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+/*
+ * Copyright (c) 2016-2020 Arm Limited.
+ *
+ * SPDX-License-Identifier: MIT
+ *
+ * Permission is hereby granted, free of charge, to any person obtaining a copy
+ * of this software and associated documentation files (the "Software"), to
+ * deal in the Software without restriction, including without limitation the
+ * rights to use, copy, modify, merge, publish, distribute, sublicense, and/or
+ * sell copies of the Software, and to permit persons to whom the Software is
+ * furnished to do so, subject to the following conditions:
+ *
+ * The above copyright notice and this permission notice shall be included in all
+ * copies or substantial portions of the Software.
+ *
+ * THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
+ * IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
+ * FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
+ * AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
+ * LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
+ * OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
+ * SOFTWARE.
+ */
+#ifndef ARM_COMPUTE_ICLKERNEL_H
+#define ARM_COMPUTE_ICLKERNEL_H
+
+#include "arm_compute/core/CL/CLKernelLibrary.h"
+#include "arm_compute/core/CL/CLTypes.h"
+#include "arm_compute/core/CL/OpenCL.h"
+#include "arm_compute/core/GPUTarget.h"
+#include "arm_compute/core/IKernel.h"
+#include "arm_compute/core/Validate.h"
+#include "arm_compute/core/experimental/Types.h"
+
+#include <string>
+
+namespace arm_compute
+{
+template <typename T>
+class ICLArray;
+class ICLTensor;
+class Window;
+
+/** Common interface for all the OpenCL kernels */
+class ICLKernel : public IKernel
+{
+private:
+ /** Returns the number of arguments enqueued per array object.
+ *
+ * @return The number of arguments enqueued per array object.
+ */
+ template <unsigned int dimension_size>
+ constexpr static unsigned int num_arguments_per_array()
+ {
+ return num_arguments_per_tensor<dimension_size>();
+ }
+ /** Returns the number of arguments enqueued per tensor object.
+ *
+ * @return The number of arguments enqueued per tensor object.
+ */
+ template <unsigned int dimension_size>
+ constexpr static unsigned int num_arguments_per_tensor()
+ {
+ return 2 + 2 * dimension_size;
+ }
+ using IKernel::configure; //Prevent children from calling IKernel::configure() directly
+protected:
+ /** Configure the kernel's window and local workgroup size hint.
+ *
+ * @param[in] window The maximum window which will be returned by window()
+ * @param[in] lws_hint (Optional) Local-Workgroup-Size to use.
+ */
+ void configure_internal(const Window &window, cl::NDRange lws_hint = CLKernelLibrary::get().default_ndrange())
+ {
+ _lws_hint = lws_hint;
+ IKernel::configure(window);
+ }
+
+public:
+ /** Constructor */
+ ICLKernel()
+ : _kernel(nullptr), _target(GPUTarget::MIDGARD), _config_id(arm_compute::default_config_id), _max_workgroup_size(0), _lws_hint()
+ {
+ }
+ /** Returns a reference to the OpenCL kernel of this object.
+ *
+ * @return A reference to the OpenCL kernel of this object.
+ */
+ cl::Kernel &kernel()
+ {
+ return _kernel;
+ }
+ /** Add the passed 1D array's parameters to the object's kernel's arguments starting from the index idx.
+ *
+ * @param[in,out] idx Index at which to start adding the array's arguments. Will be incremented by the number of kernel arguments set.
+ * @param[in] array Array to set as an argument of the object's kernel.
+ * @param[in] strides @ref Strides object containing stride of each dimension in bytes.
+ * @param[in] num_dimensions Number of dimensions of the @p array.
+ * @param[in] window Window the kernel will be executed on.
+ */
+ template <typename T>
+ void add_1D_array_argument(unsigned int &idx, const ICLArray<T> *array, const Strides &strides, unsigned int num_dimensions, const Window &window)
+ {
+ add_array_argument<T, 1>(idx, array, strides, num_dimensions, window);
+ }
+ /** Add the passed 1D tensor's parameters to the object's kernel's arguments starting from the index idx.
+ *
+ * @param[in,out] idx Index at which to start adding the tensor's arguments. Will be incremented by the number of kernel arguments set.
+ * @param[in] tensor Tensor to set as an argument of the object's kernel.
+ * @param[in] window Window the kernel will be executed on.
