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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Andrew Kerr
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<div id="projectname">Cutlass
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<div id="projectname">CUTLASS
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<div id="projectbrief">CUDA Templates for Linear Algebra Subroutines and Solvers</div>
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<li><a href="functions_vars_b.html#index_b"><span>b</span></a></li>
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<li><a href="functions_vars_c.html#index_c"><span>c</span></a></li>
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<li><a href="functions_vars_h.html#index_h"><span>h</span></a></li>
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<li><a href="functions_vars_i.html#index_i"><span>i</span></a></li>
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<li><a href="functions_vars_k.html#index_k"><span>k</span></a></li>
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<li><a href="functions_vars_l.html#index_l"><span>l</span></a></li>
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<li><a href="functions_vars_m.html#index_m"><span>m</span></a></li>
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<li><a href="functions_vars_n.html#index_n"><span>n</span></a></li>
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<li><a href="functions_vars_o.html#index_o"><span>o</span></a></li>
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<li><a href="functions_vars_p.html#index_p"><span>p</span></a></li>
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<li><a href="functions_vars_r.html#index_r"><span>r</span></a></li>
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<li><a href="functions_vars_s.html#index_s"><span>s</span></a></li>
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<li><a href="functions_vars_t.html#index_t"><span>t</span></a></li>
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<li><a href="functions_vars_u.html#index_u"><span>u</span></a></li>
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<li><a href="functions_vars_v.html#index_v"><span>v</span></a></li>
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<h3><a id="index_a"></a>- a -</h3><ul>
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<h3><a class="anchor" id="index_a"></a>- a -</h3><ul>
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<li>A
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: <a class="el" href="structcutlass_1_1gemm_1_1GemmDesc.html#a80b0aae6e67b733ae5bf289d979a7c9b">cutlass::gemm::GemmDesc< AType_, BType_, CType_, DType_, SType_, Index_ ></a>
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: <a class="el" href="structcutlass_1_1library_1_1GemmArguments.html#ab4c9ecf49885b1e2ff88ff9c7a4ffad9">cutlass::library::GemmArguments</a>
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, <a class="el" href="structcutlass_1_1library_1_1GemmArrayArguments.html#afcce27cdc91247a9e4e8e610c3a38e63">cutlass::library::GemmArrayArguments</a>
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, <a class="el" href="structcutlass_1_1library_1_1GemmDescription.html#aa821b15ab4f4c51c4890c7cac685fba4">cutlass::library::GemmDescription</a>
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</li>
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<li>aligned_
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: <a class="el" href="unioncutlass_1_1Vector.html#a9e9352594fcd022526d5b69b6c25c99c">cutlass::Vector< Scalar_, kLanes_ ></a>
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, <a class="el" href="unioncutlass_1_1Vector_3_01bin1__t_00_01kLanes___01_4.html#a1df3324868465331db13bd7775b55e87">cutlass::Vector< bin1_t, kLanes_ ></a>
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, <a class="el" href="unioncutlass_1_1Vector_3_01half_00_011_01_4.html#acc698443a38fd0ad63f931bdf172ad99">cutlass::Vector< half, 1 ></a>
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, <a class="el" href="unioncutlass_1_1Vector_3_01half_00_01kLanes___01_4.html#a9e41dbe541a7dddf1e461e0390fe8896">cutlass::Vector< half, kLanes_ ></a>
