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authorBastien Montagne <b.mont29@gmail.com>2019-11-25 21:53:17 +0300
committerBastien Montagne <b.mont29@gmail.com>2019-11-25 21:54:40 +0300
commit3f87ac368483f0dcf86a1e3057ce8a6fbbe702ac (patch)
tree41a77f2a782ea2a841c511a4d934b90774e9fef7
parent52f0d685ba9f33c559e1945c0e8c8d50d2447ffe (diff)
Revert "BLI_task: Add pooled threaded index range iterator."
This reverts commit f9028a3be1f77c01edca44a68894e2ba9d9cfb14. This is giving weird heisenbug crash on only Windows release builds... Reverting until we understand to issue.
-rw-r--r--source/blender/blenlib/BLI_task.h19
-rw-r--r--source/blender/blenlib/intern/task.c453
-rw-r--r--tests/gtests/blenlib/BLI_task_performance_test.cc90
-rw-r--r--tests/gtests/blenlib/BLI_task_test.cc120
4 files changed, 86 insertions, 596 deletions
diff --git a/source/blender/blenlib/BLI_task.h b/source/blender/blenlib/BLI_task.h
index 05c3d43a0de..7ef5e518cc8 100644
--- a/source/blender/blenlib/BLI_task.h
+++ b/source/blender/blenlib/BLI_task.h
@@ -196,22 +196,9 @@ void BLI_task_parallel_range(const int start,
const int stop,
void *userdata,
TaskParallelRangeFunc func,
- TaskParallelSettings *settings);
-
-typedef struct TaskParallelRangePool TaskParallelRangePool;
-struct TaskParallelRangePool *BLI_task_parallel_range_pool_init(
- const struct TaskParallelSettings *settings);
-void BLI_task_parallel_range_pool_push(struct TaskParallelRangePool *range_pool,
- const int start,
- const int stop,
- void *userdata,
- TaskParallelRangeFunc func,
- const struct TaskParallelSettings *settings);
-void BLI_task_parallel_range_pool_work_and_wait(struct TaskParallelRangePool *range_pool);
-void BLI_task_parallel_range_pool_free(struct TaskParallelRangePool *range_pool);
-
-/* This data is shared between all tasks, its access needs thread lock or similar protection.
- */
+ const TaskParallelSettings *settings);
+
+/* This data is shared between all tasks, its access needs thread lock or similar protection. */
typedef struct TaskParallelIteratorStateShared {
/* Maximum amount of items to acquire at once. */
int chunk_size;
diff --git a/source/blender/blenlib/intern/task.c b/source/blender/blenlib/intern/task.c
index e926cbb18bc..0613b558aec 100644
--- a/source/blender/blenlib/intern/task.c
+++ b/source/blender/blenlib/intern/task.c
@@ -1042,56 +1042,15 @@ void BLI_task_pool_delayed_push_end(TaskPool *pool, int thread_id)
if (((_mem) != NULL) && ((_size) > 8192)) \
MEM_freeN((_mem))
-/* Stores all needed data to perform a parallelized iteration,
- * with a same operation (callback function).
- * It can be chained with other tasks in a single-linked list way. */
-typedef struct TaskParallelRangeState {
- struct TaskParallelRangeState *next;
-
- /* Start and end point of integer value iteration. */
+typedef struct ParallelRangeState {
int start, stop;
+ void *userdata;
- /* User-defined data, shared between all worker threads. */
- void *userdata_shared;
- /* User-defined callback function called for each value in [start, stop[ specified range. */
TaskParallelRangeFunc func;
- /* Each instance of looping chunks will get a copy of this data
- * (similar to OpenMP's firstprivate).
