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godot/core/object/worker_thread_pool.cpp

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One Copyright Update to rule them all As many open source projects have started doing it, we're removing the current year from the copyright notice, so that we don't need to bump it every year. It seems like only the first year of publication is technically relevant for copyright notices, and even that seems to be something that many companies stopped listing altogether (in a version controlled codebase, the commits are a much better source of date of publication than a hardcoded copyright statement). We also now list Godot Engine contributors first as we're collectively the current maintainers of the project, and we clarify that the "exclusive" copyright of the co-founders covers the timespan before opensourcing (their further contributions are included as part of Godot Engine contributors). Also fixed "cf." Frenchism - it's meant as "refer to / see".
2023-01-05 12:25:55 +00:00
/**************************************************************************/
/* worker_thread_pool.cpp */
/**************************************************************************/
/* This file is part of: */
/* GODOT ENGINE */
/* https://godotengine.org */
/**************************************************************************/
/* Copyright (c) 2014-present Godot Engine contributors (see AUTHORS.md). */
/* Copyright (c) 2007-2014 Juan Linietsky, Ariel Manzur. */
/* */
/* 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. */
/**************************************************************************/
Implement a Worker ThreadPool This PR implements a worked thread pool. It uses a fixed amount of threads in a pool and allows scheduling tasks that can be run on threads (and then waited for). It satisfies the following use cases: * HTML5 thread count is fixed (and similar restrictions are known in consoles) so we need to reuse threads. * Thread spawning is slow in general, so reusing threads is faster anyway. * This implementation supports recursive waiting for tasks, making it less prone to deadlocks if threads from the pool also run tasks. After this is approved and merged, subsequent PRs will be needed to replace the ThreadWorkPool usage by this class.
2022-07-18 10:09:19 +00:00
#include "worker_thread_pool.h"
#include "core/os/os.h"
Remove ThreadWorkPool, replace by WorkerThreadPool The former needs to be allocated once per usage. The later is shared for all threads, which is more efficient. It can also be better debugged.
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void WorkerThreadPool::Task::free_template_userdata() {
ERR_FAIL_COND(!template_userdata);
ERR_FAIL_COND(native_func_userdata == nullptr);
BaseTemplateUserdata *btu = (BaseTemplateUserdata *)native_func_userdata;
memdelete(btu);
}
Implement a Worker ThreadPool This PR implements a worked thread pool. It uses a fixed amount of threads in a pool and allows scheduling tasks that can be run on threads (and then waited for). It satisfies the following use cases: * HTML5 thread count is fixed (and similar restrictions are known in consoles) so we need to reuse threads. * Thread spawning is slow in general, so reusing threads is faster anyway. * This implementation supports recursive waiting for tasks, making it less prone to deadlocks if threads from the pool also run tasks. After this is approved and merged, subsequent PRs will be needed to replace the ThreadWorkPool usage by this class.
2022-07-18 10:09:19 +00:00
WorkerThreadPool *WorkerThreadPool::singleton = nullptr;
void WorkerThreadPool::_process_task_queue() {
task_mutex.lock();
Task *task = task_queue.first()->self();
task_queue.remove(task_queue.first());
task_mutex.unlock();
_process_task(task);
}
void WorkerThreadPool::_process_task(Task *p_task) {
bool low_priority = p_task->low_priority;
if (p_task->group) {
// Handling a group
bool do_post = false;
Remove ThreadWorkPool, replace by WorkerThreadPool The former needs to be allocated once per usage. The later is shared for all threads, which is more efficient. It can also be better debugged.
2022-07-23 17:12:41 +00:00
Callable::CallError ce;
Variant ret;
Variant arg;
Variant *argptr = &arg;
Implement a Worker ThreadPool This PR implements a worked thread pool. It uses a fixed amount of threads in a pool and allows scheduling tasks that can be run on threads (and then waited for). It satisfies the following use cases: * HTML5 thread count is fixed (and similar restrictions are known in consoles) so we need to reuse threads. * Thread spawning is slow in general, so reusing threads is faster anyway. * This implementation supports recursive waiting for tasks, making it less prone to deadlocks if threads from the pool also run tasks. After this is approved and merged, subsequent PRs will be needed to replace the ThreadWorkPool usage by this class.
2022-07-18 10:09:19 +00:00
Remove ThreadWorkPool, replace by WorkerThreadPool The former needs to be allocated once per usage. The later is shared for all threads, which is more efficient. It can also be better debugged.
