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using ElementCompute = typename Gemm::GemmKernel::Epilogue::OutputOp::ElementCompute; /// Initialization cutlass::Distribution::Kind init_A; cutlass::Distribution::Kind init_B; cutlass::Distribution::Kind init_C; uint64_t seed; cutlass::HostTensor tensor_A; cutlass::HostTensor tensor_B; cutlass::HostTensor tensor_C; cutlass::HostTensor tensor_D; cutlass::HostTensor reference_D; // // Methods // Testbed( cutlass::Distribution::Kind init_A_ = cutlass::Distribution::Uniform, cutlass::Distribution::Kind init_B_ = cutlass::Distribution::Uniform, cutlass::Distribution::Kind init_C_ = cutlass::Distribution::Uniform, uint64_t seed_ = 2080 ): init_A(init_A_), init_B(init_B_), init_C(init_C_), seed(seed_) { } /// Helper to initialize a tensor view template bool initialize_tensor( cutlass::TensorView view, cutlass::Distribution::Kind dist_kind, uint64_t seed) { if (dist_kind == cutlass::Distribution::Uniform) { double scope_max, scope_min; int bits_input = cutlass::sizeof_bits::value; int bits_output = cutlass::sizeof_bits::value; if (bits_input == 1) { scope_max = 2; scope_min = 0; } else if (bits_input <= 8) { scope_max = 2; scope_min = -2; } else if (bits_output == 16) { scope_max = 5; scope_min = -5; } else { scope_max = 8; scope_min = -8; } cutlass::reference::host::TensorFillRandomUniform( view, seed, scope_max, scope_min, 0); } else if (dist_kind == cutlass::Distribution::Identity) { cutlass::reference::host::TensorFillIdentity(view); } else if (dist_kind == cutlass::Distribution::Gaussian) { cutlass::reference::host::TensorFillRandomGaussian(view, seed, 0, 0.5); } else if (dist_kind == cutlass::Distribution::Sequential) { cutlass::reference::host::BlockFillSequential( view.data(), view.capacity()); } else { // TODO: Implement the rest EXPECT_TRUE(false) << "Not implemented"; return false; } return true; } /// Initializes data structures void initialize(cutlass::gemm::GemmCoord problem_size) { // // Allocate the GEMM workspace // tensor_A.resize(problem_size.mk()); tensor_B.resize(problem_size.kn()); tensor_C.resize(problem_size.mn()); tensor_D.resize(problem_size.mn()); reference_D.resize(problem_size.mn(), false); EXPECT_TRUE(initialize_tensor(tensor_A.host_view(), init_A, seed + 2019)); EXPECT_TRUE(initialize_tensor(tensor_B.host_view(), init_B, seed + 2018)); EXPECT_TRUE(initialize_tensor(tensor_C.host_view(), init_C, seed + 2017)); // It is possible to randomly initialize to all zeros, so override this with non-zeros // in the upper left corner of each operand. tensor_A.host_view().at({0, 0}) = typename Gemm::ElementA(1); tensor_B.host_view().at({0, 0}) = typename Gemm::ElementB(1); tensor_C.host_view().at({0, 0}) = typename Gemm::ElementC(1); cutlass::reference::host::TensorCopy(reference_D.host_view(), tensor_C.host_view()); tensor_A.sync_device(); tensor_B.sync_device(); tensor_C.sync_device(); tensor_D.sync_device(); } /// Compares computed reference with device reference and outputs to a file if incorrect bool compare_reference( cutlass::gemm::GemmCoord problem_size, ElementCompute alpha, ElementCompute beta) { tensor_D.sync_host(); EXPECT_GT(cutlass::reference::host::TensorNorm(tensor_A.host_view()), 0); EXPECT_GT(cutlass::reference::host::TensorNorm(tensor_B.host_view()), 0); EXPECT_GT(cutlass::reference::host::TensorNorm(tensor_C.host_view()), 0); if (tensor_D.size() > 1) EXPECT_GT(cutlass::reference::host::TensorNorm(tensor_D.host_view()), 0); if (reference_D.size() > 1) EXPECT_GT(cutlass::reference::host::TensorNorm(reference_D.host_view()), 0); bool passed = cutlass::reference::host::TensorEquals(reference_D.host_view(), tensor_D.host_view()); EXPECT_TRUE(passed); if (!passed) { std::stringstream fname; fname << "error_Gemm_device_" << problem_size.m() << "x" << problem_size.n() << "x" << problem_size.k() << "_" << Gemm::ThreadblockShape::kM << "x" << Gemm::ThreadblockShape::kN << "x" << Gemm::ThreadblockShape::kK << "_" << Gemm::WarpShape::kM << "x" << Gemm::WarpShape::kN << "x" << Gemm::WarpShape::kK << ".txt"; std::ofstream file(fname.str()); file << "problem: " << problem_size << ", alpha: " << alpha << ", beta: " << beta << "\n\n"; file << "A =\n" << tensor_A.host_view() << "\nB =\n" << tensor_B.host_view() << "\nC =\n" << tensor_C.host_view() << "\n\nReference =\n" << reference_D.host_view() << "\nComputed =\n" << tensor_D.host_view(); } return passed; } /// Verifies the result is a GEMM bool verify( cutlass::gemm::GemmCoord problem_size, ElementCompute alpha, ElementCompute