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I would like to use gdb::parallel_for_each to implement the parallelism of the DWARF unit indexing. However, the existing implementation of gdb::parallel_for_each is blocking, which doesn't work with the model used by the DWARF indexer, which is asynchronous and callback-based. Add an asynchronouys version of gdb::parallel_for_each that will be suitable for this task. This new version accepts a callback that is invoked when the parallel for each is complete. This function uses the same strategy as gdb::task_group to invoke the "done" callback: worker threads have a shared_ptr reference to some object. The last worker thread to drop its reference causes the object to be deleted, which invokes the callback. Unlike for the sync version of gdb::parallel_for_each, it's not possible to keep any state in the calling thread's stack, because that disappears immediately after starting the workers. So all the state is kept in that same shared object. There is a limitation that the sync version doesn't have, regarding the arguments you can pass to the worker objects: it's not possibly to rely on references. There are more details in a comment in the code. It would be possible to implement the sync version of gdb::parallel_for_each on top of the async version, but I decided not to do it to avoid the unnecessary dynamic allocation of the shared object, and to avoid adding the limitations on passing references I mentioned just above. But if we judge that it would be an acceptable cost to avoid the duplication, we could do it. Add a self test for the new function. Change-Id: I6173defb1e09856d137c1aa05ad51cbf521ea0b0 Approved-By: Tom Tromey <tom@tromey.com>
259 lines
8.0 KiB
C++
259 lines
8.0 KiB
C++
/* Parallel for loops
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Copyright (C) 2019-2025 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 <atomic>
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#include <tuple>
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#include "gdbsupport/iterator-range.h"
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#include "gdbsupport/thread-pool.h"
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#include "gdbsupport/work-queue.h"
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namespace gdb
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{
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/* If enabled, print debug info about the inner workings of the parallel for
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each functions. */
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constexpr bool parallel_for_each_debug = false;
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/* A "parallel-for" implementation using a shared work queue. Work items get
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popped in batches of size up to BATCH_SIZE from the queue and handed out to
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worker threads.
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Each worker thread instantiates an object of type Worker, forwarding ARGS to
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its constructor. The Worker object can be used to keep some per-worker
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thread state.
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Worker threads call Worker::operator() repeatedly until the queue is
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empty.
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This function is synchronous, meaning that it blocks and returns once the
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processing is complete. */
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template<std::size_t batch_size, class RandomIt, class Worker,
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class... WorkerArgs>
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void
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parallel_for_each (const RandomIt first, const RandomIt last,
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WorkerArgs &&...worker_args)
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{
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gdb_assert (first <= last);
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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",
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static_cast<std::size_t> (last - first));
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debug_printf ("Parallel for: batch size: %zu\n", batch_size);
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}
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std::vector<gdb::future<void>> results;
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work_queue<RandomIt, batch_size> queue (first, last);
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/* The worker thread task.
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We need to capture args as a tuple, because it's not possible to capture
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the parameter pack directly in C++17. Once we migrate to C++20, the
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capture can be simplified to:
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... args = std::forward<Args>(args)
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and `args` can be used as-is in the lambda. */
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auto args_tuple
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= std::forward_as_tuple (std::forward<WorkerArgs> (worker_args)...);
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auto task = [&queue, first, &args_tuple] ()
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{
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/* Instantiate the user-defined worker. */
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auto worker = std::make_from_tuple<Worker> (args_tuple);
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for (;;)
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{
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const auto batch = queue.pop_batch ();
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if (batch.empty ())
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break;
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if (parallel_for_each_debug)
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debug_printf ("Processing %zu items, range [%zu, %zu[\n",
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batch.size (),
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batch.begin () - first,
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batch.end () - first);
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worker (batch);
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}
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};
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/* Start N_WORKER_THREADS tasks. */
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const size_t n_worker_threads
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= std::max<size_t> (thread_pool::g_thread_pool->thread_count (), 1);
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for (int i = 0; i < n_worker_threads; ++i)
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results.push_back (gdb::thread_pool::g_thread_pool->post_task (task));
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/* Wait for all of them to be finished. */
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for (auto &fut : results)
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fut.get ();
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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 behavior, and you want to limit
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multi-threading in a fine-grained way. */
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template<class RandomIt, class Worker, class... WorkerArgs>
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void
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sequential_for_each (RandomIt first, RandomIt last, WorkerArgs &&...worker_args)
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{
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if (first == last)
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return;
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Worker (std::forward<WorkerArgs> (worker_args)...) ({ first, last });
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}
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namespace detail
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{
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/* Type to hold the state shared between threads of
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gdb::parallel_for_each_async. */
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template<std::size_t min_batch_size, typename RandomIt, typename... WorkerArgs>
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struct pfea_state
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{
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pfea_state (RandomIt first, RandomIt last, std::function<void ()> &&done,
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WorkerArgs &&...worker_args)
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: first (first),
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last (last),
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worker_args_tuple (std::forward_as_tuple
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(std::forward<WorkerArgs> (worker_args)...)),
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queue (first, last),
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m_done (std::move (done))
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{}
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DISABLE_COPY_AND_ASSIGN (pfea_state);
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/* This gets called by the last worker thread that drops its reference on
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the shared state, thus when the processing is complete. */
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~pfea_state ()
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{
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if (m_done)
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m_done ();
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}
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/* The interval to process. */
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const RandomIt first, last;
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/* Tuple of arguments to pass when constructing the user's worker object.
