/* * ***** BEGIN GPL LICENSE BLOCK ***** * * This program is free software; you can redistribute it and/or * modify it under the terms of the GNU General Public License * as published by the Free Software Foundation; either version 2 * of the License, or (at your option) any later version. * * This program is distributed in the hope that it will be useful, * but WITHOUT ANY WARRANTY; without even the implied warranty of * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the * GNU General Public License for more details. * * You should have received a copy of the GNU General Public License * along with this program; if not, write to the Free Software Foundation, * Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301, USA. * * ***** END GPL LICENSE BLOCK ***** */ /** \file blender/blenlib/intern/task.c * \ingroup bli * * A generic task system which can be used for any task based subsystem. */ #include #include "MEM_guardedalloc.h" #include "DNA_listBase.h" #include "BLI_listbase.h" #include "BLI_math.h" #include "BLI_task.h" #include "BLI_threads.h" #include "atomic_ops.h" /* Define this to enable some detailed statistic print. */ #undef DEBUG_STATS /* Types */ /* Number of per-thread pre-allocated tasks. * * For more details see description of TaskMemPool. */ #define MEMPOOL_SIZE 256 /* Number of tasks which are pushed directly to local thread queue. * * This allows thread to fetch next task without locking the whole queue. */ #define LOCALQUEUE_SIZE 1 #ifndef NDEBUG # define ASSERT_THREAD_ID(scheduler, thread_id) \ do { \ if (!BLI_thread_is_main()) { \ TaskThread *thread = pthread_getspecific(scheduler->tls_id_key); \ if (thread == NULL) { \ BLI_assert(thread_id == 0); \ } \ else { \ BLI_assert(thread_id == thread->id); \ } \ } \ else { \ BLI_assert(thread_id == 0); \ } \ } while (false) #else # define ASSERT_THREAD_ID(scheduler, thread_id) #endif typedef struct Task { struct Task *next, *prev; TaskRunFunction run; void *taskdata; bool free_taskdata; TaskFreeFunction freedata; TaskPool *pool; } Task; /* This is a per-thread storage of pre-allocated tasks. * * The idea behind this is simple: reduce amount of malloc() calls when pushing * new task to the pool. This is done by keeping memory from the tasks which * were finished already, so instead of freeing that memory we put it to the * pool for the later re-use. * * The tricky part here is to avoid any inter-thread synchronization, hence no * lock must exist around this pool. The pool will become an owner of the pointer * from freed task, and only corresponding thread will be able to use this pool * (no memory stealing and such). * * This leads to the following use of the pool: * * - task_push() should provide proper thread ID from which the task is being * pushed from. * * - Task allocation function which check corresponding memory pool and if there * is any memory in there it'll mark memory as re-used, remove it from the pool * and use that memory for the new task. * * At this moment task queue owns the memory. * * - When task is done and task_free() is called the memory will be put to the * pool which corresponds to a thread which handled the task. */ typedef struct TaskMemPool { /* Number of pre-allocated tasks in the pool. */ int num_tasks; /* Pre-allocated task memory pointers. */ Task *tasks[MEMPOOL_SIZE]; } TaskMemPool; #ifdef DEBUG_STATS typedef struct TaskMemPoolStats { /* Number of allocations. */ int num_alloc; /* Number of avoided allocations (pointer was re-used from the pool). */ int num_reuse; /* Number of discarded memory due to pool saturation, */ int num_discard; } TaskMemPoolStats; #endif typedef struct TaskThreadLocalStorage { TaskMemPool task_mempool; int num_local_queue; Task *local_queue[LOCALQUEUE_SIZE]; } TaskThreadLocalStorage; struct TaskPool { TaskScheduler *scheduler; volatile size_t num; ThreadMutex num_mutex; ThreadCondition num_cond; void *userdata; ThreadMutex user_mutex; volatile bool do_cancel; volatile bool do_work; volatile bool is_suspended; ListBase suspended_queue; size_t num_suspended; /* If set, this pool may never be work_and_wait'ed, which means TaskScheduler * has to use its special background fallback thread in case we are in * single-threaded