2022-07-23 17:12:41 +00:00
while (true) {
uint32_t work_index = p_task->group->index.postincrement();
if (work_index >= p_task->group->max) {
break;
}
if (p_task->native_group_func) {
p_task->native_group_func(p_task->native_func_userdata, work_index);
} else if (p_task->template_userdata) {
p_task->template_userdata->callback_indexed(work_index);
} else {
Implement a Worker ThreadPool This PR implements a worked thread pool. It uses a fixed amount of threads in a pool and allows scheduling tasks that can be run on threads (and then waited for). It satisfies the following use cases: * HTML5 thread count is fixed (and similar restrictions are known in consoles) so we need to reuse threads. * Thread spawning is slow in general, so reusing threads is faster anyway. * This implementation supports recursive waiting for tasks, making it less prone to deadlocks if threads from the pool also run tasks. After this is approved and merged, subsequent PRs will be needed to replace the ThreadWorkPool usage by this class.
2022-07-18 10:09:19 +00:00
arg = work_index;
Remove Signal connect binds Remove the optional argument p_binds from `Object::connect` since it was deprecated by Callable.bind(). Changed all uses of it to Callable.bind()
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p_task->callable.callp((const Variant **)&argptr, 1, ret, ce);
Implement a Worker ThreadPool This PR implements a worked thread pool. It uses a fixed amount of threads in a pool and allows scheduling tasks that can be run on threads (and then waited for). It satisfies the following use cases: * HTML5 thread count is fixed (and similar restrictions are known in consoles) so we need to reuse threads. * Thread spawning is slow in general, so reusing threads is faster anyway. * This implementation supports recursive waiting for tasks, making it less prone to deadlocks if threads from the pool also run tasks. After this is approved and merged, subsequent PRs will be needed to replace the ThreadWorkPool usage by this class.
2022-07-18 10:09:19 +00:00
}
Remove ThreadWorkPool, replace by WorkerThreadPool The former needs to be allocated once per usage. The later is shared for all threads, which is more efficient. It can also be better debugged.
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// This is the only way to ensure posting is done when all tasks are really complete.
uint32_t completed_amount = p_task->group->completed_index.increment();
if (completed_amount == p_task->group->max) {
do_post = true;
}
}
if (do_post && p_task->template_userdata) {
memdelete(p_task->template_userdata); // This is no longer needed at this point, so get rid of it.
Implement a Worker ThreadPool This PR implements a worked thread pool. It uses a fixed amount of threads in a pool and allows scheduling tasks that can be run on threads (and then waited for). It satisfies the following use cases: * HTML5 thread count is fixed (and similar restrictions are known in consoles) so we need to reuse threads. * Thread spawning is slow in general, so reusing threads is faster anyway. * This implementation supports recursive waiting for tasks, making it less prone to deadlocks if threads from the pool also run tasks. After this is approved and merged, subsequent PRs will be needed to replace the ThreadWorkPool usage by this class.
2022-07-18 10:09:19 +00:00
}
if (low_priority && use_native_low_priority_threads) {
p_task->completed = true;
p_task->done_semaphore.post();
if (do_post) {
p_task->group->completed.set_to(true);
}
} else {
if (do_post) {
p_task->group->done_semaphore.post();
p_task->group->completed.set_to(true);
}
uint32_t max_users = p_task->group->tasks_used + 1; // Add 1 because the thread waiting for it is also user. Read before to avoid another thread freeing task after increment.
uint32_t finished_users = p_task->group->finished.increment();
if (finished_users == max_users) {
// Get rid of the group, because nobody else is using it.
task_mutex.lock();
group_allocator.free(p_task->group);
task_mutex.unlock();
}
// For groups, tasks get rid of themselves.
task_mutex.lock();
task_allocator.free(p_task);
task_mutex.unlock();
}
} else {
if (p_task->native_func) {
p_task->native_func(p_task->native_func_userdata);
Remove ThreadWorkPool, replace by WorkerThreadPool The former needs to be allocated once per usage. The later is shared for all threads, which is more efficient. It can also be better debugged.
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} else if (p_task->template_userdata) {
p_task->template_userdata->callback();
memdelete(p_task->template_userdata);
Implement a Worker ThreadPool This PR implements a worked thread pool. It uses a fixed amount of threads in a pool and allows scheduling tasks that can be run on threads (and then waited for). It satisfies the following use cases: * HTML5 thread count is fixed (and similar restrictions are known in consoles) so we need to reuse threads. * Thread spawning is slow in general, so reusing threads is faster anyway. * This implementation supports recursive waiting for tasks, making it less prone to deadlocks if threads from the pool also run tasks. After this is approved and merged, subsequent PRs will be needed to replace the ThreadWorkPool usage by this class.
