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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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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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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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<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.
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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<li class="navelem"><a class="el" href="namespacecutlass.html">cutlass</a></li><li class="navelem"><a class="el" href="namespacecutlass_1_1gemm.html">gemm</a></li><li class="navelem"><a class="el" href="structcutlass_1_1gemm_1_1GemmCoord.html">GemmCoord</a></li> </ul>
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<div class="title">cutlass::gemm::GemmCoord Member List</div> </div>
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<p>This is the complete list of members for <a class="el" href="structcutlass_1_1gemm_1_1GemmCoord.html">cutlass::gemm::GemmCoord</a>, including all inherited members.</p>
<table class="directory">
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
<tr class="even"><td class="entry"><a class="el" href="structcutlass_1_1Coord.html#a8a65128c86b236cd2bea875b85a34bc1">at</a>()</td><td class="entry"><a class="el" href="structcutlass_1_1Coord.html">cutlass::Coord&lt; 3, int &gt;</a></td><td class="entry"><span class="mlabel">inline</span></td></tr>
<tr><td class="entry"><a class="el" href="structcutlass_1_1Coord.html#a358dde78a1c2105a9aeb4adee8bb3d2d">at</a>(int dim)</td><td class="entry"><a class="el" href="structcutlass_1_1Coord.html">cutlass::Coord&lt; 3, int &gt;</a></td><td class="entry"><span class="mlabel">inline</span></td></tr>
<tr class="even"><td class="entry"><a class="el" href="structcutlass_1_1Coord.html#ac7379275d7431ead927af7966b6fa0ec">at</a>() const</td><td class="entry"><a class="el" href="structcutlass_1_1Coord.html">cutlass::Coord&lt; 3, int &gt;</a></td><td class="entry"><span class="mlabel">inline</span></td></tr>
<tr><td class="entry"><a class="el" href="structcutlass_1_1Coord.html#a06046c22b877abfb277d3f0fe4f8578a">at</a>(int dim) const</td><td class="entry"><a class="el" href="structcutlass_1_1Coord.html">cutlass::Coord&lt; 3, int &gt;</a></td><td class="entry"><span class="mlabel">inline</span></td></tr>
<tr class="even"><td class="entry"><a class="el" href="structcutlass_1_1gemm_1_1GemmCoord.html#a278900b72f38c7566adbe5937d9f86ae">Base</a> typedef</td><td class="entry"><a class="el" href="structcutlass_1_1gemm_1_1GemmCoord.html">cutlass::gemm::GemmCoord</a></td><td class="entry"></td></tr>
<tr><td class="entry"><a class="el" href="structcutlass_1_1Coord.html#a40e145063833155c800b38f82cee7461">clamp</a>(Coord const &amp;max, Coord const &amp;min=Coord())</td><td class="entry"><a class="el" href="structcutlass_1_1Coord.html">cutlass::Coord&lt; 3, int &gt;</a></td><td class="entry"><span class="mlabel">inline</span></td></tr>
<tr class="even"><td class="entry"><a class="el" href="structcutlass_1_1Coord.html#a5281db2419b5567db4265dead7ac02cc">Coord</a>(Index value=Index(0))</td><td class="entry"><a class="el" href="structcutlass_1_1Coord.html">cutlass::Coord&lt; 3, int &gt;</a></td><td class="entry"><span class="mlabel">inline</span><span class="mlabel">explicit</span></td></tr>
<tr><td class="entry"><a class="el" href="structcutlass_1_1Coord.html#ab7094975a4b7471315ca083ae575030a">Coord</a>(Index const (&amp;_idx)[kRank])</td><td class="entry"><a class="el" href="structcutlass_1_1Coord.html">cutlass::Coord&lt; 3, int &gt;</a></td><td class="entry"><span class="mlabel">inline</span></td></tr>
