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Renderive/Core/execution/Render_Executor.cpp
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2026-08-02 03:43:39 +08:00

395 lines
15 KiB
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#include "Render_Executor.h"
#include "../architecture/Render_Time.h"
#include <algorithm>
#include <array>
#include <atomic>
#include <deque>
#include <memory>
#include <mutex>
#include <optional>
#include <unordered_set>
#include <taskflow/taskflow.hpp>
#include <thread>
namespace renderive {
namespace {
struct Render_Executor_Metrics {
std::size_t worker_count{};
std::atomic<std::size_t> active_workers{0};
std::atomic<std::size_t> active_frame_jobs{0};
std::atomic<std::size_t> queued_frame_jobs{0};
std::atomic<std::uint64_t> submitted_tasks{0};
std::atomic<std::uint64_t> started_tasks{0};
std::atomic<std::uint64_t> completed_tasks{0};
std::atomic<std::uint64_t> rejected_frame_jobs{0};
std::atomic<std::uint64_t> dropped_frame_attempts{0};
std::atomic<std::uint64_t> peak_concurrency{0};
std::atomic<std::uint64_t> queue_wait_total_ns{0};
std::atomic<std::uint64_t> queue_wait_max_ns{0};
std::atomic<std::uint64_t> task_duration_total_ns{0};
std::atomic<std::uint64_t> task_duration_max_ns{0};
std::atomic<std::uint64_t> curve_tasks{0};
std::atomic<std::uint64_t> waterfall_tasks{0};
std::atomic<std::uint64_t> primitive_tasks{0};
std::atomic<std::uint64_t> compose_tasks{0};
std::atomic<std::uint64_t> performance_tasks{0};
};
void update_peak(std::atomic<std::uint64_t>& target, std::uint64_t value) {
std::uint64_t current = target.load(std::memory_order_acquire);
while (current < value && !target.compare_exchange_weak(current, value, std::memory_order_acq_rel, std::memory_order_acquire)) {}
}
void add_kind_count(Render_Executor_Metrics& metrics, Render_Task_Kind kind) {
switch (kind) {
case Render_Task_Kind::Frame:
case Render_Task_Kind::Primitive:
metrics.primitive_tasks.fetch_add(1, std::memory_order_relaxed);
break;
case Render_Task_Kind::Curve:
metrics.curve_tasks.fetch_add(1, std::memory_order_relaxed);
break;
case Render_Task_Kind::Waterfall:
metrics.waterfall_tasks.fetch_add(1, std::memory_order_relaxed);
break;
case Render_Task_Kind::Compose:
metrics.compose_tasks.fetch_add(1, std::memory_order_relaxed);
break;
case Render_Task_Kind::Performance:
metrics.performance_tasks.fetch_add(1, std::memory_order_relaxed);
break;
}
}
} // namespace
class Render_Executor_Observer final : public tf::ObserverInterface {
public:
explicit Render_Executor_Observer(std::shared_ptr<Render_Executor_Metrics> metrics)
: metrics(std::move(metrics)) {}
void set_up(std::size_t worker_count) override {
if (metrics)
metrics->worker_count = worker_count;
worker_entry_ns.clear();
worker_entry_ns.resize(worker_count);
}
void on_entry(tf::WorkerView worker, tf::TaskView) override {
if (!metrics)
return;
std::size_t worker_id = worker.id();
if (worker_id < worker_entry_ns.size())
worker_entry_ns[worker_id] = steady_now_ns();
std::size_t active = metrics->active_workers.fetch_add(1, std::memory_order_acq_rel) + 1;
metrics->started_tasks.fetch_add(1, std::memory_order_relaxed);
update_peak(metrics->peak_concurrency, static_cast<std::uint64_t>(active));
}
void on_exit(tf::WorkerView worker, tf::TaskView) override {
if (!metrics)
return;
std::size_t worker_id = worker.id();
if (worker_id < worker_entry_ns.size()) {
std::uint64_t begin_ns = worker_entry_ns[worker_id];
std::uint64_t end_ns = steady_now_ns();
std::uint64_t duration_ns = end_ns > begin_ns ? end_ns - begin_ns : 0;
metrics->task_duration_total_ns.fetch_add(duration_ns, std::memory_order_relaxed);
update_peak(metrics->task_duration_max_ns, duration_ns);
}
metrics->completed_tasks.fetch_add(1, std::memory_order_relaxed);
metrics->active_workers.fetch_sub(1, std::memory_order_acq_rel);
}
private:
std::shared_ptr<Render_Executor_Metrics> metrics;
std::vector<std::uint64_t> worker_entry_ns;
};
class Render_Executor_Private {
struct Task_Run_Record {
std::uint64_t begin_ns{};
std::uint64_t queue_wait_ns{};
};
struct Pending_Frame_Task {
Render_Executor_Task task;
std::uint64_t enqueue_ns{};
};
public:
explicit Render_Executor_Private(std::size_t worker_count)
: metrics(std::make_shared<Render_Executor_Metrics>()),
executor(worker_count) {
