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<a href="mma__tensor__op_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="l00030"></a><span class="lineno"> 30</span> <span class="preprocessor">#pragma once</span></div><div class="line"><a name="l00031"></a><span class="lineno"> 31</span> </div><div class="line"><a name="l00032"></a><span class="lineno"> 32</span> <span class="preprocessor">#include "<a class="code" href="cutlass_8h.html">cutlass/cutlass.h</a>"</span></div><div class="line"><a name="l00033"></a><span class="lineno"> 33</span> <span class="preprocessor">#include "<a class="code" href="array_8h.html">cutlass/array.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="numeric__types_8h.html">cutlass/numeric_types.h</a>"</span></div><div class="line"><a name="l00036"></a><span class="lineno"> 36</span> <span class="preprocessor">#include "<a class="code" href="matrix__shape_8h.html">cutlass/matrix_shape.h</a>"</span></div><div class="line"><a name="l00037"></a><span class="lineno"> 37</span> </div><div class="line"><a name="l00038"></a><span class="lineno"> 38</span> <span class="preprocessor">#include "<a class="code" href="memory__sm75_8h.html">cutlass/arch/memory_sm75.h</a>"</span></div><div class="line"><a name="l00039"></a><span class="lineno"> 39</span> <span class="preprocessor">#include "<a class="code" href="mma__sm75_8h.html">cutlass/arch/mma_sm75.h</a>"</span> </div><div class="line"><a name="l00040"></a><span class="lineno"> 40</span> <span class="preprocessor">#include "<a class="code" href="include_2cutlass_2gemm_2gemm_8h.html">cutlass/gemm/gemm.h</a>"</span></div><div class="line"><a name="l00041"></a><span class="lineno"> 41</span> <span class="preprocessor">#include "<a class="code" href="gemm_2warp_2mma_8h.html">cutlass/gemm/warp/mma.h</a>"</span></div><div class="line"><a name="l00042"></a><span class="lineno"> 42</span> </div><div class="line"><a name="l00043"></a><span class="lineno"> 43</span> <span class="preprocessor">#include "<a class="code" href="mma__tensor__op__policy_8h.html">cutlass/gemm/warp/mma_tensor_op_policy.h</a>"</span></div><div class="line"><a name="l00044"></a><span class="lineno"> 44</span> </div><div class="line"><a name="l00045"></a><span class="lineno"> 45</span> <span class="preprocessor">#include "<a class="code" href="mma__tensor__op__tile__iterator_8h.html">cutlass/gemm/warp/mma_tensor_op_tile_iterator.h</a>"</span></div><div class="line"><a name="l00047"></a><span class="lineno"> 47</span> </div><div class="line"><a name="l00048"></a><span class="lineno"> 48</span> <span class="keyword">namespace </span><a class="code" href="namespacecutlass.html">cutlass</a> {</div><div class="line"><a name="l00049"></a><span class="lineno"> 49</span> <span class="keyword">namespace </span>gemm {</div><div class="line"><a name="l00050"></a><span class="lineno"> 50</span> <span class="keyword">namespace </span>warp {</div><div class="line"><a name="l00051"></a><span class="lineno"> 51</span> </div><div class="line"><a name="l00053"></a><span class="lineno"> 53</span> </div><div class="line"><a name="l00055"></a><span class="lineno"> 55</span> <span class="keyword">template</span> <</div><div class="line"><a name="l00057"></a><span class="lineno"> 57</span>  <span class="keyword">typename</span> Shape_,</div><div class="line"><a name="l00059"></a><span class="lineno"> 59</span>  <span class="keyword">typename</span> ElementA_,</div><div class="line"><a name="l00061"></a><span class="lineno"> 61</span>  <span class="keyword">typename</span> LayoutA_,</div><div class="line"><a name="l00063"></a><span class="lineno"> 63</span>  <span class="keyword">typename</span> ElementB_,</div><div class="line"><a name="l00065"></a><span class="lineno"> 65</span>  <span class="keyword">typename</span> LayoutB_,</div><div class="line"><a name="l00067"></a><span class="lineno"> 67</span>  <span class="keyword">typename</span> ElementC_,</div><div class="line"><a name="l00069"></a><span class="lineno"> 69</span>  <span class="keyword">typename</span> LayoutC_,</div><div class="line"><a name="l00071"></a><span class="lineno"> 71</span>  <span class="keyword">typename</span> Policy_,</div><div class="line"><a name="l00073"></a><span class="lineno"> 73</span>  <span class="keywordtype">int</span> PartitionsK_ = 1,</div><div class="line"><a name="l00076"></a><span class="lineno"> 76</span>  <span class="keywordtype">bool</span> AccumulatorsInRowMajor = <span class="keyword">false</span>,</div><div class="line"><a name="l00078"></a><span class="lineno"> 78</span>  <span class="keywordtype">int</span> PartitionsN_ = 1,</div><div class="line"><a name="l00080"></a><span class="lineno"> 80</span>  <span class="keyword">typename</span> Enable = <span class="keywordtype">bool</span></div><div class="line"><a name="l00081"></a><span class="lineno"> 81</span> ></div><div class="line"><a name="l00082"></a><span class="lineno"><a class="line" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOp.html"> 82</a></span> <span class="keyword">class </span><a class="code" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOp.html">MmaTensorOp</a> {</div><div class="line"><a name="l00083"></a><span class="lineno"> 83</span> <span class="keyword">public</span>:</div><div