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/*
* Copyright (c) 2017-2021, 2023 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_ISCHEDULER_H
#define ARM_COMPUTE_ISCHEDULER_H
#include "arm_compute/core/CPP/CPPTypes.h"
#include "arm_compute/core/experimental/Types.h"
#include "arm_compute/core/Types.h"
#include <functional>
#include <limits>
namespace arm_compute
{
class ICPPKernel;
class ITensor;
class Window;
/** Scheduler interface to run kernels */
class IScheduler
{
public:
/** Strategies available to split a workload */
enum class StrategyHint
{
STATIC, /**< Split the workload evenly among the threads */
DYNAMIC, /**< Split the workload dynamically using a bucket system */
};
/** Function to be used and map a given thread id to a logical core id
*
* Mapping function expects the thread index and total number of cores as input,
* and returns the logical core index to bind against
*/
using BindFunc = std::function<int(int, int)>;
/** When arm_compute::ISchedular::Hints::_split_dimension is initialized with this value
* then the schedular is free to break down the problem space over as many dimensions
* as it wishes
*/
static constexpr unsigned int split_dimensions_all = std::numeric_limits<unsigned>::max();
/** Scheduler hints
*
* Collection of preferences set by the function regarding how to split a given workload
*/
class Hints
{
public:
/** Constructor
*
* @param[in] split_dimension Dimension along which to split the kernel's execution window.
* @param[in] strategy (Optional) Split strategy.
* @param[in] threshold (Optional) Dynamic scheduling capping threshold.
*/
Hints(unsigned int split_dimension, StrategyHint strategy = StrategyHint::STATIC, int threshold = 0)
: _split_dimension(split_dimension), _strategy(strategy), _threshold(threshold)
{
}
/** Set the split_dimension hint
*
* @param[in] split_dimension Dimension along which to split the kernel's execution window.
*
* @return the Hints object
*/
Hints &set_split_dimension(unsigned int split_dimension)
{
_split_dimension = split_dimension;
return *this;
}
/** Return the prefered split dimension
*
* @return The split dimension
*/
unsigned int split_dimension() const
{
return _split_dimension;
}
/** Set the strategy hint
*
* @param[in] strategy Prefered strategy to use to split the workload
*
* @return the Hints object
*/
Hints &set_strategy(StrategyHint strategy)
{
_strategy = strategy;
return *this;
}
/** Return the prefered strategy to use to split workload.
*
* @return The strategy
*/
StrategyHint strategy() const
{
return _strategy;
}
/** Return the granule capping threshold to be used by dynamic scheduling.
*
* @return The capping threshold
*/
int threshold() const
{
return _threshold;
}
private:
unsigned int _split_dimension{};
StrategyHint _strategy{};
int _threshold{};
};
/** Signature for the workloads to execute */
using Workload = std::function<void(const ThreadInfo &)>;
/** Default constructor. */
IScheduler();
/** Destructor. */
virtual ~IScheduler() = default;
/** Sets the number of threads the scheduler will use to run the kernels.
*
* @param[in] num_threads If set to 0, then one thread per CPU core available on the system will be used, otherwise the number of threads specified.
*/
virtual void set_num_threads(unsigned int num_threads) = 0;
/** Sets the number of threads the scheduler will use to run the kernels but also using a binding function to pin the threads to given logical cores
*
* @param[in] num_threads If set to 0, then one thread per CPU core available on the system will be used, otherwise the number of threads specified.
* @param[in] func Binding function to use.
*/
virtual void set_num_threads_with_affinity(unsigned int num_threads, BindFunc func);
/** Returns the number of threads that the SingleThreadScheduler has in its pool.
*
* @return Number of threads available in SingleThreadScheduler.
*/
virtual unsigned int num_threads() const = 0;
/** Runs the kernel in the same thread as the caller synchronously.
*
* @param[in] kernel Kernel to execute.
* @param[in] hints Hints for the scheduler.
*/
virtual void schedule(ICPPKernel *kernel, const Hints &hints) = 0;
/** Runs the kernel in the same thread as the caller synchronously.
*
* @param[in] kernel Kernel to execute.
* @param[in] hints Hints for the scheduler.
* @param[in] window Window to use for kernel execution.
* @param[in] tensors Vector containing the tensors to operate on.
*/
virtual void schedule_op(ICPPKernel *kernel, const Hints &hints, const Window &window, ITensorPack &tensors) = 0;
/** Execute all the passed workloads
*
* @note There is no guarantee regarding the order in which the workloads will be executed or whether or not they will be executed in parallel.
*
* @param[in] workloads List of workloads to run
* @param[in] tag String that can be used by profiling tools to identify the workloads run by the scheduler (Can be null).
*/
virtual void run_tagged_workloads(std::vector<Workload> &workloads, const char *tag);
/** Get CPU info.
*
* @return CPU info.
*/
CPUInfo &cpu_info();
/** Get a hint for the best possible number of execution threads
*
* @warning In case we can't work out the best number of threads,
* std::thread::hardware_concurrency() is returned else 1 in case of bare metal builds
*
* @return Best possible number of execution threads to use
*/
unsigned int num_threads_hint() const;
protected:
/** Execute all the passed workloads
*
* @note there is no guarantee regarding the order in which the workloads will be executed or whether or not they will be executed in parallel.
*
* @param[in] workloads Array of workloads to run
*/
virtual void run_workloads(std::vector<Workload> &workloads) = 0;
/** Common scheduler logic to execute the given kernel
*
* @param[in] kernel Kernel to execute.
* @param[in] hints Hints for the scheduler.
* @param[in] window Window to use for kernel execution.
* @param[in] tensors Vector containing the tensors to operate on.
*/
void schedule_common(ICPPKernel *kernel, const Hints &hints, const Window &window, ITensorPack &tensors);
/** Adjust the number of windows to the optimize performance
* (used for small workloads where smaller number of threads might improve the performance)
*
* @param[in] window Window to use for kernel execution
* @param[in] split_dimension Axis of dimension to split
* @param[in] init_num_windows Initial number of sub-windows to split
* @param[in] kernel Kernel to execute
* @param[in] cpu_info The CPU platform used to create the context.
*
* @return Adjusted number of windows
*/
std::size_t adjust_num_of_windows(const Window &window,
std::size_t split_dimension,
std::size_t init_num_windows,
const ICPPKernel &kernel,
const CPUInfo &cpu_info);
private:
unsigned int _num_threads_hint = {};
};
} // namespace arm_compute
#endif /* ARM_COMPUTE_ISCHEDULER_H */
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