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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.
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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.
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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.
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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.
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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.
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<div id="projectbrief">CUDA Templates for Linear Algebra Subroutines and Solvers</div>
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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.
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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.
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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.
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<li class="navelem"><a class="el" href="dir_d44c64559bbebec7f509842c48db8b23.html">include</a></li><li class="navelem"><a class="el" href="dir_6baf2bb612a2f0daa69af3101ede80a1.html">cutlass</a></li> </ul>
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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.
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<div class="title">complex.h File Reference</div> </div>
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<div class="textblock"><code>#include &lt;cuComplex.h&gt;</code><br />
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.
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<code>#include &lt;cstdint&gt;</code><br />
Updated doxygen
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<code>#include &quot;<a class="el" href="cutlass_8h_source.html">cutlass/cutlass.h</a>&quot;</code><br />
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.
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<code>#include &quot;<a class="el" href="half_8h_source.html">cutlass/half.h</a>&quot;</code><br />
<code>#include &quot;<a class="el" href="real_8h_source.html">cutlass/real.h</a>&quot;</code><br />
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<code>#include &lt;iosfwd&gt;</code><br />
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.
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<p><a href="complex_8h_source.html">Go to the source code of this file.</a></p>
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Classes</h2></td></tr>
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.
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<tr class="memitem:"><td class="memItemLeft" align="right" valign="top">class &#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classcutlass_1_1complex.html">cutlass::complex&lt; T &gt;</a></td></tr>
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<tr class="memitem:"><td class="memItemLeft" align="right" valign="top">struct &#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="structcutlass_1_1RealType_3_01complex_3_01T_01_4_01_4.html">cutlass::RealType&lt; complex&lt; T &gt; &gt;</a></td></tr>
<tr class="memdesc:"><td class="mdescLeft">&#160;</td><td class="mdescRight">Partial specialization for complex-valued type. <a href="structcutlass_1_1RealType_3_01complex_3_01T_01_4_01_4.html#details">More...</a><br /></td></tr>
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Namespaces</h2></td></tr>
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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.
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</table><table class="memberdecls">
<tr class="heading"><td colspan="2"><h2 class="groupheader"><a name="enum-members"></a>
Enumerations</h2></td></tr>
<tr class="memitem:a59f08b1b99c4d52257b962d35ba55cde"><td class="memItemLeft" align="right" valign="top">enum &#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="namespacecutlass.html#a59f08b1b99c4d52257b962d35ba55cde">cutlass::ComplexTransform</a> { <a class="el" href="namespacecutlass.html#a59f08b1b99c4d52257b962d35ba55cdea35c3ace1970663a16e5c65baa5941b13">cutlass::ComplexTransform::kNone</a>,
<a class="el" href="namespacecutlass.html#a59f08b1b99c4d52257b962d35ba55cdea8be1522542c86e700b5e787b1aabc70b">cutlass::ComplexTransform::kConjugate</a>
}<tr class="memdesc:a59f08b1b99c4d52257b962d35ba55cde"><td class="mdescLeft">&#160;</td><td class="mdescRight">Enumeraed type describing a transformation on a complex value. <a href="namespacecutlass.html#a59f08b1b99c4d52257b962d35ba55cde">More...</a><br /></td></tr>
</td></tr>
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Updated doxygen
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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.
