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CUTLASS 2.0 (#62) CUTLASS 2.0 Substantially refactored for - Better performance, particularly for native Turing Tensor Cores - Robust and durable templates spanning the design space - Encapsulated functionality embodying modern C++11 programming techniques - Optimized containers and data types for efficient, generic, portable device code Updates to: - Quick start guide - Documentation - Utilities - CUTLASS Profiler Native Turing Tensor Cores - Efficient GEMM kernels targeting Turing Tensor Cores - Mixed-precision floating point, 8-bit integer, 4-bit integer, and binarized operands Coverage of existing CUTLASS functionality: - GEMM kernels targeting CUDA and Tensor Cores in NVIDIA GPUs - Volta Tensor Cores through native mma.sync and through WMMA API - Optimizations such as parallel reductions, threadblock rasterization, and intra-threadblock reductions - Batched GEMM operations - Complex-valued GEMMs Note: this commit and all that follow require a host compiler supporting C++11 or greater.
2019-11-20 08:55:34 +08:00
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<a href="host_2tensor__foreach_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>&#160;<span class="comment">/***************************************************************************************************</span></div><div class="line"><a name="l00002"></a><span class="lineno"> 2</span>&#160;<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>&#160;<span class="comment"> *</span></div><div class="line"><a name="l00004"></a><span class="lineno"> 4</span>&#160;<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>&#160;<span class="comment"> * provided that the following conditions are met:</span></div><div class="line"><a name="l00006"></a><span class="lineno"> 6</span>&#160;<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>&#160;<span class="comment"> * conditions and the following disclaimer.</span></div><div class="line"><a name="l00008"></a><span class="lineno"> 8</span>&#160;<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>&#160;<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>&#160;<span class="comment"> * provided with the distribution.</span></div><div class="line"><a name="l00011"></a><span class="lineno"> 11</span>&#160;<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>&#160;<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>&#160;<span class="comment"> * permission.</span></div><div class="line"><a name="l00014"></a><span class="lineno"> 14</span>&#160;<span class="comment"> *</span></div><div class="line"><a name="l00015"></a><span class="lineno"> 15</span>&#160;<span class="comment"> * THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS &quot;AS IS&quot; AND ANY EXPRESS OR</span></div><div class="line"><a name="l00016"></a><span class="lineno"> 16</span>&#160;<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>&#160;<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>&#160;<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>&#160;<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>&#160;<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>&#160;<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
<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>
<div class="ttc" id="structcutlass_1_1reference_1_1host_1_1BlockForEach_html_aa2e578397b5cd68214736c2437f92480"><div class="ttname"><a href="structcutlass_1_1reference_1_1host_1_1BlockForEach.html#aa2e578397b5cd68214736c2437f92480">cutlass::reference::host::BlockForEach::BlockForEach</a></div><div class="ttdeci">BlockForEach(Element *ptr, size_t capacity, typename Func::Params params=typename Func::Params())</div><div class="ttdoc">Constructor performs the operation. </div><div class="ttdef"><b>Definition:</b> host/tensor_foreach.h:109</div></div>