metrics->worker_count = worker_count;
observer = executor.make_observer<Render_Executor_Observer>(metrics);
}
~Render_Executor_Private() {
shutdown();
}
bool try_submit(Render_Executor_Task task) {
if (shutting_down.load(std::memory_order_acquire) || (!task.work && !task.build_taskflow)) {
reject(task);
return false;
}
std::uint64_t enqueue_ns = steady_now_ns();
if (!task.frame_job) {
record_submission(task);
submit_to_executor(std::move(task), enqueue_ns);
return true;
}
bool submit_now = false;
{
std::lock_guard<std::mutex> lock(admission_mutex);
if (plot_already_pending_or_admitted_locked(task.plot_id)) {
reject(task);
return false;
}
std::size_t limit = frame_admission_limit();
if (admitted_frame_count < limit) {
admit_frame_locked(task.plot_id);
submit_now = true;
}
else {
std::size_t queue_limit = frame_queue_limit();
if (pending_frame_tasks.size() >= queue_limit) {
reject(task);
return false;
}
if (task.plot_id)
queued_frame_plots.insert(task.plot_id);
record_submission(task);
pending_frame_tasks.push_back(Pending_Frame_Task{std::move(task), enqueue_ns});
return true;
}
}
if (submit_now) {
record_submission(task);
submit_to_executor(std::move(task), enqueue_ns);
return true;
}
reject(task);
return false;
}
void shutdown() {
if (shutting_down.exchange(true, std::memory_order_acq_rel))
return;
{
std::lock_guard<std::mutex> lock(admission_mutex);
pending_frame_tasks.clear();
queued_frame_plots.clear();
}
executor.wait_for_all();
}
Render_Executor_Snapshot snapshot() const {
std::uint64_t submitted = metrics->submitted_tasks.load(std::memory_order_acquire);
std::uint64_t completed = metrics->completed_tasks.load(std::memory_order_acquire);
std::uint64_t started = metrics->started_tasks.load(std::memory_order_acquire);
std::uint64_t queue_total = metrics->queue_wait_total_ns.load(std::memory_order_acquire);
std::uint64_t duration_total = metrics->task_duration_total_ns.load(std::memory_order_acquire);
std::size_t active = metrics->active_workers.load(std::memory_order_acquire);
std::size_t workers = metrics->worker_count;
return {
workers,
active,
workers > active ? workers - active : 0,
metrics->active_frame_jobs.load(std::memory_order_acquire),
metrics->queued_frame_jobs.load(std::memory_order_acquire),
submitted,
started,
completed,
metrics->rejected_frame_jobs.load(std::memory_order_acquire),
metrics->dropped_frame_attempts.load(std::memory_order_acquire),
metrics->peak_concurrency.load(std::memory_order_acquire),
submitted ? queue_total / submitted : 0,
metrics->queue_wait_max_ns.load(std::memory_order_acquire),
completed ? duration_total / completed : 0,
metrics->task_duration_max_ns.load(std::memory_order_acquire),
metrics->curve_tasks.load(std::memory_order_acquire),
metrics->waterfall_tasks.load(std::memory_order_acquire),
metrics->primitive_tasks.load(std::memory_order_acquire),
metrics->compose_tasks.load(std::memory_order_acquire),
metrics->performance_tasks.load(std::memory_order_acquire)
};
}
std::size_t worker_count() const {
return metrics->worker_count;
}
private:
void record_submission(Render_Executor_Task& task) {
metrics->submitted_tasks.fetch_add(1, std::memory_order_relaxed);
add_kind_count(*metrics, task.kind);
if (task.frame_job)
metrics->queued_frame_jobs.fetch_add(1, std::memory_order_relaxed);
if (task.frame_stat)
task.frame_stat->executor_at_submit = snapshot();
}
void submit_to_executor(Render_Executor_Task task, std::uint64_t enqueue_ns) {
auto task_ptr = std::make_shared<Render_Executor_Task>(std::move(task));
auto completion = std::make_shared<Task>(std::move(task_ptr->completion));
auto run_record = std::make_shared<Task_Run_Record>();
auto topology = std::make_shared<tf::Taskflow>();
auto entry = topology->emplace([this, enqueue_ns, task_ptr, run_record]() mutable {
Render_Executor_Task& task = *task_ptr;
std::uint64_t begin_ns = steady_now_ns();
run_record->begin_ns = begin_ns;
std::uint64_t queue_wait_ns = begin_ns > enqueue_ns ? begin_ns - enqueue_ns : 0;
run_record->queue_wait_ns = queue_wait_ns;
metrics->queue_wait_total_ns.fetch_add(queue_wait_ns, std::memory_order_relaxed);
update_peak(metrics->queue_wait_max_ns, queue_wait_ns);
if (task.frame_job) {
metrics->queued_frame_jobs.fetch_sub(1, std::memory_order_relaxed);
metrics->active_frame_jobs.fetch_add(1, std::memory_order_relaxed);