class="line"><a name="l00085"></a><span class="lineno"><a class="line" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOp.html#ac876fbcde91b3cd490432e7c8002bc60"> 85</a></span>  <span class="keyword">using</span> <a class="code" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOp.html#ac876fbcde91b3cd490432e7c8002bc60">Shape</a> = Shape_;</div><div class="line"><a name="l00086"></a><span class="lineno"> 86</span> </div><div class="line"><a name="l00088"></a><span class="lineno"><a class="line" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOp.html#aacab39db92cb1e6c081d4475a7984c8f"> 88</a></span>  <span class="keyword">using</span> <a class="code" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOp.html#aacab39db92cb1e6c081d4475a7984c8f">ElementA</a> = ElementA_;</div><div class="line"><a name="l00089"></a><span class="lineno"> 89</span> </div><div class="line"><a name="l00091"></a><span class="lineno"><a class="line" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOp.html#a8ea4f03edb1809d4a2a07c05f22b8398"> 91</a></span>  <span class="keyword">using</span> <a class="code" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOp.html#a8ea4f03edb1809d4a2a07c05f22b8398">LayoutA</a> = LayoutA_;</div><div class="line"><a name="l00092"></a><span class="lineno"> 92</span> </div><div class="line"><a name="l00094"></a><span class="lineno"><a class="line" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOp.html#a5b4f3c2bc511330a4e41078bf08b430c"> 94</a></span>  <span class="keyword">using</span> <a class="code" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOp.html#a5b4f3c2bc511330a4e41078bf08b430c">ElementB</a> = ElementB_;</div><div class="line"><a name="l00095"></a><span class="lineno"> 95</span> </div><div class="line"><a name="l00097"></a><span class="lineno"><a class="line" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOp.html#af94b734ca46b1e68a273b35f49155e16"> 97</a></span>  <span class="keyword">using</span> <a class="code" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOp.html#af94b734ca46b1e68a273b35f49155e16">LayoutB</a> = LayoutB_;</div><div class="line"><a name="l00098"></a><span class="lineno"> 98</span> </div><div class="line"><a name="l00100"></a><span class="lineno"><a class="line" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOp.html#a48cc72d8223f19a7c8995e845124025d"> 100</a></span>  <span class="keyword">using</span> <a class="code" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOp.html#a48cc72d8223f19a7c8995e845124025d">ElementC</a> = ElementC_;</div><div class="line"><a name="l00101"></a><span class="lineno"> 101</span> </div><div class="line"><a name="l00103"></a><span class="lineno"><a class="line" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOp.html#a77dea454b02646c21c7e9d3f340b9bdb"> 103</a></span>  <span class="keyword">using</span> <a class="code" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOp.html#a77dea454b02646c21c7e9d3f340b9bdb">LayoutC</a> = LayoutC_;</div><div class="line"><a name="l00104"></a><span class="lineno"> 104</span> </div><div class="line"><a name="l00106"></a><span class="lineno"><a class="line" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOp.html#aca53ae2c2f98f6b1e735b332904aa9aa"> 106</a></span>  <span class="keyword">using</span> <a class="code" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOp.html#aca53ae2c2f98f6b1e735b332904aa9aa">Policy</a> = Policy_;</div><div class="line"><a name="l00107"></a><span class="lineno"> 107</span> </div><div class="line"><a name="l00109"></a><span class="lineno"><a class="line" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOp.html#a2663baf282d4a7e9549cd52ffbf3cc02"> 109</a></span>  <span class="keyword">using</span> <a class="code" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOp.html#a2663baf282d4a7e9549cd52ffbf3cc02">OperatorClass</a> = arch::OpClassTensorOp;</div><div class="line"><a name="l00110"></a><span class="lineno"> 110</span> </div><div class="line"><a name="l00112"></a><span class="lineno"><a class="line" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOp.html#a51960b3e3cdde83bc7321b1607b78302"> 112</a></span>  <span class="keyword">static</span> <span class="keywordtype">int</span> <span class="keyword">const</span> <a class="code" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOp.html#a51960b3e3cdde83bc7321b1607b78302">kThreadCount</a> = 32;</div><div class="line"><a name="l00113"></a><span class="lineno"> 113</span> </div><div class="line"><a name="l00115"></a><span class="lineno"><a class="line" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOp.html#a9e73c525ef6835bd6500f714166a7c43"> 115</a></span>  <span class="keyword">static</span> <span class="keywordtype">int</span> <span class="keyword">const</span> <a class="code" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOp.html#a9e73c525ef6835bd6500f714166a7c43">kPartitionsK</a> = PartitionsK_;</div><div class="line"><a name="l00116"></a><span class="lineno"> 116</span> </div><div class="line"><a name="l00118"></a><span class="lineno"><a class="line" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOp.html#ac47c26a237de7990a53df77a4535141b"> 118</a></span>  <span class="keyword">static</span> <span class="keywordtype">int</span> <span