Optimize Neon™ Logistic Activation
- Use a 1d execution window to improve memory access pattern.
Resolves: [COMPMID-5465]
Signed-off-by: Mohammed Suhail Munshi <MohammedSuhail.Munshi@arm.com>
Change-Id: Ida30669ffa06eb002ca43a6edf15e25a6eaad2f6
Reviewed-on: https://review.mlplatform.org/c/ml/ComputeLibrary/+/8344
Comments-Addressed: Arm Jenkins <bsgcomp@arm.com>
Tested-by: Arm Jenkins <bsgcomp@arm.com>
Reviewed-by: Gunes Bayir <gunes.bayir@arm.com>
Benchmark: Arm Jenkins <bsgcomp@arm.com>
diff --git a/src/core/helpers/WindowHelpers.cpp b/src/core/helpers/WindowHelpers.cpp
index fa152c9..a4d46db 100644
--- a/src/core/helpers/WindowHelpers.cpp
+++ b/src/core/helpers/WindowHelpers.cpp
@@ -234,15 +234,15 @@
std::pair<Window, size_t> calculate_squashed_or_max_window(const ITensorInfo &src0, const ITensorInfo &src1)
{
- const auto &shape0 = src0.tensor_shape();
- const auto &shape1 = src1.tensor_shape();
- const auto &strides0 = src0.strides_in_bytes();
- const auto &strides1 = src1.strides_in_bytes();
- const auto num_dimensions = std::max(src0.num_dimensions(), src1.num_dimensions());
+ const auto &shape0 = src0.tensor_shape();
+ const auto &shape1 = src1.tensor_shape();
+ const auto &strides0 = src0.strides_in_bytes();
+ const auto &strides1 = src1.strides_in_bytes();
+ const auto num_dimensions = std::max(src0.num_dimensions(), src1.num_dimensions());
Window win;
size_t split_dimension = Window::DimY;
- size_t dim = 0;
+ size_t dim = 0;
size_t squashed_bytes = src0.element_size();
@@ -282,4 +282,47 @@
return std::make_pair(win, split_dimension);
}
+
+std::pair<Window, size_t> calculate_squashed_or_max_window(const ITensorInfo &src)
+{
+ const auto &shape = src.tensor_shape();
+ const auto &strides = src.strides_in_bytes();
+ const auto num_dimensions = src.num_dimensions();
+
+ Window win;
+ size_t split_dimension = Window::DimY;
+ size_t dim = 0;
+ size_t squashed_bytes = src.element_size();
+
+ // Try to squash the low dimensions together.
+ for(; dim < num_dimensions; ++dim)
+ {
+ if(strides[dim] != squashed_bytes)
+ {
+ break;
+ }
+ squashed_bytes *= shape[dim];
+ }
+ if(dim == num_dimensions)
+ {
+ const auto squashed_elements = squashed_bytes / src.element_size();
+ split_dimension = Window::DimX;
+ // The input tensor can be interpreted as 1D array.
+ win.set(0, Window::Dimension(0, squashed_elements, 1));
+ for(dim = 1; dim < Coordinates::num_max_dimensions; ++dim)
+ {
+ win.set(dim, Window::Dimension(0, 1, 1));
+ }
+ }
+ else
+ {
+ // Generate the max window.
+ for(dim = 0; dim < Coordinates::num_max_dimensions; ++dim)
+ {
+ win.set(dim, Window::Dimension(0, shape[dim], 1));
+ }
+ }
+ return std::make_pair(win, split_dimension);
+}
+
} // namespace arm_compute
diff --git a/src/core/helpers/WindowHelpers.h b/src/core/helpers/WindowHelpers.h
index c9e5a13..eccf7f2 100644
--- a/src/core/helpers/WindowHelpers.h
+++ b/src/core/helpers/WindowHelpers.h
@@ -176,6 +176,18 @@
return calculate_max_enlarged_window(info.valid_region(), steps, border_size);
}
+/** Calculate the squashed or maximum window for the given tensor shape.
+ *
+ * If the tensor data resides continuously in the memory, the tensor can be interpreted
+ * as 1D array and all the dimensions can be squashed together into the x-dimension.
+ * Otherwise, generate the max window for the given tensor shape.
+ *
+ * @param[in] src Tensor info object defining the shape of the input tensor.
+ *
+ * @return The maximum window the kernel can be executed on and the preferred split dimension.
+ */
+std::pair<Window, size_t> calculate_squashed_or_max_window(const ITensorInfo &src);
+
/** Calculate the squashed or maximum window for the given tensor shapes.
