BLI: remove TaskParallelRangePool
This is not currently used and will take some work to support with TBB, so remove it until we have a new implementation based on TBB. Fixes T76005, parallel range pool tests failing. Ref D7475
This commit is contained in:
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1fce2ea743
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3b47f335c6
Notes:
blender-bot
2023-02-14 06:32:27 +01:00
Referenced by issue #76005, test: failing test BLI_task_test in master
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@ -201,18 +201,6 @@ void BLI_task_parallel_range(const int start,
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TaskParallelRangeFunc func,
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TaskParallelSettings *settings);
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typedef struct TaskParallelRangePool TaskParallelRangePool;
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struct TaskParallelRangePool *BLI_task_parallel_range_pool_init(
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const struct TaskParallelSettings *settings);
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void BLI_task_parallel_range_pool_push(struct TaskParallelRangePool *range_pool,
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const int start,
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const int stop,
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void *userdata,
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TaskParallelRangeFunc func,
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const struct TaskParallelSettings *settings);
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void BLI_task_parallel_range_pool_work_and_wait(struct TaskParallelRangePool *range_pool);
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void BLI_task_parallel_range_pool_free(struct TaskParallelRangePool *range_pool);
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/* This data is shared between all tasks, its access needs thread lock or similar protection.
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*/
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typedef struct TaskParallelIteratorStateShared {
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@ -382,210 +382,6 @@ void BLI_task_parallel_range(const int start,
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}
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}
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/**
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* Initialize a task pool to parallelize several for loops at the same time.
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*
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* See public API doc of ParallelRangeSettings for description of all settings.
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* Note that loop-specific settings (like 'tls' data or reduce/free functions) must be left NULL
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* here. Only settings controlling how iteration is parallelized must be defined, as those will
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* affect all loops added to that pool.
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*/
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TaskParallelRangePool *BLI_task_parallel_range_pool_init(const TaskParallelSettings *settings)
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{
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TaskParallelRangePool *range_pool = MEM_callocN(sizeof(*range_pool), __func__);
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BLI_assert(settings->userdata_chunk == NULL);
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BLI_assert(settings->func_reduce == NULL);
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BLI_assert(settings->func_free == NULL);
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range_pool->settings = MEM_mallocN(sizeof(*range_pool->settings), __func__);
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*range_pool->settings = *settings;
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return range_pool;
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}
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/**
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* Add a loop task to the pool. It does not execute it at all.
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*
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* See public API doc of ParallelRangeSettings for description of all settings.
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* Note that only 'tls'-related data are used here.
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*/
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void BLI_task_parallel_range_pool_push(TaskParallelRangePool *range_pool,
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const int start,
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const int stop,
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void *userdata,
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TaskParallelRangeFunc func,
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const TaskParallelSettings *settings)
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{
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BLI_assert(range_pool->pool == NULL);
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if (start == stop) {
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return;
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}
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BLI_assert(start < stop);
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if (settings->userdata_chunk_size != 0) {
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BLI_assert(settings->userdata_chunk != NULL);
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}
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TaskParallelRangeState *state = MEM_callocN(sizeof(*state), __func__);
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state->start = start;
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state->stop = stop;
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state->userdata_shared = userdata;
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state->func = func;
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state->iter_value = start;
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state->initial_tls_memory = settings->userdata_chunk;
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state->tls_data_size = settings->userdata_chunk_size;
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state->func_reduce = settings->func_reduce;
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state->func_free = settings->func_free;
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state->next = range_pool->parallel_range_states;
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range_pool->parallel_range_states = state;
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}
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static void parallel_range_func_finalize(TaskPool *__restrict pool,
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void *v_state,
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int UNUSED(thread_id))
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{
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TaskParallelRangePool *__restrict range_pool = BLI_task_pool_user_data(pool);
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TaskParallelRangeState *state = v_state;
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for (int i = 0; i < range_pool->num_tasks; i++) {
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void *tls_data = (char *)state->flatten_tls_storage + (state->tls_data_size * (size_t)i);
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if (state->func_reduce != NULL) {
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state->func_reduce(state->userdata_shared, state->initial_tls_memory, tls_data);
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}
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if (state->func_free != NULL) {
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/* `func_free` should only free data that was created during execution of `func`. */
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state->func_free(state->userdata_shared, tls_data);
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}
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}
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}
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/**
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* Run all tasks pushed to the range_pool.
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*
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* Note that the range pool is re-usable (you may push new tasks into it and call this function
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* again).
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*/
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void BLI_task_parallel_range_pool_work_and_wait(TaskParallelRangePool *range_pool)
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{
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BLI_assert(range_pool->pool == NULL);
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/* If it's not enough data to be crunched, don't bother with tasks at all,
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* do everything from the current thread.
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*/
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if (!range_pool->settings->use_threading) {
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parallel_range_single_thread(range_pool);
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return;
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}
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TaskScheduler *task_scheduler = BLI_task_scheduler_get();
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const int num_threads = BLI_task_scheduler_num_threads(task_scheduler);
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/* The idea here is to prevent creating task for each of the loop iterations
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* and instead have tasks which are evenly distributed across CPU cores and
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* pull next iter to be crunched using the queue.