class="keyword">const</span> <a class="code" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOp.html#ac47c26a237de7990a53df77a4535141b">kPartitionsN</a> = PartitionsN_;</div><div class="line"><a name="l00119"></a><span class="lineno"> 119</span> </div><div class="line"><a name="l00120"></a><span class="lineno"> 120</span> <span class="keyword">public</span>:</div><div class="line"><a name="l00121"></a><span class="lineno"> 121</span> </div><div class="line"><a name="l00123"></a><span class="lineno"> 123</span>  <span class="keyword">using</span> <a class="code" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator.html">IteratorA</a> = <a class="code" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator.html">MmaTensorOpMultiplicandTileIterator</a><</div><div class="line"><a name="l00124"></a><span class="lineno"> 124</span>  <a class="code" href="structcutlass_1_1MatrixShape.html">MatrixShape<Shape::kM, Shape::kK></a>, <a class="code" href="namespacecutlass_1_1gemm.html#a34338284023da7403c9ecbd3f406b2a6a30f767aa191cd5d261e767fd78393607">Operand::kA</a>, <a class="code" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOp.html#aacab39db92cb1e6c081d4475a7984c8f">ElementA</a>, <a class="code" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOp.html#a8ea4f03edb1809d4a2a07c05f22b8398">LayoutA</a>,</div><div class="line"><a name="l00125"></a><span class="lineno"> 125</span>  <a class="code" href="structcutlass_1_1MatrixShape.html">MatrixShape<Policy::Operator::Shape::kM, Policy::Operator::Shape::kK></a>,</div><div class="line"><a name="l00126"></a><span class="lineno"><a class="line" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOp.html#a794384bbf37bce5504232a862dd1e089"> 126</a></span>  Policy::OpDelta::kRow, <a class="code" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOp.html#a51960b3e3cdde83bc7321b1607b78302">kThreadCount</a>, kPartitionsK>;</div><div class="line"><a name="l00127"></a><span class="lineno"> 127</span> </div><div class="line"><a name="l00129"></a><span class="lineno"><a class="line" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOp.html#ae7958be3c77c61ee500688bba2195b1a"> 129</a></span>  <span class="keyword">using</span> <a class="code" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOp.html#ae7958be3c77c61ee500688bba2195b1a">FragmentA</a> = <span class="keyword">typename</span> IteratorA::Fragment;</div><div class="line"><a name="l00130"></a><span class="lineno"> 130</span> </div><div class="line"><a name="l00132"></a><span class="lineno"> 132</span>  <span class="keyword">using</span> <a class="code" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator.html">IteratorB</a> = <a class="code" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator.html">MmaTensorOpMultiplicandTileIterator</a><</div><div class="line"><a name="l00133"></a><span class="lineno"> 133</span>  <a class="code" href="structcutlass_1_1MatrixShape.html">MatrixShape<Shape::kK, Shape::kN></a>, <a class="code" href="namespacecutlass_1_1gemm.html#a34338284023da7403c9ecbd3f406b2a6a3e56c011b37f0bc78fb9eb175c1181c6">Operand::kB</a>, <a class="code" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOp.html#a5b4f3c2bc511330a4e41078bf08b430c">ElementB</a>, <a class="code" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOp.html#af94b734ca46b1e68a273b35f49155e16">LayoutB</a>,</div><div class="line"><a name="l00134"></a><span class="lineno"> 134</span>  <a class="code" href="structcutlass_1_1MatrixShape.html">MatrixShape<Policy::Operator::Shape::kK, Policy::Operator::Shape::kN></a>,</div><div class="line"><a name="l00135"></a><span class="lineno"><a class="line" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOp.html#a83f46087d7f39e4e039e74cbb79e3b89"> 135</a></span>  Policy::OpDelta::kRow, <a class="code" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOp.html#a51960b3e3cdde83bc7321b1607b78302">kThreadCount</a>, kPartitionsK>;</div><div class="line"><a name="l00136"></a><span class="lineno"> 136</span> </div><div class="line"><a name="l00138"></a><span class="lineno"><a class="line" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOp.html#a268f27ae31f2e1a4e8a2e734ec1c1816"> 138</a></span>  <span class="keyword">using</span> <a class="code" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOp.html#a268f27ae31f2e1a4e8a2e734ec1c1816">FragmentB</a> = <span class="keyword">typename</span> IteratorB::Fragment;</div><div class="line"><a name="l00139"></a><span class="lineno"> 139</span> </div><div class="line"><a name="l00141"></a><span class="lineno"> 141</span>  <span class="keyword">using</span> <a class="code" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpAccumulatorTileIterator.html">IteratorC</a> = <a class="code" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpAccumulatorTileIterator.html">MmaTensorOpAccumulatorTileIterator</a><</div><div class="line"><a name="l00142"></a><span class="lineno"> 142</span>  <a class="code" href="structcutlass_1_1MatrixShape.html">MatrixShape<Shape::kM, Shape::kN></a>, <a class="code" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOp.html#a48cc72d8223f19a7c8995e845124025d">ElementC</a>, <a class="code" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOp.html#a77dea454b02646c21c7e9d3f340b9bdb">LayoutC</a>,</div><div