<tr class="even"><td class="entry"><a class="el" href="structcutlass_1_1Coord.html#a42aefbb547e39b8cc7267c58a610c147">Coord</a>(Coord&lt; kRank, Index, LongIndex &gt; const &amp;coord)</td><td class="entry"><a class="el" href="structcutlass_1_1Coord.html">cutlass::Coord&lt; 3, int &gt;</a></td><td class="entry"><span class="mlabel">inline</span></td></tr>
<tr><td class="entry"><a class="el" href="structcutlass_1_1Coord.html#a057a417a4d4a6e2f69e0b55a6f7ee902">dot</a>(Coord const &amp;b, LongIndex sum=LongIndex(0)) const</td><td class="entry"><a class="el" href="structcutlass_1_1Coord.html">cutlass::Coord&lt; 3, int &gt;</a></td><td class="entry"><span class="mlabel">inline</span></td></tr>
Updated doxygen
2018-09-20 05:02:08 +08:00
<tr class="even"><td class="entry"><a class="el" href="structcutlass_1_1gemm_1_1GemmCoord.html#abaa87475d518a2e5cdf44c62122b9e01">GemmCoord</a>()</td><td class="entry"><a class="el" href="structcutlass_1_1gemm_1_1GemmCoord.html">cutlass::gemm::GemmCoord</a></td><td class="entry"><span class="mlabel">inline</span></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.
2019-11-20 08:55:34 +08:00
<tr><td class="entry"><a class="el" href="structcutlass_1_1gemm_1_1GemmCoord.html#a05b05eb23fa3f7b3343e1a1d39692c6c">GemmCoord</a>(Coord&lt; 3, Index &gt; const &amp;coord)</td><td class="entry"><a class="el" href="structcutlass_1_1gemm_1_1GemmCoord.html">cutlass::gemm::GemmCoord</a></td><td class="entry"><span class="mlabel">inline</span></td></tr>
<tr class="even"><td class="entry"><a class="el" href="structcutlass_1_1gemm_1_1GemmCoord.html#a5fabf4babb6ab8a9593300f8e1af2845">GemmCoord</a>(Index m, Index n, Index k)</td><td class="entry"><a class="el" href="structcutlass_1_1gemm_1_1GemmCoord.html">cutlass::gemm::GemmCoord</a></td><td class="entry"><span class="mlabel">inline</span></td></tr>
<tr><td class="entry"><a class="el" href="structcutlass_1_1gemm_1_1GemmCoord.html#a8e3f0250e2265503862354c729dca892">Index</a> typedef</td><td class="entry"><a class="el" href="structcutlass_1_1gemm_1_1GemmCoord.html">cutlass::gemm::GemmCoord</a></td><td class="entry"></td></tr>
<tr class="even"><td class="entry"><a class="el" href="structcutlass_1_1gemm_1_1GemmCoord.html#a18835ec84cbb6250143327e93697c7e9">k</a>() const </td><td class="entry"><a class="el" href="structcutlass_1_1gemm_1_1GemmCoord.html">cutlass::gemm::GemmCoord</a></td><td class="entry"><span class="mlabel">inline</span></td></tr>
<tr><td class="entry"><a class="el" href="structcutlass_1_1gemm_1_1GemmCoord.html#ae12eb84ec47ddf01b4d459c7aabc22ad">k</a>()</td><td class="entry"><a class="el" href="structcutlass_1_1gemm_1_1GemmCoord.html">cutlass::gemm::GemmCoord</a></td><td class="entry"><span class="mlabel">inline</span></td></tr>
Updated doxygen
2018-09-20 05:02:08 +08:00
<tr class="even"><td class="entry"><a class="el" href="structcutlass_1_1gemm_1_1GemmCoord.html#a521d4b8e720d2261c825e05397c92a5e">kK</a></td><td class="entry"><a class="el" href="structcutlass_1_1gemm_1_1GemmCoord.html">cutlass::gemm::GemmCoord</a></td><td class="entry"><span class="mlabel">static</span></td></tr>
<tr><td class="entry"><a class="el" href="structcutlass_1_1gemm_1_1GemmCoord.html#af1f5c03c35eaa406c6a63082da26bec3">kM</a></td><td class="entry"><a class="el" href="structcutlass_1_1gemm_1_1GemmCoord.html">cutlass::gemm::GemmCoord</a></td><td class="entry"><span class="mlabel">static</span></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.
