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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="default__thread__map__simt_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
<div class="ttc" id="structcutlass_1_1epilogue_1_1threadblock_1_1OutputTileOptimalThreadMap_html"><div class="ttname"><a href="structcutlass_1_1epilogue_1_1threadblock_1_1OutputTileOptimalThreadMap.html">cutlass::epilogue::threadblock::OutputTileOptimalThreadMap</a></div><div class="ttdef"><b>Definition:</b> output_tile_thread_map.h:228</div></div>
<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_1epilogue_1_1threadblock_1_1DefaultThreadMapSimt_html_ab5aa7dc4a1b43ac634f1a19e6a4f3899"><div class="ttname"><a href="structcutlass_1_1epilogue_1_1threadblock_1_1DefaultThreadMapSimt.html#ab5aa7dc4a1b43ac634f1a19e6a4f3899">cutlass::epilogue::threadblock::DefaultThreadMapSimt::ThreadblockShape</a></div><div class="ttdeci">ThreadblockShape_ ThreadblockShape</div><div class="ttdef"><b>Definition:</b> default_thread_map_simt.h:54</div></div>
<div class="ttc" id="structcutlass_1_1epilogue_1_1threadblock_1_1DefaultThreadMapSimt_html_a9a6af9fcf3e00b00012d0ca488fd6fb8"><div class="ttname"><a href="structcutlass_1_1epilogue_1_1threadblock_1_1DefaultThreadMapSimt.html#a9a6af9fcf3e00b00012d0ca488fd6fb8">cutlass::epilogue::threadblock::DefaultThreadMapSimt::MmaSimtPolicy</a></div><div class="ttdeci">MmaSimtPolicy_ MmaSimtPolicy</div><div class="ttdef"><b>Definition:</b> default_thread_map_simt.h:56</div></div>
<div class="ttc" id="structcutlass_1_1epilogue_1_1threadblock_1_1OutputTileShape_html"><div class="ttname"><a href="structcutlass_1_1epilogue_1_1threadblock_1_1OutputTileShape.html">cutlass::epilogue::threadblock::OutputTileShape</a></div><div class="ttdoc">Tuple defining point in output tile. </div><div class="ttdef"><b>Definition:</b> output_tile_thread_map.h:57</div></div>
<div class="ttc" id="structcutlass_1_1epilogue_1_1threadblock_1_1DefaultThreadMapSimt_1_1Detail_html_a62b7574dcf62d9c0409d986848f3844c"><div class="ttname"><a href="structcutlass_1_1epilogue_1_1threadblock_1_1DefaultThreadMapSimt_1_1Detail.html#a62b7574dcf62d9c0409d986848f3844c">cutlass::epilogue::threadblock::DefaultThreadMapSimt::Detail::kThreads</a></div><div class="ttdeci">static int const kThreads</div><div class="ttdoc">Number of participating threads. </div><div class="ttdef"><b>Definition:</b> default_thread_map_simt.h:85</div></div>
<div class="ttc" id="epilogue_2threadblock_2predicated__tile__iterator_8h_html"><div class="ttname"><a href="epilogue_2threadblock_2predicated__tile__iterator_8h.html">predicated_tile_iterator.h</a></div><div class="ttdoc">Epilogue for threadblock scoped GEMMs using Tensor Ops. </div></div>
<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>
<div class="ttc" id="structcutlass_1_1gemm_1_1GemmShape_html_a3768273d392c8e133812f2b3313f45e8"><div class="ttname"><a href="structcutlass_1_1gemm_1_1GemmShape.html#a3768273d392c8e133812f2b3313f45e8">cutlass::gemm::GemmShape::kCount</a></div><div class="ttdeci">static int const kCount</div><div class="ttdef"><b>Definition:</b> include/cutlass/gemm/gemm.h:67</div></div>
<div class="ttc" id="structcutlass_1_1epilogue_1_1threadblock_1_1DefaultThreadMapSimt_html"><div class="ttname"><a href="structcutlass_1_1epilogue_1_1threadblock_1_1DefaultThreadMapSimt.html">cutlass::epilogue::threadblock::DefaultThreadMapSimt</a></div><div class="ttdoc">Defines the optimal thread map for SIMT accumulator layouts. </div><div class="ttdef"><b>Definition:</b> default_thread_map_simt.h:52</div></div>
<div class="ttc" id="structcutlass_1_1sizeof__bits_html"><div class="ttname"><a href="structcutlass_1_1sizeof__bits.html">cutlass::sizeof_bits</a></div><div class="ttdoc">Defines the size of an element in bits. </div><div class="ttdef"><b>Definition:</b> numeric_types.h:42</div></div>