- */
- void *initial_tls_memory; /* Pointer to actual user-defined 'tls' data. */
- size_t tls_data_size; /* Size of that data. */
-
- void *flatten_tls_storage; /* 'tls' copies of initial_tls_memory for each running task. */
- /* Number of 'tls' copies in the array, i.e. number of worker threads. */
- size_t num_elements_in_tls_storage;
-
- /* Function called from calling thread once whole range have been processed. */
- TaskParallelFinalizeFunc func_finalize;
-
- /* Current value of the iterator, shared between all threads (atomically updated). */
- int iter_value;
- int iter_chunk_num; /* Amount of iterations to process in a single step. */
-} TaskParallelRangeState;
-
-/* Stores all the parallel tasks for a single pool. */
-typedef struct TaskParallelRangePool {
- /* The workers' task pool. */
- TaskPool *pool;
- /* The number of worker tasks we need to create. */
- int num_tasks;
- /* The total number of iterations in all the added ranges. */
- int num_total_iters;
- /* The size (number of items) processed at once by a worker task. */
+ int iter;
int chunk_size;
-
- /* Linked list of range tasks to process. */
- TaskParallelRangeState *parallel_range_states;
- /* Current range task beeing processed, swapped atomically. */
- TaskParallelRangeState *current_state;
- /* Scheduling settings common to all tasks. */
- TaskParallelSettings *settings;
-} TaskParallelRangePool;
+} ParallelRangeState;
BLI_INLINE void task_parallel_calc_chunk_size(const TaskParallelSettings *settings,
const int tot_items,
@@ -1154,102 +1113,66 @@ BLI_INLINE void task_parallel_calc_chunk_size(const TaskParallelSettings *settin
}
}
-BLI_INLINE void task_parallel_range_calc_chunk_size(TaskParallelRangePool *range_pool)
+BLI_INLINE void task_parallel_range_calc_chunk_size(const TaskParallelSettings *settings,
+ const int num_tasks,
+ ParallelRangeState *state)
{
- int num_iters = 0;
- int min_num_iters = INT_MAX;
- for (TaskParallelRangeState *state = range_pool->parallel_range_states; state != NULL;
- state = state->next) {
- const int ni = state->stop - state->start;
- num_iters += ni;
- if (min_num_iters > ni) {
- min_num_iters = ni;
- }
- }
- range_pool->num_total_iters = num_iters;
- /* Note: Passing min_num_iters here instead of num_iters kind of partially breaks the 'static'
- * scheduling, but pooled range iterator is inherently non-static anyway, so adding a small level
- * of dynamic scheduling here should be fine. */
task_parallel_calc_chunk_size(
- range_pool->settings, min_num_iters, range_pool->num_tasks, &range_pool->chunk_size);
+ settings, state->stop - state->start, num_tasks, &state->chunk_size);
}
-BLI_INLINE bool parallel_range_next_iter_get(TaskParallelRangePool *__restrict range_pool,
- int *__restrict r_iter,
- int *__restrict r_count,
- TaskParallelRangeState **__restrict r_state)
+BLI_INLINE bool parallel_range_next_iter_get(ParallelRangeState *__restrict state,
+ int *__restrict iter,
+ int *__restrict count)
{
- TaskParallelRangeState *state;
- int previter = INT32_MAX;
+ int previter = atomic_fetch_and_add_int32(&state->iter, state->chunk_size);
- do {
- if ((state = range_pool->current_state) == NULL) {
- break;
- }
+ *iter = previter;
+ *count = max_ii(0, min_ii(state->chunk_size, state->stop - previter));
- previter = atomic_fetch_and_add_int32(&state->iter_value, range_pool->chunk_size);
- *r_iter = previter;
- *r_count = max_ii(0, min_ii(range_pool->chunk_size, state->stop - previter));
-
- if (previter >= state->stop) {
- /* At this point the state we got is done, we need to go to the next one. In case some other
- * thread already did it, then this does nothing, and we'll just get current valid state
- * at start of the next loop. */
- atomic_cas_ptr((void **)&range_pool->current_state, state, state->next);
- }
- } while (state != NULL && previter >= state->stop);
-
- *r_state = state;
- return (state != NULL && previter < state->stop);
+ return (previter < state->stop);
}
-static void parallel_range_func(TaskPool *__restrict pool, void *tls_data_idx, int thread_id)
+static void parallel_range_func(TaskPool *__restrict pool, void *userdata_chunk, int thread_id)
{
- TaskParallelRangePool *__restrict range_pool = BLI_task_pool_userdata(pool);
