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<div class="title">fft_operations.hpp</div> </div>
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<a href="cuda_2fft__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_FFT_OPERATIONS_HPP_</span></div>
<div class="line"><a name="l00002"></a><span class="lineno"> 2</span> <span class="preprocessor">#define VIENNACL_LINALG_CUDA_FFT_OPERATIONS_HPP_</span></div>
<div class="line"><a name="l00003"></a><span class="lineno"> 3</span> </div>
<div class="line"><a name="l00004"></a><span class="lineno"> 4</span> <span class="comment">/* =========================================================================</span></div>
<div class="line"><a name="l00005"></a><span class="lineno"> 5</span> <span class="comment"> Copyright (c) 2010-2016, Institute for Microelectronics,</span></div>
<div class="line"><a name="l00006"></a><span class="lineno"> 6</span> <span class="comment"> Institute for Analysis and Scientific Computing,</span></div>
<div class="line"><a name="l00007"></a><span class="lineno"> 7</span> <span class="comment"> TU Wien.</span></div>
<div class="line"><a name="l00008"></a><span class="lineno"> 8</span> <span class="comment"> Portions of this software are copyright by UChicago Argonne, LLC.</span></div>
<div class="line"><a name="l00009"></a><span class="lineno"> 9</span> <span class="comment"></span></div>
<div class="line"><a name="l00010"></a><span class="lineno"> 10</span> <span class="comment"> -----------------</span></div>
<div class="line"><a name="l00011"></a><span class="lineno"> 11</span> <span class="comment"> ViennaCL - The Vienna Computing Library</span></div>
<div class="line"><a name="l00012"></a><span class="lineno"> 12</span> <span class="comment"> -----------------</span></div>
<div class="line"><a name="l00013"></a><span class="lineno"> 13</span> <span class="comment"></span></div>
<div class="line"><a name="l00014"></a><span class="lineno"> 14</span> <span class="comment"> Project Head: Karl Rupp rupp@iue.tuwien.ac.at</span></div>
<div class="line"><a name="l00015"></a><span class="lineno"> 15</span> <span class="comment"></span></div>
<div class="line"><a name="l00016"></a><span class="lineno"> 16</span> <span class="comment"> (A list of authors and contributors can be found in the manual)</span></div>
<div class="line"><a name="l00017"></a><span class="lineno"> 17</span> <span class="comment"></span></div>
<div class="line"><a name="l00018"></a><span class="lineno"> 18</span> <span class="comment"> License: MIT (X11), see file LICENSE in the base directory</span></div>
<div class="line"><a name="l00019"></a><span class="lineno"> 19</span> <span class="comment">============================================================================= */</span></div>
<div class="line"><a name="l00020"></a><span class="lineno"> 20</span> </div>
<div class="line"><a name="l00024"></a><span class="lineno"> 24</span> <span class="preprocessor">#include <cmath></span></div>
<div class="line"><a name="l00025"></a><span class="lineno"> 25</span> <span class="preprocessor">#include <<a class="code" href="matrix_8hpp.html">viennacl/matrix.hpp</a>></span></div>
<div class="line"><a name="l00026"></a><span class="lineno"> 26</span> <span class="preprocessor">#include <<a class="code" href="vector_8hpp.html">viennacl/vector.hpp</a>></span></div>
<div class="line"><a name="l00027"></a><span class="lineno"> 27</span> </div>
<div class="line"><a name="l00028"></a><span class="lineno"> 28</span> <span class="preprocessor">#include "<a class="code" href="forwards_8h.html">viennacl/forwards.h</a>"</span></div>
<div class="line"><a name="l00029"></a><span class="lineno"> 29</span> <span class="preprocessor">#include "<a class="code" href="scalar_8hpp.html">viennacl/scalar.hpp</a>"</span></div>
<div class="line"><a name="l00030"></a><span class="lineno"> 30</span> <span class="preprocessor">#include "<a class="code" href="tools_8hpp.html">viennacl/tools/tools.hpp</a>"</span></div>
<div class="line"><a name="l00031"></a><span class="lineno"> 31</span> <span class="preprocessor">#include "<a class="code" href="linalg_2cuda_2common_8hpp.html">viennacl/linalg/cuda/common.hpp</a>"</span></div>
<div class="line"><a name="l00032"></a><span class="lineno"> 32</span> <span class="preprocessor">#include "<a class="code" href="host__based_2vector__operations_8hpp.html">viennacl/linalg/host_based/vector_operations.hpp</a>"</span></div>
<div class="line"><a name="l00033"></a><span class="lineno"> 33</span> <span class="preprocessor">#include "<a class="code" href="host__based_2fft__operations_8hpp.html">viennacl/linalg/host_based/fft_operations.hpp</a>"</span></div>
<div class="line"><a name="l00034"></a><span class="lineno"> 34</span> </div>
<div class="line"><a name="l00035"></a><span class="lineno"> 35</span> <span class="keyword">namespace </span>viennacl</div>
<div class="line"><a name="l00036"></a><span class="lineno"> 36</span> {</div>
<div class="line"><a name="l00037"></a><span class="lineno"> 37</span> <span class="keyword">namespace </span>linalg</div>
<div class="line"><a name="l00038"></a><span class="lineno"> 38</span> {</div>
<div class="line"><a name="l00039"></a><span class="lineno"> 39</span> <span class="keyword">namespace </span>cuda</div>
<div class="line"><a name="l00040"></a><span class="lineno"> 40</span> {</div>
<div class="line"><a name="l00041"></a><span class="lineno"> 41</span> <span class="keyword">namespace </span>detail</div>
<div class="line"><a name="l00042"></a><span class="lineno"> 42</span> {</div>
<div class="line"><a name="l00043"></a><span class="lineno"><a class="line" href="namespaceviennacl_1_1linalg_1_1cuda_1_1detail_1_1fft.html"> 43</a></span>  <span class="keyword">namespace </span><a class="code" href="fft__1d_8cpp.html#a56353420d188d1181ae49bf69283b497">fft</a></div>
<div class="line"><a name="l00044"></a><span class="lineno"> 44</span>  {</div>
<div class="line"><a name="l00045"></a><span class="lineno"><a class="line" href="namespaceviennacl_1_1linalg_1_1cuda_1_1detail_1_1fft.html#a6b937b778b0e08dd5393ffed32c96020"> 45</a></span>  <span class="keyword">const</span> <a class="code" href="namespaceviennacl.html#a98a0afcc513111ffa0bd138f891930df">vcl_size_t</a> <a class="code" href="namespaceviennacl_1_1linalg_1_1cuda_1_1detail_1_1fft.html#a6b937b778b0e08dd5393ffed32c96020">MAX_LOCAL_POINTS_NUM</a> = 512;</div>
<div class="line"><a name="l00046"></a><span class="lineno"> 46</span> </div>
<div class="line"><a name="l00047"></a><span class="lineno"><a class="line" href="namespaceviennacl_1_1linalg_1_1cuda_1_1detail_1_1fft.html#abd87824ce2e6428991a3f1a936d9a250"> 47</a></span>  <span class="keyword">inline</span> <a class="code" href="namespaceviennacl.html#a98a0afcc513111ffa0bd138f891930df">vcl_size_t</a> <a class="code" href="namespaceviennacl_1_1linalg_1_1cuda_1_1detail_1_1fft.html#abd87824ce2e6428991a3f1a936d9a250">num_bits</a>(<a class="code" href="namespaceviennacl.html#a98a0afcc513111ffa0bd138f891930df">vcl_size_t</a> <a class="code" href="namespaceviennacl_1_1traits.html#aa2344ea20469f55fbc15a8e9526494d0">size</a>)</div>
<div class="line"><a name="l00048"></a><span class="lineno"> 48</span>  {</div>
<div class="line"><a name="l00049"></a><span class="lineno"> 49</span>  <a class="code" href="namespaceviennacl.html#a98a0afcc513111ffa0bd138f891930df">vcl_size_t</a> bits_datasize = 0;</div>
<div class="line"><a name="l00050"></a><span class="lineno"> 50</span>  <a class="code" href="namespaceviennacl.html#a98a0afcc513111ffa0bd138f891930df">vcl_size_t</a> ds = 1;</div>
<div class="line"><a name="l00051"></a><span class="lineno"> 51</span> </div>
<div class="line"><a name="l00052"></a><span class="lineno"> 52</span>  <span class="keywordflow">while</span> (ds < size)</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>  ds = ds << 1;</div>
<div class="line"><a name="l00055"></a><span class="lineno"> 55</span>  bits_datasize++;</div>
<div class="line"><a name="l00056"></a><span class="lineno"> 56</span>  }</div>
<div class="line"><a name="l00057"></a><span class="lineno"> 57</span> </div>
<div class="line"><a name="l00058"></a><span class="lineno"> 58</span>  <span class="keywordflow">return</span> bits_datasize;</div>
<div class="line"><a name="l00059"></a><span class="lineno"> 59</span>  }</div>
<div class="line"><a name="l00060"></a><span class="lineno"> 60</span> </div>
<div class="line"><a name="l00061"></a><span class="lineno"><a class="line" href="namespaceviennacl_1_1linalg_1_1cuda_1_1detail_1_1fft.html#ad8af53105450cfc6a0adb586742a028e"> 61</a></span>  <span class="keyword">inline</span> <a class="code" href="namespaceviennacl.html#a98a0afcc513111ffa0bd138f891930df">vcl_size_t</a> <a class="code" href="namespaceviennacl_1_1linalg_1_1cuda_1_1detail_1_1fft.html#ad8af53105450cfc6a0adb586742a028e">next_power_2</a>(<a class="code" href="namespaceviennacl.html#a98a0afcc513111ffa0bd138f891930df">vcl_size_t</a> n)</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>  n = n - 1;</div>
<div class="line"><a name="l00064"></a><span class="lineno"> 64</span> </div>
<div class="line"><a name="l00065"></a><span class="lineno"> 65</span>  <a class="code" href="namespaceviennacl.html#a98a0afcc513111ffa0bd138f891930df">vcl_size_t</a> power = 1;</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">while</span> (power < <span class="keyword">sizeof</span>(<a class="code" href="namespaceviennacl.html#a98a0afcc513111ffa0bd138f891930df">vcl_size_t</a>) * 8)</div>
<div class="line"><a name="l00068"></a><span class="lineno"> 68</span>  {</div>
<div class="line"><a name="l00069"></a><span class="lineno"> 69</span>  n = n | (n >> power);</div>
<div class="line"><a name="l00070"></a><span class="lineno"> 70</span>  power *= 2;</div>
<div class="line"><a name="l00071"></a><span class="lineno"> 71</span>  }</div>
<div class="line"><a name="l00072"></a><span class="lineno"> 72</span> </div>
<div class="line"><a name="l00073"></a><span class="lineno"> 73</span>  <span class="keywordflow">return</span> n + 1;</div>
<div class="line"><a name="l00074"></a><span class="lineno"> 74</span>  }</div>
<div class="line"><a name="l00075"></a><span class="lineno"> 75</span> </div>
<div class="line"><a name="l00076"></a><span class="lineno"> 76</span>  } <span class="comment">//namespace fft</span></div>
<div class="line"><a name="l00077"></a><span class="lineno"> 77</span> } <span class="comment">//namespace detail</span></div>
<div class="line"><a name="l00078"></a><span class="lineno"> 78</span> </div>
<div class="line"><a name="l00079"></a><span class="lineno"> 79</span> <span class="comment">// addition</span></div>
<div class="line"><a name="l00080"></a><span class="lineno"><a class="line" href="namespaceviennacl_1_1linalg_1_1cuda.html#aa33540cbd35a517b2f196d96b549efe4"> 80</a></span> <span class="keyword">inline</span> __host__ __device__ float2 <a class="code" href="namespaceviennacl_1_1linalg_1_1cuda.html#aa33540cbd35a517b2f196d96b549efe4">operator+</a>(float2 a, float2 b)</div>
<div class="line"><a name="l00081"></a><span class="lineno"> 81</span> {</div>
<div class="line"><a name="l00082"></a><span class="lineno"> 82</span>  <span class="keywordflow">return</span> make_float2(a.x + b.x, a.y + b.y);</div>
<div class="line"><a name="l00083"></a><span class="lineno"> 83</span> }</div>
<div class="line"><a name="l00084"></a><span class="lineno"> 84</span> </div>
<div class="line"><a name="l00085"></a><span class="lineno"> 85</span> <span class="comment">// subtract</span></div>
<div class="line"><a name="l00086"></a><span class="lineno"><a class="line" href="namespaceviennacl_1_1linalg_1_1cuda.html#a2bbc92ab80300afeae4b52a1ddd78674"> 86</a></span> <span class="keyword">inline</span> __host__ __device__ float2 <a class="code" href="namespaceviennacl_1_1linalg_1_1cuda.html#a2bbc92ab80300afeae4b52a1ddd78674">operator-</a>(float2 a, float2 b)</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>  <span class="keywordflow">return</span> make_float2(a.x - b.x, a.y - b.y);</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> <span class="comment">// division</span></div>
<div class="line"><a name="l00091"></a><span class="lineno"> 91</span> <span class="keyword">template</span><<span class="keyword">typename</span> SCALARTYPE></div>
<div class="line"><a name="l00092"></a><span class="lineno"><a class="line" href="namespaceviennacl_1_1linalg_1_1cuda.html#a6b46337d1aab49f0bc5d20e2699e4231"> 92</a></span> <span class="keyword">inline</span> __device__ float2 <a class="code" href="namespaceviennacl_1_1linalg_1_1cuda.html#a6b46337d1aab49f0bc5d20e2699e4231">operator/</a>(float2 a,SCALARTYPE b)</div>
<div class="line"><a name="l00093"></a><span class="lineno"> 93</span> {</div>
<div class="line"><a name="l00094"></a><span class="lineno"> 94</span>  <span class="keywordflow">return</span> make_float2(a.x/b, a.y/b);</div>
<div class="line"><a name="l00095"></a><span class="lineno"> 95</span> }</div>
<div class="line"><a name="l00096"></a><span class="lineno"> 96</span> </div>
<div class="line"><a name="l00097"></a><span class="lineno"> 97</span> <span class="comment">//multiplication</span></div>
<div class="line"><a name="l00098"></a><span class="lineno"><a class="line" href="namespaceviennacl_1_1linalg_1_1cuda.html#a1e6214e945b8d60ea371f578f5ee58db"> 98</a></span> <span class="keyword">inline</span> __device__ float2 <a class="code" href="namespaceviennacl_1_1linalg_1_1cuda.html#a1e6214e945b8d60ea371f578f5ee58db">operator*</a>(float2 in1, float2 in2)</div>
<div class="line"><a name="l00099"></a><span class="lineno"> 99</span> {</div>
<div class="line"><a name="l00100"></a><span class="lineno"> 100</span>  <span class="keywordflow">return</span> make_float2(in1.x * in2.x - in1.y * in2.y, in1.x * in2.y + in1.y * in2.x);</div>
<div class="line"><a name="l00101"></a><span class="lineno"> 101</span> }</div>
<div class="line"><a name="l00102"></a><span class="lineno"> 102</span> </div>
<div class="line"><a name="l00103"></a><span class="lineno"> 103</span> <span class="comment">// addition</span></div>
<div class="line"><a name="l00104"></a><span class="lineno"><a class="line" href="namespaceviennacl_1_1linalg_1_1cuda.html#aa3b01993e9ea32760b16a85bdb96ab69"> 104</a></span> <span class="keyword">inline</span> __host__ __device__ double2 <a class="code" href="namespaceviennacl_1_1linalg_1_1cuda.html#aa33540cbd35a517b2f196d96b549efe4">operator+</a>(double2 a, double2 b)</div>
<div class="line"><a name="l00105"></a><span class="lineno"> 105</span> {</div>
<div class="line"><a name="l00106"></a><span class="lineno"> 106</span>  <span class="keywordflow">return</span> make_double2(a.x + b.x, a.y + b.y);</div>
<div class="line"><a name="l00107"></a><span class="lineno"> 107</span> }</div>
<div class="line"><a name="l00108"></a><span class="lineno"> 108</span> </div>
<div class="line"><a name="l00109"></a><span class="lineno"> 109</span> <span class="comment">// subtraction</span></div>
<div class="line"><a name="l00110"></a><span class="lineno"><a class="line" href="namespaceviennacl_1_1linalg_1_1cuda.html#a62766cf517bab1547813f7db8ae78116"> 110</a></span> <span class="keyword">inline</span> __host__ __device__ double2 <a class="code" href="namespaceviennacl_1_1linalg_1_1cuda.html#a2bbc92ab80300afeae4b52a1ddd78674">operator-</a>(double2 a, double2 b)</div>
<div class="line"><a name="l00111"></a><span class="lineno"> 111</span> {</div>
<div class="line"><a name="l00112"></a><span class="lineno"> 112</span>  <span class="keywordflow">return</span> make_double2(a.x - b.x, a.y - b.y);</div>
<div class="line"><a name="l00113"></a><span class="lineno"> 113</span> }</div>
<div class="line"><a name="l00114"></a><span class="lineno"> 114</span> </div>
<div class="line"><a name="l00115"></a><span class="lineno"> 115</span> <span class="comment">// division</span></div>
<div class="line"><a name="l00116"></a><span class="lineno"> 116</span> <span class="keyword">template</span><<span class="keyword">typename</span> SCALARTYPE></div>
<div class="line"><a name="l00117"></a><span class="lineno"><a class="line" href="namespaceviennacl_1_1linalg_1_1cuda.html#a0830a649eef44ee28c7c6ecc68b6d68d"> 117</a></span> <span class="keyword">inline</span> __host__ __device__ double2 <a class="code" href="namespaceviennacl_1_1linalg_1_1cuda.html#a6b46337d1aab49f0bc5d20e2699e4231">operator/</a>(double2 a,SCALARTYPE b)</div>
<div class="line"><a name="l00118"></a><span class="lineno"> 118</span> {</div>
<div class="line"><a name="l00119"></a><span class="lineno"> 119</span>  <span class="keywordflow">return</span> make_double2(a.x/b, a.y/b);</div>
<div class="line"><a name="l00120"></a><span class="lineno"> 120</span> }</div>
<div class="line"><a name="l00121"></a><span class="lineno"> 121</span> </div>
<div class="line"><a name="l00122"></a><span class="lineno"> 122</span> <span class="comment">//multiplication</span></div>
<div class="line"><a name="l00123"></a><span class="lineno"><a class="line" href="namespaceviennacl_1_1linalg_1_1cuda.html#aa7099a1c89cf870fad5b1fa8c4378bfd"> 123</a></span> <span class="keyword">inline</span> __host__ __device__ double2 <a class="code" href="namespaceviennacl_1_1linalg_1_1cuda.html#a1e6214e945b8d60ea371f578f5ee58db">operator*</a>(double2 in1, double2 in2)</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>  <span class="keywordflow">return</span> make_double2(in1.x * in2.x - in1.y * in2.y, in1.x * in2.y + in1.y * in2.x);</div>
<div class="line"><a name="l00126"></a><span class="lineno"> 126</span> }</div>
<div class="line"><a name="l00127"></a><span class="lineno"> 127</span> </div>
<div class="line"><a name="l00128"></a><span class="lineno"><a class="line" href="namespaceviennacl_1_1linalg_1_1cuda.html#aa55045c0b6db4bd69bc523b5243320fc"> 128</a></span> <span class="keyword">inline</span> __device__ <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> <a class="code" href="namespaceviennacl_1_1linalg_1_1cuda.html#aa55045c0b6db4bd69bc523b5243320fc">get_reorder_num</a>(<span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> v, <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> bit_size)</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>  v = ((v >> 1) & 0x55555555) | ((v & 0x55555555) << 1);</div>
<div class="line"><a name="l00131"></a><span class="lineno"> 131</span>  v = ((v >> 2) & 0x33333333) | ((v & 0x33333333) << 2);</div>
<div class="line"><a name="l00132"></a><span class="lineno"> 132</span>  v = ((v >> 4) & 0x0F0F0F0F) | ((v & 0x0F0F0F0F) << 4);</div>
<div class="line"><a name="l00133"></a><span class="lineno"> 133</span>  v = ((v >> 8) & 0x00FF00FF) | ((v & 0x00FF00FF) << 8);</div>