}
});
auto exit = topology->emplace([this, task_ptr, run_record]() mutable {
Render_Executor_Task& task = *task_ptr;
std::uint64_t end_ns = steady_now_ns();
std::uint64_t begin_ns = run_record->begin_ns;
std::uint64_t queue_wait_ns = run_record->queue_wait_ns;
std::uint64_t run_ns = end_ns > begin_ns ? end_ns - begin_ns : 0;
if (task.frame_stat) {
Frame_Worker_Stats& stat = *task.frame_stat;
stat.task_count += std::max<std::uint32_t>(1, task.logical_task_count);
stat.peak_parallelism = static_cast<std::uint32_t>(std::max<std::uint64_t>(stat.peak_parallelism, metrics->peak_concurrency.load(std::memory_order_acquire)));
stat.queue_wait_total_ns += queue_wait_ns;
stat.queue_wait_max_ns = std::max(stat.queue_wait_max_ns, queue_wait_ns);
stat.worker_run_total_ns += run_ns;
stat.parallel_stage_wall_ns += run_ns;
stat.executor_at_finish = snapshot();
}
if (task.frame_job)
metrics->active_frame_jobs.fetch_sub(1, std::memory_order_relaxed);
});
if (task_ptr->build_taskflow) {
task_ptr->build_taskflow(*topology, entry, exit);
}
else {
auto work = topology->emplace([task_ptr]() mutable {
if (task_ptr->work)
task_ptr->work();
});
entry.precede(work);
work.precede(exit);
}
executor.run(*topology, [this, topology, completion, task_ptr]() mutable {
release_and_drain_next(*task_ptr);
if (completion && *completion)
(*completion)();
});
}
std::size_t frame_admission_limit() const {
return std::max<std::size_t>(1, metrics->worker_count);
}
std::size_t frame_queue_limit() const {
return std::max<std::size_t>(1, frame_admission_limit() * 2);
}
bool plot_already_pending_or_admitted_locked(Plot_Execution_Id plot_id) const {
if (!plot_id)
return false;
return admitted_frame_plots.find(plot_id) != admitted_frame_plots.end()
|| queued_frame_plots.find(plot_id) != queued_frame_plots.end();
}
void admit_frame_locked(Plot_Execution_Id plot_id) {
++admitted_frame_count;
if (plot_id)
admitted_frame_plots.insert(plot_id);
}
std::optional<Pending_Frame_Task> take_next_frame_task_locked() {
if (shutting_down.load(std::memory_order_acquire) || pending_frame_tasks.empty())
return std::nullopt;
if (admitted_frame_count >= frame_admission_limit())
return std::nullopt;
Pending_Frame_Task next = std::move(pending_frame_tasks.front());
pending_frame_tasks.pop_front();
if (next.task.plot_id)
queued_frame_plots.erase(next.task.plot_id);
admit_frame_locked(next.task.plot_id);
return next;
}
void release_and_drain_next(const Render_Executor_Task& task) {
if (!task.frame_job)
return;
std::optional<Pending_Frame_Task> next;
{
std::lock_guard<std::mutex> lock(admission_mutex);
if (admitted_frame_count)
--admitted_frame_count;
if (task.plot_id)
admitted_frame_plots.erase(task.plot_id);
next = take_next_frame_task_locked();
}
if (next)
submit_to_executor(std::move(next->task), next->enqueue_ns);
}
void reject(const Render_Executor_Task& task) {
if (task.frame_job)
metrics->rejected_frame_jobs.fetch_add(1, std::memory_order_relaxed);
else
metrics->dropped_frame_attempts.fetch_add(1, std::memory_order_relaxed);
if (task.frame_stat)
task.frame_stat->rejected_task_count++;
}
std::shared_ptr<Render_Executor_Metrics> metrics;
tf::Executor executor;
std::shared_ptr<tf::ObserverInterface> observer;
std::mutex admission_mutex;
std::unordered_set<Plot_Execution_Id> admitted_frame_plots;
std::unordered_set<Plot_Execution_Id> queued_frame_plots;
std::deque<Pending_Frame_Task> pending_frame_tasks;
std::size_t admitted_frame_count{};
std::atomic_bool shutting_down{false};
};
std::size_t resolve_render_worker_count(std::size_t configured_count) {
if (configured_count)
return configured_count;
auto cpu_count = std::thread::hardware_concurrency();
return cpu_count > 1 ? cpu_count - 1 : 1;
}
Render_Executor::Render_Executor(Render_Runtime_Config config)
: d(std::make_unique<Render_Executor_Private>(resolve_render_worker_count(config.worker_count))) {}
Render_Executor::~Render_Executor() = default;
bool Render_Executor::try_submit(Render_Executor_Task task) {
return d->try_submit(std::move(task));
}
void Render_Executor::shutdown() {
d->shutdown();
}
Render_Executor_Snapshot Render_Executor::snapshot() const {
return d->snapshot();
}
std::size_t Render_Executor::worker_count() const {
return d->worker_count();
}
} // namespace renderive