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<li class="navelem"><a class="el" href="namespacecutlass.html">cutlass</a></li><li class="navelem"><a class="el" href="namespacecutlass_1_1reduction.html">reduction</a></li><li class="navelem"><a class="el" href="structcutlass_1_1reduction_1_1BatchedReductionTraits.html">BatchedReductionTraits</a></li><li class="navelem"><a class="el" href="structcutlass_1_1reduction_1_1BatchedReductionTraits_1_1Params.html">Params</a></li> </ul>
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<a href="#pub-methods">Public Member Functions</a> |
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<a href="structcutlass_1_1reduction_1_1BatchedReductionTraits_1_1Params-members.html">List of all members</a> </div>
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<div class="headertitle">
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<div class="title">cutlass::reduction::BatchedReductionTraits< ScalarA_, ScalarC_, ScalarD_, ScalarAlphaBeta_, ScalarAccum_, ReductionSize_, OutputTile_, SubTile_, ThreadShape_, Index_, BlockSwizzle_, maxInReg_, maxOutReg_, Functor_ >::Params Struct Reference</div> </div>
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<p><code>#include <<a class="el" href="batched__reduction__traits_8h_source.html">batched_reduction_traits.h</a>></code></p>
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<table class="memberdecls">
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<tr class="heading"><td colspan="2"><h2 class="groupheader"><a name="pub-methods"></a>
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Public Member Functions</h2></td></tr>
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<tr class="memitem:ac27f42beb3625c5183b76b26677c0cb0"><td class="memItemLeft" align="right" valign="top"><a class="el" href="cutlass_8h.html#a28c2443a142676d3d71effdae1a986b1">CUTLASS_HOST_DEVICE</a> int </td><td class="memItemRight" valign="bottom"><a class="el" href="structcutlass_1_1reduction_1_1BatchedReductionTraits_1_1Params.html#ac27f42beb3625c5183b76b26677c0cb0">initialize</a> (<a class="el" href="structcutlass_1_1reduction_1_1BatchedReductionTraits.html#ab0c9e548f3ee62746e727127e387a8f4">Index</a> m_, <a class="el" href="structcutlass_1_1reduction_1_1BatchedReductionTraits.html#ab0c9e548f3ee62746e727127e387a8f4">Index</a> n_, <a class="el" href="structcutlass_1_1reduction_1_1BatchedReductionTraits.html#ab89c35cfce0017a47341a1e3b2894e0f">ScalarAlphaBeta</a> alpha_, <a class="el" href="structcutlass_1_1reduction_1_1BatchedReductionTraits.html#ab89c35cfce0017a47341a1e3b2894e0f">ScalarAlphaBeta</a> beta_, long long int reduction_stride_, <a class="el" href="structcutlass_1_1reduction_1_1BatchedReductionTraits.html#a1c6cd0a76b2b2fc9cd021b016f30f459">ScalarA</a> const *d_a_, <a class="el" href="structcutlass_1_1reduction_1_1BatchedReductionTraits.html#ab0c9e548f3ee62746e727127e387a8f4">Index</a> lda_, <a class="el" href="structcutlass_1_1reduction_1_1BatchedReductionTraits.html#adb39cf54a839bdb2e38fbc8a0bf304a8">ScalarC</a> const *d_c_, <a class="el" href="structcutlass_1_1reduction_1_1BatchedReductionTraits.html#ab0c9e548f3ee62746e727127e387a8f4">Index</a> ldc_, <a class="el" href="structcutlass_1_1reduction_1_1BatchedReductionTraits.html#abb54e3addfee4097b37deb5cb30fb582">ScalarD</a> *d_d_, <a class="el" href="structcutlass_1_1reduction_1_1BatchedReductionTraits.html#ab0c9e548f3ee62746e727127e387a8f4">Index</a> ldd_)</td></tr>
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<tr class="memdesc:ac27f42beb3625c5183b76b26677c0cb0"><td class="mdescLeft"> </td><td class="mdescRight">Initialize the parameters for 2D output tensor. <a href="#ac27f42beb3625c5183b76b26677c0cb0">More...</a><br /></td></tr>