+ ParallelRangeState *__restrict state = BLI_task_pool_userdata(pool);
TaskParallelTLS tls = {
.thread_id = thread_id,
- .userdata_chunk = NULL,
+ .userdata_chunk = userdata_chunk,
};
- TaskParallelRangeState *state;
int iter, count;
- while (parallel_range_next_iter_get(range_pool, &iter, &count, &state)) {
- tls.userdata_chunk = (char *)state->flatten_tls_storage +
- (((size_t)POINTER_AS_INT(tls_data_idx)) * state->tls_data_size);
+ while (parallel_range_next_iter_get(state, &iter, &count)) {
for (int i = 0; i < count; i++) {
- state->func(state->userdata_shared, iter + i, &tls);
+ state->func(state->userdata, iter + i, &tls);
}
}
}
-static void parallel_range_single_thread(TaskParallelRangePool *range_pool)
+static void parallel_range_single_thread(const int start,
+ int const stop,
+ void *userdata,
+ TaskParallelRangeFunc func,
+ const TaskParallelSettings *settings)
{
- for (TaskParallelRangeState *state = range_pool->parallel_range_states; state != NULL;
- state = state->next) {
- const int start = state->start;
- const int stop = state->stop;
- void *userdata = state->userdata_shared;
- TaskParallelRangeFunc func = state->func;
-
- void *initial_tls_memory = state->initial_tls_memory;
- const size_t tls_data_size = state->tls_data_size;
- void *flatten_tls_storage = NULL;
- const bool use_tls_data = (tls_data_size != 0) && (initial_tls_memory != NULL);
- if (use_tls_data) {
- flatten_tls_storage = MALLOCA(tls_data_size);
- memcpy(flatten_tls_storage, initial_tls_memory, tls_data_size);
- }
- TaskParallelTLS tls = {
- .thread_id = 0,
- .userdata_chunk = flatten_tls_storage,
- };
- for (int i = start; i < stop; i++) {
- func(userdata, i, &tls);
- }
- if (state->func_finalize != NULL) {
- state->func_finalize(userdata, flatten_tls_storage);
- }
- MALLOCA_FREE(flatten_tls_storage, tls_data_size);
+ void *userdata_chunk = settings->userdata_chunk;
+ const size_t userdata_chunk_size = settings->userdata_chunk_size;
+ void *userdata_chunk_local = NULL;
+ const bool use_userdata_chunk = (userdata_chunk_size != 0) && (userdata_chunk != NULL);
+ if (use_userdata_chunk) {
+ userdata_chunk_local = MALLOCA(userdata_chunk_size);
+ memcpy(userdata_chunk_local, userdata_chunk, userdata_chunk_size);
}
+ TaskParallelTLS tls = {
+ .thread_id = 0,
+ .userdata_chunk = userdata_chunk_local,
+ };
+ for (int i = start; i < stop; i++) {
+ func(userdata, i, &tls);
+ }
+ if (settings->func_finalize != NULL) {
+ settings->func_finalize(userdata, userdata_chunk_local);
+ }
+ MALLOCA_FREE(userdata_chunk_local, userdata_chunk_size);
}
/**
@@ -1262,85 +1185,78 @@ void BLI_task_parallel_range(const int start,
const int stop,
void *userdata,
TaskParallelRangeFunc func,
- TaskParallelSettings *settings)
+ const TaskParallelSettings *settings)
{
+ TaskScheduler *task_scheduler;
+ TaskPool *task_pool;
+ ParallelRangeState state;
+ int i, num_threads, num_tasks;
+
+ void *userdata_chunk = settings->userdata_chunk;
+ const size_t userdata_chunk_size = settings->userdata_chunk_size;
+ void *userdata_chunk_local = NULL;
+ void *userdata_chunk_array = NULL;
+ const bool use_userdata_chunk = (userdata_chunk_size != 0) && (userdata_chunk != NULL);
+
if (start == stop) {
return;
}
BLI_assert(start < stop);
-
- TaskParallelRangeState state = {
- .next = NULL,
- .start = start,
- .stop = stop,
- .userdata_shared = userdata,
- .func = func,
- .iter_value = start,
- .initial_tls_memory = settings->userdata_chunk,
- .tls_data_size = settings->userdata_chunk_size,
- .func_finalize = settings->func_finalize,
- };
- TaskParallelRangePool range_pool = {
- .pool = NULL, .parallel_range_states = &state, .current_state = NULL, .settings = settings};
- int i, num_threads, num_tasks;
-
- void *tls_data = settings->userdata_chunk;
- const size_t tls_data_size = settings->userdata_chunk_size;
- if (tls_data_size != 0) {
- BLI_assert(tls_data != NULL);
+ if (userdata_chunk_size != 0) {
+ BLI_assert(userdata_chunk != NULL);
}
- const bool use_tls_data = (tls_data_size != 0) && (tls_data != NULL);
- void *flatten_tls_storage = NULL;
/* If it's not enough data to be crunched, don't bother with tasks at all,
- * do everything from the current thread.
