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    <p>Here's a possible solution to measure the average of all previously finished tasks. After each task finishes, an <code>Action&lt;T&gt;</code> is called where you could summarize all times and divide it by the total tasks finished. This is however just the current state and has no way to predict any future tasks / averages. (As others mentioned, this is quite difficult)</p> <p>However: You'll have to measure if it fits for your problem because there is a possibility for lock contention on both the method level declared variables.</p> <pre><code> static void ComputeParallelForWithTLS() { var collection = new List&lt;int&gt;() { 1000, 2000, 3000, 4000 }; // values used as sleep parameter var sync = new object(); TimeSpan averageTime = new TimeSpan(); int amountOfItemsDone = 0; // referenced by the TPL, increment it with lock / interlocked.increment Parallel.For(0, collection.Count, () =&gt; new TimeSpan(), (i, loopState, tlData) =&gt; { var sw = Stopwatch.StartNew(); DoWork(collection, i); sw.Stop(); return sw.Elapsed; }, threadLocalData =&gt; // Called each time a task finishes { lock (sync) { averageTime += threadLocalData; // add time used for this task to the total. } Interlocked.Increment(ref amountOfItemsDone); // increment the tasks done Console.WriteLine(averageTime.TotalMilliseconds / amountOfItemsDone + ms."); /*print out the average for all done tasks so far. For an estimation, multiply with the remaining items.*/ }); } static void DoWork(List&lt;int&gt; items, int current) { System.Threading.Thread.Sleep(items[current]); } </code></pre>
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    1. COThis is a really bad implementation with regard to performance as each thread will lock and have to wait for all others to access the shared variable, just to show a progress indicator. This approach is especially bad if the work is divided into many small chunks and partitioned among many different threads.
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    2. CO@Niclas While I agree that access to shared variables comes with a price, lock contention only happens after each task has finished its work (And only IF two or more tasks finish at the same time). So you can't broadly state that this will be a problem. You'd have to measure in your exact use case.
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    3. COYes, you are completely right. Perhaps I was a bit harsh when I said it was a really bad implementation. However it is a risky implementation since you don't control the division of tasks and threading yourself. Therefore it could completely kill performance, or it could not alter it at all and there is really no way to be sure if you have a dynamic problem that could change at runtime. I wouldn't recommend this implementation without more knowledge of the problem at hand.
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