+ */
+ void add_1D_tensor_argument(unsigned int &idx, const ICLTensor *tensor, const Window &window)
+ {
+ add_tensor_argument<1>(idx, tensor, window);
+ }
+ /** Add the passed 1D tensor's parameters to the object's kernel's arguments starting from the index idx if the condition is true.
+ *
+ * @param[in] cond Condition to check
+ * @param[in,out] idx Index at which to start adding the tensor's arguments. Will be incremented by the number of kernel arguments set.
+ * @param[in] tensor Tensor to set as an argument of the object's kernel.
+ * @param[in] window Window the kernel will be executed on.
+ */
+ void add_1D_tensor_argument_if(bool cond, unsigned int &idx, const ICLTensor *tensor, const Window &window)
+ {
+ if(cond)
+ {
+ add_1D_tensor_argument(idx, tensor, window);
+ }
+ }
+ /** Add the passed 2D tensor's parameters to the object's kernel's arguments starting from the index idx.
+ *
+ * @param[in,out] idx Index at which to start adding the tensor's arguments. Will be incremented by the number of kernel arguments set.
+ * @param[in] tensor Tensor to set as an argument of the object's kernel.
+ * @param[in] window Window the kernel will be executed on.
+ */
+ void add_2D_tensor_argument(unsigned int &idx, const ICLTensor *tensor, const Window &window)
+ {
+ add_tensor_argument<2>(idx, tensor, window);
+ }
+ /** Add the passed 2D tensor's parameters to the object's kernel's arguments starting from the index idx if the condition is true.
+ *
+ * @param[in] cond Condition to check
+ * @param[in,out] idx Index at which to start adding the tensor's arguments. Will be incremented by the number of kernel arguments set.
+ * @param[in] tensor Tensor to set as an argument of the object's kernel.
+ * @param[in] window Window the kernel will be executed on.
+ */
+ void add_2D_tensor_argument_if(bool cond, unsigned int &idx, const ICLTensor *tensor, const Window &window)
+ {
+ if(cond)
+ {
+ add_2D_tensor_argument(idx, tensor, window);
+ }
+ }
+ /** Add the passed 3D tensor's parameters to the object's kernel's arguments starting from the index idx.
+ *
+ * @param[in,out] idx Index at which to start adding the tensor's arguments. Will be incremented by the number of kernel arguments set.
+ * @param[in] tensor Tensor to set as an argument of the object's kernel.
+ * @param[in] window Window the kernel will be executed on.
+ */
+ void add_3D_tensor_argument(unsigned int &idx, const ICLTensor *tensor, const Window &window)
+ {
+ add_tensor_argument<3>(idx, tensor, window);
+ }
+ /** Add the passed 4D tensor's parameters to the object's kernel's arguments starting from the index idx.
+ *
+ * @param[in,out] idx Index at which to start adding the tensor's arguments. Will be incremented by the number of kernel arguments set.
+ * @param[in] tensor Tensor to set as an argument of the object's kernel.
+ * @param[in] window Window the kernel will be executed on.
+ */
+ void add_4D_tensor_argument(unsigned int &idx, const ICLTensor *tensor, const Window &window)
+ {
+ add_tensor_argument<4>(idx, tensor, window);
+ }
+ /** Returns the number of arguments enqueued per 1D array object.
+ *
+ * @return The number of arguments enqueues per 1D array object.
+ */
+ constexpr static unsigned int num_arguments_per_1D_array()
+ {
+ return num_arguments_per_array<1>();
+ }
+ /** Returns the number of arguments enqueued per 1D tensor object.
+ *
+ * @return The number of arguments enqueues per 1D tensor object.
+ */
+ constexpr static unsigned int num_arguments_per_1D_tensor()
+ {
+ return num_arguments_per_tensor<1>();
+ }
+ /** Returns the number of arguments enqueued per 2D tensor object.
+ *
+ * @return The number of arguments enqueues per 2D tensor object.
+ */
+ constexpr static unsigned int num_arguments_per_2D_tensor()
+ {
+ return num_arguments_per_tensor<2>();
+ }
+ /** Returns the number of arguments enqueued per 3D tensor object.
+ *
+ * @return The number of arguments enqueues per 3D tensor object.
+ */
+ constexpr static unsigned int num_arguments_per_3D_tensor()
+ {
+ return num_arguments_per_tensor<3>();
+ }
+ /** Returns the number of arguments enqueued per 4D tensor object.