<div class="line"><a name="l00134"></a><span class="lineno"> 134</span>  v = (v >> 16) | (v << 16);</div>
<div class="line"><a name="l00135"></a><span class="lineno"> 135</span>  v = v >> (32 - bit_size);</div>
<div class="line"><a name="l00136"></a><span class="lineno"> 136</span>  <span class="keywordflow">return</span> v;</div>
<div class="line"><a name="l00137"></a><span class="lineno"> 137</span> }</div>
<div class="line"><a name="l00138"></a><span class="lineno"> 138</span> </div>
<div class="line"><a name="l00139"></a><span class="lineno"> 139</span> <span class="keyword">template</span><<span class="keyword">typename</span> Numeric2T, <span class="keyword">typename</span> NumericT></div>
<div class="line"><a name="l00140"></a><span class="lineno"><a class="line" href="namespaceviennacl_1_1linalg_1_1cuda.html#a4284d9526bb5275f446048381072c1c1"> 140</a></span> __global__ <span class="keywordtype">void</span> <a class="code" href="namespaceviennacl_1_1linalg_1_1cuda.html#a4284d9526bb5275f446048381072c1c1">fft_direct</a>(</div>
<div class="line"><a name="l00141"></a><span class="lineno"> 141</span>  <span class="keyword">const</span> Numeric2T * input,</div>
<div class="line"><a name="l00142"></a><span class="lineno"> 142</span>  Numeric2T * output,</div>
<div class="line"><a name="l00143"></a><span class="lineno"> 143</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="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#a09997870f4802fa5d4ac2c43cf4020d1">stride</a>,</div>
<div class="line"><a name="l00145"></a><span class="lineno"> 145</span>  <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> batch_num,</div>
<div class="line"><a name="l00146"></a><span class="lineno"> 146</span>  <a class="code" href="tests_2src_2bisect_8cpp.html#a52b5d30a2d7b064678644a3bf49b7f6c">NumericT</a> <a class="code" href="namespaceviennacl_1_1linalg_1_1detail.html#a7bfa1c9cb0afb4ca0f975e690f4a8f07">sign</a>,</div>
<div class="line"><a name="l00147"></a><span class="lineno"> 147</span>  <span class="keywordtype">bool</span> <a class="code" href="structviennacl_1_1is__row__major.html">is_row_major</a>)</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> </div>
<div class="line"><a name="l00150"></a><span class="lineno"> 150</span>  <span class="keyword">const</span> <a class="code" href="tests_2src_2bisect_8cpp.html#a52b5d30a2d7b064678644a3bf49b7f6c">NumericT</a> NUM_PI(3.14159265358979323846);</div>
<div class="line"><a name="l00151"></a><span class="lineno"> 151</span> </div>
<div class="line"><a name="l00152"></a><span class="lineno"> 152</span>  <span class="keywordflow">for</span> (<span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> batch_id = 0; batch_id < batch_num; batch_id++)</div>
<div class="line"><a name="l00153"></a><span class="lineno"> 153</span>  {</div>
<div class="line"><a name="l00154"></a><span class="lineno"> 154</span>  <span class="keywordflow">for</span> (<span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> k = blockIdx.x * blockDim.x + threadIdx.x; k < size; k += gridDim.x * blockDim.x)</div>
<div class="line"><a name="l00155"></a><span class="lineno"> 155</span>  {</div>
<div class="line"><a name="l00156"></a><span class="lineno"> 156</span>  Numeric2T f;</div>
<div class="line"><a name="l00157"></a><span class="lineno"> 157</span>  f.x = 0;</div>
<div class="line"><a name="l00158"></a><span class="lineno"> 158</span>  f.y = 0;</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>  <span class="keywordflow">for</span> (<span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> n = 0; n < <a class="code" href="namespaceviennacl_1_1traits.html#aa2344ea20469f55fbc15a8e9526494d0">size</a>; n++)</div>
<div class="line"><a name="l00161"></a><span class="lineno"> 161</span>  {</div>
<div class="line"><a name="l00162"></a><span class="lineno"> 162</span>  Numeric2T in;</div>
<div class="line"><a name="l00163"></a><span class="lineno"> 163</span>  <span class="keywordflow">if</span> (!is_row_major)</div>
<div class="line"><a name="l00164"></a><span class="lineno"> 164</span>  in = input[batch_id * stride + n]; <span class="comment">//input index here</span></div>
<div class="line"><a name="l00165"></a><span class="lineno"> 165</span>  <span class="keywordflow">else</span></div>
<div class="line"><a name="l00166"></a><span class="lineno"> 166</span>  in = input[n * stride + batch_id];<span class="comment">//input index here</span></div>
<div class="line"><a name="l00167"></a><span class="lineno"> 167</span> </div>
<div class="line"><a name="l00168"></a><span class="lineno"> 168</span>  <a class="code" href="tests_2src_2bisect_8cpp.html#a52b5d30a2d7b064678644a3bf49b7f6c">NumericT</a> sn,cs;</div>
<div class="line"><a name="l00169"></a><span class="lineno"> 169</span>  <a class="code" href="tests_2src_2bisect_8cpp.html#a52b5d30a2d7b064678644a3bf49b7f6c">NumericT</a> arg = sign * 2 * NUM_PI * k / size * n;</div>
<div class="line"><a name="l00170"></a><span class="lineno"> 170</span>  sn = sin(arg);</div>
<div class="line"><a name="l00171"></a><span class="lineno"> 171</span>  cs = cos(arg);</div>
<div class="line"><a name="l00172"></a><span class="lineno"> 172</span> </div>
<div class="line"><a name="l00173"></a><span class="lineno"> 173</span>  Numeric2T ex;</div>
<div class="line"><a name="l00174"></a><span class="lineno"> 174</span>  ex.x = cs;</div>
<div class="line"><a name="l00175"></a><span class="lineno"> 175</span>  ex.y = sn;</div>
<div class="line"><a name="l00176"></a><span class="lineno"> 176</span>  Numeric2T tmp;</div>
<div class="line"><a name="l00177"></a><span class="lineno"> 177</span>  tmp.x = in.x * ex.x - in.y * ex.y;</div>
<div class="line"><a name="l00178"></a><span class="lineno"> 178</span>  tmp.y = in.x * ex.y + in.y * ex.x;</div>
<div class="line"><a name="l00179"></a><span class="lineno"> 179</span>  f = f + tmp;</div>
<div class="line"><a name="l00180"></a><span class="lineno"> 180</span>  }</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="keywordflow">if</span> (!is_row_major)</div>
<div class="line"><a name="l00183"></a><span class="lineno"> 183</span>  output[batch_id * stride + k] = f; <span class="comment">// output index here</span></div>
<div class="line"><a name="l00184"></a><span class="lineno"> 184</span>  <span class="keywordflow">else</span></div>
<div class="line"><a name="l00185"></a><span class="lineno"> 185</span>  output[k * stride + batch_id] = f;<span class="comment">// output index here</span></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>  }</div>
<div class="line"><a name="l00188"></a><span class="lineno"> 188</span> }</div>
<div class="line"><a name="l00189"></a><span class="lineno"> 189</span> </div>
<div class="line"><a name="l00196"></a><span class="lineno"> 196</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="l00197"></a><span class="lineno"><a class="line" href="namespaceviennacl_1_1linalg_1_1cuda.html#ac69a0d15af9665507cd4df1493e24070"> 197</a></span> <span class="keywordtype">void</span> <a class="code" href="namespaceviennacl_1_1linalg_1_1cuda.html#ac69a0d15af9665507cd4df1493e24070">direct</a>(<a class="code" href="classviennacl_1_1vector.html">viennacl::vector<NumericT, AlignmentV></a> <span class="keyword">const</span> & in,</div>
<div class="line"><a name="l00198"></a><span class="lineno"> 198</span>  <a class="code" href="classviennacl_1_1vector.html">viennacl::vector<NumericT, AlignmentV></a> & out,</div>
<div class="line"><a name="l00199"></a><span class="lineno"> 199</span>  <a class="code" href="namespaceviennacl.html#a98a0afcc513111ffa0bd138f891930df">vcl_size_t</a> <a class="code" href="namespaceviennacl_1_1traits.html#aa2344ea20469f55fbc15a8e9526494d0">size</a>, <a class="code" href="namespaceviennacl.html#a98a0afcc513111ffa0bd138f891930df">vcl_size_t</a> <a class="code" href="namespaceviennacl_1_1traits.html#a09997870f4802fa5d4ac2c43cf4020d1">stride</a>, <a class="code" href="namespaceviennacl.html#a98a0afcc513111ffa0bd138f891930df">vcl_size_t</a> batch_num,</div>
<div class="line"><a name="l00200"></a><span class="lineno"> 200</span>  <a class="code" href="tests_2src_2bisect_8cpp.html#a52b5d30a2d7b064678644a3bf49b7f6c">NumericT</a> <a class="code" href="namespaceviennacl_1_1linalg_1_1detail.html#a7bfa1c9cb0afb4ca0f975e690f4a8f07">sign</a> = <a class="code" href="tests_2src_2bisect_8cpp.html#a52b5d30a2d7b064678644a3bf49b7f6c">NumericT</a>(-1),</div>
<div class="line"><a name="l00201"></a><span class="lineno"> 201</span>  <a class="code" href="namespaceviennacl_1_1linalg_1_1host__based_1_1detail_1_1fft_1_1_f_f_t___d_a_t_a___o_r_d_e_r.html#aac2583f16e35875f2696e9220bd262f2">viennacl::linalg::host_based::detail::fft::FFT_DATA_ORDER::DATA_ORDER</a> data_order = <a class="code" href="namespaceviennacl_1_1linalg_1_1host__based_1_1detail_1_1fft_1_1_f_f_t___d_a_t_a___o_r_d_e_r.html#aac2583f16e35875f2696e9220bd262f2afffdaee3461226037812d7c99faf6e1b">viennacl::linalg::host_based::detail::fft::FFT_DATA_ORDER::ROW_MAJOR</a>)</div>
<div class="line"><a name="l00202"></a><span class="lineno"> 202</span> {</div>
<div class="line"><a name="l00203"></a><span class="lineno"> 203</span>  <span class="keyword">typedef</span> <span class="keyword">typename</span> <a class="code" href="structviennacl_1_1linalg_1_1cuda_1_1detail_1_1type__to__type2.html">viennacl::linalg::cuda::detail::type_to_type2<NumericT>::type</a> numeric2_type;</div>
<div class="line"><a name="l00204"></a><span class="lineno"> 204</span> </div>
<div class="line"><a name="l00205"></a><span class="lineno"> 205</span>  fft_direct<<<128,128>>>(<span class="keyword">reinterpret_cast<</span><span class="keyword">const </span>numeric2_type *<span class="keyword">></span>(<a class="code" href="namespaceviennacl.html#ae7d5db0c2c91be75218db5b52c4d13da">viennacl::cuda_arg</a>(in)),</div>
<div class="line"><a name="l00206"></a><span class="lineno"> 206</span>  reinterpret_cast< numeric2_type *>(<a class="code" href="namespaceviennacl.html#ae7d5db0c2c91be75218db5b52c4d13da">viennacl::cuda_arg</a>(out)),</div>
<div class="line"><a name="l00207"></a><span class="lineno"> 207</span>  static_cast<unsigned int>(size),</div>
<div class="line"><a name="l00208"></a><span class="lineno"> 208</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#a09997870f4802fa5d4ac2c43cf4020d1">stride</a>),</div>
<div class="line"><a name="l00209"></a><span class="lineno"> 209</span>  static_cast<unsigned int>(batch_num),</div>
<div class="line"><a name="l00210"></a><span class="lineno"> 210</span>  <a class="code" href="namespaceviennacl_1_1linalg_1_1detail.html#a7bfa1c9cb0afb4ca0f975e690f4a8f07">sign</a>,</div>
<div class="line"><a name="l00211"></a><span class="lineno"> 211</span>  bool(data_order != <a class="code" href="namespaceviennacl_1_1linalg_1_1host__based_1_1detail_1_1fft_1_1_f_f_t___d_a_t_a___o_r_d_e_r.html#aac2583f16e35875f2696e9220bd262f2afffdaee3461226037812d7c99faf6e1b">viennacl::linalg::host_based::detail::fft::FFT_DATA_ORDER::ROW_MAJOR</a>));</div>
<div class="line"><a name="l00212"></a><span class="lineno"> 212</span>  <a class="code" href="linalg_2cuda_2common_8hpp.html#acdb31f22f4d1e12f1c2a27d4c4aa6865">VIENNACL_CUDA_LAST_ERROR_CHECK</a>(<span class="stringliteral">"fft_direct"</span>);</div>
<div class="line"><a name="l00213"></a><span class="lineno"> 213</span> }</div>
<div class="line"><a name="l00214"></a><span class="lineno"> 214</span> </div>
<div class="line"><a name="l00221"></a><span class="lineno"> 221</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="l00222"></a><span class="lineno"><a class="line" href="namespaceviennacl_1_1linalg_1_1cuda.html#a45552f281789dd7a0dd7d27b966af3fb"> 222</a></span> <span class="keywordtype">void</span> <a class="code" href="namespaceviennacl_1_1linalg_1_1cuda.html#ac69a0d15af9665507cd4df1493e24070">direct</a>(<a class="code" href="classviennacl_1_1matrix.html">viennacl::matrix<NumericT, viennacl::row_major, AlignmentV></a> <span class="keyword">const</span> & in,</div>
<div class="line"><a name="l00223"></a><span class="lineno"> 223</span>  <a class="code" href="classviennacl_1_1matrix.html">viennacl::matrix<NumericT, viennacl::row_major, AlignmentV></a> & out,</div>
<div class="line"><a name="l00224"></a><span class="lineno"> 224</span>  <a class="code" href="namespaceviennacl.html#a98a0afcc513111ffa0bd138f891930df">vcl_size_t</a> size, <a class="code" href="namespaceviennacl.html#a98a0afcc513111ffa0bd138f891930df">vcl_size_t</a> stride, <a class="code" href="namespaceviennacl.html#a98a0afcc513111ffa0bd138f891930df">vcl_size_t</a> batch_num,</div>
<div class="line"><a name="l00225"></a><span class="lineno"> 225</span>  <a class="code" href="tests_2src_2bisect_8cpp.html#a52b5d30a2d7b064678644a3bf49b7f6c">NumericT</a> <a class="code" href="namespaceviennacl_1_1linalg_1_1detail.html#a7bfa1c9cb0afb4ca0f975e690f4a8f07">sign</a> = <a class="code" href="tests_2src_2bisect_8cpp.html#a52b5d30a2d7b064678644a3bf49b7f6c">NumericT</a>(-1),</div>
<div class="line"><a name="l00226"></a><span class="lineno"> 226</span>  <a class="code" href="namespaceviennacl_1_1linalg_1_1host__based_1_1detail_1_1fft_1_1_f_f_t___d_a_t_a___o_r_d_e_r.html#aac2583f16e35875f2696e9220bd262f2">viennacl::linalg::host_based::detail::fft::FFT_DATA_ORDER::DATA_ORDER</a> data_order = <a class="code" href="namespaceviennacl_1_1linalg_1_1host__based_1_1detail_1_1fft_1_1_f_f_t___d_a_t_a___o_r_d_e_r.html#aac2583f16e35875f2696e9220bd262f2afffdaee3461226037812d7c99faf6e1b">viennacl::linalg::host_based::detail::fft::FFT_DATA_ORDER::ROW_MAJOR</a>)</div>
<div class="line"><a name="l00227"></a><span class="lineno"> 227</span> {</div>
<div class="line"><a name="l00228"></a><span class="lineno"> 228</span>  <span class="keyword">typedef</span> <span class="keyword">typename</span> <a class="code" href="structviennacl_1_1linalg_1_1cuda_1_1detail_1_1type__to__type2.html">viennacl::linalg::cuda::detail::type_to_type2<NumericT>::type</a> numeric2_type;</div>
<div class="line"><a name="l00229"></a><span class="lineno"> 229</span> </div>
<div class="line"><a name="l00230"></a><span class="lineno"> 230</span>  fft_direct<<<128,128>>>(<span class="keyword">reinterpret_cast<</span><span class="keyword">const </span>numeric2_type *<span class="keyword">></span>(<a class="code" href="namespaceviennacl.html#ae7d5db0c2c91be75218db5b52c4d13da">viennacl::cuda_arg</a>(in)),</div>
<div class="line"><a name="l00231"></a><span class="lineno"> 231</span>  reinterpret_cast< numeric2_type *>(<a class="code" href="namespaceviennacl.html#ae7d5db0c2c91be75218db5b52c4d13da">viennacl::cuda_arg</a>(out)),</div>
<div class="line"><a name="l00232"></a><span class="lineno"> 232</span>  static_cast<unsigned int>(size),</div>
<div class="line"><a name="l00233"></a><span class="lineno"> 233</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#a09997870f4802fa5d4ac2c43cf4020d1">stride</a>),</div>
<div class="line"><a name="l00234"></a><span class="lineno"> 234</span>  static_cast<unsigned int>(batch_num),</div>
<div class="line"><a name="l00235"></a><span class="lineno"> 235</span>  <a class="code" href="namespaceviennacl_1_1linalg_1_1detail.html#a7bfa1c9cb0afb4ca0f975e690f4a8f07">sign</a>,</div>
<div class="line"><a name="l00236"></a><span class="lineno"> 236</span>  bool(data_order != <a class="code" href="namespaceviennacl_1_1linalg_1_1host__based_1_1detail_1_1fft_1_1_f_f_t___d_a_t_a___o_r_d_e_r.html#aac2583f16e35875f2696e9220bd262f2afffdaee3461226037812d7c99faf6e1b">viennacl::linalg::host_based::detail::fft::FFT_DATA_ORDER::ROW_MAJOR</a>));</div>
<div class="line"><a name="l00237"></a><span class="lineno"> 237</span>  <a class="code" href="linalg_2cuda_2common_8hpp.html#acdb31f22f4d1e12f1c2a27d4c4aa6865">VIENNACL_CUDA_LAST_ERROR_CHECK</a>(<span class="stringliteral">"fft_direct"</span>);</div>
<div class="line"><a name="l00238"></a><span class="lineno"> 238</span> }</div>
<div class="line"><a name="l00239"></a><span class="lineno"> 239</span> </div>
<div class="line"><a name="l00240"></a><span class="lineno"> 240</span> <span class="keyword">template</span><<span class="keyword">typename</span> NumericT></div>
<div class="line"><a name="l00241"></a><span class="lineno"><a class="line" href="namespaceviennacl_1_1linalg_1_1cuda.html#a549bb69fa59c1d82ec34402e917db258"> 241</a></span> __global__ <span class="keywordtype">void</span> <a class="code" href="namespaceviennacl_1_1linalg_1_1cuda.html#a549bb69fa59c1d82ec34402e917db258">fft_reorder</a>(<a class="code" href="tests_2src_2bisect_8cpp.html#a52b5d30a2d7b064678644a3bf49b7f6c">NumericT</a> * input,</div>
<div class="line"><a name="l00242"></a><span class="lineno"> 242</span>  <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> bit_size,</div>
<div class="line"><a name="l00243"></a><span class="lineno"> 243</span>  <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> size,</div>
<div class="line"><a name="l00244"></a><span class="lineno"> 244</span>  <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> stride,</div>
<div class="line"><a name="l00245"></a><span class="lineno"> 245</span>  <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> batch_num,</div>
<div class="line"><a name="l00246"></a><span class="lineno"> 246</span>  <span class="keywordtype">bool</span> <a class="code" href="structviennacl_1_1is__row__major.html">is_row_major</a>)</div>
<div class="line"><a name="l00247"></a><span class="lineno"> 247</span> {</div>
<div class="line"><a name="l00248"></a><span class="lineno"> 248</span> </div>
<div class="line"><a name="l00249"></a><span class="lineno"> 249</span>  <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> glb_id = blockIdx.x * blockDim.x + threadIdx.x;</div>
<div class="line"><a name="l00250"></a><span class="lineno"> 250</span>  <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> glb_sz = gridDim.x * blockDim.x;</div>
<div class="line"><a name="l00251"></a><span class="lineno"> 251</span> </div>
<div class="line"><a name="l00252"></a><span class="lineno"> 252</span>  <span class="keywordflow">for</span> (<span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> batch_id = 0; batch_id < batch_num; batch_id++)</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>  <span class="keywordflow">for</span> (<span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> i = glb_id; i < <a class="code" href="namespaceviennacl_1_1traits.html#aa2344ea20469f55fbc15a8e9526494d0">size</a>; i += glb_sz)</div>
<div class="line"><a name="l00255"></a><span class="lineno"> 255</span>  {</div>