<div class="ttc" id="structcutlass_1_1reference_1_1host_1_1detail_1_1TensorForEachHelper_html_a1161a761c596e714982fe30141211cca"><div class="ttname"><a href="structcutlass_1_1reference_1_1host_1_1detail_1_1TensorForEachHelper.html#a1161a761c596e714982fe30141211cca">cutlass::reference::host::detail::TensorForEachHelper::kActiveRank</a></div><div class="ttdeci">static int const kActiveRank</div><div class="ttdoc">Index of the active rank. </div><div class="ttdef"><b>Definition:</b> host/tensor_foreach.h:44</div></div>
<div class="ttc" id="structcutlass_1_1reference_1_1host_1_1detail_1_1TensorForEachHelper_html_aa63906bbecfe42eec1991c9176f066d9"><div class="ttname"><a href="structcutlass_1_1reference_1_1host_1_1detail_1_1TensorForEachHelper.html#aa63906bbecfe42eec1991c9176f066d9">cutlass::reference::host::detail::TensorForEachHelper::TensorForEachHelper</a></div><div class="ttdeci">TensorForEachHelper(Func &amp;func, Coord&lt; Rank &gt; const &amp;extent, Coord&lt; Rank &gt; &amp;coord)</div><div class="ttdoc">Constructor for general rank. </div><div class="ttdef"><b>Definition:</b> host/tensor_foreach.h:47</div></div>
<div class="ttc" id="structcutlass_1_1reference_1_1host_1_1detail_1_1TensorForEachHelper_html"><div class="ttname"><a href="structcutlass_1_1reference_1_1host_1_1detail_1_1TensorForEachHelper.html">cutlass::reference::host::detail::TensorForEachHelper</a></div><div class="ttdoc">Helper to perform for-each operation. </div><div class="ttdef"><b>Definition:</b> host/tensor_foreach.h:41</div></div>
<div class="ttc" id="structcutlass_1_1reference_1_1host_1_1detail_1_1TensorForEachHelper_3_01Func_00_01Rank_00_010_01_4_html_a5029a4405a9a5e64011addb43bb88120"><div class="ttname"><a href="structcutlass_1_1reference_1_1host_1_1detail_1_1TensorForEachHelper_3_01Func_00_01Rank_00_010_01_4.html#a5029a4405a9a5e64011addb43bb88120">cutlass::reference::host::detail::TensorForEachHelper&lt; Func, Rank, 0 &gt;::TensorForEachHelper</a></div><div class="ttdeci">TensorForEachHelper(Func &amp;func, Coord&lt; Rank &gt; const &amp;extent, Coord&lt; Rank &gt; &amp;coord)</div><div class="ttdoc">Constructor for fastest chaning rank. </div><div class="ttdef"><b>Definition:</b> host/tensor_foreach.h:67</div></div>
<div class="ttc" id="structcutlass_1_1Coord_html"><div class="ttname"><a href="structcutlass_1_1Coord.html">cutlass::Coord</a></div><div class="ttdoc">Statically-sized array specifying Coords within a tensor. </div><div class="ttdef"><b>Definition:</b> coord.h:43</div></div>
<div class="ttc" id="namespacecutlass_1_1reference_1_1host_html_a3825b1aaaf5e5abf0de5f427e3481ada"><div class="ttname"><a href="namespacecutlass_1_1reference_1_1host.html#a3825b1aaaf5e5abf0de5f427e3481ada">cutlass::reference::host::TensorForEachLambda</a></div><div class="ttdeci">void TensorForEachLambda(Coord&lt; Rank &gt; extent, Func func)</div><div class="ttdoc">Iterates over the index space of a tensor and calls a C++ lambda. </div><div class="ttdef"><b>Definition:</b> host/tensor_foreach.h:98</div></div>
<div class="ttc" id="namespacecutlass_1_1reference_1_1host_html_a8c798c04df572b34e3ed3976d69f993d"><div class="ttname"><a href="namespacecutlass_1_1reference_1_1host.html#a8c798c04df572b34e3ed3976d69f993d">cutlass::reference::host::TensorForEach</a></div><div class="ttdeci">void TensorForEach(Coord&lt; Rank &gt; extent, Func &amp;func)</div><div class="ttdoc">Iterates over the index space of a tensor. </div><div class="ttdef"><b>Definition:</b> host/tensor_foreach.h:87</div></div>
<div class="ttc" id="structcutlass_1_1Coord_html_a8a65128c86b236cd2bea875b85a34bc1"><div class="ttname"><a href="structcutlass_1_1Coord.html#a8a65128c86b236cd2bea875b85a34bc1">cutlass::Coord::at</a></div><div class="ttdeci">CUTLASS_HOST_DEVICE Index &amp; at()</div><div class="ttdoc">Gets the index of a given Coord element. </div><div class="ttdef"><b>Definition:</b> coord.h:255</div></div>
<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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