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<a href="mma__tensor__op__wmma_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="wmma_8h.html">cutlass/arch/wmma.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">#if defined(CUTLASS_ARCH_WMMA_ENABLED)</span></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="preprocessor">#include "<a class="code" href="wmma__array_8h.html">cutlass/wmma_array.h</a>"</span></div><div class="line"><a name="l00038"></a><span class="lineno"> 38</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="l00039"></a><span class="lineno"> 39</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="l00040"></a><span class="lineno"> 40</span> </div><div class="line"><a name="l00041"></a><span class="lineno"> 41</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="l00042"></a><span class="lineno"> 42</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="l00043"></a><span class="lineno"> 43</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="l00044"></a><span class="lineno"> 44</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="l00045"></a><span class="lineno"> 45</span> </div><div class="line"><a name="l00046"></a><span class="lineno"> 46</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="l00047"></a><span class="lineno"> 47</span> </div><div class="line"><a name="l00048"></a><span class="lineno"> 48</span> <span class="preprocessor">#include "<a class="code" href="mma__tensor__op__tile__iterator__wmma_8h.html">cutlass/gemm/warp/mma_tensor_op_tile_iterator_wmma.h</a>"</span></div><div class="line"><a name="l00049"></a><span class="lineno"> 49</span> </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="keyword">namespace </span><a class="code" href="namespacecutlass.html">cutlass</a> {</div><div class="line"><a name="l00053"></a><span class="lineno"> 53</span> <span class="keyword">namespace </span>gemm {</div><div class="line"><a name="l00054"></a><span class="lineno"> 54</span> <span class="keyword">namespace </span>warp {</div><div class="line"><a name="l00055"></a><span class="lineno"> 55</span> </div><div class="line"><a name="l00057"></a><span class="lineno"> 57</span> </div><div class="line"><a name="l00059"></a><span class="lineno"> 59</span> <span class="keyword">template</span> < </div><div class="line"><a name="l00061"></a><span class="lineno"> 61</span>  <span class="keyword">typename</span> Shape_,</div><div class="line"><a name="l00063"></a><span class="lineno"> 63</span>  <span class="keyword">typename</span> ElementA_,</div><div class="line"><a name="l00065"></a><span class="lineno"> 65</span>  <span class="keyword">typename</span> LayoutA_,</div><div class="line"><a name="l00067"></a><span class="lineno"> 67</span>  <span class="keyword">typename</span> ElementB_,</div><div class="line"><a name="l00069"></a><span class="lineno"> 69</span>  <span class="keyword">typename</span> LayoutB_,</div><div class="line"><a name="l00071"></a><span class="lineno"> 71</span>  <span class="keyword">typename</span> ElementC_,</div><div class="line"><a name="l00073"></a><span class="lineno"> 73</span>  <span class="keyword">typename</span> LayoutC_,</div><div class="line"><a name="l00075"></a><span class="lineno"> 75</span>  <span class="keyword">typename</span> Policy_,</div><div class="line"><a name="l00077"></a><span class="lineno"> 77</span>  <span class="keywordtype">int</span> PartitionsK_ = 1,</div><div class="line"><a name="l00079"></a><span class="lineno"> 79</span>  <span class="keywordtype">int</span> PartitionsN_ = 1,</div><div class="line"><a name="l00081"></a><span class="lineno"> 81</span>  <span class="keyword">typename</span> Enable = <span class="keywordtype">bool</span></div><div class="line"><a name="l00082"></a><span class="lineno"> 82</span> ></div><div class="line"><a name="l00083"></a><span class="lineno"> 83</span> <span class="keyword">class </span>MmaTensorOpWmma {</div><div class="line"><a name="l00084"></a><span class="lineno"> 