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https://sourceware.org/git/binutils-gdb.git
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63078a0498
I found that parallel_for_each would submit empty tasks to the thread pool. For example, this can happen if the number of tasks is smaller than the number of available threads. In the DWARF reader, this resulted in the cooked index containing empty sub-indices. This patch arranges to instead shrink the result vector and process the trailing entries in the calling thread.
330 lines
9.1 KiB
C++
330 lines
9.1 KiB
C++
/* Parallel for loops
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Copyright (C) 2019-2023 Free Software Foundation, Inc.
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This file is part of GDB.
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This program is free software; you can redistribute it and/or modify
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it under the terms of the GNU General Public License as published by
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the Free Software Foundation; either version 3 of the License, or
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(at your option) any later version.
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This program is distributed in the hope that it will be useful,
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but WITHOUT ANY WARRANTY; without even the implied warranty of
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MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
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GNU General Public License for more details.
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You should have received a copy of the GNU General Public License
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along with this program. If not, see <http://www.gnu.org/licenses/>. */
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#ifndef GDBSUPPORT_PARALLEL_FOR_H
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#define GDBSUPPORT_PARALLEL_FOR_H
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#include <algorithm>
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#include <type_traits>
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#include "gdbsupport/invoke-result.h"
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#include "gdbsupport/thread-pool.h"
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#include "gdbsupport/function-view.h"
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namespace gdb
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{
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namespace detail
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{
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/* This is a helper class that is used to accumulate results for
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parallel_for. There is a specialization for 'void', below. */
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template<typename T>
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struct par_for_accumulator
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{
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public:
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explicit par_for_accumulator (size_t n_threads)
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: m_futures (n_threads)
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{
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}
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/* The result type that is accumulated. */
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typedef std::vector<T> result_type;
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/* Post the Ith task to a background thread, and store a future for
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later. */
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void post (size_t i, std::function<T ()> task)
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{
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m_futures[i]
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= gdb::thread_pool::g_thread_pool->post_task (std::move (task));
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}
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/* Invoke TASK in the current thread, then compute all the results
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from all background tasks and put them into a result vector,
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which is returned. */
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result_type finish (gdb::function_view<T ()> task)
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{
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result_type result (m_futures.size () + 1);
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result.back () = task ();
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for (size_t i = 0; i < m_futures.size (); ++i)
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result[i] = m_futures[i].get ();
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return result;
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}
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/* Resize the results to N. */
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void resize (size_t n)
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{
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m_futures.resize (n);
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}
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private:
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/* A vector of futures coming from the tasks run in the
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background. */
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std::vector<gdb::future<T>> m_futures;
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};
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/* See the generic template. */
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template<>
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struct par_for_accumulator<void>
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{
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public:
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explicit par_for_accumulator (size_t n_threads)
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: m_futures (n_threads)
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{
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}
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/* This specialization does not compute results. */
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typedef void result_type;
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void post (size_t i, std::function<void ()> task)
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{
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m_futures[i]
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= gdb::thread_pool::g_thread_pool->post_task (std::move (task));
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}
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result_type finish (gdb::function_view<void ()> task)
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{
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task ();
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for (auto &future : m_futures)
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{
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/* Use 'get' and not 'wait', to propagate any exception. */
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future.get ();
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}
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}
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/* Resize the results to N. */
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void resize (size_t n)
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{
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m_futures.resize (n);
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}
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private:
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std::vector<gdb::future<void>> m_futures;
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};
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}
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/* A very simple "parallel for". This splits the range of iterators
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into subranges, and then passes each subrange to the callback. The
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work may or may not be done in separate threads.
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This approach was chosen over having the callback work on single
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items because it makes it simple for the caller to do
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once-per-subrange initialization and destruction.
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The parameter N says how batching ought to be done -- there will be
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at least N elements processed per thread. Setting N to 0 is not
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allowed.