+ * do everything from the main thread.
*/
if (!settings->use_threading) {
- parallel_range_single_thread(&range_pool);
+ parallel_range_single_thread(start, stop, userdata, func, settings);
return;
}
- TaskScheduler *task_scheduler = BLI_task_scheduler_get();
+ task_scheduler = BLI_task_scheduler_get();
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.
*/
- range_pool.num_tasks = num_tasks = num_threads + 2;
+ num_tasks = num_threads + 2;
+
+ state.start = start;
+ state.stop = stop;
+ state.userdata = userdata;
+ state.func = func;
+ state.iter = start;
- task_parallel_range_calc_chunk_size(&range_pool);
- range_pool.num_tasks = num_tasks = min_ii(num_tasks,
- max_ii(1, (stop - start) / range_pool.chunk_size));
+ task_parallel_range_calc_chunk_size(settings, num_tasks, &state);
+ num_tasks = min_ii(num_tasks, max_ii(1, (stop - start) / state.chunk_size));
if (num_tasks == 1) {
- parallel_range_single_thread(&range_pool);
+ parallel_range_single_thread(start, stop, userdata, func, settings);
return;
}
- TaskPool *task_pool = range_pool.pool = BLI_task_pool_create_suspended(task_scheduler,
- &range_pool);
+ task_pool = BLI_task_pool_create_suspended(task_scheduler, &state);
/* NOTE: This way we are adding a memory barrier and ensure all worker
* threads can read and modify the value, without any locks. */
- atomic_cas_ptr((void **)&range_pool.current_state, NULL, &state);
- BLI_assert(range_pool.current_state == &state);
+ atomic_fetch_and_add_int32(&state.iter, 0);
- if (use_tls_data) {
- state.flatten_tls_storage = flatten_tls_storage = MALLOCA(tls_data_size * (size_t)num_tasks);
- state.tls_data_size = tls_data_size;
+ if (use_userdata_chunk) {
+ userdata_chunk_array = MALLOCA(userdata_chunk_size * num_tasks);
}
for (i = 0; i < num_tasks; i++) {
- if (use_tls_data) {
- void *userdata_chunk_local = (char *)flatten_tls_storage + (tls_data_size * (size_t)i);
- memcpy(userdata_chunk_local, tls_data, tls_data_size);
+ 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,
- POINTER_FROM_INT(i),
+ userdata_chunk_local,
false,
TASK_PRIORITY_HIGH,
task_pool->thread_id);
@@ -1349,222 +1265,15 @@ void BLI_task_parallel_range(const int start,
BLI_task_pool_work_and_wait(task_pool);
BLI_task_pool_free(task_pool);
- if (use_tls_data) {
+ if (use_userdata_chunk) {
if (settings->func_finalize != NULL) {
for (i = 0; i < num_tasks; i++) {
- void *userdata_chunk_local = (char *)flatten_tls_storage + (tls_data_size * (size_t)i);
+ userdata_chunk_local = (char *)userdata_chunk_array + (userdata_chunk_size * i);
settings->func_finalize(userdata, userdata_chunk_local);
}
}
- MALLOCA_FREE(flatten_tls_storage, tls_data_size * (size_t)num_tasks);
- }
-}
-
-/**
- * Initialize a task pool to parallelize several for loops at the same time.