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, <a class="el" href="unioncutlass_1_1Vector_3_01int4__t_00_01kLanes___01_4.html#ad6784e347f068ad20af52379286337c0">cutlass::Vector< int4_t, kLanes_ ></a>
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, <a class="el" href="unioncutlass_1_1Vector_3_01uint4__t_00_01kLanes___01_4.html#a4eab187b6f7650bd88ccd421c8330d3c">cutlass::Vector< uint4_t, kLanes_ ></a>
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<li>A_tile
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: <a class="el" href="structcutlass_1_1reference_1_1device_1_1thread_1_1Gemm.html#a2d63fe67429aa6441e6e247563db1a11">cutlass::reference::device::thread::Gemm< TensorRefA, TensorRefB, TensorRefC, ScalarType, AccumulatorType, OutputTile, InnerProductOp, ConvertOp ></a>
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</li>
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<li>accum
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: <a class="el" href="structcutlass_1_1reference_1_1device_1_1thread_1_1Gemm.html#a304c308d4cf13915cf1ba796c506dda6">cutlass::reference::device::thread::Gemm< TensorRefA, TensorRefB, TensorRefC, ScalarType, AccumulatorType, OutputTile, InnerProductOp, ConvertOp ></a>
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</li>
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<li>advance_cluster
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: <a class="el" href="structcutlass_1_1epilogue_1_1threadblock_1_1PredicatedTileIterator_1_1Params.html#a38a6dcfddaf9078334107eb8a38595fb">cutlass::epilogue::threadblock::PredicatedTileIterator< ThreadMap_, Element_ >::Params</a>
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</li>
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<li>advance_column
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: <a class="el" href="structcutlass_1_1epilogue_1_1threadblock_1_1InterleavedPredicatedTileIterator_1_1Params.html#a5593ba3ee47ba8bb6dc2b0b001b38824">cutlass::epilogue::threadblock::InterleavedPredicatedTileIterator< ThreadMap_, Element_, InterleavedK >::Params</a>
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</li>
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<li>advance_group
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: <a class="el" href="structcutlass_1_1epilogue_1_1threadblock_1_1PredicatedTileIterator_1_1Params.html#a010385e2b1e39fb0a42ce65c68e07e8e">cutlass::epilogue::threadblock::PredicatedTileIterator< ThreadMap_, Element_ >::Params</a>
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</li>
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<li>advance_row
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: <a class="el" href="structcutlass_1_1epilogue_1_1threadblock_1_1InterleavedPredicatedTileIterator_1_1Params.html#a31c6472b5e890a37657d573646114156">cutlass::epilogue::threadblock::InterleavedPredicatedTileIterator< ThreadMap_, Element_, InterleavedK >::Params</a>
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, <a class="el" href="structcutlass_1_1epilogue_1_1threadblock_1_1PredicatedTileIterator_1_1Params.html#a4ceaade8da07a3951a30c6d24b79f557">cutlass::epilogue::threadblock::PredicatedTileIterator< ThreadMap_, Element_ >::Params</a>
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</li>
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<li>advance_tile
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: <a class="el" href="structcutlass_1_1epilogue_1_1threadblock_1_1PredicatedTileIterator_1_1Params.html#a93f34cf9a98ab9bf6b2f7156848c9efd">cutlass::epilogue::threadblock::PredicatedTileIterator< ThreadMap_, Element_ >::Params</a>
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</li>
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<li>alignment
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: <a class="el" href="structcutlass_1_1library_1_1TensorDescription.html#a9fed369aad059bda36c528e72f8bb8fd">cutlass::library::TensorDescription</a>
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</li>
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<li>alpha
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: <a class="el" href="structcutlass_1_1gemm_1_1GemmDesc.html#aa82600c82e17ea1233f2f74be4aa3785">cutlass::gemm::GemmDesc< AType_, BType_, CType_, DType_, SType_, Index_ ></a>