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<tr class="memitem:ac0ea92c9a2a594446a84f7f86a79e143"><td class="memItemLeft" align="right" valign="top"><a class="el" href="cutlass_8h.html#a28c2443a142676d3d71effdae1a986b1">CUTLASS_HOST_DEVICE</a> float const &amp;&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="namespacecutlass.html#ac0ea92c9a2a594446a84f7f86a79e143">cutlass::real</a> (cuFloatComplex const &amp;z)</td></tr>
<tr class="memdesc:ac0ea92c9a2a594446a84f7f86a79e143"><td class="mdescLeft">&#160;</td><td class="mdescRight">Returns the real part of the complex number. <a href="namespacecutlass.html#ac0ea92c9a2a594446a84f7f86a79e143">More...</a><br /></td></tr>
<tr class="separator:ac0ea92c9a2a594446a84f7f86a79e143"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:a8fd098f5be681292ce2051ce171f0aa5"><td class="memItemLeft" align="right" valign="top"><a class="el" href="cutlass_8h.html#a28c2443a142676d3d71effdae1a986b1">CUTLASS_HOST_DEVICE</a> float &amp;&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="namespacecutlass.html#a8fd098f5be681292ce2051ce171f0aa5">cutlass::real</a> (cuFloatComplex &amp;z)</td></tr>
<tr class="memdesc:a8fd098f5be681292ce2051ce171f0aa5"><td class="mdescLeft">&#160;</td><td class="mdescRight">Returns the real part of the complex number. <a href="namespacecutlass.html#a8fd098f5be681292ce2051ce171f0aa5">More...</a><br /></td></tr>
<tr class="separator:a8fd098f5be681292ce2051ce171f0aa5"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:ae0cde0dbf619d61fcbeed8bf9f21c6ca"><td class="memItemLeft" align="right" valign="top"><a class="el" href="cutlass_8h.html#a28c2443a142676d3d71effdae1a986b1">CUTLASS_HOST_DEVICE</a> double const &amp;&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="namespacecutlass.html#ae0cde0dbf619d61fcbeed8bf9f21c6ca">cutlass::real</a> (cuDoubleComplex const &amp;z)</td></tr>
<tr class="memdesc:ae0cde0dbf619d61fcbeed8bf9f21c6ca"><td class="mdescLeft">&#160;</td><td class="mdescRight">Returns the real part of the complex number. <a href="namespacecutlass.html#ae0cde0dbf619d61fcbeed8bf9f21c6ca">More...</a><br /></td></tr>
<tr class="separator:ae0cde0dbf619d61fcbeed8bf9f21c6ca"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:a2ccc4e86a30fe5337bc3664e6bcd1bb4"><td class="memItemLeft" align="right" valign="top"><a class="el" href="cutlass_8h.html#a28c2443a142676d3d71effdae1a986b1">CUTLASS_HOST_DEVICE</a> double &amp;&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="namespacecutlass.html#a2ccc4e86a30fe5337bc3664e6bcd1bb4">cutlass::real</a> (cuDoubleComplex &amp;z)</td></tr>
<tr class="memdesc:a2ccc4e86a30fe5337bc3664e6bcd1bb4"><td class="mdescLeft">&#160;</td><td class="mdescRight">Returns the real part of the complex number. <a href="namespacecutlass.html#a2ccc4e86a30fe5337bc3664e6bcd1bb4">More...</a><br /></td></tr>
<tr class="separator:a2ccc4e86a30fe5337bc3664e6bcd1bb4"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:a236d41e43fc97943fb2412fcbb40aec1"><td class="memItemLeft" align="right" valign="top"><a class="el" href="cutlass_8h.html#a28c2443a142676d3d71effdae1a986b1">CUTLASS_HOST_DEVICE</a> float const &amp;&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="namespacecutlass.html#a236d41e43fc97943fb2412fcbb40aec1">cutlass::imag</a> (cuFloatComplex const &amp;z)</td></tr>
<tr class="memdesc:a236d41e43fc97943fb2412fcbb40aec1"><td class="mdescLeft">&#160;</td><td class="mdescRight">Returns the imaginary part of the complex number. <a href="namespacecutlass.html#a236d41e43fc97943fb2412fcbb40aec1">More...</a><br /></td></tr>