84</span> <span class="keyword">public</span>:</div><div class="line"><a name="l00086"></a><span class="lineno"> 86</span>  <span class="keyword">using</span> Shape = Shape_;</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">using</span> ElementA = ElementA_;</div><div class="line"><a name="l00090"></a><span class="lineno"> 90</span> </div><div class="line"><a name="l00092"></a><span class="lineno"> 92</span>  <span class="keyword">using</span> LayoutA = LayoutA_;</div><div class="line"><a name="l00093"></a><span class="lineno"> 93</span> </div><div class="line"><a name="l00095"></a><span class="lineno"> 95</span>  <span class="keyword">using</span> ElementB = ElementB_;</div><div class="line"><a name="l00096"></a><span class="lineno"> 96</span> </div><div class="line"><a name="l00098"></a><span class="lineno"> 98</span>  <span class="keyword">using</span> LayoutB = LayoutB_;</div><div class="line"><a name="l00099"></a><span class="lineno"> 99</span> </div><div class="line"><a name="l00101"></a><span class="lineno"> 101</span>  <span class="keyword">using</span> ElementC = ElementC_;</div><div class="line"><a name="l00102"></a><span class="lineno"> 102</span> </div><div class="line"><a name="l00104"></a><span class="lineno"> 104</span>  <span class="keyword">using</span> LayoutC = LayoutC_;</div><div class="line"><a name="l00105"></a><span class="lineno"> 105</span> </div><div class="line"><a name="l00107"></a><span class="lineno"> 107</span>  <span class="keyword">using</span> Policy = Policy_;</div><div class="line"><a name="l00108"></a><span class="lineno"> 108</span> </div><div class="line"><a name="l00110"></a><span class="lineno"> 110</span>  <span class="keyword">using</span> OperatorClass = arch::OpClassTensorOp;</div><div class="line"><a name="l00111"></a><span class="lineno"> 111</span> </div><div class="line"><a name="l00113"></a><span class="lineno"> 113</span>  <span class="keyword">static</span> <span class="keywordtype">int</span> <span class="keyword">const</span> kThreadCount = 32;</div><div class="line"><a name="l00114"></a><span class="lineno"> 114</span> </div><div class="line"><a name="l00116"></a><span class="lineno"> 116</span>  <span class="keyword">static</span> <span class="keywordtype">int</span> <span class="keyword">const</span> kPartitionsK = PartitionsK_;</div><div class="line"><a name="l00117"></a><span class="lineno"> 117</span> </div><div class="line"><a name="l00119"></a><span class="lineno"> 119</span>  <span class="keyword">static</span> <span class="keywordtype">int</span> <span class="keyword">const</span> kPartitionsN = PartitionsN_;</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="keyword">public</span>:</div><div class="line"><a name="l00122"></a><span class="lineno"> 122</span> </div><div class="line"><a name="l00124"></a><span class="lineno"> 124</span>  <span class="keyword">using</span> IteratorA = MmaTensorOpWmmaMultiplicandTileIterator<</div><div class="line"><a name="l00125"></a><span class="lineno"> 125</span>  MatrixShape<Shape::kM, Shape::kK>, <a class="code" href="namespacecutlass_1_1gemm.html#a34338284023da7403c9ecbd3f406b2a6a30f767aa191cd5d261e767fd78393607">Operand::kA</a>, ElementA, LayoutA,</div><div class="line"><a name="l00126"></a><span class="lineno"> 126</span>  Policy::OpDelta::kRow, kThreadCount, Policy>;</div><div class="line"><a name="l00127"></a><span class="lineno"> 127</span> </div><div class="line"><a name="l00129"></a><span class="lineno"> 129</span>  <span class="keyword">using</span> FragmentA = <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> IteratorB = MmaTensorOpWmmaMultiplicandTileIterator<</div><div class="line"><a name="l00133"></a><span class="lineno"> 133</span>  MatrixShape<Shape::kK, Shape::kN>, <a class="code" href="namespacecutlass_1_1gemm.html#a34338284023da7403c9ecbd3f406b2a6a3e56c011b37f0bc78fb9eb175c1181c6">Operand::kB</a>, ElementB, LayoutB,</div><div class="line"><a name="l00134"></a><span class="lineno"> 134</span>  