diff options
Diffstat (limited to 'src/runtime/IScheduler.cpp')
| -rw-r--r-- | src/runtime/IScheduler.cpp | 178 |
1 files changed, 172 insertions, 6 deletions
diff --git a/src/runtime/IScheduler.cpp b/src/runtime/IScheduler.cpp index b2edad0ca5..ecf84abd2c 100644 --- a/src/runtime/IScheduler.cpp +++ b/src/runtime/IScheduler.cpp @@ -1,5 +1,5 @@ /* - * Copyright (c) 2016-2018 ARM Limited. + * Copyright (c) 2016-2023 Arm Limited. * * SPDX-License-Identifier: MIT * @@ -23,32 +23,198 @@ */ #include "arm_compute/runtime/IScheduler.h" +#include "arm_compute/core/CPP/ICPPKernel.h" #include "arm_compute/core/Error.h" -#include "arm_compute/runtime/CPUUtils.h" +#include "arm_compute/core/Log.h" +#include "arm_compute/core/Window.h" + +#include "src/common/cpuinfo/CpuInfo.h" +#include "src/runtime/SchedulerUtils.h" namespace arm_compute { IScheduler::IScheduler() - : _cpu_info() { - get_cpu_configuration(_cpu_info); // Work out the best possible number of execution threads - _num_threads_hint = get_threads_hint(); + _num_threads_hint = cpuinfo::num_threads_hint(); } CPUInfo &IScheduler::cpu_info() { - return _cpu_info; + return CPUInfo::get(); +} + +void IScheduler::set_num_threads_with_affinity(unsigned int num_threads, BindFunc func) +{ + ARM_COMPUTE_UNUSED(num_threads, func); + ARM_COMPUTE_ERROR("Feature for affinity setting is not implemented"); } unsigned int IScheduler::num_threads_hint() const { return _num_threads_hint; } + +void IScheduler::schedule_common(ICPPKernel *kernel, const Hints &hints, const Window &window, ITensorPack &tensors) +{ + ARM_COMPUTE_ERROR_ON_MSG(!kernel, "The child class didn't set the kernel"); +#ifndef BARE_METAL + const Window &max_window = window; + if (hints.split_dimension() == IScheduler::split_dimensions_all) + { + /* + * if the split dim is size_t max then this signals we should parallelise over + * all dimensions + */ + const std::size_t m = max_window.num_iterations(Window::DimX); + const std::size_t n = max_window.num_iterations(Window::DimY); + + //in c++17 this can be swapped for auto [ m_threads, n_threads ] = split_2d(... + unsigned m_threads, n_threads; + std::tie(m_threads, n_threads) = scheduler_utils::split_2d(this->num_threads(), m, n); + + std::vector<IScheduler::Workload> workloads; + for (unsigned int ni = 0; ni != n_threads; ++ni) + { + for (unsigned int mi = 0; mi != m_threads; ++mi) + { + workloads.push_back( + [ni, mi, m_threads, n_threads, &max_window, &kernel](const ThreadInfo &info) + { + //narrow the window to our mi-ni workload + Window win = max_window.split_window(Window::DimX, mi, m_threads) + .split_window(Window::DimY, ni, n_threads); + + win.validate(); + + Window thread_locator; + thread_locator.set(Window::DimX, Window::Dimension(mi, m_threads)); + thread_locator.set(Window::DimY, Window::Dimension(ni, n_threads)); + + thread_locator.validate(); + + kernel->run_nd(win, info, thread_locator); + }); + } + } + run_workloads(workloads); + } + else + { + const unsigned int num_iterations = max_window.num_iterations(hints.split_dimension()); + const unsigned int num_threads = std::min(num_iterations, this->num_threads()); + + if (num_iterations == 0) + { + return; + } + + if (!kernel->is_parallelisable() || num_threads == 1) + { + ThreadInfo info; + info.cpu_info = &cpu_info(); + if (tensors.empty()) + { + kernel->run(max_window, info); + } + else + { + kernel->run_op(tensors, max_window, info); + } + } + else + { + unsigned int num_windows = 0; + switch (hints.strategy()) + { + case StrategyHint::STATIC: + num_windows = num_threads; + break; + case StrategyHint::DYNAMIC: + { + const unsigned int granule_threshold = + (hints.threshold() <= 0) ? num_threads : static_cast<unsigned int>(hints.threshold()); + // Make sure we don't use some windows which are too small as this might create some contention on the ThreadFeeder + num_windows = num_iterations > granule_threshold ? granule_threshold : num_iterations; + break; + } + default: + ARM_COMPUTE_ERROR("Unknown strategy"); + } + // Make sure the smallest window is larger than minimum workload size + num_windows = adjust_num_of_windows(max_window, hints.split_dimension(), num_windows, *kernel, cpu_info()); + + std::vector<IScheduler::Workload> workloads(num_windows); + for (unsigned int t = 0; t < num_windows; ++t) + { + //Capture 't' by copy, all the other variables by reference: + workloads[t] = [t, &hints, &max_window, &num_windows, &kernel, &tensors](const ThreadInfo &info) + { + Window win = max_window.split_window(hints.split_dimension(), t, num_windows); + win.validate(); + + if (tensors.empty()) + { + kernel->run(win, info); + } + else + { + kernel->run_op(tensors, win, info); + } + }; + } + run_workloads(workloads); + } + } +#else /* !BARE_METAL */ + ARM_COMPUTE_UNUSED(kernel, hints, window, tensors); +#endif /* !BARE_METAL */ +} + void IScheduler::run_tagged_workloads(std::vector<Workload> &workloads, const char *tag) { ARM_COMPUTE_UNUSED(tag); run_workloads(workloads); } +std::size_t IScheduler::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) +{ + // Mitigation of the narrow split issue, which occurs when the split dimension is too small to split (hence "narrow"). + if (window.num_iterations(split_dimension) < init_num_windows) + { + auto recommended_split_dim = Window::DimX; + for (std::size_t dims = Window::DimY; dims <= Window::DimW; ++dims) + { + if (window.num_iterations(recommended_split_dim) < window.num_iterations(dims)) + { + recommended_split_dim = dims; + } + } + ARM_COMPUTE_LOG_INFO_MSG_WITH_FORMAT_CORE( + "%zu dimension is not a suitable dimension to split the workload. Recommended: %zu recommended_split_dim", + split_dimension, recommended_split_dim); + } + + for (auto t = init_num_windows; t > 0; --t) // Trying the highest number of windows ,init_num_windows, first + { + // Try splitting the workload into t, subject to each subworkload size <= mws. + if ((window.num_iterations(split_dimension) / kernel.get_mws(cpu_info, t)) >= t) + { + if (t != init_num_windows) + { + ARM_COMPUTE_LOG_INFO_MSG_CORE( + "The scheduler is using a different thread count than the one assigned by the user."); + } + return t; + } + } + ARM_COMPUTE_LOG_INFO_MSG_CORE( + "The scheduler is using single thread instead of the thread count assigned by the user."); + return 1; // If the workload is so small that it can't be split, we should run a single thread +} + } // namespace arm_compute |