<tr class="separator:a236d41e43fc97943fb2412fcbb40aec1"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:ad6975e38412bb0d0cae679747768836d"><td class="memItemLeft" align="right" valign="top"><a class="el" href="cutlass_8h.html#a28c2443a142676d3d71effdae1a986b1">CUTLASS_HOST_DEVICE</a> float &amp;&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="namespacecutlass.html#ad6975e38412bb0d0cae679747768836d">cutlass::imag</a> (cuFloatComplex &amp;z)</td></tr>
<tr class="memdesc:ad6975e38412bb0d0cae679747768836d"><td class="mdescLeft">&#160;</td><td class="mdescRight">Returns the imaginary part of the complex number. <a href="namespacecutlass.html#ad6975e38412bb0d0cae679747768836d">More...</a><br /></td></tr>
<tr class="separator:ad6975e38412bb0d0cae679747768836d"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:a38dd941a4f22a75d902bc8384b663fd4"><td class="memItemLeft" align="right" valign="top"><a class="el" href="cutlass_8h.html#a28c2443a142676d3d71effdae1a986b1">CUTLASS_HOST_DEVICE</a> double const &amp;&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="namespacecutlass.html#a38dd941a4f22a75d902bc8384b663fd4">cutlass::imag</a> (cuDoubleComplex const &amp;z)</td></tr>
<tr class="memdesc:a38dd941a4f22a75d902bc8384b663fd4"><td class="mdescLeft">&#160;</td><td class="mdescRight">Returns the imaginary part of the complex number. <a href="namespacecutlass.html#a38dd941a4f22a75d902bc8384b663fd4">More...</a><br /></td></tr>
<tr class="separator:a38dd941a4f22a75d902bc8384b663fd4"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:a6b4672114b504719d4b3925dc4fec203"><td class="memItemLeft" align="right" valign="top"><a class="el" href="cutlass_8h.html#a28c2443a142676d3d71effdae1a986b1">CUTLASS_HOST_DEVICE</a> double &amp;&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="namespacecutlass.html#a6b4672114b504719d4b3925dc4fec203">cutlass::imag</a> (cuDoubleComplex &amp;z)</td></tr>
<tr class="memdesc:a6b4672114b504719d4b3925dc4fec203"><td class="mdescLeft">&#160;</td><td class="mdescRight">Returns the imaginary part of the complex number. <a href="namespacecutlass.html#a6b4672114b504719d4b3925dc4fec203">More...</a><br /></td></tr>
<tr class="separator:a6b4672114b504719d4b3925dc4fec203"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:a8538ac12cfc174e0965cabfe6bd3d859"><td class="memTemplParams" colspan="2">template&lt;typename T &gt; </td></tr>
<tr class="memitem:a8538ac12cfc174e0965cabfe6bd3d859"><td class="memTemplItemLeft" align="right" valign="top"><a class="el" href="cutlass_8h.html#a28c2443a142676d3d71effdae1a986b1">CUTLASS_HOST_DEVICE</a> T const &amp;&#160;</td><td class="memTemplItemRight" valign="bottom"><a class="el" href="namespacecutlass.html#a8538ac12cfc174e0965cabfe6bd3d859">cutlass::real</a> (complex&lt; T &gt; const &amp;z)</td></tr>
<tr class="memdesc:a8538ac12cfc174e0965cabfe6bd3d859"><td class="mdescLeft">&#160;</td><td class="mdescRight">Returns the real part of the complex number. <a href="namespacecutlass.html#a8538ac12cfc174e0965cabfe6bd3d859">More...</a><br /></td></tr>
<tr class="separator:a8538ac12cfc174e0965cabfe6bd3d859"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:a491c61e7a51c2efdc93c61a549e20eb6"><td class="memTemplParams" colspan="2">template&lt;typename T &gt; </td></tr>
<tr class="memitem:a491c61e7a51c2efdc93c61a549e20eb6"><td class="memTemplItemLeft" align="right" valign="top"><a class="el" href="cutlass_8h.html#a28c2443a142676d3d71effdae1a986b1">CUTLASS_HOST_DEVICE</a> T &amp;&#160;</td><td class="memTemplItemRight" valign="bottom"><a class="el" href="namespacecutlass.html#a491c61e7a51c2efdc93c61a549e20eb6">cutlass::real</a> (complex&lt; T &gt; &amp;z)</td></tr>
<tr class="memdesc:a491c61e7a51c2efdc93c61a549e20eb6"><td class="mdescLeft">&#160;</td><td class="mdescRight">Returns the real part of the complex number. <a href="namespacecutlass.html#a491c61e7a51c2efdc93c61a549e20eb6">More...</a><br /></td></tr>
