A high-performance C++20 coroutine library designed for batch task processing and high-throughput scenarios.

English | 中文

• High Performance: Optimized for high-throughput scenarios with Profile-Guided Optimization (PGO)
• Lock-free Architecture: Efficient queue operations with load balancing
• C++20 Coroutines: Modern coroutine-based task scheduling
• Batch Processing: Designed for concurrent task execution
• Advanced Concurrency: WhenAny, WhenAll operations with optimized scheduling
• Channel Communication: Thread-safe async channels for producer-consumer patterns
• Memory Pool: Custom memory allocation inspired by Redis/Nginx design
• PGO Optimization: Performance improvements through profile-guided compilation
• Deterministic Real-Time Execution: Single-thread-affine RtExecutor for robotics / control / embedded — periodic ticks, CPU pinning, zero syscall in steady state (see flowcoro::rt) and a ready-made Autonomous Driving pipeline demo

Performance Data: For detailed performance metrics and benchmarks, see Performance Data Reference

• Coroutine Creation & Execution: Optimized performance with PGO
• Hello World Throughput: Competitive performance compared to traditional threading
• WhenAny Operations: Efficient concurrent scheduling
• Lock-free Queue: High-performance operations
• Memory Pool Allocation: Faster than standard system allocation
• HTTP Request Processing: Good throughput performance

FlowCoro demonstrates good performance compared to Go and Rust in key areas:

• Coroutine Creation & Execution: Competitive performance against Go and Rust
• Lock-free Queue: Good performance characteristics
• HTTP Request Processing: Solid performance metrics
• Simple Computation: Efficient computational performance
• Memory Pool Allocation: Optimized memory management

Best suited for: Coroutine-based scheduling, batch processing, concurrent task management

• C++20 compiler (GCC 11+, Clang 12+)
• CMake 3.16+
• Linux/macOS/Windows

git clone https://github.com/caixuf/flowcoro.git
cd flowcoro
mkdir build && cd build
cmake .. -DCMAKE_BUILD_TYPE=Release
make -j$(nproc)

Note: PGO optimization is automatically enabled when profile data is available in pgo_profiles/ directory.

#include <flowcoro.hpp>
using namespace flowcoro;

// Simple coroutine task
Task<int> compute(int value) {
    // Simulate work
    co_await sleep_for(std::chrono::milliseconds(10));
    co_return value * 2;
}

// Concurrent execution
Task<void> example() {
    // Tasks start executing synchronously, then are scheduled when they suspend
    auto task1 = compute(10);
    auto task2 = compute(20);
    auto task3 = compute(30);
    
    // Wait for results
    auto result1 = co_await task1;
    auto result2 = co_await task2;
    auto result3 = co_await task3;
    
    std::cout << "Results: " << result1 << ", " << result2 << ", " << result3 << std::endl;
    co_return;
}

// Producer-Consumer with Channel
Task<void> channel_example() {
    auto channel = make_channel<int>(10); // Buffer size: 10
    
    // Producer
    auto producer = [channel]() -> Task<void> {
        for (int i = 0; i < 5; ++i) {
            co_await channel->send(i);
            std::cout << "Produced: " << i << std::endl;
        }
        channel->close();
    };
    
    // Consumer
    auto consumer = [channel]() -> Task<void> {
        while (true) {
            auto value = co_await channel->recv();
            if (!value.has_value()) break; // Channel closed
            std::cout << "Consumed: " << value.value() << std::endl;
        }
    };
    
    auto prod_task = producer();
    auto cons_task = consumer();
    
    co_await prod_task;
    co_await cons_task;
    co_return;
}

int main() {
    sync_wait(example());
    sync_wait(channel_example());
    return 0;
}

FlowCoro uses a three-layer scheduling architecture:

Task Creation → Coroutine Manager → Coroutine Pool → Thread Pool
     ↓              ↓                   ↓              ↓
suspend_never   Load Balancing    Lock-free Queue   Execution

• suspend_never: Tasks start executing synchronously on creation, then suspend at first co_await point
• Smart Load Balancing: Automatic scheduler selection after suspension
• Lock-free Queues: High-performance task distribution
• Continuation Mechanism: Zero-copy task chaining

Alongside the high-throughput scheduler, FlowCoro ships a single-thread deterministic real-time model (RtExecutor) for latency-critical control loops (robotics / autonomous driving / embedded):

• Single-thread affinity: every resume / destroy happens on the executor thread; cross-thread events only post_ready(h) the handle back — never inline resume. This is what FlowEngine depends on to avoid data races.
• Periodic tick: run() is a non-blocking tick (timers → ready → resume/destroy). Lazy-start tasks (RtTask) run at fixed cadence; rt::yield() defers to the next tick, guaranteeing no re-entrancy within one tick.
• CPU pinning: Config{.pin_cpu = N} binds the executor thread to a core (run_blocking).
• Zero syscall steady state: internal re-post uses an executor-thread-local vector snapshot; cross-thread path uses an MPSC lock-free queue.
• Two-phase shutdown: request_stop() → cooperative stop checked at cycle boundary → frames co_return and are destroyed on the executor thread.

#include <flowcoro/rt_executor.h>

flowcoro::rt::RtExecutor ex{{ .pin_cpu = 2 }};
ex.spawn(periodic_control_task(), "control");
ex.run_blocking();   // periodic ticks until all tasks finish
// or: while (!ex.is_finished()) ex.run();

See the complete usage in API Reference §9 and the Autonomous Driving pipeline demo (DDS Pub/Sub + when_any QoS deadline degradation).

Ideal for:

• Web API servers (high request throughput)
• Batch data processing
• High-frequency trading systems
• Microservice gateways
• Producer-consumer pipelines
• Multi-stage data processing workflows

With the Real-Time layer (flowcoro::rt):

• Robotics / autonomous driving control loops (periodic, latency-critical)
• AMR / drone stabilization and navigation
• Embedded deterministic scheduling
• Any embedded/control workload needing single-thread affinity + CPU pinning

Try the Autonomous Driving pipeline demo:

cd build && cmake .. && make ad_pipeline_demo
./examples/autonomous_driving/ad_pipeline_demo 5

Enhanced with Channels:

• Inter-coroutine communication
• Buffered message passing
• Async data pipelines
• Coordinated multi-producer/multi-consumer systems

# Run performance tests
./build/benchmarks/professional_flowcoro_benchmark

# Test different scales
./build/examples/hello_world 10000   # 10K tasks
./build/examples/hello_world 100000  # 100K tasks

• Introduction (中文)
• Quick Start Guide
• API Reference
• Architecture Design
• Performance Data
• PGO Optimization Guide

MIT License - see LICENSE file for details.

Contributions are welcome! Please read our contributing guidelines and submit pull requests.