78 lines
3.4 KiB
C++
78 lines
3.4 KiB
C++
/***************************************************************************************************
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* Copyright (c) 2018, NVIDIA CORPORATION. All rights reserved.
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*
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* Redistribution and use in source and binary forms, with or without modification, are permitted
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* provided that the following conditions are met:
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* * Redistributions of source code must retain the above copyright notice, this list of
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* conditions and the following disclaimer.
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* * Redistributions in binary form must reproduce the above copyright notice, this list of
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* conditions and the following disclaimer in the documentation and/or other materials
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* provided with the distribution.
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* * Neither the name of the NVIDIA CORPORATION nor the names of its contributors may be used
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* to endorse or promote products derived from this software without specific prior written
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* permission.
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*
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* THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" AND ANY EXPRESS OR
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* IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND
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* FITNESS FOR A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL NVIDIA CORPORATION BE LIABLE
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* FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING,
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* BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS;
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* OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT,
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* STRICT LIABILITY, OR TOR (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE
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* OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
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*
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**************************************************************************************************/
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#include "cutlass/cutlass.h"
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template <typename GemmTraits_>
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static void run_binary_gemm(int m, int n, int k, int alpha = 1, int beta = 1) {
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typedef cutlass::gemm::Gemm<GemmTraits_> Gemm;
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typename Gemm::Params params;
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test::GemmTestbed<cutlass::Vector<cutlass::bin1_t, 32>, // AType
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cutlass::Vector<cutlass::bin1_t, 32>, // BType
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int32_t, // CType
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int32_t, // Accumulator
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int // Scalar
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>
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testbed(m,
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n,
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k / 32,
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test::convert(GemmTraits_::kLayoutA),
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test::convert(GemmTraits_::kLayoutB),
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alpha,
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beta);
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// Initializes the input vectors for computation
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testbed.initialize_binary();
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// Compute the reference result on the host (CPU)
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testbed.compute_host();
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params.initialize(testbed.M(),
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testbed.N(),
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testbed.K() * 32,
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testbed.alpha,
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testbed.ptr_A(),
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testbed.lda(),
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testbed.ptr_B(),
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testbed.ldb(),
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testbed.beta,
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testbed.ptr_C_initial(),
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testbed.ldc(),
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testbed.ptr_computed(),
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testbed.ldc());
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Gemm::launch(params);
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cudaError_t result = cudaDeviceSynchronize();
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ASSERT_EQ(result, cudaSuccess) << "\nCUDA kernel launch error: " << cudaGetErrorString(result)
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<< "\n";
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testbed.computed.sync_host();
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// Check the results
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ASSERT_TRUE(testbed.computed.bit_equals(testbed.ref_host));
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}
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