Policy::OpDelta::kRow, kThreadCount, Policy>;</div><div class="line"><a name="l00135"></a><span class="lineno"> 135</span> </div><div class="line"><a name="l00137"></a><span class="lineno"> 137</span>  <span class="keyword">using</span> FragmentB = <span class="keyword">typename</span> IteratorB::Fragment;</div><div class="line"><a name="l00138"></a><span class="lineno"> 138</span> </div><div class="line"><a name="l00140"></a><span class="lineno"> 140</span>  <span class="keyword">using</span> IteratorC = MmaTensorOpWmmaAccumulatorTileIterator<</div><div class="line"><a name="l00141"></a><span class="lineno"> 141</span>  MatrixShape<Shape::kM, Shape::kN>, ElementC, LayoutC,</div><div class="line"><a name="l00142"></a><span class="lineno"> 142</span>  <span class="keyword">typename</span> Policy::OpDelta, Policy>;</div><div class="line"><a name="l00143"></a><span class="lineno"> 143</span> </div><div class="line"><a name="l00145"></a><span class="lineno"> 145</span>  <span class="keyword">using</span> FragmentC = <span class="keyword">typename</span> IteratorC::Fragment;</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> <span class="keyword">private</span>:</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>  <a class="code" href="platform_8h.html#adde4c9ea91b753491851361a4198c009">static_assert</a>(</div><div class="line"><a name="l00150"></a><span class="lineno"> 150</span>  !(Shape::kM % Policy::Operator::Shape::kM) && </div><div class="line"><a name="l00151"></a><span class="lineno"> 151</span>  !(Shape::kN % Policy::Operator::Shape::kN),</div><div class="line"><a name="l00152"></a><span class="lineno"> 152</span>  <span class="stringliteral">"Shape of warp-level Wmma must be divisible by operator shape (wmma native size)"</span>);</div><div class="line"><a name="l00153"></a><span class="lineno"> 153</span> </div><div class="line"><a name="l00155"></a><span class="lineno"> 155</span>  <span class="keyword">using</span> WmmaIterations = MatrixShape<</div><div class="line"><a name="l00156"></a><span class="lineno"> 156</span>  Shape::kM / Policy::Operator::Shape::kM,</div><div class="line"><a name="l00157"></a><span class="lineno"> 157</span>  (Shape::kN / Policy::Operator::Shape::kN / kPartitionsN > 0) ?</div><div class="line"><a name="l00158"></a><span class="lineno"> 158</span>  Shape::kN / Policy::Operator::Shape::kN / kPartitionsN :</div><div class="line"><a name="l00159"></a><span class="lineno"> 159</span>  1</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> </div><div class="line"><a name="l00162"></a><span class="lineno"> 162</span> <span class="keyword">public</span>:</div><div class="line"><a name="l00163"></a><span class="lineno"> 163</span> </div><div class="line"><a name="l00165"></a><span class="lineno"> 165</span>  <span class="keyword">typename</span> Policy::Operator wmma;</div><div class="line"><a name="l00166"></a><span class="lineno"> 166</span> </div><div class="line"><a name="l00167"></a><span class="lineno"> 167</span> <span class="keyword">public</span>:</div><div class="line"><a name="l00168"></a><span class="lineno"> 168</span> </div><div class="line"><a name="l00169"></a><span class="lineno"> 169</span>  <span class="comment">//</span></div><div class="line"><a name="l00170"></a><span class="lineno"> 170</span>  <span class="comment">// Methods</span></div><div class="line"><a name="l00171"></a><span class="lineno"> 171</span>  <span class="comment">//</span></div><div class="line"><a name="l00172"></a><span class="lineno"> 172</span> </div><div class="line"><a name="l00174"></a><span class="lineno"> 174</span>  CUTLASS_DEVICE</div><div class="line"><a name="l00175"></a><span class="lineno"> 175</span>  MmaTensorOpWmma() {}</div><div class="line"><a name="l00176"></a><span class="lineno"> 176</span> </div><div class="line"><a name="l00178"></a><span class="lineno"> 178</span>  CUTLASS_DEVICE</div><div class="line"><a name="l00179"></a><span class="lineno"> 179</span>  <span