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) | 22 | 53.33 | 0.50 | 0 | 0.00 | 0.00 | 0.00 | 0.00 | 0.00 | true |
maxwell_scudnn_128x128_relu_interior_nn | 0 | 101.50 | 0.96 | 73629696 | 0.00 | 0.00 | 0.00 | 0.00 | 725.42 | true |
maxwell_scudnn_128x32_relu_interior_nn | 6 | 637.50 | 6.01 | 181231616 | 0.00 | 0.00 | 0.00 | 0.00 | 284.28 | true |
maxwell_scudnn_128x64_relu_interior_nn | 14 | 1184.00 | 11.16 | 533676032 | 0.00 | 0.00 | 0.00 | 0.00 | 450.74 | true |
maxwell_scudnn_winograd_128x128_ldg1_ldg4_tile148n_nt | 26 | 1211.33 | 11.42 | 1711661056 | 0.00 | 0.00 | 0.00 | 0.00 | 1413.04 | 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*) | 5 | 365.00 | 3.44 | 302993344 | 0.00 | 0.00 | 0.00 | 0.00 | 830.12 | 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*) | 8 | 567.17 | 5.35 | 278177440 | 0.00 | 0.00 | 0.00 | 0.00 | 490.47 | 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) | 5 | 416.67 | 3.93 | 198331392 | 0.00 | 0.00 | 0.00 | 0.00 | 475.99 | 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) | 1 | 270.83 | 2.55 | 124956521 | 0.00 | 0.00 | 0.00 | 0.00 | 461.38 | 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) | 7 | 137.33 | 1.29 | 20229646 | 0.00 | 0.00 | 0.00 | 0.00 | 147.30 | 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) | 4 | 57.83 | 0.55 | 492352 | 0.00 | 0.00 | 0.00 | 0.00 | 8.51 | true |
void cudnn::winograd::generateWinogradTilesKernel<0, float, float>(cudnn::winograd::GenerateWinogradTilesParams<float, float>) | 26 | 189.33 | 1.79 | 37416960 | 0.00 | 0.00 | 0.00 | 0.00 | 197.63 | 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) | 44 | 145.00 | 1.37 | 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) | 67 | 292.50 | 2.76 | 2921184 | 0.00 | 0.00 | 0.00 | 0.00 | 9.99 | true |
void im2col4d_kernel<float, int>(im2col4d_params, cudnnConvolutionStruct, cudnnTensor4dStruct, float const*, float*, int) | 14 | 1280.89 | 12.08 | 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 | 0.04 | 24024 | 0.00 | 0.00 | 0.00 | 0.00 | 6.01 | true |
void tensorflow::BiasNCHWKernel<float>(int, float const*, float const*, float*, int, int) | 1 | 21.00 | 0.20 | 803817 | 0.00 | 0.00 | 0.00 | 0.00 | 38.28 | true |
void tensorflow::functor::PadInputCustomKernelNCHW<float, 4>(int, float const*, tensorflow::functor::Dimension<4>, float*, tensorflow::functor::Dimension<4>, tensorflow::functor::Dimension<(4)-(2)>) | 4 | 37.00 | 0.35 | 0 | 0.00 | 0.00 | 0.00 | 0.00 | 0.00 | 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 | 12.00 | 0.11 | 10431 | 0.00 | 0.00 | 0.00 | 0.00 | 0.87 | 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 | 0.06 | 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*) | 70 | 741.00 | 6.99 | 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 | 10.67 | 0.10 | 0 | 0.00 | 0.00 | 0.00 | 0.00 | 0.00 | true |
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