2019-11-20 08:55:34 +08:00
<tr class="even"><td class="entry"><a class="el" href="structcutlass_1_1gemm_1_1GemmCoord.html#ad60d91a8e6acafca1f62ab3b3088b733">km</a>() const </td><td class="entry"><a class="el" href="structcutlass_1_1gemm_1_1GemmCoord.html">cutlass::gemm::GemmCoord</a></td><td class="entry"><span class="mlabel">inline</span></td></tr>
<tr><td class="entry"><a class="el" href="structcutlass_1_1gemm_1_1GemmCoord.html#af8f0abf128e5e0fb74bc81b3560e8110">kn</a>() const </td><td class="entry"><a class="el" href="structcutlass_1_1gemm_1_1GemmCoord.html">cutlass::gemm::GemmCoord</a></td><td class="entry"><span class="mlabel">inline</span></td></tr>
Updating Doxygen docs
2018-10-27 05:54:58 +08:00
<tr class="even"><td class="entry"><a class="el" href="structcutlass_1_1gemm_1_1GemmCoord.html#a67f08a03dabee497fa5547cff0f1faea">kN</a></td><td class="entry"><a class="el" href="structcutlass_1_1gemm_1_1GemmCoord.html">cutlass::gemm::GemmCoord</a></td><td class="entry"><span class="mlabel">static</span></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.
2019-11-20 08:55:34 +08:00
<tr><td class="entry"><a class="el" href="structcutlass_1_1gemm_1_1GemmCoord.html#ae4d6a46e4036d5f3d574ab6ae305e619">knm</a>() const </td><td class="entry"><a class="el" href="structcutlass_1_1gemm_1_1GemmCoord.html">cutlass::gemm::GemmCoord</a></td><td class="entry"><span class="mlabel">inline</span></td></tr>
<tr class="even"><td class="entry"><a class="el" href="structcutlass_1_1Coord.html#a2b07d7291d175920274c5e3346e5b68b">kRank</a></td><td class="entry"><a class="el" href="structcutlass_1_1Coord.html">cutlass::Coord&lt; 3, int &gt;</a></td><td class="entry"><span class="mlabel">static</span></td></tr>
<tr><td class="entry"><a class="el" href="structcutlass_1_1Coord.html#ab61db7c2bfacaf0b7ce465e70d48c44f">LongIndex</a> typedef</td><td class="entry"><a class="el" href="structcutlass_1_1Coord.html">cutlass::Coord&lt; 3, int &gt;</a></td><td class="entry"></td></tr>
<tr class="even"><td class="entry"><a class="el" href="structcutlass_1_1gemm_1_1GemmCoord.html#a93515a41db6c4b7e9101067f60d41b8c">m</a>() const </td><td class="entry"><a class="el" href="structcutlass_1_1gemm_1_1GemmCoord.html">cutlass::gemm::GemmCoord</a></td><td class="entry"><span class="mlabel">inline</span></td></tr>
<tr><td class="entry"><a class="el" href="structcutlass_1_1gemm_1_1GemmCoord.html#a8199f5e336a20c31e54d68b11e9fa3d3">m</a>()</td><td class="entry"><a class="el" href="structcutlass_1_1gemm_1_1GemmCoord.html">cutlass::gemm::GemmCoord</a></td><td class="entry"><span class="mlabel">inline</span></td></tr>
<tr class="even"><td class="entry"><a class="el" href="structcutlass_1_1Coord.html#abe58b7c8f153a6029c2adc173f340fe0">max_dim_index</a>() const</td><td class="entry"><a class="el" href="structcutlass_1_1Coord.html">cutlass::Coord&lt; 3, int &gt;</a></td><td class="entry"><span class="mlabel">inline</span></td></tr>