situation. */ bool run_in_background; /* This is a task scheduler's ID of a thread at which pool was constructed. * It will be used to access task TLS. */ int thread_id; /* For the pools which are created from non-main thread which is not a * scheduler worker thread we can't re-use any of scheduler's threads TLS * and have to use our own one. */ bool use_local_tls; TaskThreadLocalStorage local_tls; #ifndef NDEBUG pthread_t creator_thread_id; #endif #ifdef DEBUG_STATS TaskMemPoolStats *mempool_stats; #endif }; struct TaskScheduler { pthread_t *threads; struct TaskThread *task_threads; int num_threads; bool background_thread_only; ListBase queue; ThreadMutex queue_mutex; ThreadCondition queue_cond; volatile bool do_exit; /* NOTE: In pthread's TLS we store the whole TaskThread structure. */ pthread_key_t tls_id_key; }; typedef struct TaskThread { TaskScheduler *scheduler; int id; TaskThreadLocalStorage tls; } TaskThread; /* Helper */ BLI_INLINE void task_data_free(Task *task, const int thread_id) { if (task->free_taskdata) { if (task->freedata) { task->freedata(task->pool, task->taskdata, thread_id); } else { MEM_freeN(task->taskdata); } } } BLI_INLINE void initialize_task_tls(TaskThreadLocalStorage *tls) { memset(tls, 0, sizeof(TaskThreadLocalStorage)); } BLI_INLINE TaskThreadLocalStorage *get_task_tls(TaskPool *pool, const int thread_id) { TaskScheduler *scheduler = pool->scheduler; BLI_assert(thread_id >= 0); BLI_assert(thread_id <= scheduler->num_threads); if (pool->use_local_tls && thread_id == 0) { BLI_assert(pool->thread_id == 0); BLI_assert(!BLI_thread_is_main()); BLI_assert(pthread_equal(pthread_self(), pool->creator_thread_id)); return &pool->local_tls; } if (thread_id == 0) { BLI_assert(BLI_thread_is_main()); return &scheduler->task_threads[pool->thread_id].tls; } return &scheduler->task_threads[thread_id].tls; } BLI_INLINE void free_task_tls(TaskThreadLocalStorage *tls) { TaskMemPool *task_mempool = &tls->task_mempool; for (int i = 0; i < task_mempool->num_tasks; ++i) { MEM_freeN(task_mempool->tasks[i]); } } static Task *task_alloc(TaskPool *pool, const int thread_id) { BLI_assert(thread_id <= pool->scheduler->num_threads); if (thread_id != -1) { BLI_assert(thread_id >= 0); BLI_assert(thread_id <= pool->scheduler->num_threads); TaskThreadLocalStorage *tls = get_task_tls(pool, thread_id); TaskMemPool *task_mempool = &tls->task_mempool; /* Try to re-use task memory from a thread local storage. */ if (task_mempool->num_tasks > 0) { --task_mempool->num_tasks; /* Success! We've just avoided task allocation. */ #ifdef DEBUG_STATS pool->mempool_stats[thread_id].num_reuse++; #endif return task_mempool->tasks[task_mempool->num_tasks]; } /* We are doomed to allocate new task data. */ #ifdef DEBUG_STATS pool->mempool_stats[thread_id].num_alloc++; #endif } return MEM_mallocN(sizeof(Task), "New task"); } static void task_free(TaskPool *pool, Task *task, const int thread_id) { task_data_free(task, thread_id); BLI_assert(thread_id >= 0); BLI_assert(thread_id <= pool->scheduler->num_threads); if (thread_id == 0) { BLI_assert(pool->use_local_tls || BLI_thread_is_main()); } TaskThreadLocalStorage *tls = get_task_tls(pool, thread_id); TaskMemPool *task_mempool = &tls->task_mempool; if (task_mempool->num_tasks < MEMPOOL_SIZE - 1) { /* Successfully allowed the task to be re-used later. */ task_mempool->tasks[task_mempool->num_tasks] = task; ++task_mempool->num_tasks; } else { /* Local storage saturated, no other way than just discard * the memory. * * TODO(sergey): We can perhaps store such pointer in a global * scheduler pool, maybe it'll be faster than discarding and * allocating again. */ MEM_freeN(task); #ifdef DEBUG_STATS pool->mempool_stats[thread_id].num_discard++; #endif } } /* Task Scheduler */ static void task_pool_num_decrease(TaskPool *pool, size_t done) { BLI_mutex_lock(&pool->num_mutex); BLI_assert(pool->num >= done); pool->num -= done; if (pool->num == 0) BLI_condition_notify_all(&pool->num_cond); BLI_mutex_unlock(&pool->num_mutex); } static void task_pool_num_increase(TaskPool *pool, size_t new) { BLI_mutex_lock(&pool->num_mutex); pool->num += new; BLI_condition_notify_all(&pool->num_cond); BLI_mutex_unlock(&pool->num_mutex); } static bool