<div class="line"><a name="l00256"></a><span class="lineno"> 256</span>  <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> v = <a class="code" href="namespaceviennacl_1_1linalg_1_1cuda.html#aa55045c0b6db4bd69bc523b5243320fc">get_reorder_num</a>(i, bit_size);</div>
<div class="line"><a name="l00257"></a><span class="lineno"> 257</span> </div>
<div class="line"><a name="l00258"></a><span class="lineno"> 258</span>  <span class="keywordflow">if</span> (i < v)</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>  <span class="keywordflow">if</span> (!is_row_major)</div>
<div class="line"><a name="l00261"></a><span class="lineno"> 261</span>  {</div>
<div class="line"><a name="l00262"></a><span class="lineno"> 262</span>  <a class="code" href="tests_2src_2bisect_8cpp.html#a52b5d30a2d7b064678644a3bf49b7f6c">NumericT</a> tmp = input[batch_id * stride + i]; <span class="comment">// index</span></div>
<div class="line"><a name="l00263"></a><span class="lineno"> 263</span>  input[batch_id * stride + i] = input[batch_id * stride + v];<span class="comment">//index</span></div>
<div class="line"><a name="l00264"></a><span class="lineno"> 264</span>  input[batch_id * stride + v] = tmp;<span class="comment">//index</span></div>
<div class="line"><a name="l00265"></a><span class="lineno"> 265</span>  }</div>
<div class="line"><a name="l00266"></a><span class="lineno"> 266</span>  <span class="keywordflow">else</span></div>
<div class="line"><a name="l00267"></a><span class="lineno"> 267</span>  {</div>
<div class="line"><a name="l00268"></a><span class="lineno"> 268</span>  <a class="code" href="tests_2src_2bisect_8cpp.html#a52b5d30a2d7b064678644a3bf49b7f6c">NumericT</a> tmp = input[i * stride + batch_id];</div>
<div class="line"><a name="l00269"></a><span class="lineno"> 269</span>  input[i * stride + batch_id] = input[v * stride + batch_id];</div>
<div class="line"><a name="l00270"></a><span class="lineno"> 270</span>  input[v * stride + batch_id] = tmp;</div>
<div class="line"><a name="l00271"></a><span class="lineno"> 271</span>  }</div>
<div class="line"><a name="l00272"></a><span class="lineno"> 272</span>  }</div>
<div class="line"><a name="l00273"></a><span class="lineno"> 273</span>  }</div>
<div class="line"><a name="l00274"></a><span class="lineno"> 274</span>  }</div>
<div class="line"><a name="l00275"></a><span class="lineno"> 275</span> }</div>
<div class="line"><a name="l00276"></a><span class="lineno"> 276</span> </div>
<div class="line"><a name="l00277"></a><span class="lineno"> 277</span> <span class="comment">/***</span></div>
<div class="line"><a name="l00278"></a><span class="lineno"> 278</span> <span class="comment"> * This function performs reorder of input data. Indexes are sorted in bit-reversal order.</span></div>
<div class="line"><a name="l00279"></a><span class="lineno"> 279</span> <span class="comment"> * Such reordering should be done before in-place FFT.</span></div>
<div class="line"><a name="l00280"></a><span class="lineno"> 280</span> <span class="comment"> */</span></div>
<div class="line"><a name="l00281"></a><span class="lineno"> 281</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="l00282"></a><span class="lineno"><a class="line" href="namespaceviennacl_1_1linalg_1_1cuda.html#a479324e6bbbd101136667151607e3d0a"> 282</a></span> <span class="keywordtype">void</span> <a class="code" href="namespaceviennacl_1_1linalg_1_1cuda.html#a479324e6bbbd101136667151607e3d0a">reorder</a>(<a class="code" href="classviennacl_1_1vector.html">viennacl::vector<NumericT, AlignmentV></a> & in,</div>
<div class="line"><a name="l00283"></a><span class="lineno"> 283</span>  <a class="code" href="namespaceviennacl.html#a98a0afcc513111ffa0bd138f891930df">vcl_size_t</a> size, <a class="code" href="namespaceviennacl.html#a98a0afcc513111ffa0bd138f891930df">vcl_size_t</a> stride, <a class="code" href="namespaceviennacl.html#a98a0afcc513111ffa0bd138f891930df">vcl_size_t</a> bits_datasize, <a class="code" href="namespaceviennacl.html#a98a0afcc513111ffa0bd138f891930df">vcl_size_t</a> batch_num,</div>
<div class="line"><a name="l00284"></a><span class="lineno"> 284</span>  <a class="code" href="namespaceviennacl_1_1linalg_1_1host__based_1_1detail_1_1fft_1_1_f_f_t___d_a_t_a___o_r_d_e_r.html#aac2583f16e35875f2696e9220bd262f2">viennacl::linalg::host_based::detail::fft::FFT_DATA_ORDER::DATA_ORDER</a> data_order = <a class="code" href="namespaceviennacl_1_1linalg_1_1host__based_1_1detail_1_1fft_1_1_f_f_t___d_a_t_a___o_r_d_e_r.html#aac2583f16e35875f2696e9220bd262f2afffdaee3461226037812d7c99faf6e1b">viennacl::linalg::host_based::detail::fft::FFT_DATA_ORDER::ROW_MAJOR</a>)</div>
<div class="line"><a name="l00285"></a><span class="lineno"> 285</span> {</div>
<div class="line"><a name="l00286"></a><span class="lineno"> 286</span>  <span class="keyword">typedef</span> <span class="keyword">typename</span> <a class="code" href="structviennacl_1_1linalg_1_1cuda_1_1detail_1_1type__to__type2.html">viennacl::linalg::cuda::detail::type_to_type2<NumericT>::type</a> numeric2_type;</div>
<div class="line"><a name="l00287"></a><span class="lineno"> 287</span> </div>
<div class="line"><a name="l00288"></a><span class="lineno"> 288</span>  fft_reorder<<<128,128>>>(<span class="keyword">reinterpret_cast<</span>numeric2_type *<span class="keyword">></span>(<a class="code" href="namespaceviennacl.html#ae7d5db0c2c91be75218db5b52c4d13da">viennacl::cuda_arg</a>(in)),</div>
<div class="line"><a name="l00289"></a><span class="lineno"> 289</span>  static_cast<unsigned int>(bits_datasize),</div>
<div class="line"><a name="l00290"></a><span class="lineno"> 290</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#aa2344ea20469f55fbc15a8e9526494d0">size</a>),</div>
<div class="line"><a name="l00291"></a><span class="lineno"> 291</span>  static_cast<unsigned int>(stride),</div>
<div class="line"><a name="l00292"></a><span class="lineno"> 292</span>  <span class="keyword">static_cast<</span><span class="keywordtype">unsigned</span> <span class="keywordtype">int</span><span class="keyword">></span>(batch_num),</div>
<div class="line"><a name="l00293"></a><span class="lineno"> 293</span>  static_cast<bool>(data_order));</div>
<div class="line"><a name="l00294"></a><span class="lineno"> 294</span>  <a class="code" href="linalg_2cuda_2common_8hpp.html#acdb31f22f4d1e12f1c2a27d4c4aa6865">VIENNACL_CUDA_LAST_ERROR_CHECK</a>(<span class="stringliteral">"fft_reorder"</span>);</div>
<div class="line"><a name="l00295"></a><span class="lineno"> 295</span> }</div>
<div class="line"><a name="l00296"></a><span class="lineno"> 296</span> </div>
<div class="line"><a name="l00297"></a><span class="lineno"> 297</span> <span class="keyword">template</span><<span class="keyword">typename</span> Numeric2T, <span class="keyword">typename</span> NumericT></div>
<div class="line"><a name="l00298"></a><span class="lineno"><a class="line" href="namespaceviennacl_1_1linalg_1_1cuda.html#ad2f2f30942dedf7d5ab7adc5a282bb32"> 298</a></span> __global__ <span class="keywordtype">void</span> <a class="code" href="namespaceviennacl_1_1linalg_1_1cuda.html#ad2f2f30942dedf7d5ab7adc5a282bb32">fft_radix2_local</a>(Numeric2T * input,</div>
<div class="line"><a name="l00299"></a><span class="lineno"> 299</span>  <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> bit_size,</div>
<div class="line"><a name="l00300"></a><span class="lineno"> 300</span>  <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> size,</div>
<div class="line"><a name="l00301"></a><span class="lineno"> 301</span>  <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> stride,</div>
<div class="line"><a name="l00302"></a><span class="lineno"> 302</span>  <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> batch_num,</div>
<div class="line"><a name="l00303"></a><span class="lineno"> 303</span>  <a class="code" href="tests_2src_2bisect_8cpp.html#a52b5d30a2d7b064678644a3bf49b7f6c">NumericT</a> <a class="code" href="namespaceviennacl_1_1linalg_1_1detail.html#a7bfa1c9cb0afb4ca0f975e690f4a8f07">sign</a>,</div>
<div class="line"><a name="l00304"></a><span class="lineno"> 304</span>  <span class="keywordtype">bool</span> <a class="code" href="structviennacl_1_1is__row__major.html">is_row_major</a>)</div>
<div class="line"><a name="l00305"></a><span class="lineno"> 305</span> {</div>
<div class="line"><a name="l00306"></a><span class="lineno"> 306</span>  __shared__ Numeric2T lcl_input[1024];</div>
<div class="line"><a name="l00307"></a><span class="lineno"> 307</span>  <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> grp_id = blockIdx.x;</div>
<div class="line"><a name="l00308"></a><span class="lineno"> 308</span>  <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> grp_num = gridDim.x;</div>
<div class="line"><a name="l00309"></a><span class="lineno"> 309</span> </div>
<div class="line"><a name="l00310"></a><span class="lineno"> 310</span>  <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> lcl_sz = blockDim.x;</div>
<div class="line"><a name="l00311"></a><span class="lineno"> 311</span>  <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> lcl_id = threadIdx.x;</div>
<div class="line"><a name="l00312"></a><span class="lineno"> 312</span>  <span class="keyword">const</span> <a class="code" href="tests_2src_2bisect_8cpp.html#a52b5d30a2d7b064678644a3bf49b7f6c">NumericT</a> NUM_PI(3.14159265358979323846);</div>
<div class="line"><a name="l00313"></a><span class="lineno"> 313</span> </div>
<div class="line"><a name="l00314"></a><span class="lineno"> 314</span>  <span class="keywordflow">for</span> (<span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> batch_id = grp_id; batch_id < batch_num; batch_id += grp_num)</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>  <span class="keywordflow">for</span> (<span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> p = lcl_id; p < <a class="code" href="namespaceviennacl_1_1traits.html#aa2344ea20469f55fbc15a8e9526494d0">size</a>; p += lcl_sz)</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="keywordtype">unsigned</span> <span class="keywordtype">int</span> v = <a class="code" href="namespaceviennacl_1_1linalg_1_1cuda.html#aa55045c0b6db4bd69bc523b5243320fc">get_reorder_num</a>(p, bit_size);</div>
<div class="line"><a name="l00319"></a><span class="lineno"> 319</span>  <span class="keywordflow">if</span> (!is_row_major)</div>
<div class="line"><a name="l00320"></a><span class="lineno"> 320</span>  lcl_input[v] = input[batch_id * stride + p];</div>
<div class="line"><a name="l00321"></a><span class="lineno"> 321</span>  <span class="keywordflow">else</span></div>
<div class="line"><a name="l00322"></a><span class="lineno"> 322</span>  lcl_input[v] = input[p * stride + batch_id];</div>
<div class="line"><a name="l00323"></a><span class="lineno"> 323</span>  }</div>
<div class="line"><a name="l00324"></a><span class="lineno"> 324</span> </div>
<div class="line"><a name="l00325"></a><span class="lineno"> 325</span>  __syncthreads();</div>
<div class="line"><a name="l00326"></a><span class="lineno"> 326</span> </div>
<div class="line"><a name="l00327"></a><span class="lineno"> 327</span>  <span class="comment">//performs Cooley-Tukey FFT on local arrayfft</span></div>
<div class="line"><a name="l00328"></a><span class="lineno"> 328</span>  <span class="keywordflow">for</span> (<span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> s = 0; s < bit_size; s++)</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>  <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> ss = 1 << s;</div>
<div class="line"><a name="l00331"></a><span class="lineno"> 331</span>  <a class="code" href="tests_2src_2bisect_8cpp.html#a52b5d30a2d7b064678644a3bf49b7f6c">NumericT</a> cs, sn;</div>
<div class="line"><a name="l00332"></a><span class="lineno"> 332</span>  <span class="keywordflow">for</span> (<span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> tid = lcl_id; tid < <a class="code" href="namespaceviennacl_1_1traits.html#aa2344ea20469f55fbc15a8e9526494d0">size</a>; tid += lcl_sz)</div>
<div class="line"><a name="l00333"></a><span class="lineno"> 333</span>  {</div>
<div class="line"><a name="l00334"></a><span class="lineno"> 334</span>  <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> group = (tid & (ss - 1));</div>
<div class="line"><a name="l00335"></a><span class="lineno"> 335</span>  <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> pos = ((tid >> s) << (s + 1)) + group;</div>
<div class="line"><a name="l00336"></a><span class="lineno"> 336</span> </div>
<div class="line"><a name="l00337"></a><span class="lineno"> 337</span>  Numeric2T in1 = lcl_input[pos];</div>
<div class="line"><a name="l00338"></a><span class="lineno"> 338</span>  Numeric2T in2 = lcl_input[pos + ss];</div>
<div class="line"><a name="l00339"></a><span class="lineno"> 339</span> </div>
<div class="line"><a name="l00340"></a><span class="lineno"> 340</span>  <a class="code" href="tests_2src_2bisect_8cpp.html#a52b5d30a2d7b064678644a3bf49b7f6c">NumericT</a> arg = group * sign * NUM_PI / ss;</div>
<div class="line"><a name="l00341"></a><span class="lineno"> 341</span> </div>
<div class="line"><a name="l00342"></a><span class="lineno"> 342</span>  sn = sin(arg);</div>
<div class="line"><a name="l00343"></a><span class="lineno"> 343</span>  cs = cos(arg);</div>
<div class="line"><a name="l00344"></a><span class="lineno"> 344</span>  Numeric2T ex;</div>
<div class="line"><a name="l00345"></a><span class="lineno"> 345</span>  ex.x = cs;</div>
<div class="line"><a name="l00346"></a><span class="lineno"> 346</span>  ex.y = sn;</div>
<div class="line"><a name="l00347"></a><span class="lineno"> 347</span> </div>
<div class="line"><a name="l00348"></a><span class="lineno"> 348</span>  Numeric2T tmp;</div>
<div class="line"><a name="l00349"></a><span class="lineno"> 349</span>  tmp.x = in2.x * ex.x - in2.y * ex.y;</div>
<div class="line"><a name="l00350"></a><span class="lineno"> 350</span>  tmp.y = in2.x * ex.y + in2.y * ex.x;</div>
<div class="line"><a name="l00351"></a><span class="lineno"> 351</span> </div>
<div class="line"><a name="l00352"></a><span class="lineno"> 352</span>  lcl_input[pos + ss] = in1 - tmp;</div>
<div class="line"><a name="l00353"></a><span class="lineno"> 353</span>  lcl_input[pos] = in1 + tmp;</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>  __syncthreads();</div>
<div class="line"><a name="l00356"></a><span class="lineno"> 356</span>  }</div>
<div class="line"><a name="l00357"></a><span class="lineno"> 357</span> </div>
<div class="line"><a name="l00358"></a><span class="lineno"> 358</span>  <span class="comment">//copy local array back to global memory</span></div>
<div class="line"><a name="l00359"></a><span class="lineno"> 359</span>  <span class="keywordflow">for</span> (<span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> p = lcl_id; p < <a class="code" href="namespaceviennacl_1_1traits.html#aa2344ea20469f55fbc15a8e9526494d0">size</a>; p += lcl_sz)</div>
<div class="line"><a name="l00360"></a><span class="lineno"> 360</span>  {</div>
<div class="line"><a name="l00361"></a><span class="lineno"> 361</span>  <span class="keywordflow">if</span> (!is_row_major)</div>
<div class="line"><a name="l00362"></a><span class="lineno"> 362</span>  input[batch_id * stride + p] = lcl_input[p]; <span class="comment">//index</span></div>
<div class="line"><a name="l00363"></a><span class="lineno"> 363</span>  <span class="keywordflow">else</span></div>
<div class="line"><a name="l00364"></a><span class="lineno"> 364</span>  input[p * stride + batch_id] = lcl_input[p];</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> </div>
<div class="line"><a name="l00367"></a><span class="lineno"> 367</span>  }</div>
<div class="line"><a name="l00368"></a><span class="lineno"> 368</span> }</div>
<div class="line"><a name="l00369"></a><span class="lineno"> 369</span> </div>
<div class="line"><a name="l00370"></a><span class="lineno"> 370</span> <span class="keyword">template</span><<span class="keyword">typename</span> Numeric2T, <span class="keyword">typename</span> NumericT></div>
<div class="line"><a name="l00371"></a><span class="lineno"><a class="line" href="namespaceviennacl_1_1linalg_1_1cuda.html#a6632b858aba1849edd0d834dab27486f"> 371</a></span> __global__ <span class="keywordtype">void</span> <a class="code" href="namespaceviennacl_1_1linalg_1_1cuda.html#a6632b858aba1849edd0d834dab27486f">fft_radix2</a>(Numeric2T * input,</div>
<div class="line"><a name="l00372"></a><span class="lineno"> 372</span>  <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> s,</div>
<div class="line"><a name="l00373"></a><span class="lineno"> 373</span>  <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> bit_size,</div>
<div class="line"><a name="l00374"></a><span class="lineno"> 374</span>  <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> size,</div>
<div class="line"><a name="l00375"></a><span class="lineno"> 375</span>  <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> stride,</div>
<div class="line"><a name="l00376"></a><span class="lineno"> 376</span>  <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> batch_num,</div>
<div class="line"><a name="l00377"></a><span class="lineno"> 377</span>  <a class="code" href="tests_2src_2bisect_8cpp.html#a52b5d30a2d7b064678644a3bf49b7f6c">NumericT</a> <a class="code" href="namespaceviennacl_1_1linalg_1_1detail.html#a7bfa1c9cb0afb4ca0f975e690f4a8f07">sign</a>,</div>
<div class="line"><a name="l00378"></a><span class="lineno"> 378</span>  <span class="keywordtype">bool</span> <a class="code" href="structviennacl_1_1is__row__major.html">is_row_major</a>)</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>  <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> ss = 1 << s;</div>
<div class="line"><a name="l00382"></a><span class="lineno"> 382</span>  <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> half_size = size >> 1;</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>  <a class="code" href="tests_2src_2bisect_8cpp.html#a52b5d30a2d7b064678644a3bf49b7f6c">NumericT</a> cs, sn;</div>
<div class="line"><a name="l00385"></a><span class="lineno"> 385</span>  <span class="keyword">const</span> <a class="code" href="tests_2src_2bisect_8cpp.html#a52b5d30a2d7b064678644a3bf49b7f6c">NumericT</a> NUM_PI(3.14159265358979323846);</div>
<div class="line"><a name="l00386"></a><span class="lineno"> 386</span> </div>
<div class="line"><a name="l00387"></a><span class="lineno"> 387</span>  <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> glb_id = blockIdx.x * blockDim.x + threadIdx.x;</div>
<div class="line"><a name="l00388"></a><span class="lineno"> 388</span>  <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> glb_sz = gridDim.x * blockDim.x;</div>