<tr><td class="entry"><a class="el" href="structcutlass_1_1Coord.html#ae89e8a9fa3f07308f8938052ef1aa1fb">min_dim_index</a>() const</td><td class="entry"><a class="el" href="structcutlass_1_1Coord.html">cutlass::Coord&lt; 3, int &gt;</a></td><td class="entry"><span class="mlabel">inline</span></td></tr>
<tr class="even"><td class="entry"><a class="el" href="structcutlass_1_1gemm_1_1GemmCoord.html#a68e79e339f5de2ce79fb90f2ec099233">mk</a>() const </td><td class="entry"><a class="el" href="structcutlass_1_1gemm_1_1GemmCoord.html">cutlass::gemm::GemmCoord</a></td><td class="entry"><span class="mlabel">inline</span></td></tr>
<tr><td class="entry"><a class="el" href="structcutlass_1_1gemm_1_1GemmCoord.html#ad8b9f6a9a69546f7a245e0d9a9296137">mn</a>() const </td><td class="entry"><a class="el" href="structcutlass_1_1gemm_1_1GemmCoord.html">cutlass::gemm::GemmCoord</a></td><td class="entry"><span class="mlabel">inline</span></td></tr>
<tr class="even"><td class="entry"><a class="el" href="structcutlass_1_1gemm_1_1GemmCoord.html#ae86d164050023469df1a5cd86e055c6f">mnk</a>() const </td><td class="entry"><a class="el" href="structcutlass_1_1gemm_1_1GemmCoord.html">cutlass::gemm::GemmCoord</a></td><td class="entry"><span class="mlabel">inline</span></td></tr>
<tr><td class="entry"><a class="el" href="structcutlass_1_1gemm_1_1GemmCoord.html#a1b29d2cb15360ad5499216859ad5436a">n</a>() const </td><td class="entry"><a class="el" href="structcutlass_1_1gemm_1_1GemmCoord.html">cutlass::gemm::GemmCoord</a></td><td class="entry"><span class="mlabel">inline</span></td></tr>
<tr class="even"><td class="entry"><a class="el" href="structcutlass_1_1gemm_1_1GemmCoord.html#a1327b9b4b9379df24df3d4b716952d11">n</a>()</td><td class="entry"><a class="el" href="structcutlass_1_1gemm_1_1GemmCoord.html">cutlass::gemm::GemmCoord</a></td><td class="entry"><span class="mlabel">inline</span></td></tr>
<tr><td class="entry"><a class="el" href="structcutlass_1_1gemm_1_1GemmCoord.html#aa5e22c102d48dfd91c28e1c08ba687ea">nk</a>() const </td><td class="entry"><a class="el" href="structcutlass_1_1gemm_1_1GemmCoord.html">cutlass::gemm::GemmCoord</a></td><td class="entry"><span class="mlabel">inline</span></td></tr>
<tr class="even"><td class="entry"><a class="el" href="structcutlass_1_1gemm_1_1GemmCoord.html#a1fc9861bfa5074513ab8f1cae7adab0d">nm</a>() const </td><td class="entry"><a class="el" href="structcutlass_1_1gemm_1_1GemmCoord.html">cutlass::gemm::GemmCoord</a></td><td class="entry"><span class="mlabel">inline</span></td></tr>
<tr><td class="entry"><a class="el" href="structcutlass_1_1Coord.html#a88096d051dd05111cf265a011a89f7f6">operator bool</a>() const</td><td class="entry"><a class="el" href="structcutlass_1_1Coord.html">cutlass::Coord&lt; 3, int &gt;</a></td><td class="entry"><span class="mlabel">inline</span><span class="mlabel">explicit</span></td></tr>
<tr class="even"><td class="entry"><a class="el" href="structcutlass_1_1Coord.html#aa733c6fae0da553053530cba2dddcaa0">operator!</a>() const</td><td class="entry"><a class="el" href="structcutlass_1_1Coord.html">cutlass::Coord&lt; 3, int &gt;</a></td><td class="entry"><span class="mlabel">inline</span></td></tr>