*
* If the tensor data resides continuously in the memory, the tensor can be interpreted
diff --git a/src/cpu/kernels/CpuActivationKernel.cpp b/src/cpu/kernels/CpuActivationKernel.cpp
index 61efcb2..f1e4858 100644
--- a/src/cpu/kernels/CpuActivationKernel.cpp
+++ b/src/cpu/kernels/CpuActivationKernel.cpp
@@ -182,10 +182,16 @@
void CpuActivationKernel::configure(const ITensorInfo *src, ITensorInfo *dst, ActivationLayerInfo activation_info)
{
+ ARM_COMPUTE_UNUSED(dst);
ARM_COMPUTE_ERROR_ON_NULLPTR(src);
ARM_COMPUTE_ERROR_THROW_ON(validate_arguments(src, dst, activation_info));
const auto uk = CpuActivationKernel::get_implementation(ActivationDataTypeISASelectorData{ src->data_type(), CPUInfo::get().get_isa(), activation_info.activation() });
+ if(dst != nullptr)
+ {
+ // dst auto inizialitation if not yet initialized
+ auto_init_if_empty(*dst, *src->clone());
+ }
ARM_COMPUTE_ERROR_ON_NULLPTR(uk);
@@ -200,10 +206,20 @@
#endif // __aarch64__
_act_info = activation_info;
- // Configure kernel window
- auto win_config = validate_and_configure_window(src, dst);
- ARM_COMPUTE_ERROR_THROW_ON(win_config.first);
- ICPPKernel::configure(win_config.second);
+ Window win;
+
+ if(src->data_layout() != DataLayout::NHWC)
+ {
+ // Use squashed window
+ std::tie(win, _split_dimension) = calculate_squashed_or_max_window(*src);
+ ICPPKernel::configure(win);
+ }
+ else
+ {
+ // Configure kernel window
+ win = calculate_max_window(*src, Steps());
+ ICPPKernel::configure(win);
+ }
}
Status CpuActivationKernel::validate(const ITensorInfo *src, const ITensorInfo *dst, const ActivationLayerInfo &act_info)
diff --git a/src/cpu/kernels/CpuActivationKernel.h b/src/cpu/kernels/CpuActivationKernel.h
index d856a93..fe2d783 100644
--- a/src/cpu/kernels/CpuActivationKernel.h
+++ b/src/cpu/kernels/CpuActivationKernel.h
@@ -73,6 +73,15 @@
void run_op(ITensorPack &tensors, const Window &window, const ThreadInfo &info) override;
const char *name() const override;
+ /** Get the preferred dimension in which the scheduler splits the work into multiple jobs.
+ *
+ * @return The split dimension hint.
+ */
+ size_t get_split_dimension_hint() const
+ {
+ return _split_dimension;
+ }
+
struct ActivationKernel
{
const char *name;
@@ -85,6 +94,7 @@
private:
ActivationLayerInfo _act_info{};
ActivationKernelPtr _run_method{ nullptr };
+ size_t _split_dimension{ Window::DimY };
std::string _name{};
};
} // namespace kernels
diff --git a/src/cpu/operators/CpuActivation.cpp b/src/cpu/operators/CpuActivation.cpp
index 3945fa5..197e985 100644
--- a/src/cpu/operators/CpuActivation.cpp
+++ b/src/cpu/operators/CpuActivation.cpp
@@ -1,5 +1,5 @@
/*
- * Copyright (c) 2021 Arm Limited.
+ * Copyright (c) 2021-2022 Arm Limited.
*
* SPDX-License-Identifier: MIT
*
@@ -23,6 +23,7 @@
*/
#include "src/cpu/operators/CpuActivation.h"
+#include "arm_compute/runtime/NEON/NEScheduler.h"
#include "src/common/IOperator.h"
#include "src/common/utils/LegacySupport.h"
#include "src/common/utils/Log.h"
@@ -46,6 +47,13 @@
return kernels::CpuActivationKernel::validate(input, output, activation_info);
}
+void CpuActivation::run(ITensorPack &tensors)
+{
+ ARM_COMPUTE_ERROR_ON_MSG(tensors.empty(), "No inputs provided");
+ auto split_dimension = static_cast<kernels::CpuActivationKernel *>(_kernel.get())->get_split_dimension_hint();
+ NEScheduler::get().schedule_op(_kernel.get(), split_dimension, _kernel->window(), tensors);
+}
+
std::tuple<IOperator *, StatusCode> CpuContext::create_activation(const AclTensorDescriptor &src, const AclTensorDescriptor &dst, const AclActivationDescriptor &act, bool is_validate)
{
TensorInfo src_info = detail::convert_to_legacy_tensor_info(src);
diff --git a/src/cpu/operators/CpuActivation.h b/src/cpu/operators/CpuActivation.h
index 9b97c9d..f1807d5 100644
--- a/src/cpu/operators/CpuActivation.h
+++ b/src/cpu/operators/CpuActivation.h
@@ -1,5 +1,5 @@
/*
- * Copyright (c) 2021 Arm Limited.
+ * Copyright (c) 2021-2022 Arm Limited.
*
* SPDX-License-Identifier: MIT
*
@@ -48,6 +48,9 @@
* @return a status
*/
static Status validate(const ITensorInfo *input, const ITensorInfo *output, const ActivationLayerInfo &act_info);
+
+ // Inherited methods overridden:
+ void run(ITensorPack &tensors) override;
};
} // namespace cpu
} // namespace arm_compute