task_scheduler_thread_wait_pop(TaskScheduler *scheduler, Task **task) { bool found_task = false; BLI_mutex_lock(&scheduler->queue_mutex); while (!scheduler->queue.first && !scheduler->do_exit) BLI_condition_wait(&scheduler->queue_cond, &scheduler->queue_mutex); do { Task *current_task; /* Assuming we can only have a void queue in 'exit' case here seems logical (we should only be here after * our worker thread has been woken up from a condition_wait(), which only happens after a new task was * added to the queue), but it is wrong. * Waiting on condition may wake up the thread even if condition is not signaled (spurious wake-ups), and some * race condition may also empty the queue **after** condition has been signaled, but **before** awoken thread * reaches this point... * See http://stackoverflow.com/questions/8594591 * * So we only abort here if do_exit is set. */ if (scheduler->do_exit) { BLI_mutex_unlock(&scheduler->queue_mutex); return false; } for (current_task = scheduler->queue.first; current_task != NULL; current_task = current_task->next) { TaskPool *pool = current_task->pool; if (scheduler->background_thread_only && !pool->run_in_background) { continue; } *task = current_task; found_task = true; BLI_remlink(&scheduler->queue, *task); break; } if (!found_task) BLI_condition_wait(&scheduler->queue_cond, &scheduler->queue_mutex); } while (!found_task); BLI_mutex_unlock(&scheduler->queue_mutex); return true; } BLI_INLINE void handle_local_queue(TaskThreadLocalStorage *tls, const int thread_id) { while (tls->num_local_queue > 0) { /* We pop task from queue before handling it so handler of the task can * push next job to the local queue. */ tls->num_local_queue--; Task *local_task = tls->local_queue[tls->num_local_queue]; /* TODO(sergey): Double-check work_and_wait() doesn't handle other's * pool tasks. */ TaskPool *local_pool = local_task->pool; local_task->run(local_pool, local_task->taskdata, thread_id); task_free(local_pool, local_task, thread_id); } } static void *task_scheduler_thread_run(void *thread_p) { TaskThread *thread = (TaskThread *) thread_p; TaskThreadLocalStorage *tls = &thread->tls; TaskScheduler *scheduler = thread->scheduler; int thread_id = thread->id; Task *task; pthread_setspecific(scheduler->tls_id_key, thread); /* keep popping off tasks */ while (task_scheduler_thread_wait_pop(scheduler, &task)) { TaskPool *pool = task->pool; /* run task */ task->run(pool, task->taskdata, thread_id); /* delete task */ task_free(pool, task, thread_id); /* Handle all tasks from local queue. */ handle_local_queue(tls, thread_id); /* notify pool task was done */ task_pool_num_decrease(pool, 1); } return NULL; } TaskScheduler *BLI_task_scheduler_create(int num_threads) { TaskScheduler *scheduler = MEM_callocN(sizeof(TaskScheduler), "TaskScheduler"); /* multiple places can use this task scheduler, sharing the same * threads, so we keep track of the number of users. */ scheduler->do_exit = false; BLI_listbase_clear(&scheduler->queue); BLI_mutex_init(&scheduler->queue_mutex); BLI_condition_init(&scheduler->queue_cond); if (num_threads == 0) { /* automatic number of threads will be main thread + num cores */ num_threads = BLI_system_thread_count(); } /* main thread will also work, so we count it too */ num_threads -= 1; /* Add background-only thread if needed. */ if (num_threads == 0) { scheduler->background_thread_only = true; num_threads = 1; } scheduler->task_threads = MEM_mallocN(sizeof(TaskThread) * (num_threads + 1), "TaskScheduler task threads"); /* Initialize TLS for main thread. */ initialize_task_tls(&scheduler->task_threads[0].tls); pthread_key_create(&scheduler->tls_id_key, NULL); /* launch threads that will be waiting for work */ if (num_threads > 0) { int i; scheduler->num_threads = num_threads; scheduler->threads = MEM_callocN(sizeof(pthread_t) * num_threads, "TaskScheduler threads"); for (i = 0; i < num_threads; i++) { TaskThread *thread = &scheduler->task_threads[i + 1]; thread->scheduler = scheduler; thread->id = i + 1; initialize_task_tls(&thread->tls); if (pthread_create(&scheduler->threads[i], NULL, task_scheduler_thread_run, thread) != 0) { fprintf(stderr, "TaskScheduler failed to launch thread %d/%d\n", i, num_threads); } } } return scheduler; } void