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<tr class="separator:ac27f42beb3625c5183b76b26677c0cb0"><td class="memSeparator" colspan="2"> </td></tr>
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</table><table class="memberdecls">
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<tr class="heading"><td colspan="2"><h2 class="groupheader"><a name="pub-attribs"></a>
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Public Attributes</h2></td></tr>
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<tr class="memitem:adbd0cf20c4f7033016d1b8fdaca6aeae"><td class="memItemLeft" align="right" valign="top"><a class="el" href="structcutlass_1_1Coord.html">Coord</a>< 3 > </td><td class="memItemRight" valign="bottom"><a class="el" href="structcutlass_1_1reduction_1_1BatchedReductionTraits_1_1Params.html#adbd0cf20c4f7033016d1b8fdaca6aeae">problem_size</a></td></tr>
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<tr class="memdesc:adbd0cf20c4f7033016d1b8fdaca6aeae"><td class="mdescLeft"> </td><td class="mdescRight">The dimension of output tensor. <a href="#adbd0cf20c4f7033016d1b8fdaca6aeae">More...</a><br /></td></tr>
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<tr class="separator:adbd0cf20c4f7033016d1b8fdaca6aeae"><td class="memSeparator" colspan="2"> </td></tr>
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<tr class="memitem:afada1cbad87636228fb58d8577bb8470"><td class="memItemLeft" align="right" valign="top"><a class="el" href="structcutlass_1_1reduction_1_1BatchedReductionTraits.html#ab89c35cfce0017a47341a1e3b2894e0f">ScalarAlphaBeta</a> </td><td class="memItemRight" valign="bottom"><a class="el" href="structcutlass_1_1reduction_1_1BatchedReductionTraits_1_1Params.html#afada1cbad87636228fb58d8577bb8470">alpha</a></td></tr>
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<tr class="memdesc:afada1cbad87636228fb58d8577bb8470"><td class="mdescLeft"> </td><td class="mdescRight">The alpha. <a href="#afada1cbad87636228fb58d8577bb8470">More...</a><br /></td></tr>
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<tr class="separator:afada1cbad87636228fb58d8577bb8470"><td class="memSeparator" colspan="2"> </td></tr>
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<tr class="memitem:a805f78cae27c3305c988f251207d85f7"><td class="memItemLeft" align="right" valign="top"><a class="el" href="structcutlass_1_1reduction_1_1BatchedReductionTraits.html#ab89c35cfce0017a47341a1e3b2894e0f">ScalarAlphaBeta</a> </td><td class="memItemRight" valign="bottom"><a class="el" href="structcutlass_1_1reduction_1_1BatchedReductionTraits_1_1Params.html#a805f78cae27c3305c988f251207d85f7">beta</a></td></tr>
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<tr class="memdesc:a805f78cae27c3305c988f251207d85f7"><td class="mdescLeft"> </td><td class="mdescRight">The beta. <a href="#a805f78cae27c3305c988f251207d85f7">More...</a><br /></td></tr>
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<tr class="separator:a805f78cae27c3305c988f251207d85f7"><td class="memSeparator" colspan="2"> </td></tr>
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<tr class="memitem:a5d1463d473d4226b0d19c581b16ed3b2"><td class="memItemLeft" align="right" valign="top">long long int </td><td class="memItemRight" valign="bottom"><a class="el" href="structcutlass_1_1reduction_1_1BatchedReductionTraits_1_1Params.html#a5d1463d473d4226b0d19c581b16ed3b2">reduction_stride</a></td></tr>
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<tr class="memdesc:a5d1463d473d4226b0d19c581b16ed3b2"><td class="mdescLeft"> </td><td class="mdescRight">stride between two element that will be sumed <a href="#a5d1463d473d4226b0d19c581b16ed3b2">More...</a><br /></td></tr>
