></div><div class="ttdeci">unsigned int num_coarse_</div><div class="ttdef"><b>Definition:</b> <a href="amg__base_8hpp_source.html#l00199">amg_base.hpp:199</a></div></div>
<div class="ttc" id="namespaceviennacl_1_1linalg_1_1cuda_1_1amg_html_ac6c4463d335fc3dd604639b87ed6229d"><div class="ttname"><a href="namespaceviennacl_1_1linalg_1_1cuda_1_1amg.html#ac6c4463d335fc3dd604639b87ed6229d">viennacl::linalg::cuda::amg::assign_to_dense</a></div><div class="ttdeci">void assign_to_dense(viennacl::compressed_matrix< NumericT, AlignmentV > const &A, viennacl::matrix_base< NumericT > &B)</div><div class="ttdef"><b>Definition:</b> <a href="cuda_2amg__operations_8hpp_source.html#l00730">amg_operations.hpp:730</a></div></div>
<div class="ttc" id="classviennacl_1_1compressed__matrix_html_a91f5145351151a66f916bdc3901206f2"><div class="ttname"><a href="classviennacl_1_1compressed__matrix.html#a91f5145351151a66f916bdc3901206f2">viennacl::compressed_matrix::handle2</a></div><div class="ttdeci">const handle_type & handle2() const </div><div class="ttdoc">Returns the OpenCL handle to the column index array. </div><div class="ttdef"><b>Definition:</b> <a href="compressed__matrix_8hpp_source.html#l00938">compressed_matrix.hpp:938</a></div></div>
<div class="ttc" id="namespaceviennacl_1_1linalg_1_1cuda_1_1amg_html_a24916ce5eec2c7fa4b4542a4c082e75e"><div class="ttname"><a href="namespaceviennacl_1_1linalg_1_1cuda_1_1amg.html#a24916ce5eec2c7fa4b4542a4c082e75e">viennacl::linalg::cuda::amg::amg_coarse_ag_stage1_mis2</a></div><div class="ttdeci">void amg_coarse_ag_stage1_mis2(compressed_matrix< NumericT > const &A, viennacl::linalg::detail::amg::amg_level_context &amg_context, viennacl::linalg::amg_tag &tag)</div><div class="ttdoc">AG (aggregation based) coarsening, single-threaded version of stage 1. </div><div class="ttdef"><b>Definition:</b> <a href="cuda_2amg__operations_8hpp_source.html#l00290">amg_operations.hpp:290</a></div></div>
<div class="ttc" id="namespaceviennacl_1_1linalg_1_1cuda_1_1amg_html_a696559c185d8b0ff86edc633f6cbc643"><div class="ttname"><a href="namespaceviennacl_1_1linalg_1_1cuda_1_1amg.html#a696559c185d8b0ff86edc633f6cbc643">viennacl::linalg::cuda::amg::amg_interpol_ag_kernel</a></div><div class="ttdeci">__global__ void amg_interpol_ag_kernel(unsigned int *P_row_buffer, unsigned int *P_col_buffer, NumericT *P_elements, unsigned int *coarse_ids, unsigned int size)</div><div class="ttdef"><b>Definition:</b> <a href="cuda_2amg__operations_8hpp_source.html#l00543">amg_operations.hpp:543</a></div></div>
<div class="ttc" id="namespaceviennacl_1_1linalg_1_1cuda_1_1amg_html_aed74cfedec05f6e080eee9abdd60f123"><div class="ttname"><a href="namespaceviennacl_1_1linalg_1_1cuda_1_1amg.html#aed74cfedec05f6e080eee9abdd60f123">viennacl::linalg::cuda::amg::smooth_jacobi</a></div><div class="ttdeci">void smooth_jacobi(unsigned int iterations, compressed_matrix< NumericT > const &A, vector< NumericT > &x, vector< NumericT > &x_backup, vector< NumericT > const &rhs_smooth, NumericT weight)</div><div class="ttdoc">Damped Jacobi Smoother (CUDA version) </div><div class="ttdef"><b>Definition:</b> <a href="cuda_2amg__operations_8hpp_source.html#l00791">amg_operations.hpp:791</a></div></div>
<div class="ttc" id="structviennacl_1_1linalg_1_1detail_1_1amg_1_1amg__level__context_html_aa97530b4793135fb8d5e71010c8ff637adf77f4d874aa905e58b1d01448d599b7"><div class="ttname"><a href="structviennacl_1_1linalg_1_1detail_1_1amg_1_1amg__level__context.html#aa97530b4793135fb8d5e71010c8ff637adf77f4d874aa905e58b1d01448d599b7">viennacl::linalg::detail::amg::amg_level_context::POINT_TYPE_UNDECIDED</a></div><div class="ttdef"><b>Definition:</b> <a href="amg__base_8hpp_source.html#l00189">amg_base.hpp:189</a></div></div>
