what is the best way to synchronize container access between multiple threads in real-time application

Question

Hi,

I have std::list<Info> infoList in my application that is shared between two threads. These 2 threads are accessing this list as follows:

Thread 1: uses push_back(), pop_front() or clear() on the list (Depending on the situation) Thread 2: uses an iterator to iterate through the items in the list and do some actions.

Thread 2 is iterating the list like the following:

for(std::list<Info>::iterator i = infoList.begin(); i != infoList.end(); ++i)
{
  DoAction(i);
}

The code is compiled using GCC 4.4.2.

Sometimes ++i causes a segfault and crashes the application. The error is caused in std_list.h line 143 at the following line:

_M_node = _M_node->_M_next;

I guess this is a racing condition. The list might have changed or even cleared by thread 1 while thread 2 was iterating it.

I used Mutex to synchronize access to this list and all went ok during my initial test. But the system just freezes under stress test making this solution totally unacceptable. This application is a real-time application and i need to find a solution so both threads can run as fast as possible without hurting the total applications throughput.

My question is this: Thread 1 and Thread 2 need to execute as fast as possible since this is a real-time application. what can i do to prevent this problem and still maintain the application performance? Are there any lock-free algorithms available for such a problem?

Its ok if i miss some newly added Info objects in thread 2's iteration but what can i do to prevent the iterator from becoming a dangling pointer?

Thanks

Answer 1

To prevent your iterator from being invalidated you have to lock the whole for loop. Now I guess the first thread may have difficulties updating the list. I would try to give it a chance to do its job on each (or every Nth iteration).

In pseudo-code that would look like:

mutex_lock();
for(...){
  doAction();
  mutex_unlock();
  thread_yield();  // give first thread a chance
  mutex_lock();
  if(iterator_invalidated_flag) // set by first thread
    reset_iterator();
}
mutex_unlock();

Answer 2

I don't think you can get away without any synchronisation at all in this case as certain operation will invalidate the iterators you are using. With a list, this is fairly limited (basically, if both threads are trying to manipulate iterators to the same element at the same time) but there is still a danger that you'll be removing an element at the same time you're trying to append one to it.

Are you by any chance holding the lock across DoAction(i)? You obviously only want to hold the lock for the absolute minimum of time that you can get away with in order to maximise the performance. From the code above I think you'll want to decompose the loop somewhat in order to speed up both sides of the operation.

Something along the lines of:

while (processItems) {
  Info item;
  lock(mutex);
  if (!infoList.empty()) {
     item = infoList.front();
     infoList.pop_front();
  }
  unlock(mutex);
  DoAction(item);
  delayALittle();
}

And the insert function would still have to look like this:

lock(mutex);
infoList.push_back(item);
unlock(mutex);

Unless the queue is likely to be massive, I'd be tempted to use something like a std::vector<Info> or even a std::vector<boost::shared_ptr<Info> > to minimize the copying of the Info objects (assuming that these are somewhat more expensive to copy compared to a boost::shared_ptr. Generally, operations on a vector tend to be a little faster than on a list, especially if the objects stored in the vector are small and cheap to copy.

Answer 3

You have to decide which thread is the more important. If it is the update thread, then it must signal the iterator thread to stop, wait and start again. If it is the iterator thread, it can simply lock the list until iteration is done.

Answer 4

Your for() loop can potentially keep a lock for a relatively long time, depending on how many elements it iterates. You can get in real trouble if it "polls" the queue, constantly checking if a new element became available. That makes the thread own the mutex for an unreasonably long time, giving few opportunities to the producer thread to break in and add an element. And burning lots of unnecessary CPU cycles in the process.

You need a "bounded blocking queue". Don't write it yourself, the lock design is not trivial. Hard to find good examples, most of it is .NET code. This article looks promising.

Answer 5

You must be using some threading library. If you are using Intel TBB, you can use concurrent_vector or concurrent_queue. See this.