class="line"><a name="l00143"></a><span class="lineno"><a class="line" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOp.html#a40ea7a332afaa4e6476020a7357ed541"> 143</a></span>  <span class="keyword">typename</span> Policy::Operator::Shape, <span class="keyword">typename</span> Policy::OpDelta>;</div><div class="line"><a name="l00144"></a><span class="lineno"> 144</span> </div><div class="line"><a name="l00146"></a><span class="lineno"><a class="line" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOp.html#ae03fe3d58f3d96e875055e7721548bab"> 146</a></span>  <span class="keyword">using</span> <a class="code" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOp.html#ae03fe3d58f3d96e875055e7721548bab">FragmentC</a> = <span class="keyword">typename</span> IteratorC::Fragment;</div><div class="line"><a name="l00147"></a><span class="lineno"> 147</span> </div><div class="line"><a name="l00148"></a><span class="lineno"> 148</span> <span class="keyword">private</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>  <a class="code" href="platform_8h.html#adde4c9ea91b753491851361a4198c009">static_assert</a>(</div><div class="line"><a name="l00151"></a><span class="lineno"> 151</span>  !(Shape::kM % Policy::Operator::Shape::kM) && </div><div class="line"><a name="l00152"></a><span class="lineno"> 152</span>  !(Shape::kN % Policy::Operator::Shape::kN),</div><div class="line"><a name="l00153"></a><span class="lineno"> 153</span>  <span class="stringliteral">"Shape of warp-level Mma must be divisible by operator shape."</span>);</div><div class="line"><a name="l00154"></a><span class="lineno"> 154</span> </div><div class="line"><a name="l00156"></a><span class="lineno"> 156</span>  <span class="keyword">using</span> MmaIterations = <a class="code" href="structcutlass_1_1MatrixShape.html">MatrixShape</a><</div><div class="line"><a name="l00157"></a><span class="lineno"> 157</span>  Shape::kM / Policy::Operator::Shape::kM,</div><div class="line"><a name="l00158"></a><span class="lineno"> 158</span>  (Shape::kN / Policy::Operator::Shape::kN / kPartitionsN > 0) ?</div><div class="line"><a name="l00159"></a><span class="lineno"> 159</span>  Shape::kN / Policy::Operator::Shape::kN / kPartitionsN :</div><div class="line"><a name="l00160"></a><span class="lineno"> 160</span>  1</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> </div><div class="line"><a name="l00163"></a><span class="lineno"> 163</span> <span class="keyword">public</span>:</div><div class="line"><a name="l00164"></a><span class="lineno"> 164</span> </div><div class="line"><a name="l00166"></a><span class="lineno"><a class="line" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOp.html#a2eddba2b1644d2df5ade4de535b95ed7"> 166</a></span>  <span class="keyword">typename</span> Policy::Operator <a class="code" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOp.html#a2eddba2b1644d2df5ade4de535b95ed7">mma</a>;</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> <span class="keyword">public</span>:</div><div class="line"><a name="l00169"></a><span class="lineno"> 169</span> </div><div class="line"><a name="l00170"></a><span class="lineno"> 170</span>  <span class="comment">//</span></div><div class="line"><a name="l00171"></a><span class="lineno"> 171</span>  <span class="comment">// Methods</span></div><div class="line"><a name="l00172"></a><span class="lineno"> 172</span>  <span class="comment">//</span></div><div class="line"><a name="l00173"></a><span class="lineno"> 173</span> </div><div class="line"><a name="l00175"></a><span class="lineno"> 175</span>  CUTLASS_DEVICE</div><div class="line"><a name="l00176"></a><span class="lineno"><a class="line" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOp.html#ae344dbb59b9234254768238bee17f2d7"> 176</a></span>  <a class="code" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOp.html#ae344dbb59b9234254768238bee17f2d7">MmaTensorOp</a>() {}</div><div class="line"><a name="l00177"></a><span class="lineno"> 177</span> </div><div class="line"><a name="l00179"></a><span class="lineno"> 179</span>  CUTLASS_DEVICE</div><div class="line"><a name="l00180"></a><span class="lineno"><a class="line" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOp.html#ac7b9462528c81aa23995760c8c104f47"> 180</a></span>  <span class="keywordtype">void</span> <a class="code" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOp.html#ac7b9462528c81aa23995760c8c104f47">operator()</a>(</div><div class="line"><a name="l00181"></a><span class="lineno"> 181</span>  <a class="code" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOp.html#ae03fe3d58f3d96e875055e7721548bab">FragmentC</a> &D, </div><div class="line"><a name="l00182"></a><span class="lineno"> 182</span>  <a class="code" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOp.html#ae7958be3c77c61ee500688bba2195b1a">FragmentA</a> <span class="keyword">const</span> &A, </div><div class="line"><a name="l00183"></a><span class="lineno"> 183</span>  <a class="code" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOp.html#a268f27ae31f2e1a4e8a2e734ec1c1816">FragmentB</a> <span class="keyword">const</span> &B, </div><div class="line"><a name="l00184"></a><span class="lineno"> 184</span>  <a