<div class="ttc" id="classviennacl_1_1vector_html"><div class="ttname"><a href="classviennacl_1_1vector.html">viennacl::vector< unsigned int ></a></div></div>
<div class="ttc" id="namespaceviennacl_html_a507d2ac469c79997f2bb6e82b37b7483"><div class="ttname"><a href="namespaceviennacl.html#a507d2ac469c79997f2bb6e82b37b7483">viennacl::diag</a></div><div class="ttdeci">vector_expression< const matrix_base< NumericT >, const int, op_matrix_diag > diag(const matrix_base< NumericT > &A, int k=0)</div><div class="ttdef"><b>Definition:</b> <a href="matrix_8hpp_source.html#l00895">matrix.hpp:895</a></div></div>
<div class="ttc" id="namespaceviennacl_1_1linalg_1_1cuda_1_1amg_html_a72f36c48c3a517297e28ec9b87aea14f"><div class="ttname"><a href="namespaceviennacl_1_1linalg_1_1cuda_1_1amg.html#a72f36c48c3a517297e28ec9b87aea14f">viennacl::linalg::cuda::amg::amg_agg_propagate_coarse_indices</a></div><div class="ttdeci">__global__ void amg_agg_propagate_coarse_indices(IndexT *point_types, IndexT *coarse_ids, IndexT const *influences_row, IndexT const *influences_id, unsigned int size)</div><div class="ttdef"><b>Definition:</b> <a href="cuda_2amg__operations_8hpp_source.html#l00386">amg_operations.hpp:386</a></div></div>
<div class="ttc" id="namespaceviennacl_1_1traits_html_ace596004f16c075adbfcd329e6c60e91"><div class="ttname"><a href="namespaceviennacl_1_1traits.html#ace596004f16c075adbfcd329e6c60e91">viennacl::traits::stride2</a></div><div class="ttdeci">result_of::size_type< matrix_base< NumericT > >::type stride2(matrix_base< NumericT > const &s)</div><div class="ttdef"><b>Definition:</b> <a href="stride_8hpp_source.html#l00065">stride.hpp:65</a></div></div>
<div class="ttc" id="namespaceviennacl_html_a0a574e6cd04ca0e42298b4ab845700e4"><div class="ttname"><a href="namespaceviennacl.html#a0a574e6cd04ca0e42298b4ab845700e4">viennacl::row</a></div><div class="ttdeci">vector_expression< const matrix_base< NumericT, F >, const unsigned int, op_row > row(const matrix_base< NumericT, F > &A, unsigned int i)</div><div class="ttdef"><b>Definition:</b> <a href="matrix_8hpp_source.html#l00910">matrix.hpp:910</a></div></div>
<div class="ttc" id="structviennacl_1_1linalg_1_1detail_1_1amg_1_1amg__level__context_html_aa97530b4793135fb8d5e71010c8ff637af803b8af4a6abdaf3d0fd08c18da6de6"><div class="ttname"><a href="structviennacl_1_1linalg_1_1detail_1_1amg_1_1amg__level__context.html#aa97530b4793135fb8d5e71010c8ff637af803b8af4a6abdaf3d0fd08c18da6de6">viennacl::linalg::detail::amg::amg_level_context::POINT_TYPE_FINE</a></div><div class="ttdef"><b>Definition:</b> <a href="amg__base_8hpp_source.html#l00191">amg_base.hpp:191</a></div></div>
<div class="ttc" id="namespaceviennacl_html_a00b40450b6b2fd87aad3527d9b2084b8a427356f0fb1b8d32b28f37e36b272df4"><div class="ttname"><a href="namespaceviennacl.html#a00b40450b6b2fd87aad3527d9b2084b8a427356f0fb1b8d32b28f37e36b272df4">viennacl::MAIN_MEMORY</a></div><div class="ttdef"><b>Definition:</b> <a href="forwards_8h_source.html#l00348">forwards.h:348</a></div></div>