2022-07-18 10:09:19 +00:00
} else {
Callable::CallError ce;
Variant ret;
Remove Signal connect binds Remove the optional argument p_binds from `Object::connect` since it was deprecated by Callable.bind(). Changed all uses of it to Callable.bind()
2022-07-28 20:56:41 +00:00
p_task->callable.callp(nullptr, 0, ret, ce);
Implement a Worker ThreadPool This PR implements a worked thread pool. It uses a fixed amount of threads in a pool and allows scheduling tasks that can be run on threads (and then waited for). It satisfies the following use cases: * HTML5 thread count is fixed (and similar restrictions are known in consoles) so we need to reuse threads. * Thread spawning is slow in general, so reusing threads is faster anyway. * This implementation supports recursive waiting for tasks, making it less prone to deadlocks if threads from the pool also run tasks. After this is approved and merged, subsequent PRs will be needed to replace the ThreadWorkPool usage by this class.
2022-07-18 10:09:19 +00:00
}
p_task->completed = true;
p_task->done_semaphore.post();
}
if (!use_native_low_priority_threads && low_priority) {
// A low prioriry task was freed, so see if we can move a pending one to the high priority queue.
bool post = false;
task_mutex.lock();
if (low_priority_task_queue.first()) {
Task *low_prio_task = low_priority_task_queue.first()->self();
low_priority_task_queue.remove(low_priority_task_queue.first());
task_queue.add_last(&low_prio_task->task_elem);
post = true;
} else {
low_priority_threads_used.decrement();
}
task_mutex.lock();
if (post) {
task_available_semaphore.post();
}
}
}
void WorkerThreadPool::_thread_function(void *p_user) {
while (true) {
singleton->task_available_semaphore.wait();
if (singleton->exit_threads.is_set()) {
break;
}
singleton->_process_task_queue();
}
}
void WorkerThreadPool::_native_low_priority_thread_function(void *p_user) {
Task *task = (Task *)p_user;
singleton->_process_task(task);
}
void WorkerThreadPool::_post_task(Task *p_task, bool p_high_priority) {
task_mutex.lock();
p_task->low_priority = !p_high_priority;
if (!p_high_priority && use_native_low_priority_threads) {
task_mutex.unlock();
p_task->low_priority_thread = native_thread_allocator.alloc();
p_task->low_priority_thread->start(_native_low_priority_thread_function, p_task); // Pask task directly to thread.
} else if (p_high_priority || low_priority_threads_used.get() < max_low_priority_threads) {
task_queue.add_last(&p_task->task_elem);
if (!p_high_priority) {
low_priority_threads_used.increment();
}
task_mutex.unlock();
task_available_semaphore.post();
} else {
// Too many threads using low priority, must go to queue.
low_priority_task_queue.add_last(&p_task->task_elem);
task_mutex.unlock();
}
}
WorkerThreadPool::TaskID WorkerThreadPool::add_native_task(void (*p_func)(void *), void *p_userdata, bool p_high_priority, const String &p_description) {
Remove ThreadWorkPool, replace by WorkerThreadPool The former needs to be allocated once per usage. The later is shared for all threads, which is more efficient. It can also be better debugged.
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return _add_task(Callable(), p_func, p_userdata, nullptr, p_high_priority, p_description);
}
WorkerThreadPool::TaskID WorkerThreadPool::_add_task(const Callable &p_callable, void (*p_func)(void *), void *p_userdata, BaseTemplateUserdata *p_template_userdata, bool p_high_priority, const String &p_description) {
Implement a Worker ThreadPool This PR implements a worked thread pool. It uses a fixed amount of threads in a pool and allows scheduling tasks that can be run on threads (and then waited for). It satisfies the following use cases: * HTML5 thread count is fixed (and similar restrictions are known in consoles) so we need to reuse threads. * Thread spawning is slow in general, so reusing threads is faster anyway. * This implementation supports recursive waiting for tasks, making it less prone to deadlocks if threads from the pool also run tasks. After this is approved and merged, subsequent PRs will be needed to replace the ThreadWorkPool usage by this class.
