The idea is to accumulate all new tasks in a thread local queue
first without doing any thread synchronization (aka, locks and
conditional variables) and move those tasks to a scheduler queue
once they are all ready. This way we avoid per-task-pool lock
and only have one lock per bunch of tasks.
This is particularly handy when scheduling new dependency graph
node children. Brings FPS of cached simulation from the linked
below file from ~30 to ~50.
See documentation for BLI_task_pool_delayed_push_{begin, end}
and for TaskThreadLocalStorage::do_delayed_push.
Fixes T50027: Rigidbody playback and simulation performance regression with new depsgraph
Thanks Bastien for the review!
1358 lines
40 KiB
C
1358 lines
40 KiB
C
/*
|
|
* ***** BEGIN GPL LICENSE BLOCK *****
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*
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* This program is free software; you can redistribute it and/or
|
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* modify it under the terms of the GNU General Public License
|
|
* as published by the Free Software Foundation; either version 2
|
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* of the License, or (at your option) any later version.
|
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*
|
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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
|
|
* 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.
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*
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* ***** END GPL LICENSE BLOCK *****
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*/
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|
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/** \file blender/blenlib/intern/task.c
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* \ingroup bli
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*
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* A generic task system which can be used for any task based subsystem.
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*/
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#include <stdlib.h>
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#include "MEM_guardedalloc.h"
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#include "DNA_listBase.h"
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#include "BLI_listbase.h"
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#include "BLI_math.h"
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#include "BLI_task.h"
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#include "BLI_threads.h"
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|
|
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#include "atomic_ops.h"
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|
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/* Define this to enable some detailed statistic print. */
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#undef DEBUG_STATS
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|
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/* Types */
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|
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/* Number of per-thread pre-allocated tasks.
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*
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* For more details see description of TaskMemPool.
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*/
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#define MEMPOOL_SIZE 256
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|
|
|
/* Number of tasks which are pushed directly to local thread queue.
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*
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* This allows thread to fetch next task without locking the whole queue.
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*/
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#define LOCAL_QUEUE_SIZE 1
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|
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/* Number of tasks which are allowed to be scheduled in a delayed manner.
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*
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* This allows to use less locks per graph node children schedule. More details
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* could be found at TaskThreadLocalStorage::do_delayed_push.
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*/
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#define DELAYED_QUEUE_SIZE 4096
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|
|
#ifndef NDEBUG
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# define ASSERT_THREAD_ID(scheduler, thread_id) \
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do { \
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if (!BLI_thread_is_main()) { \
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TaskThread *thread = pthread_getspecific(scheduler->tls_id_key); \
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if (thread == NULL) { \
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BLI_assert(thread_id == 0); \
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} \
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else { \
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BLI_assert(thread_id == thread->id); \
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} \
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} \
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else { \
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BLI_assert(thread_id == 0); \
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} \
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} while (false)
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#else
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# define ASSERT_THREAD_ID(scheduler, thread_id)
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#endif
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typedef struct Task {
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struct Task *next, *prev;
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TaskRunFunction run;
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void *taskdata;
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bool free_taskdata;
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TaskFreeFunction freedata;
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TaskPool *pool;
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} Task;
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|
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/* This is a per-thread storage of pre-allocated tasks.
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*
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* The idea behind this is simple: reduce amount of malloc() calls when pushing
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* new task to the pool. This is done by keeping memory from the tasks which
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* were finished already, so instead of freeing that memory we put it to the
|
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* pool for the later re-use.
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*
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* The tricky part here is to avoid any inter-thread synchronization, hence no
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* lock must exist around this pool. The pool will become an owner of the pointer
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* from freed task, and only corresponding thread will be able to use this pool
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* (no memory stealing and such).
|
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*
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* This leads to the following use of the pool:
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*
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* - task_push() should provide proper thread ID from which the task is being
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* pushed from.
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*
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* - Task allocation function which check corresponding memory pool and if there
|
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* is any memory in there it'll mark memory as re-used, remove it from the pool
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* and use that memory for the new task.
|
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*
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* At this moment task queue owns the memory.
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*
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* - When task is done and task_free() is called the memory will be put to the
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* pool which corresponds to a thread which handled the task.