<div class="ttc" id="classviennacl_1_1linalg_1_1amg__tag_html"><div class="ttname"><a href="classviennacl_1_1linalg_1_1amg__tag.html">viennacl::linalg::amg_tag</a></div><div class="ttdoc">A tag for algebraic multigrid (AMG). Used to transport information from the user to the implementatio...</div><div class="ttdef"><b>Definition:</b> <a href="amg__base_8hpp_source.html#l00064">amg_base.hpp:64</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_1linalg_1_1cuda_1_1amg_html_a9cc8c1d739430a807751738aa5559a32"><div class="ttname"><a href="namespaceviennacl_1_1linalg_1_1cuda_1_1amg.html#a9cc8c1d739430a807751738aa5559a32">viennacl::linalg::cuda::amg::amg_interpol_sa</a></div><div class="ttdeci">void amg_interpol_sa(compressed_matrix< NumericT > const &A, compressed_matrix< NumericT > &P, viennacl::linalg::detail::amg::amg_level_context &amg_context, viennacl::linalg::amg_tag &tag)</div><div class="ttdoc">Smoothed aggregation interpolation. (VIENNACL_INTERPOL_SA) </div><div class="ttdef"><b>Definition:</b> <a href="cuda_2amg__operations_8hpp_source.html#l00654">amg_operations.hpp:654</a></div></div>
<div class="ttc" id="classviennacl_1_1vector__base_html_a15c47ae4326098aeaa4ed6b91fc6df9b"><div class="ttname"><a href="classviennacl_1_1vector__base.html#a15c47ae4326098aeaa4ed6b91fc6df9b">viennacl::vector_base::size</a></div><div class="ttdeci">size_type size() const </div><div class="ttdoc">Returns the length of the vector (cf. std::vector) </div><div class="ttdef"><b>Definition:</b> <a href="vector__def_8hpp_source.html#l00118">vector_def.hpp:118</a></div></div>
<div class="ttc" id="structviennacl_1_1linalg_1_1detail_1_1amg_1_1amg__level__context_html_a8856e6db54e88c12e2ac728b5fcbe1e4"><div class="ttname"><a href="structviennacl_1_1linalg_1_1detail_1_1amg_1_1amg__level__context.html#a8856e6db54e88c12e2ac728b5fcbe1e4">viennacl::linalg::detail::amg::amg_level_context::point_types_</a></div><div class="ttdeci">viennacl::vector< unsigned int > point_types_</div><div class="ttdef"><b>Definition:</b> <a href="amg__base_8hpp_source.html#l00197">amg_base.hpp:197</a></div></div>
<div class="ttc" id="namespaceviennacl_1_1linalg_1_1cuda_1_1amg_html_a644a8509ef334ceb151a8ffa6d8f6111"><div class="ttname"><a href="namespaceviennacl_1_1linalg_1_1cuda_1_1amg.html#a644a8509ef334ceb151a8ffa6d8f6111">viennacl::linalg::cuda::amg::compressed_matrix_assign_to_dense</a></div><div class="ttdeci">__global__ void compressed_matrix_assign_to_dense(const unsigned int *row_indices, const unsigned int *column_indices, const NumericT *elements, NumericT *B, unsigned int B_row_start, unsigned int B_col_start, unsigned int B_row_inc, unsigned int B_col_inc, unsigned int B_row_size, unsigned int B_col_size, unsigned int B_internal_rows, unsigned int B_internal_cols)</div><div class="ttdef"><b>Definition:</b> <a href="cuda_2amg__operations_8hpp_source.html#l00708">amg_operations.hpp:708</a></div></div>
<div class="ttc" id="classviennacl_1_1linalg_1_1amg__tag_html_afb4b14cf0b9e99161fa8c1da4647ad0d"><div class="ttname"><a href="classviennacl_1_1linalg_1_1amg__tag.html#afb4b14cf0b9e99161fa8c1da4647ad0d">viennacl::linalg::amg_tag::get_interpolation_method</a></div><div class="ttdeci">amg_interpolation_method get_interpolation_method() const </div><div class="ttdoc">Returns the current interpolation method. </div><div class="ttdef"><b>Definition:</b> <a href="amg__base_8hpp_source.html#l00093">amg_base.hpp:93</a></div></div>
<div class="ttc" id="classviennacl_1_1backend_1_1mem__handle_html_ac8373f0d899b89c843e14de4cb7a1c4a"><div class="ttname"><a href="classviennacl_1_1backend_1_1mem__handle.html#ac8373f0d899b89c843e14de4cb7a1c4a">viennacl::backend::mem_handle::raw_size</a></div><div class="ttdeci">vcl_size_t raw_size() const </div><div class="ttdoc">Returns the number of bytes of the currently active buffer. </div><div class="ttdef"><b>Definition:</b> <a href="mem__handle_8hpp_source.html#l00230">mem_handle.hpp:230</a></div></div>