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<tr class="separator:a5d1463d473d4226b0d19c581b16ed3b2"><td class="memSeparator" colspan="2"> </td></tr>
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<tr class="memitem:af1b12ba220602692e84616b420b00f1c"><td class="memItemLeft" align="right" valign="top"><a class="el" href="structcutlass_1_1reduction_1_1BatchedReductionTraits.html#a1c6cd0a76b2b2fc9cd021b016f30f459">ScalarA</a> const * </td><td class="memItemRight" valign="bottom"><a class="el" href="structcutlass_1_1reduction_1_1BatchedReductionTraits_1_1Params.html#af1b12ba220602692e84616b420b00f1c">d_a</a></td></tr>
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<tr class="separator:af1b12ba220602692e84616b420b00f1c"><td class="memSeparator" colspan="2"> </td></tr>
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<tr class="memitem:ab14fa69759f1d600a28df4fabaf59c28"><td class="memItemLeft" align="right" valign="top"><a class="el" href="structcutlass_1_1reduction_1_1BatchedReductionTraits.html#ab0c9e548f3ee62746e727127e387a8f4">Index</a> </td><td class="memItemRight" valign="bottom"><a class="el" href="structcutlass_1_1reduction_1_1BatchedReductionTraits_1_1Params.html#ab14fa69759f1d600a28df4fabaf59c28">lda</a></td></tr>
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<tr class="separator:ab14fa69759f1d600a28df4fabaf59c28"><td class="memSeparator" colspan="2"> </td></tr>
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<tr class="memitem:ac79830eaf080ea0ffddd2100db6cf3e1"><td class="memItemLeft" align="right" valign="top"><a class="el" href="structcutlass_1_1reduction_1_1BatchedReductionTraits.html#adb39cf54a839bdb2e38fbc8a0bf304a8">ScalarC</a> const * </td><td class="memItemRight" valign="bottom"><a class="el" href="structcutlass_1_1reduction_1_1BatchedReductionTraits_1_1Params.html#ac79830eaf080ea0ffddd2100db6cf3e1">d_c</a></td></tr>
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<tr class="separator:ac79830eaf080ea0ffddd2100db6cf3e1"><td class="memSeparator" colspan="2"> </td></tr>
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<tr class="memitem:a6bdb4dfce17da648b55c7aa68ef5b191"><td class="memItemLeft" align="right" valign="top"><a class="el" href="structcutlass_1_1reduction_1_1BatchedReductionTraits.html#ab0c9e548f3ee62746e727127e387a8f4">Index</a> </td><td class="memItemRight" valign="bottom"><a class="el" href="structcutlass_1_1reduction_1_1BatchedReductionTraits_1_1Params.html#a6bdb4dfce17da648b55c7aa68ef5b191">ldc</a></td></tr>
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<tr class="memitem:abf9744373a72f3819a616b5a5b3bff22"><td class="memItemLeft" align="right" valign="top"><a class="el" href="structcutlass_1_1reduction_1_1BatchedReductionTraits.html#abb54e3addfee4097b37deb5cb30fb582">ScalarD</a> * </td><td class="memItemRight" valign="bottom"><a class="el" href="structcutlass_1_1reduction_1_1BatchedReductionTraits_1_1Params.html#abf9744373a72f3819a616b5a5b3bff22">d_d</a></td></tr>
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<tr class="separator:abf9744373a72f3819a616b5a5b3bff22"><td class="memSeparator" colspan="2"> </td></tr>
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<tr class="memitem:ad24096385e51009866b5aafd90b42ad2"><td class="memItemLeft" align="right" valign="top"><a class="el" href="structcutlass_1_1reduction_1_1BatchedReductionTraits.html#ab0c9e548f3ee62746e727127e387a8f4">Index</a> </td><td class="memItemRight" valign="bottom"><a class="el" href="structcutlass_1_1reduction_1_1BatchedReductionTraits_1_1Params.html#ad24096385e51009866b5aafd90b42ad2">ldd</a></td></tr>