<div class="line"><a name="l00389"></a><span class="lineno"> 389</span> </div>
<div class="line"><a name="l00390"></a><span class="lineno"> 390</span>  <span class="keywordflow">for</span> (<span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> batch_id = 0; batch_id < batch_num; batch_id++)</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="keywordflow">for</span> (<span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> tid = glb_id; tid < half_size; tid += glb_sz)</div>
<div class="line"><a name="l00393"></a><span class="lineno"> 393</span>  {</div>
<div class="line"><a name="l00394"></a><span class="lineno"> 394</span>  <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> group = (tid & (ss - 1));</div>
<div class="line"><a name="l00395"></a><span class="lineno"> 395</span>  <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> pos = ((tid >> s) << (s + 1)) + group;</div>
<div class="line"><a name="l00396"></a><span class="lineno"> 396</span>  Numeric2T in1;</div>
<div class="line"><a name="l00397"></a><span class="lineno"> 397</span>  Numeric2T in2;</div>
<div class="line"><a name="l00398"></a><span class="lineno"> 398</span>  <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> offset;</div>
<div class="line"><a name="l00399"></a><span class="lineno"> 399</span>  <span class="keywordflow">if</span> (!is_row_major)</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>  offset = batch_id * stride + pos;</div>
<div class="line"><a name="l00402"></a><span class="lineno"> 402</span>  in1 = input[offset]; <span class="comment">//index</span></div>
<div class="line"><a name="l00403"></a><span class="lineno"> 403</span>  in2 = input[offset + ss];<span class="comment">//index</span></div>
<div class="line"><a name="l00404"></a><span class="lineno"> 404</span>  }</div>
<div class="line"><a name="l00405"></a><span class="lineno"> 405</span>  <span class="keywordflow">else</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>  offset = pos * stride + batch_id;</div>
<div class="line"><a name="l00408"></a><span class="lineno"> 408</span>  in1 = input[offset]; <span class="comment">//index</span></div>
<div class="line"><a name="l00409"></a><span class="lineno"> 409</span>  in2 = input[offset + ss * <a class="code" href="namespaceviennacl_1_1traits.html#a09997870f4802fa5d4ac2c43cf4020d1">stride</a>];<span class="comment">//index</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>  <a class="code" href="tests_2src_2bisect_8cpp.html#a52b5d30a2d7b064678644a3bf49b7f6c">NumericT</a> arg = group * sign * NUM_PI / ss;</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>  sn = sin(arg);</div>
<div class="line"><a name="l00415"></a><span class="lineno"> 415</span>  cs = cos(arg);</div>
<div class="line"><a name="l00416"></a><span class="lineno"> 416</span> </div>
<div class="line"><a name="l00417"></a><span class="lineno"> 417</span>  Numeric2T ex;</div>
<div class="line"><a name="l00418"></a><span class="lineno"> 418</span>  ex.x = cs;</div>
<div class="line"><a name="l00419"></a><span class="lineno"> 419</span>  ex.y = sn;</div>
<div class="line"><a name="l00420"></a><span class="lineno"> 420</span> </div>
<div class="line"><a name="l00421"></a><span class="lineno"> 421</span>  Numeric2T tmp;</div>
<div class="line"><a name="l00422"></a><span class="lineno"> 422</span>  tmp.x = in2.x * ex.x - in2.y * ex.y;</div>
<div class="line"><a name="l00423"></a><span class="lineno"> 423</span>  tmp.y = in2.x * ex.y + in2.y * ex.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">if</span> (!is_row_major)</div>
<div class="line"><a name="l00426"></a><span class="lineno"> 426</span>  input[offset + ss] = in1 - tmp; <span class="comment">//index</span></div>
<div class="line"><a name="l00427"></a><span class="lineno"> 427</span>  <span class="keywordflow">else</span></div>
<div class="line"><a name="l00428"></a><span class="lineno"> 428</span>  input[offset + ss * <a class="code" href="namespaceviennacl_1_1traits.html#a09997870f4802fa5d4ac2c43cf4020d1">stride</a>] = in1 - tmp; <span class="comment">//index</span></div>
<div class="line"><a name="l00429"></a><span class="lineno"> 429</span>  input[offset] = in1 + tmp; <span class="comment">//index</span></div>
<div class="line"><a name="l00430"></a><span class="lineno"> 430</span>  }</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> }</div>
<div class="line"><a name="l00433"></a><span class="lineno"> 433</span> </div>
<div class="line"><a name="l00441"></a><span class="lineno"> 441</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="l00442"></a><span class="lineno"><a class="line" href="namespaceviennacl_1_1linalg_1_1cuda.html#a4e265c3922f011df324691017677c08b"> 442</a></span> <span class="keywordtype">void</span> <a class="code" href="namespaceviennacl_1_1linalg_1_1cuda.html#a4e265c3922f011df324691017677c08b">radix2</a>(<a class="code" href="classviennacl_1_1vector.html">viennacl::vector<NumericT, AlignmentV></a> & in,</div>
<div class="line"><a name="l00443"></a><span class="lineno"> 443</span>  <a class="code" href="namespaceviennacl.html#a98a0afcc513111ffa0bd138f891930df">vcl_size_t</a> size, <a class="code" href="namespaceviennacl.html#a98a0afcc513111ffa0bd138f891930df">vcl_size_t</a> stride, <a class="code" href="namespaceviennacl.html#a98a0afcc513111ffa0bd138f891930df">vcl_size_t</a> batch_num, <a class="code" href="tests_2src_2bisect_8cpp.html#a52b5d30a2d7b064678644a3bf49b7f6c">NumericT</a> <a class="code" href="namespaceviennacl_1_1linalg_1_1detail.html#a7bfa1c9cb0afb4ca0f975e690f4a8f07">sign</a> = <a class="code" href="tests_2src_2bisect_8cpp.html#a52b5d30a2d7b064678644a3bf49b7f6c">NumericT</a>(-1),</div>
<div class="line"><a name="l00444"></a><span class="lineno"> 444</span>  <a class="code" href="namespaceviennacl_1_1linalg_1_1host__based_1_1detail_1_1fft_1_1_f_f_t___d_a_t_a___o_r_d_e_r.html#aac2583f16e35875f2696e9220bd262f2">viennacl::linalg::host_based::detail::fft::FFT_DATA_ORDER::DATA_ORDER</a> data_order = <a class="code" href="namespaceviennacl_1_1linalg_1_1host__based_1_1detail_1_1fft_1_1_f_f_t___d_a_t_a___o_r_d_e_r.html#aac2583f16e35875f2696e9220bd262f2afffdaee3461226037812d7c99faf6e1b">viennacl::linalg::host_based::detail::fft::FFT_DATA_ORDER::ROW_MAJOR</a>)</div>
<div class="line"><a name="l00445"></a><span class="lineno"> 445</span> {</div>
<div class="line"><a name="l00446"></a><span class="lineno"> 446</span>  <span class="keyword">typedef</span> <span class="keyword">typename</span> <a class="code" href="structviennacl_1_1linalg_1_1cuda_1_1detail_1_1type__to__type2.html">viennacl::linalg::cuda::detail::type_to_type2<NumericT>::type</a> numeric2_type;</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> bit_size = <a class="code" href="namespaceviennacl_1_1linalg_1_1cuda_1_1detail_1_1fft.html#abd87824ce2e6428991a3f1a936d9a250">viennacl::linalg::cuda::detail::fft::num_bits</a>(size);</div>
<div class="line"><a name="l00449"></a><span class="lineno"> 449</span> </div>
<div class="line"><a name="l00450"></a><span class="lineno"> 450</span>  <span class="keywordflow">if</span> (size <= <a class="code" href="namespaceviennacl_1_1linalg_1_1cuda_1_1detail_1_1fft.html#a6b937b778b0e08dd5393ffed32c96020">viennacl::linalg::cuda::detail::fft::MAX_LOCAL_POINTS_NUM</a>)</div>
<div class="line"><a name="l00451"></a><span class="lineno"> 451</span>  {</div>
<div class="line"><a name="l00452"></a><span class="lineno"> 452</span>  fft_radix2_local<<<128,128>>>(<span class="keyword">reinterpret_cast<</span>numeric2_type *<span class="keyword">></span>(<a class="code" href="namespaceviennacl.html#ae7d5db0c2c91be75218db5b52c4d13da">viennacl::cuda_arg</a>(in)),</div>
<div class="line"><a name="l00453"></a><span class="lineno"> 453</span>  static_cast<unsigned int>(bit_size),</div>
<div class="line"><a name="l00454"></a><span class="lineno"> 454</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#aa2344ea20469f55fbc15a8e9526494d0">size</a>),</div>
<div class="line"><a name="l00455"></a><span class="lineno"> 455</span>  static_cast<unsigned int>(stride),</div>
<div class="line"><a name="l00456"></a><span class="lineno"> 456</span>  <span class="keyword">static_cast<</span><span class="keywordtype">unsigned</span> <span class="keywordtype">int</span><span class="keyword">></span>(batch_num),</div>
<div class="line"><a name="l00457"></a><span class="lineno"> 457</span>  static_cast<NumericT>(<a class="code" href="namespaceviennacl_1_1linalg_1_1detail.html#a7bfa1c9cb0afb4ca0f975e690f4a8f07">sign</a>),</div>
<div class="line"><a name="l00458"></a><span class="lineno"> 458</span>  <span class="keyword">static_cast<</span><span class="keywordtype">bool</span><span class="keyword">></span>(data_order));</div>
<div class="line"><a name="l00459"></a><span class="lineno"> 459</span>  <a class="code" href="linalg_2cuda_2common_8hpp.html#acdb31f22f4d1e12f1c2a27d4c4aa6865">VIENNACL_CUDA_LAST_ERROR_CHECK</a>(<span class="stringliteral">"fft_radix2_local"</span>);</div>
<div class="line"><a name="l00460"></a><span class="lineno"> 460</span>  }</div>
<div class="line"><a name="l00461"></a><span class="lineno"> 461</span>  <span class="keywordflow">else</span></div>
<div class="line"><a name="l00462"></a><span class="lineno"> 462</span>  {</div>
<div class="line"><a name="l00463"></a><span class="lineno"> 463</span>  fft_reorder<<<128,128>>>(<span class="keyword">reinterpret_cast<</span>numeric2_type *<span class="keyword">></span>(<a class="code" href="namespaceviennacl.html#ae7d5db0c2c91be75218db5b52c4d13da">viennacl::cuda_arg</a>(in)),</div>
<div class="line"><a name="l00464"></a><span class="lineno"> 464</span>  static_cast<unsigned int>(bit_size),</div>
<div class="line"><a name="l00465"></a><span class="lineno"> 465</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#aa2344ea20469f55fbc15a8e9526494d0">size</a>),</div>
<div class="line"><a name="l00466"></a><span class="lineno"> 466</span>  static_cast<unsigned int>(stride),</div>
<div class="line"><a name="l00467"></a><span class="lineno"> 467</span>  <span class="keyword">static_cast<</span><span class="keywordtype">unsigned</span> <span class="keywordtype">int</span><span class="keyword">></span>(batch_num),</div>
<div class="line"><a name="l00468"></a><span class="lineno"> 468</span>  static_cast<bool>(data_order));</div>
<div class="line"><a name="l00469"></a><span class="lineno"> 469</span>  <a class="code" href="linalg_2cuda_2common_8hpp.html#acdb31f22f4d1e12f1c2a27d4c4aa6865">VIENNACL_CUDA_LAST_ERROR_CHECK</a>(<span class="stringliteral">"fft_reorder"</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>  <span class="keywordflow">for</span> (<a class="code" href="namespaceviennacl.html#a98a0afcc513111ffa0bd138f891930df">vcl_size_t</a> <a class="code" href="least-squares_8cpp.html#a3bd576e398e7f02a27a19950bb8530ad">step</a> = 0; <a class="code" href="least-squares_8cpp.html#a3bd576e398e7f02a27a19950bb8530ad">step</a> < bit_size; <a class="code" href="least-squares_8cpp.html#a3bd576e398e7f02a27a19950bb8530ad">step</a>++)</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>  fft_radix2<<<128,128>>>(<span class="keyword">reinterpret_cast<</span>numeric2_type *<span class="keyword">></span>(<a class="code" href="namespaceviennacl.html#ae7d5db0c2c91be75218db5b52c4d13da">viennacl::cuda_arg</a>(in)),</div>
<div class="line"><a name="l00474"></a><span class="lineno"> 474</span>  static_cast<unsigned int>(<a class="code" href="least-squares_8cpp.html#a3bd576e398e7f02a27a19950bb8530ad">step</a>),</div>
<div class="line"><a name="l00475"></a><span class="lineno"> 475</span>  <span class="keyword">static_cast<</span><span class="keywordtype">unsigned</span> <span class="keywordtype">int</span><span class="keyword">></span>(bit_size),</div>
<div class="line"><a name="l00476"></a><span class="lineno"> 476</span>  static_cast<unsigned int>(size),</div>
<div class="line"><a name="l00477"></a><span class="lineno"> 477</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#a09997870f4802fa5d4ac2c43cf4020d1">stride</a>),</div>
<div class="line"><a name="l00478"></a><span class="lineno"> 478</span>  static_cast<unsigned int>(batch_num),</div>
<div class="line"><a name="l00479"></a><span class="lineno"> 479</span>  <a class="code" href="namespaceviennacl_1_1linalg_1_1detail.html#a7bfa1c9cb0afb4ca0f975e690f4a8f07">sign</a>,</div>
<div class="line"><a name="l00480"></a><span class="lineno"> 480</span>  <span class="keyword">static_cast<</span><span class="keywordtype">bool</span><span class="keyword">></span>(data_order));</div>
<div class="line"><a name="l00481"></a><span class="lineno"> 481</span>  <a class="code" href="linalg_2cuda_2common_8hpp.html#acdb31f22f4d1e12f1c2a27d4c4aa6865">VIENNACL_CUDA_LAST_ERROR_CHECK</a>(<span class="stringliteral">"fft_radix2"</span>);</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>  }</div>
<div class="line"><a name="l00484"></a><span class="lineno"> 484</span> }</div>
<div class="line"><a name="l00485"></a><span class="lineno"> 485</span> </div>
<div class="line"><a name="l00493"></a><span class="lineno"> 493</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="l00494"></a><span class="lineno"><a class="line" href="namespaceviennacl_1_1linalg_1_1cuda.html#acecac3e84dfd3027715f8f0aacf204da"> 494</a></span> <span class="keywordtype">void</span> <a class="code" href="namespaceviennacl_1_1linalg_1_1cuda.html#a4e265c3922f011df324691017677c08b">radix2</a>(<a class="code" href="classviennacl_1_1matrix.html">viennacl::matrix<NumericT, viennacl::row_major, AlignmentV></a>& in,</div>
<div class="line"><a name="l00495"></a><span class="lineno"> 495</span>  <a class="code" href="namespaceviennacl.html#a98a0afcc513111ffa0bd138f891930df">vcl_size_t</a> size, <a class="code" href="namespaceviennacl.html#a98a0afcc513111ffa0bd138f891930df">vcl_size_t</a> stride, <a class="code" href="namespaceviennacl.html#a98a0afcc513111ffa0bd138f891930df">vcl_size_t</a> batch_num, <a class="code" href="tests_2src_2bisect_8cpp.html#a52b5d30a2d7b064678644a3bf49b7f6c">NumericT</a> <a class="code" href="namespaceviennacl_1_1linalg_1_1detail.html#a7bfa1c9cb0afb4ca0f975e690f4a8f07">sign</a> = <a class="code" href="tests_2src_2bisect_8cpp.html#a52b5d30a2d7b064678644a3bf49b7f6c">NumericT</a>(-1),</div>
<div class="line"><a name="l00496"></a><span class="lineno"> 496</span>  <a class="code" href="namespaceviennacl_1_1linalg_1_1host__based_1_1detail_1_1fft_1_1_f_f_t___d_a_t_a___o_r_d_e_r.html#aac2583f16e35875f2696e9220bd262f2">viennacl::linalg::host_based::detail::fft::FFT_DATA_ORDER::DATA_ORDER</a> data_order = <a class="code" href="namespaceviennacl_1_1linalg_1_1host__based_1_1detail_1_1fft_1_1_f_f_t___d_a_t_a___o_r_d_e_r.html#aac2583f16e35875f2696e9220bd262f2afffdaee3461226037812d7c99faf6e1b">viennacl::linalg::host_based::detail::fft::FFT_DATA_ORDER::ROW_MAJOR</a>)</div>
<div class="line"><a name="l00497"></a><span class="lineno"> 497</span> {</div>
<div class="line"><a name="l00498"></a><span class="lineno"> 498</span>  <span class="keyword">typedef</span> <span class="keyword">typename</span> <a class="code" href="structviennacl_1_1linalg_1_1cuda_1_1detail_1_1type__to__type2.html">viennacl::linalg::cuda::detail::type_to_type2<NumericT>::type</a> numeric2_type;</div>
<div class="line"><a name="l00499"></a><span class="lineno"> 499</span> </div>
<div class="line"><a name="l00500"></a><span class="lineno"> 500</span>  <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> bit_size = <a class="code" href="namespaceviennacl_1_1linalg_1_1cuda_1_1detail_1_1fft.html#abd87824ce2e6428991a3f1a936d9a250">viennacl::linalg::cuda::detail::fft::num_bits</a>(size);</div>
<div class="line"><a name="l00501"></a><span class="lineno"> 501</span> </div>
<div class="line"><a name="l00502"></a><span class="lineno"> 502</span>  <span class="keywordflow">if</span> (size <= <a class="code" href="namespaceviennacl_1_1linalg_1_1cuda_1_1detail_1_1fft.html#a6b937b778b0e08dd5393ffed32c96020">viennacl::linalg::cuda::detail::fft::MAX_LOCAL_POINTS_NUM</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>  fft_radix2_local<<<128,128>>>(<span class="keyword">reinterpret_cast<</span>numeric2_type *<span class="keyword">></span>(<a class="code" href="namespaceviennacl.html#ae7d5db0c2c91be75218db5b52c4d13da">viennacl::cuda_arg</a>(in)),</div>
<div class="line"><a name="l00505"></a><span class="lineno"> 505</span>  static_cast<unsigned int>(bit_size),</div>
<div class="line"><a name="l00506"></a><span class="lineno"> 506</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#aa2344ea20469f55fbc15a8e9526494d0">size</a>),</div>
<div class="line"><a name="l00507"></a><span class="lineno"> 507</span>  static_cast<unsigned int>(stride),</div>
<div class="line"><a name="l00508"></a><span class="lineno"> 508</span>  <span class="keyword">static_cast<</span><span class="keywordtype">unsigned</span> <span class="keywordtype">int</span><span class="keyword">></span>(batch_num),</div>
<div class="line"><a name="l00509"></a><span class="lineno"> 509</span>  <a class="code" href="namespaceviennacl_1_1linalg_1_1detail.html#a7bfa1c9cb0afb4ca0f975e690f4a8f07">sign</a>,</div>
<div class="line"><a name="l00510"></a><span class="lineno"> 510</span>  static_cast<bool>(data_order));</div>
<div class="line"><a name="l00511"></a><span class="lineno"> 511</span>  <a class="code" href="linalg_2cuda_2common_8hpp.html#acdb31f22f4d1e12f1c2a27d4c4aa6865">VIENNACL_CUDA_LAST_ERROR_CHECK</a>(<span class="stringliteral">"fft_radix2_local"</span>);</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>  <span class="keywordflow">else</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>  fft_reorder<<<128,128>>>(<span class="keyword">reinterpret_cast<</span>numeric2_type *<span class="keyword">></span>(<a class="code" href="namespaceviennacl.html#ae7d5db0c2c91be75218db5b52c4d13da">viennacl::cuda_arg</a>(in)),</div>
<div class="line"><a name="l00516"></a><span class="lineno"> 516</span>  static_cast<unsigned int>(bit_size),</div>
<div class="line"><a name="l00517"></a><span class="lineno"> 517</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#aa2344ea20469f55fbc15a8e9526494d0">size</a>),</div>
<div class="line"><a name="l00518"></a><span class="lineno"> 518</span>  static_cast<unsigned int>(stride),</div>
<div class="line"><a name="l00519"></a><span class="lineno"> 519</span>  <span class="keyword">static_cast<</span><span class="keywordtype">unsigned</span> <span class="keywordtype">int</span><span class="keyword">></span>(batch_num),</div>
<div class="line"><a name="l00520"></a><span class="lineno"> 520</span>  static_cast<bool>(data_order));</div>