<tr class="separator:a491c61e7a51c2efdc93c61a549e20eb6"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:ae0b2f240ec391709671b3561d04b2826"><td class="memTemplParams" colspan="2">template&lt;typename T &gt; </td></tr>
<tr class="memitem:ae0b2f240ec391709671b3561d04b2826"><td class="memTemplItemLeft" align="right" valign="top"><a class="el" href="cutlass_8h.html#a28c2443a142676d3d71effdae1a986b1">CUTLASS_HOST_DEVICE</a> T const &amp;&#160;</td><td class="memTemplItemRight" valign="bottom"><a class="el" href="namespacecutlass.html#ae0b2f240ec391709671b3561d04b2826">cutlass::imag</a> (complex&lt; T &gt; const &amp;z)</td></tr>
<tr class="memdesc:ae0b2f240ec391709671b3561d04b2826"><td class="mdescLeft">&#160;</td><td class="mdescRight">Returns the imaginary part of the complex number. <a href="namespacecutlass.html#ae0b2f240ec391709671b3561d04b2826">More...</a><br /></td></tr>
<tr class="separator:ae0b2f240ec391709671b3561d04b2826"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:ae84f289e03399a5393c184ce6f6ea25b"><td class="memTemplParams" colspan="2">template&lt;typename T &gt; </td></tr>
<tr class="memitem:ae84f289e03399a5393c184ce6f6ea25b"><td class="memTemplItemLeft" align="right" valign="top"><a class="el" href="cutlass_8h.html#a28c2443a142676d3d71effdae1a986b1">CUTLASS_HOST_DEVICE</a> T &amp;&#160;</td><td class="memTemplItemRight" valign="bottom"><a class="el" href="namespacecutlass.html#ae84f289e03399a5393c184ce6f6ea25b">cutlass::imag</a> (complex&lt; T &gt; &amp;z)</td></tr>
<tr class="memdesc:ae84f289e03399a5393c184ce6f6ea25b"><td class="mdescLeft">&#160;</td><td class="mdescRight">Returns the imaginary part of the complex number. <a href="namespacecutlass.html#ae84f289e03399a5393c184ce6f6ea25b">More...</a><br /></td></tr>
<tr class="separator:ae84f289e03399a5393c184ce6f6ea25b"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:addd443fc82f2acf867a61acff6c1cd29"><td class="memTemplParams" colspan="2">template&lt;typename T &gt; </td></tr>
<tr class="memitem:addd443fc82f2acf867a61acff6c1cd29"><td class="memTemplItemLeft" align="right" valign="top">std::ostream &amp;&#160;</td><td class="memTemplItemRight" valign="bottom"><a class="el" href="namespacecutlass.html#addd443fc82f2acf867a61acff6c1cd29">cutlass::operator&lt;&lt;</a> (std::ostream &amp;out, complex&lt; T &gt; const &amp;z)</td></tr>
<tr class="separator:addd443fc82f2acf867a61acff6c1cd29"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:a512b1ef2b0213d48738cac7bbb87a98e"><td class="memTemplParams" colspan="2">template&lt;typename T &gt; </td></tr>
<tr class="memitem:a512b1ef2b0213d48738cac7bbb87a98e"><td class="memTemplItemLeft" align="right" valign="top"><a class="el" href="cutlass_8h.html#a28c2443a142676d3d71effdae1a986b1">CUTLASS_HOST_DEVICE</a> T&#160;</td><td class="memTemplItemRight" valign="bottom"><a class="el" href="namespacecutlass.html#a512b1ef2b0213d48738cac7bbb87a98e">cutlass::abs</a> (complex&lt; T &gt; const &amp;z)</td></tr>
<tr class="memdesc:a512b1ef2b0213d48738cac7bbb87a98e"><td class="mdescLeft">&#160;</td><td class="mdescRight">Returns the magnitude of the complex number. <a href="namespacecutlass.html#a512b1ef2b0213d48738cac7bbb87a98e">More...</a><br /></td></tr>
<tr class="separator:a512b1ef2b0213d48738cac7bbb87a98e"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:a2d34a68d49bf2a35de81b6600425b645"><td class="memTemplParams" colspan="2">template&lt;typename T &gt; </td></tr>
<tr class="memitem:a2d34a68d49bf2a35de81b6600425b645"><td class="memTemplItemLeft" align="right" valign="top"><a class="el" href="cutlass_8h.html#a28c2443a142676d3d71effdae1a986b1">CUTLASS_HOST_DEVICE</a> T&#160;</td><td class="memTemplItemRight" valign="bottom"><a class="el" href="namespacecutlass.html#a2d34a68d49bf2a35de81b6600425b645">cutlass::arg</a> (complex&lt; T &gt; const &amp;z)</td></tr>
