GPU Kernel Information Aggregated by Name
kernel_name | kernel_count | kernel_duration (us) | model_duration_percentage | kernel_flops | kernel_dram_read_bytes | kernel_dram_write_bytes | kernel_achieved_occupancy (%) | kernel_arithmetic_intensity (flops/byte) | kernel_arithmetic_throughput (GFlops) | kernel_memory_bound |
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kernel_name | kernel_count | kernel_duration (us) | model_duration_percentage | kernel_flops | kernel_dram_read_bytes | kernel_dram_write_bytes | kernel_achieved_occupancy (%) | kernel_arithmetic_intensity (flops/byte) | kernel_arithmetic_throughput (GFlops) | kernel_memory_bound |
---|---|---|---|---|---|---|---|---|---|---|
cudnn::maxwell::gemm::computeOffsetsKernel(cudnn::maxwell::gemm::ComputeOffsetsParams) | 27 | 59.67 | 0.34 | 0 | 0.00 | 0.00 | 0.00 | 0.00 | 0.00 | true |
maxwell_gcgemm_64x32_nt | 1 | 67.50 | 0.38 | 218505216 | 0.00 | 0.00 | 0.00 | 0.00 | 3237.11 | true |
maxwell_scudnn_128x32_relu_interior_nn | 3 | 233.83 | 1.32 | 188014592 | 0.00 | 0.00 | 0.00 | 0.00 | 804.05 | true |
maxwell_scudnn_128x64_relu_interior_nn | 23 | 2971.67 | 16.80 | 1860763648 | 0.00 | 0.00 | 0.00 | 0.00 | 626.17 | true |
maxwell_scudnn_winograd_128x128_ldg1_ldg4_tile148n_nt | 11 | 813.17 | 4.60 | 2601928704 | 0.00 | 0.00 | 0.00 | 0.00 | 3199.75 | true |
void cudnn::detail::explicit_convolve_sgemm<float, int, 1024, 5, 5, 3, 3, 3, 0, true>(int, int, int, float const*, int, float const*, int, float*, kernel_conv_params, int, int, float, float, int, float*, float*) | 7 | 1091.33 | 6.17 | 1497729088 | 0.00 | 0.00 | 0.00 | 0.00 | 1372.39 | true |
void cudnn::detail::explicit_convolve_sgemm<float, int, 128, 5, 5, 3, 3, 3, 0, true>(int, int, int, float const*, int, float const*, int, float*, kernel_conv_params, int, int, float, float, int, float*, float*) | 37 | 3350.83 | 18.95 | 4011294848 | 0.00 | 0.00 | 0.00 | 0.00 | 1197.10 | true |
void cudnn::detail::implicit_convolve_sgemm<float, float, 1024, 5, 5, 3, 3, 3, 1, true, false, true>(int, int, int, float const*, int, float*, float*, kernel_conv_params, int, float, float, int, float*, float*, int, int) | 1 | 188.00 | 1.06 | 125903104 | 0.00 | 0.00 | 0.00 | 0.00 | 669.70 | true |
void cudnn::detail::implicit_convolve_sgemm<float, float, 128, 5, 5, 3, 3, 3, 1, true, false, true>(int, int, int, float const*, int, float*, float*, kernel_conv_params, int, float, float, int, float*, float*, int, int) | 4 | 840.00 | 4.75 | 448976489 | 0.00 | 0.00 | 0.00 | 0.00 | 534.50 | true |
void cudnn::detail::pooling_fw_4d_kernel<float, float, cudnn::detail::averpooling_func<float>, 2, false>(cudnnTensorStruct, float const*, cudnnTensorStruct, float*, cudnnPoolingStruct, float, float, int, cudnn::reduced_divisor, cudnn::reduced_divisor) | 9 | 266.17 | 1.51 | 44446259 | 0.00 | 0.00 | 0.00 | 0.00 | 166.99 | true |
void cudnn::detail::pooling_fw_4d_kernel<float, float, cudnn::detail::maxpooling_func<float, (cudnnNanPropagation_t)0>, 0, false>(cudnnTensorStruct, float const*, cudnnTensorStruct, float*, cudnnPoolingStruct, float, float, int, cudnn::reduced_divisor, cudnn::reduced_divisor) | 3 | 73.50 | 0.42 | 708640 | 0.00 | 0.00 | 0.00 | 0.00 | 9.64 | true |
void cudnn::winograd::generateWinogradTilesKernel<0, float, float>(cudnn::winograd::GenerateWinogradTilesParams<float, float>) | 11 | 124.00 | 0.70 | 24053760 | 0.00 | 0.00 | 0.00 | 0.00 | 193.98 | true |
void Eigen::internal::EigenMetaKernel<Eigen::TensorEvaluator<Eigen::TensorAssignOp<Eigen::TensorMap<Eigen::Tensor<float, 1, 1, long>, 16, Eigen::MakePointer>, Eigen::TensorCwiseBinaryOp<Eigen::internal::scalar_max_op<float const, float const>, Eigen::TensorMap<Eigen::Tensor<float const, 1, 1, long>, 16, Eigen::MakePointer> const, Eigen::TensorCwiseNullaryOp<Eigen::internal::scalar_constant_op<float const>, Eigen::TensorMap<Eigen::Tensor<float const, 1, 1, long>, 16, Eigen::MakePointer> const> const> const> const, Eigen::GpuDevice>, long>(Eigen::TensorEvaluator<Eigen::TensorAssignOp<Eigen::TensorMap<Eigen::Tensor<float, 1, 1, long>, 16, Eigen::MakePointer>, Eigen::TensorCwiseBinaryOp<Eigen::internal::scalar_max_op<float const, float const>, Eigen::TensorMap<Eigen::Tensor<float const, 1, 1, long>, 16, Eigen::MakePointer> const, Eigen::TensorCwiseNullaryOp<Eigen::internal::scalar_constant_op<float const>, Eigen::TensorMap<Eigen::Tensor<float const, 1, 1, long>, 16, Eigen::MakePointer> const> const> const> const, Eigen::GpuDevice>, long) | 62 | 238.00 | 1.35 | 0 | 0.00 | 0.00 | 0.00 | 0.00 | 0.00 | true |