- *
- * See public API doc of ParallelRangeSettings for description of all settings.
- * Note that loop-specific settings (like 'tls' data or finalize function) must be left NULL here.
- * Only settings controlling how iteration is parallelized must be defined, as those will affect
- * all loops added to that pool.
- */
-TaskParallelRangePool *BLI_task_parallel_range_pool_init(const TaskParallelSettings *settings)
-{
- TaskParallelRangePool *range_pool = MEM_callocN(sizeof(*range_pool), __func__);
-
- BLI_assert(settings->userdata_chunk == NULL);
- BLI_assert(settings->func_finalize == NULL);
- range_pool->settings = MEM_mallocN(sizeof(*range_pool->settings), __func__);
- *range_pool->settings = *settings;
-
- return range_pool;
-}
-
-/**
- * Add a loop task to the pool. It does not execute it at all.
- *
- * See public API doc of ParallelRangeSettings for description of all settings.
- * Note that only 'tls'-related data are used here.
- */
-void BLI_task_parallel_range_pool_push(TaskParallelRangePool *range_pool,
- const int start,
- const int stop,
- void *userdata,
- TaskParallelRangeFunc func,
- const TaskParallelSettings *settings)
-{
- BLI_assert(range_pool->pool == NULL);
-
- if (start == stop) {
- return;
- }
-
- BLI_assert(start < stop);
- if (settings->userdata_chunk_size != 0) {
- BLI_assert(settings->userdata_chunk != NULL);
- }
-
- TaskParallelRangeState *state = MEM_callocN(sizeof(*state), __func__);
- state->start = start;
- state->stop = stop;
- state->userdata_shared = userdata;
- state->func = func;
- state->iter_value = start;
- state->initial_tls_memory = settings->userdata_chunk;
- state->tls_data_size = settings->userdata_chunk_size;
- state->func_finalize = settings->func_finalize;
-
- state->next = range_pool->parallel_range_states;
- range_pool->parallel_range_states = state;
-}
-
-static void parallel_range_func_finalize(TaskPool *__restrict pool,
- void *v_state,
- int UNUSED(thread_id))
-{
- TaskParallelRangePool *__restrict range_pool = BLI_task_pool_userdata(pool);
- TaskParallelRangeState *state = v_state;
-
- for (int i = 0; i < range_pool->num_tasks; i++) {
- void *tls_data = (char *)state->flatten_tls_storage + (state->tls_data_size * (size_t)i);
- state->func_finalize(state->userdata_shared, tls_data);
- }
-}
-
-/**
- * Run all tasks pushed to the range_pool.
- *
- * Note that the range pool is re-usable (you may push new tasks into it and call this function
- * again).
- */
-void BLI_task_parallel_range_pool_work_and_wait(TaskParallelRangePool *range_pool)
-{
- BLI_assert(range_pool->pool == NULL);
-
- /* If it's not enough data to be crunched, don't bother with tasks at all,
- * do everything from the current thread.
- */
- if (!range_pool->settings->use_threading) {
- parallel_range_single_thread(range_pool);
- return;
- }
-
- TaskScheduler *task_scheduler = BLI_task_scheduler_get();
- const int 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.