BLI_task_scheduler_free(TaskScheduler *scheduler) { Task *task; /* stop all waiting threads */ BLI_mutex_lock(&scheduler->queue_mutex); scheduler->do_exit = true; BLI_condition_notify_all(&scheduler->queue_cond); BLI_mutex_unlock(&scheduler->queue_mutex); pthread_key_delete(scheduler->tls_id_key); /* delete threads */ if (scheduler->threads) { int i; for (i = 0; i < scheduler->num_threads; i++) { if (pthread_join(scheduler->threads[i], NULL) != 0) fprintf(stderr, "TaskScheduler failed to join thread %d/%d\n", i, scheduler->num_threads); } MEM_freeN(scheduler->threads); } /* Delete task thread data */ if (scheduler->task_threads) { for (int i = 0; i < scheduler->num_threads + 1; ++i) { TaskThreadLocalStorage *tls = &scheduler->task_threads[i].tls; free_task_tls(tls); } MEM_freeN(scheduler->task_threads); } /* delete leftover tasks */ for (task = scheduler->queue.first; task; task = task->next) { task_data_free(task, 0); } BLI_freelistN(&scheduler->queue); /* delete mutex/condition */ BLI_mutex_end(&scheduler->queue_mutex); BLI_condition_end(&scheduler->queue_cond); MEM_freeN(scheduler); } int BLI_task_scheduler_num_threads(TaskScheduler *scheduler) { return scheduler->num_threads + 1; } static void task_scheduler_push(TaskScheduler *scheduler, Task *task, TaskPriority priority) { task_pool_num_increase(task->pool, 1); /* add task to queue */ BLI_mutex_lock(&scheduler->queue_mutex); if (priority == TASK_PRIORITY_HIGH) BLI_addhead(&scheduler->queue, task); else BLI_addtail(&scheduler->queue, task); BLI_condition_notify_one(&scheduler->queue_cond); BLI_mutex_unlock(&scheduler->queue_mutex); } static void task_scheduler_clear(TaskScheduler *scheduler, TaskPool *pool) { Task *task, *nexttask; size_t done = 0; BLI_mutex_lock(&scheduler->queue_mutex); /* free all tasks from this pool from the queue */ for (task = scheduler->queue.first; task; task = nexttask) { nexttask = task->next; if (task->pool == pool) { task_data_free(task, pool->thread_id); BLI_freelinkN(&scheduler->queue, task); done++; } } BLI_mutex_unlock(&scheduler->queue_mutex); /* notify done */ task_pool_num_decrease(pool, done); } /* Task Pool */ static TaskPool *task_pool_create_ex(TaskScheduler *scheduler, void *userdata, const bool is_background, const bool is_suspended) { TaskPool *pool = MEM_mallocN(sizeof(TaskPool), "TaskPool"); #ifndef NDEBUG /* Assert we do not try to create a background pool from some parent task - those only work OK from main thread. */ if (is_background) { const pthread_t thread_id = pthread_self(); int i = scheduler->num_threads; while (i--) { BLI_assert(!pthread_equal(scheduler->threads[i], thread_id)); } } #endif pool->scheduler = scheduler; pool->num = 0; pool->do_cancel = false; pool->do_work = false; pool->is_suspended = is_suspended; pool->num_suspended = 0; pool->suspended_queue.first = pool->suspended_queue.last = NULL; pool->run_in_background = is_background; pool->use_local_tls = false; BLI_mutex_init(&pool->num_mutex); BLI_condition_init(&pool->num_cond); pool->userdata = userdata; BLI_mutex_init(&pool->user_mutex); if (BLI_thread_is_main()) { pool->thread_id = 0; } else { TaskThread *thread = pthread_getspecific(scheduler->tls_id_key); if (thread == NULL) { /* NOTE: Task pool is created from non-main thread which is not * managed by the task scheduler. We identify ourselves as thread ID * 0 but we do not use scheduler's TLS storage and use our own * instead to avoid any possible threading conflicts. */ pool->thread_id = 0; pool->use_local_tls = true; #ifndef NDEBUG pool->creator_thread_id = pthread_self(); #endif initialize_task_tls(&pool->local_tls); } else { pool->thread_id = thread->id; } } #ifdef DEBUG_STATS pool->mempool_stats = MEM_callocN(sizeof(*pool->mempool_stats) * (scheduler->num_threads + 1), "per-taskpool mempool stats"); #endif /* Ensure malloc will go fine from threads, * * This is needed because we could be in main thread here * and malloc could be non-threda safe at this point because * no other jobs are running. */ BLI_begin_threaded_malloc(); return pool; } /** * Create a normal task pool. * This means that in single-threaded context, it will not be executed at all until you call * \a BLI_task_pool_work_and_wait() on it. */ TaskPool *BLI_task_pool_create(TaskScheduler *scheduler, void *userdata) { return task_pool_create_ex(scheduler, userdata, false, false); } /** * Create a background task pool. * In multi-threaded context, there is no differences with \a BLI_task_pool_create(), but in single-threaded case * it is ensured to have at least one worker thread to run on (i.e. you do not have to call * \a BLI_task_pool_work_and_wait() on it to be sure it will be processed). * * \note Background pools are non-recursive (that is, you should not create other background pools in tasks assigned * to a background pool, they could end never being executed, since the 'fallback' background thread is already * busy with parent task in single-threaded context). */ TaskPool *BLI_task_pool_create_background(TaskScheduler *scheduler, void *userdata) { return task_pool_create_ex(scheduler, userdata, true, false); } /** * Similar to BLI_task_pool_create() but does not schedule any tasks for execution * for until BLI_task_pool_work_and_wait() is called. This helps reducing therading * overhead when pushing huge amount of small initial tasks from the main thread. */ TaskPool *BLI_task_pool_create_suspended(TaskScheduler *scheduler, void *userdata) { return task_pool_create_ex(scheduler, userdata, false, true); } void BLI_task_pool_free(TaskPool *pool) { BLI_task_pool_cancel(pool); BLI_mutex_end(&pool->num_mutex); BLI_condition_end(&pool->num_cond); BLI_mutex_end(&pool->user_mutex); #ifdef DEBUG_STATS printf("Thread ID Allocated Reused Discarded\n"); for (int i = 0; i < pool->scheduler->num_threads + 1; ++i) { printf("%02d %05d %05d %05d\n", i, pool->mempool_stats[i].num_alloc, pool->mempool_stats[i].num_reuse, pool->mempool_stats[i].num_discard); } MEM_freeN(pool->mempool_stats); #endif if (pool->use_local_tls) { free_task_tls(&pool->local_tls); } MEM_freeN(pool); BLI_end_threaded_malloc(); } static void task_pool_push( TaskPool *pool, TaskRunFunction run, void *taskdata, bool free_taskdata, TaskFreeFunction freedata, TaskPriority priority, int thread_id) { Task *task = task_alloc(pool, thread_id); task->run = run; task->taskdata = taskdata; task->free_taskdata = free_taskdata; task->freedata = freedata; task->pool = pool; if (pool->is_suspended) { BLI_addhead(&pool->suspended_queue, task); atomic_fetch_and_add_z(&pool->num_suspended, 1); return; } if (thread_id != -1 && (thread_id != pool->thread_id || pool->do_work)) { ASSERT_THREAD_ID(pool->scheduler, thread_id); TaskThreadLocalStorage *tls = get_task_tls(pool, thread_id); if (tls->num_local_queue < LOCALQUEUE_SIZE) { tls->local_queue[tls->num_local_queue] = task; tls->num_local_queue++; return; } } task_scheduler_push(pool->scheduler, task, priority); } void BLI_task_pool_push_ex( TaskPool *pool, TaskRunFunction run, void *taskdata, bool free_taskdata, TaskFreeFunction freedata, TaskPriority priority) { task_pool_push(pool, run, taskdata, free_taskdata, freedata, priority, -1); } void BLI_task_pool_push( TaskPool *pool, TaskRunFunction run, void *taskdata, bool free_taskdata, TaskPriority priority) { BLI_task_pool_push_ex(pool, run, taskdata, free_taskdata, NULL, priority); } void BLI_task_pool_push_from_thread(TaskPool *pool, TaskRunFunction run, void *taskdata, bool free_taskdata, TaskPriority priority, int thread_id) { task_pool_push(pool, run, taskdata, free_taskdata, NULL, priority, thread_id); } void BLI_task_pool_work_and_wait(TaskPool *pool) { TaskThreadLocalStorage *tls = get_task_tls(pool, pool->thread_id); TaskScheduler *scheduler = pool->scheduler; if (atomic_fetch_and_and_uint8((uint8_t *)&pool->is_suspended, 0)) { if (pool->num_suspended) { task_pool_num_increase(pool, pool->num_suspended); BLI_mutex_lock(&scheduler->queue_mutex); BLI_movelisttolist(&scheduler->queue, &pool->suspended_queue); BLI_condition_notify_all(&scheduler->queue_cond); BLI_mutex_unlock(&scheduler->queue_mutex); } } pool->do_work = true; ASSERT_THREAD_ID(pool->scheduler, pool->thread_id); BLI_mutex_lock(&pool->num_mutex); while (pool->num != 0) { Task *task, *work_task = NULL; bool found_task = false; BLI_mutex_unlock(&pool->num_mutex); BLI_mutex_lock(&scheduler->queue_mutex); /* find task from this pool. if we get a task from another pool, * we can get into