+ *
+ * @return The number of arguments enqueues per 4D tensor object.
+ */
+ constexpr static unsigned int num_arguments_per_4D_tensor()
+ {
+ return num_arguments_per_tensor<4>();
+ }
+ /** Enqueue the OpenCL kernel to process the given window on the passed OpenCL command queue.
+ *
+ * @note The queue is *not* flushed by this method, and therefore the kernel will not have been executed by the time this method returns.
+ *
+ * @param[in] window Region on which to execute the kernel. (Must be a valid region of the window returned by window()).
+ * @param[in,out] queue Command queue on which to enqueue the kernel.
+ */
+ virtual void run(const Window &window, cl::CommandQueue &queue)
+ {
+ ARM_COMPUTE_UNUSED(window, queue);
+ }
+ /** Enqueue the OpenCL kernel to process the given window on the passed OpenCL command queue.
+ *
+ * @note The queue is *not* flushed by this method, and therefore the kernel will not have been executed by the time this method returns.
+ *
+ * @param[in] tensors A vector containing the tensors to operato on.
+ * @param[in] window Region on which to execute the kernel. (Must be a valid region of the window returned by window()).
+ * @param[in,out] queue Command queue on which to enqueue the kernel.
+ */
+ virtual void run_op(ITensorPack &tensors, const Window &window, cl::CommandQueue &queue)
+ {
+ ARM_COMPUTE_UNUSED(tensors, window, queue);
+ }
+ /** Add the passed parameters to the object's kernel's arguments starting from the index idx.
+ *
+ * @param[in,out] idx Index at which to start adding the arguments. Will be incremented by the number of kernel arguments set.
+ * @param[in] value Value to set as an argument of the object's kernel.
+ */
+ template <typename T>
+ void add_argument(unsigned int &idx, T value)
+ {
+ _kernel.setArg(idx++, value);
+ }
+
+ /** Set the Local-Workgroup-Size hint
+ *
+ * @note This method should be called after the configuration of the kernel
+ *
+ * @param[in] lws_hint Local-Workgroup-Size to use
+ */
+ void set_lws_hint(const cl::NDRange &lws_hint)
+ {
+ ARM_COMPUTE_ERROR_ON_UNCONFIGURED_KERNEL(this); // lws_hint will be overwritten by configure()
+ _lws_hint = lws_hint;
+ }
+
+ /** Return the Local-Workgroup-Size hint
+ *
+ * @return Current lws hint
+ */
+ cl::NDRange lws_hint() const
+ {
+ return _lws_hint;
+ }
+
+ /** Get the configuration ID
+ *
+ * @note The configuration ID can be used by the caller to distinguish different calls of the same OpenCL kernel
+ * In particular, this method can be used by CLScheduler to keep track of the best LWS for each configuration of the same kernel.
+ * The configuration ID should be provided only for the kernels potentially affected by the LWS geometry
+ *
+ * @note This method should be called after the configuration of the kernel
+ *
+ * @return configuration id string
+ */
+ const std::string &config_id() const
+ {
+ return _config_id;
+ }
+
+ /** Set the targeted GPU architecture
+ *
+ * @param[in] target The targeted GPU architecture
+ */
+ void set_target(GPUTarget target)
+ {
+ _target = target;
+ }
+
+ /** Set the targeted GPU architecture according to the CL device
+ *
+ * @param[in] device A CL device
+ */
+ void set_target(cl::Device &device);
+
+ /** Get the targeted GPU architecture
+ *
+ * @return The targeted GPU architecture.
+ */
+ GPUTarget get_target() const
+ {
+ return _target;
+ }
+
+ /** Get the maximum workgroup size for the device the CLKernelLibrary uses.
+ *
+ * @return The maximum workgroup size value.
+ */
+ size_t get_max_workgroup_size();
+ /** Get the global work size given an execution window
+ *
+ * @param[in] window Execution window
+ *
+ * @return Global work size of the given execution window
+ */
+ static cl::NDRange gws_from_window(const Window &window);
+
+private:
+ /** Add the passed array's parameters to the object's kernel's arguments starting from the index idx.
+ *
+ * @param[in,out] idx Index at which to start adding the array's arguments. Will be incremented by the number of kernel arguments set.