Answer 6

In general it is not safe to use STL containers this way. You will have to implement specific method to make your code thread safe. The solution you chose depends on your needs. I would probably solve this by maintaining two lists, one in each thread. And communicating the changes through a lock free queue (mentioned in the comments to this question). You could also limit the lifetime of your Info objects by wrapping them in boost::shared_ptr e.g.

typedef boost::shared_ptr<Info> InfoReference; 
typedef std::list<InfoReference> InfoList;

enum CommandValue
{
    Insert,
    Delete
}

struct Command
{
    CommandValue operation;
    InfoReference reference;
}

typedef LockFreeQueue<Command> CommandQueue;

class Thread1
{
    Thread1(CommandQueue queue) : m_commands(queue) {}
    void run()
    {
        while (!finished)
        {
            //Process Items and use 
            // deleteInfo() or addInfo()
        };

    }

    void deleteInfo(InfoReference reference)
    {
        Command command;
        command.operation = Delete;
        command.reference = reference;
        m_commands.produce(command);
    }

    void addInfo(InfoReference reference)
    {
        Command command;
        command.operation = Insert;
        command.reference = reference;
        m_commands.produce(command);
    }
}

private:
    CommandQueue& m_commands;
    InfoList m_infoList;
}   

class Thread2
{
    Thread2(CommandQueue queue) : m_commands(queue) {}

    void run()
    {
        while(!finished)
        {
            processQueue();
            processList();
        }   
    }

    void processQueue()
    {
        Command command;
        while (m_commands.consume(command))
        {
            switch(command.operation)
            {
                case Insert:
                    m_infoList.push_back(command.reference);
                    break;
                case Delete:
                    m_infoList.remove(command.reference);
                    break;
            }
        }
    }

    void processList()
    {
        // Iterate over m_infoList
    }

private:
    CommandQueue& m_commands;
    InfoList m_infoList;
}   


void main()
{
CommandQueue commands;

Thread1 thread1(commands);
Thread2 thread2(commands);

thread1.start();
thread2.start();

waitforTermination();

}

This has not been compiled. You still need to make sure that access to your Info objects is thread safe.

Answer 7

I would like to know what is the purpose of this list, it would be easier to answer the question then.

As Hoare said, it is generally a bad idea to try to share data to communicate between two threads, rather you should communicate to share data: ie messaging.

If this list is modelling a queue, for example, you might simply use one of the various ways to communicate (such as sockets) between the two threads. Consumer / Producer is a standard and well-known problem.

If your items are expensive, then only pass the pointers around during communication, you'll avoid copying the items themselves.

In general, it's exquisitely difficult to share data, although it is unfortunately the only way of programming we hear of in school. Normally only low-level implementation of "channels" of communication should ever worry about synchronization and you should learn to use the channels to communicate instead of trying to emulate them.

Answer 8

If you want to continue using std::list in a multi-threaded environment, I would recommend wrapping it in a class with a mutex that provides locked access to it. Depending on the exact usage, it might make sense to switch to a event-driven queue model where messages are passed on a queue that multiple worker threads are consuming (hint: producer-consumer).

I would seriously take Matthieu's thought into consideration. Many problems that are being solved using multi-threaded programming are better solved using message-passing between threads or processes. If you need high throughput and do not absolutely require that the processing share the same memory space, consider using something like the Message-Passing Interface (MPI) instead of rolling your own multi-threaded solution. There are a bunch of C++ implementations available - OpenMPI, Boost.MPI, Microsoft MPI, etc. etc.

Answer 9

As you mentioned that you don't care if your iterating consumer misses some newly-added entries, you could use a copy-on-write list underneath. That allows the iterating consumer to operate on a consistent snapshot of the list as of when it first started, while, in other threads, updates to the list yield fresh but consistent copies, without perturbing any of the extant snapshots.

The trade here is that each update to the list requires locking for exclusive access long enough to copy the entire list. This technique is biased toward having many concurrent readers and less frequent updates.