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|
*/
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typedef struct TaskMemPool {
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/* Number of pre-allocated tasks in the pool. */
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int num_tasks;
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/* Pre-allocated task memory pointers. */
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Task *tasks[MEMPOOL_SIZE];
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} TaskMemPool;
|
|
|
|
#ifdef DEBUG_STATS
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typedef struct TaskMemPoolStats {
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|
/* Number of allocations. */
|
|
int num_alloc;
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/* 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;
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|
} TaskMemPoolStats;
|
|
#endif
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|
|
|
typedef struct TaskThreadLocalStorage {
|
|
/* Memory pool for faster task allocation.
|
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* The idea is to re-use memory of finished/discarded tasks by this thread.
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|
*/
|
|
TaskMemPool task_mempool;
|
|
|
|
/* Local queue keeps thread alive by keeping small amount of tasks ready
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* to be picked up without causing global thread locks for synchronization.
|
|
*/
|
|
int num_local_queue;
|
|
Task *local_queue[LOCAL_QUEUE_SIZE];
|
|
|
|
/* Thread can be marked for delayed tasks push. This is helpful when it's
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* know that lots of subsequent task pushed will happen from the same thread
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|
* without "interrupting" for task execution.
|
|
*
|
|
* We try to accumulate as much tasks as possible in a local queue without
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* any locks first, and then we push all of them into a scheduler's queue
|
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* from within a single mutex lock.
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|
*/
|
|
bool do_delayed_push;
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|
int num_delayed_queue;
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|
Task *delayed_queue[DELAYED_QUEUE_SIZE];
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} TaskThreadLocalStorage;
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|
|
struct TaskPool {
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TaskScheduler *scheduler;
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|
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volatile size_t num;
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ThreadMutex num_mutex;
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ThreadCondition num_cond;
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|
|
void *userdata;
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ThreadMutex user_mutex;
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volatile bool do_cancel;
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volatile bool do_work;
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|
volatile bool is_suspended;
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|
ListBase suspended_queue;
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size_t num_suspended;
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|
|
|
/* If set, this pool may never be work_and_wait'ed, which means TaskScheduler
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|
* has to use its special background fallback thread in case we are in
|
|
* single-threaded situation.
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|
*/
|
|
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;
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|
|
|
/* For the pools which are created from non-main thread which is not a
|
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* scheduler worker thread we can't re-use any of scheduler's threads TLS
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* and have to use our own one.
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|
*/
|
|
bool use_local_tls;
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TaskThreadLocalStorage local_tls;
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|
#ifndef NDEBUG
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|
pthread_t creator_thread_id;
|
|
#endif
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|
|
#ifdef DEBUG_STATS
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TaskMemPoolStats *mempool_stats;
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#endif
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|
};
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|
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struct TaskScheduler {
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|
pthread_t *threads;
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struct TaskThread *task_threads;
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int num_threads;
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bool background_thread_only;
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|
|
ListBase queue;
|
|
ThreadMutex queue_mutex;
|
|
ThreadCondition queue_cond;
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|
|
volatile bool do_exit;
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|
|
/* NOTE: In pthread's TLS we store the whole TaskThread structure. */
|
|
pthread_key_t tls_id_key;