2022-07-18 10:09:19 +00:00
task_mutex.lock();
// Get a free task
Task *task = task_allocator.alloc();
TaskID id = last_task++;
Remove ThreadWorkPool, replace by WorkerThreadPool The former needs to be allocated once per usage. The later is shared for all threads, which is more efficient. It can also be better debugged.
2022-07-23 17:12:41 +00:00
task->callable = p_callable;
Implement a Worker ThreadPool This PR implements a worked thread pool. It uses a fixed amount of threads in a pool and allows scheduling tasks that can be run on threads (and then waited for). It satisfies the following use cases: * HTML5 thread count is fixed (and similar restrictions are known in consoles) so we need to reuse threads. * Thread spawning is slow in general, so reusing threads is faster anyway. * This implementation supports recursive waiting for tasks, making it less prone to deadlocks if threads from the pool also run tasks. After this is approved and merged, subsequent PRs will be needed to replace the ThreadWorkPool usage by this class.
2022-07-18 10:09:19 +00:00
task->native_func = p_func;
task->native_func_userdata = p_userdata;
task->description = p_description;
Remove ThreadWorkPool, replace by WorkerThreadPool The former needs to be allocated once per usage. The later is shared for all threads, which is more efficient. It can also be better debugged.
2022-07-23 17:12:41 +00:00
task->template_userdata = p_template_userdata;
Implement a Worker ThreadPool This PR implements a worked thread pool. It uses a fixed amount of threads in a pool and allows scheduling tasks that can be run on threads (and then waited for). It satisfies the following use cases: * HTML5 thread count is fixed (and similar restrictions are known in consoles) so we need to reuse threads. * Thread spawning is slow in general, so reusing threads is faster anyway. * This implementation supports recursive waiting for tasks, making it less prone to deadlocks if threads from the pool also run tasks. After this is approved and merged, subsequent PRs will be needed to replace the ThreadWorkPool usage by this class.
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tasks.insert(id, task);
task_mutex.unlock();
_post_task(task, p_high_priority);
return id;
}
WorkerThreadPool::TaskID WorkerThreadPool::add_task(const Callable &p_action, bool p_high_priority, const String &p_description) {
Remove ThreadWorkPool, replace by WorkerThreadPool The former needs to be allocated once per usage. The later is shared for all threads, which is more efficient. It can also be better debugged.
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return _add_task(p_action, nullptr, nullptr, nullptr, p_high_priority, p_description);
Implement a Worker ThreadPool This PR implements a worked thread pool. It uses a fixed amount of threads in a pool and allows scheduling tasks that can be run on threads (and then waited for). It satisfies the following use cases: * HTML5 thread count is fixed (and similar restrictions are known in consoles) so we need to reuse threads. * Thread spawning is slow in general, so reusing threads is faster anyway. * This implementation supports recursive waiting for tasks, making it less prone to deadlocks if threads from the pool also run tasks. After this is approved and merged, subsequent PRs will be needed to replace the ThreadWorkPool usage by this class.
2022-07-18 10:09:19 +00:00
}
bool WorkerThreadPool::is_task_completed(TaskID p_task_id) const {
task_mutex.lock();
const Task *const *taskp = tasks.getptr(p_task_id);
if (!taskp) {
task_mutex.unlock();
ERR_FAIL_V_MSG(false, "Invalid Task ID"); // Invalid task
}
bool completed = (*taskp)->completed;
task_mutex.unlock();
return completed;
}
void WorkerThreadPool::wait_for_task_completion(TaskID p_task_id) {
task_mutex.lock();
Task **taskp = tasks.getptr(p_task_id);
if (!taskp) {
task_mutex.unlock();
ERR_FAIL_MSG("Invalid Task ID"); // Invalid task
}
Task *task = *taskp;
if (task->waiting) {
String description = task->description;
task_mutex.unlock();
if (description.is_empty()) {
ERR_FAIL_MSG("Another thread is waiting on this task: " + itos(p_task_id)); // Invalid task
} else {
ERR_FAIL_MSG("Another thread is waiting on this task: " + description + " (" + itos(p_task_id) + ")"); // Invalid task
}
}
task->waiting = true;
task_mutex.unlock();
if (use_native_low_priority_threads && task->low_priority) {
task->low_priority_thread->wait_to_finish();
native_thread_allocator.free(task->low_priority_thread);
} else {
int *index = thread_ids.getptr(Thread::get_caller_id());
if (index) {
// We are an actual process thread, we must not be blocked so continue processing stuff if available.
while (true) {
if (task->done_semaphore.try_wait()) {
// If done, exit
break;
}
if (task_available_semaphore.try_wait()) {
// Solve tasks while they are around.