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, <a class="el" href="structcutlass_1_1gemm_1_1LinearScaling_1_1Params.html#a3248d6b3d9bcc59365d582b879292a70">cutlass::gemm::LinearScaling< Scalar_, FragmentMultiplyAdd_ >::Params</a>
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: <a class="el" href="structcutlass_1_1epilogue_1_1thread_1_1LinearCombination_1_1Params.html#aebf79db277fc69c1fafae975538f8c57">cutlass::epilogue::thread::LinearCombination< ElementOutput_, Count, ElementAccumulator_, ElementCompute_, Round >::Params</a>
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, <a class="el" href="structcutlass_1_1epilogue_1_1thread_1_1LinearCombinationClamp_1_1Params.html#a92b42f2498efb637ba4e2eb2bc7710c8">cutlass::epilogue::thread::LinearCombinationClamp< ElementOutput_, Count, ElementAccumulator_, ElementCompute_, Round >::Params</a>
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, <a class="el" href="structcutlass_1_1epilogue_1_1thread_1_1LinearCombinationRelu_1_1Params.html#a48d23248d58b6f7b5aa6aae7cd66afa0">cutlass::epilogue::thread::LinearCombinationRelu< ElementOutput_, Count, ElementAccumulator_, ElementCompute_, Round >::Params</a>
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, <a class="el" href="structcutlass_1_1epilogue_1_1thread_1_1LinearCombinationRelu_3_01ElementOutput___00_01Count_00_00274a94522c46cd041d0b10d484e2ef3.html#a4a225cb1f8a09c643a8016024ccbf6cb">cutlass::epilogue::thread::LinearCombinationRelu< ElementOutput_, Count, int, float, Round >::Params</a>
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, <a class="el" href="structcutlass_1_1gemm_1_1kernel_1_1detail_1_1GemvBatchedStridedEpilogueScaling.html#afd6c2151dbdd056d214d5ccee685c676">cutlass::gemm::kernel::detail::GemvBatchedStridedEpilogueScaling< ElementAlphaBeta, BetaIsZero ></a>
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, <a class="el" href="structcutlass_1_1library_1_1GemmArguments.html#a94a7760d5bbee524c2381adf7a2fd683">cutlass::library::GemmArguments</a>
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, <a class="el" href="structcutlass_1_1library_1_1GemmArrayArguments.html#a2de0ca18e82590a98ac2ffea6a741840">cutlass::library::GemmArrayArguments</a>
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, <a class="el" href="structcutlass_1_1reduction_1_1BatchedReductionTraits_1_1Params.html#afada1cbad87636228fb58d8577bb8470">cutlass::reduction::BatchedReductionTraits< ScalarA_, ScalarC_, ScalarD_, ScalarAlphaBeta_, ScalarAccum_, ReductionSize_, OutputTile_, SubTile_, ThreadShape_, Index_, BlockSwizzle_, maxInReg_, maxOutReg_, Functor_ >::Params</a>
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</li>
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<li>alpha_ptr
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: <a class="el" href="structcutlass_1_1epilogue_1_1thread_1_1LinearCombination_1_1Params.html#aabd9260f2a8a1b809864fe20dc3c7553">cutlass::epilogue::thread::LinearCombination< ElementOutput_, Count, ElementAccumulator_, ElementCompute_, Round >::Params</a>
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, <a class="el" href="structcutlass_1_1epilogue_1_1thread_1_1LinearCombinationClamp_1_1Params.html#a0ddbb24a81370a342d05509bb78f122c">cutlass::epilogue::thread::LinearCombinationClamp< ElementOutput_, Count, ElementAccumulator_, ElementCompute_, Round >::Params</a>
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, <a class="el" href="structcutlass_1_1epilogue_1_1thread_1_1LinearCombinationRelu_1_1Params.html#a6c266e54081c08d25f4d6832ca24e673">cutlass::epilogue::thread::LinearCombinationRelu< ElementOutput_, Count, ElementAccumulator_, ElementCompute_, Round >::Params</a>
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, <a class="el" href="structcutlass_1_1epilogue_1_1thread_1_1LinearCombinationRelu_3_01ElementOutput___00_01Count_00_00274a94522c46cd041d0b10d484e2ef3.html#aa4d227d5db2999f4738a207183fc4fc3">cutlass::epilogue::thread::LinearCombinationRelu< ElementOutput_, Count, int, float, Round >::Params</a>
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</li>
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<li>args
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: <a class="el" href="structcutlass_1_1CommandLine.html#a6a338671a8d323882f9d9463863eb1c1">cutlass::CommandLine</a>
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