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*/
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int num_tasks = num_threads + 2;
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range_pool->num_tasks = num_tasks;
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task_parallel_range_calc_chunk_size(range_pool);
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range_pool->num_tasks = num_tasks = min_ii(
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num_tasks, max_ii(1, range_pool->num_total_iters / range_pool->chunk_size));
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if (num_tasks == 1) {
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parallel_range_single_thread(range_pool);
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return;
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}
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/* We create all 'tls' data here in a single loop. */
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for (TaskParallelRangeState *state = range_pool->parallel_range_states; state != NULL;
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state = state->next) {
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void *userdata_chunk = state->initial_tls_memory;
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const size_t userdata_chunk_size = state->tls_data_size;
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if (userdata_chunk_size == 0) {
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BLI_assert(userdata_chunk == NULL);
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continue;
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}
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void *userdata_chunk_array = NULL;
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state->flatten_tls_storage = userdata_chunk_array = MALLOCA(userdata_chunk_size *
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(size_t)num_tasks);
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for (int i = 0; i < num_tasks; i++) {
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void *userdata_chunk_local = (char *)userdata_chunk_array +
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(userdata_chunk_size * (size_t)i);
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memcpy(userdata_chunk_local, userdata_chunk, userdata_chunk_size);
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}
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}
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TaskPool *task_pool = range_pool->pool = BLI_task_pool_create_suspended(
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task_scheduler, range_pool, TASK_PRIORITY_HIGH);
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range_pool->current_state = range_pool->parallel_range_states;
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const int thread_id = BLI_task_pool_creator_thread_id(task_pool);
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for (int i = 0; i < num_tasks; i++) {
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BLI_task_pool_push_from_thread(
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task_pool, parallel_range_func, POINTER_FROM_INT(i), false, NULL, thread_id);
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}
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BLI_task_pool_work_and_wait(task_pool);
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BLI_assert(atomic_cas_ptr((void **)&range_pool->current_state, NULL, NULL) == NULL);
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/* Finalize all tasks. */
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for (TaskParallelRangeState *state = range_pool->parallel_range_states; state != NULL;
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state = state->next) {
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const size_t userdata_chunk_size = state->tls_data_size;
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void *userdata_chunk_array = state->flatten_tls_storage;
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UNUSED_VARS_NDEBUG(userdata_chunk_array);
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if (userdata_chunk_size == 0) {
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BLI_assert(userdata_chunk_array == NULL);
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continue;
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}
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if (state->func_reduce != NULL || state->func_free != NULL) {
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BLI_task_pool_push_from_thread(
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task_pool, parallel_range_func_finalize, state, false, NULL, thread_id);
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}
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}
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BLI_task_pool_work_and_wait(task_pool);
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BLI_task_pool_free(task_pool);
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range_pool->pool = NULL;
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/* Cleanup all tasks. */
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TaskParallelRangeState *state_next;
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for (TaskParallelRangeState *state = range_pool->parallel_range_states; state != NULL;
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state = state_next) {
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state_next = state->next;
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const size_t userdata_chunk_size = state->tls_data_size;
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void *userdata_chunk_array = state->flatten_tls_storage;
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if (userdata_chunk_size != 0) {
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BLI_assert(userdata_chunk_array != NULL);
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MALLOCA_FREE(userdata_chunk_array, userdata_chunk_size * (size_t)num_tasks);
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}
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MEM_freeN(state);
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}
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range_pool->parallel_range_states = NULL;
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}
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/**
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* Clear/free given \a range_pool.