_process_task_queue();
continue;
}
OS::get_singleton()->delay_usec(1); // Microsleep, this could be converted to waiting for multiple objects in supported platforms for a bit more performance.
}
} else {
task->done_semaphore.wait();
}
}
task_mutex.lock();
tasks.erase(p_task_id);
task_allocator.free(task);
task_mutex.unlock();
}
Remove ThreadWorkPool, replace by WorkerThreadPool The former needs to be allocated once per usage. The later is shared for all threads, which is more efficient. It can also be better debugged.
2022-07-23 17:12:41 +00:00
WorkerThreadPool::GroupID WorkerThreadPool::_add_group_task(const Callable &p_callable, void (*p_func)(void *, uint32_t), void *p_userdata, BaseTemplateUserdata *p_template_userdata, int p_elements, int p_tasks, bool p_high_priority, const String &p_description) {
ERR_FAIL_COND_V(p_elements < 0, INVALID_TASK_ID);
Implement a Worker ThreadPool This PR implements a worked thread pool. It uses a fixed amount of threads in a pool and allows scheduling tasks that can be run on threads (and then waited for). It satisfies the following use cases: * HTML5 thread count is fixed (and similar restrictions are known in consoles) so we need to reuse threads. * Thread spawning is slow in general, so reusing threads is faster anyway. * This implementation supports recursive waiting for tasks, making it less prone to deadlocks if threads from the pool also run tasks. After this is approved and merged, subsequent PRs will be needed to replace the ThreadWorkPool usage by this class.
2022-07-18 10:09:19 +00:00
if (p_tasks < 0) {
p_tasks = threads.size();
}
task_mutex.lock();
Group *group = group_allocator.alloc();
GroupID id = last_task++;
group->max = p_elements;
group->self = id;
Remove ThreadWorkPool, replace by WorkerThreadPool The former needs to be allocated once per usage. The later is shared for all threads, which is more efficient. It can also be better debugged.
2022-07-23 17:12:41 +00:00
Task **tasks_posted = nullptr;
if (p_elements == 0) {
// Should really not call it with zero Elements, but at least it should work.
group->completed.set_to(true);
group->done_semaphore.post();
group->tasks_used = 0;
p_tasks = 0;
if (p_template_userdata) {
memdelete(p_template_userdata);
}
} else {
group->tasks_used = p_tasks;
tasks_posted = (Task **)alloca(sizeof(Task *) * p_tasks);
for (int i = 0; i < p_tasks; i++) {
Task *task = task_allocator.alloc();
task->native_group_func = p_func;
task->native_func_userdata = p_userdata;
task->description = p_description;
task->group = group;
task->callable = p_callable;
task->template_userdata = p_template_userdata;
tasks_posted[i] = task;
// No task ID is used.
}
Implement a Worker ThreadPool This PR implements a worked thread pool. It uses a fixed amount of threads in a pool and allows scheduling tasks that can be run on threads (and then waited for). It satisfies the following use cases: * HTML5 thread count is fixed (and similar restrictions are known in consoles) so we need to reuse threads. * Thread spawning is slow in general, so reusing threads is faster anyway. * This implementation supports recursive waiting for tasks, making it less prone to deadlocks if threads from the pool also run tasks. After this is approved and merged, subsequent PRs will be needed to replace the ThreadWorkPool usage by this class.
2022-07-18 10:09:19 +00:00
}
Remove ThreadWorkPool, replace by WorkerThreadPool The former needs to be allocated once per usage. The later is shared for all threads, which is more efficient. It can also be better debugged.
2022-07-23 17:12:41 +00:00
Implement a Worker ThreadPool This PR implements a worked thread pool. It uses a fixed amount of threads in a pool and allows scheduling tasks that can be run on threads (and then waited for). It satisfies the following use cases: * HTML5 thread count is fixed (and similar restrictions are known in consoles) so we need to reuse threads. * Thread spawning is slow in general, so reusing threads is faster anyway. * This implementation supports recursive waiting for tasks, making it less prone to deadlocks if threads from the pool also run tasks. After this is approved and merged, subsequent PRs will be needed to replace the ThreadWorkPool usage by this class.