<tr class="memdesc:a2d34a68d49bf2a35de81b6600425b645"><td class="mdescLeft">&#160;</td><td class="mdescRight">Returns the magnitude of the complex number. <a href="namespacecutlass.html#a2d34a68d49bf2a35de81b6600425b645">More...</a><br /></td></tr>
<tr class="separator:a2d34a68d49bf2a35de81b6600425b645"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:a8d529517dadbc9ff697183cfb3e9a21f"><td class="memTemplParams" colspan="2">template&lt;typename T &gt; </td></tr>
<tr class="memitem:a8d529517dadbc9ff697183cfb3e9a21f"><td class="memTemplItemLeft" align="right" valign="top"><a class="el" href="cutlass_8h.html#a28c2443a142676d3d71effdae1a986b1">CUTLASS_HOST_DEVICE</a> T&#160;</td><td class="memTemplItemRight" valign="bottom"><a class="el" href="namespacecutlass.html#a8d529517dadbc9ff697183cfb3e9a21f">cutlass::norm</a> (T const &amp;z)</td></tr>
<tr class="memdesc:a8d529517dadbc9ff697183cfb3e9a21f"><td class="mdescLeft">&#160;</td><td class="mdescRight">Returns the squared magnitude of a real number. <a href="namespacecutlass.html#a8d529517dadbc9ff697183cfb3e9a21f">More...</a><br /></td></tr>
<tr class="separator:a8d529517dadbc9ff697183cfb3e9a21f"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:ac6da2f4c8e675ef7c53cffeb04ccaff1"><td class="memTemplParams" colspan="2">template&lt;&gt; </td></tr>
<tr class="memitem:ac6da2f4c8e675ef7c53cffeb04ccaff1"><td class="memTemplItemLeft" align="right" valign="top"><a class="el" href="cutlass_8h.html#a28c2443a142676d3d71effdae1a986b1">CUTLASS_HOST_DEVICE</a> int8_t&#160;</td><td class="memTemplItemRight" valign="bottom"><a class="el" href="namespacecutlass.html#ac6da2f4c8e675ef7c53cffeb04ccaff1">cutlass::norm</a> (int8_t const &amp;z)</td></tr>
<tr class="memdesc:ac6da2f4c8e675ef7c53cffeb04ccaff1"><td class="mdescLeft">&#160;</td><td class="mdescRight">Returns the squared magnitude of a real number. <a href="namespacecutlass.html#ac6da2f4c8e675ef7c53cffeb04ccaff1">More...</a><br /></td></tr>
<tr class="separator:ac6da2f4c8e675ef7c53cffeb04ccaff1"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:a462c9f7d686d23a0a764a773c9af2f47"><td class="memTemplParams" colspan="2">template&lt;typename T &gt; </td></tr>
<tr class="memitem:a462c9f7d686d23a0a764a773c9af2f47"><td class="memTemplItemLeft" align="right" valign="top"><a class="el" href="cutlass_8h.html#a28c2443a142676d3d71effdae1a986b1">CUTLASS_HOST_DEVICE</a> double&#160;</td><td class="memTemplItemRight" valign="bottom"><a class="el" href="namespacecutlass.html#a462c9f7d686d23a0a764a773c9af2f47">cutlass::norm</a> (complex&lt; T &gt; const &amp;z)</td></tr>
<tr class="memdesc:a462c9f7d686d23a0a764a773c9af2f47"><td class="mdescLeft">&#160;</td><td class="mdescRight">Returns the squared magnitude of a complex number. <a href="namespacecutlass.html#a462c9f7d686d23a0a764a773c9af2f47">More...</a><br /></td></tr>
<tr class="separator:a462c9f7d686d23a0a764a773c9af2f47"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:a326d3123e33cfd02c4e7ad519c56561f"><td class="memTemplParams" colspan="2">template&lt;typename T , typename R &gt; </td></tr>
<tr class="memitem:a326d3123e33cfd02c4e7ad519c56561f"><td class="memTemplItemLeft" align="right" valign="top"><a class="el" href="cutlass_8h.html#a28c2443a142676d3d71effdae1a986b1">CUTLASS_HOST_DEVICE</a> R&#160;</td><td class="memTemplItemRight" valign="bottom"><a class="el" href="namespacecutlass.html#a326d3123e33cfd02c4e7ad519c56561f">cutlass::norm_accumulate</a> (T const &amp;x, R const &amp;accumulator)</td></tr>