- */
- int num_tasks = num_threads + 2;
- range_pool->num_tasks = num_tasks;
-
- task_parallel_range_calc_chunk_size(range_pool);
- range_pool->num_tasks = num_tasks = min_ii(
- num_tasks, max_ii(1, range_pool->num_total_iters / range_pool->chunk_size));
-
- if (num_tasks == 1) {
- parallel_range_single_thread(range_pool);
- return;
- }
-
- /* We create all 'tls' data here in a single loop. */
- for (TaskParallelRangeState *state = range_pool->parallel_range_states; state != NULL;
- state = state->next) {
- void *userdata_chunk = state->initial_tls_memory;
- const size_t userdata_chunk_size = state->tls_data_size;
- if (userdata_chunk_size == 0) {
- BLI_assert(userdata_chunk == NULL);
- continue;
- }
-
- void *userdata_chunk_array = NULL;
- state->flatten_tls_storage = userdata_chunk_array = MALLOCA(userdata_chunk_size *
- (size_t)num_tasks);
- for (int i = 0; i < num_tasks; i++) {
- void *userdata_chunk_local = (char *)userdata_chunk_array +
- (userdata_chunk_size * (size_t)i);
- memcpy(userdata_chunk_local, userdata_chunk, userdata_chunk_size);
- }
- }
-
- TaskPool *task_pool = range_pool->pool = BLI_task_pool_create_suspended(task_scheduler,
- range_pool);
-
- /* NOTE: This way we are adding a memory barrier and ensure all worker
- * threads can read and modify the value, without any locks. */
- atomic_cas_ptr((void **)&range_pool->current_state, NULL, range_pool->parallel_range_states);
- BLI_assert(range_pool->current_state == range_pool->parallel_range_states);
-
- for (int i = 0; i < num_tasks; i++) {
- BLI_task_pool_push_from_thread(task_pool,
- parallel_range_func,
- POINTER_FROM_INT(i),
- false,
- TASK_PRIORITY_HIGH,
- task_pool->thread_id);
- }
-
- BLI_task_pool_work_and_wait(task_pool);
-
- BLI_assert(range_pool->current_state == NULL);
-
- /* Finalize all tasks. */
- for (TaskParallelRangeState *state = range_pool->parallel_range_states; state != NULL;
- state = state->next) {
- const size_t userdata_chunk_size = state->tls_data_size;
- void *userdata_chunk_array = state->flatten_tls_storage;
- if (userdata_chunk_size == 0) {
- BLI_assert(userdata_chunk_array == NULL);
- MEM_freeN(state);
- continue;
- }
-
- if (state->func_finalize != NULL) {
- BLI_task_pool_push_from_thread(task_pool,
- parallel_range_func_finalize,
- state,
- false,
- TASK_PRIORITY_HIGH,
- task_pool->thread_id);
- }
- }
-
- BLI_task_pool_work_and_wait(task_pool);
- BLI_task_pool_free(task_pool);
- range_pool->pool = NULL;
-
- /* Cleanup all tasks. */
- TaskParallelRangeState *state_next;
- for (TaskParallelRangeState *state = range_pool->parallel_range_states; state != NULL;
- state = state_next) {
- state_next = state->next;
-
- const size_t userdata_chunk_size = state->tls_data_size;
- void *userdata_chunk_array = state->flatten_tls_storage;
- if (userdata_chunk_size != 0) {
- BLI_assert(userdata_chunk_array != NULL);
- MALLOCA_FREE(userdata_chunk_array, userdata_chunk_size * (size_t)num_tasks);
- }
-
- MEM_freeN(state);
+ MALLOCA_FREE(userdata_chunk_array, userdata_chunk_size * num_tasks);
}
- range_pool->parallel_range_states = NULL;
-}
-
-/**
- * Clear/free given \a range_pool.