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<tr class="memitem:a11e54597165b66e3054c6b9f43210760"><td class="memItemLeft" align="right" valign="top">Functor::Params </td><td class="memItemRight" valign="bottom"><a class="el" href="structcutlass_1_1reduction_1_1BatchedReductionTraits_1_1Params.html#a11e54597165b66e3054c6b9f43210760">functorParams</a></td></tr>
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<tr class="memdesc:a11e54597165b66e3054c6b9f43210760"><td class="mdescLeft"> </td><td class="mdescRight">The functor params. <a href="#a11e54597165b66e3054c6b9f43210760">More...</a><br /></td></tr>
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</table>
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<h2 class="groupheader">Member Function Documentation</h2>
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<a id="ac27f42beb3625c5183b76b26677c0cb0"></a>
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<h2 class="memtitle"><span class="permalink"><a href="#ac27f42beb3625c5183b76b26677c0cb0">◆ </a></span>initialize()</h2>
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<div class="memtemplate">
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template<typename ScalarA_ , typename ScalarC_ , typename ScalarD_ , typename ScalarAlphaBeta_ , typename ScalarAccum_ , int ReductionSize_ = 1, typename OutputTile_ = Shape<1, 1, 128>, typename SubTile_ = Shape<1, 1, 64>, typename ThreadShape_ = Shape<1, 1, 2>, typename Index_ = int, typename BlockSwizzle_ = DefaultBlockSwizzle, int maxInReg_ = 160, int maxOutReg_ = 64, typename Functor_ = typename cutlass::gemm::LinearScaling<ScalarAlphaBeta_, typename cutlass::gemm::FragmentMultiplyAdd<ScalarAlphaBeta_, ScalarAccum_, (ThreadShape_::kW % 2 == 0)> >> </div>
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<td class="memname"><a class="el" href="cutlass_8h.html#a28c2443a142676d3d71effdae1a986b1">CUTLASS_HOST_DEVICE</a> int <a class="el" href="structcutlass_1_1reduction_1_1BatchedReductionTraits.html">cutlass::reduction::BatchedReductionTraits</a>< ScalarA_, ScalarC_, ScalarD_, ScalarAlphaBeta_, ScalarAccum_, ReductionSize_, OutputTile_, SubTile_, ThreadShape_, Index_, BlockSwizzle_, maxInReg_, maxOutReg_, Functor_ >::Params::initialize </td>
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<td>(</td>
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<td class="paramtype"><a class="el" href="structcutlass_1_1reduction_1_1BatchedReductionTraits.html#ab0c9e548f3ee62746e727127e387a8f4">Index</a> </td>
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<td class="paramname"><em>m_</em>, </td>
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<td class="paramtype"><a class="el" href="structcutlass_1_1reduction_1_1BatchedReductionTraits.html#ab0c9e548f3ee62746e727127e387a8f4">Index</a> </td>
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<td class="paramname"><em>n_</em>, </td>
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<td class="paramtype"><a class="el" href="structcutlass_1_1reduction_1_1BatchedReductionTraits.html#ab89c35cfce0017a47341a1e3b2894e0f">ScalarAlphaBeta</a> </td>
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<td class="paramname"><em>alpha_</em>, </td>
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<td class="paramtype"><a class="el" href="structcutlass_1_1reduction_1_1BatchedReductionTraits.html#ab89c35cfce0017a47341a1e3b2894e0f">ScalarAlphaBeta</a> </td>
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<td class="paramname"><em>beta_</em>, </td>
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<td class="paramtype">long long int </td>
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<td class="paramname"><em>reduction_stride_</em>, </td>