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Use std::decay_t to avoid storing references to the caller's local
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variables. If we didn't use it and the caller passed an lvalue `foo *`,
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we would store it as a reference to `foo *`, thus storing a reference to
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the caller's local variable.
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The downside is that it's not possible to pass arguments by reference,
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callers need to pass pointers or std::reference_wrappers. */
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std::tuple<std::decay_t<WorkerArgs>...> worker_args_tuple;
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/* Work queue that worker threads pull work items from. */
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work_queue<RandomIt, min_batch_size> queue;
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private:
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/* Callable called when the parallel-for is done. */
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std::function<void ()> m_done;
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};
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} /* namespace detail */
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/* A "parallel-for" implementation using a shared work queue. Work items get
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popped in batches from the queue and handed out to worker threads.
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Batch sizes are proportional to the number of remaining items in the queue,
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but always greater or equal to MIN_BATCH_SIZE.
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The DONE callback is invoked when processing is done.
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Each worker thread instantiates an object of type Worker, forwarding ARGS to
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its constructor. The Worker object can be used to keep some per-worker
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thread state. This version does not support passing references as arguments
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to the worker. Use std::reference_wrapper or pointers instead.
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Worker threads call Worker::operator() repeatedly until the queue is
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empty.
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This function is asynchronous. An arbitrary worker thread will call the DONE
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callback when processing is done. */
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template<std::size_t min_batch_size, class RandomIt, class Worker,
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class... WorkerArgs>
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void
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parallel_for_each_async (const RandomIt first, const RandomIt last,
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std::function<void ()> &&done,
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WorkerArgs &&...worker_args)
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{
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gdb_assert (first <= last);
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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",
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static_cast<std::size_t> (last - first));
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debug_printf ("Parallel for: min batch size: %zu\n", min_batch_size);
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}
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const size_t n_worker_threads
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= std::max<size_t> (thread_pool::g_thread_pool->thread_count (), 1);
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/* The state shared between all worker threads. All worker threads get a
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reference on the shared pointer through the lambda below. The last worker
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thread to drop its reference will cause this object to be destroyed, which
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will call the DONE callback. */
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using state_t = detail::pfea_state<min_batch_size, RandomIt, WorkerArgs...>;
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auto state
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= std::make_shared<state_t> (first, last, std::move (done),
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std::forward<WorkerArgs> (worker_args)...);
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/* The worker thread task. */
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auto task = [state] ()
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{
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/* Instantiate the user-defined worker. */
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auto worker = std::make_from_tuple<Worker> (state->worker_args_tuple);
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for (;;)
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{
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const auto batch = state->queue.pop_batch ();
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if (batch.empty ())
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break;
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if (parallel_for_each_debug)
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debug_printf ("Processing %zu items, range [%zu, %zu[\n",
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batch.size (),
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batch.begin () - state->first,
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batch.end () - state->first);
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worker (batch);
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}
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};
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/* Start N_WORKER_THREADS tasks. */
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for (int i = 0; i < n_worker_threads; ++i)
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gdb::thread_pool::g_thread_pool->post_task (task);
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}
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}
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#endif /* GDBSUPPORT_PARALLEL_FOR_H */
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