<div class="ttc" id="classviennacl_1_1compressed__matrix_html"><div class="ttname"><a href="classviennacl_1_1compressed__matrix.html">viennacl::compressed_matrix< NumericT ></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="namespaceviennacl_html_ae7d5db0c2c91be75218db5b52c4d13da"><div class="ttname"><a href="namespaceviennacl.html#ae7d5db0c2c91be75218db5b52c4d13da">viennacl::cuda_arg</a></div><div class="ttdeci">NumericT * cuda_arg(scalar< NumericT > &obj)</div><div class="ttdoc">Convenience helper function for extracting the CUDA handle from a ViennaCL scalar. Non-const version. </div><div class="ttdef"><b>Definition:</b> <a href="linalg_2cuda_2common_8hpp_source.html#l00039">common.hpp:39</a></div></div>
<div class="ttc" id="amg__base_8hpp_html"><div class="ttname"><a href="amg__base_8hpp.html">amg_base.hpp</a></div><div class="ttdoc">Helper classes and functions for the AMG preconditioner. Experimental. </div></div>
<div class="ttc" id="structviennacl_1_1linalg_1_1detail_1_1amg_1_1amg__level__context_html_aa97530b4793135fb8d5e71010c8ff637afbc2c39efc86491c26c2401d06f2cc8a"><div class="ttname"><a href="structviennacl_1_1linalg_1_1detail_1_1amg_1_1amg__level__context.html#aa97530b4793135fb8d5e71010c8ff637afbc2c39efc86491c26c2401d06f2cc8a">viennacl::linalg::detail::amg::amg_level_context::POINT_TYPE_COARSE</a></div><div class="ttdef"><b>Definition:</b> <a href="amg__base_8hpp_source.html#l00190">amg_base.hpp:190</a></div></div>
<div class="ttc" id="structviennacl_1_1linalg_1_1detail_1_1amg_1_1amg__level__context_html_aa647069a4102267171e395fcfd10e7ac"><div class="ttname"><a href="structviennacl_1_1linalg_1_1detail_1_1amg_1_1amg__level__context.html#aa647069a4102267171e395fcfd10e7ac">viennacl::linalg::detail::amg::amg_level_context::coarse_id_</a></div><div class="ttdeci">viennacl::vector< unsigned int > coarse_id_</div><div class="ttdef"><b>Definition:</b> <a href="amg__base_8hpp_source.html#l00198">amg_base.hpp:198</a></div></div>
<div class="ttc" id="namespaceviennacl_1_1linalg_1_1cuda_1_1amg_html_a1c10960302d546fd274e68564f1409de"><div class="ttname"><a href="namespaceviennacl_1_1linalg_1_1cuda_1_1amg.html#a1c10960302d546fd274e68564f1409de">viennacl::linalg::cuda::amg::amg_pmis2_reset_state</a></div><div class="ttdeci">__global__ void amg_pmis2_reset_state(unsigned int *point_types, unsigned int size)</div><div class="ttdoc">CUDA kernel for resetting non-MIS (i.e. coarse) points to undecided so that subsequent kernels work...</div><div class="ttdef"><b>Definition:</b> <a href="cuda_2amg__operations_8hpp_source.html#l00271">amg_operations.hpp:271</a></div></div>
<div class="ttc" id="classviennacl_1_1vector__base_html_a64e98aea5aa298ad63e3832a04c19648"><div class="ttname"><a href="classviennacl_1_1vector__base.html#a64e98aea5aa298ad63e3832a04c19648">viennacl::vector_base::handle</a></div><div class="ttdeci">const handle_type & handle() const </div><div class="ttdoc">Returns the memory handle. </div><div class="ttdef"><b>Definition:</b> <a href="vector__def_8hpp_source.html#l00128">vector_def.hpp:128</a></div></div>
<div class="ttc" id="structviennacl_1_1linalg_1_1detail_1_1amg_1_1amg__level__context_html_a757fe2a72ed0d9eb3649ecda1c83129e"><div class="ttname"><a href="structviennacl_1_1linalg_1_1detail_1_1amg_1_1amg__level__context.html#a757fe2a72ed0d9eb3649ecda1c83129e">viennacl::linalg::detail::amg::amg_level_context::influence_values_</a></div><div class="ttdeci">viennacl::vector< unsigned int > influence_values_</div><div class="ttdef"><b>Definition:</b> <a href="amg__base_8hpp_source.html#l00196">amg_base.hpp:196</a></div></div>