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<td class="paramtype"><a class="el" href="structcutlass_1_1reduction_1_1BatchedReductionTraits.html#a1c6cd0a76b2b2fc9cd021b016f30f459">ScalarA</a> const * </td>
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<td class="paramname"><em>d_a_</em>, </td>
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<td class="paramtype"><a class="el" href="structcutlass_1_1reduction_1_1BatchedReductionTraits.html#ab0c9e548f3ee62746e727127e387a8f4">Index</a> </td>
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<td class="paramname"><em>lda_</em>, </td>
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<td class="paramtype"><a class="el" href="structcutlass_1_1reduction_1_1BatchedReductionTraits.html#adb39cf54a839bdb2e38fbc8a0bf304a8">ScalarC</a> const * </td>
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<td class="paramname"><em>d_c_</em>, </td>
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<td class="paramtype"><a class="el" href="structcutlass_1_1reduction_1_1BatchedReductionTraits.html#ab0c9e548f3ee62746e727127e387a8f4">Index</a> </td>
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<td class="paramname"><em>ldc_</em>, </td>
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<td class="paramtype"><a class="el" href="structcutlass_1_1reduction_1_1BatchedReductionTraits.html#abb54e3addfee4097b37deb5cb30fb582">ScalarD</a> * </td>
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<td class="paramname"><em>d_d_</em>, </td>
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<td class="paramname"><em>ldd_</em> </td>
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<h2 class="groupheader">Member Data Documentation</h2>
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<h2 class="memtitle"><span class="permalink"><a href="#afada1cbad87636228fb58d8577bb8470">◆ </a></span>alpha</h2>
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template<typename ScalarA_ , typename ScalarC_ , typename ScalarD_ , typename ScalarAlphaBeta_ , typename ScalarAccum_ , int ReductionSize_ = 1, typename OutputTile_ = Shape<1, 1, 128>, typename SubTile_ = Shape<1, 1, 64>, typename ThreadShape_ = Shape<1, 1, 2>, typename Index_ = int, typename BlockSwizzle_ = DefaultBlockSwizzle, int maxInReg_ = 160, int maxOutReg_ = 64, typename Functor_ = typename cutlass::gemm::LinearScaling<ScalarAlphaBeta_, typename cutlass::gemm::FragmentMultiplyAdd<ScalarAlphaBeta_, ScalarAccum_, (ThreadShape_::kW % 2 == 0)> >> </div>
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<td class="memname"><a class="el" href="structcutlass_1_1reduction_1_1BatchedReductionTraits.html#ab89c35cfce0017a47341a1e3b2894e0f">ScalarAlphaBeta</a> <a class="el" href="structcutlass_1_1reduction_1_1BatchedReductionTraits.html">cutlass::reduction::BatchedReductionTraits</a>< ScalarA_, ScalarC_, ScalarD_, ScalarAlphaBeta_, ScalarAccum_, ReductionSize_, OutputTile_, SubTile_, ThreadShape_, Index_, BlockSwizzle_, maxInReg_, maxOutReg_, Functor_ >::Params::alpha</td>
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template<typename ScalarA_ , typename ScalarC_ , typename ScalarD_ , typename ScalarAlphaBeta_ , typename ScalarAccum_ , int ReductionSize_ = 1, typename OutputTile_ = Shape<1, 1, 128>, typename SubTile_ = Shape<1, 1, 64>, typename ThreadShape_ = Shape<1, 1, 2>, typename Index_ = int, typename BlockSwizzle_ = DefaultBlockSwizzle, int maxInReg_ = 160, int maxOutReg_ = 64, typename Functor_ = typename cutlass::gemm::LinearScaling<ScalarAlphaBeta_, typename cutlass::gemm::FragmentMultiplyAdd<ScalarAlphaBeta_, ScalarAccum_, (ThreadShape_::kW % 2 == 0)> >> </div>