<tr><td class="entry"><a class="el" href="structcutlass_1_1Coord.html#a8183b9203a213d4b6381ad7dc120deea">operator!=</a>(Coord const &amp;b) const</td><td class="entry"><a class="el" href="structcutlass_1_1Coord.html">cutlass::Coord&lt; 3, int &gt;</a></td><td class="entry"><span class="mlabel">inline</span></td></tr>
<tr class="even"><td class="entry"><a class="el" href="structcutlass_1_1gemm_1_1GemmCoord.html#ae5fad509fbf1354e4717bf2bca593a25">operator*</a>(Base const &amp;b) const </td><td class="entry"><a class="el" href="structcutlass_1_1gemm_1_1GemmCoord.html">cutlass::gemm::GemmCoord</a></td><td class="entry"><span class="mlabel">inline</span></td></tr>
<tr><td class="entry"><a class="el" href="structcutlass_1_1Coord.html#ac6b5fd8d0e5cb856d363fbff9a5b89dd">Coord&lt; 3, int &gt;::operator*</a>(Coord const &amp;b) const</td><td class="entry"><a class="el" href="structcutlass_1_1Coord.html">cutlass::Coord&lt; 3, int &gt;</a></td><td class="entry"><span class="mlabel">inline</span></td></tr>
<tr class="even"><td class="entry"><a class="el" href="structcutlass_1_1gemm_1_1GemmCoord.html#a69fb0bb5e73f35d3c8df71a0174d6520">operator*=</a>(Base const &amp;b)</td><td class="entry"><a class="el" href="structcutlass_1_1gemm_1_1GemmCoord.html">cutlass::gemm::GemmCoord</a></td><td class="entry"><span class="mlabel">inline</span></td></tr>
<tr><td class="entry"><a class="el" href="structcutlass_1_1Coord.html#a00e618bc944d355badf67c0edd791412">Coord&lt; 3, int &gt;::operator*=</a>(Coord const &amp;b)</td><td class="entry"><a class="el" href="structcutlass_1_1Coord.html">cutlass::Coord&lt; 3, int &gt;</a></td><td class="entry"><span class="mlabel">inline</span></td></tr>
<tr class="even"><td class="entry"><a class="el" href="structcutlass_1_1gemm_1_1GemmCoord.html#a20618962d649b187cb5d5613572946db">operator+</a>(Base const &amp;b) const </td><td class="entry"><a class="el" href="structcutlass_1_1gemm_1_1GemmCoord.html">cutlass::gemm::GemmCoord</a></td><td class="entry"><span class="mlabel">inline</span></td></tr>
<tr><td class="entry"><a class="el" href="structcutlass_1_1Coord.html#aec4c529a728118c0df6a3f527daba746">Coord&lt; 3, int &gt;::operator+</a>(Coord const &amp;b) const</td><td class="entry"><a class="el" href="structcutlass_1_1Coord.html">cutlass::Coord&lt; 3, int &gt;</a></td><td class="entry"><span class="mlabel">inline</span></td></tr>
<tr class="even"><td class="entry"><a class="el" href="structcutlass_1_1gemm_1_1GemmCoord.html#a5465f7308778eac5d14d8020179a65e0">operator+=</a>(Base const &amp;b)</td><td class="entry"><a class="el" href="structcutlass_1_1gemm_1_1GemmCoord.html">cutlass::gemm::GemmCoord</a></td><td class="entry"><span class="mlabel">inline</span></td></tr>
<tr><td class="entry"><a class="el" href="structcutlass_1_1Coord.html#acb799faf60a17b708d0802f9e23c812f">Coord&lt; 3, int &gt;::operator+=</a>(Coord const &amp;b)</td><td class="entry"><a class="el" href="structcutlass_1_1Coord.html">cutlass::Coord&lt; 3, int &gt;</a></td><td class="entry"><span class="mlabel">inline</span></td></tr>