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|
};
|
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|
|
typedef struct TaskThread {
|
|
TaskScheduler *scheduler;
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int id;
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TaskThreadLocalStorage tls;
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|
} TaskThread;
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|
|
/* Helper */
|
|
BLI_INLINE void task_data_free(Task *task, const int thread_id)
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|
{
|
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if (task->free_taskdata) {
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if (task->freedata) {
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|
task->freedata(task->pool, task->taskdata, thread_id);
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|
}
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else {
|
|
MEM_freeN(task->taskdata);
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|
}
|
|
}
|
|
}
|
|
|
|
BLI_INLINE void initialize_task_tls(TaskThreadLocalStorage *tls)
|
|
{
|
|
memset(tls, 0, sizeof(TaskThreadLocalStorage));
|
|
}
|
|
|
|
BLI_INLINE TaskThreadLocalStorage *get_task_tls(TaskPool *pool,
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const int thread_id)
|
|
{
|
|
TaskScheduler *scheduler = pool->scheduler;
|
|
BLI_assert(thread_id >= 0);
|
|
BLI_assert(thread_id <= scheduler->num_threads);
|
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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;
|
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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);
|
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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)
|
|
{
|
|
BLI_assert(!tls->do_delayed_push);
|
|
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);
|
|
}
|
|
BLI_assert(!tls->do_delayed_push);
|
|
}
|
|
|
|
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 */
|
|
BLI_assert(!tls->do_delayed_push);
|
|
task->run(pool, task->taskdata, thread_id);
|
|
BLI_assert(!tls->do_delayed_push);
|
|
|
|
/* 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_push_all(TaskScheduler *scheduler,
|
|
TaskPool *pool,
|
|
Task **tasks,
|
|
int num_tasks)
|
|
{
|
|
if (num_tasks == 0) {
|
|
return;
|
|
}
|
|
|
|
task_pool_num_increase(pool, num_tasks);
|
|
|
|
BLI_mutex_lock(&scheduler->queue_mutex);
|
|
|
|
for (int i = 0; i < num_tasks; i++) {
|
|
BLI_addhead(&scheduler->queue, tasks[i]);
|
|
}
|
|
|
|
BLI_condition_notify_all(&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();
|
|
}
|
|
|
|
BLI_INLINE bool task_can_use_local_queues(TaskPool *pool, int thread_id)
|
|
{
|
|
return (thread_id != -1 && (thread_id != pool->thread_id || pool->do_work));
|
|
}
|
|
|
|
static void task_pool_push(
|
|
TaskPool *pool, TaskRunFunction run, void *taskdata,
|
|
bool free_taskdata, TaskFreeFunction freedata, TaskPriority priority,
|
|
int thread_id)
|
|
{
|
|
/* Allocate task and fill it's properties. */
|
|
Task *task = task_alloc(pool, thread_id);
|
|
task->run = run;
|
|
task->taskdata = taskdata;
|
|
task->free_taskdata = free_taskdata;
|
|
task->freedata = freedata;
|
|
task->pool = pool;
|
|
/* For suspended pools we put everything yo a global queue first
|
|
* and exit as soon as possible.
|
|
*
|
|
* This tasks will be moved to actual execution when pool is
|
|
* activated by work_and_wait().
|
|
*/
|
|
if (pool->is_suspended) {
|
|
BLI_addhead(&pool->suspended_queue, task);
|
|
atomic_fetch_and_add_z(&pool->num_suspended, 1);
|
|
return;
|
|
}
|
|
/* Populate to any local queue first, this is cheapest push ever. */
|
|
if (task_can_use_local_queues(pool, thread_id)) {
|
|
ASSERT_THREAD_ID(pool->scheduler, thread_id);
|
|
TaskThreadLocalStorage *tls = get_task_tls(pool, thread_id);
|
|
/* Try to push to a local execution queue.
|
|
* These tasks will be picked up next.
|
|
*/
|
|
if (tls->num_local_queue < LOCAL_QUEUE_SIZE) {
|
|
tls->local_queue[tls->num_local_queue] = task;
|
|
tls->num_local_queue++;
|
|
return;
|
|
}
|
|
/* If we are in the delayed tasks push mode, we push tasks to a
|
|
* temporary local queue first without any locks, and then move them
|
|
* to global execution queue with a single lock.
|
|
*/
|
|
if (tls->do_delayed_push && tls->num_delayed_queue < DELAYED_QUEUE_SIZE) {
|
|
tls->delayed_queue[tls->num_delayed_queue] = task;
|
|
tls->num_delayed_queue++;
|
|
return;
|
|
}
|
|
}
|
|
/* Do push to a global execution ppol, slowest possible method,
|
|
* causes quite reasonable amount of threading overhead.
|
|
*/
|
|
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 */
|
|
BLI_assert(!tls->do_delayed_push);
|
|
work_task->run(pool, work_task->taskdata, pool->thread_id);
|
|
BLI_assert(!tls->do_delayed_push);
|
|
|
|
/* 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;
|
|
}
|
|
|
|
void BLI_task_pool_delayed_push_begin(TaskPool *pool, int thread_id)
|
|
{
|
|
if (task_can_use_local_queues(pool, thread_id)) {
|
|
ASSERT_THREAD_ID(pool->scheduler, thread_id);
|
|
TaskThreadLocalStorage *tls = get_task_tls(pool, thread_id);
|
|
tls->do_delayed_push = true;
|
|
}
|
|
}
|
|
|
|
void BLI_task_pool_delayed_push_end(TaskPool *pool, int thread_id)
|
|
{
|
|
if (task_can_use_local_queues(pool, thread_id)) {
|
|
ASSERT_THREAD_ID(pool->scheduler, thread_id);
|
|
TaskThreadLocalStorage *tls = get_task_tls(pool, thread_id);
|
|
BLI_assert(tls->do_delayed_push);
|
|
task_scheduler_push_all(pool->scheduler,
|
|
pool,
|
|
tls->delayed_queue,
|
|
tls->num_delayed_queue);
|
|
tls->do_delayed_push = false;
|
|
tls->num_delayed_queue = 0;
|
|
}
|
|
}
|
|
|
|
/* 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);
|
|
}
|