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<a href="arch_2mma__sm60_8h.html">Go to the documentation of this file.</a><div class="fragment"><div class="line"><a name="l00001"></a><span class="lineno"> 1</span> <span class="comment">/***************************************************************************************************</span></div><div class="line"><a name="l00002"></a><span class="lineno"> 2</span> <span class="comment"> * Copyright (c) 2017-2019, NVIDIA CORPORATION. All rights reserved.</span></div><div class="line"><a name="l00003"></a><span class="lineno"> 3</span> <span class="comment"> *</span></div><div class="line"><a name="l00004"></a><span class="lineno"> 4</span> <span class="comment"> * Redistribution and use in source and binary forms, with or without modification, are permitted</span></div><div class="line"><a name="l00005"></a><span class="lineno"> 5</span> <span class="comment"> * provided that the following conditions are met:</span></div><div class="line"><a name="l00006"></a><span class="lineno"> 6</span> <span class="comment"> * * Redistributions of source code must retain the above copyright notice, this list of</span></div><div class="line"><a name="l00007"></a><span class="lineno"> 7</span> <span class="comment"> * conditions and the following disclaimer.</span></div><div class="line"><a name="l00008"></a><span class="lineno"> 8</span> <span class="comment"> * * Redistributions in binary form must reproduce the above copyright notice, this list of</span></div><div class="line"><a name="l00009"></a><span class="lineno"> 9</span> <span class="comment"> * conditions and the following disclaimer in the documentation and/or other materials</span></div><div class="line"><a name="l00010"></a><span class="lineno"> 10</span> <span class="comment"> * provided with the distribution.</span></div><div class="line"><a name="l00011"></a><span class="lineno"> 11</span> <span class="comment"> * * Neither the name of the NVIDIA CORPORATION nor the names of its contributors may be used</span></div><div class="line"><a name="l00012"></a><span class="lineno"> 12</span> <span class="comment"> * to endorse or promote products derived from this software without specific prior written</span></div><div class="line"><a name="l00013"></a><span class="lineno"> 13</span> <span class="comment"> * permission.</span></div><div class="line"><a name="l00014"></a><span class="lineno"> 14</span> <span class="comment"> *</span></div><div class="line"><a name="l00015"></a><span class="lineno"> 15</span> <span class="comment"> * THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" AND ANY EXPRESS OR</span></div><div class="line"><a name="l00016"></a><span class="lineno"> 16</span> <span class="comment"> * IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND</span></div><div class="line"><a name="l00017"></a><span class="lineno"> 17</span> <span class="comment"> * FITNESS FOR A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL NVIDIA CORPORATION BE LIABLE</span></div><div class="line"><a name="l00018"></a><span class="lineno"> 18</span> <span class="comment"> * FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING,</span></div><div class="line"><a name="l00019"></a><span class="lineno"> 19</span> <span class="comment"> * BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS;</span></div><div class="line"><a name="l00020"></a><span class="lineno"> 20</span> <span class="comment"> * OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT,</span></div><div class="line"><a name="l00021"></a><span class="lineno"> 21</span> <span class="comment"> * STRICT LIABILITY, OR TOR (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE</span></div><div class="line"><a name="l00022"></a><span class="lineno"> 22</span> <span class="comment"> * OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.</span></div><div class="line"><a name="l00023"></a><span class="lineno"> 23</span> <span class="comment"> *</span></div><div class="line"><a name="l00024"></a><span class="lineno"> 24</span> <span class="comment"> **************************************************************************************************/</span></div><div class="line"><a name="l00029"></a><span class="lineno"> 29</span> <span class="preprocessor">#pragma once</span></div><div class="line"><a name="l00030"></a><span class="lineno"> 30</span> </div><div class="line"><a name="l00031"></a><span class="lineno"> 31</span> <span class="preprocessor">#include <cuda_fp16.h></span></div><div class="line"><a name="l00032"></a><span class="lineno"> 32</span> </div><div class="line"><a name="l00033"></a><span class="lineno"> 33</span> <span class="preprocessor">#include "<a class="code" href="arch_2mma_8h.html">cutlass/arch/mma.h</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="preprocessor">#include "<a class="code" href="layout_2matrix_8h.html">cutlass/layout/matrix.h</a>"</span></div><div class="line"><a name="l00036"></a><span class="lineno"> 36</span> </div><div class="line"><a name="l00038"></a><span class="lineno"> 38</span> </div><div class="line"><a name="l00039"></a><span class="lineno"> 39</span> <span class="keyword">namespace </span><a class="code" href="namespacecutlass.html">cutlass</a> {</div><div class="line"><a name="l00040"></a><span class="lineno"> 40</span> <span class="keyword">namespace </span>arch {</div><div class="line"><a name="l00041"></a><span class="lineno"> 41</span> </div><div class="line"><a name="l00043"></a><span class="lineno"> 43</span> </div><div class="line"><a name="l00045"></a><span class="lineno"> 45</span> <span class="keyword">template</span> <<span class="keyword">typename</span> LayoutA, <span class="keyword">typename</span> LayoutB, <span class="keyword">typename</span> LayoutC></div><div class="line"><a name="l00046"></a><span class="lineno"><a class="line" href="structcutlass_1_1arch_1_1Mma_3_01gemm_1_1GemmShape_3_012_00_011_00_011_01_4_00_011_00_01half__t_8cf78649807b93684f3d431bfa34ee28.html"> 46</a></span> <span class="keyword">struct </span><a class="code" href="structcutlass_1_1arch_1_1Mma.html">Mma</a><</div><div class="line"><a name="l00047"></a><span class="lineno"> 47</span>  gemm::GemmShape<2,1,1>,</div><div class="line"><a name="l00048"></a><span class="lineno"> 48</span>  1,</div><div class="line"><a name="l00049"></a><span class="lineno"> 49</span>  <a class="code" href="structcutlass_1_1half__t.html">half_t</a>,</div><div class="line"><a name="l00050"></a><span class="lineno"> 50</span>  LayoutA,</div><div class="line"><a name="l00051"></a><span class="lineno"> 51</span>  <a class="code" href="structcutlass_1_1half__t.html">half_t</a>,</div><div class="line"><a name="l00052"></a><span class="lineno"> 52</span>  LayoutB,</div><div class="line"><a name="l00053"></a><span class="lineno"> 53</span>  <a class="code" href="structcutlass_1_1half__t.html">half_t</a>,</div><div class="line"><a name="l00054"></a><span class="lineno"> 54</span>  LayoutC,</div><div class="line"><a name="l00055"></a><span class="lineno"> 55</span>  OpMultiplyAdd> {</div><div class="line"><a name="l00056"></a><span class="lineno"> 56</span> </div><div class="line"><a name="l00057"></a><span class="lineno"><a class="line" href="structcutlass_1_1arch_1_1Mma_3_01gemm_1_1GemmShape_3_012_00_011_00_011_01_4_00_011_00_01half__t_8cf78649807b93684f3d431bfa34ee28.html#a9250a8883963f94065bfa6ff7f888fa5"> 57</a></span>  <span class="keyword">using</span> <a class="code" href="structcutlass_1_1gemm_1_1GemmShape.html">Shape</a> = <a class="code" href="structcutlass_1_1gemm_1_1GemmShape.html">gemm::GemmShape<2, 1, 1></a>;</div><div class="line"><a name="l00058"></a><span class="lineno"> 58</span> </div><div class="line"><a name="l00059"></a><span class="lineno"> 59</span>  <a class="code" href="cutlass_8h.html#a28c2443a142676d3d71effdae1a986b1">CUTLASS_HOST_DEVICE</a></div><div class="line"><a name="l00060"></a><span class="lineno"><a class="line" href="structcutlass_1_1arch_1_1Mma_3_01gemm_1_1GemmShape_3_012_00_011_00_011_01_4_00_011_00_01half__t_8cf78649807b93684f3d431bfa34ee28.html#a602ba0c72022da14a4def190581ca0de"> 60</a></span>  <span class="keywordtype">void</span> <a class="code" href="structcutlass_1_1arch_1_1Mma_3_01gemm_1_1GemmShape_3_012_00_011_00_011_01_4_00_011_00_01half__t_8cf78649807b93684f3d431bfa34ee28.html#a602ba0c72022da14a4def190581ca0de">operator()</a>(</div><div class="line"><a name="l00061"></a><span class="lineno"> 61</span>  Array<half_t, 2> &d,</div><div class="line"><a name="l00062"></a><span class="lineno"> 62</span>  Array<half_t, 2> <span class="keyword">const</span> &a,</div><div class="line"><a name="l00063"></a><span class="lineno"> 63</span>  Array<half_t, 1> <span class="keyword">const</span> &b,</div><div class="line"><a name="l00064"></a><span class="lineno"> 64</span>  Array<half_t, 2> <span class="keyword">const</span> &c</div><div class="line"><a name="l00065"></a><span class="lineno"> 65</span>  ) {</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="preprocessor">#if (defined(__CUDA_ARCH__) && (__CUDA_ARCH__ >= 600))</span></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>  __half2 <span class="keyword">const</span> & A = <span class="keyword">reinterpret_cast<</span>__half2 <span class="keyword">const </span>&<span class="keyword">></span>(a);</div><div class="line"><a name="l00070"></a><span class="lineno"> 70</span>  __half2 B = __half2half2(reinterpret_cast<__half const &>(b));</div><div class="line"><a name="l00071"></a><span class="lineno"> 71</span>  __half2 <span class="keyword">const</span> & C = <span class="keyword">reinterpret_cast<</span>__half2 <span class="keyword">const </span>&<span class="keyword">></span>(c);</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>  __half2 D = __hfma2(A, B, C);</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>  d = <span class="keyword">reinterpret_cast<</span>Array<half_t, 2> &<span class="keyword">></span>(D);</div><div class="line"><a name="l00076"></a><span class="lineno"> 76</span> </div><div class="line"><a name="l00077"></a><span class="lineno"> 77</span> <span class="preprocessor">#else</span></div><div class="line"><a name="l00078"></a><span class="lineno"> 78</span>  <a class="code" href="cutlass_8h.html#a4b1c9f25ab6eaa25e1f2258dd63e6ce4">CUTLASS_PRAGMA_UNROLL</a></div><div class="line"><a name="l00079"></a><span class="lineno"> 79</span>  <span class="keywordflow">for</span> (<span class="keywordtype">int</span> i = 0; i < 2; ++i) {</div><div class="line"><a name="l00080"></a><span class="lineno"> 80</span>  d[i] = a[i] * b[0] + c[i];</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="preprocessor">#endif</span></div><div class="line"><a name="l00083"></a><span class="lineno"> 83</span>  }</div><div class="line"><a name="l00084"></a><span class="lineno"> 84</span> };</div><div class="line"><a name="l00085"></a><span class="lineno"> 85</span> </div><div class="line"><a name="l00087"></a><span class="lineno"> 87</span> </div><div class="line"><a name="l00089"></a><span class="lineno"> 89</span> <span class="keyword">template</span> <<span class="keyword">typename</span> LayoutA, <span class="keyword">typename</span> LayoutB></div><div class="line"><a name="l00090"></a><span class="lineno"><a class="line" href="structcutlass_1_1arch_1_1Mma_3_01gemm_1_1GemmShape_3_011_00_012_00_011_01_4_00_011_00_01half__t_f3dc2e59f857ada163d1e0781ea8f391.html"> 90</a></span> <span class="keyword">struct </span><a class="code" href="structcutlass_1_1arch_1_1Mma.html">Mma</a><</div><div class="line"><a name="l00091"></a><span class="lineno"> 91</span>  gemm::GemmShape<1,2,1>,</div><div class="line"><a name="l00092"></a><span class="lineno"> 92</span>  1,</div><div class="line"><a name="l00093"></a><span class="lineno"> 93</span>  <a class="code" href="structcutlass_1_1half__t.html">half_t</a>,</div><div class="line"><a name="l00094"></a><span class="lineno"> 94</span>  LayoutA,</div><div class="line"><a name="l00095"></a><span class="lineno"> 95</span>  <a class="code" href="structcutlass_1_1half__t.html">half_t</a>,</div><div class="line"><a name="l00096"></a><span class="lineno"> 96</span>  LayoutB,</div><div class="line"><a name="l00097"></a><span class="lineno"> 97</span>  <a class="code" href="structcutlass_1_1half__t.html">half_t</a>,</div><div class="line"><a name="l00098"></a><span class="lineno"> 98</span>  <a class="code" href="classcutlass_1_1layout_1_1RowMajor.html">layout::RowMajor</a>,</div><div class="line"><a name="l00099"></a><span class="lineno"> 99</span>  OpMultiplyAdd> {</div><div class="line"><a name="l00100"></a><span class="lineno"> 100</span> </div><div class="line"><a name="l00101"></a><span class="lineno"><a class="line" href="structcutlass_1_1arch_1_1Mma_3_01gemm_1_1GemmShape_3_011_00_012_00_011_01_4_00_011_00_01half__t_f3dc2e59f857ada163d1e0781ea8f391.html#a18f5d500040e4b64431f991689f841da"> 101</a></span>  <span class="keyword">using</span> <a class="code" href="structcutlass_1_1gemm_1_1GemmShape.html">Shape</a> = <a class="code" href="structcutlass_1_1gemm_1_1GemmShape.html">gemm::GemmShape<1, 2, 1></a>;</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>  <a class="code" href="cutlass_8h.html#a28c2443a142676d3d71effdae1a986b1">CUTLASS_HOST_DEVICE</a></div><div class="line"><a name="l00104"></a><span class="lineno"><a class="line" href="structcutlass_1_1arch_1_1Mma_3_01gemm_1_1GemmShape_3_011_00_012_00_011_01_4_00_011_00_01half__t_f3dc2e59f857ada163d1e0781ea8f391.html#a58bfd183b9425b6eebe825192569fd3f"> 104</a></span>  <span class="keywordtype">void</span> <a class="code" href="structcutlass_1_1arch_1_1Mma_3_01gemm_1_1GemmShape_3_011_00_012_00_011_01_4_00_011_00_01half__t_f3dc2e59f857ada163d1e0781ea8f391.html#a58bfd183b9425b6eebe825192569fd3f">operator()</a>(</div><div class="line"><a name="l00105"></a><span class="lineno"> 105</span>  Array<half_t, 2> &d,</div><div class="line"><a name="l00106"></a><span class="lineno"> 106</span>  Array<half_t, 1> <span class="keyword">const</span> &a,</div><div class="line"><a name="l00107"></a><span class="lineno"> 