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<td class="memname"><a class="el" href="structcutlass_1_1reduction_1_1BatchedReductionTraits.html#ab89c35cfce0017a47341a1e3b2894e0f">ScalarAlphaBeta</a> <a class="el" href="structcutlass_1_1reduction_1_1BatchedReductionTraits.html">cutlass::reduction::BatchedReductionTraits</a>< ScalarA_, ScalarC_, ScalarD_, ScalarAlphaBeta_, ScalarAccum_, ReductionSize_, OutputTile_, SubTile_, ThreadShape_, Index_, BlockSwizzle_, maxInReg_, maxOutReg_, Functor_ >::Params::beta</td>
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template<typename ScalarA_ , typename ScalarC_ , typename ScalarD_ , typename ScalarAlphaBeta_ , typename ScalarAccum_ , int ReductionSize_ = 1, typename OutputTile_ = Shape<1, 1, 128>, typename SubTile_ = Shape<1, 1, 64>, typename ThreadShape_ = Shape<1, 1, 2>, typename Index_ = int, typename BlockSwizzle_ = DefaultBlockSwizzle, int maxInReg_ = 160, int maxOutReg_ = 64, typename Functor_ = typename cutlass::gemm::LinearScaling<ScalarAlphaBeta_, typename cutlass::gemm::FragmentMultiplyAdd<ScalarAlphaBeta_, ScalarAccum_, (ThreadShape_::kW % 2 == 0)> >> </div>
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<td class="memname"><a class="el" href="structcutlass_1_1reduction_1_1BatchedReductionTraits.html#a1c6cd0a76b2b2fc9cd021b016f30f459">ScalarA</a> const* <a class="el" href="structcutlass_1_1reduction_1_1BatchedReductionTraits.html">cutlass::reduction::BatchedReductionTraits</a>< ScalarA_, ScalarC_, ScalarD_, ScalarAlphaBeta_, ScalarAccum_, ReductionSize_, OutputTile_, SubTile_, ThreadShape_, Index_, BlockSwizzle_, maxInReg_, maxOutReg_, Functor_ >::Params::d_a</td>
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template<typename ScalarA_ , typename ScalarC_ , typename ScalarD_ , typename ScalarAlphaBeta_ , typename ScalarAccum_ , int ReductionSize_ = 1, typename OutputTile_ = Shape<1, 1, 128>, typename SubTile_ = Shape<1, 1, 64>, typename ThreadShape_ = Shape<1, 1, 2>, typename Index_ = int, typename BlockSwizzle_ = DefaultBlockSwizzle, int maxInReg_ = 160, int maxOutReg_ = 64, typename Functor_ = typename cutlass::gemm::LinearScaling<ScalarAlphaBeta_, typename cutlass::gemm::FragmentMultiplyAdd<ScalarAlphaBeta_, ScalarAccum_, (ThreadShape_::kW % 2 == 0)> >> </div>
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<td class="memname"><a class="el" href="structcutlass_1_1reduction_1_1BatchedReductionTraits.html#adb39cf54a839bdb2e38fbc8a0bf304a8">ScalarC</a> const* <a class="el" href="structcutlass_1_1reduction_1_1BatchedReductionTraits.html">cutlass::reduction::BatchedReductionTraits</a>< ScalarA_, ScalarC_, ScalarD_, ScalarAlphaBeta_, ScalarAccum_, ReductionSize_, OutputTile_, SubTile_, ThreadShape_, Index_, BlockSwizzle_, maxInReg_, maxOutReg_, Functor_ >::Params::d_c</td>
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template<typename ScalarA_ , typename ScalarC_ , typename ScalarD_ , typename ScalarAlphaBeta_ , typename ScalarAccum_ , int ReductionSize_ = 1, typename OutputTile_ = Shape<1, 1, 128>, typename SubTile_ = Shape<1, 1, 64>, typename ThreadShape_ = Shape<1, 1, 2>, typename Index_ = int, typename BlockSwizzle_ = DefaultBlockSwizzle, int maxInReg_ = 160, int maxOutReg_ = 64, typename Functor_ = typename cutlass::gemm::LinearScaling<ScalarAlphaBeta_, typename cutlass::gemm::FragmentMultiplyAdd<ScalarAlphaBeta_, ScalarAccum_, (ThreadShape_::kW % 2 == 0)> >> </div>
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<td class="memname"><a class="el" href="structcutlass_1_1reduction_1_1BatchedReductionTraits.html#abb54e3addfee4097b37deb5cb30fb582">ScalarD</a>* <a class="el" href="structcutlass_1_1reduction_1_1BatchedReductionTraits.html">cutlass::reduction::BatchedReductionTraits</a>< ScalarA_, ScalarC_, ScalarD_, ScalarAlphaBeta_, ScalarAccum_, ReductionSize_, OutputTile_, SubTile_, ThreadShape_, Index_, BlockSwizzle_, maxInReg_, maxOutReg_, Functor_ >::Params::d_d</td>