<div class="ttc" id="namespaceviennacl_1_1linalg_1_1cuda_1_1amg_html_ac6522518fb686a2fe0bd3db0d34a3fcd"><div class="ttname"><a href="namespaceviennacl_1_1linalg_1_1cuda_1_1amg.html#ac6522518fb686a2fe0bd3db0d34a3fcd">viennacl::linalg::cuda::amg::amg_pmis2_max_neighborhood</a></div><div class="ttdeci">__global__ void amg_pmis2_max_neighborhood(IndexT const *work_state, IndexT const *work_random, IndexT const *work_index, IndexT *work_state2, IndexT *work_random2, IndexT *work_index2, IndexT const *influences_row, IndexT const *influences_id, unsigned int size)</div><div class="ttdoc">CUDA kernel propagating the state triple (status, weight, nodeID) to neighbors using a max()-operatio...</div><div class="ttdef"><b>Definition:</b> <a href="cuda_2amg__operations_8hpp_source.html#l00167">amg_operations.hpp:167</a></div></div>
<div class="ttc" id="structviennacl_1_1linalg_1_1detail_1_1amg_1_1amg__level__context_html_a262b6f406db2b16b53936b8759f83d05"><div class="ttname"><a href="structviennacl_1_1linalg_1_1detail_1_1amg_1_1amg__level__context.html#a262b6f406db2b16b53936b8759f83d05">viennacl::linalg::detail::amg::amg_level_context::influence_ids_</a></div><div class="ttdeci">viennacl::vector< unsigned int > influence_ids_</div><div class="ttdef"><b>Definition:</b> <a href="amg__base_8hpp_source.html#l00195">amg_base.hpp:195</a></div></div>
<div class="ttc" id="namespaceviennacl_1_1linalg_1_1cuda_1_1amg_html_ac4a8f8869f8ba360558b53e40059dacb"><div class="ttname"><a href="namespaceviennacl_1_1linalg_1_1cuda_1_1amg.html#ac4a8f8869f8ba360558b53e40059dacb">viennacl::linalg::cuda::amg::amg_coarse_ag</a></div><div class="ttdeci">void amg_coarse_ag(compressed_matrix< NumericT > const &A, viennacl::linalg::detail::amg::amg_level_context &amg_context, viennacl::linalg::amg_tag &tag)</div><div class="ttdoc">AG (aggregation based) coarsening. Partially single-threaded version (VIENNACL_AMG_COARSE_AG) ...</div><div class="ttdef"><b>Definition:</b> <a href="cuda_2amg__operations_8hpp_source.html#l00466">amg_operations.hpp:466</a></div></div>
<div class="ttc" id="classviennacl_1_1vector_html_a59f2ec43f298cc04d2f2bbbeee239bfe"><div class="ttname"><a href="classviennacl_1_1vector.html#a59f2ec43f298cc04d2f2bbbeee239bfe">viennacl::vector::switch_memory_context</a></div><div class="ttdeci">void switch_memory_context(viennacl::context new_ctx)</div><div class="ttdef"><b>Definition:</b> <a href="vector_8hpp_source.html#l01064">vector.hpp:1064</a></div></div>
<div class="ttc" id="namespaceviennacl_1_1linalg_1_1cuda_1_1amg_html_a28e3755d2f30432e39bb842732129098"><div class="ttname"><a href="namespaceviennacl_1_1linalg_1_1cuda_1_1amg.html#a28e3755d2f30432e39bb842732129098">viennacl::linalg::cuda::amg::amg_influence</a></div><div class="ttdeci">void amg_influence(compressed_matrix< NumericT > const &A, viennacl::linalg::detail::amg::amg_level_context &amg_context, viennacl::linalg::amg_tag &tag)</div><div class="ttdoc">Dispatcher for influence processing. </div><div class="ttdef"><b>Definition:</b> <a href="cuda_2amg__operations_8hpp_source.html#l00103">amg_operations.hpp:103</a></div></div>
<div class="ttc" id="structviennacl_1_1linalg_1_1detail_1_1amg_1_1amg__level__context_html_ad537babcb184069cc920bfb2140860de"><div class="ttname"><a href="structviennacl_1_1linalg_1_1detail_1_1amg_1_1amg__level__context.html#ad537babcb184069cc920bfb2140860de">viennacl::linalg::detail::amg::amg_level_context::influence_jumper_</a></div><div class="ttdeci">viennacl::vector< unsigned int > influence_jumper_</div><div class="ttdef"><b>Definition:</b> <a href="amg__base_8hpp_source.html#l00194">amg_base.hpp:194</a></div></div>
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