class="code" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOp.html#ae03fe3d58f3d96e875055e7721548bab">FragmentC</a> <span class="keyword">const</span> &C,</div><div class="line"><a name="l00185"></a><span class="lineno"> 185</span>  <span class="keywordtype">int</span> <span class="keyword">const</span> &partitionN_idx = 0)<span class="keyword"> const </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>  <span class="keyword">using</span> MmaOperandA = <span class="keyword">typename</span> Policy::Operator::FragmentA;</div><div class="line"><a name="l00188"></a><span class="lineno"> 188</span>  <span class="keyword">using</span> MmaOperandB = <span class="keyword">typename</span> Policy::Operator::FragmentB;</div><div class="line"><a name="l00189"></a><span class="lineno"> 189</span>  <span class="keyword">using</span> MmaOperandC = <span class="keyword">typename</span> Policy::Operator::FragmentC;</div><div class="line"><a name="l00190"></a><span class="lineno"> 190</span> </div><div class="line"><a name="l00191"></a><span class="lineno"> 191</span>  D = C;</div><div class="line"><a name="l00192"></a><span class="lineno"> 192</span> </div><div class="line"><a name="l00193"></a><span class="lineno"> 193</span>  MmaOperandA <span class="keyword">const</span> *ptr_A = <span class="keyword">reinterpret_cast<</span>MmaOperandA <span class="keyword">const </span>*<span class="keyword">></span>(&A);</div><div class="line"><a name="l00194"></a><span class="lineno"> 194</span>  MmaOperandB <span class="keyword">const</span> *ptr_B = <span class="keyword">reinterpret_cast<</span>MmaOperandB <span class="keyword">const </span>*<span class="keyword">></span>(&B);</div><div class="line"><a name="l00195"></a><span class="lineno"> 195</span>  MmaOperandC *ptr_D = <span class="keyword">reinterpret_cast<</span>MmaOperandC *<span class="keyword">></span>(&D);</div><div class="line"><a name="l00196"></a><span class="lineno"> 196</span> </div><div class="line"><a name="l00197"></a><span class="lineno"> 197</span>  <span class="comment">// The offset of multilicand B for current partition</span></div><div class="line"><a name="l00198"></a><span class="lineno"> 198</span>  <span class="keyword">const</span> <span class="keywordtype">int</span> n_off = partitionN_idx * FragmentB::kElements / MmaOperandB::kElements / <a class="code" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOp.html#ac47c26a237de7990a53df77a4535141b">kPartitionsN</a>;</div><div class="line"><a name="l00199"></a><span class="lineno"> 199</span>  <span class="comment">// Serpentine visitation order maximizing reuse of Rb</span></div><div class="line"><a name="l00200"></a><span class="lineno"> 200</span>  <a class="code" href="cutlass_8h.html#a4b1c9f25ab6eaa25e1f2258dd63e6ce4">CUTLASS_PRAGMA_UNROLL</a></div><div class="line"><a name="l00201"></a><span class="lineno"> 201</span>  <span class="keywordflow">for</span> (<span class="keywordtype">int</span> n = 0; n < MmaIterations::kColumn; ++n) {</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>  <a class="code" href="cutlass_8h.html#a4b1c9f25ab6eaa25e1f2258dd63e6ce4">CUTLASS_PRAGMA_UNROLL</a></div><div class="line"><a name="l00204"></a><span class="lineno"> 204</span>  <span class="keywordflow">for</span> (<span class="keywordtype">int</span> m = 0; m < MmaIterations::kRow; ++m) {</div><div class="line"><a name="l00205"></a><span class="lineno"> 205</span> </div><div class="line"><a name="l00206"></a><span class="lineno"> 206</span>  <span class="keywordtype">int</span> m_serpentine = ((n % 2) ? (MmaIterations::kRow - 1 - m) : m);</div><div class="line"><a name="l00207"></a><span class="lineno"> 207</span> </div><div class="line"><a name="l00208"></a><span class="lineno"> 208</span>  <span class="keywordflow">if</span> (AccumulatorsInRowMajor) { <span class="comment">// matrix B is reordered</span></div><div class="line"><a name="l00209"></a><span class="lineno"> 209</span>  <a class="code" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOp.html#a2eddba2b1644d2df5ade4de535b95ed7">mma</a>(</div><div class="line"><a name="l00210"></a><span class="lineno"> 210</span>  ptr_D[n + m_serpentine * MmaIterations::kColumn],</div><div class="line"><a name="l00211"></a><span class="lineno"> 211</span>  ptr_A[m_serpentine],</div><div class="line"><a name="l00212"></a><span class="lineno"> 212</span>  ptr_B[n],</div><div class="line"><a name="l00213"></a><span class="lineno"> 213</span>  ptr_D[n + m_serpentine * MmaIterations::kColumn]);</div><div class="line"><a name="l00214"></a><span class="lineno"> 214</span>  } <span class="keywordflow">else</span> {</div><div class="line"><a name="l00215"></a><span class="lineno"> 215</span>  <a class="code" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOp.html#a2eddba2b1644d2df5ade4de535b95ed7">mma</a>(</div><div class="line"><a name="l00216"></a><span class="lineno"> 216</span>  ptr_D[m_serpentine + (n + n_off) * MmaIterations::kRow],</div><div class="line"><a name="l00217"></a><span class="lineno"> 217</span>  ptr_A[m_serpentine],</div><div class="line"><a name="l00218"></a><span class="lineno"> 218</span>  ptr_B[n + n_off],</div><div class="line"><a name="l00219"></a><span class="lineno"> 219</span>  ptr_D[m_serpentine + (n + n_off) * MmaIterations::kRow]);</div><div class="line"><a