我想使用 boost::asio 来设置线程池。 我的问题是:如何将特定数据附加到创建的每个线程，以及如何管理单独的输出？

更具体地说，我编写了一个类Simulation，它通过一种在输入中获取一些参数的方法来执行模拟。 该类包含计算所需的所有数据。 由于数据不是太大，我想复制它以便在池的每个线程中使用类 Simulation 的不同实例。

我想做这样的事情: (这里解释了如何设置线程池:SO 和 Asio recipes)

class ParallelSimulation
{
  public:
    static const std::size_t N = 10;

  protected:
    std::vector< boost::shared_ptr<Simulation> > simuInst; // N copy of a reference instance.

  public:

    ...

    // Simulation with a large (>>N) number of inputs
    void eval( std::vector< SimulationInput > inputs )
    {
      // Creation of the pool using N threads
      asio::io_service io_service;
      asio::io_service::work work(io_service);
      boost::thread_group threads;
      for (std::size_t i = 0; i < N; ++i)
        threads.create_thread(boost::bind(&asio::io_service::run, &io_service));

      // Here ? Attaching the duplicates instances of class Simulation ?

      // Adding tasks
      for( std::size_t i = 0, i_end = inputs.size(); i<i_end; ++i)
        io_service.post(...); // add simulation with inputs[i] to the queue

      // How to deal with outputs ?  

      // End of the tasks
      io_service.stop();
      threads.join_all();
    }
};

也许用于设置线程池的技术(使用 boost::asio)不适合我的问题。你有什么建议吗？ 谢谢。

最佳答案

这是我的研究结果!

分布式模拟基于一个主类DistributedSimulation，使用两个实现类:impl::m_io_service 和impl::dispatcher。

boost::asio 线程池基于将io_service::run() 方法附加到不同的线程。
想法是重新定义此方法并包含一种识别当前线程的机制。下面的解决方案基于 boost::uuid 的线程本地存储 boost::thread_specific_ptr。 在阅读了 Tres 的评论后，我认为使用 boost::thread::id 识别线程是一个更好的解决方案(但等价且没有太大区别)。
最后，另一个类用于将输入数据分派(dispatch)给类 Simulation 的实例。此类创建同一个类 Simulation 的多个实例，并使用它们计算每个线程中的结果。

namespace impl {

  // Create a derived class of io_service including thread specific data (a unique identifier of the thread)
  struct m_io_service : public boost::asio::io_service
  {
    static boost::thread_specific_ptr<boost::uuids::uuid> ptrSpec_;

    std::size_t run()
    {
      if(ptrSpec_.get() == 0) 
        ptrSpec_.reset(new boost::uuids::uuid(boost::uuids::random_generator()())  );

      return boost::asio::io_service::run();
    }
  };


  // Create a class that dispatches the input data over the N instances of the class Simulation
  template <class Simulation>
  class dispatcher
  {  
    public:
      static const std::size_t N = 6;

      typedef Simulation::input_t input_t;
      typedef Simulation::output_t output_t;

      friend DistributedSimulation;

    protected:
      std::vector< boost::shared_ptr<Simulation> > simuInst;
      std::vector< boost::uuids::uuid >            map;

    public:

      // Constructor, creating the N instances of class Simulation
      dispatcher( const Simulation& simuRef) 
      {
        simuInst.resize(N);
        for(std::size_t i=0; i<N; ++i)
          simuInst[i].reset( simuRef.clone() );
      }

      // Record the unique identifiers and do the calculation using the right instance of class Simulation
      void dispatch( const Simulation::input_t& in  )
      {
        if( map.size() == 0 ) {
          map.push_back(*m_io_service::ptrSpec_);
          simuInst[0]->eval(in, *m_io_service::ptrSpec_);
        }    
        else {
          if( map.size() < N ) {
            map.push_back(*m_io_service::ptrSpec_);
            simuInst[map.size()-1]->eval(in, *m_io_service::ptrSpec_);
          }
          else {
            for(size_t i=0; i<N;++i) {
              if( map[i] == *m_io_service::ptrSpec_) {
                simuInst[i]->eval(in, *m_io_service::ptrSpec_);
                return;
              }
            }
          }
        }
      }
  };

  boost::thread_specific_ptr<boost::uuids::uuid> m_io_service::ptrSpec_;
}


  // Main class, create a distributed simulation based on a class Simulation
  template <class Simulation>
  class DistributedSimulation
  {
  public:
    static const std::size_t N = impl::dispatcher::N;

  protected: 
    impl::dispatcher _disp;

  public:
    DistributedSimulation() : _disp( Simulation() ) {}

    DistributedSimulation(Simulation& simuRef) 
    : _disp( simuRef ) {  }


    // Simulation with a large (>>N) number of inputs
    void eval( const std::vector< Simulation::input_t >& inputs, std::vector< Simulation::output_t >& outputs )
    {

      // Clear the results from a previous calculation (and stored in instances of class Simulation)
      ...