<tr class="memdesc:a326d3123e33cfd02c4e7ad519c56561f"><td class="mdescLeft">&#160;</td><td class="mdescRight">Norm-accumulate calculation. <a href="namespacecutlass.html#a326d3123e33cfd02c4e7ad519c56561f">More...</a><br /></td></tr>
<tr class="separator:a326d3123e33cfd02c4e7ad519c56561f"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:a47fce4c8a33798ec16ad04e8c8bc651d"><td class="memTemplParams" colspan="2">template&lt;typename T , typename R &gt; </td></tr>
<tr class="memitem:a47fce4c8a33798ec16ad04e8c8bc651d"><td class="memTemplItemLeft" align="right" valign="top"><a class="el" href="cutlass_8h.html#a28c2443a142676d3d71effdae1a986b1">CUTLASS_HOST_DEVICE</a> R&#160;</td><td class="memTemplItemRight" valign="bottom"><a class="el" href="namespacecutlass.html#a47fce4c8a33798ec16ad04e8c8bc651d">cutlass::norm_accumulate</a> (complex&lt; T &gt; const &amp;z, R const &amp;accumulator)</td></tr>
<tr class="memdesc:a47fce4c8a33798ec16ad04e8c8bc651d"><td class="mdescLeft">&#160;</td><td class="mdescRight">Norm accumulate specialized for complex types. <a href="namespacecutlass.html#a47fce4c8a33798ec16ad04e8c8bc651d">More...</a><br /></td></tr>
<tr class="separator:a47fce4c8a33798ec16ad04e8c8bc651d"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:adba9348e32642fa40c186b5ca6e5ba4e"><td class="memTemplParams" colspan="2">template&lt;typename T &gt; </td></tr>
<tr class="memitem:adba9348e32642fa40c186b5ca6e5ba4e"><td class="memTemplItemLeft" align="right" valign="top"><a class="el" href="cutlass_8h.html#a28c2443a142676d3d71effdae1a986b1">CUTLASS_HOST_DEVICE</a> complex&lt; T &gt;&#160;</td><td class="memTemplItemRight" valign="bottom"><a class="el" href="namespacecutlass.html#adba9348e32642fa40c186b5ca6e5ba4e">cutlass::conj</a> (complex&lt; T &gt; const &amp;z)</td></tr>
<tr class="memdesc:adba9348e32642fa40c186b5ca6e5ba4e"><td class="mdescLeft">&#160;</td><td class="mdescRight">Returns the complex conjugate. <a href="namespacecutlass.html#adba9348e32642fa40c186b5ca6e5ba4e">More...</a><br /></td></tr>
<tr class="separator:adba9348e32642fa40c186b5ca6e5ba4e"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:a325f724545a11d64c5353664a1494ab2"><td class="memTemplParams" colspan="2">template&lt;typename T &gt; </td></tr>
<tr class="memitem:a325f724545a11d64c5353664a1494ab2"><td class="memTemplItemLeft" align="right" valign="top"><a class="el" href="cutlass_8h.html#a28c2443a142676d3d71effdae1a986b1">CUTLASS_HOST_DEVICE</a> complex&lt; T &gt;&#160;</td><td class="memTemplItemRight" valign="bottom"><a class="el" href="namespacecutlass.html#a325f724545a11d64c5353664a1494ab2">cutlass::proj</a> (complex&lt; T &gt; const &amp;z)</td></tr>
<tr class="memdesc:a325f724545a11d64c5353664a1494ab2"><td class="mdescLeft">&#160;</td><td class="mdescRight">Projects the complex number z onto the Riemann sphere. <a href="namespacecutlass.html#a325f724545a11d64c5353664a1494ab2">More...</a><br /></td></tr>
<tr class="separator:a325f724545a11d64c5353664a1494ab2"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:a7bd7a35ae6ef9c350ae342b8c75958c5"><td class="memTemplParams" colspan="2">template&lt;typename T &gt; </td></tr>
<tr class="memitem:a7bd7a35ae6ef9c350ae342b8c75958c5"><td class="memTemplItemLeft" align="right" valign="top"><a class="el" href="cutlass_8h.html#a28c2443a142676d3d71effdae1a986b1">CUTLASS_HOST_DEVICE</a> complex&lt; T &gt;&#160;</td><td class="memTemplItemRight" valign="bottom"><a class="el" href="namespacecutlass.html#a7bd7a35ae6ef9c350ae342b8c75958c5">cutlass::polar</a> (T const &amp;r, T const &amp;theta=T())</td></tr>
<tr class="memdesc:a7bd7a35ae6ef9c350ae342b8c75958c5"><td class="mdescLeft">&#160;</td><td class="mdescRight">Returns a complex number with magnitude r and phase theta. <a href="namespacecutlass.html#a7bd7a35ae6ef9c350ae342b8c75958c5">More...</a><br /></td></tr>