name="l00220"></a><span class="lineno"> 220</span>  }</div><div class="line"><a name="l00221"></a><span class="lineno"> 221</span>  }</div><div class="line"><a name="l00222"></a><span class="lineno"> 222</span>  }</div><div class="line"><a name="l00223"></a><span class="lineno"> 223</span>  }</div><div class="line"><a name="l00224"></a><span class="lineno"> 224</span> };</div><div class="line"><a name="l00225"></a><span class="lineno"> 225</span> </div><div class="line"><a name="l00227"></a><span class="lineno"> 227</span> </div><div class="line"><a name="l00228"></a><span class="lineno"> 228</span> } <span class="comment">// namespace warp</span></div><div class="line"><a name="l00229"></a><span class="lineno"> 229</span> } <span class="comment">// namespace gemm</span></div><div class="line"><a name="l00230"></a><span class="lineno"> 230</span> } <span class="comment">// namespace cutlass</span></div><div class="ttc" id="structcutlass_1_1MatrixShape_html"><div class="ttname"><a href="structcutlass_1_1MatrixShape.html">cutlass::MatrixShape</a></div><div class="ttdoc">Describes the size of a matrix tile. </div><div class="ttdef"><b>Definition:</b> matrix_shape.h:42</div></div>
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<div class="ttc" id="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOp_html_ae7958be3c77c61ee500688bba2195b1a"><div class="ttname"><a href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOp.html#ae7958be3c77c61ee500688bba2195b1a">cutlass::gemm::warp::MmaTensorOp::FragmentA</a></div><div class="ttdeci">typename IteratorA::Fragment FragmentA</div><div class="ttdoc">Storage for A tile. </div><div class="ttdef"><b>Definition:</b> mma_tensor_op.h:129</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="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOp_html_af94b734ca46b1e68a273b35f49155e16"><div class="ttname"><a href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOp.html#af94b734ca46b1e68a273b35f49155e16">cutlass::gemm::warp::MmaTensorOp::LayoutB</a></div><div class="ttdeci">LayoutB_ LayoutB</div><div class="ttdoc">Layout of multiplicand B. </div><div class="ttdef"><b>Definition:</b> mma_tensor_op.h:97</div></div>
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<div class="ttc" id="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOp_html_ae344dbb59b9234254768238bee17f2d7"><div class="ttname"><a href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOp.html#ae344dbb59b9234254768238bee17f2d7">cutlass::gemm::warp::MmaTensorOp::MmaTensorOp</a></div><div class="ttdeci">CUTLASS_DEVICE MmaTensorOp()</div><div class="ttdoc">Ctor. </div><div class="ttdef"><b>Definition:</b> mma_tensor_op.h:176</div></div>
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<div class="ttc" id="memory__sm75_8h_html"><div class="ttname"><a href="memory__sm75_8h.html">memory_sm75.h</a></div><div class="ttdoc">Architecture-specific operators on memory added for SM75. </div></div>
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<div class="ttc" id="mma__tensor__op__tile__iterator_8h_html"><div class="ttname"><a href="mma__tensor__op__tile__iterator_8h.html">mma_tensor_op_tile_iterator.h</a></div><div class="ttdoc">Defines iterators used by warp-level matrix multiply operations targeting Tensor Cores. </div></div>
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<div class="ttc" id="include_2cutlass_2gemm_2gemm_8h_html"><div class="ttname"><a href="include_2cutlass_2gemm_2gemm_8h.html">gemm.h</a></div><div class="ttdoc">Defines common types used for all GEMM-like operators. </div></div>
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<div class="ttc" id="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOp_html_a51960b3e3cdde83bc7321b1607b78302"><div class="ttname"><a href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOp.html#a51960b3e3cdde83bc7321b1607b78302">cutlass::gemm::warp::MmaTensorOp::kThreadCount</a></div><div class="ttdeci">static int const kThreadCount</div><div class="ttdoc">Number of threads participating in warp-level matrix product. </div><div class="ttdef"><b>Definition:</b> mma_tensor_op.h:112</div></div>
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<div class="ttc" id="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOp_html_ac47c26a237de7990a53df77a4535141b"><div class="ttname"><a href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOp.html#ac47c26a237de7990a53df77a4535141b">cutlass::gemm::warp::MmaTensorOp::kPartitionsN</a></div><div class="ttdeci">static int const kPartitionsN</div><div class="ttdoc">PartitionsN indicating how many PartitionsN for multiplicand B. </div><div class="ttdef"><b>Definition:</b> mma_tensor_op.h:118</div></div>
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<div class="ttc" id="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOp_html"><div class="ttname"><a href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOp.html">cutlass::gemm::warp::MmaTensorOp</a></div><div class="ttdoc">Structure to compute the matrix product targeting CUDA cores and SIMT math instructions. </div><div class="ttdef"><b>Definition:</b> mma_tensor_op.h:82</div></div>