- */
-void BLI_task_parallel_range_pool_free(TaskParallelRangePool *range_pool)
-{
- TaskParallelRangeState *state_next = NULL;
- for (TaskParallelRangeState *state = range_pool->parallel_range_states; state != NULL;
- state = state_next) {
- state_next = state->next;
- MEM_freeN(state);
- }
- MEM_freeN(range_pool->settings);
- MEM_freeN(range_pool);
}
typedef struct TaskParallelIteratorState {
diff --git a/tests/gtests/blenlib/BLI_task_performance_test.cc b/tests/gtests/blenlib/BLI_task_performance_test.cc
index 84b7b8b6439..dc8981f8064 100644
--- a/tests/gtests/blenlib/BLI_task_performance_test.cc
+++ b/tests/gtests/blenlib/BLI_task_performance_test.cc
@@ -19,6 +19,8 @@ extern "C" {
#include "MEM_guardedalloc.h"
}
+/* *** Parallel iterations over double-linked list items. *** */
+
#define NUM_RUN_AVERAGED 100
static uint gen_pseudo_random_number(uint num)
@@ -36,94 +38,6 @@ static uint gen_pseudo_random_number(uint num)
return ((num & 255) << 6) + 1;
}
-/* *** Parallel iterations over range of indices. *** */
-
-static void task_parallel_range_func(void *UNUSED(userdata),
- int index,
- const TaskParallelTLS *__restrict UNUSED(tls))
-{
- const uint limit = gen_pseudo_random_number((uint)index);
- for (uint i = (uint)index; i < limit;) {
- i += gen_pseudo_random_number(i);
- }
-}
-
-static void task_parallel_range_test_do(const char *id,
- const int num_items,
- const bool use_threads)
-{
- TaskParallelSettings settings;
- BLI_parallel_range_settings_defaults(&settings);
- settings.use_threading = use_threads;
-
- double averaged_timing = 0.0;
- for (int i = 0; i < NUM_RUN_AVERAGED; i++) {
- const double init_time = PIL_check_seconds_timer();
- for (int j = 0; j < 10; j++) {
- BLI_task_parallel_range(i + j, i + j + num_items, NULL, task_parallel_range_func, &settings);
- }
- averaged_timing += PIL_check_seconds_timer() - init_time;
- }
-
- printf("\t%s: non-pooled done in %fs on average over %d runs\n",
- id,
- averaged_timing / NUM_RUN_AVERAGED,
- NUM_RUN_AVERAGED);
-
- averaged_timing = 0.0;
- for (int i = 0; i < NUM_RUN_AVERAGED; i++) {
- const double init_time = PIL_check_seconds_timer();
- TaskParallelRangePool *range_pool = BLI_task_parallel_range_pool_init(&settings);
- for (int j = 0; j < 10; j++) {
- BLI_task_parallel_range_pool_push(
- range_pool, i + j, i + j + num_items, NULL, task_parallel_range_func, &settings);
- }
- BLI_task_parallel_range_pool_work_and_wait(range_pool);
- BLI_task_parallel_range_pool_free(range_pool);
- averaged_timing += PIL_check_seconds_timer() - init_time;
- }
-
- printf("\t%s: pooled done in %fs on average over %d runs\n",
- id,
- averaged_timing / NUM_RUN_AVERAGED,
- NUM_RUN_AVERAGED);
-}
-
-TEST(task, RangeIter10KNoThread)
-{
- task_parallel_range_test_do(
- "Range parallel iteration - Single thread - 10K items", 10000, false);
-}
-
-TEST(task, RangeIter10k)
-{
- task_parallel_range_test_do("Range parallel iteration - Threaded - 10K items", 10000, true);
-}
-
-TEST(task, RangeIter100KNoThread)
-{
- task_parallel_range_test_do(
- "Range parallel iteration - Single thread - 100K items", 100000, false);
-}
-
-TEST(task, RangeIter100k)
-{
- task_parallel_range_test_do("Range parallel iteration - Threaded - 100K items", 100000, true);
-}
-
-TEST(task, RangeIter1000KNoThread)
-{
- task_parallel_range_test_do(
- "Range parallel iteration - Single thread - 1000K items", 1000000, false);
-}
-
-TEST(task, RangeIter1000k)
-{
- task_parallel_range_test_do("Range parallel iteration - Threaded - 1000K items", 1000000, true);
-}
-
-/* *** Parallel iterations over double-linked list items. *** */
-
static void task_listbase_light_iter_func(void *UNUSED(userdata),
void *item,
int index,