<div class="line"><a name="l00521"></a><span class="lineno"> 521</span>  <a class="code" href="linalg_2cuda_2common_8hpp.html#acdb31f22f4d1e12f1c2a27d4c4aa6865">VIENNACL_CUDA_LAST_ERROR_CHECK</a>(<span class="stringliteral">"fft_reorder"</span>);</div>
<div class="line"><a name="l00522"></a><span class="lineno"> 522</span>  <span class="keywordflow">for</span> (<a class="code" href="namespaceviennacl.html#a98a0afcc513111ffa0bd138f891930df">vcl_size_t</a> <a class="code" href="least-squares_8cpp.html#a3bd576e398e7f02a27a19950bb8530ad">step</a> = 0; <a class="code" href="least-squares_8cpp.html#a3bd576e398e7f02a27a19950bb8530ad">step</a> < bit_size; <a class="code" href="least-squares_8cpp.html#a3bd576e398e7f02a27a19950bb8530ad">step</a>++)</div>
<div class="line"><a name="l00523"></a><span class="lineno"> 523</span>  {</div>
<div class="line"><a name="l00524"></a><span class="lineno"> 524</span>  fft_radix2<<<128,128>>>(<span class="keyword">reinterpret_cast<</span>numeric2_type *<span class="keyword">></span>(<a class="code" href="namespaceviennacl.html#ae7d5db0c2c91be75218db5b52c4d13da">viennacl::cuda_arg</a>(in)),</div>
<div class="line"><a name="l00525"></a><span class="lineno"> 525</span>  static_cast<unsigned int>(<a class="code" href="least-squares_8cpp.html#a3bd576e398e7f02a27a19950bb8530ad">step</a>),</div>
<div class="line"><a name="l00526"></a><span class="lineno"> 526</span>  <span class="keyword">static_cast<</span><span class="keywordtype">unsigned</span> <span class="keywordtype">int</span><span class="keyword">></span>(bit_size),</div>
<div class="line"><a name="l00527"></a><span class="lineno"> 527</span>  static_cast<unsigned int>(size),</div>
<div class="line"><a name="l00528"></a><span class="lineno"> 528</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#a09997870f4802fa5d4ac2c43cf4020d1">stride</a>),</div>
<div class="line"><a name="l00529"></a><span class="lineno"> 529</span>  static_cast<unsigned int>(batch_num),</div>
<div class="line"><a name="l00530"></a><span class="lineno"> 530</span>  <a class="code" href="namespaceviennacl_1_1linalg_1_1detail.html#a7bfa1c9cb0afb4ca0f975e690f4a8f07">sign</a>,</div>
<div class="line"><a name="l00531"></a><span class="lineno"> 531</span>  <span class="keyword">static_cast<</span><span class="keywordtype">bool</span><span class="keyword">></span>(data_order));</div>
<div class="line"><a name="l00532"></a><span class="lineno"> 532</span>  <a class="code" href="linalg_2cuda_2common_8hpp.html#acdb31f22f4d1e12f1c2a27d4c4aa6865">VIENNACL_CUDA_LAST_ERROR_CHECK</a>(<span class="stringliteral">"fft_radix2"</span>);</div>
<div class="line"><a name="l00533"></a><span class="lineno"> 533</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> <span class="keyword">template</span><<span class="keyword">typename</span> Numeric2T, <span class="keyword">typename</span> NumericT></div>
<div class="line"><a name="l00538"></a><span class="lineno"><a class="line" href="namespaceviennacl_1_1linalg_1_1cuda.html#a6e1532b6287c40a5d9a7155c8143ffd6"> 538</a></span> __global__ <span class="keywordtype">void</span> <a class="code" href="namespaceviennacl_1_1linalg_1_1cuda.html#a6e1532b6287c40a5d9a7155c8143ffd6">bluestein_post</a>(Numeric2T * Z, Numeric2T * out, <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> size, <a class="code" href="tests_2src_2bisect_8cpp.html#a52b5d30a2d7b064678644a3bf49b7f6c">NumericT</a> <a class="code" href="namespaceviennacl_1_1linalg_1_1detail.html#a7bfa1c9cb0afb4ca0f975e690f4a8f07">sign</a>)</div>
<div class="line"><a name="l00539"></a><span class="lineno"> 539</span> {</div>
<div class="line"><a name="l00540"></a><span class="lineno"> 540</span>  <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> glb_id = blockIdx.x * blockDim.x + threadIdx.x;</div>
<div class="line"><a name="l00541"></a><span class="lineno"> 541</span>  <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> glb_sz =gridDim.x * blockDim.x;</div>
<div class="line"><a name="l00542"></a><span class="lineno"> 542</span> </div>
<div class="line"><a name="l00543"></a><span class="lineno"> 543</span>  <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> double_size = size << 1;</div>
<div class="line"><a name="l00544"></a><span class="lineno"> 544</span>  <a class="code" href="tests_2src_2bisect_8cpp.html#a52b5d30a2d7b064678644a3bf49b7f6c">NumericT</a> sn_a, cs_a;</div>
<div class="line"><a name="l00545"></a><span class="lineno"> 545</span>  <span class="keyword">const</span> <a class="code" href="tests_2src_2bisect_8cpp.html#a52b5d30a2d7b064678644a3bf49b7f6c">NumericT</a> NUM_PI(3.14159265358979323846);</div>
<div class="line"><a name="l00546"></a><span class="lineno"> 546</span> </div>
<div class="line"><a name="l00547"></a><span class="lineno"> 547</span>  <span class="keywordflow">for</span> (<span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> i = glb_id; i < <a class="code" href="namespaceviennacl_1_1traits.html#aa2344ea20469f55fbc15a8e9526494d0">size</a>; i += glb_sz)</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> rm = i * i % (double_size);</div>
<div class="line"><a name="l00550"></a><span class="lineno"> 550</span>  <a class="code" href="tests_2src_2bisect_8cpp.html#a52b5d30a2d7b064678644a3bf49b7f6c">NumericT</a> angle = (<a class="code" href="tests_2src_2bisect_8cpp.html#a52b5d30a2d7b064678644a3bf49b7f6c">NumericT</a>)rm / size * (-NUM_PI);</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>  sn_a = sin(angle);</div>
<div class="line"><a name="l00553"></a><span class="lineno"> 553</span>  cs_a= cos(angle);</div>
<div class="line"><a name="l00554"></a><span class="lineno"> 554</span> </div>
<div class="line"><a name="l00555"></a><span class="lineno"> 555</span>  Numeric2T b_i;</div>
<div class="line"><a name="l00556"></a><span class="lineno"> 556</span>  b_i.x = cs_a;</div>
<div class="line"><a name="l00557"></a><span class="lineno"> 557</span>  b_i.y = sn_a;</div>
<div class="line"><a name="l00558"></a><span class="lineno"> 558</span>  out[i].x = Z[i].x * b_i.x - Z[i].y * b_i.y;</div>
<div class="line"><a name="l00559"></a><span class="lineno"> 559</span>  out[i].y = Z[i].x * b_i.y + Z[i].y * b_i.x;</div>
<div class="line"><a name="l00560"></a><span class="lineno"> 560</span>  }</div>
<div class="line"><a name="l00561"></a><span class="lineno"> 561</span> }</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> <span class="keyword">template</span><<span class="keyword">typename</span> Numeric2T, <span class="keyword">typename</span> NumericT></div>
<div class="line"><a name="l00564"></a><span class="lineno"><a class="line" href="namespaceviennacl_1_1linalg_1_1cuda.html#a7ef8c7e5ff783ca07aaa5b664eae2b2f"> 564</a></span> __global__ <span class="keywordtype">void</span> <a class="code" href="namespaceviennacl_1_1linalg_1_1cuda.html#a7ef8c7e5ff783ca07aaa5b664eae2b2f">bluestein_pre</a>(Numeric2T * input, Numeric2T * A, Numeric2T * B,</div>
<div class="line"><a name="l00565"></a><span class="lineno"> 565</span>  <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> size, <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> ext_size, <a class="code" href="tests_2src_2bisect_8cpp.html#a52b5d30a2d7b064678644a3bf49b7f6c">NumericT</a> <a class="code" href="namespaceviennacl_1_1linalg_1_1detail.html#a7bfa1c9cb0afb4ca0f975e690f4a8f07">sign</a>)</div>
<div class="line"><a name="l00566"></a><span class="lineno"> 566</span> {</div>
<div class="line"><a name="l00567"></a><span class="lineno"> 567</span>  <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> glb_id = blockIdx.x * blockDim.x + threadIdx.x;</div>
<div class="line"><a name="l00568"></a><span class="lineno"> 568</span>  <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> glb_sz = gridDim.x * blockDim.x;</div>
<div class="line"><a name="l00569"></a><span class="lineno"> 569</span> </div>
<div class="line"><a name="l00570"></a><span class="lineno"> 570</span>  <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> double_size = size << 1;</div>
<div class="line"><a name="l00571"></a><span class="lineno"> 571</span> </div>
<div class="line"><a name="l00572"></a><span class="lineno"> 572</span>  <a class="code" href="tests_2src_2bisect_8cpp.html#a52b5d30a2d7b064678644a3bf49b7f6c">NumericT</a> sn_a, cs_a;</div>
<div class="line"><a name="l00573"></a><span class="lineno"> 573</span>  <span class="keyword">const</span> <a class="code" href="tests_2src_2bisect_8cpp.html#a52b5d30a2d7b064678644a3bf49b7f6c">NumericT</a> NUM_PI(3.14159265358979323846);</div>
<div class="line"><a name="l00574"></a><span class="lineno"> 574</span> </div>
<div class="line"><a name="l00575"></a><span class="lineno"> 575</span>  <span class="keywordflow">for</span> (<span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> i = glb_id; i < <a class="code" href="namespaceviennacl_1_1traits.html#aa2344ea20469f55fbc15a8e9526494d0">size</a>; i += glb_sz)</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>  <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> rm = i * i % (double_size);</div>
<div class="line"><a name="l00578"></a><span class="lineno"> 578</span>  <a class="code" href="tests_2src_2bisect_8cpp.html#a52b5d30a2d7b064678644a3bf49b7f6c">NumericT</a> angle = (<a class="code" href="tests_2src_2bisect_8cpp.html#a52b5d30a2d7b064678644a3bf49b7f6c">NumericT</a>)rm / size * NUM_PI;</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>  sn_a = sin(-angle);</div>
<div class="line"><a name="l00581"></a><span class="lineno"> 581</span>  cs_a= cos(-angle);</div>
<div class="line"><a name="l00582"></a><span class="lineno"> 582</span> </div>
<div class="line"><a name="l00583"></a><span class="lineno"> 583</span>  Numeric2T a_i;</div>
<div class="line"><a name="l00584"></a><span class="lineno"> 584</span>  a_i.x =cs_a;</div>
<div class="line"><a name="l00585"></a><span class="lineno"> 585</span>  a_i.y =sn_a;</div>
<div class="line"><a name="l00586"></a><span class="lineno"> 586</span> </div>
<div class="line"><a name="l00587"></a><span class="lineno"> 587</span>  Numeric2T b_i;</div>
<div class="line"><a name="l00588"></a><span class="lineno"> 588</span>  b_i.x =cs_a;</div>
<div class="line"><a name="l00589"></a><span class="lineno"> 589</span>  b_i.y =-sn_a;</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>  A[i].x = input[i].x * a_i.x - input[i].y * a_i.y;</div>
<div class="line"><a name="l00592"></a><span class="lineno"> 592</span>  A[i].y = input[i].x * a_i.y + input[i].y * a_i.x;</div>
<div class="line"><a name="l00593"></a><span class="lineno"> 593</span>  B[i] = b_i;</div>
<div class="line"><a name="l00594"></a><span class="lineno"> 594</span> </div>
<div class="line"><a name="l00595"></a><span class="lineno"> 595</span>  <span class="comment">// very bad instruction, to be fixed</span></div>
<div class="line"><a name="l00596"></a><span class="lineno"> 596</span>  <span class="keywordflow">if</span> (i)</div>
<div class="line"><a name="l00597"></a><span class="lineno"> 597</span>  B[ext_size - i] = b_i;</div>
<div class="line"><a name="l00598"></a><span class="lineno"> 598</span>  }</div>
<div class="line"><a name="l00599"></a><span class="lineno"> 599</span> }</div>
<div class="line"><a name="l00600"></a><span class="lineno"> 600</span> </div>
<div class="line"><a name="l00601"></a><span class="lineno"> 601</span> <span class="keyword">template</span><<span class="keyword">typename</span> NumericT></div>
<div class="line"><a name="l00602"></a><span class="lineno"><a class="line" href="namespaceviennacl_1_1linalg_1_1cuda.html#ac939f8ae31fdf532db77b38aa3a264f9"> 602</a></span> __global__ <span class="keywordtype">void</span> <a class="code" href="namespaceviennacl_1_1linalg_1_1cuda.html#ac939f8ae31fdf532db77b38aa3a264f9">zero2</a>(<a class="code" href="tests_2src_2bisect_8cpp.html#a52b5d30a2d7b064678644a3bf49b7f6c">NumericT</a> * input1, <a class="code" href="tests_2src_2bisect_8cpp.html#a52b5d30a2d7b064678644a3bf49b7f6c">NumericT</a> * input2, <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> size)</div>
<div class="line"><a name="l00603"></a><span class="lineno"> 603</span> {</div>
<div class="line"><a name="l00604"></a><span class="lineno"> 604</span>  <span class="keywordflow">for</span> (<span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> i = blockIdx.x * blockDim.x + threadIdx.x; i < size; i += gridDim.x * blockDim.x)</div>
<div class="line"><a name="l00605"></a><span class="lineno"> 605</span>  {</div>
<div class="line"><a name="l00606"></a><span class="lineno"> 606</span>  input1[i].x = 0;</div>
<div class="line"><a name="l00607"></a><span class="lineno"> 607</span>  input1[i].y = 0;</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>  input2[i].x = 0;</div>
<div class="line"><a name="l00610"></a><span class="lineno"> 610</span>  input2[i].y = 0;</div>
<div class="line"><a name="l00611"></a><span class="lineno"> 611</span>  }</div>
<div class="line"><a name="l00612"></a><span class="lineno"> 612</span> }</div>
<div class="line"><a name="l00613"></a><span class="lineno"> 613</span> </div>
<div class="line"><a name="l00621"></a><span class="lineno"> 621</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="l00622"></a><span class="lineno"><a class="line" href="namespaceviennacl_1_1linalg_1_1cuda.html#a466e914c7abb876ee2711dfb1006e5ad"> 622</a></span> <span class="keywordtype">void</span> <a class="code" href="namespaceviennacl_1_1linalg_1_1cuda.html#a466e914c7abb876ee2711dfb1006e5ad">bluestein</a>(<a class="code" href="classviennacl_1_1vector.html">viennacl::vector<NumericT, AlignmentV></a> & in,</div>
<div class="line"><a name="l00623"></a><span class="lineno"> 623</span>  <a class="code" href="classviennacl_1_1vector.html">viennacl::vector<NumericT, AlignmentV></a> & out, <a class="code" href="namespaceviennacl.html#a98a0afcc513111ffa0bd138f891930df">vcl_size_t</a> <span class="comment">/*batch_num*/</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>  <span class="keyword">typedef</span> <span class="keyword">typename</span> <a class="code" href="structviennacl_1_1linalg_1_1cuda_1_1detail_1_1type__to__type2.html">viennacl::linalg::cuda::detail::type_to_type2<NumericT>::type</a> numeric2_type;</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>  <a class="code" href="namespaceviennacl.html#a98a0afcc513111ffa0bd138f891930df">vcl_size_t</a> size = in.<a class="code" href="classviennacl_1_1vector__base.html#a15c47ae4326098aeaa4ed6b91fc6df9b">size</a>() >> 1;</div>
<div class="line"><a name="l00628"></a><span class="lineno"> 628</span>  <a class="code" href="namespaceviennacl.html#a98a0afcc513111ffa0bd138f891930df">vcl_size_t</a> ext_size = <a class="code" href="namespaceviennacl_1_1linalg_1_1cuda_1_1detail_1_1fft.html#ad8af53105450cfc6a0adb586742a028e">viennacl::linalg::cuda::detail::fft::next_power_2</a>(2 * size - 1);</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>  <a class="code" href="classviennacl_1_1vector.html">viennacl::vector<NumericT, AlignmentV></a> A(ext_size << 1);</div>
<div class="line"><a name="l00631"></a><span class="lineno"> 631</span>  <a class="code" href="classviennacl_1_1vector.html">viennacl::vector<NumericT, AlignmentV></a> B(ext_size << 1);</div>
<div class="line"><a name="l00632"></a><span class="lineno"> 632</span>  <a class="code" href="classviennacl_1_1vector.html">viennacl::vector<NumericT, AlignmentV></a> Z(ext_size << 1);</div>
<div class="line"><a name="l00633"></a><span class="lineno"> 633</span> </div>
<div class="line"><a name="l00634"></a><span class="lineno"> 634</span>  zero2<<<128,128>>>(<span class="keyword">reinterpret_cast<</span>numeric2_type *<span class="keyword">></span>(<a class="code" href="namespaceviennacl.html#ae7d5db0c2c91be75218db5b52c4d13da">viennacl::cuda_arg</a>(A)),</div>
<div class="line"><a name="l00635"></a><span class="lineno"> 635</span>  reinterpret_cast<numeric2_type *>(<a class="code" href="namespaceviennacl.html#ae7d5db0c2c91be75218db5b52c4d13da">viennacl::cuda_arg</a>(B)),</div>
<div class="line"><a name="l00636"></a><span class="lineno"> 636</span>  static_cast<unsigned int>(ext_size));</div>
<div class="line"><a name="l00637"></a><span class="lineno"> 637</span>  <a class="code" href="linalg_2cuda_2common_8hpp.html#acdb31f22f4d1e12f1c2a27d4c4aa6865">VIENNACL_CUDA_LAST_ERROR_CHECK</a>(<span class="stringliteral">"zero2"</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>  bluestein_pre<<<128,128>>>(<span class="keyword">reinterpret_cast<</span>numeric2_type *<span class="keyword">></span>(<a class="code" href="namespaceviennacl.html#ae7d5db0c2c91be75218db5b52c4d13da">viennacl::cuda_arg</a>(in)),</div>
<div class="line"><a name="l00640"></a><span class="lineno"> 640</span>  reinterpret_cast<numeric2_type *>(<a class="code" href="namespaceviennacl.html#ae7d5db0c2c91be75218db5b52c4d13da">viennacl::cuda_arg</a>(A)),</div>
<div class="line"><a name="l00641"></a><span class="lineno"> 641</span>  reinterpret_cast<numeric2_type *>(<a class="code" href="namespaceviennacl.html#ae7d5db0c2c91be75218db5b52c4d13da">viennacl::cuda_arg</a>(B)),</div>
<div class="line"><a name="l00642"></a><span class="lineno"> 642</span>  static_cast<unsigned int>(size),</div>
<div class="line"><a name="l00643"></a><span class="lineno"> 643</span>  <span class="keyword">static_cast<</span><span class="keywordtype">unsigned</span> <span class="keywordtype">int</span><span class="keyword">></span>(ext_size),</div>
<div class="line"><a name="l00644"></a><span class="lineno"> 644</span>  <a class="code" href="tests_2src_2bisect_8cpp.html#a52b5d30a2d7b064678644a3bf49b7f6c">NumericT</a>(1));</div>
<div class="line"><a name="l00645"></a><span class="lineno"> 645</span>  <a class="code" href="linalg_2cuda_2common_8hpp.html#acdb31f22f4d1e12f1c2a27d4c4aa6865">VIENNACL_CUDA_LAST_ERROR_CHECK</a>(<span class="stringliteral">"bluestein_pre"</span>);</div>
<div class="line"><a name="l00646"></a><span class="lineno"> 646</span> </div>
<div class="line"><a name="l00647"></a><span class="lineno"> 647</span>  <a class="code" href="namespaceviennacl_1_1linalg.html#a7b596f98d234d40fe9460d0077d1fcc3">viennacl::linalg::convolve_i</a>(A, B, Z);</div>
<div class="line"><a name="l00648"></a><span class="lineno"> 648</span> </div>
<div class="line"><a name="l00649"></a><span class="lineno"> 649</span>  bluestein_post<<<128,128>>>(<span class="keyword">reinterpret_cast<</span>numeric2_type *<span class="keyword">></span>(<a class="code" href="namespaceviennacl.html#ae7d5db0c2c91be75218db5b52c4d13da">viennacl::cuda_arg</a>(Z)),</div>
<div class="line"><a name="l00650"></a><span class="lineno"> 650</span>  reinterpret_cast<numeric2_type *>(<a class="code" href="namespaceviennacl.html#ae7d5db0c2c91be75218db5b52c4d13da">viennacl::cuda_arg</a>(out)),</div>
