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public class SharedQueue3 { class Node { Object task; Node next; Node(Object task) {thistask = task; next = null;}
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private Node head = new Node(null); private Node last = head; private Object putLock = new Object(); private Object takeLock = new Object(); public void put(Object task) { synchronized(putLock) { assert task != null: "Cannot insert null task"; Node p = new Node(task); lastnext = p; last = p; } } public Object take() { Object task = null; synchronized(takeLock) { if (!isEmpty()) { Node first = headnext; task = firsttask; firsttask = null; head = first; } } return task; } }
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Concurrency-control protocols using nested locks
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The approach shown in Fig 539 isn't as easy to apply to a block on empty queue, however First of all, the wait, notify, and notifyAll methods on an object can only be invoked within a block synchronized on that object Also, if we have optimized the invocations of notify as described previously, then w, the count of waiting threads, is accessed in both put and take Therefore, we use putLock both to protect w and to serve as the lock on which a taking thread blocks when the queue is empty Code is shown in Fig 540 Notice that putLockwait() in get will release only the lock on putLock, so a blocked thread will continue to block other takers from the outer block synchronized on takeLock This is okay for this particular problem This scheme continues to allow putters and takers to execute concurrently; the only exception being when the queue is empty
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Figure 540 Blocking queue with multiple locks to allow concurrent put and take on a nonempty queue
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pubic class SharedQueue4 { class Node { Object task; Node next; Node(Object task) {thistask = task; next = null;} Node head = new Node(null); Node last = head; int w; Object putLock = new Object(); Object takeLock = new Object();
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private private private private private
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public void put(0bject task) { synchronized(putLock) { assert task != null: "Cannot insert null task"; Node p = new Node(task); lastnext = p; last = p; if(w>0){putLocknotify();} } } public Object take() { Object task = null; synchronized(takeLock) { //returns first task in queue, waits if queue is empty while (isEmpty()) { try{synchronized(putLock){w++; putLockwait();w--;} } catch(InterruptedException error){assert false;}} { Node first = headnext; task = firsttask; firsttask = null; head = first;
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} } return task; } private boolean isEmpty() {return headnext == null;} }
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Another issue to note is that this solution has nested synchronized blocks in both take and put Nested synchronized blocks should always be examined for potential deadlocks In this case, there will be no deadlock because put only acquires one lock, putLock More generally, we would define a partial order over all the locks and ensure that the locks are always acquired in an order consistent with our partial order For example, here, we could define takeLock < putLock and make sure that the synchronized blocks are entered in a way that respects that partial order As mentioned earlier, several Java based implementations of queues are included in Java 2 15 in the javautilconcurrent package, some based on the simple strategies discussed here and some based on more complex strategies that provide additional flexibility and performance
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Distributed shared queues
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A centralized shared queue may cause a hot spot, indicating that performance might be improved by a more distributed implementation As an example, we will develop a simple package to support fork/join programs using a pool of threads and a distributed task queue in the underlying implementation The package is a much simplified version of the FJTask package [Lea00b], which in
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turn uses ideas from [BJK 96 + ] The idea is to create a fixed pool of threads to execute the tasks that are dynamically created as the program executes Instead of a single central task queue, we associate a nonblocking queue with each thread When a thread generates a new task, it is placed in its own queue When a thread is able to execute a new task, it first tries to obtain a task from its own queue If its own queue is empty, it randomly chooses another thread and attempts to steal a task from that thread's queue and continues checking the other queues until a task is found (In [BJK 96 + ], this is called random work stealing)
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A thread terminates when it receives a poison pill task For the fork/join programs we have in mind, this approach has been shown to work well when threads remove tasks from their own queue in LIFO (last in, first out) order and from other queues in FIFO (first in, first out) order Therefore, we will add to the ADT an operation that removes the last element, to be used by threads to remove tasks from their own queues The implementation can then be similar to Fig 540, but with an additional method takeLast for the added operation The result is shown in Fig 541 The remainder of the package comprises three classes
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Task is an abstract class Applications extend it and override its run method to indicate the functionality of a task in the computation Methods offered by the class include fork and
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