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ThreadPool and methods with while(true) loops?

ThreadPool utilizes recycling of threads for optimal performance over using multiple of the Thread class. However, how does this apply to processing methods with while loops inside of the ThreadPool?
As an example, if we were to apply a thread in the ThreadPool to a client that has connected to a TCP server, that client would need a while loop to keep checking for incoming data. The loop can be exited to disconnect the client, but only if the server closes or if the client demands a disconnection.
If that is the case, then how would having a ThreadPool help when masses of clients connect? Either way the same amount of memory is used if the clients stay connected. If they stay connected, then the threads cannot be recycled. If so, then ThreadPool would not help much until a client disconnects and opens up a thread to recycle.
On the other hand it was suggested to me to use the Network.BeginReceive and NetworkStream.EndReceive asynchronous methods to avoid threads all together to save RAM usage and CPU usage. Is this true or not?

Either way the same amount of memory is used if the clients stay
connected.
So far this is true. It's up to your app to decide how much state it needs to keep per client.
If they stay connected, then the threads cannot be recycled. If so,
then ThreadPool would not help much until a client disconnects and
opens up a thread to recycle.
This is untrue, because it assumes that all interesting operations performed by these threads are synchronous. This is a naive mode of operation, and in fact real world code is asynchronous: a thread makes a call to request an action and is then free to do other things. When a result is made available as a result of that action, some thread looking for other things to do will run the code that acts on the result.
On the other hand it was suggested to me to use the
Network.BeginReceive and NetworkStream.EndReceive asynchronous methods
to avoid threads all together to save RAM usage and CPU usage. Is this
true or not?
As explained above, async methods like these will allow you to service a potentially very large number of clients with only a small number of worker threads -- but by itself it will do nothing to either help or hurt the memory situation.

You are correct. Slow blocking codes can cause poor performances both on the client-side as well as server-side. You can run slow work on a separate thread and that might work well enough on the client-side but may not help on the server-side. Having blocking methods in the server can diminish the overall performance of the server because it can lead to a situation where your server has a large no of threads running and all blocked. So, even simple request might end up taking a long time. It is better to use asynchronous APIs if they are available for slow running tasks just like the situation you are in. (Note: even if the asynchronous operations are not available, you can implement one by implementing a custom awaiter class) This is better for the clients as well as servers. The main point of asynchronous code is to reduce the no of threads. Because servers can have larger no of requests in progress simultaneously because reducing no of threads to handle a particular no of clients can improve scalability.
If you dont need to have more control over the threads or the thread-pool you can go with asynchronous approach.
Also, each thread takes 1 MB space on the heap. So, asynchronous methods will definitely help reduce memory usage. However, I think the nature of the work you have described here is going to take pretty much the same amount of time in multi-threaded as well as asynchronous approach.

Threads eating into CPU performance

I have a console application(c#) where I have to call various third party API's and collect data. This I have to do simultaneously for different users. I am using threads for it. But as the number of users are increasing this service is eating into the CPU performance. It is affecting other processes. Is there a way we can use threads for parallel processing but do not affect the CPU performance in a huge way.

I assume from your question that you're creating threads manually, and so the quick way to answer this is to suggest that you use an API like the Task Parallel Library, because this will take an arbitrary number of tasks and try to use a sensible number of threads to process them - so given 500 API requests, it would limit itself to just a few threads.
However, to answer in more detail: the typical reason that you would see this problem is that code is creating too many threads. Threads are not free resources - they are expensive.
A made up example based on your question might be this:
you have 5 3rd party APIs that you need to call, and each is going to return ~1MB of data per user
you call each API on a separate background thread, for each user
you have 100 users
you therefore have created 500 threads in total, each of which is waiting on data from the network
The problem here is that there are 500 threads the program is trying to manage, and they are all waiting on the slowest piece of the system - the network.
More simply, we are trying to download 500 pieces of data at once (which in this example would mean everything finishes slowly), rather than downloading them one at a time so that individual items will finish earlier. Because each thread will be doing nothing (just waiting for the network), the CPU will switch between idle threads continually. As you increase your number of users, the number of threads increases - which increases the CPU usage just for switch between threads, even though each thread is actually downloading more slowly. This is (approximately) why you'll be seeing slower performance as your user count goes up.
A better example would be to take the same scenario and use just one background thread:
you have 5 3rd party APIs that you need to call, and each is going to return ~1MB of data per user
each API call is put into a queue and the queue is processed by a single thread
you have 100 users
you therefore have 1 thread running in the background which is using the full available bandwidth of the network for each request
In this example, your CPU usage will be pretty consistent - no matter how many users you have, there is only one background thread running, so context switching is minimised. Each individual API call runs at the maximum rate of the network card and so finishes as quickly as possible.
The reality is that one thread is probably not enough: a single request is unlikely to saturate the network, as there will be limiting factors elsewhere. But this is something you can tune later: maybe 2 or 3 threads would be more performant, but 4 threads would be slower again. The general rule when threading is to start small and work up, not to create a thread for each piece of work.