<div class="line"><a name="l00651"></a><span class="lineno"> 651</span>  static_cast<unsigned int>(size),</div>
<div class="line"><a name="l00652"></a><span class="lineno"> 652</span>  <a class="code" href="tests_2src_2bisect_8cpp.html#a52b5d30a2d7b064678644a3bf49b7f6c">NumericT</a>(1));</div>
<div class="line"><a name="l00653"></a><span class="lineno"> 653</span>  <a class="code" href="linalg_2cuda_2common_8hpp.html#acdb31f22f4d1e12f1c2a27d4c4aa6865">VIENNACL_CUDA_LAST_ERROR_CHECK</a>(<span class="stringliteral">"bluestein_post"</span>);</div>
<div class="line"><a name="l00654"></a><span class="lineno"> 654</span> }</div>
<div class="line"><a name="l00655"></a><span class="lineno"> 655</span> </div>
<div class="line"><a name="l00656"></a><span class="lineno"> 656</span> <span class="keyword">template</span><<span class="keyword">typename</span> NumericT></div>
<div class="line"><a name="l00657"></a><span class="lineno"><a class="line" href="namespaceviennacl_1_1linalg_1_1cuda.html#aed30c13333f60176cc7527b1a674ac4f"> 657</a></span> __global__ <span class="keywordtype">void</span> <a class="code" href="namespaceviennacl_1_1linalg_1_1cuda.html#aed30c13333f60176cc7527b1a674ac4f">fft_mult_vec</a>(<span class="keyword">const</span> <a class="code" href="tests_2src_2bisect_8cpp.html#a52b5d30a2d7b064678644a3bf49b7f6c">NumericT</a> * input1,</div>
<div class="line"><a name="l00658"></a><span class="lineno"> 658</span>  <span class="keyword">const</span> <a class="code" href="tests_2src_2bisect_8cpp.html#a52b5d30a2d7b064678644a3bf49b7f6c">NumericT</a> * input2,</div>
<div class="line"><a name="l00659"></a><span class="lineno"> 659</span>  <a class="code" href="tests_2src_2bisect_8cpp.html#a52b5d30a2d7b064678644a3bf49b7f6c">NumericT</a> * output,</div>
<div class="line"><a name="l00660"></a><span class="lineno"> 660</span>  <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> size)</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="keywordflow">for</span> (<span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> i = blockIdx.x * blockDim.x + threadIdx.x; i < size; i += gridDim.x * blockDim.x)</div>
<div class="line"><a name="l00663"></a><span class="lineno"> 663</span>  {</div>
<div class="line"><a name="l00664"></a><span class="lineno"> 664</span>  <a class="code" href="tests_2src_2bisect_8cpp.html#a52b5d30a2d7b064678644a3bf49b7f6c">NumericT</a> in1 = input1[i];</div>
<div class="line"><a name="l00665"></a><span class="lineno"> 665</span>  <a class="code" href="tests_2src_2bisect_8cpp.html#a52b5d30a2d7b064678644a3bf49b7f6c">NumericT</a> in2 = input2[i];</div>
<div class="line"><a name="l00666"></a><span class="lineno"> 666</span>  output[i] = in1 * in2;</div>
<div class="line"><a name="l00667"></a><span class="lineno"> 667</span>  }</div>
<div class="line"><a name="l00668"></a><span class="lineno"> 668</span> }</div>
<div class="line"><a name="l00669"></a><span class="lineno"> 669</span> </div>
<div class="line"><a name="l00673"></a><span class="lineno"> 673</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="l00674"></a><span class="lineno"><a class="line" href="namespaceviennacl_1_1linalg_1_1cuda.html#a506556434450509c7e70e9de7ce3f2c6"> 674</a></span> <span class="keywordtype">void</span> <a class="code" href="namespaceviennacl_1_1linalg_1_1cuda.html#a506556434450509c7e70e9de7ce3f2c6">multiply_complex</a>(<a class="code" href="classviennacl_1_1vector.html">viennacl::vector<NumericT, AlignmentV></a> <span class="keyword">const</span> & input1,</div>
<div class="line"><a name="l00675"></a><span class="lineno"> 675</span>  <a class="code" href="classviennacl_1_1vector.html">viennacl::vector<NumericT, AlignmentV></a> <span class="keyword">const</span> & input2,</div>
<div class="line"><a name="l00676"></a><span class="lineno"> 676</span>  <a class="code" href="classviennacl_1_1vector.html">viennacl::vector<NumericT, AlignmentV></a> & output)</div>
<div class="line"><a name="l00677"></a><span class="lineno"> 677</span> {</div>
<div class="line"><a name="l00678"></a><span class="lineno"> 678</span>  <span class="keyword">typedef</span> <span class="keyword">typename</span> <a class="code" href="structviennacl_1_1linalg_1_1cuda_1_1detail_1_1type__to__type2.html">viennacl::linalg::cuda::detail::type_to_type2<NumericT>::type</a> numeric2_type;</div>
<div class="line"><a name="l00679"></a><span class="lineno"> 679</span> </div>
<div class="line"><a name="l00680"></a><span class="lineno"> 680</span>  <a class="code" href="namespaceviennacl.html#a98a0afcc513111ffa0bd138f891930df">vcl_size_t</a> size = input1.<a class="code" href="classviennacl_1_1vector__base.html#a15c47ae4326098aeaa4ed6b91fc6df9b">size</a>() / 2;</div>
<div class="line"><a name="l00681"></a><span class="lineno"> 681</span> </div>
<div class="line"><a name="l00682"></a><span class="lineno"> 682</span>  fft_mult_vec<<<128,128>>>(<span class="keyword">reinterpret_cast<</span><span class="keyword">const </span>numeric2_type *<span class="keyword">></span>(<a class="code" href="namespaceviennacl.html#ae7d5db0c2c91be75218db5b52c4d13da">viennacl::cuda_arg</a>(input1)),</div>
<div class="line"><a name="l00683"></a><span class="lineno"> 683</span>  reinterpret_cast<const numeric2_type *>(<a class="code" href="namespaceviennacl.html#ae7d5db0c2c91be75218db5b52c4d13da">viennacl::cuda_arg</a>(input2)),</div>
<div class="line"><a name="l00684"></a><span class="lineno"> 684</span>  reinterpret_cast< numeric2_type *>(<a class="code" href="namespaceviennacl.html#ae7d5db0c2c91be75218db5b52c4d13da">viennacl::cuda_arg</a>(output)),</div>
<div class="line"><a name="l00685"></a><span class="lineno"> 685</span>  static_cast<unsigned int>(size));</div>
<div class="line"><a name="l00686"></a><span class="lineno"> 686</span>  <a class="code" href="linalg_2cuda_2common_8hpp.html#acdb31f22f4d1e12f1c2a27d4c4aa6865">VIENNACL_CUDA_LAST_ERROR_CHECK</a>(<span class="stringliteral">"fft_mult_vec"</span>);</div>
<div class="line"><a name="l00687"></a><span class="lineno"> 687</span> }</div>
<div class="line"><a name="l00688"></a><span class="lineno"> 688</span> </div>
<div class="line"><a name="l00689"></a><span class="lineno"> 689</span> <span class="keyword">template</span><<span class="keyword">typename</span> Numeric2T, <span class="keyword">typename</span> NumericT></div>
<div class="line"><a name="l00690"></a><span class="lineno"><a class="line" href="namespaceviennacl_1_1linalg_1_1cuda.html#a5163d49d9052ef3b0d7f9c51795fb295"> 690</a></span> __global__ <span class="keywordtype">void</span> <a class="code" href="namespaceviennacl_1_1linalg_1_1cuda.html#a5163d49d9052ef3b0d7f9c51795fb295">fft_div_vec_scalar</a>(Numeric2T * input1, <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> size, <a class="code" href="tests_2src_2bisect_8cpp.html#a52b5d30a2d7b064678644a3bf49b7f6c">NumericT</a> factor)</div>
<div class="line"><a name="l00691"></a><span class="lineno"> 691</span> {</div>
<div class="line"><a name="l00692"></a><span class="lineno"> 692</span>  <span class="keywordflow">for</span> (<span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> i = blockIdx.x * blockDim.x + threadIdx.x; i < size; i += gridDim.x*blockDim.x)</div>
<div class="line"><a name="l00693"></a><span class="lineno"> 693</span>  input1[i] = input1[i]/factor;</div>
<div class="line"><a name="l00694"></a><span class="lineno"> 694</span> }</div>
<div class="line"><a name="l00695"></a><span class="lineno"> 695</span> </div>
<div class="line"><a name="l00699"></a><span class="lineno"> 699</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="l00700"></a><span class="lineno"><a class="line" href="namespaceviennacl_1_1linalg_1_1cuda.html#a9ba098e125e95f83b4b9260c51972e28"> 700</a></span> <span class="keywordtype">void</span> <a class="code" href="namespaceviennacl_1_1linalg_1_1cuda.html#a9ba098e125e95f83b4b9260c51972e28">normalize</a>(<a class="code" href="classviennacl_1_1vector.html">viennacl::vector<NumericT, AlignmentV></a> & input)</div>
<div class="line"><a name="l00701"></a><span class="lineno"> 701</span> {</div>
<div class="line"><a name="l00702"></a><span class="lineno"> 702</span>  <span class="keyword">typedef</span> <span class="keyword">typename</span> <a class="code" href="structviennacl_1_1linalg_1_1cuda_1_1detail_1_1type__to__type2.html">viennacl::linalg::cuda::detail::type_to_type2<NumericT>::type</a> numeric2_type;</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>  <a class="code" href="namespaceviennacl.html#a98a0afcc513111ffa0bd138f891930df">vcl_size_t</a> size = input.<a class="code" href="classviennacl_1_1vector__base.html#a15c47ae4326098aeaa4ed6b91fc6df9b">size</a>() >> 1;</div>
<div class="line"><a name="l00705"></a><span class="lineno"> 705</span>  <a class="code" href="tests_2src_2bisect_8cpp.html#a52b5d30a2d7b064678644a3bf49b7f6c">NumericT</a> norm_factor = <span class="keyword">static_cast<</span><a class="code" href="tests_2src_2bisect_8cpp.html#a52b5d30a2d7b064678644a3bf49b7f6c">NumericT</a><span class="keyword">></span>(<a class="code" href="namespaceviennacl_1_1traits.html#aa2344ea20469f55fbc15a8e9526494d0">size</a>);</div>
<div class="line"><a name="l00706"></a><span class="lineno"> 706</span>  fft_div_vec_scalar<<<128,128>>>(<span class="keyword">reinterpret_cast<</span>numeric2_type *<span class="keyword">></span>(<a class="code" href="namespaceviennacl.html#ae7d5db0c2c91be75218db5b52c4d13da">viennacl::cuda_arg</a>(input)),</div>
<div class="line"><a name="l00707"></a><span class="lineno"> 707</span>  static_cast<unsigned int>(size),</div>
<div class="line"><a name="l00708"></a><span class="lineno"> 708</span>  norm_factor);</div>
<div class="line"><a name="l00709"></a><span class="lineno"> 709</span>  <a class="code" href="linalg_2cuda_2common_8hpp.html#acdb31f22f4d1e12f1c2a27d4c4aa6865">VIENNACL_CUDA_LAST_ERROR_CHECK</a>(<span class="stringliteral">"fft_div_vec_scalar"</span>);</div>
<div class="line"><a name="l00710"></a><span class="lineno"> 710</span> }</div>
<div class="line"><a name="l00711"></a><span class="lineno"> 711</span> </div>
<div class="line"><a name="l00712"></a><span class="lineno"> 712</span> <span class="keyword">template</span><<span class="keyword">typename</span> NumericT></div>
<div class="line"><a name="l00713"></a><span class="lineno"><a class="line" href="namespaceviennacl_1_1linalg_1_1cuda.html#a8b569744691c4e3302480e8b42bb3091"> 713</a></span> __global__ <span class="keywordtype">void</span> <a class="code" href="namespaceviennacl_1_1linalg_1_1cuda.html#a8b569744691c4e3302480e8b42bb3091">transpose</a>(<span class="keyword">const</span> <a class="code" href="tests_2src_2bisect_8cpp.html#a52b5d30a2d7b064678644a3bf49b7f6c">NumericT</a> * input,</div>
<div class="line"><a name="l00714"></a><span class="lineno"> 714</span>  <a class="code" href="tests_2src_2bisect_8cpp.html#a52b5d30a2d7b064678644a3bf49b7f6c">NumericT</a> * output,</div>
<div class="line"><a name="l00715"></a><span class="lineno"> 715</span>  <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> row_num,</div>
<div class="line"><a name="l00716"></a><span class="lineno"> 716</span>  <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> col_num)</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="keywordtype">unsigned</span> <span class="keywordtype">int</span> size = row_num * col_num;</div>
<div class="line"><a name="l00719"></a><span class="lineno"> 719</span>  <span class="keywordflow">for</span> (<span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> i =blockIdx.x * blockDim.x + threadIdx.x; i < size; i+= gridDim.x * blockDim.x)</div>
<div class="line"><a name="l00720"></a><span class="lineno"> 720</span>  {</div>
<div class="line"><a name="l00721"></a><span class="lineno"> 721</span>  <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> <a class="code" href="namespaceviennacl.html#a0a574e6cd04ca0e42298b4ab845700e4">row</a> = i / col_num;</div>
<div class="line"><a name="l00722"></a><span class="lineno"> 722</span>  <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> col = i - row*col_num;</div>
<div class="line"><a name="l00723"></a><span class="lineno"> 723</span>  <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> new_pos = col * row_num + <a class="code" href="namespaceviennacl.html#a0a574e6cd04ca0e42298b4ab845700e4">row</a>;</div>
<div class="line"><a name="l00724"></a><span class="lineno"> 724</span>  output[new_pos] = input[i];</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="l00731"></a><span class="lineno"> 731</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="l00732"></a><span class="lineno"><a class="line" href="namespaceviennacl_1_1linalg_1_1cuda.html#a54247e89216ce1d9956cacbad2955d20"> 732</a></span> <span class="keywordtype">void</span> <a class="code" href="namespaceviennacl_1_1linalg_1_1cuda.html#a8b569744691c4e3302480e8b42bb3091">transpose</a>(<a class="code" href="classviennacl_1_1matrix.html">viennacl::matrix<NumericT, viennacl::row_major, AlignmentV></a> <span class="keyword">const</span> & input,</div>
<div class="line"><a name="l00733"></a><span class="lineno"> 733</span>  <a class="code" href="classviennacl_1_1matrix.html">viennacl::matrix<NumericT, viennacl::row_major, AlignmentV></a> & output)</div>
<div class="line"><a name="l00734"></a><span class="lineno"> 734</span> {</div>
<div class="line"><a name="l00735"></a><span class="lineno"> 735</span>  <span class="keyword">typedef</span> <span class="keyword">typename</span> <a class="code" href="structviennacl_1_1linalg_1_1cuda_1_1detail_1_1type__to__type2.html">viennacl::linalg::cuda::detail::type_to_type2<NumericT>::type</a> numeric2_type;</div>
<div class="line"><a name="l00736"></a><span class="lineno"> 736</span> </div>
<div class="line"><a name="l00737"></a><span class="lineno"> 737</span>  transpose<<<128,128>>>(<span class="keyword">reinterpret_cast<</span><span class="keyword">const </span>numeric2_type *<span class="keyword">></span>(<a class="code" href="namespaceviennacl.html#ae7d5db0c2c91be75218db5b52c4d13da">viennacl::cuda_arg</a>(input)),</div>
<div class="line"><a name="l00738"></a><span class="lineno"> 738</span>  reinterpret_cast< numeric2_type *>(<a class="code" href="namespaceviennacl.html#ae7d5db0c2c91be75218db5b52c4d13da">viennacl::cuda_arg</a>(output)),</div>
<div class="line"><a name="l00739"></a><span class="lineno"> 739</span>  static_cast<unsigned int>(input.<a class="code" href="classviennacl_1_1matrix__base.html#a82018b4e169973bdfb9d3be68ceb5be0">internal_size1</a>()>>1),</div>
<div class="line"><a name="l00740"></a><span class="lineno"> 740</span>  static_cast<unsigned int>(input.<a class="code" href="classviennacl_1_1matrix__base.html#a00e30fdc61081a73995b54175a91d220">internal_size2</a>()>>1));</div>
<div class="line"><a name="l00741"></a><span class="lineno"> 741</span>  <a class="code" href="linalg_2cuda_2common_8hpp.html#acdb31f22f4d1e12f1c2a27d4c4aa6865">VIENNACL_CUDA_LAST_ERROR_CHECK</a>(<span class="stringliteral">"transpose"</span>);</div>
<div class="line"><a name="l00742"></a><span class="lineno"> 742</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> <span class="keyword">template</span><<span class="keyword">typename</span> NumericT></div>
<div class="line"><a name="l00746"></a><span class="lineno"><a class="line" href="namespaceviennacl_1_1linalg_1_1cuda.html#a0ea13b0623b669778e42c76d25182418"> 746</a></span> __global__ <span class="keywordtype">void</span> <a class="code" href="namespaceviennacl_1_1linalg_1_1cuda.html#a0ea13b0623b669778e42c76d25182418">transpose_inplace</a>(</div>
<div class="line"><a name="l00747"></a><span class="lineno"> 747</span>  <a class="code" href="tests_2src_2bisect_8cpp.html#a52b5d30a2d7b064678644a3bf49b7f6c">NumericT</a> * input,</div>
<div class="line"><a name="l00748"></a><span class="lineno"> 748</span>  <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> row_num,</div>
<div class="line"><a name="l00749"></a><span class="lineno"> 749</span>  <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> col_num)</div>
<div class="line"><a name="l00750"></a><span class="lineno"> 750</span> {</div>
<div class="line"><a name="l00751"></a><span class="lineno"> 751</span>  <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> size = row_num * col_num;</div>
<div class="line"><a name="l00752"></a><span class="lineno"> 752</span>  <span class="keywordflow">for</span> (<span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> i = blockIdx.x * blockDim.x + threadIdx.x; i < size; i+= gridDim.x * blockDim.x)</div>
<div class="line"><a name="l00753"></a><span class="lineno"> 753</span>  {</div>
<div class="line"><a name="l00754"></a><span class="lineno"> 754</span>  <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> <a class="code" href="namespaceviennacl.html#a0a574e6cd04ca0e42298b4ab845700e4">row</a> = i / col_num;</div>
<div class="line"><a name="l00755"></a><span class="lineno"> 755</span>  <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> col = i - row*col_num;</div>
<div class="line"><a name="l00756"></a><span class="lineno"> 756</span>  <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> new_pos = col * row_num + <a class="code" href="namespaceviennacl.html#a0a574e6cd04ca0e42298b4ab845700e4">row</a>;</div>
<div class="line"><a name="l00757"></a><span class="lineno"> 757</span>  <span class="keywordflow">if</span> (i < new_pos)</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>  <a class="code" href="tests_2src_2bisect_8cpp.html#a52b5d30a2d7b064678644a3bf49b7f6c">NumericT</a> val = input[i];</div>
<div class="line"><a name="l00760"></a><span class="lineno"> 760</span>  input[i] = input[new_pos];</div>
<div class="line"><a name="l00761"></a><span class="lineno"> 761</span>  input[new_pos] = val;</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>  }</div>
<div class="line"><a name="l00764"></a><span class="lineno"> 764</span> }</div>
<div class="line"><a name="l00765"></a><span class="lineno"> 765</span> </div>
<div class="line"><a name="l00769"></a><span class="lineno"> 769</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="l00770"></a><span class="lineno"><a class="line" href="namespaceviennacl_1_1linalg_1_1cuda.html#a2ad74d61aa443f66d5a872027289f890"> 770</a></span> <span class="keywordtype">void</span> <a class="code" href="namespaceviennacl_1_1linalg_1_1cuda.html#a8b569744691c4e3302480e8b42bb3091">transpose</a>(<a class="code" href="classviennacl_1_1matrix.html">viennacl::matrix<NumericT, viennacl::row_major, AlignmentV></a> & input)</div>
<div class="line"><a name="l00771"></a><span class="lineno"> 771</span> {</div>