<div class="ttc" id="structcutlass_1_1epilogue_1_1threadblock_1_1DefaultThreadMapSimt_html_ad270ab7a314a65337812bb9377f40fb4"><div class="ttname"><a href="structcutlass_1_1epilogue_1_1threadblock_1_1DefaultThreadMapSimt.html#ad270ab7a314a65337812bb9377f40fb4">cutlass::epilogue::threadblock::DefaultThreadMapSimt::Element</a></div><div class="ttdeci">Element_ Element</div><div class="ttdef"><b>Definition:</b> default_thread_map_simt.h:58</div></div>
<div class="ttc" id="structcutlass_1_1epilogue_1_1threadblock_1_1DefaultThreadMapSimt_html_a5cad2530f66c02df18228866da95011e"><div class="ttname"><a href="structcutlass_1_1epilogue_1_1threadblock_1_1DefaultThreadMapSimt.html#a5cad2530f66c02df18228866da95011e">cutlass::epilogue::threadblock::DefaultThreadMapSimt::kElementsPerAccess</a></div><div class="ttdeci">static int const kElementsPerAccess</div><div class="ttdef"><b>Definition:</b> default_thread_map_simt.h:59</div></div>
<div class="ttc" id="structcutlass_1_1epilogue_1_1threadblock_1_1DefaultThreadMapSimt_1_1Detail_html_a3129fc3da8ee72066cc96de03318afae"><div class="ttname"><a href="structcutlass_1_1epilogue_1_1threadblock_1_1DefaultThreadMapSimt_1_1Detail.html#a3129fc3da8ee72066cc96de03318afae">cutlass::epilogue::threadblock::DefaultThreadMapSimt::Detail::kIterations</a></div><div class="ttdeci">static int const kIterations</div><div class="ttdoc">Number of iterations. </div><div class="ttdef"><b>Definition:</b> default_thread_map_simt.h:88</div></div>
<div class="ttc" id="structcutlass_1_1epilogue_1_1threadblock_1_1DefaultThreadMapSimt_1_1Detail_html_afa4da0a64b7775eb859a62ce13b43beb"><div class="ttname"><a href="structcutlass_1_1epilogue_1_1threadblock_1_1DefaultThreadMapSimt_1_1Detail.html#afa4da0a64b7775eb859a62ce13b43beb">cutlass::epilogue::threadblock::DefaultThreadMapSimt::Detail::kWarpSize</a></div><div class="ttdeci">static int const kWarpSize</div><div class="ttdef"><b>Definition:</b> default_thread_map_simt.h:67</div></div>
<div class="ttc" id="structcutlass_1_1epilogue_1_1threadblock_1_1DefaultThreadMapSimt_html_a24ca41463fa323d6a92f9456d4adbca9"><div class="ttname"><a href="structcutlass_1_1epilogue_1_1threadblock_1_1DefaultThreadMapSimt.html#a24ca41463fa323d6a92f9456d4adbca9">cutlass::epilogue::threadblock::DefaultThreadMapSimt::kPartitionsK</a></div><div class="ttdeci">static int const kPartitionsK</div><div class="ttdef"><b>Definition:</b> default_thread_map_simt.h:57</div></div>
<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>
<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>
<div class="ttc" id="structcutlass_1_1epilogue_1_1threadblock_1_1DefaultThreadMapSimt_1_1Detail_html"><div class="ttname"><a href="structcutlass_1_1epilogue_1_1threadblock_1_1DefaultThreadMapSimt_1_1Detail.html">cutlass::epilogue::threadblock::DefaultThreadMapSimt::Detail</a></div><div class="ttdef"><b>Definition:</b> default_thread_map_simt.h:65</div></div>
<div class="ttc" id="structcutlass_1_1epilogue_1_1threadblock_1_1DefaultThreadMapSimt_html_a62295374512b766ce8b42186d84d9712"><div class="ttname"><a href="structcutlass_1_1epilogue_1_1threadblock_1_1DefaultThreadMapSimt.html#a62295374512b766ce8b42186d84d9712">cutlass::epilogue::threadblock::DefaultThreadMapSimt::WarpShape</a></div><div class="ttdeci">WarpShape_ WarpShape</div><div class="ttdef"><b>Definition:</b> default_thread_map_simt.h:55</div></div>
<div class="ttc" id="structcutlass_1_1epilogue_1_1threadblock_1_1DefaultThreadMapSimt_1_1Detail_html_a29cdfb7311f00b37c18a8e1e83984323"><div class="ttname"><a href="structcutlass_1_1epilogue_1_1threadblock_1_1DefaultThreadMapSimt_1_1Detail.html#a29cdfb7311f00b37c18a8e1e83984323">cutlass::epilogue::threadblock::DefaultThreadMapSimt::Detail::kGroupCount</a></div><div class="ttdeci">static int const kGroupCount</div><div class="ttdoc">Computes number of thread-level matrix multiplies are needed to span a warp. </div><div class="ttdef"><b>Definition:</b> default_thread_map_simt.h:81</div></div>
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