First, run a profiler and checkout some refactoring tools to see if you can perform code optimization to resolve the issue. If your application is still overloading the server then setup or purchase load balancing. In the meantime, if you are running the latest OS's you could try setting a hacky CPU rate limit...however, that may not work for the needs you described.

Thread.Sleep() usage to Prevent Server Overload

I wrote some code that mass imports a high volume of users into AD. To refrain from overloading the server, I put a thread.sleep() in the code, executed at every iteration.
Is this a good use of the method, or is there a better alternative (.NET 4.0 applies here)?
Does Thread.Sleep() even aid in performance? What is the cost and performance impact of sleeping a thread?

The Thread.Sleep() method will just put the thread in a pause state for the specified amount of time. I could tell you there are 3 different ways to achieve the same Sleep() calling the method from three different Types. They all have different features. Anyway most important, if you use Sleep() on the main UI thread, it will stop processing messages during that pause and the GUI will look locked. You need to use a BackgroundWorker to run the job you need to sleep.
My opinion is to use the Thread.Sleep() method and just follow my previous advice. In your specific case I guess you'll have no issues. If you put some efforts looking for the same exact topic on SO, I'm sure you'll find much better explanations about what I just summarized before.
If you have no way to receive a feedback from the called service, like it would happen on a typical event driven system (talking in abstract..we could also say callback or any information to understand how the service is affected by your call), the Sleep may be the way to go.

I think that Thread.Sleep is one way to handle this; #cHao is correct that using a timer would allow you to do this in another fashion. Essentially, you're trying to cut down number of commands sent to the AD server over a period of time.
In using timers, you're going to need to devise a way to detect trouble (that's more intuitive than a try/catch). For instance, if your server starts stalling and responding slower, you're going to continue stacking commands that the server can't handle (which may cascade in other errors).
When working with AD I've seen the Domain Controller freak out when too many commands come in (similar to a DOS attack) and bring the server to a crawl or crash. I think by using the sleep method you're creating a manageable and measurable flow.
In this instance, using a thread with a low priority may slow it down, but not to any controllable level. The thread priority will only be a factor on the machine sending the commands, not to the server having to process them.
Hope this helps; cheers!

If what you want is not overload the server you can just reduce the priority of the thread.
Thread.Sleep() do not consume any resources. However, the correct way to do this is set the priority of thread to a value below than Normal: Thread.Current.Priority = ThreadPriority.Lowest for example.
Thread.Sleep is not that "evil, do not do it ever", but maybe (just maybe) the fact that you need to use it reflects some lack on solution design. But this is not a rule at all.
Personally I never find a situation where I have to use Thread.Sleep.
Right now I'm working on an ASP.NET MVC application that uses a background thread to load a lot of data from database into a memory cache and after that write some data to the database.
The only feature I have used to prevent this thread to eat all my webserver and db processors was reduce the thread priority to the Lowest level. That thread will get about to 35 minutes to conclude all the operations instead of 7 minutes if a use a Normal priority thread. By the end of process, thread will have done about 230k selects to the database server, but this do not has affected my database or webserver performance in a perceptive way for the user.
tip: remember to set the priority back to Normal if you are using a thread from ThreadPool.
Here you can read about Thread.Priority:
http://msdn.microsoft.com/en-us/library/system.threading.thread.priority.aspx
Here a good article about why not use Thread.Sleep in production environment:
http://msmvps.com/blogs/peterritchie/archive/2007/04/26/thread-sleep-is-a-sign-of-a-poorly-designed-program.aspx
EDIT Like others said here, maybe just reduce your thread priority will not prevent the thread to send a large number of commands/data to AD. Maybe you'll get better results if you rethink all the thing and use timers or something like that. I personally think that reduce priority could resolve your problem, although I think you need to do some tests using your data to see what happens to your server and other servers involved in the process.