107</span>  Array<half_t, 2> <span class="keyword">const</span> &b,</div><div class="line"><a name="l00108"></a><span class="lineno"> 108</span>  Array<half_t, 2> <span class="keyword">const</span> &c</div><div class="line"><a name="l00109"></a><span class="lineno"> 109</span>  ) {</div><div class="line"><a name="l00110"></a><span class="lineno"> 110</span> </div><div class="line"><a name="l00111"></a><span class="lineno"> 111</span> <span class="preprocessor">#if (defined(__CUDA_ARCH__) && (__CUDA_ARCH__ >= 600))</span></div><div class="line"><a name="l00112"></a><span class="lineno"> 112</span> </div><div class="line"><a name="l00113"></a><span class="lineno"> 113</span>  __half2 <span class="keyword">const</span> & A = __half2half2(reinterpret_cast<__half const &>(a));</div><div class="line"><a name="l00114"></a><span class="lineno"> 114</span>  __half2 B = <span class="keyword">reinterpret_cast<</span>__half2 <span class="keyword">const </span>&<span class="keyword">></span>(b);</div><div class="line"><a name="l00115"></a><span class="lineno"> 115</span>  __half2 <span class="keyword">const</span> & C = <span class="keyword">reinterpret_cast<</span>__half2 <span class="keyword">const </span>&<span class="keyword">></span>(c);</div><div class="line"><a name="l00116"></a><span class="lineno"> 116</span> </div><div class="line"><a name="l00117"></a><span class="lineno"> 117</span>  __half2 D = __hfma2(A, B, C);</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>  d = <span class="keyword">reinterpret_cast<</span>Array<half_t, 2> &<span class="keyword">></span>(D);</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> <span class="preprocessor">#else</span></div><div class="line"><a name="l00122"></a><span class="lineno"> 122</span>  <a class="code" href="cutlass_8h.html#a4b1c9f25ab6eaa25e1f2258dd63e6ce4">CUTLASS_PRAGMA_UNROLL</a></div><div class="line"><a name="l00123"></a><span class="lineno"> 123</span>  <span class="keywordflow">for</span> (<span class="keywordtype">int</span> i = 0; i < 2; ++i) {</div><div class="line"><a name="l00124"></a><span class="lineno"> 124</span>  d[i] = a[0] * b[i] + c[i];</div><div class="line"><a name="l00125"></a><span class="lineno"> 125</span>  }</div><div class="line"><a name="l00126"></a><span class="lineno"> 126</span> <span class="preprocessor">#endif</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"> 128</span> };</div><div class="line"><a name="l00129"></a><span class="lineno"> 129</span> </div><div class="line"><a name="l00131"></a><span class="lineno"> 131</span> </div><div class="line"><a name="l00133"></a><span class="lineno"> 133</span> <span class="keyword">template</span> <></div><div class="line"><a name="l00134"></a><span class="lineno"><a class="line" href="structcutlass_1_1arch_1_1Mma_3_01gemm_1_1GemmShape_3_012_00_012_00_011_01_4_00_011_00_01half__t_ccde11d1bbbdab3702772ce44eb9729a.html"> 134</a></span> <span class="keyword">struct </span><a class="code" href="structcutlass_1_1arch_1_1Mma.html">Mma</a> <</div><div class="line"><a name="l00135"></a><span class="lineno"> 135</span>  gemm::GemmShape<2, 2, 1>,</div><div class="line"><a name="l00136"></a><span class="lineno"> 136</span>  1,</div><div class="line"><a name="l00137"></a><span class="lineno"> 137</span>  <a class="code" href="structcutlass_1_1half__t.html">half_t</a>,</div><div class="line"><a name="l00138"></a><span class="lineno"> 138</span>  <a class="code" href="classcutlass_1_1layout_1_1ColumnMajor.html">layout::ColumnMajor</a>,</div><div class="line"><a name="l00139"></a><span class="lineno"> 139</span>  <a class="code" href="structcutlass_1_1half__t.html">half_t</a>,</div><div class="line"><a name="l00140"></a><span class="lineno"> 140</span>  <a class="code" href="classcutlass_1_1layout_1_1RowMajor.html">layout::RowMajor</a>,</div><div class="line"><a name="l00141"></a><span class="lineno"> 141</span>  <a class="code" href="structcutlass_1_1half__t.html">half_t</a>,</div><div class="line"><a name="l00142"></a><span class="lineno"> 142</span>  <a class="code" href="classcutlass_1_1layout_1_1ColumnMajor.html">layout::ColumnMajor</a>,</div><div class="line"><a name="l00143"></a><span class="lineno"> 143</span>  OpMultiplyAdd> {</div><div class="line"><a name="l00144"></a><span class="lineno"> 144</span> </div><div class="line"><a name="l00145"></a><span class="lineno"><a class="line" href="structcutlass_1_1arch_1_1Mma_3_01gemm_1_1GemmShape_3_012_00_012_00_011_01_4_00_011_00_01half__t_ccde11d1bbbdab3702772ce44eb9729a.html#a7522914cdd5e5357475e4743f5f1a5e5"> 145</a></span>  <span class="keyword">using</span> <a class="code" href="structcutlass_1_1gemm_1_1GemmShape.html">Shape</a> = <a