2022-07-18 10:09:19 +00:00
groups[id] = group;
task_mutex.unlock();
if (!p_high_priority && use_native_low_priority_threads) {
group->low_priority_native_tasks.resize(p_tasks);
}
for (int i = 0; i < p_tasks; i++) {
_post_task(tasks_posted[i], p_high_priority);
if (!p_high_priority && use_native_low_priority_threads) {
group->low_priority_native_tasks[i] = tasks_posted[i];
}
}
return id;
}
Remove ThreadWorkPool, replace by WorkerThreadPool The former needs to be allocated once per usage. The later is shared for all threads, which is more efficient. It can also be better debugged.
2022-07-23 17:12:41 +00:00
WorkerThreadPool::GroupID WorkerThreadPool::add_native_group_task(void (*p_func)(void *, uint32_t), void *p_userdata, int p_elements, int p_tasks, bool p_high_priority, const String &p_description) {
return _add_group_task(Callable(), p_func, p_userdata, nullptr, p_elements, p_tasks, p_high_priority, p_description);
}
Implement a Worker ThreadPool This PR implements a worked thread pool. It uses a fixed amount of threads in a pool and allows scheduling tasks that can be run on threads (and then waited for). It satisfies the following use cases: * HTML5 thread count is fixed (and similar restrictions are known in consoles) so we need to reuse threads. * Thread spawning is slow in general, so reusing threads is faster anyway. * This implementation supports recursive waiting for tasks, making it less prone to deadlocks if threads from the pool also run tasks. After this is approved and merged, subsequent PRs will be needed to replace the ThreadWorkPool usage by this class.
2022-07-18 10:09:19 +00:00
WorkerThreadPool::GroupID WorkerThreadPool::add_group_task(const Callable &p_action, int p_elements, int p_tasks, bool p_high_priority, const String &p_description) {
Remove ThreadWorkPool, replace by WorkerThreadPool The former needs to be allocated once per usage. The later is shared for all threads, which is more efficient. It can also be better debugged.
2022-07-23 17:12:41 +00:00
return _add_group_task(p_action, nullptr, nullptr, nullptr, p_elements, p_tasks, p_high_priority, p_description);
}
Implement a Worker ThreadPool This PR implements a worked thread pool. It uses a fixed amount of threads in a pool and allows scheduling tasks that can be run on threads (and then waited for). It satisfies the following use cases: * HTML5 thread count is fixed (and similar restrictions are known in consoles) so we need to reuse threads. * Thread spawning is slow in general, so reusing threads is faster anyway. * This implementation supports recursive waiting for tasks, making it less prone to deadlocks if threads from the pool also run tasks. After this is approved and merged, subsequent PRs will be needed to replace the ThreadWorkPool usage by this class.
2022-07-18 10:09:19 +00:00
Remove ThreadWorkPool, replace by WorkerThreadPool The former needs to be allocated once per usage. The later is shared for all threads, which is more efficient. It can also be better debugged.
2022-07-23 17:12:41 +00:00
uint32_t WorkerThreadPool::get_group_processed_element_count(GroupID p_group) const {
Implement a Worker ThreadPool This PR implements a worked thread pool. It uses a fixed amount of threads in a pool and allows scheduling tasks that can be run on threads (and then waited for). It satisfies the following use cases: * HTML5 thread count is fixed (and similar restrictions are known in consoles) so we need to reuse threads. * Thread spawning is slow in general, so reusing threads is faster anyway. * This implementation supports recursive waiting for tasks, making it less prone to deadlocks if threads from the pool also run tasks. After this is approved and merged, subsequent PRs will be needed to replace the ThreadWorkPool usage by this class.
2022-07-18 10:09:19 +00:00
task_mutex.lock();
Remove ThreadWorkPool, replace by WorkerThreadPool The former needs to be allocated once per usage. The later is shared for all threads, which is more efficient. It can also be better debugged.
2022-07-23 17:12:41 +00:00
const Group *const *groupp = groups.getptr(p_group);
if (!groupp) {
task_mutex.unlock();
ERR_FAIL_V_MSG(0, "Invalid Group ID");
Implement a Worker ThreadPool This PR implements a worked thread pool. It uses a fixed amount of threads in a pool and allows scheduling tasks that can be run on threads (and then waited for). It satisfies the following use cases: * HTML5 thread count is fixed (and similar restrictions are known in consoles) so we need to reuse threads. * Thread spawning is slow in general, so reusing threads is faster anyway. * This implementation supports recursive waiting for tasks, making it less prone to deadlocks if threads from the pool also run tasks. After this is approved and merged, subsequent PRs will be needed to replace the ThreadWorkPool usage by this class.