<tr class="separator:a7bd7a35ae6ef9c350ae342b8c75958c5"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:a05d95f26c93a6d956d770f140469ac07"><td class="memTemplParams" colspan="2">template&lt;typename T &gt; </td></tr>
<tr class="memitem:a05d95f26c93a6d956d770f140469ac07"><td class="memTemplItemLeft" align="right" valign="top"><a class="el" href="cutlass_8h.html#a28c2443a142676d3d71effdae1a986b1">CUTLASS_HOST_DEVICE</a> complex&lt; T &gt;&#160;</td><td class="memTemplItemRight" valign="bottom"><a class="el" href="namespacecutlass.html#a05d95f26c93a6d956d770f140469ac07">cutlass::exp</a> (complex&lt; T &gt; const &amp;z)</td></tr>
<tr class="memdesc:a05d95f26c93a6d956d770f140469ac07"><td class="mdescLeft">&#160;</td><td class="mdescRight">Computes the complex exponential of z. <a href="namespacecutlass.html#a05d95f26c93a6d956d770f140469ac07">More...</a><br /></td></tr>
<tr class="separator:a05d95f26c93a6d956d770f140469ac07"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:a67f9e83dd59615eff837ea66984c121c"><td class="memTemplParams" colspan="2">template&lt;typename T &gt; </td></tr>
<tr class="memitem:a67f9e83dd59615eff837ea66984c121c"><td class="memTemplItemLeft" align="right" valign="top"><a class="el" href="cutlass_8h.html#a28c2443a142676d3d71effdae1a986b1">CUTLASS_HOST_DEVICE</a> complex&lt; T &gt;&#160;</td><td class="memTemplItemRight" valign="bottom"><a class="el" href="namespacecutlass.html#a67f9e83dd59615eff837ea66984c121c">cutlass::log</a> (complex&lt; T &gt; const &amp;z)</td></tr>
<tr class="memdesc:a67f9e83dd59615eff837ea66984c121c"><td class="mdescLeft">&#160;</td><td class="mdescRight">Computes the complex exponential of z. <a href="namespacecutlass.html#a67f9e83dd59615eff837ea66984c121c">More...</a><br /></td></tr>
<tr class="separator:a67f9e83dd59615eff837ea66984c121c"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:aaa5f2bd47498161eb6cde61ff0461b59"><td class="memTemplParams" colspan="2">template&lt;typename T &gt; </td></tr>
<tr class="memitem:aaa5f2bd47498161eb6cde61ff0461b59"><td class="memTemplItemLeft" align="right" valign="top"><a class="el" href="cutlass_8h.html#a28c2443a142676d3d71effdae1a986b1">CUTLASS_HOST_DEVICE</a> complex&lt; T &gt;&#160;</td><td class="memTemplItemRight" valign="bottom"><a class="el" href="namespacecutlass.html#aaa5f2bd47498161eb6cde61ff0461b59">cutlass::log10</a> (complex&lt; T &gt; const &amp;z)</td></tr>
<tr class="memdesc:aaa5f2bd47498161eb6cde61ff0461b59"><td class="mdescLeft">&#160;</td><td class="mdescRight">Computes the complex exponential of z. <a href="namespacecutlass.html#aaa5f2bd47498161eb6cde61ff0461b59">More...</a><br /></td></tr>
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<tr class="memitem:a28f05d94dbdfc97cddbeab3a5d23839d"><td class="memTemplParams" colspan="2">template&lt;typename T &gt; </td></tr>
<tr class="memitem:a28f05d94dbdfc97cddbeab3a5d23839d"><td class="memTemplItemLeft" align="right" valign="top"><a class="el" href="cutlass_8h.html#a28c2443a142676d3d71effdae1a986b1">CUTLASS_HOST_DEVICE</a> complex&lt; T &gt;&#160;</td><td class="memTemplItemRight" valign="bottom"><a class="el" href="namespacecutlass.html#a28f05d94dbdfc97cddbeab3a5d23839d">cutlass::sqrt</a> (complex&lt; T &gt; const &amp;z)</td></tr>
<tr class="memdesc:a28f05d94dbdfc97cddbeab3a5d23839d"><td class="mdescLeft">&#160;</td><td class="mdescRight">Computes the square root of complex number z. <a href="namespacecutlass.html#a28f05d94dbdfc97cddbeab3a5d23839d">More...</a><br /></td></tr>
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<tr class="memitem:a2337866060023f87d4d821850738541f"><td class="memTemplParams" colspan="2">template&lt;typename T &gt; </td></tr>