class="code" href="structcutlass_1_1gemm_1_1GemmShape.html">gemm::GemmShape<2, 2, 1></a>;</div><div class="line"><a name="l00146"></a><span class="lineno"> 146</span> </div><div class="line"><a name="l00147"></a><span class="lineno"> 147</span>  <a class="code" href="cutlass_8h.html#a28c2443a142676d3d71effdae1a986b1">CUTLASS_HOST_DEVICE</a></div><div class="line"><a name="l00148"></a><span class="lineno"><a class="line" href="structcutlass_1_1arch_1_1Mma_3_01gemm_1_1GemmShape_3_012_00_012_00_011_01_4_00_011_00_01half__t_ccde11d1bbbdab3702772ce44eb9729a.html#a6e7f4b55f118e81ee493bcbf51519e77"> 148</a></span>  <span class="keywordtype">void</span> <a class="code" href="structcutlass_1_1arch_1_1Mma_3_01gemm_1_1GemmShape_3_012_00_012_00_011_01_4_00_011_00_01half__t_ccde11d1bbbdab3702772ce44eb9729a.html#a6e7f4b55f118e81ee493bcbf51519e77">operator()</a>(</div><div class="line"><a name="l00149"></a><span class="lineno"> 149</span>  Array<half_t, 4> &d,</div><div class="line"><a name="l00150"></a><span class="lineno"> 150</span>  Array<half_t, 2> <span class="keyword">const</span> &a,</div><div class="line"><a name="l00151"></a><span class="lineno"> 151</span>  Array<half_t, 2> <span class="keyword">const</span> &b,</div><div class="line"><a name="l00152"></a><span class="lineno"> 152</span>  Array<half_t, 4> <span class="keyword">const</span> &c</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> </div><div class="line"><a name="l00155"></a><span class="lineno"> 155</span> <span class="preprocessor">#if (defined(__CUDA_ARCH__) && (__CUDA_ARCH__ >= 600))</span></div><div class="line"><a name="l00156"></a><span class="lineno"> 156</span> </div><div class="line"><a name="l00157"></a><span class="lineno"> 157</span>  __half2 <span class="keyword">const</span> & A = <span class="keyword">reinterpret_cast<</span>__half2 <span class="keyword">const </span>&<span class="keyword">></span>(a);</div><div class="line"><a name="l00158"></a><span class="lineno"> 158</span>  __half2 Blo = __low2half2(reinterpret_cast<__half2 const &>(b));</div><div class="line"><a name="l00159"></a><span class="lineno"> 159</span>  __half2 Bhi = __high2half2(reinterpret_cast<__half2 const &>(b));</div><div class="line"><a name="l00160"></a><span class="lineno"> 160</span> </div><div class="line"><a name="l00161"></a><span class="lineno"> 161</span>  __half2 <span class="keyword">const</span> *C = <span class="keyword">reinterpret_cast<</span>__half2 <span class="keyword">const </span>*<span class="keyword">></span>(&c);</div><div class="line"><a name="l00162"></a><span class="lineno"> 162</span> </div><div class="line"><a name="l00163"></a><span class="lineno"> 163</span>  __half2 Dlo = __hfma2(A, Blo, C[0]);</div><div class="line"><a name="l00164"></a><span class="lineno"> 164</span>  __half2 Dhi = __hfma2(A, Bhi, C[1]);</div><div class="line"><a name="l00165"></a><span class="lineno"> 165</span> </div><div class="line"><a name="l00166"></a><span class="lineno"> 166</span>  Array<half_t, 2> * D = <span class="keyword">reinterpret_cast<</span>Array<half_t, 2> *<span class="keyword">></span>(&d);</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>  D[0] = <span class="keyword">reinterpret_cast<</span>Array<half_t, 2> <span class="keyword">const </span>&<span class="keyword">></span>(Dlo);</div><div class="line"><a name="l00169"></a><span class="lineno"> 169</span>  D[1] = <span class="keyword">reinterpret_cast<</span>Array<half_t, 2> <span class="keyword">const </span>&<span class="keyword">></span>(Dhi);</div><div class="line"><a name="l00170"></a><span class="lineno"> 170</span> </div><div class="line"><a name="l00171"></a><span class="lineno"> 171</span> <span class="preprocessor">#else</span></div><div class="line"><a name="l00172"></a><span class="lineno"> 172</span>  <a class="code" href="cutlass_8h.html#a4b1c9f25ab6eaa25e1f2258dd63e6ce4">CUTLASS_PRAGMA_UNROLL</a></div><div class="line"><a name="l00173"></a><span class="lineno"> 173</span>  <span class="keywordflow">for</span> (<span class="keywordtype">int</span> j = 0; j < 2; ++j) {</div><div class="line"><a name="l00174"></a><span class="lineno"> 174</span>  <a class="code" href="cutlass_8h.html#a4b1c9f25ab6eaa25e1f2258dd63e6ce4">CUTLASS_PRAGMA_UNROLL</a></div><div class="line"><a name="l00175"></a><span class="lineno"> 175</span>  <span class="keywordflow">for</span> (<span class="keywordtype">int</span> i = 0; i < 2; ++i) {</div><div class="line"><a name="l00176"></a><span class="lineno"> 176</span>  d[i + 2 * j] = a[i] * b[j] + c[i + 2 * j];</div><div class="line"><a name="l00177"></a><span class="lineno"> 177</span>  }</div><div class="line"><a name="l00178"></a><span class="lineno"> 178</span>  }</div><div class="line"><a