+ * @param[in] array Array to set as an argument of the object's kernel.
+ * @param[in] strides @ref Strides object containing stride of each dimension in bytes.
+ * @param[in] num_dimensions Number of dimensions of the @p array.
+ * @param[in] window Window the kernel will be executed on.
+ */
+ template <typename T, unsigned int dimension_size>
+ void add_array_argument(unsigned int &idx, const ICLArray<T> *array, const Strides &strides, unsigned int num_dimensions, const Window &window);
+ /** Add the passed tensor's parameters to the object's kernel's arguments starting from the index idx.
+ *
+ * @param[in,out] idx Index at which to start adding the tensor's arguments. Will be incremented by the number of kernel arguments set.
+ * @param[in] tensor Tensor to set as an argument of the object's kernel.
+ * @param[in] window Window the kernel will be executed on.
+ */
+ template <unsigned int dimension_size>
+ void add_tensor_argument(unsigned int &idx, const ICLTensor *tensor, const Window &window);
+
+protected:
+ cl::Kernel _kernel; /**< OpenCL kernel to run */
+ GPUTarget _target; /**< The targeted GPU */
+ std::string _config_id; /**< Configuration ID */
+ size_t _max_workgroup_size; /**< The maximum workgroup size for this kernel */
+private:
+ cl::NDRange _lws_hint; /**< Local workgroup size hint for the OpenCL kernel */
+};
+
+/** Add the kernel to the command queue with the given window.
+ *
+ * @note Depending on the size of the window, this might translate into several jobs being enqueued.
+ *
+ * @note If kernel->kernel() is empty then the function will return without adding anything to the queue.
+ *
+ * @param[in,out] queue OpenCL command queue.
+ * @param[in] kernel Kernel to enqueue
+ * @param[in] window Window the kernel has to process.
+ * @param[in] lws_hint (Optional) Local workgroup size requested. Default is based on the device target.
+ * @param[in] use_dummy_work_items (Optional) Use dummy work items in order to have two dimensional power of two NDRange. Default is false
+ * Note: it is kernel responsibility to check if the work-item is out-of-range
+ *
+ * @note If any dimension of the lws is greater than the global workgroup size then no lws will be passed.
+ */
+void enqueue(cl::CommandQueue &queue, ICLKernel &kernel, const Window &window, const cl::NDRange &lws_hint = CLKernelLibrary::get().default_ndrange(), bool use_dummy_work_items = false);
+
+/** Add the passed array's parameters to the object's kernel's arguments starting from the index idx.
+ *
+ * @param[in,out] idx Index at which to start adding the array's arguments. Will be incremented by the number of kernel arguments set.
+ * @param[in] array Array to set as an argument of the object's kernel.
+ * @param[in] strides @ref Strides object containing stride of each dimension in bytes.
+ * @param[in] num_dimensions Number of dimensions of the @p array.
+ * @param[in] window Window the kernel will be executed on.
+ */
+template <typename T, unsigned int dimension_size>
+void ICLKernel::add_array_argument(unsigned &idx, const ICLArray<T> *array, const Strides &strides, unsigned int num_dimensions, const Window &window)
+{
+ ARM_COMPUTE_ERROR_ON(array == nullptr);
+
+ // Calculate offset to the start of the window
+ unsigned int offset_first_element = 0;
+
+ for(unsigned int n = 0; n < num_dimensions; ++n)
+ {
+ offset_first_element += window[n].start() * strides[n];
+ }
+
+ unsigned int idx_start = idx;
+ _kernel.setArg(idx++, array->cl_buffer());
+
+ for(unsigned int dimension = 0; dimension < dimension_size; dimension++)
+ {
+ _kernel.setArg<cl_uint>(idx++, strides[dimension]);
+ _kernel.setArg<cl_uint>(idx++, strides[dimension] * window[dimension].step());
+ }
+
+ _kernel.setArg<cl_uint>(idx++, offset_first_element);
+
+ ARM_COMPUTE_ERROR_ON_MSG_VAR(idx_start + num_arguments_per_array<dimension_size>() != idx,
+ "add_%dD_array_argument() is supposed to add exactly %d arguments to the kernel", dimension_size, num_arguments_per_array<dimension_size>());
+ ARM_COMPUTE_UNUSED(idx_start);
+}
+}
+#endif /*ARM_COMPUTE_ICLKERNEL_H */