<div class="line"><a name="l00772"></a><span class="lineno"> 772</span>  <span class="keyword">typedef</span> <span class="keyword">typename</span> <a class="code" href="structviennacl_1_1linalg_1_1cuda_1_1detail_1_1type__to__type2.html">viennacl::linalg::cuda::detail::type_to_type2<NumericT>::type</a> numeric2_type;</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>  transpose_inplace<<<128,128>>>(<span class="keyword">reinterpret_cast<</span>numeric2_type *<span class="keyword">></span>(<a class="code" href="namespaceviennacl.html#ae7d5db0c2c91be75218db5b52c4d13da">viennacl::cuda_arg</a>(input)),</div>
<div class="line"><a name="l00775"></a><span class="lineno"> 775</span>  static_cast<unsigned int>(input.<a class="code" href="classviennacl_1_1matrix__base.html#a82018b4e169973bdfb9d3be68ceb5be0">internal_size1</a>()>>1),</div>
<div class="line"><a name="l00776"></a><span class="lineno"> 776</span>  static_cast<unsigned int>(input.<a class="code" href="classviennacl_1_1matrix__base.html#a00e30fdc61081a73995b54175a91d220">internal_size2</a>() >> 1));</div>
<div class="line"><a name="l00777"></a><span class="lineno"> 777</span>  <a class="code" href="linalg_2cuda_2common_8hpp.html#acdb31f22f4d1e12f1c2a27d4c4aa6865">VIENNACL_CUDA_LAST_ERROR_CHECK</a>(<span class="stringliteral">"transpose_inplace"</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="l00781"></a><span class="lineno"> 781</span> <span class="keyword">template</span><<span class="keyword">typename</span> RealT,<span class="keyword">typename</span> ComplexT></div>
<div class="line"><a name="l00782"></a><span class="lineno"><a class="line" href="namespaceviennacl_1_1linalg_1_1cuda.html#a88ae883dc9ba03947be366e889176953"> 782</a></span> __global__ <span class="keywordtype">void</span> <a class="code" href="namespaceviennacl_1_1linalg_1_1cuda.html#a88ae883dc9ba03947be366e889176953">real_to_complex</a>(<span class="keyword">const</span> RealT * in, ComplexT * out, <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> size)</div>
<div class="line"><a name="l00783"></a><span class="lineno"> 783</span> {</div>
<div class="line"><a name="l00784"></a><span class="lineno"> 784</span>  <span class="keywordflow">for</span> (<span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> i = blockIdx.x * blockDim.x + threadIdx.x; i < size; i += gridDim.x * blockDim.x)</div>
<div class="line"><a name="l00785"></a><span class="lineno"> 785</span>  {</div>
<div class="line"><a name="l00786"></a><span class="lineno"> 786</span>  ComplexT val;</div>
<div class="line"><a name="l00787"></a><span class="lineno"> 787</span>  val.x = in[i];</div>
<div class="line"><a name="l00788"></a><span class="lineno"> 788</span>  val.y = 0;</div>
<div class="line"><a name="l00789"></a><span class="lineno"> 789</span>  out[i] = val;</div>
<div class="line"><a name="l00790"></a><span class="lineno"> 790</span>  }</div>
<div class="line"><a name="l00791"></a><span class="lineno"> 791</span> }</div>
<div class="line"><a name="l00792"></a><span class="lineno"> 792</span> </div>
<div class="line"><a name="l00796"></a><span class="lineno"> 796</span> <span class="keyword">template</span><<span class="keyword">typename</span> NumericT></div>
<div class="line"><a name="l00797"></a><span class="lineno"><a class="line" href="namespaceviennacl_1_1linalg_1_1cuda.html#add9c66d64b960d29ec4eef2f5de79389"> 797</a></span> <span class="keywordtype">void</span> <a class="code" href="namespaceviennacl_1_1linalg_1_1cuda.html#a88ae883dc9ba03947be366e889176953">real_to_complex</a>(<a class="code" href="classviennacl_1_1vector__base.html">viennacl::vector_base<NumericT></a> <span class="keyword">const</span> & in,</div>
<div class="line"><a name="l00798"></a><span class="lineno"> 798</span>  <a class="code" href="classviennacl_1_1vector__base.html">viennacl::vector_base<NumericT></a> & out, <a class="code" href="namespaceviennacl.html#a98a0afcc513111ffa0bd138f891930df">vcl_size_t</a> size)</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>  <span class="keyword">typedef</span> <span class="keyword">typename</span> <a class="code" href="structviennacl_1_1linalg_1_1cuda_1_1detail_1_1type__to__type2.html">viennacl::linalg::cuda::detail::type_to_type2<NumericT>::type</a> numeric2_type;</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>  real_to_complex<<<128,128>>>(<a class="code" href="namespaceviennacl.html#ae7d5db0c2c91be75218db5b52c4d13da">viennacl::cuda_arg</a>(in),</div>
<div class="line"><a name="l00803"></a><span class="lineno"> 803</span>  <span class="keyword">reinterpret_cast<</span>numeric2_type *<span class="keyword">></span>(<a class="code" href="namespaceviennacl.html#ae7d5db0c2c91be75218db5b52c4d13da">viennacl::cuda_arg</a>(out)),</div>
<div class="line"><a name="l00804"></a><span class="lineno"> 804</span>  static_cast<unsigned int>(size));</div>
<div class="line"><a name="l00805"></a><span class="lineno"> 805</span>  <a class="code" href="linalg_2cuda_2common_8hpp.html#acdb31f22f4d1e12f1c2a27d4c4aa6865">VIENNACL_CUDA_LAST_ERROR_CHECK</a>(<span class="stringliteral">"real_to_complex"</span>);</div>
<div class="line"><a name="l00806"></a><span class="lineno"> 806</span> }</div>
<div class="line"><a name="l00807"></a><span class="lineno"> 807</span> </div>
<div class="line"><a name="l00808"></a><span class="lineno"> 808</span> <span class="keyword">template</span><<span class="keyword">typename</span> ComplexT,<span class="keyword">typename</span> RealT></div>
<div class="line"><a name="l00809"></a><span class="lineno"><a class="line" href="namespaceviennacl_1_1linalg_1_1cuda.html#a5fba21e48290e4123b1287d1e6bd43bd"> 809</a></span> __global__ <span class="keywordtype">void</span> <a class="code" href="namespaceviennacl_1_1linalg_1_1cuda.html#a5fba21e48290e4123b1287d1e6bd43bd">complex_to_real</a>(<span class="keyword">const</span> ComplexT * in, RealT * out, <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> size)</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>  <span class="keywordflow">for</span> (<span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> i = blockIdx.x * blockDim.x + threadIdx.x; i < size; i += gridDim.x * blockDim.x)</div>
<div class="line"><a name="l00812"></a><span class="lineno"> 812</span>  out[i] = in[i].x;</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="l00818"></a><span class="lineno"> 818</span> <span class="keyword">template</span><<span class="keyword">typename</span> NumericT></div>
<div class="line"><a name="l00819"></a><span class="lineno"><a class="line" href="namespaceviennacl_1_1linalg_1_1cuda.html#ac6c275c75ed9f49d6822e1a7a221de5b"> 819</a></span> <span class="keywordtype">void</span> <a class="code" href="namespaceviennacl_1_1linalg_1_1cuda.html#a5fba21e48290e4123b1287d1e6bd43bd">complex_to_real</a>(<a class="code" href="classviennacl_1_1vector__base.html">viennacl::vector_base<NumericT></a> <span class="keyword">const</span> & in,</div>
<div class="line"><a name="l00820"></a><span class="lineno"> 820</span>  <a class="code" href="classviennacl_1_1vector__base.html">viennacl::vector_base<NumericT></a>& out, <a class="code" href="namespaceviennacl.html#a98a0afcc513111ffa0bd138f891930df">vcl_size_t</a> size)</div>
<div class="line"><a name="l00821"></a><span class="lineno"> 821</span> {</div>
<div class="line"><a name="l00822"></a><span class="lineno"> 822</span>  <span class="keyword">typedef</span> <span class="keyword">typename</span> <a class="code" href="structviennacl_1_1linalg_1_1cuda_1_1detail_1_1type__to__type2.html">viennacl::linalg::cuda::detail::type_to_type2<NumericT>::type</a> numeric2_type;</div>
<div class="line"><a name="l00823"></a><span class="lineno"> 823</span> </div>
<div class="line"><a name="l00824"></a><span class="lineno"> 824</span>  complex_to_real<<<128,128>>>(<span class="keyword">reinterpret_cast<</span><span class="keyword">const </span>numeric2_type *<span class="keyword">></span>(<a class="code" href="namespaceviennacl.html#ae7d5db0c2c91be75218db5b52c4d13da">viennacl::cuda_arg</a>(in)),</div>
<div class="line"><a name="l00825"></a><span class="lineno"> 825</span>  <a class="code" href="namespaceviennacl.html#ae7d5db0c2c91be75218db5b52c4d13da">viennacl::cuda_arg</a>(out),</div>
<div class="line"><a name="l00826"></a><span class="lineno"> 826</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#aa2344ea20469f55fbc15a8e9526494d0">size</a>));</div>
<div class="line"><a name="l00827"></a><span class="lineno"> 827</span>  <a class="code" href="linalg_2cuda_2common_8hpp.html#acdb31f22f4d1e12f1c2a27d4c4aa6865">VIENNACL_CUDA_LAST_ERROR_CHECK</a>(<span class="stringliteral">"complex_to_real"</span>);</div>
<div class="line"><a name="l00828"></a><span class="lineno"> 828</span> </div>
<div class="line"><a name="l00829"></a><span class="lineno"> 829</span> }</div>
<div class="line"><a name="l00830"></a><span class="lineno"> 830</span> </div>
<div class="line"><a name="l00831"></a><span class="lineno"> 831</span> <span class="keyword">template</span><<span class="keyword">typename</span> NumericT></div>
<div class="line"><a name="l00832"></a><span class="lineno"><a class="line" href="namespaceviennacl_1_1linalg_1_1cuda.html#a038f4f2510cb6267938cc1049df9b609"> 832</a></span> __global__ <span class="keywordtype">void</span> <a class="code" href="namespaceviennacl_1_1linalg_1_1cuda.html#a038f4f2510cb6267938cc1049df9b609">reverse_inplace</a>(<a class="code" href="tests_2src_2bisect_8cpp.html#a52b5d30a2d7b064678644a3bf49b7f6c">NumericT</a> * vec, <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> size)</div>
<div class="line"><a name="l00833"></a><span class="lineno"> 833</span> {</div>
<div class="line"><a name="l00834"></a><span class="lineno"> 834</span>  <span class="keywordflow">for</span> (<span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> i = blockIdx.x * blockDim.x + threadIdx.x; i < (size >> 1); i+=gridDim.x * blockDim.x)</div>
<div class="line"><a name="l00835"></a><span class="lineno"> 835</span>  {</div>
<div class="line"><a name="l00836"></a><span class="lineno"> 836</span>  <a class="code" href="tests_2src_2bisect_8cpp.html#a52b5d30a2d7b064678644a3bf49b7f6c">NumericT</a> val1 = vec[i];</div>
<div class="line"><a name="l00837"></a><span class="lineno"> 837</span>  <a class="code" href="tests_2src_2bisect_8cpp.html#a52b5d30a2d7b064678644a3bf49b7f6c">NumericT</a> val2 = vec[size - i - 1];</div>
<div class="line"><a name="l00838"></a><span class="lineno"> 838</span>  vec[i] = val2;</div>
<div class="line"><a name="l00839"></a><span class="lineno"> 839</span>  vec[size - i - 1] = val1;</div>
<div class="line"><a name="l00840"></a><span class="lineno"> 840</span>  }</div>
<div class="line"><a name="l00841"></a><span class="lineno"> 841</span> }</div>
<div class="line"><a name="l00842"></a><span class="lineno"> 842</span> </div>
<div class="line"><a name="l00846"></a><span class="lineno"> 846</span> <span class="keyword">template</span><<span class="keyword">typename</span> NumericT></div>
<div class="line"><a name="l00847"></a><span class="lineno"><a class="line" href="namespaceviennacl_1_1linalg_1_1cuda.html#a5abf912b0fe2132fcc95233c46546951"> 847</a></span> <span class="keywordtype">void</span> <a class="code" href="namespaceviennacl_1_1linalg_1_1cuda.html#a5abf912b0fe2132fcc95233c46546951">reverse</a>(<a class="code" href="classviennacl_1_1vector__base.html">viennacl::vector_base<NumericT></a>& in)</div>
<div class="line"><a name="l00848"></a><span class="lineno"> 848</span> {</div>
<div class="line"><a name="l00849"></a><span class="lineno"> 849</span>  <a class="code" href="namespaceviennacl.html#a98a0afcc513111ffa0bd138f891930df">vcl_size_t</a> size = in.<a class="code" href="classviennacl_1_1vector__base.html#a15c47ae4326098aeaa4ed6b91fc6df9b">size</a>();</div>
<div class="line"><a name="l00850"></a><span class="lineno"> 850</span>  reverse_inplace<<<128,128>>>(<a class="code" href="namespaceviennacl.html#ae7d5db0c2c91be75218db5b52c4d13da">viennacl::cuda_arg</a>(in), <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#aa2344ea20469f55fbc15a8e9526494d0">size</a>));</div>
<div class="line"><a name="l00851"></a><span class="lineno"> 851</span>  <a class="code" href="linalg_2cuda_2common_8hpp.html#acdb31f22f4d1e12f1c2a27d4c4aa6865">VIENNACL_CUDA_LAST_ERROR_CHECK</a>(<span class="stringliteral">"reverse_inplace"</span>);</div>
<div class="line"><a name="l00852"></a><span class="lineno"> 852</span> }</div>
<div class="line"><a name="l00853"></a><span class="lineno"> 853</span> </div>
<div class="line"><a name="l00854"></a><span class="lineno"> 854</span> } <span class="comment">//namespace cuda</span></div>
<div class="line"><a name="l00855"></a><span class="lineno"> 855</span> } <span class="comment">//namespace linalg</span></div>
<div class="line"><a name="l00856"></a><span class="lineno"> 856</span> } <span class="comment">//namespace viennacl</span></div>
<div class="line"><a name="l00857"></a><span class="lineno"> 857</span> </div>
<div class="line"><a name="l00858"></a><span class="lineno"> 858</span> <span class="preprocessor">#endif </span><span class="comment">/* FFT_OPERATIONS_HPP_ */</span><span class="preprocessor"></span></div>
<div class="ttc" id="namespaceviennacl_1_1linalg_1_1host__based_1_1detail_1_1fft_1_1_f_f_t___d_a_t_a___o_r_d_e_r_html_aac2583f16e35875f2696e9220bd262f2"><div class="ttname"><a href="namespaceviennacl_1_1linalg_1_1host__based_1_1detail_1_1fft_1_1_f_f_t___d_a_t_a___o_r_d_e_r.html#aac2583f16e35875f2696e9220bd262f2">viennacl::linalg::host_based::detail::fft::FFT_DATA_ORDER::DATA_ORDER</a></div><div class="ttdeci">DATA_ORDER</div><div class="ttdef"><b>Definition:</b> <a href="host__based_2fft__operations_8hpp_source.html#l00049">fft_operations.hpp:49</a></div></div>
<div class="ttc" id="structviennacl_1_1is__row__major_html"><div class="ttname"><a href="structviennacl_1_1is__row__major.html">viennacl::is_row_major</a></div><div class="ttdoc">Helper class for checking whether a matrix has a row-major layout. </div><div class="ttdef"><b>Definition:</b> <a href="forwards_8h_source.html#l00484">forwards.h:484</a></div></div>
<div class="ttc" id="matrix_8hpp_html"><div class="ttname"><a href="matrix_8hpp.html">matrix.hpp</a></div><div class="ttdoc">Implementation of the dense matrix class. </div></div>
<div class="ttc" id="namespaceviennacl_1_1linalg_1_1cuda_html_a6e1532b6287c40a5d9a7155c8143ffd6"><div class="ttname"><a href="namespaceviennacl_1_1linalg_1_1cuda.html#a6e1532b6287c40a5d9a7155c8143ffd6">viennacl::linalg::cuda::bluestein_post</a></div><div class="ttdeci">__global__ void bluestein_post(Numeric2T *Z, Numeric2T *out, unsigned int size, NumericT sign)</div><div class="ttdef"><b>Definition:</b> <a href="cuda_2fft__operations_8hpp_source.html#l00538">fft_operations.hpp:538</a></div></div>
<div class="ttc" id="tools_8hpp_html"><div class="ttname"><a href="tools_8hpp.html">tools.hpp</a></div><div class="ttdoc">Various little tools used here and there in ViennaCL. </div></div>
<div class="ttc" id="namespaceviennacl_1_1linalg_1_1cuda_html_a88ae883dc9ba03947be366e889176953"><div class="ttname"><a href="namespaceviennacl_1_1linalg_1_1cuda.html#a88ae883dc9ba03947be366e889176953">viennacl::linalg::cuda::real_to_complex</a></div><div class="ttdeci">__global__ void real_to_complex(const RealT *in, ComplexT *out, unsigned int size)</div><div class="ttdef"><b>Definition:</b> <a href="cuda_2fft__operations_8hpp_source.html#l00782">fft_operations.hpp:782</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_1linalg_1_1cuda_html_a4284d9526bb5275f446048381072c1c1"><div class="ttname"><a href="namespaceviennacl_1_1linalg_1_1cuda.html#a4284d9526bb5275f446048381072c1c1">viennacl::linalg::cuda::fft_direct</a></div><div class="ttdeci">__global__ void fft_direct(const Numeric2T *input, Numeric2T *output, unsigned int size, unsigned int stride, unsigned int batch_num, NumericT sign, bool is_row_major)</div><div class="ttdef"><b>Definition:</b> <a href="cuda_2fft__operations_8hpp_source.html#l00140">fft_operations.hpp:140</a></div></div>
<div class="ttc" id="forwards_8h_html"><div class="ttname"><a href="forwards_8h.html">forwards.h</a></div><div class="ttdoc">This file provides the forward declarations for the main types used within ViennaCL. </div></div>
<div class="ttc" id="least-squares_8cpp_html_a3bd576e398e7f02a27a19950bb8530ad"><div class="ttname"><a href="least-squares_8cpp.html#a3bd576e398e7f02a27a19950bb8530ad">step</a></div><div class="ttdeci">endcode *Final step</div><div class="ttdef"><b>Definition:</b> <a href="least-squares_8cpp_source.html#l00145">least-squares.cpp:145</a></div></div>
<div class="ttc" id="classviennacl_1_1matrix_html"><div class="ttname"><a href="classviennacl_1_1matrix.html">viennacl::matrix</a></div><div class="ttdoc">A dense matrix class. </div><div class="ttdef"><b>Definition:</b> <a href="forwards_8h_source.html#l00375">forwards.h:375</a></div></div>
<div class="ttc" id="namespaceviennacl_1_1linalg_1_1cuda_html_aed30c13333f60176cc7527b1a674ac4f"><div class="ttname"><a href="namespaceviennacl_1_1linalg_1_1cuda.html#aed30c13333f60176cc7527b1a674ac4f">viennacl::linalg::cuda::fft_mult_vec</a></div><div class="ttdeci">__global__ void fft_mult_vec(const NumericT *input1, const NumericT *input2, NumericT *output, unsigned int size)</div><div class="ttdef"><b>Definition:</b> <a href="cuda_2fft__operations_8hpp_source.html#l00657">fft_operations.hpp:657</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_html_aa33540cbd35a517b2f196d96b549efe4"><div class="ttname"><a href="namespaceviennacl_1_1linalg_1_1cuda.html#aa33540cbd35a517b2f196d96b549efe4">viennacl::linalg::cuda::operator+</a></div><div class="ttdeci">__host__ __device__ float2 operator+(float2 a, float2 b)</div><div class="ttdef"><b>Definition:</b> <a href="cuda_2fft__operations_8hpp_source.html#l00080">fft_operations.hpp:80</a></div></div>
<div class="ttc" id="namespaceviennacl_1_1linalg_1_1cuda_1_1detail_1_1fft_html_a6b937b778b0e08dd5393ffed32c96020"><div class="ttname"><a href="namespaceviennacl_1_1linalg_1_1cuda_1_1detail_1_1fft.html#a6b937b778b0e08dd5393ffed32c96020">viennacl::linalg::cuda::detail::fft::MAX_LOCAL_POINTS_NUM</a></div><div class="ttdeci">const vcl_size_t MAX_LOCAL_POINTS_NUM</div><div class="ttdef"><b>Definition:</b> <a href="cuda_2fft__operations_8hpp_source.html#l00045">fft_operations.hpp:45</a></div></div>
<div class="ttc" id="namespaceviennacl_1_1linalg_1_1cuda_1_1detail_1_1fft_html_abd87824ce2e6428991a3f1a936d9a250"><div class="ttname"><a href="namespaceviennacl_1_1linalg_1_1cuda_1_1detail_1_1fft.html#abd87824ce2e6428991a3f1a936d9a250">viennacl::linalg::cuda::detail::fft::num_bits</a></div><div class="ttdeci">vcl_size_t num_bits(vcl_size_t size)</div><div class="ttdef"><b>Definition:</b> <a href="cuda_2fft__operations_8hpp_source.html#l00047">fft_operations.hpp:47</a></div></div>