<tr class="even"><td class="entry"><a class="el" href="structcutlass_1_1gemm_1_1GemmCoord.html#aff600813c52c6f0a8e08b4a9a2925c02">operator-</a>(Base const &amp;b) const </td><td class="entry"><a class="el" href="structcutlass_1_1gemm_1_1GemmCoord.html">cutlass::gemm::GemmCoord</a></td><td class="entry"><span class="mlabel">inline</span></td></tr>
<tr><td class="entry"><a class="el" href="structcutlass_1_1Coord.html#a2e1a706629eae28128230a0fa34b84a0">Coord&lt; 3, int &gt;::operator-</a>(Coord const &amp;b) const</td><td class="entry"><a class="el" href="structcutlass_1_1Coord.html">cutlass::Coord&lt; 3, int &gt;</a></td><td class="entry"><span class="mlabel">inline</span></td></tr>
<tr class="even"><td class="entry"><a class="el" href="structcutlass_1_1gemm_1_1GemmCoord.html#a12ba250be3d5474b7c6fc4eddd4f58d5">operator-=</a>(Base const &amp;b)</td><td class="entry"><a class="el" href="structcutlass_1_1gemm_1_1GemmCoord.html">cutlass::gemm::GemmCoord</a></td><td class="entry"><span class="mlabel">inline</span></td></tr>
<tr><td class="entry"><a class="el" href="structcutlass_1_1Coord.html#a15ac170c861b34d418432aeb62ea86e0">Coord&lt; 3, int &gt;::operator-=</a>(Coord const &amp;b)</td><td class="entry"><a class="el" href="structcutlass_1_1Coord.html">cutlass::Coord&lt; 3, int &gt;</a></td><td class="entry"><span class="mlabel">inline</span></td></tr>
<tr class="even"><td class="entry"><a class="el" href="structcutlass_1_1gemm_1_1GemmCoord.html#a2d03dab79e54b8a17c0e7d91b9e0afd7">operator/</a>(Base const &amp;b) const </td><td class="entry"><a class="el" href="structcutlass_1_1gemm_1_1GemmCoord.html">cutlass::gemm::GemmCoord</a></td><td class="entry"><span class="mlabel">inline</span></td></tr>
<tr><td class="entry"><a class="el" href="structcutlass_1_1Coord.html#a6ae9f189d1a7a5ce7bb5e4416559c79f">Coord&lt; 3, int &gt;::operator/</a>(Coord const &amp;b) const</td><td class="entry"><a class="el" href="structcutlass_1_1Coord.html">cutlass::Coord&lt; 3, int &gt;</a></td><td class="entry"><span class="mlabel">inline</span></td></tr>
<tr class="even"><td class="entry"><a class="el" href="structcutlass_1_1gemm_1_1GemmCoord.html#aac1e1bad751237fd76d32a1ea10f6c40">operator/=</a>(Base const &amp;b)</td><td class="entry"><a class="el" href="structcutlass_1_1gemm_1_1GemmCoord.html">cutlass::gemm::GemmCoord</a></td><td class="entry"><span class="mlabel">inline</span></td></tr>
<tr><td class="entry"><a class="el" href="structcutlass_1_1Coord.html#af515e669363986dbbd60951ea6b69e14">Coord&lt; 3, int &gt;::operator/=</a>(Coord const &amp;b)</td><td class="entry"><a class="el" href="structcutlass_1_1Coord.html">cutlass::Coord&lt; 3, int &gt;</a></td><td class="entry"><span class="mlabel">inline</span></td></tr>
<tr class="even"><td class="entry"><a class="el" href="structcutlass_1_1Coord.html#a47ad37153eb8d291266a51b39ead5948">operator&lt;</a>(Coord const &amp;b) const</td><td class="entry"><a class="el" href="structcutlass_1_1Coord.html">cutlass::Coord&lt; 3, int &gt;</a></td><td class="entry"><span class="mlabel">inline</span></td></tr>