name="l00179"></a><span class="lineno"> 179</span> <span class="preprocessor">#endif</span></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> </div><div class="line"><a name="l00184"></a><span class="lineno"> 184</span> </div><div class="line"><a name="l00186"></a><span class="lineno"> 186</span> <span class="keyword">template</span> <></div><div class="line"><a name="l00187"></a><span class="lineno"><a class="line" href="structcutlass_1_1arch_1_1Mma_3_01gemm_1_1GemmShape_3_012_00_012_00_011_01_4_00_011_00_01half__t_c07cc6439298fa5486a719e577be2538.html"> 187</a></span> <span class="keyword">struct </span><a class="code" href="structcutlass_1_1arch_1_1Mma.html">Mma</a><</div><div class="line"><a name="l00188"></a><span class="lineno"> 188</span>  gemm::GemmShape<2, 2, 1>,</div><div class="line"><a name="l00189"></a><span class="lineno"> 189</span>  1,</div><div class="line"><a name="l00190"></a><span class="lineno"> 190</span>  <a class="code" href="structcutlass_1_1half__t.html">half_t</a>,</div><div class="line"><a name="l00191"></a><span class="lineno"> 191</span>  <a class="code" href="classcutlass_1_1layout_1_1ColumnMajor.html">layout::ColumnMajor</a>,</div><div class="line"><a name="l00192"></a><span class="lineno"> 192</span>  <a class="code" href="structcutlass_1_1half__t.html">half_t</a>,</div><div class="line"><a name="l00193"></a><span class="lineno"> 193</span>  <a class="code" href="classcutlass_1_1layout_1_1RowMajor.html">layout::RowMajor</a>,</div><div class="line"><a name="l00194"></a><span class="lineno"> 194</span>  <a class="code" href="structcutlass_1_1half__t.html">half_t</a>,</div><div class="line"><a name="l00195"></a><span class="lineno"> 195</span>  <a class="code" href="classcutlass_1_1layout_1_1RowMajor.html">layout::RowMajor</a>,</div><div class="line"><a name="l00196"></a><span class="lineno"> 196</span>  OpMultiplyAdd> {</div><div class="line"><a name="l00197"></a><span class="lineno"> 197</span> </div><div class="line"><a name="l00198"></a><span class="lineno"><a class="line" href="structcutlass_1_1arch_1_1Mma_3_01gemm_1_1GemmShape_3_012_00_012_00_011_01_4_00_011_00_01half__t_c07cc6439298fa5486a719e577be2538.html#acb118c7cfb980fc4f5cbb541792e8977"> 198</a></span>  <span class="keyword">using</span> <a class="code" href="structcutlass_1_1gemm_1_1GemmShape.html">Shape</a> = <a class="code" href="structcutlass_1_1gemm_1_1GemmShape.html">gemm::GemmShape<2, 2, 1></a>;</div><div class="line"><a name="l00199"></a><span class="lineno"> 199</span> </div><div class="line"><a name="l00200"></a><span class="lineno"> 200</span>  <a class="code" href="cutlass_8h.html#a28c2443a142676d3d71effdae1a986b1">CUTLASS_HOST_DEVICE</a></div><div class="line"><a name="l00201"></a><span class="lineno"><a class="line" href="structcutlass_1_1arch_1_1Mma_3_01gemm_1_1GemmShape_3_012_00_012_00_011_01_4_00_011_00_01half__t_c07cc6439298fa5486a719e577be2538.html#a37ea44d16dbc07ca46888812caf5773c"> 201</a></span>  <span class="keywordtype">void</span> <a class="code" href="structcutlass_1_1arch_1_1Mma_3_01gemm_1_1GemmShape_3_012_00_012_00_011_01_4_00_011_00_01half__t_c07cc6439298fa5486a719e577be2538.html#a37ea44d16dbc07ca46888812caf5773c">operator()</a>(</div><div class="line"><a name="l00202"></a><span class="lineno"> 202</span>  Array<half_t, 4> &d,</div><div class="line"><a name="l00203"></a><span class="lineno"> 203</span>  Array<half_t, 2> <span class="keyword">const</span> &a,</div><div class="line"><a name="l00204"></a><span class="lineno"> 204</span>  Array<half_t, 2> <span class="keyword">const</span> &b,</div><div class="line"><a name="l00205"></a><span class="lineno"> 205</span>  Array<half_t, 4> <span class="keyword">const</span> &c</div><div class="line"><a name="l00206"></a><span class="lineno"> 206</span>  ) {</div><div class="line"><a name="l00207"></a><span class="lineno"> 207</span> </div><div class="line"><a name="l00208"></a><span class="lineno"> 208</span> <span class="preprocessor">#if (defined(__CUDA_ARCH__) && (__CUDA_ARCH__ >= 600))</span></div><div class="line"><a name="l00209"></a><span class="lineno"> 209</span> </div><div class="line"><a name="l00210"></a><span class="lineno"> 210</span>  __half2 Alo = __low2half2(reinterpret_cast<__half2 const &>(a));</div><div class="line"><a name="l00211"></a><span class="lineno"> 211</span>  __half2 Ahi = __high2half2(reinterpret_cast<__half2 const &>(a));</div><div class="line"><a name="l00212"></a><span class="lineno"> 212</span>  __half2 <span class="keyword">const</span> & B = <span class="keyword">reinterpret_cast<</span>__half2 <span class="keyword">const </span>&<span class="keyword">></span>(b);</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>  __half2 <span class="keyword">const</span> *C = <span class="keyword">reinterpret_cast<</span>__half2 <span class="keyword">const </span>*<span class="keyword">></span>(&c);</div><div class="line"><a name="l00215"></a><span class="lineno"> 215</span> </div><div class="line"><a name="l00216"></a><span class="lineno"> 216</span>  __half2 Dlo = __hfma2(Alo, B, C[0]);</div><div class="line"><a name="l00217"></a><span class="lineno"> 217</span>  __half2 Dhi = __hfma2(Ahi, B, C[0]);</div><div class="line"><a name="l00218"></a><span class="lineno"> 218</span>  </div><div class="line"><a name="l00219"></a><span class="lineno"> 219</span>  Array<half_t, 2> * D = <span class="keyword">reinterpret_cast<</span>Array<half_t, 2> *<span class="keyword">></span>(&d);</div><div class="line"><a name="l00220"></a><span class="lineno"> 220</span> </div><div class="line"><a name="l00221"></a><span class="lineno"> 221</span>  D[0] = <span class="keyword">reinterpret_cast<</span>Array<half_t, 2> &<span class="keyword">></span>(Dlo);</div><div class="line"><a name="l00222"></a><span class="lineno"> 222</span>  D[1] = <span class="keyword">reinterpret_cast<</span>Array<half_t, 2> &<span class="keyword">></span>(Dhi);</div><div class="line"><a name="l00223"></a><span class="lineno"> 223</span> <span class="preprocessor">#else</span></div><div class="line"><a name="l00224"></a><span class="lineno"> 224</span>  <a class="code" href="cutlass_8h.html#a4b1c9f25ab6eaa25e1f2258dd63e6ce4">CUTLASS_PRAGMA_UNROLL</a></div><div class="line"><a name="l00225"></a><span class="lineno"> 225</span>  <span class="keywordflow">for</span> (<span class="keywordtype">int</span> i = 0; i < 2; ++i) {</div><div class="line"><a name="l00226"></a><span class="lineno"> 226</span>  <a class="code" href="cutlass_8h.html#a4b1c9f25ab6eaa25e1f2258dd63e6ce4">CUTLASS_PRAGMA_UNROLL</a></div><div class="line"><a name="l00227"></a><span class="lineno"> 227</span>  <span class="keywordflow">for</span> (<span class="keywordtype">int</span> j = 0; j < 2; ++j) {</div><div class="line"><a name="l00228"></a><span class="lineno"> 228</span>  d[i * 2 + j] = a[i] * b[j] + c[i * 2 + j];</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>  }</div><div class="line"><a name="l00231"></a><span class="lineno"> 231</span> <span class="preprocessor">#endif</span></div><div class="line"><a name="l00232"></a><span class="lineno"> 232</span>  }</div><div class="line"><a name="l00233"></a><span class="lineno"> 233</span> };</div><div class="line"><a name="l00234"></a><span class="lineno"> 234</span> </div><div class="line"><a name="l00236"></a><span class="lineno"> 236</span> </div><div class="line"><a name="l00237"></a><span class="lineno"> 237</span> }</div><div class="line"><a name="l00238"></a><span class="lineno"> 238</span> }</div><div class="line"><a name="l00239"></a><span class="lineno"> 239</span> </div><div class="ttc" id="structcutlass_1_1arch_1_1Mma_3_01gemm_1_1GemmShape_3_011_00_012_00_011_01_4_00_011_00_01half__t_f3dc2e59f857ada163d1e0781ea8f391_html_a58bfd183b9425b6eebe825192569fd3f"><div class="ttname"><a href="structcutlass_1_1arch_1_1Mma_3_01gemm_1_1GemmShape_3_011_00_012_00_011_01_4_00_011_00_01half__t_f3dc2e59f857ada163d1e0781ea8f391.html#a58bfd183b9425b6eebe825192569fd3f">cutlass::arch::Mma< gemm::GemmShape< 1, 2, 1 >, 1, half_t, LayoutA, half_t, LayoutB, half_t, layout::RowMajor, OpMultiplyAdd >::operator()</a></div><div class="ttdeci">CUTLASS_HOST_DEVICE void operator()(Array< half_t, 2 > &d, Array< half_t, 1 > const &a, Array< half_t, 2 > const &b, Array< half_t, 2 > const &c)</div><div class="ttdef"><b>Definition:</b> arch/mma_sm60.h:104</div></div>
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<div class="ttc" id="namespacecutlass_html"><div class="ttname"><a href="namespacecutlass.html">cutlass</a></div><div class="ttdef"><b>Definition:</b> aligned_buffer.h:35</div></div>
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<div class="ttc" id="structcutlass_1_1half__t_html"><div class="ttname"><a href="structcutlass_1_1half__t.html">cutlass::half_t</a></div><div class="ttdoc">IEEE half-precision floating-point type. </div><div class="ttdef"><b>Definition:</b> half.h:126</div></div>
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<div class="ttc" id="structcutlass_1_1arch_1_1Mma_3_01gemm_1_1GemmShape_3_012_00_011_00_011_01_4_00_011_00_01half__t_8cf78649807b93684f3d431bfa34ee28_html_a602ba0c72022da14a4def190581ca0de"><div class="ttname"><a href="structcutlass_1_1arch_1_1Mma_3_01gemm_1_1GemmShape_3_012_00_011_00_011_01_4_00_011_00_01half__t_8cf78649807b93684f3d431bfa34ee28.html#a602ba0c72022da14a4def190581ca0de">cutlass::arch::Mma< gemm::GemmShape< 2, 1, 1 >, 1, half_t, LayoutA, half_t, LayoutB, half_t, LayoutC, OpMultiplyAdd >::operator()</a></div><div class="ttdeci">CUTLASS_HOST_DEVICE void operator()(Array< half_t, 2 > &d, Array< half_t, 2 > const &a, Array< half_t, 1 > const &b, Array< half_t, 2 > const &c)</div><div class="ttdef"><b>Definition:</b> arch/mma_sm60.h:60</div></div>