<div class="ttc" id="namespaceviennacl_1_1linalg_1_1cuda_html_a038f4f2510cb6267938cc1049df9b609"><div class="ttname"><a href="namespaceviennacl_1_1linalg_1_1cuda.html#a038f4f2510cb6267938cc1049df9b609">viennacl::linalg::cuda::reverse_inplace</a></div><div class="ttdeci">__global__ void reverse_inplace(NumericT *vec, unsigned int size)</div><div class="ttdef"><b>Definition:</b> <a href="cuda_2fft__operations_8hpp_source.html#l00832">fft_operations.hpp:832</a></div></div>
<div class="ttc" id="namespaceviennacl_1_1linalg_1_1cuda_html_a8b569744691c4e3302480e8b42bb3091"><div class="ttname"><a href="namespaceviennacl_1_1linalg_1_1cuda.html#a8b569744691c4e3302480e8b42bb3091">viennacl::linalg::cuda::transpose</a></div><div class="ttdeci">__global__ void transpose(const NumericT *input, NumericT *output, unsigned int row_num, unsigned int col_num)</div><div class="ttdef"><b>Definition:</b> <a href="cuda_2fft__operations_8hpp_source.html#l00713">fft_operations.hpp:713</a></div></div>
<div class="ttc" id="namespaceviennacl_1_1linalg_1_1host__based_1_1detail_1_1fft_1_1_f_f_t___d_a_t_a___o_r_d_e_r_html_aac2583f16e35875f2696e9220bd262f2afffdaee3461226037812d7c99faf6e1b"><div class="ttname"><a href="namespaceviennacl_1_1linalg_1_1host__based_1_1detail_1_1fft_1_1_f_f_t___d_a_t_a___o_r_d_e_r.html#aac2583f16e35875f2696e9220bd262f2afffdaee3461226037812d7c99faf6e1b">viennacl::linalg::host_based::detail::fft::FFT_DATA_ORDER::ROW_MAJOR</a></div><div class="ttdef"><b>Definition:</b> <a href="host__based_2fft__operations_8hpp_source.html#l00051">fft_operations.hpp:51</a></div></div>
<div class="ttc" id="namespaceviennacl_1_1traits_html_aa2344ea20469f55fbc15a8e9526494d0"><div class="ttname"><a href="namespaceviennacl_1_1traits.html#aa2344ea20469f55fbc15a8e9526494d0">viennacl::traits::size</a></div><div class="ttdeci">vcl_size_t size(VectorType const &vec)</div><div class="ttdoc">Generic routine for obtaining the size of a vector (ViennaCL, uBLAS, etc.) </div><div class="ttdef"><b>Definition:</b> <a href="size_8hpp_source.html#l00239">size.hpp:239</a></div></div>
<div class="ttc" id="namespaceviennacl_1_1linalg_1_1cuda_html_a4e265c3922f011df324691017677c08b"><div class="ttname"><a href="namespaceviennacl_1_1linalg_1_1cuda.html#a4e265c3922f011df324691017677c08b">viennacl::linalg::cuda::radix2</a></div><div class="ttdeci">void radix2(viennacl::vector< NumericT, AlignmentV > &in, vcl_size_t size, vcl_size_t stride, vcl_size_t batch_num, NumericT sign=NumericT(-1), viennacl::linalg::host_based::detail::fft::FFT_DATA_ORDER::DATA_ORDER data_order=viennacl::linalg::host_based::detail::fft::FFT_DATA_ORDER::ROW_MAJOR)</div><div class="ttdoc">Radix-2 1D algorithm for computing Fourier transformation. </div><div class="ttdef"><b>Definition:</b> <a href="cuda_2fft__operations_8hpp_source.html#l00442">fft_operations.hpp:442</a></div></div>
<div class="ttc" id="namespaceviennacl_1_1linalg_1_1cuda_html_a466e914c7abb876ee2711dfb1006e5ad"><div class="ttname"><a href="namespaceviennacl_1_1linalg_1_1cuda.html#a466e914c7abb876ee2711dfb1006e5ad">viennacl::linalg::cuda::bluestein</a></div><div class="ttdeci">void bluestein(viennacl::vector< NumericT, AlignmentV > &in, viennacl::vector< NumericT, AlignmentV > &out, vcl_size_t)</div><div class="ttdoc">Bluestein's algorithm for computing Fourier transformation. </div><div class="ttdef"><b>Definition:</b> <a href="cuda_2fft__operations_8hpp_source.html#l00622">fft_operations.hpp:622</a></div></div>
<div class="ttc" id="namespaceviennacl_1_1linalg_1_1cuda_html_a5163d49d9052ef3b0d7f9c51795fb295"><div class="ttname"><a href="namespaceviennacl_1_1linalg_1_1cuda.html#a5163d49d9052ef3b0d7f9c51795fb295">viennacl::linalg::cuda::fft_div_vec_scalar</a></div><div class="ttdeci">__global__ void fft_div_vec_scalar(Numeric2T *input1, unsigned int size, NumericT factor)</div><div class="ttdef"><b>Definition:</b> <a href="cuda_2fft__operations_8hpp_source.html#l00690">fft_operations.hpp:690</a></div></div>
<div class="ttc" id="namespaceviennacl_1_1linalg_1_1cuda_html_a549bb69fa59c1d82ec34402e917db258"><div class="ttname"><a href="namespaceviennacl_1_1linalg_1_1cuda.html#a549bb69fa59c1d82ec34402e917db258">viennacl::linalg::cuda::fft_reorder</a></div><div class="ttdeci">__global__ void fft_reorder(NumericT *input, unsigned int bit_size, unsigned int size, unsigned int stride, unsigned int batch_num, bool is_row_major)</div><div class="ttdef"><b>Definition:</b> <a href="cuda_2fft__operations_8hpp_source.html#l00241">fft_operations.hpp:241</a></div></div>
<div class="ttc" id="namespaceviennacl_1_1linalg_1_1cuda_html_a1e6214e945b8d60ea371f578f5ee58db"><div class="ttname"><a href="namespaceviennacl_1_1linalg_1_1cuda.html#a1e6214e945b8d60ea371f578f5ee58db">viennacl::linalg::cuda::operator*</a></div><div class="ttdeci">__device__ float2 operator*(float2 in1, float2 in2)</div><div class="ttdef"><b>Definition:</b> <a href="cuda_2fft__operations_8hpp_source.html#l00098">fft_operations.hpp:98</a></div></div>
<div class="ttc" id="classviennacl_1_1vector__base_html"><div class="ttname"><a href="classviennacl_1_1vector__base.html">viennacl::vector_base< NumericT ></a></div></div>
<div class="ttc" id="namespaceviennacl_html_a98a0afcc513111ffa0bd138f891930df"><div class="ttname"><a href="namespaceviennacl.html#a98a0afcc513111ffa0bd138f891930df">viennacl::vcl_size_t</a></div><div class="ttdeci">std::size_t vcl_size_t</div><div class="ttdef"><b>Definition:</b> <a href="forwards_8h_source.html#l00075">forwards.h:75</a></div></div>
<div class="ttc" id="classviennacl_1_1vector_html"><div class="ttname"><a href="classviennacl_1_1vector.html">viennacl::vector< NumericT, AlignmentV ></a></div></div>
<div class="ttc" id="namespaceviennacl_1_1linalg_1_1cuda_html_a6b46337d1aab49f0bc5d20e2699e4231"><div class="ttname"><a href="namespaceviennacl_1_1linalg_1_1cuda.html#a6b46337d1aab49f0bc5d20e2699e4231">viennacl::linalg::cuda::operator/</a></div><div class="ttdeci">__device__ float2 operator/(float2 a, SCALARTYPE b)</div><div class="ttdef"><b>Definition:</b> <a href="cuda_2fft__operations_8hpp_source.html#l00092">fft_operations.hpp:92</a></div></div>
<div class="ttc" id="namespaceviennacl_1_1linalg_1_1cuda_html_a9ba098e125e95f83b4b9260c51972e28"><div class="ttname"><a href="namespaceviennacl_1_1linalg_1_1cuda.html#a9ba098e125e95f83b4b9260c51972e28">viennacl::linalg::cuda::normalize</a></div><div class="ttdeci">void normalize(viennacl::vector< NumericT, AlignmentV > &input)</div><div class="ttdoc">Normalize vector on with his own size. </div><div class="ttdef"><b>Definition:</b> <a href="cuda_2fft__operations_8hpp_source.html#l00700">fft_operations.hpp:700</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="namespaceviennacl_1_1linalg_html_a7b596f98d234d40fe9460d0077d1fcc3"><div class="ttname"><a href="namespaceviennacl_1_1linalg.html#a7b596f98d234d40fe9460d0077d1fcc3">viennacl::linalg::convolve_i</a></div><div class="ttdeci">void convolve_i(viennacl::vector< SCALARTYPE, ALIGNMENT > &input1, viennacl::vector< SCALARTYPE, ALIGNMENT > &input2, viennacl::vector< SCALARTYPE, ALIGNMENT > &output)</div></div>
<div class="ttc" id="namespaceviennacl_1_1linalg_1_1cuda_html_ac939f8ae31fdf532db77b38aa3a264f9"><div class="ttname"><a href="namespaceviennacl_1_1linalg_1_1cuda.html#ac939f8ae31fdf532db77b38aa3a264f9">viennacl::linalg::cuda::zero2</a></div><div class="ttdeci">__global__ void zero2(NumericT *input1, NumericT *input2, unsigned int size)</div><div class="ttdef"><b>Definition:</b> <a href="cuda_2fft__operations_8hpp_source.html#l00602">fft_operations.hpp:602</a></div></div>
<div class="ttc" id="namespaceviennacl_1_1linalg_1_1cuda_html_a6632b858aba1849edd0d834dab27486f"><div class="ttname"><a href="namespaceviennacl_1_1linalg_1_1cuda.html#a6632b858aba1849edd0d834dab27486f">viennacl::linalg::cuda::fft_radix2</a></div><div class="ttdeci">__global__ void fft_radix2(Numeric2T *input, unsigned int s, unsigned int bit_size, unsigned int size, unsigned int stride, unsigned int batch_num, NumericT sign, bool is_row_major)</div><div class="ttdef"><b>Definition:</b> <a href="cuda_2fft__operations_8hpp_source.html#l00371">fft_operations.hpp:371</a></div></div>
<div class="ttc" id="linalg_2cuda_2common_8hpp_html"><div class="ttname"><a href="linalg_2cuda_2common_8hpp.html">common.hpp</a></div><div class="ttdoc">Common routines for CUDA execution. </div></div>
<div class="ttc" id="vector_8hpp_html"><div class="ttname"><a href="vector_8hpp.html">vector.hpp</a></div><div class="ttdoc">The vector type with operator-overloads and proxy classes is defined here. Linear algebra operations ...</div></div>
<div class="ttc" id="namespaceviennacl_1_1linalg_1_1cuda_html_aa55045c0b6db4bd69bc523b5243320fc"><div class="ttname"><a href="namespaceviennacl_1_1linalg_1_1cuda.html#aa55045c0b6db4bd69bc523b5243320fc">viennacl::linalg::cuda::get_reorder_num</a></div><div class="ttdeci">__device__ unsigned int get_reorder_num(unsigned int v, unsigned int bit_size)</div><div class="ttdef"><b>Definition:</b> <a href="cuda_2fft__operations_8hpp_source.html#l00128">fft_operations.hpp:128</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="namespaceviennacl_1_1linalg_1_1cuda_html_a7ef8c7e5ff783ca07aaa5b664eae2b2f"><div class="ttname"><a href="namespaceviennacl_1_1linalg_1_1cuda.html#a7ef8c7e5ff783ca07aaa5b664eae2b2f">viennacl::linalg::cuda::bluestein_pre</a></div><div class="ttdeci">__global__ void bluestein_pre(Numeric2T *input, Numeric2T *A, Numeric2T *B, unsigned int size, unsigned int ext_size, NumericT sign)</div><div class="ttdef"><b>Definition:</b> <a href="cuda_2fft__operations_8hpp_source.html#l00564">fft_operations.hpp:564</a></div></div>
<div class="ttc" id="host__based_2fft__operations_8hpp_html"><div class="ttname"><a href="host__based_2fft__operations_8hpp.html">fft_operations.hpp</a></div><div class="ttdoc">Implementations of Fast Furier Transformation using a plain single-threaded or OpenMP-enabled executi...</div></div>
<div class="ttc" id="linalg_2cuda_2common_8hpp_html_acdb31f22f4d1e12f1c2a27d4c4aa6865"><div class="ttname"><a href="linalg_2cuda_2common_8hpp.html#acdb31f22f4d1e12f1c2a27d4c4aa6865">VIENNACL_CUDA_LAST_ERROR_CHECK</a></div><div class="ttdeci">#define VIENNACL_CUDA_LAST_ERROR_CHECK(message)</div><div class="ttdef"><b>Definition:</b> <a href="linalg_2cuda_2common_8hpp_source.html#l00030">common.hpp:30</a></div></div>
<div class="ttc" id="classviennacl_1_1matrix__base_html_a00e30fdc61081a73995b54175a91d220"><div class="ttname"><a href="classviennacl_1_1matrix__base.html#a00e30fdc61081a73995b54175a91d220">viennacl::matrix_base< NumericT >::internal_size2</a></div><div class="ttdeci">size_type internal_size2() const</div><div class="ttdoc">Returns the internal number of columns. Usually required for launching OpenCL kernels only...</div><div class="ttdef"><b>Definition:</b> <a href="matrix__def_8hpp_source.html#l00240">matrix_def.hpp:240</a></div></div>
<div class="ttc" id="namespaceviennacl_1_1linalg_1_1cuda_html_a0ea13b0623b669778e42c76d25182418"><div class="ttname"><a href="namespaceviennacl_1_1linalg_1_1cuda.html#a0ea13b0623b669778e42c76d25182418">viennacl::linalg::cuda::transpose_inplace</a></div><div class="ttdeci">__global__ void transpose_inplace(NumericT *input, unsigned int row_num, unsigned int col_num)</div><div class="ttdef"><b>Definition:</b> <a href="cuda_2fft__operations_8hpp_source.html#l00746">fft_operations.hpp:746</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="namespaceviennacl_1_1linalg_1_1cuda_html_a5abf912b0fe2132fcc95233c46546951"><div class="ttname"><a href="namespaceviennacl_1_1linalg_1_1cuda.html#a5abf912b0fe2132fcc95233c46546951">viennacl::linalg::cuda::reverse</a></div><div class="ttdeci">void reverse(viennacl::vector_base< NumericT > &in)</div><div class="ttdoc">Reverse vector to oposite order and save it in input vector. </div><div class="ttdef"><b>Definition:</b> <a href="cuda_2fft__operations_8hpp_source.html#l00847">fft_operations.hpp:847</a></div></div>
<div class="ttc" id="classviennacl_1_1matrix__base_html_a82018b4e169973bdfb9d3be68ceb5be0"><div class="ttname"><a href="classviennacl_1_1matrix__base.html#a82018b4e169973bdfb9d3be68ceb5be0">viennacl::matrix_base< NumericT >::internal_size1</a></div><div class="ttdeci">size_type internal_size1() const</div><div class="ttdoc">Returns the internal number of rows. Usually required for launching OpenCL kernels only...</div><div class="ttdef"><b>Definition:</b> <a href="matrix__def_8hpp_source.html#l00238">matrix_def.hpp:238</a></div></div>
<div class="ttc" id="namespaceviennacl_1_1linalg_1_1cuda_html_a506556434450509c7e70e9de7ce3f2c6"><div class="ttname"><a href="namespaceviennacl_1_1linalg_1_1cuda.html#a506556434450509c7e70e9de7ce3f2c6">viennacl::linalg::cuda::multiply_complex</a></div><div class="ttdeci">void multiply_complex(viennacl::vector< NumericT, AlignmentV > const &input1, viennacl::vector< NumericT, AlignmentV > const &input2, viennacl::vector< NumericT, AlignmentV > &output)</div><div class="ttdoc">Mutiply two complex vectors and store result in output. </div><div class="ttdef"><b>Definition:</b> <a href="cuda_2fft__operations_8hpp_source.html#l00674">fft_operations.hpp:674</a></div></div>
<div class="ttc" id="namespaceviennacl_1_1linalg_1_1cuda_html_a5fba21e48290e4123b1287d1e6bd43bd"><div class="ttname"><a href="namespaceviennacl_1_1linalg_1_1cuda.html#a5fba21e48290e4123b1287d1e6bd43bd">viennacl::linalg::cuda::complex_to_real</a></div><div class="ttdeci">__global__ void complex_to_real(const ComplexT *in, RealT *out, unsigned int size)</div><div class="ttdef"><b>Definition:</b> <a href="cuda_2fft__operations_8hpp_source.html#l00809">fft_operations.hpp:809</a></div></div>
<div class="ttc" id="namespaceviennacl_1_1linalg_1_1cuda_html_a2bbc92ab80300afeae4b52a1ddd78674"><div class="ttname"><a href="namespaceviennacl_1_1linalg_1_1cuda.html#a2bbc92ab80300afeae4b52a1ddd78674">viennacl::linalg::cuda::operator-</a></div><div class="ttdeci">__host__ __device__ float2 operator-(float2 a, float2 b)</div><div class="ttdef"><b>Definition:</b> <a href="cuda_2fft__operations_8hpp_source.html#l00086">fft_operations.hpp:86</a></div></div>
<div class="ttc" id="namespaceviennacl_1_1linalg_1_1cuda_html_a479324e6bbbd101136667151607e3d0a"><div class="ttname"><a href="namespaceviennacl_1_1linalg_1_1cuda.html#a479324e6bbbd101136667151607e3d0a">viennacl::linalg::cuda::reorder</a></div><div class="ttdeci">void reorder(viennacl::vector< NumericT, AlignmentV > &in, vcl_size_t size, vcl_size_t stride, vcl_size_t bits_datasize, vcl_size_t batch_num, viennacl::linalg::host_based::detail::fft::FFT_DATA_ORDER::DATA_ORDER data_order=viennacl::linalg::host_based::detail::fft::FFT_DATA_ORDER::ROW_MAJOR)</div><div class="ttdef"><b>Definition:</b> <a href="cuda_2fft__operations_8hpp_source.html#l00282">fft_operations.hpp:282</a></div></div>
<div class="ttc" id="namespaceviennacl_1_1linalg_1_1cuda_html_ac69a0d15af9665507cd4df1493e24070"><div class="ttname"><a href="namespaceviennacl_1_1linalg_1_1cuda.html#ac69a0d15af9665507cd4df1493e24070">viennacl::linalg::cuda::direct</a></div><div class="ttdeci">void direct(viennacl::vector< NumericT, AlignmentV > const &in, viennacl::vector< NumericT, AlignmentV > &out, vcl_size_t size, vcl_size_t stride, vcl_size_t batch_num, NumericT sign=NumericT(-1), viennacl::linalg::host_based::detail::fft::FFT_DATA_ORDER::DATA_ORDER data_order=viennacl::linalg::host_based::detail::fft::FFT_DATA_ORDER::ROW_MAJOR)</div><div class="ttdoc">Direct 1D algorithm for computing Fourier transformation. </div><div class="ttdef"><b>Definition:</b> <a href="cuda_2fft__operations_8hpp_source.html#l00197">fft_operations.hpp:197</a></div></div>
<div class="ttc" id="namespaceviennacl_1_1linalg_1_1cuda_1_1detail_1_1fft_html_ad8af53105450cfc6a0adb586742a028e"><div class="ttname"><a href="namespaceviennacl_1_1linalg_1_1cuda_1_1detail_1_1fft.html#ad8af53105450cfc6a0adb586742a028e">viennacl::linalg::cuda::detail::fft::next_power_2</a></div><div class="ttdeci">vcl_size_t next_power_2(vcl_size_t n)</div><div class="ttdef"><b>Definition:</b> <a href="cuda_2fft__operations_8hpp_source.html#l00061">fft_operations.hpp:61</a></div></div>
<div class="ttc" id="namespaceviennacl_1_1linalg_1_1cuda_html_ad2f2f30942dedf7d5ab7adc5a282bb32"><div class="ttname"><a href="namespaceviennacl_1_1linalg_1_1cuda.html#ad2f2f30942dedf7d5ab7adc5a282bb32">viennacl::linalg::cuda::fft_radix2_local</a></div><div class="ttdeci">__global__ void fft_radix2_local(Numeric2T *input, unsigned int bit_size, unsigned int size, unsigned int stride, unsigned int batch_num, NumericT sign, bool is_row_major)</div><div class="ttdef"><b>Definition:</b> <a href="cuda_2fft__operations_8hpp_source.html#l00298">fft_operations.hpp:298</a></div></div>
<div class="ttc" id="structviennacl_1_1linalg_1_1cuda_1_1detail_1_1type__to__type2_html"><div class="ttname"><a href="structviennacl_1_1linalg_1_1cuda_1_1detail_1_1type__to__type2.html">viennacl::linalg::cuda::detail::type_to_type2</a></div><div class="ttdef"><b>Definition:</b> <a href="linalg_2cuda_2common_8hpp_source.html#l00178">common.hpp:178</a></div></div>
<div class="ttc" id="scalar_8hpp_html"><div class="ttname"><a href="scalar_8hpp.html">scalar.hpp</a></div><div class="ttdoc">Implementation of the ViennaCL scalar class. </div></div>
<div class="ttc" id="fft__1d_8cpp_html_a56353420d188d1181ae49bf69283b497"><div class="ttname"><a href="fft__1d_8cpp.html#a56353420d188d1181ae49bf69283b497">fft</a></div><div class="ttdeci">ScalarType fft(std::vector< ScalarType > &in, std::vector< ScalarType > &out, unsigned int, unsigned int, unsigned int batch_size)</div><div class="ttdef"><b>Definition:</b> <a href="fft__1d_8cpp_source.html#l00719">fft_1d.cpp:719</a></div></div>
<div class="ttc" id="namespaceviennacl_1_1linalg_1_1detail_html_a7bfa1c9cb0afb4ca0f975e690f4a8f07"><div class="ttname"><a href="namespaceviennacl_1_1linalg_1_1detail.html#a7bfa1c9cb0afb4ca0f975e690f4a8f07">viennacl::linalg::detail::sign</a></div><div class="ttdeci">SCALARTYPE sign(SCALARTYPE val)</div><div class="ttdef"><b>Definition:</b> <a href="qr-method-common_8hpp_source.html#l00071">qr-method-common.hpp:71</a></div></div>
<div class="ttc" id="host__based_2vector__operations_8hpp_html"><div class="ttname"><a href="host__based_2vector__operations_8hpp.html">vector_operations.hpp</a></div><div class="ttdoc">Implementations of NMF operations using a plain single-threaded or OpenMP-enabled execution on CPU...</div></div>
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