<tr class="memitem:a2337866060023f87d4d821850738541f"><td class="memTemplItemLeft" align="right" valign="top"><a class="el" href="cutlass_8h.html#a28c2443a142676d3d71effdae1a986b1">CUTLASS_HOST_DEVICE</a> complex&lt; T &gt;&#160;</td><td class="memTemplItemRight" valign="bottom"><a class="el" href="namespacecutlass.html#a2337866060023f87d4d821850738541f">cutlass::cos</a> (complex&lt; T &gt; const &amp;z)</td></tr>
<tr class="memdesc:a2337866060023f87d4d821850738541f"><td class="mdescLeft">&#160;</td><td class="mdescRight">Computes the cosine of complex z. <a href="namespacecutlass.html#a2337866060023f87d4d821850738541f">More...</a><br /></td></tr>
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<tr class="memitem:a9ef7187befb09019b92e7eefa5e230d7"><td class="memTemplParams" colspan="2">template&lt;typename T &gt; </td></tr>
<tr class="memitem:a9ef7187befb09019b92e7eefa5e230d7"><td class="memTemplItemLeft" align="right" valign="top"><a class="el" href="cutlass_8h.html#a28c2443a142676d3d71effdae1a986b1">CUTLASS_HOST_DEVICE</a> complex&lt; T &gt;&#160;</td><td class="memTemplItemRight" valign="bottom"><a class="el" href="namespacecutlass.html#a9ef7187befb09019b92e7eefa5e230d7">cutlass::sin</a> (complex&lt; T &gt; const &amp;z)</td></tr>
<tr class="memdesc:a9ef7187befb09019b92e7eefa5e230d7"><td class="mdescLeft">&#160;</td><td class="mdescRight">Computes the sin of complex z. <a href="namespacecutlass.html#a9ef7187befb09019b92e7eefa5e230d7">More...</a><br /></td></tr>
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<tr class="memitem:ac0bfc6f3e3e772bf15ecad24481194cb"><td class="memTemplParams" colspan="2">template&lt;&gt; </td></tr>
<tr class="memitem:ac0bfc6f3e3e772bf15ecad24481194cb"><td class="memTemplItemLeft" align="right" valign="top"><a class="el" href="cutlass_8h.html#a28c2443a142676d3d71effdae1a986b1">CUTLASS_HOST_DEVICE</a> <a class="el" href="classcutlass_1_1complex.html">cutlass::complex</a>&lt; half_t &gt;&#160;</td><td class="memTemplItemRight" valign="bottom"><a class="el" href="namespacecutlass.html#ac0bfc6f3e3e772bf15ecad24481194cb">cutlass::from_real&lt; cutlass::complex&lt; half_t &gt; &gt;</a> (double r)</td></tr>
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<tr class="memitem:a7604eaf7d08b2362906b87ebeab6b761"><td class="memTemplParams" colspan="2">template&lt;&gt; </td></tr>
<tr class="memitem:a7604eaf7d08b2362906b87ebeab6b761"><td class="memTemplItemLeft" align="right" valign="top"><a class="el" href="cutlass_8h.html#a28c2443a142676d3d71effdae1a986b1">CUTLASS_HOST_DEVICE</a> <a class="el" href="classcutlass_1_1complex.html">cutlass::complex</a>&lt; float &gt;&#160;</td><td class="memTemplItemRight" valign="bottom"><a class="el" href="namespacecutlass.html#a7604eaf7d08b2362906b87ebeab6b761">cutlass::from_real&lt; cutlass::complex&lt; float &gt; &gt;</a> (double r)</td></tr>
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<tr class="memitem:a39965d02765d0e4aa491b7654d0ea7e4"><td class="memTemplParams" colspan="2">template&lt;&gt; </td></tr>
<tr class="memitem:a39965d02765d0e4aa491b7654d0ea7e4"><td class="memTemplItemLeft" align="right" valign="top"><a class="el" href="cutlass_8h.html#a28c2443a142676d3d71effdae1a986b1">CUTLASS_HOST_DEVICE</a> <a class="el" href="classcutlass_1_1complex.html">cutlass::complex</a>&lt; double &gt;&#160;</td><td class="memTemplItemRight" valign="bottom"><a class="el" href="namespacecutlass.html#a39965d02765d0e4aa491b7654d0ea7e4">cutlass::from_real&lt; cutlass::complex&lt; double &gt; &gt;</a> (double r)</td></tr>
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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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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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