diff --git a/tests/gtests/blenlib/BLI_task_test.cc b/tests/gtests/blenlib/BLI_task_test.cc
index a682e8aedf6..62ae0baaec9 100644
--- a/tests/gtests/blenlib/BLI_task_test.cc
+++ b/tests/gtests/blenlib/BLI_task_test.cc
@@ -17,126 +17,6 @@ extern "C" {
#define NUM_ITEMS 10000
-/* *** Parallel iterations over range of integer values. *** */
-
-static void task_range_iter_func(void *userdata, int index, const TaskParallelTLS *__restrict tls)
-{
- int *data = (int *)userdata;
- data[index] = index;
- *((int *)tls->userdata_chunk) += index;
- // printf("%d, %d, %d\n", index, data[index], *((int *)tls->userdata_chunk));
-}
-
-static void task_range_iter_finalize_func(void *__restrict userdata,
- void *__restrict userdata_chunk)
-{
- int *data = (int *)userdata;
- data[NUM_ITEMS] += *(int *)userdata_chunk;
- // printf("%d, %d\n", data[NUM_ITEMS], *((int *)userdata_chunk));
-}
-
-TEST(task, RangeIter)
-{
- int data[NUM_ITEMS + 1] = {0};
- int sum = 0;
-
- BLI_threadapi_init();
-
- TaskParallelSettings settings;
- BLI_parallel_range_settings_defaults(&settings);
- settings.min_iter_per_thread = 1;
-
- settings.userdata_chunk = &sum;
- settings.userdata_chunk_size = sizeof(sum);
- settings.func_finalize = task_range_iter_finalize_func;
-
- BLI_task_parallel_range(0, NUM_ITEMS, data, task_range_iter_func, &settings);
-
- /* Those checks should ensure us all items of the listbase were processed once, and only once -
- * as expected. */
-
- int expected_sum = 0;
- for (int i = 0; i < NUM_ITEMS; i++) {
- EXPECT_EQ(data[i], i);
- expected_sum += i;
- }
- EXPECT_EQ(data[NUM_ITEMS], expected_sum);
-
- BLI_threadapi_exit();
-}
-
-TEST(task, RangeIterPool)
-{
- const int num_tasks = 10;
- int data[num_tasks][NUM_ITEMS + 1] = {{0}};
- int sum = 0;
-
- BLI_threadapi_init();
-
- TaskParallelSettings settings;
- BLI_parallel_range_settings_defaults(&settings);
- settings.min_iter_per_thread = 1;
-
- TaskParallelRangePool *range_pool = BLI_task_parallel_range_pool_init(&settings);
-
- for (int j = 0; j < num_tasks; j++) {
- settings.userdata_chunk = &sum;
- settings.userdata_chunk_size = sizeof(sum);
- settings.func_finalize = task_range_iter_finalize_func;
-
- BLI_task_parallel_range_pool_push(
- range_pool, 0, NUM_ITEMS, data[j], task_range_iter_func, &settings);
- }
-
- BLI_task_parallel_range_pool_work_and_wait(range_pool);
-
- /* Those checks should ensure us all items of the listbase were processed once, and only once -
- * as expected. */
-
- for (int j = 0; j < num_tasks; j++) {
- int expected_sum = 0;
- for (int i = 0; i < NUM_ITEMS; i++) {
- // EXPECT_EQ(data[j][i], i);
- expected_sum += i;
- }
- EXPECT_EQ(data[j][NUM_ITEMS], expected_sum);
- }
-
- /* A pool can be re-used untill it is freed. */
-
- for (int j = 0; j < num_tasks; j++) {
- memset(data[j], 0, sizeof(data[j]));
- }
- sum = 0;
-
- for (int j = 0; j < num_tasks; j++) {
- settings.userdata_chunk = &sum;
- settings.userdata_chunk_size = sizeof(sum);
- settings.func_finalize = task_range_iter_finalize_func;
-
- BLI_task_parallel_range_pool_push(
- range_pool, 0, NUM_ITEMS, data[j], task_range_iter_func, &settings);
- }
-
- BLI_task_parallel_range_pool_work_and_wait(range_pool);
-
- BLI_task_parallel_range_pool_free(range_pool);
-
- /* Those checks should ensure us all items of the listbase were processed once, and only once -
- * as expected. */
-
- for (int j = 0; j < num_tasks; j++) {
- int expected_sum = 0;
- for (int i = 0; i < NUM_ITEMS; i++) {
- // EXPECT_EQ(data[j][i], i);
- expected_sum += i;
- }
- EXPECT_EQ(data[j][NUM_ITEMS], expected_sum);
- }
-
- BLI_threadapi_exit();
-}
-
/* *** Parallel iterations over mempool items. *** */
static void task_mempool_iter_func(void *userdata, MempoolIterData *item)