<tr><td class="entry"><a class="el" href="structcutlass_1_1Coord.html#a0e6405e081936a4fb23f15160e94ad08">operator&lt;=</a>(Coord const &amp;b) const</td><td class="entry"><a class="el" href="structcutlass_1_1Coord.html">cutlass::Coord&lt; 3, int &gt;</a></td><td class="entry"><span class="mlabel">inline</span></td></tr>
<tr class="even"><td class="entry"><a class="el" href="structcutlass_1_1Coord.html#a8424ccd74e7e0ff1cf358ef571779cba">operator==</a>(Coord const &amp;b) const</td><td class="entry"><a class="el" href="structcutlass_1_1Coord.html">cutlass::Coord&lt; 3, int &gt;</a></td><td class="entry"><span class="mlabel">inline</span></td></tr>
<tr><td class="entry"><a class="el" href="structcutlass_1_1Coord.html#a08507ff13f518a93a7d16ea0018f8a53">operator&gt;</a>(Coord const &amp;b) const</td><td class="entry"><a class="el" href="structcutlass_1_1Coord.html">cutlass::Coord&lt; 3, int &gt;</a></td><td class="entry"><span class="mlabel">inline</span></td></tr>
<tr class="even"><td class="entry"><a class="el" href="structcutlass_1_1Coord.html#ae37243e9f51b2b92b5fd09de69392657">operator&gt;=</a>(Coord const &amp;b) const</td><td class="entry"><a class="el" href="structcutlass_1_1Coord.html">cutlass::Coord&lt; 3, int &gt;</a></td><td class="entry"><span class="mlabel">inline</span></td></tr>
<tr><td class="entry"><a class="el" href="structcutlass_1_1Coord.html#a6eee93e5fdbe147f751ec108b28275a1">operator[]</a>(int dim)</td><td class="entry"><a class="el" href="structcutlass_1_1Coord.html">cutlass::Coord&lt; 3, int &gt;</a></td><td class="entry"><span class="mlabel">inline</span></td></tr>
<tr class="even"><td class="entry"><a class="el" href="structcutlass_1_1Coord.html#accf5689f0d6a6f91965bff0cfd9ec296">operator[]</a>(int dim) const</td><td class="entry"><a class="el" href="structcutlass_1_1Coord.html">cutlass::Coord&lt; 3, int &gt;</a></td><td class="entry"><span class="mlabel">inline</span></td></tr>
<tr><td class="entry"><a class="el" href="structcutlass_1_1Coord.html#ad5a2fb5b6b57e0726624c2b6e7c6545c">product</a>() const</td><td class="entry"><a class="el" href="structcutlass_1_1Coord.html">cutlass::Coord&lt; 3, int &gt;</a></td><td class="entry"><span class="mlabel">inline</span></td></tr>
<tr class="even"><td class="entry"><a class="el" href="structcutlass_1_1Coord.html#a329f97d4a09ef34e8470fe55800871f8">slice</a>(int start=0, Index identity=0) const</td><td class="entry"><a class="el" href="structcutlass_1_1Coord.html">cutlass::Coord&lt; 3, int &gt;</a></td><td class="entry"><span class="mlabel">inline</span></td></tr>
<tr><td class="entry"><a class="el" href="structcutlass_1_1Coord.html#a49bb1a68198bd4c520d15efe3e84f757">sum</a>() const</td><td class="entry"><a class="el" href="structcutlass_1_1Coord.html">cutlass::Coord&lt; 3, int &gt;</a></td><td class="entry"><span class="mlabel">inline</span></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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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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