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Three of the thread pool s features per-logical-processor queues, LIFO ordering, and stealing from the end of the queue share a single goal: working efficiently with CPU caches. When possible, you want a task to be executed on the same logical processor that generated the work because that logical processor s cache probably already contains a lot of the information relating to the task. Handling the task on a different logical processor would mean shuffling data out of the originating logical processor and into the one running the task. That s why each logical processor has its own queue, and new tasks are allocated to the queue of the logical processor that creates them. The rationale behind LIFO ordering is that the most recently created tasks are the ones most likely to have associated data still in the cache, so the average throughput will be better if we handle those first. One reason work stealing between CPUs happens from the back end of the queue is that when stealing work from another logical processor you want to pick the item that is least likely to still have data sitting in the other logical processor s cache, to minimize the amount of data that may need to be moved. So in that case, the oldest item is the best bet. Another benefit of this is that it can reduce contention queues can be constructed in such a way that different CPUs can access opposite ends of the queue simultaneously.

The examples we ve seen so far simply perform work and return no results. But a task can produce a result.

The Task<TResult> class derives from Task and adds a Result property which, once the task is complete, contains the result produced by the task. Task<TResult> represents a concept known in some concurrent programming literature as a future it represents some work that will produce a result at some point. The TaskFactory.StartNew method we ve already used can create either kind of task it has overloads that accept methods that return a result. (So you can pass a Func<TResult> or Func<object, TResult>, instead of the Action or Action<object> passed in the previous examples.) These overloads return a Task<TResult>. (Alternatively, you can call StartNew on the Task<TResult>.Factory static property.) You can start a Task<TResult> and then call Wait to wait for the result, or you can read the Result property, which will call Wait for you if the result is not yet available. But blocking until the task is complete may not be especially useful it s just a very roundabout way of invoking the code synchronously. In fact, you might sometimes want to do this you might create multiple child tasks and then wait for all of them to complete, and you d be able to take advantage of the TPL s common exception-handling framework to manage any errors. However, it s often useful to be able to provide some sort of callback method to be invoked once the task completes, rather than blocking. You can do this with a continuation.

The contents of the named.conf file are still commented with the hash symbols and you need to uncomment them so that named can read the commands. After those changes, the named.conf contents should look like Listing 11-8.

7. Each activity within the workflow is processed in this case, the ExecuteCode handler of each Code activity. 8. Sub Main completes.

A continuation is a task that gets invoked when another tasks completes. The Task class provides a ContinueWith method that lets you provide the code for that continuation task. It requires a delegate that takes as its single argument the task that just completed. ContinueWith offers overloads that allow the delegate to return a value (in which case the continuation task will be another Task<TResult>), or not to return a value (in which case the continuation task will just be a Task). ContinueWith returns the Task object that represents the continuation. So you can string these things together:

static void Main(string[] args) { Task t = Task.Factory.StartNew(() => Go("One", 100)) .ContinueWith(t1 => Go("Two", 500)) .ContinueWith(t2 => Go("Three", 200)); t.Wait(); }

Listing 11-8. The named.conf File # Use with the following in named.conf, adjusting the allow list as needed: key "rndckey" { algorithm hmac-md5; secret "9mt/YqgRTHjiA2H924sfyg=="; }; controls { inet 127.0.0.1 port 953 allow { 127.0.0.1; } keys { "rndckey"; }; }; # End of named.conf Save the file and you are done.

This will execute the three tasks one after another. Notice that the t variable here refers to the third task the final continuation. So t.Wait() will wait until all the tasks are complete it doesn t need to wait for the first two because the final task can t even

In case you ve come across continuations in the sense meant by languages such as Scheme that offer call with current continuation, be aware that this is not the same idea. There s a tenuous connection in the sense that both represent the ability to continue some work sometime later, but they re really quite different.