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<div class="ttc" id="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOp_html_a8ea4f03edb1809d4a2a07c05f22b8398"><div class="ttname"><a href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOp.html#a8ea4f03edb1809d4a2a07c05f22b8398">cutlass::gemm::warp::MmaTensorOp::LayoutA</a></div><div class="ttdeci">LayoutA_ LayoutA</div><div class="ttdoc">Layout of multiplicand A. </div><div class="ttdef"><b>Definition:</b> mma_tensor_op.h:91</div></div>
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<div class="ttc" id="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOp_html_a268f27ae31f2e1a4e8a2e734ec1c1816"><div class="ttname"><a href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOp.html#a268f27ae31f2e1a4e8a2e734ec1c1816">cutlass::gemm::warp::MmaTensorOp::FragmentB</a></div><div class="ttdeci">typename IteratorB::Fragment FragmentB</div><div class="ttdoc">Storage for B tile. </div><div class="ttdef"><b>Definition:</b> mma_tensor_op.h:138</div></div>
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<div class="ttc" id="array_8h_html"><div class="ttname"><a href="array_8h.html">array.h</a></div><div class="ttdoc">Statically sized array of elements that accommodates all CUTLASS-supported numeric types and is safe ...</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="gemm_2warp_2mma_8h_html"><div class="ttname"><a href="gemm_2warp_2mma_8h.html">mma.h</a></div><div class="ttdoc">Templates exposing architecture support for warp-level multiply-add operations. </div></div>
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<div class="ttc" id="namespacecutlass_1_1gemm_html_a34338284023da7403c9ecbd3f406b2a6a30f767aa191cd5d261e767fd78393607"><div class="ttname"><a href="namespacecutlass_1_1gemm.html#a34338284023da7403c9ecbd3f406b2a6a30f767aa191cd5d261e767fd78393607">cutlass::gemm::Operand::kA</a></div></div>
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<div class="ttc" id="matrix__shape_8h_html"><div class="ttname"><a href="matrix__shape_8h.html">matrix_shape.h</a></div><div class="ttdoc">Defines a Shape template for matrix tiles. </div></div>
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<div class="ttc" id="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOp_html_ae03fe3d58f3d96e875055e7721548bab"><div class="ttname"><a href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOp.html#ae03fe3d58f3d96e875055e7721548bab">cutlass::gemm::warp::MmaTensorOp::FragmentC</a></div><div class="ttdeci">typename IteratorC::Fragment FragmentC</div><div class="ttdoc">Storage for C tile. </div><div class="ttdef"><b>Definition:</b> mma_tensor_op.h:146</div></div>
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<div class="ttc" id="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpAccumulatorTileIterator_html"><div class="ttname"><a href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpAccumulatorTileIterator.html">cutlass::gemm::warp::MmaTensorOpAccumulatorTileIterator</a></div><div class="ttdef"><b>Definition:</b> mma_tensor_op_tile_iterator.h:1794</div></div>
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<div class="ttc" id="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOp_html_ac7b9462528c81aa23995760c8c104f47"><div class="ttname"><a href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOp.html#ac7b9462528c81aa23995760c8c104f47">cutlass::gemm::warp::MmaTensorOp::operator()</a></div><div class="ttdeci">CUTLASS_DEVICE void operator()(FragmentC &D, FragmentA const &A, FragmentB const &B, FragmentC const &C, int const &partitionN_idx=0) const </div><div class="ttdoc">Performs a warp-level matrix multiply-accumulate operation. </div><div class="ttdef"><b>Definition:</b> mma_tensor_op.h:180</div></div>
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<div class="ttc" id="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOp_html_a2eddba2b1644d2df5ade4de535b95ed7"><div class="ttname"><a href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOp.html#a2eddba2b1644d2df5ade4de535b95ed7">cutlass::gemm::warp::MmaTensorOp::mma</a></div><div class="ttdeci">Policy::Operator mma</div><div class="ttdoc">Underlying matrix multiply operator (concept: arch::Mma) </div><div class="ttdef"><b>Definition:</b> mma_tensor_op.h:166</div></div>
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<div class="ttc" id="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOp_html_a48cc72d8223f19a7c8995e845124025d"><div class="ttname"><a href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOp.html#a48cc72d8223f19a7c8995e845124025d">cutlass::gemm::warp::MmaTensorOp::ElementC</a></div><div class="ttdeci">ElementC_ ElementC</div><div class="ttdoc">Data type of accumulator matrix C. </div><div class="ttdef"><b>Definition:</b> mma_tensor_op.h:100</div></div>
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<div class="ttc" id="numeric__types_8h_html"><div class="ttname"><a href="numeric__types_8h.html">numeric_types.h</a></div><div class="ttdoc">Top-level include for all CUTLASS numeric types. </div></div>
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<div class="ttc" id="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_html"><div class="ttname"><a href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator.html">cutlass::gemm::warp::MmaTensorOpMultiplicandTileIterator</a></div><div class="ttdef"><b>Definition:</b> mma_tensor_op_tile_iterator.h:75</div></div>