beta) { // // Verify // cutlass::reference::host::Gemm< typename Gemm::ElementA, typename Gemm::LayoutA, typename Gemm::ElementB, typename Gemm::LayoutB, typename Gemm::ElementC, typename Gemm::LayoutC, ElementCompute, ElementAccumulator, typename Gemm::Operator> reference_gemm; reference_gemm( problem_size, alpha, tensor_A.host_ref(), tensor_B.host_ref(), beta, reference_D.host_ref(), ElementAccumulator(0) ); return compare_reference(problem_size, alpha, beta); } /// Executes one test bool run( cutlass::gemm::GemmCoord problem_size, int split_k_slices = 1, ElementCompute alpha = ElementCompute(1), ElementCompute beta = ElementCompute(0)) { this->initialize(problem_size); // // Initialize the GEMM operator // typename Gemm::Arguments arguments{ problem_size, tensor_A.device_ref(), tensor_B.device_ref(), tensor_C.device_ref(), tensor_D.device_ref(), {alpha, beta}, split_k_slices }; Gemm gemm_op; size_t workspace_size = Gemm::get_workspace_size(arguments); cutlass::device_memory::allocation workspace(workspace_size); cutlass::Status status = gemm_op.initialize(arguments, workspace.get()); EXPECT_TRUE(status == cutlass::Status::kSuccess) << to_string(status); // // Run the GEMM // status = gemm_op(); EXPECT_TRUE(status == cutlass::Status::kSuccess) << to_string(status); // // Verify // bool passed = this->verify(problem_size, alpha, beta); if (!passed) { std::cout << "Error with split_k_slices = " << split_k_slices << ", alpha: " << alpha << std::endl; } return passed; } }; ///////////////////////////////////////////////////////////////////////////////////////////////// template bool TestAllGemm() { bool passed = true; int const kMinimumOperandElementSize = std::min( int(cutlass::sizeof_bits::value), int(cutlass::sizeof_bits::value)); int const kAlignment = cutlass::platform::is_same< typename Gemm::OperatorClass, cutlass::arch::OpClassSimt>::value ? 1 : 128 / kMinimumOperandElementSize; // int8_t gemm alignment constraints int const kAlignmentM = cutlass::platform::is_same::value && cutlass::platform::is_same::value && cutlass::platform::is_same::value ? 4 : kAlignment; int const kAlignmentN = cutlass::platform::is_same::value && cutlass::platform::is_same::value && cutlass::platform::is_same::value ? 4 : kAlignment; int const kAlignmentK = cutlass::platform::is_same::value && cutlass::platform::is_same::value && cutlass::platform::is_same::value && (cutlass::platform::is_same::value || cutlass::platform::is_same::value) ? 4 : kAlignment; int problem_size_m[] = {kAlignmentM, 512 - 3 * kAlignmentM}; int problem_size_n[] = {kAlignmentN, 512 - 2 * kAlignmentN}; int problem_size_k[] = { kAlignmentK, Gemm::ThreadblockShape::kK * (Gemm::kStages + 1) - kAlignmentK}; int split_k_slices[] = { 1, 2, 3 }; double problem_alpha[] = { 1 }; double problem_beta[] = { 2.0 }; Testbed testbed; using ElementCompute = typename Gemm::EpilogueOutputOp::ElementCompute; for (int m : problem_size_m) { for (int n : problem_size_n) { for (int k : problem_size_k) { for (int split_k : split_k_slices) { if (!Gemm::kSplitKSerial && split_k > 1) { continue; } if (split_k > 1 && k / Gemm::ThreadblockShape::kK < split_k) { continue; } for (auto alpha : problem_alpha) { for (auto beta : problem_beta) { cutlass::gemm::GemmCoord problem_size(m, n, k); passed = testbed.run( problem_size, split_k, cutlass::from_real(alpha), cutlass::from_real(beta) ); if (!passed) { return false; } } } } } } } return passed; } ///////////////////////////////////////////////////////////////////////////////////////////////// template bool TestGemmPerf(int iterations = 1) { bool passed = true; int problem_size_m[] = { 2048 }; int problem_size_n[] = { 4352 }; int problem_size_k[] = { 4096 }; int split_k_slices[] = { 1 }; double problem_alpha[] = { 1 }; double problem_beta[] = { 0.0 }; Testbed testbed; using ElementCompute = typename Gemm::EpilogueOutputOp::ElementCompute; for (int m : problem_size_m) { for (int n : problem_size_n) { for (int k : problem_size_k) { for (int split_k : split_k_slices) { if (!Gemm::kSplitKSerial && split_k > 1) { continue; } for (auto alpha : problem_alpha) { for (auto beta : problem_beta) { cutlass::gemm::GemmCoord problem_size(m, n, k); for (int i = 0; i < iterations; i++){ passed = testbed.run( problem_size, split_k, cutlass::from_real(alpha), cutlass::from_real(beta) ); } if (!passed) { return false; } } } } } } } return passed; } } // namespace device } // namespace gemm } // namespace test /////////////////////////////////////////////////////////////////////////////////////////////////