2022-07-18 10:09:19 +00:00
}
Remove ThreadWorkPool, replace by WorkerThreadPool The former needs to be allocated once per usage. The later is shared for all threads, which is more efficient. It can also be better debugged.
2022-07-23 17:12:41 +00:00
uint32_t elements = (*groupp)->completed_index.get();
Implement a Worker ThreadPool This PR implements a worked thread pool. It uses a fixed amount of threads in a pool and allows scheduling tasks that can be run on threads (and then waited for). It satisfies the following use cases: * HTML5 thread count is fixed (and similar restrictions are known in consoles) so we need to reuse threads. * Thread spawning is slow in general, so reusing threads is faster anyway. * This implementation supports recursive waiting for tasks, making it less prone to deadlocks if threads from the pool also run tasks. After this is approved and merged, subsequent PRs will be needed to replace the ThreadWorkPool usage by this class.
2022-07-18 10:09:19 +00:00
task_mutex.unlock();
Remove ThreadWorkPool, replace by WorkerThreadPool The former needs to be allocated once per usage. The later is shared for all threads, which is more efficient. It can also be better debugged.
2022-07-23 17:12:41 +00:00
return elements;
Implement a Worker ThreadPool This PR implements a worked thread pool. It uses a fixed amount of threads in a pool and allows scheduling tasks that can be run on threads (and then waited for). It satisfies the following use cases: * HTML5 thread count is fixed (and similar restrictions are known in consoles) so we need to reuse threads. * Thread spawning is slow in general, so reusing threads is faster anyway. * This implementation supports recursive waiting for tasks, making it less prone to deadlocks if threads from the pool also run tasks. After this is approved and merged, subsequent PRs will be needed to replace the ThreadWorkPool usage by this class.
2022-07-18 10:09:19 +00:00
}
bool WorkerThreadPool::is_group_task_completed(GroupID p_group) const {
task_mutex.lock();
const Group *const *groupp = groups.getptr(p_group);
if (!groupp) {
task_mutex.unlock();
ERR_FAIL_V_MSG(false, "Invalid Group ID");
}
bool completed = (*groupp)->completed.is_set();
task_mutex.unlock();
return completed;
}
void WorkerThreadPool::wait_for_group_task_completion(GroupID p_group) {
task_mutex.lock();
Group **groupp = groups.getptr(p_group);
task_mutex.unlock();
if (!groupp) {
ERR_FAIL_MSG("Invalid Group ID");
}
Group *group = *groupp;
if (group->low_priority_native_tasks.size() > 0) {
for (uint32_t i = 0; i < group->low_priority_native_tasks.size(); i++) {
group->low_priority_native_tasks[i]->low_priority_thread->wait_to_finish();
native_thread_allocator.free(group->low_priority_native_tasks[i]->low_priority_thread);
task_mutex.lock();
task_allocator.free(group->low_priority_native_tasks[i]);
task_mutex.unlock();
}
task_mutex.lock();
group_allocator.free(group);
task_mutex.unlock();
} else {
group->done_semaphore.wait();
uint32_t max_users = group->tasks_used + 1; // Add 1 because the thread waiting for it is also user. Read before to avoid another thread freeing task after increment.
uint32_t finished_users = group->finished.increment(); // fetch happens before inc, so increment later.
if (finished_users == max_users) {
Fix typos with codespell Using codespell 2.3-dev from current git. And fix typo in `methods.py` for `vsproj=yes` option (still won't work though).
2022-09-30 12:23:36 +00:00
// All tasks using this group are gone (finished before the group), so clear the group too.
Implement a Worker ThreadPool This PR implements a worked thread pool. It uses a fixed amount of threads in a pool and allows scheduling tasks that can be run on threads (and then waited for). It satisfies the following use cases: * HTML5 thread count is fixed (and similar restrictions are known in consoles) so we need to reuse threads. * Thread spawning is slow in general, so reusing threads is faster anyway. * This implementation supports recursive waiting for tasks, making it less prone to deadlocks if threads from the pool also run tasks. After this is approved and merged, subsequent PRs will be needed to replace the ThreadWorkPool usage by this class.
2022-07-18 10:09:19 +00:00
task_mutex.lock();
group_allocator.free(group);
task_mutex.unlock();
}
}
Fixes HashMap::erase related race condition in WorkerThreadPool when Physics 2D or 3D is selected to run on a separate thread.