class="keywordtype">void</span> operator()(</div><div class="line"><a name="l00180"></a><span class="lineno"> 180</span>  FragmentC &D, </div><div class="line"><a name="l00181"></a><span class="lineno"> 181</span>  FragmentA <span class="keyword">const</span> &A, </div><div class="line"><a name="l00182"></a><span class="lineno"> 182</span>  FragmentB <span class="keyword">const</span> &B, </div><div class="line"><a name="l00183"></a><span class="lineno"> 183</span>  FragmentC <span class="keyword">const</span> &C,</div><div class="line"><a name="l00184"></a><span class="lineno"> 184</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="l00185"></a><span class="lineno"> 185</span> </div><div class="line"><a name="l00186"></a><span class="lineno"> 186</span>  <a class="code" href="cutlass_8h.html#a4b1c9f25ab6eaa25e1f2258dd63e6ce4">CUTLASS_PRAGMA_UNROLL</a></div><div class="line"><a name="l00187"></a><span class="lineno"> 187</span>  <span class="keywordflow">for</span> (<span class="keywordtype">int</span> n = 0; n < WmmaIterations::kColumn; ++n) {</div><div class="line"><a name="l00188"></a><span class="lineno"> 188</span>  <a class="code" href="cutlass_8h.html#a4b1c9f25ab6eaa25e1f2258dd63e6ce4">CUTLASS_PRAGMA_UNROLL</a></div><div class="line"><a name="l00189"></a><span class="lineno"> 189</span>  <span class="keywordflow">for</span> (<span class="keywordtype">int</span> m = 0; m < WmmaIterations::kRow; ++m) {</div><div class="line"><a name="l00190"></a><span class="lineno"> 190</span> </div><div class="line"><a name="l00191"></a><span class="lineno"> 191</span>  <span class="comment">// accumulate wmma mma</span></div><div class="line"><a name="l00192"></a><span class="lineno"> 192</span>  wmma(D[m * WmmaIterations::kColumn + n], A[m], B[n], C[m * WmmaIterations::kColumn + n]);</div><div class="line"><a name="l00193"></a><span class="lineno"> 193</span>  }</div><div class="line"><a name="l00194"></a><span class="lineno"> 194</span>  } </div><div class="line"><a name="l00195"></a><span class="lineno"> 195</span>  }</div><div class="line"><a name="l00196"></a><span class="lineno"> 196</span> </div><div class="line"><a name="l00197"></a><span class="lineno"> 197</span> };</div><div class="line"><a name="l00198"></a><span class="lineno"> 198</span> </div><div class="line"><a name="l00200"></a><span class="lineno"> 200</span> </div><div class="line"><a name="l00201"></a><span class="lineno"> 201</span> } <span class="comment">// namespace warp</span></div><div class="line"><a name="l00202"></a><span class="lineno"> 202</span> } <span class="comment">// namespace gemm</span></div><div class="line"><a name="l00203"></a><span class="lineno"> 203</span> } <span class="comment">// namespace cutlass</span></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> <span class="preprocessor">#endif // if defined(CUTLASS_ARCH_WMMA_ENABLED)</span></div><div class="line"><a name="l00206"></a><span class="lineno"> 206</span> </div><div class="ttc" id="wmma__array_8h_html"><div class="ttname"><a href="wmma__array_8h.html">wmma_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="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="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="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="mma__tensor__op__tile__iterator__wmma_8h_html"><div class="ttname"><a href="mma__tensor__op__tile__iterator__wmma_8h.html">mma_tensor_op_tile_iterator_wmma.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="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="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="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="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="wmma_8h_html"><div class="ttname"><a href="wmma_8h.html">wmma.h</a></div><div class="ttdoc">Templates exposing architecture support for warp matrix multiply-add (WMMA) operations. </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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