      // Creation of the pool using N threads
      impl::m_io_service io_service;
      boost::asio::io_service::work work(io_service);
      boost::thread_group threads;
      for (std::size_t i = 0; i < N; ++i)
        threads.create_thread(boost::bind(&impl::m_io_service::run, &io_service));

      // Adding tasks
      for( std::size_t i = 0, i_end = inputs.size(); i<i_end; ++i)
        io_service.post( boost::bind(&impl::dispatcher::dispatch, &_disp, inputs[i]) );

      // End of the tasks
      io_service.stop();
      threads.join_all();

      // Gather the results iterating through instances of class simulation
      ...
    }
  };

编辑

考虑到 Tres 的评论，下面的代码是我之前解决方案的更新。正如我之前所说，它的可读性要好得多!

  template <class Simulation>
  class DistributedSimulation
  {
    public:
      typedef typename Simulation::input_t  input_t;
      typedef typename Simulation::output_t output_t;

      typedef boost::shared_ptr<Simulation> SimulationSPtr_t;
      typedef boost::thread::id             id_t;      
      typedef std::map< id_t, std::size_t >::iterator IDMapIterator_t;

    protected: 
      unsigned int                    _NThreads;   // Number of threads
      std::vector< SimulationSPtr_t > _simuInst;   // Instances of class Simulation
      std::map< id_t, std::size_t >   _IDMap;      // Map between thread id and instance index.

    private:
      boost::mutex _mutex;

    public:

      DistributedSimulation(  ) {}

      DistributedSimulation( const Simulation& simuRef, const unsigned int NThreads = boost::thread::hardware_concurrency() ) 
        { init(simuRef, NThreads); }

      DistributedSimulation(const DistributedSimulation& simuDistrib) 
        { init(simuRef, NThreads); }

      virtual ~DistributedSimulation() {}

      void init(const Simulation& simuRef, const unsigned int NThreads = boost::thread::hardware_concurrency())
      {
        _NThreads = (NThreads == 0) ? 1 : NThreads;
        _simuInst.resize(_NThreads);
        for(std::size_t i=0; i<_NThreads; ++i)
          _simuInst[i].reset( simuRef.clone() );
        _IDMap.clear();
      }


      void dispatch( const input_t& input )
      {
        // Get current thread id
        boost::thread::id id0 = boost::this_thread::get_id();

        // Get the right instance 
        Simulation* sim = NULL;        
        { 
          boost::mutex::scoped_lock scoped_lock(_mutex);
          IDMapIterator_t it = _IDMap.find(id0);
          if( it != _IDMap.end() )
            sim = _simuInst[it->second].get();
        } 

        // Simulation
        if( NULL != sim )
          sim->eval(input);
      }


      // Distributed evaluation.
      void eval( const std::vector< input_t >& inputs, std::vector< output_t >& outputs )
      {
        //--Initialisation
        const std::size_t NInputs = inputs.size();

        // Clear the ouptuts f(contained in instances of class Simulation) from a previous run
        ...

        // Create thread pool and save ids
        boost::asio::io_service io_service;
        boost::asio::io_service::work work(io_service);
        boost::thread_group threads;
        for (std::size_t i = 0; i < _NThreads; ++i)
        {
          boost::thread* thread_ptr = threads.create_thread(boost::bind(&boost::asio::io_service::run, &io_service));
          _IDMap[ thread_ptr->get_id() ] = i;
        }

        // Add tasks
        for( std::size_t i = 0; i < NInputs; ++i)
          io_service.post( boost::bind(&DistributedSimulation::dispatch, this, inputs[i]) );

        // Stop the service
        io_service.stop();
        threads.join_all();

        // Gather results (contained in each instances of class Simulation)
        ...
      }
  }; 

关于c++ - 使用线程池进行模拟: boost-thread and boost-asio，我们在Stack Overflow上找到一个类似的问题： https://stackoverflow.com/questions/11000258/