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<div class="ttc" id="platform_8h_html_adde4c9ea91b753491851361a4198c009"><div class="ttname"><a href="platform_8h.html#adde4c9ea91b753491851361a4198c009">static_assert</a></div><div class="ttdeci">#define static_assert(__e, __m)</div><div class="ttdef"><b>Definition:</b> platform.h:153</div></div>
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<div class="ttc" id="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOp_html_a77dea454b02646c21c7e9d3f340b9bdb"><div class="ttname"><a href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOp.html#a77dea454b02646c21c7e9d3f340b9bdb">cutlass::gemm::warp::MmaTensorOp::LayoutC</a></div><div class="ttdeci">LayoutC_ LayoutC</div><div class="ttdoc">Layout of accumulator matrix C. </div><div class="ttdef"><b>Definition:</b> mma_tensor_op.h:103</div></div>
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<div class="ttc" id="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOp_html_aca53ae2c2f98f6b1e735b332904aa9aa"><div class="ttname"><a href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOp.html#aca53ae2c2f98f6b1e735b332904aa9aa">cutlass::gemm::warp::MmaTensorOp::Policy</a></div><div class="ttdeci">Policy_ Policy</div><div class="ttdoc">Shape of the warp in units of thread (concept: MmaLanePolicySimt) </div><div class="ttdef"><b>Definition:</b> mma_tensor_op.h:106</div></div>
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<div class="ttc" id="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOp_html_ac876fbcde91b3cd490432e7c8002bc60"><div class="ttname"><a href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOp.html#ac876fbcde91b3cd490432e7c8002bc60">cutlass::gemm::warp::MmaTensorOp::Shape</a></div><div class="ttdeci">Shape_ Shape</div><div class="ttdoc">Shape of warp-level matrix operation (concept: GemmShape) </div><div class="ttdef"><b>Definition:</b> mma_tensor_op.h:85</div></div>
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<div class="ttc" id="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOp_html_a5b4f3c2bc511330a4e41078bf08b430c"><div class="ttname"><a href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOp.html#a5b4f3c2bc511330a4e41078bf08b430c">cutlass::gemm::warp::MmaTensorOp::ElementB</a></div><div class="ttdeci">ElementB_ ElementB</div><div class="ttdoc">Data type of multiplicand B. </div><div class="ttdef"><b>Definition:</b> mma_tensor_op.h:94</div></div>
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<div class="ttc" id="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOp_html_a9e73c525ef6835bd6500f714166a7c43"><div class="ttname"><a href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOp.html#a9e73c525ef6835bd6500f714166a7c43">cutlass::gemm::warp::MmaTensorOp::kPartitionsK</a></div><div class="ttdeci">static int const kPartitionsK</div><div class="ttdoc">Number of partitions along K dimension. </div><div class="ttdef"><b>Definition:</b> mma_tensor_op.h:115</div></div>
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<div class="ttc" id="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOp_html_a2663baf282d4a7e9549cd52ffbf3cc02"><div class="ttname"><a href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOp.html#a2663baf282d4a7e9549cd52ffbf3cc02">cutlass::gemm::warp::MmaTensorOp::OperatorClass</a></div><div class="ttdeci">arch::OpClassTensorOp OperatorClass</div><div class="ttdoc">Indicates class of matrix operator. </div><div class="ttdef"><b>Definition:</b> mma_tensor_op.h:109</div></div>
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<div class="ttc" id="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOp_html_aacab39db92cb1e6c081d4475a7984c8f"><div class="ttname"><a href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOp.html#aacab39db92cb1e6c081d4475a7984c8f">cutlass::gemm::warp::MmaTensorOp::ElementA</a></div><div class="ttdeci">ElementA_ ElementA</div><div class="ttdoc">Data type of multiplicand A. </div><div class="ttdef"><b>Definition:</b> mma_tensor_op.h:88</div></div>
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<div class="ttc" id="mma__sm75_8h_html"><div class="ttname"><a href="mma__sm75_8h.html">mma_sm75.h</a></div><div class="ttdoc">Matrix multiply for SM75. </div></div>
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<div class="ttc" id="namespacecutlass_1_1gemm_html_a34338284023da7403c9ecbd3f406b2a6a3e56c011b37f0bc78fb9eb175c1181c6"><div class="ttname"><a href="namespacecutlass_1_1gemm.html#a34338284023da7403c9ecbd3f406b2a6a3e56c011b37f0bc78fb9eb175c1181c6">cutlass::gemm::Operand::kB</a></div><div class="ttdoc">A multiplicand. </div></div>
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<div class="ttc" id="cutlass_8h_html"><div class="ttname"><a href="cutlass_8h.html">cutlass.h</a></div><div class="ttdoc">Basic include for CUTLASS. </div></div>
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<div class="ttc" id="mma__tensor__op__policy_8h_html"><div class="ttname"><a href="mma__tensor__op__policy_8h.html">mma_tensor_op_policy.h</a></div><div class="ttdoc">Policy describing implementation details of warp-level GEMM targeting Tensor Cores. </div></div>
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