deadlock */ for (task = scheduler->queue.first; task; task = task->next) { if (task->pool == pool) { work_task = task; found_task = true; BLI_remlink(&scheduler->queue, task); break; } } BLI_mutex_unlock(&scheduler->queue_mutex); /* if found task, do it, otherwise wait until other tasks are done */ if (found_task) { /* run task */ work_task->run(pool, work_task->taskdata, pool->thread_id); /* delete task */ task_free(pool, task, pool->thread_id); /* Handle all tasks from local queue. */ handle_local_queue(tls, pool->thread_id); /* notify pool task was done */ task_pool_num_decrease(pool, 1); } BLI_mutex_lock(&pool->num_mutex); if (pool->num == 0) break; if (!found_task) BLI_condition_wait(&pool->num_cond, &pool->num_mutex); } BLI_mutex_unlock(&pool->num_mutex); handle_local_queue(tls, pool->thread_id); } void BLI_task_pool_cancel(TaskPool *pool) { pool->do_cancel = true; task_scheduler_clear(pool->scheduler, pool); /* wait until all entries are cleared */ BLI_mutex_lock(&pool->num_mutex); while (pool->num) BLI_condition_wait(&pool->num_cond, &pool->num_mutex); BLI_mutex_unlock(&pool->num_mutex); pool->do_cancel = false; } bool BLI_task_pool_canceled(TaskPool *pool) { return pool->do_cancel; } void *BLI_task_pool_userdata(TaskPool *pool) { return pool->userdata; } ThreadMutex *BLI_task_pool_user_mutex(TaskPool *pool) { return &pool->user_mutex; } /* Parallel range routines */ /** * * Main functions: * - #BLI_task_parallel_range * - #BLI_task_parallel_listbase (#ListBase - double linked list) * * TODO: * - #BLI_task_parallel_foreach_link (#Link - single linked list) * - #BLI_task_parallel_foreach_ghash/gset (#GHash/#GSet - hash & set) * - #BLI_task_parallel_foreach_mempool (#BLI_mempool - iterate over mempools) * */ /* Allows to avoid using malloc for userdata_chunk in tasks, when small enough. */ #define MALLOCA(_size) ((_size) <= 8192) ? alloca((_size)) : MEM_mallocN((_size), __func__) #define MALLOCA_FREE(_mem, _size) if (((_mem) != NULL) && ((_size) > 8192)) MEM_freeN((_mem)) typedef struct ParallelRangeState { int start, stop; void *userdata; TaskParallelRangeFunc func; TaskParallelRangeFuncEx func_ex; int iter; int chunk_size; } ParallelRangeState; BLI_INLINE bool parallel_range_next_iter_get( ParallelRangeState * __restrict state, int * __restrict iter, int * __restrict count) { uint32_t uval = atomic_fetch_and_add_uint32((uint32_t *)(&state->iter), state->chunk_size); int previter = *(int32_t *)&uval; *iter = previter; *count = max_ii(0, min_ii(state->chunk_size, state->stop - previter)); return (previter < state->stop); } static void parallel_range_func( TaskPool * __restrict pool, void *userdata_chunk, int threadid) { ParallelRangeState * __restrict state = BLI_task_pool_userdata(pool); int iter, count; while (parallel_range_next_iter_get(state, &iter, &count)) { int i; if (state->func_ex) { for (i = 0; i < count; ++i) { state->func_ex(state->userdata, userdata_chunk, iter + i, threadid); } } else { for (i = 0; i < count; ++i) { state->func(state->userdata, iter + i); } } } } /** * This function allows to parallelized for loops in a similar way to OpenMP's 'parallel for' statement. * * See public API doc for description of parameters. */ static void task_parallel_range_ex( int start, int stop, void *userdata, void *userdata_chunk, const size_t userdata_chunk_size, TaskParallelRangeFunc func, TaskParallelRangeFuncEx func_ex, TaskParallelRangeFuncFinalize func_finalize, const bool use_threading, const bool use_dynamic_scheduling) { TaskScheduler *task_scheduler; TaskPool *task_pool; ParallelRangeState state; int i, num_threads, num_tasks; void *userdata_chunk_local = NULL; void *userdata_chunk_array = NULL; const bool use_userdata_chunk = (func_ex != NULL) && (userdata_chunk_size != 0) && (userdata_chunk != NULL); if (start == stop) { return; } BLI_assert(start < stop); if (userdata_chunk_size != 0) { BLI_assert(func_ex != NULL && func == NULL); BLI_assert(userdata_chunk != NULL); } /* If it's not enough data to be crunched, don't bother with tasks at all, * do everything from the main thread. */ if (!use_threading) { if (func_ex) { if (use_userdata_chunk) { userdata_chunk_local = MALLOCA(userdata_chunk_size); memcpy(userdata_chunk_local, userdata_chunk, userdata_chunk_size); } for (i = start; i < stop; ++i) { func_ex(userdata, userdata_chunk_local, i, 0); } if (func_finalize) { func_finalize(userdata, userdata_chunk_local); } MALLOCA_FREE(userdata_chunk_local, userdata_chunk_size); } else { for (i = start; i < stop; ++i) { func(userdata, i); } } return; } task_scheduler = BLI_task_scheduler_get(); task_pool = BLI_task_pool_create(task_scheduler, &state); num_threads = BLI_task_scheduler_num_threads(task_scheduler); /* The idea here is to prevent creating task for each of the loop iterations * and instead have tasks which are evenly distributed across CPU cores and * pull next iter to be crunched using the queue. */ num_tasks = num_threads * 2; state.start = start; state.stop = stop; state.userdata = userdata; state.func = func; state.func_ex = func_ex; state.iter = start; if (use_dynamic_scheduling) { state.chunk_size = 32; } else { state.chunk_size = max_ii(1, (stop - start) / (num_tasks)); } num_tasks = min_ii(num_tasks, (stop - start) / state.chunk_size); atomic_fetch_and_add_uint32((uint32_t *)(&state.iter), 0); if (use_userdata_chunk) { userdata_chunk_array = MALLOCA(userdata_chunk_size * num_tasks); } for (i = 0; i < num_tasks; i++) { if (use_userdata_chunk) { userdata_chunk_local = (char *)userdata_chunk_array + (userdata_chunk_size * i); memcpy(userdata_chunk_local, userdata_chunk, userdata_chunk_size); } /* Use this pool's pre-allocated tasks. */ BLI_task_pool_push_from_thread(task_pool, parallel_range_func, userdata_chunk_local, false, TASK_PRIORITY_HIGH, task_pool->thread_id); } BLI_task_pool_work_and_wait(task_pool); BLI_task_pool_free(task_pool); if (use_userdata_chunk) { if (func_finalize) { for (i = 0; i < num_tasks; i++) { userdata_chunk_local = (char *)userdata_chunk_array + (userdata_chunk_size * i); func_finalize(userdata, userdata_chunk_local); } } MALLOCA_FREE(userdata_chunk_array, userdata_chunk_size * num_tasks); } } /** * This function allows to parallelize for loops in a similar way to OpenMP's 'parallel for' statement. * * \param start First index to process. * \param stop Index to stop looping (excluded). * \param userdata Common userdata passed to all instances of \a func. * \param userdata_chunk Optional, each instance of looping chunks will get a copy of this data * (similar to OpenMP's firstprivate). * \param userdata_chunk_size Memory size of \a userdata_chunk. * \param func_ex Callback function (advanced version). * \param use_threading If \a true, actually split-execute loop in threads, else just do a sequential forloop * (allows caller to use any kind of test to switch on parallelization or not). * \param use_dynamic_scheduling If \a true, the whole range is divided in a lot of small chunks (of size 32 currently), * otherwise whole range is split in a few big chunks (num_threads * 2 chunks currently). */ void BLI_task_parallel_range_ex( int start, int stop, void *userdata, void *userdata_chunk, const size_t userdata_chunk_size, TaskParallelRangeFuncEx func_ex, const bool use_threading, const bool use_dynamic_scheduling) { task_parallel_range_ex( start, stop, userdata, userdata_chunk, userdata_chunk_size, NULL, func_ex, NULL, use_threading, use_dynamic_scheduling); } /** * A simpler version of \a BLI_task_parallel_range_ex, which does not use \a use_dynamic_scheduling, * and does not handle 'firstprivate'-like \a userdata_chunk. * * \param start First index to process. * \param stop Index to stop looping (excluded). * \param userdata Common userdata passed to all instances of \a func. * \param func Callback function (simple version). * \param use_threading If \a true, actually split-execute loop in threads, else just do a sequential forloop * (allows caller to use any kind of test to switch on parallelization or not). */ void BLI_task_parallel_range( int start, int stop, void *userdata, TaskParallelRangeFunc func, const bool use_threading) { task_parallel_range_ex(start, stop, userdata, NULL, 0, func, NULL, NULL, use_threading, false); } /** * This function allows to parallelize for loops in a similar way to OpenMP's 'parallel for' statement, * with an additional 'finalize' func called from calling thread once whole range have been processed. * * \param start