2022-10-20 16:47:20 +00:00
task_mutex.lock(); // This mutex is needed when Physics 2D and/or 3D is selected to run on a separate thread.
groups.erase(p_group);
task_mutex.unlock();
Implement a Worker ThreadPool This PR implements a worked thread pool. It uses a fixed amount of threads in a pool and allows scheduling tasks that can be run on threads (and then waited for). It satisfies the following use cases: * HTML5 thread count is fixed (and similar restrictions are known in consoles) so we need to reuse threads. * Thread spawning is slow in general, so reusing threads is faster anyway. * This implementation supports recursive waiting for tasks, making it less prone to deadlocks if threads from the pool also run tasks. After this is approved and merged, subsequent PRs will be needed to replace the ThreadWorkPool usage by this class.
2022-07-18 10:09:19 +00:00
}
void WorkerThreadPool::init(int p_thread_count, bool p_use_native_threads_low_priority, float p_low_priority_task_ratio) {
ERR_FAIL_COND(threads.size() > 0);
if (p_thread_count < 0) {
p_thread_count = OS::get_singleton()->get_default_thread_pool_size();
}
if (p_use_native_threads_low_priority) {
max_low_priority_threads = 0;
} else {
max_low_priority_threads = CLAMP(p_thread_count * p_low_priority_task_ratio, 1, p_thread_count);
}
use_native_low_priority_threads = p_use_native_threads_low_priority;
threads.resize(p_thread_count);
for (uint32_t i = 0; i < threads.size(); i++) {
threads[i].index = i;
threads[i].thread.start(&WorkerThreadPool::_thread_function, &threads[i]);
thread_ids.insert(threads[i].thread.get_id(), i);
}
}
void WorkerThreadPool::finish() {
if (threads.size() == 0) {
return;
}
task_mutex.lock();
SelfList<Task> *E = low_priority_task_queue.first();
while (E) {
print_error("Task waiting was never re-claimed: " + E->self()->description);
E = E->next();
}
task_mutex.unlock();
exit_threads.set_to(true);
for (uint32_t i = 0; i < threads.size(); i++) {
task_available_semaphore.post();
}
for (uint32_t i = 0; i < threads.size(); i++) {
threads[i].thread.wait_to_finish();
}
threads.clear();
}
void WorkerThreadPool::_bind_methods() {
ClassDB::bind_method(D_METHOD("add_task", "action", "high_priority", "description"), &WorkerThreadPool::add_task, DEFVAL(false), DEFVAL(String()));
ClassDB::bind_method(D_METHOD("is_task_completed", "task_id"), &WorkerThreadPool::is_task_completed);
ClassDB::bind_method(D_METHOD("wait_for_task_completion", "task_id"), &WorkerThreadPool::wait_for_task_completion);
ClassDB::bind_method(D_METHOD("add_group_task", "action", "elements", "tasks_needed", "high_priority", "description"), &WorkerThreadPool::add_group_task, DEFVAL(-1), DEFVAL(false), DEFVAL(String()));
ClassDB::bind_method(D_METHOD("is_group_task_completed", "group_id"), &WorkerThreadPool::is_group_task_completed);
Remove ThreadWorkPool, replace by WorkerThreadPool The former needs to be allocated once per usage. The later is shared for all threads, which is more efficient. It can also be better debugged.
2022-07-23 17:12:41 +00:00
ClassDB::bind_method(D_METHOD("get_group_processed_element_count", "group_id"), &WorkerThreadPool::get_group_processed_element_count);
Implement a Worker ThreadPool This PR implements a worked thread pool. It uses a fixed amount of threads in a pool and allows scheduling tasks that can be run on threads (and then waited for). It satisfies the following use cases: * HTML5 thread count is fixed (and similar restrictions are known in consoles) so we need to reuse threads. * Thread spawning is slow in general, so reusing threads is faster anyway. * This implementation supports recursive waiting for tasks, making it less prone to deadlocks if threads from the pool also run tasks. After this is approved and merged, subsequent PRs will be needed to replace the ThreadWorkPool usage by this class.
2022-07-18 10:09:19 +00:00
ClassDB::bind_method(D_METHOD("wait_for_group_task_completion", "group_id"), &WorkerThreadPool::wait_for_group_task_completion);
}
WorkerThreadPool::WorkerThreadPool() {
singleton = this;
}
WorkerThreadPool::~WorkerThreadPool() {
finish();
}