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template<typename ScalarA_ , typename ScalarC_ , typename ScalarD_ , typename ScalarAlphaBeta_ , typename ScalarAccum_ , int ReductionSize_ = 1, typename OutputTile_ = Shape<1, 1, 128>, typename SubTile_ = Shape<1, 1, 64>, typename ThreadShape_ = Shape<1, 1, 2>, typename Index_ = int, typename BlockSwizzle_ = DefaultBlockSwizzle, int maxInReg_ = 160, int maxOutReg_ = 64, typename Functor_ = typename cutlass::gemm::LinearScaling<ScalarAlphaBeta_, typename cutlass::gemm::FragmentMultiplyAdd<ScalarAlphaBeta_, ScalarAccum_, (ThreadShape_::kW % 2 == 0)> >> </div>
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<td class="memname">Functor::Params <a class="el" href="structcutlass_1_1reduction_1_1BatchedReductionTraits.html">cutlass::reduction::BatchedReductionTraits</a>< ScalarA_, ScalarC_, ScalarD_, ScalarAlphaBeta_, ScalarAccum_, ReductionSize_, OutputTile_, SubTile_, ThreadShape_, Index_, BlockSwizzle_, maxInReg_, maxOutReg_, Functor_ >::Params::functorParams</td>
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template<typename ScalarA_ , typename ScalarC_ , typename ScalarD_ , typename ScalarAlphaBeta_ , typename ScalarAccum_ , int ReductionSize_ = 1, typename OutputTile_ = Shape<1, 1, 128>, typename SubTile_ = Shape<1, 1, 64>, typename ThreadShape_ = Shape<1, 1, 2>, typename Index_ = int, typename BlockSwizzle_ = DefaultBlockSwizzle, int maxInReg_ = 160, int maxOutReg_ = 64, typename Functor_ = typename cutlass::gemm::LinearScaling<ScalarAlphaBeta_, typename cutlass::gemm::FragmentMultiplyAdd<ScalarAlphaBeta_, ScalarAccum_, (ThreadShape_::kW % 2 == 0)> >> </div>
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<td class="memname"><a class="el" href="structcutlass_1_1reduction_1_1BatchedReductionTraits.html#ab0c9e548f3ee62746e727127e387a8f4">Index</a> <a class="el" href="structcutlass_1_1reduction_1_1BatchedReductionTraits.html">cutlass::reduction::BatchedReductionTraits</a>< ScalarA_, ScalarC_, ScalarD_, ScalarAlphaBeta_, ScalarAccum_, ReductionSize_, OutputTile_, SubTile_, ThreadShape_, Index_, BlockSwizzle_, maxInReg_, maxOutReg_, Functor_ >::Params::lda</td>
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template<typename ScalarA_ , typename ScalarC_ , typename ScalarD_ , typename ScalarAlphaBeta_ , typename ScalarAccum_ , int ReductionSize_ = 1, typename OutputTile_ = Shape<1, 1, 128>, typename SubTile_ = Shape<1, 1, 64>, typename ThreadShape_ = Shape<1, 1, 2>, typename Index_ = int, typename BlockSwizzle_ = DefaultBlockSwizzle, int maxInReg_ = 160, int maxOutReg_ = 64, typename Functor_ = typename cutlass::gemm::LinearScaling<ScalarAlphaBeta_, typename cutlass::gemm::FragmentMultiplyAdd<ScalarAlphaBeta_, ScalarAccum_, (ThreadShape_::kW % 2 == 0)> >> </div>
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<td class="memname"><a class="el" href="structcutlass_1_1reduction_1_1BatchedReductionTraits.html#ab0c9e548f3ee62746e727127e387a8f4">Index</a> <a class="el" href="structcutlass_1_1reduction_1_1BatchedReductionTraits.html">cutlass::reduction::BatchedReductionTraits</a>< ScalarA_, ScalarC_, ScalarD_, ScalarAlphaBeta_, ScalarAccum_, ReductionSize_, OutputTile_, SubTile_, ThreadShape_, Index_, BlockSwizzle_, maxInReg_, maxOutReg_, Functor_ >::Params::ldc</td>