First index to process. * \param stop Index to stop looping (excluded). * \param userdata Common userdata passed to all instances of \a func. * \param userdata_chunk Optional, each instance of looping chunks will get a copy of this data * (similar to OpenMP's firstprivate). * \param userdata_chunk_size Memory size of \a userdata_chunk. * \param func_ex Callback function (advanced version). * \param func_finalize Callback function, called after all workers have finished, * useful to finalize accumulative tasks. * \param use_threading If \a true, actually split-execute loop in threads, else just do a sequential forloop * (allows caller to use any kind of test to switch on parallelization or not). * \param use_dynamic_scheduling If \a true, the whole range is divided in a lot of small chunks (of size 32 currently), * otherwise whole range is split in a few big chunks (num_threads * 2 chunks currently). */ void BLI_task_parallel_range_finalize( int start, int stop, void *userdata, void *userdata_chunk, const size_t userdata_chunk_size, TaskParallelRangeFuncEx func_ex, TaskParallelRangeFuncFinalize func_finalize, const bool use_threading, const bool use_dynamic_scheduling) { task_parallel_range_ex( start, stop, userdata, userdata_chunk, userdata_chunk_size, NULL, func_ex, func_finalize, use_threading, use_dynamic_scheduling); } #undef MALLOCA #undef MALLOCA_FREE typedef struct ParallelListbaseState { void *userdata; TaskParallelListbaseFunc func; int chunk_size; int index; Link *link; SpinLock lock; } ParallelListState; BLI_INLINE Link *parallel_listbase_next_iter_get( ParallelListState * __restrict state, int * __restrict index, int * __restrict count) { int task_count = 0; BLI_spin_lock(&state->lock); Link *result = state->link; if (LIKELY(result != NULL)) { *index = state->index; while (state->link != NULL && task_count < state->chunk_size) { ++task_count; state->link = state->link->next; } state->index += task_count; } BLI_spin_unlock(&state->lock); *count = task_count; return result; } static void parallel_listbase_func( TaskPool * __restrict pool, void *UNUSED(taskdata), int UNUSED(threadid)) { ParallelListState * __restrict state = BLI_task_pool_userdata(pool); Link *link; int index, count; while ((link = parallel_listbase_next_iter_get(state, &index, &count)) != NULL) { for (int i = 0; i < count; ++i) { state->func(state->userdata, link, index + i); link = link->next; } } } /** * This function allows to parallelize for loops over ListBase items. * * \param listbase The double linked list to loop over. * \param userdata Common userdata passed to all instances of \a func. * \param func Callback function. * \param use_threading If \a true, actually split-execute loop in threads, else just do a sequential forloop * (allows caller to use any kind of test to switch on parallelization or not). * * \note There is no static scheduling here, since it would need another full loop over items to count them... */ void BLI_task_parallel_listbase( struct ListBase *listbase, void *userdata, TaskParallelListbaseFunc func, const bool use_threading) { TaskScheduler *task_scheduler; TaskPool *task_pool; ParallelListState state; int i, num_threads, num_tasks; if (BLI_listbase_is_empty(listbase)) { return; } if (!use_threading) { i = 0; for (Link *link = listbase->first; link != NULL; link = link->next, ++i) { func(userdata, link, i); } return; } task_scheduler = BLI_task_scheduler_get(); task_pool = BLI_task_pool_create(task_scheduler, &state); num_threads = BLI_task_scheduler_num_threads(task_scheduler); /* The idea here is to prevent creating task for each of the loop iterations * and instead have tasks which are evenly distributed across CPU cores and * pull next iter to be crunched using the queue. */ num_tasks = num_threads * 2; state.index = 0; state.link = listbase->first; state.userdata = userdata; state.func = func; state.chunk_size = 32; BLI_spin_init(&state.lock); for (i = 0; i < num_tasks; i++) { /* Use this pool's pre-allocated tasks. */ BLI_task_pool_push_from_thread(task_pool, parallel_listbase_func, NULL, false, TASK_PRIORITY_HIGH, task_pool->thread_id); } BLI_task_pool_work_and_wait(task_pool); BLI_task_pool_free(task_pool); BLI_spin_end(&state.lock); }