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<div class="ttc" id="classcutlass_1_1layout_1_1ColumnMajor_html"><div class="ttname"><a href="classcutlass_1_1layout_1_1ColumnMajor.html">cutlass::layout::ColumnMajor</a></div><div class="ttdoc">Mapping function for column-major matrices. </div><div class="ttdef"><b>Definition:</b> layout/matrix.h:142</div></div>
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<div class="ttc" id="cutlass_8h_html_a4b1c9f25ab6eaa25e1f2258dd63e6ce4"><div class="ttname"><a href="cutlass_8h.html#a4b1c9f25ab6eaa25e1f2258dd63e6ce4">CUTLASS_PRAGMA_UNROLL</a></div><div class="ttdeci">#define CUTLASS_PRAGMA_UNROLL</div><div class="ttdef"><b>Definition:</b> cutlass.h:110</div></div>
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<div class="ttc" id="arch_2mma_8h_html"><div class="ttname"><a href="arch_2mma_8h.html">mma.h</a></div><div class="ttdoc">Templates exposing architecture support for multiply-add operations. </div></div>
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<div class="ttc" id="structcutlass_1_1arch_1_1Mma_3_01gemm_1_1GemmShape_3_012_00_012_00_011_01_4_00_011_00_01half__t_ccde11d1bbbdab3702772ce44eb9729a_html_a6e7f4b55f118e81ee493bcbf51519e77"><div class="ttname"><a href="structcutlass_1_1arch_1_1Mma_3_01gemm_1_1GemmShape_3_012_00_012_00_011_01_4_00_011_00_01half__t_ccde11d1bbbdab3702772ce44eb9729a.html#a6e7f4b55f118e81ee493bcbf51519e77">cutlass::arch::Mma< gemm::GemmShape< 2, 2, 1 >, 1, half_t, layout::ColumnMajor, half_t, layout::RowMajor, half_t, layout::ColumnMajor, OpMultiplyAdd >::operator()</a></div><div class="ttdeci">CUTLASS_HOST_DEVICE void operator()(Array< half_t, 4 > &d, Array< half_t, 2 > const &a, Array< half_t, 2 > const &b, Array< half_t, 4 > const &c)</div><div class="ttdef"><b>Definition:</b> arch/mma_sm60.h:148</div></div>
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<div class="ttc" id="cutlass_8h_html_a28c2443a142676d3d71effdae1a986b1"><div class="ttname"><a href="cutlass_8h.html#a28c2443a142676d3d71effdae1a986b1">CUTLASS_HOST_DEVICE</a></div><div class="ttdeci">#define CUTLASS_HOST_DEVICE</div><div class="ttdef"><b>Definition:</b> cutlass.h:89</div></div>
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<div class="ttc" id="structcutlass_1_1gemm_1_1GemmShape_html"><div class="ttname"><a href="structcutlass_1_1gemm_1_1GemmShape.html">cutlass::gemm::GemmShape</a></div><div class="ttdoc">Shape of a matrix multiply-add operation. </div><div class="ttdef"><b>Definition:</b> include/cutlass/gemm/gemm.h:57</div></div>
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<div class="ttc" id="classcutlass_1_1layout_1_1RowMajor_html"><div class="ttname"><a href="classcutlass_1_1layout_1_1RowMajor.html">cutlass::layout::RowMajor</a></div><div class="ttdoc">Mapping function for row-major matrices. </div><div class="ttdef"><b>Definition:</b> layout/matrix.h:50</div></div>
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<div class="ttc" id="layout_2matrix_8h_html"><div class="ttname"><a href="layout_2matrix_8h.html">matrix.h</a></div><div class="ttdoc">Defines layout functions used by TensorRef and derived classes. </div></div>
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<div class="ttc" id="structcutlass_1_1arch_1_1Mma_html"><div class="ttname"><a href="structcutlass_1_1arch_1_1Mma.html">cutlass::arch::Mma</a></div><div class="ttdoc">Matrix multiply-add operation. </div><div class="ttdef"><b>Definition:</b> arch/mma.h:92</div></div>
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<div class="ttc" id="structcutlass_1_1arch_1_1Mma_3_01gemm_1_1GemmShape_3_012_00_012_00_011_01_4_00_011_00_01half__t_c07cc6439298fa5486a719e577be2538_html_a37ea44d16dbc07ca46888812caf5773c"><div class="ttname"><a href="structcutlass_1_1arch_1_1Mma_3_01gemm_1_1GemmShape_3_012_00_012_00_011_01_4_00_011_00_01half__t_c07cc6439298fa5486a719e577be2538.html#a37ea44d16dbc07ca46888812caf5773c">cutlass::arch::Mma< gemm::GemmShape< 2, 2, 1 >, 1, half_t, layout::ColumnMajor, half_t, layout::RowMajor, half_t, layout::RowMajor, OpMultiplyAdd >::operator()</a></div><div class="ttdeci">CUTLASS_HOST_DEVICE void operator()(Array< half_t, 4 > &d, Array< half_t, 2 > const &a, Array< half_t, 2 > const &b, Array< half_t, 4 > const &c)</div><div class="ttdef"><b>Definition:</b> arch/mma_sm60.h:201</div></div>
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