Trying to add intrinsic locking to the container first requires you to think about which operations need to behave in atomic groups. For instance, checking if the list is empty before trying to pop off the first element requires an atomic pop-if-not-empty operation; otherwise, the answer to the list being empty can change in between when the caller receives the answer and attempts to act upon it.

It's not clear in your example above what guarantees the iteration must obey. Must every element in the list eventually be visited by the iterating thread? Does it make multiple passes? What does it mean for one thread to remove an element from the list while another thread is running DoAction() against it? I suspect that working through these questions will lead to significant design changes.

---

You're working in C++, and you mentioned needing a queue with a pop-if-not-empty operation. I wrote a two-lock queue many years ago using the ACE Library's concurrency primitives, as the Boost thread library was not yet ready for production use, and the chance for the C++ Standard Library including such facilities was a distant dream. Porting it to something more modern would be easy.

This queue of mine -- called concurrent::two_lock_queue -- allows access to the head of the queue only via RAII. This ensures that acquiring the lock to read the head will always be mated with a release of the lock. A consumer constructs a const_front (const access to head element), a front (non-const access to head element), or a renewable_front (non-const access to head and successor elements) object to represent the exclusive right to access the head element of the queue. Such "front" objects can't be copied.

Class two_lock_queue also offers a pop_front() function that waits until at least one element is available to be removed, but, in keeping with std::queue's and std::stack's style of not mixing container mutation and value copying, pop_front() returns void.

In a companion file, there's a type called concurrent::unconditional_pop, which allows one to ensure through RAII that the head element of the queue will be popped upon exit from the current scope.

The companion file error.hh defines the exceptions that arise from use of the function two_lock_queue::interrupt(), used to unblock threads waiting for access to the head of the queue.

Take a look at the code and let me know if you need more explanation as to how to use it.

Answer 10

The best way to do this is to use a container that is internally synchronized. TBB and Microsoft's concurrent_queue do this. Anthony Williams also has a good implementation on his blog here

Answer 11

Others have already suggested lock-free alternatives, so I'll answer as if you were stuck using locks...

When you modify a list, existing iterators can become invalidated because they no longer point to valid memory (the list automagically reallocates more memory when it needs to grow). To prevent invalidated iterators, you could make the producer block on a mutex while your consumer traverses the list, but that would be needless waiting for the producer.

Life would be easier if you used a queue instead of a list, and have your consumer use a synchronized queue<Info>::pop_front() call instead of iterators that can be invalidated behind your back. If your consumer really needs to gobble chunks of Info at a time, then use a condition variable that'll make your consumer block until queue.size() >= minimum.

The Boost library has a nice portable implementation of condition variables (that even works with older versions of Windows), as well as the usual threading library stuff.

For a producer-consumer queue that uses (old-fashioned) locking, check out the BlockingQueue template class of the ZThreads library. I have not used ZThreads myself, being worried about lack of recent updates, and because it didn't seem to be widely used. However, I have used it as inspiration for rolling my own thread-safe producer-consumer queue (before I learned about lock-free queues and TBB).

A lock-free queue/stack library seems to be in the Boost review queue. Let's hope we see a new Boost.Lockfree in the near future! :)

If there's interest, I can write up an example of a blocking queue that uses std::queue and Boost thread locking.

EDIT:

The blog referenced by Rick's answer already has a blocking queue example that uses std::queue and Boost condvars. If your consumer needs to gobble chunks, you can extend the example as follows:

void wait_for_data(size_t how_many)
    {
        boost::mutex::scoped_lock lock(the_mutex);
        while(the_queue.size() < how_many)
        {
            the_condition_variable.wait(lock);
        }
    }

You may also want to tweak it to allow time-outs and cancellations.

You mentioned that speed was a concern. If your Infos are heavyweight, you should consider passing them around by shared_ptr. You can also try making your Infos fixed size and use a memory pool (which can be much faster than the heap).