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template<typename ScalarA_ , typename ScalarC_ , typename ScalarD_ , typename ScalarAlphaBeta_ , typename ScalarAccum_ , int ReductionSize_ = 1, typename OutputTile_ = Shape<1, 1, 128>, typename SubTile_ = Shape<1, 1, 64>, typename ThreadShape_ = Shape<1, 1, 2>, typename Index_ = int, typename BlockSwizzle_ = DefaultBlockSwizzle, int maxInReg_ = 160, int maxOutReg_ = 64, typename Functor_ = typename cutlass::gemm::LinearScaling<ScalarAlphaBeta_, typename cutlass::gemm::FragmentMultiplyAdd<ScalarAlphaBeta_, ScalarAccum_, (ThreadShape_::kW % 2 == 0)> >> </div>
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<td class="memname"><a class="el" href="structcutlass_1_1reduction_1_1BatchedReductionTraits.html#ab0c9e548f3ee62746e727127e387a8f4">Index</a> <a class="el" href="structcutlass_1_1reduction_1_1BatchedReductionTraits.html">cutlass::reduction::BatchedReductionTraits</a>< ScalarA_, ScalarC_, ScalarD_, ScalarAlphaBeta_, ScalarAccum_, ReductionSize_, OutputTile_, SubTile_, ThreadShape_, Index_, BlockSwizzle_, maxInReg_, maxOutReg_, Functor_ >::Params::ldd</td>
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<h2 class="memtitle"><span class="permalink"><a href="#adbd0cf20c4f7033016d1b8fdaca6aeae">◆ </a></span>problem_size</h2>
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template<typename ScalarA_ , typename ScalarC_ , typename ScalarD_ , typename ScalarAlphaBeta_ , typename ScalarAccum_ , int ReductionSize_ = 1, typename OutputTile_ = Shape<1, 1, 128>, typename SubTile_ = Shape<1, 1, 64>, typename ThreadShape_ = Shape<1, 1, 2>, typename Index_ = int, typename BlockSwizzle_ = DefaultBlockSwizzle, int maxInReg_ = 160, int maxOutReg_ = 64, typename Functor_ = typename cutlass::gemm::LinearScaling<ScalarAlphaBeta_, typename cutlass::gemm::FragmentMultiplyAdd<ScalarAlphaBeta_, ScalarAccum_, (ThreadShape_::kW % 2 == 0)> >> </div>
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<td class="memname"><a class="el" href="structcutlass_1_1Coord.html">Coord</a><3> <a class="el" href="structcutlass_1_1reduction_1_1BatchedReductionTraits.html">cutlass::reduction::BatchedReductionTraits</a>< ScalarA_, ScalarC_, ScalarD_, ScalarAlphaBeta_, ScalarAccum_, ReductionSize_, OutputTile_, SubTile_, ThreadShape_, Index_, BlockSwizzle_, maxInReg_, maxOutReg_, Functor_ >::Params::problem_size</td>
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<h2 class="memtitle"><span class="permalink"><a href="#a5d1463d473d4226b0d19c581b16ed3b2">◆ </a></span>reduction_stride</h2>
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template<typename ScalarA_ , typename ScalarC_ , typename ScalarD_ , typename ScalarAlphaBeta_ , typename ScalarAccum_ , int ReductionSize_ = 1, typename OutputTile_ = Shape<1, 1, 128>, typename SubTile_ = Shape<1, 1, 64>, typename ThreadShape_ = Shape<1, 1, 2>, typename Index_ = int, typename BlockSwizzle_ = DefaultBlockSwizzle, int maxInReg_ = 160, int maxOutReg_ = 64, typename Functor_ = typename cutlass::gemm::LinearScaling<ScalarAlphaBeta_, typename cutlass::gemm::FragmentMultiplyAdd<ScalarAlphaBeta_, ScalarAccum_, (ThreadShape_::kW % 2 == 0)> >> </div>
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<td class="memname">long long int <a class="el" href="structcutlass_1_1reduction_1_1BatchedReductionTraits.html">cutlass::reduction::BatchedReductionTraits</a>< ScalarA_, ScalarC_, ScalarD_, ScalarAlphaBeta_, ScalarAccum_, ReductionSize_, OutputTile_, SubTile_, ThreadShape_, Index_, BlockSwizzle_, maxInReg_, maxOutReg_, Functor_ >::Params::reduction_stride</td>
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<hr/>The documentation for this struct was generated from the following file:<ul>
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<li><a class="el" href="batched__reduction__traits_8h_source.html">batched_reduction_traits.h</a></li>
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