Thinking In C++. Volume 2: Practical Programming

    cout << "~NeedsCleanup " << id << endl;

  }

};

class Blocked3 : public Runnable {

  volatile double d;

public:

  Blocked3() : d(0.0) {}

  void run() {

    try {

      while(!Thread::interrupted()) {

        point1:

        NeedsCleanup n1(1);

        cout << "Sleeping" << endl;

        Thread::sleep(1000);

        point2:

        NeedsCleanup n2(2);

        cout << "Calculating" << endl;

        // A time-consuming, non-blocking operation:

        for(int i = 1; i < 100000; i++)

          d = d + (M_PI + M_E) / (double)i;

      }

      cout << "Exiting via while() test" << endl;

    } catch(Interrupted_Exception&) {

      cout << "Exiting via Interrupted_Exception" << endl;

    }

  }

};

int main(int argc, char* argv[]) {

  if(argc != 2) {

    cerr << "usage: " << argv[0]

      << " delay-in-milliseconds" << endl;

    exit(1);

  }

  int delay = atoi(argv[1]);

  try {

    Thread t(new Blocked3);

    Thread::sleep(delay);

    t.interrupt();

  } catch(Synchronization_Exception& e) {

    cerr << e.what() << endl;

  }

} ///:~

The NeedsCleanup class emphasizes the necessity of proper resource cleanup if you leave the loop via an exception. Note that no pointers are defined in Blocked3::run( ) because, for exception safety, all resources must be enclosed in stack-based objects so that the exception handler can automatically clean them up by calling the destructor.

You must give the program a command-line argument which is the delay time in milliseconds before it calls interrupt( ). By using different delays, you can exit Blocked3::run( ) at different points in the loop: in the blocking sleep( ) call, and in the non-blocking mathematical calculation. You’ll see that if interrupt( ) is called after the label point2 (during the non-blocking operation), first the loop is completed, then all the local objects are destructed, and finally the loop is exited at the top via the while statement. However, if interrupt( ) is called between point1 and point2 (after the while statement but before or during the blocking operation sleep( )), the task exits via the Interrupted_Exception. In that case, only the stack objects that have been created up to the point where the exception is thrown are cleaned up, and you have the opportunity to perform any other cleanup in the catch clause.

A class designed to respond to an interrupt( ) must establish a policy that ensures it will remain in a consistent state. This generally means that all resource acquisition should be wrapped inside stack-based objects so that the destructors will be called regardless of how the run( ) loop exits. Correctly done, code like this can be elegant. Components can be created that completely encapsulate their synchronization mechanisms but are still responsive to an external stimulus (via interrupt( )) without adding any special functions to an object’s interface.

Cooperation between threads

As you’ve seen, when you use threads to run more than one task at a time, you can keep one task from interfering with another task’s resources by using a mutex to synchronize the behavior of the two tasks. That is, if two tasks are stepping on each other over a shared resource (usually memory), you use a mutex to allow only one task at a time to access that resource.

With that problem solved, you can move on to the issue of getting threads to cooperate, so that multiple threads can work together to solve a problem. Now the issue is not about interfering with one another, but rather about working in unison, since portions of such problems must be solved before other portions can be solved. It’s much like project planning: the footings for the house must be dug first, but the steel can be laid and the concrete forms can be built in parallel, and both of those tasks must be finished before the concrete foundation can be poured. The plumbing must be in place before the concrete slab can be poured, the concrete slab must be in place before you start framing, and so on. Some of these tasks can be done in parallel, but certain steps require all tasks to be completed before you can move ahead.

The key issue when tasks are cooperating is handshaking between those tasks. To accomplish this handshaking, we use the same foundation: the mutex, which in this case guarantees that only one task can respond to a signal. This eliminates any possible race conditions. On top of the mutex, we add a way for a task to suspend itself until some external state changes ("the plumbing is now in place"), indicating that it’s time for that task to move forward. In this section, we’ll look at the issues of handshaking between tasks, the problems that can arise, and their solutions.

Wait and signal