void Eigen::internal::EigenMetaKernel<Eigen::TensorEvaluator<Eigen::TensorAssignOp<Eigen::TensorMap<Eigen::Tensor<float, 2, 1, int>, 16, Eigen::MakePointer>, Eigen::TensorCwiseBinaryOp<Eigen::internal::scalar_sum_op<float, float>, Eigen::TensorMap<Eigen::Tensor<float const, 2, 1, int>, 16, Eigen::MakePointer> const, Eigen::TensorBroadcastingOp<Eigen::array<long, 2ul> const, Eigen::TensorMap<Eigen::Tensor<float const, 2, 1, int>, 16, Eigen::MakePointer> const> const> const> const, Eigen::GpuDevice>, int>(Eigen::TensorEvaluator<Eigen::TensorAssignOp<Eigen::TensorMap<Eigen::Tensor<float, 2, 1, int>, 16, Eigen::MakePointer>, Eigen::TensorCwiseBinaryOp<Eigen::internal::scalar_sum_op<float, float>, Eigen::TensorMap<Eigen::Tensor<float const, 2, 1, int>, 16, Eigen::MakePointer> const, Eigen::TensorBroadcastingOp<Eigen::array<long, 2ul> const, Eigen::TensorMap<Eigen::Tensor<float const, 2, 1, int>, 16, Eigen::MakePointer> const> const> const> const, Eigen::GpuDevice>, int) | 93 | 428.00 | 2.42 | 8967488 | 0.00 | 0.00 | 0.00 | 0.00 | 20.95 | true |
void fft1d_c2r_32<float2, float, float, false, true, false, true>(float*, float2 const*, int, int3, int3, int2, int, float, float, float*, float*) | 1 | 15.33 | 0.09 | 1453568 | 0.00 | 0.00 | 0.00 | 0.00 | 94.80 | true |
void fft1d_r2c_32<float, float, float2, false, true>(float2*, float const*, int, int3, int3, int2, int2) | 1 | 24.17 | 0.14 | 1549312 | 0.00 | 0.00 | 0.00 | 0.00 | 64.11 | true |
void fft1d_r2c_32<float, float, float2, true, false>(float2*, float const*, int, int3, int3, int2, int2) | 1 | 40.50 | 0.23 | 11665408 | 0.00 | 0.00 | 0.00 | 0.00 | 288.03 | true |
void im2col4d_kernel<float, int>(im2col4d_params, cudnnConvolutionStruct, cudnnTensor4dStruct, float const*, float*, int) | 45 | 4242.33 | 23.99 | 0 | 0.00 | 0.00 | 0.00 | 0.00 | 0.00 | true |
void tensorflow::(anonymous namespace)::GenerateNormalizedProb<float, float>(float const*, float const*, float const*, float*, int, int, bool) | 0 | 4.00 | 0.02 | 24024 | 0.00 | 0.00 | 0.00 | 0.00 | 6.01 | true |
void tensorflow::BiasNCHWKernel<float>(int, float const*, float const*, float*, int, int) | 0 | 4.00 | 0.02 | 1001 | 0.00 | 0.00 | 0.00 | 0.00 | 0.25 | true |
void tensorflow::functor::RowReduceKernel<cub::TransformInputIterator<float, tensorflow::(anonymous namespace)::SubtractAndExpFunctor<float, float>, cub::CountingInputIterator<int, long>, long>, float*, cub::Sum>(cub::TransformInputIterator<float, tensorflow::(anonymous namespace)::SubtractAndExpFunctor<float, float>, cub::CountingInputIterator<int, long>, long>, float*, int, int, cub::Sum, std::iterator_traits<cub::TransformInputIterator<float, tensorflow::(anonymous namespace)::SubtractAndExpFunctor<float, float>, cub::CountingInputIterator<int, long>, long> >::value_type) | 0 | 13.00 | 0.07 | 10431 | 0.00 | 0.00 | 0.00 | 0.00 | 0.80 | true |
void tensorflow::functor::RowReduceKernel<float const*, float*, cub::Max>(float const*, float*, int, int, cub::Max, std::iterator_traits<float const*>::value_type) | 0 | 6.00 | 0.03 | 0 | 0.00 | 0.00 | 0.00 | 0.00 | 0.00 | true |
void tensorflow::functor::ShuffleInTensor3Simple<float, 2, 1, 0, false>(int, float const*, tensorflow::functor::Dimension<3>, float*) | 94 | 1378.83 | 7.80 | 0 | 0.00 | 0.00 | 0.00 | 0.00 | 0.00 | true |
void tensorflow::functor::SwapDimension1And2InTensor3UsingTiles<unsigned int, 1024, 1024, 2, false>(unsigned int const*, tensorflow::functor::Dimension<3>, unsigned int*) | 0 | 18.00 | 0.10 | 0 | 0.00 | 0.00 | 0.00 | 0.00 | 0.00 | true |
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