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*/
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void BLI_task_parallel_range_pool_free(TaskParallelRangePool *range_pool)
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{
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TaskParallelRangeState *state_next = NULL;
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for (TaskParallelRangeState *state = range_pool->parallel_range_states; state != NULL;
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state = state_next) {
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state_next = state->next;
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MEM_freeN(state);
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}
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MEM_freeN(range_pool->settings);
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MEM_freeN(range_pool);
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}
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typedef struct TaskParallelIteratorState {
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void *userdata;
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TaskParallelIteratorIterFunc iter_func;
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@ -36,92 +36,6 @@ static uint gen_pseudo_random_number(uint num)
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return ((num & 255) << 6) + 1;
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}
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/* *** Parallel iterations over range of indices. *** */
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static void task_parallel_range_func(void *UNUSED(userdata),
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int index,
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const TaskParallelTLS *__restrict UNUSED(tls))
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{
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const uint limit = gen_pseudo_random_number((uint)index);
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for (uint i = (uint)index; i < limit;) {
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i += gen_pseudo_random_number(i);
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}
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}
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static void task_parallel_range_test_do(const char *id,
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const int num_items,
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const bool use_threads)
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{
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TaskParallelSettings settings;
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BLI_parallel_range_settings_defaults(&settings);
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settings.use_threading = use_threads;
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double averaged_timing = 0.0;
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for (int i = 0; i < NUM_RUN_AVERAGED; i++) {
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const double init_time = PIL_check_seconds_timer();
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for (int j = 0; j < 10; j++) {
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BLI_task_parallel_range(i + j, i + j + num_items, NULL, task_parallel_range_func, &settings);
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}
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averaged_timing += PIL_check_seconds_timer() - init_time;
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}
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printf("\t%s: non-pooled done in %fs on average over %d runs\n",
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id,
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averaged_timing / NUM_RUN_AVERAGED,
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NUM_RUN_AVERAGED);
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averaged_timing = 0.0;
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for (int i = 0; i < NUM_RUN_AVERAGED; i++) {
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const double init_time = PIL_check_seconds_timer();
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TaskParallelRangePool *range_pool = BLI_task_parallel_range_pool_init(&settings);
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for (int j = 0; j < 10; j++) {
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BLI_task_parallel_range_pool_push(
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range_pool, i + j, i + j + num_items, NULL, task_parallel_range_func, &settings);
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}
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BLI_task_parallel_range_pool_work_and_wait(range_pool);
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BLI_task_parallel_range_pool_free(range_pool);
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averaged_timing += PIL_check_seconds_timer() - init_time;
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}
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printf("\t%s: pooled done in %fs on average over %d runs\n",
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id,
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averaged_timing / NUM_RUN_AVERAGED,
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NUM_RUN_AVERAGED);
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}
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TEST(task, RangeIter10KNoThread)
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{
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task_parallel_range_test_do(
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"Range parallel iteration - Single thread - 10K items", 10000, false);
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}
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TEST(task, RangeIter10k)
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{
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task_parallel_range_test_do("Range parallel iteration - Threaded - 10K items", 10000, true);
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}
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TEST(task, RangeIter100KNoThread)
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{
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task_parallel_range_test_do(
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"Range parallel iteration - Single thread - 100K items", 100000, false);
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}
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TEST(task, RangeIter100k)
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{
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task_parallel_range_test_do("Range parallel iteration - Threaded - 100K items", 100000, true);
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}
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TEST(task, RangeIter1000KNoThread)
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{
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task_parallel_range_test_do(
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"Range parallel iteration - Single thread - 1000K items", 1000000, false);
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}
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TEST(task, RangeIter1000k)
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{
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task_parallel_range_test_do("Range parallel iteration - Threaded - 1000K items", 1000000, true);
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}
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/* *** Parallel iterations over double-linked list items. *** */
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static void task_listbase_light_iter_func(void *UNUSED(userdata),
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@ -67,80 +67,6 @@ TEST(task, RangeIter)
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BLI_threadapi_exit();
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}
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TEST(task, RangeIterPool)
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{
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const int num_tasks = 10;
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int data[num_tasks][NUM_ITEMS] = {{0}};
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int sum = 0;
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BLI_threadapi_init();
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TaskParallelSettings settings;
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BLI_parallel_range_settings_defaults(&settings);
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settings.min_iter_per_thread = 1;
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TaskParallelRangePool *range_pool = BLI_task_parallel_range_pool_init(&settings);
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for (int j = 0; j < num_tasks; j++) {
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settings.userdata_chunk = ∑
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settings.userdata_chunk_size = sizeof(sum);
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settings.func_reduce = task_range_iter_reduce_func;
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BLI_task_parallel_range_pool_push(
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range_pool, 0, NUM_ITEMS, data[j], task_range_iter_func, &settings);
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}
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BLI_task_parallel_range_pool_work_and_wait(range_pool);
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/* Those checks should ensure us all items of the listbase were processed once, and only once -
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* as expected. */
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{
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int expected_sum = 0;
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for (int j = 0; j < num_tasks; j++) {
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for (int i = 0; i < NUM_ITEMS; i++) {
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// EXPECT_EQ(data[j][i], i);
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expected_sum += i;
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}
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}
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EXPECT_EQ(sum, expected_sum);
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}
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/* A pool can be re-used until it is freed. */
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for (int j = 0; j < num_tasks; j++) {
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memset(data[j], 0, sizeof(data[j]));
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}
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sum = 0;
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for (int j = 0; j < num_tasks; j++) {
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settings.userdata_chunk = ∑
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settings.userdata_chunk_size = sizeof(sum);
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settings.func_reduce = task_range_iter_reduce_func;
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BLI_task_parallel_range_pool_push(
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range_pool, 0, NUM_ITEMS, data[j], task_range_iter_func, &settings);
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}
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BLI_task_parallel_range_pool_work_and_wait(range_pool);
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BLI_task_parallel_range_pool_free(range_pool);
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/* Those checks should ensure us all items of the listbase were processed once, and only once -
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* as expected. */
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{
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int expected_sum = 0;
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for (int j = 0; j < num_tasks; j++) {
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for (int i = 0; i < NUM_ITEMS; i++) {
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// EXPECT_EQ(data[j][i], i);
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expected_sum += i;
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}
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}
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EXPECT_EQ(sum, expected_sum);
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}
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BLI_threadapi_exit();
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}
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/* *** Parallel iterations over mempool items. *** */
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static void task_mempool_iter_func(void *userdata, MempoolIterData *item)
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