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If the function returns a non-void type, then a vector of the
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results is returned. The size of the resulting vector depends on
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the number of threads that were used. */
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template<class RandomIt, class RangeFunction>
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typename gdb::detail::par_for_accumulator<
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typename gdb::invoke_result<RangeFunction, RandomIt, RandomIt>::type
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>::result_type
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parallel_for_each (unsigned n, RandomIt first, RandomIt last,
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RangeFunction callback,
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gdb::function_view<size_t(RandomIt)> task_size = nullptr)
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{
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using result_type
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= typename gdb::invoke_result<RangeFunction, RandomIt, RandomIt>::type;
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/* If enabled, print debug info about how the work is distributed across
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the threads. */
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const bool parallel_for_each_debug = false;
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size_t n_worker_threads = thread_pool::g_thread_pool->thread_count ();
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size_t n_threads = n_worker_threads;
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size_t n_elements = last - first;
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size_t elts_per_thread = 0;
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size_t elts_left_over = 0;
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size_t total_size = 0;
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size_t size_per_thread = 0;
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size_t max_element_size = n_elements == 0 ? 1 : SIZE_MAX / n_elements;
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if (n_threads > 1)
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{
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if (task_size != nullptr)
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{
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gdb_assert (n == 1);
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for (RandomIt i = first; i != last; ++i)
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{
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size_t element_size = task_size (i);
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gdb_assert (element_size > 0);
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if (element_size > max_element_size)
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/* We could start scaling here, but that doesn't seem to be
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worth the effort. */
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element_size = max_element_size;
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size_t prev_total_size = total_size;
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total_size += element_size;
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/* Check for overflow. */
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gdb_assert (prev_total_size < total_size);
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}
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size_per_thread = total_size / n_threads;
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}
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else
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{
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/* Require that there should be at least N elements in a
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thread. */
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gdb_assert (n > 0);
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if (n_elements / n_threads < n)
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n_threads = std::max (n_elements / n, (size_t) 1);
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elts_per_thread = n_elements / n_threads;
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elts_left_over = n_elements % n_threads;
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/* n_elements == n_threads * elts_per_thread + elts_left_over. */
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}
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}
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size_t count = n_threads == 0 ? 0 : n_threads - 1;
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gdb::detail::par_for_accumulator<result_type> results (count);
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if (parallel_for_each_debug)
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{
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debug_printf (_("Parallel for: n_elements: %zu\n"), n_elements);
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if (task_size != nullptr)
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{
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debug_printf (_("Parallel for: total_size: %zu\n"), total_size);
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debug_printf (_("Parallel for: size_per_thread: %zu\n"), size_per_thread);
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}
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else
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{
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debug_printf (_("Parallel for: minimum elements per thread: %u\n"), n);
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debug_printf (_("Parallel for: elts_per_thread: %zu\n"), elts_per_thread);
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}
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}
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size_t remaining_size = total_size;
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for (int i = 0; i < count; ++i)
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{
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RandomIt end;
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size_t chunk_size = 0;
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if (task_size == nullptr)
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{
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end = first + elts_per_thread;
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if (i < elts_left_over)
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/* Distribute the leftovers over the worker threads, to avoid having
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to handle all of them in a single thread. */
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end++;
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}
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else
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{
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RandomIt j;
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for (j = first; j < last && chunk_size < size_per_thread; ++j)
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{
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size_t element_size = task_size (j);
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if (element_size > max_element_size)
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element_size = max_element_size;
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chunk_size += element_size;
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}
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end = j;
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remaining_size -= chunk_size;
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}
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/* This case means we don't have enough elements to really
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distribute them. Rather than ever submit a task that does
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nothing, we short-circuit here. */
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if (first == end)
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end = last;
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if (end == last)
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{
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/* We're about to dispatch the last batch of elements, which
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we normally process in the main thread. So just truncate
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the result list here. This avoids submitting empty tasks
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to the thread pool. */
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count = i;
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results.resize (count);
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break;
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}
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if (parallel_for_each_debug)
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{
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debug_printf (_("Parallel for: elements on worker thread %i\t: %zu"),
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i, (size_t)(end - first));
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if (task_size != nullptr)
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debug_printf (_("\t(size: %zu)"), chunk_size);
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debug_printf (_("\n"));
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}
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results.post (i, [=] ()
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{
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return callback (first, end);
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});
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first = end;
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}
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for (int i = count; i < n_worker_threads; ++i)
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if (parallel_for_each_debug)
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{
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debug_printf (_("Parallel for: elements on worker thread %i\t: 0"), i);
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if (task_size != nullptr)
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debug_printf (_("\t(size: 0)"));
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debug_printf (_("\n"));
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}
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/* Process all the remaining elements in the main thread. */
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if (parallel_for_each_debug)
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{
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debug_printf (_("Parallel for: elements on main thread\t\t: %zu"),
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(size_t)(last - first));
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if (task_size != nullptr)
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debug_printf (_("\t(size: %zu)"), remaining_size);
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debug_printf (_("\n"));
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}
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return results.finish ([=] ()
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{
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return callback (first, last);
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});
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}
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/* A sequential drop-in replacement of parallel_for_each. This can be useful
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when debugging multi-threading behaviour, and you want to limit
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multi-threading in a fine-grained way. */
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template<class RandomIt, class RangeFunction>
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typename gdb::detail::par_for_accumulator<
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typename gdb::invoke_result<RangeFunction, RandomIt, RandomIt>::type
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>::result_type
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sequential_for_each (unsigned n, RandomIt first, RandomIt last,
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RangeFunction callback,
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gdb::function_view<size_t(RandomIt)> task_size = nullptr)
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{
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using result_type = typename gdb::invoke_result<RangeFunction, RandomIt, RandomIt>::type;
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gdb::detail::par_for_accumulator<result_type> results (0);
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/* Process all the remaining elements in the main thread. */
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return results.finish ([=] ()
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{
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return callback (first, last);
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});
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}
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}
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#endif /* GDBSUPPORT_PARALLEL_FOR_H */
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