![]() ![]() NET 4.0 should have a whole bunch of properly implemented thread-safe collections, but that's still nearly a year away unfortunately. So as you can't safely dequeue anything from a synchronized queue, I wouldn't bother with it and would just use manual locking. The queue lock has to be taken when irqs are disabled as the request function can be called in interrupt context. checking the count and dequeueing the item) as follows: object item You can safely write this using a manual lock around the entire unit-of-work (i.e. This function is an extension to the standard. To avoid errors when threads use MSMPIWaitsomeinterruptible in multi-threaded applications, all threads must acquire the global lock before they call MPI functions. the next line will throw an InvalidOperationException. Applications should normally allocate the queue structure on the stack each time they acquire the lock. at this point another thread dequeues the last item, and then This occurs because each individual operation is thread-safe, but the value of Count can change between when you query it and when you use the value. There's a classic race condition with a synchronized queue, shown below where you check the Count to see if it is safe to dequeue, but then the Dequeue method throws an exception indicating the queue is empty. There's a major problem with the Synchronized methods in the old collection library, in that they synchronize at too low a level of granularity (per method rather than per unit-of-work). If calling Synchronized() doesn't ensure thread-safety what's the point of it? Am I missing something here? Or is it recommended to use Queue.Synchronized like this: Queue.Synchronized(myQueue).whatever_i_want_to_do() įrom reading the MSDN docs it says I should use Queue.Synchronized to make it thread-safe, but then it gives an example using a lock object. Would it be better to use a lock object like this: lock(myLockObject) This article provides a pseudo-code for the lock-free queue algorithm, which is also very small, so it can be easily implemented by various programming languages.I have a Queue object that I need to ensure is thread-safe. Most of the lock-free algorithms are implemented through CAS operations. This implementation employs an efficient non-blocking algorithm based on one described in Simple, Fast, and Practical Non-Blocking and Blocking Concurrent Queue Algorithms by Maged M. It is only worth mentioning that Java’s ConcurrentLinkedQueue is based on this algorithm: This article has been cited nearly 1000 times. Scott’s 1996 paper Simple, Fast, and Practical Non-Blocking and BlockingĬoncurrent Queue Algorithms, which reviews some implementations of concurrent queues and their limitations, proposes a very simple implementation of lock-free queue, and also provides a two-lock queue algorithm on specific machines such as those without CAS instructions. Speaking of lock-free queue algorithms, we have to mention Maged M. The code base can be found on github: smallnest/queue lock-free queue algorithm This article introduces some background knowledge of the lock-free queue algorithm, and implements three concurrent queues and provides the results of performance tests. before getting the data from the Queue, the subscribe function first executes lock.acquire(), then gets the data with data. However, in some cases, by implementing lock-free algorithm, we can further improve the performance of concurrent queues. The first publisher Process publishes data to the Queue, the second subscriber Process reads the data from the Queue and logs. Generally, the queue is implemented through pointers and only operates at the head and tail of the queue, so the critical area protected by this out-of-exclusion lock does not have a very complex execution logic and the critical area is processed quickly, so in general the efficiency of the queue is already very high by implementing the out-of-exclusion lock. In a concurrent environment using queues, it is necessary to take into account the multi-threaded (multi-threaded) concurrent read and write problems, there may be multiple write (queue) operation threads, while there may also be multiple threads read operation threads, in this case, we want to ensure that the data is not lost, not duplicated, but also to ensure that the function of the queue remains unchanged, that is, the first-in-first-out logic, as long as there is data, you can get out of the column.Īdmittedly, concurrent access to the queue can be achieved through an out-of-exclusion lock. The end that performs the insert operation is called the tail and the end that performs the delete operation is called the header. Like the stack data structure, a queue is a linear table with restricted operations. A queue is a very common data structure that allows only outgoing ( dequeue) operations at the front end of a table ( head) and incoming ( enqueue) operations at the back end of a table ( tail). ![]()
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