You could schedule the thread at BelowNormal priority instead. That said, that could potentially lead to your task never running if something else overloads the server. (Assuming Windows scheduling works the way the documentation on scheduling threads mentions for "some operating systems".)
That said, you said you're moving data into AD. If it's over the nework, it's entirely possible the CPU impact of your code will be negligible compared to I/O and processing on the AD side.

I don't see any issue with it except that during the time you put the thread to sleep then that thread will not be responsive. If that is your main thread then your GUI will become non responsive. If it is a background thread then you won't be able to communicate with it (eg to cancel it). If the time you sleep is short then it shouldn't matter.
I don't think reducing the priority of the thread will help as 1) your code might not even be running on the server and 2) most of the work being done by the server is probably not going to be on your thread anyway.

Thread.sleep does not aid performance (unless your thread has to wait for some resource). It incurs at least some overhead, and the amount of time that you sleep for is not guaranteed. The OS can decide to have your Thread sleep longer than the amount of time you specify.
As such, it would make more sense to do a significant batch of work between calls to Thread.Sleep().

Thread.Sleep() is a CPU-less wait state. Its overhead should be pretty minimal. If execute Thread.Sleep(0), you don't [necessarily] sleep, but you voluntarily surrender your time slice so the scheduler can let lower priority thread run.
You can also lower your thread's priority by setting Thread.Priority.
Another way of throttling your task is to use a Timer:
// instantiate a timer that 'ticks' 10 times per second (your ideal rate might be different)
Timer timer = new Timer( ImportUserIntoActiveDirectory , null , 0 , 100 ) ;
where ImportUserIntoActiveDirectory is an event handler that will import just user into AD:
private void ImportUserIntoActiveDirectory( object state )
{
// import just one user into AD
return
}
This lets you dial things in. The event handler is called on thread pool worker threads, so you don't tie up your primary thread. Let the OS do the work for you: all you do is decide on your target transaction rate.

CPU usage of worker processes on a multicore server

The setup
We've written a Windows service, which fires off separate worker processes to perform various CPU-intensive tasks. The server and workers communicate via IPC named pipes.
At present, we create the workers via a simple Process.Start() call.
When we run up a number of workers on a fairly low-spec'd dual core server VM, Task Manager tells us that each worker uses approximately 2 - 3% CPU.
However (this is thing that's confusing us), when we perform the same test on a very powerful eight-core server, we still see each worker process using 2 - 3% CPU. Now, because there is more CPU 'power' available, I would expect to see each worker using a much smaller percentage of CPU.
This also means that on the low-powered server we hit 100% CPU after 30ish worker processes are created. But on the high-powered CPU, we hit the same limit after the same number of workers. We would expect to be able to run far more workers.
The issue
So, I have a couple of questions:
Are we misunderstanding the values that Task Manager is telling us? The CPU % value is the amount of CPU time consumed across all cores? If so, why is it the same on vastly different hardware?
Should we be doing something special / different to properly distribute our worker processes across multiple cores? At the moment, the processes have the default processor affinity (so they are able to run on any core).
Any help, advice, links, would be greatly appreciated.
Some extra info for people who have left comments:
I didn't mention it initially as I didn't necessarily want to add extra complexity to my question, but our worker processes are doing video transcoding of live video streams. As such, no worker ever 'completes' its task - it simply works for as long as a client is connected.
Essentially:
A client connects to the server
The server fires off a worker process which connects to a remote video stream
When video is received from said video stream, the worker transcodes it and sends the transcoded video back to the client.
Not sure if this helps with any other suggestions? Thanks for all the comments so far.

The fact that the processes are using 2-3% of the CPU suggests that your process is not CPU bound, but rather is likely to be IO bound or have some other limitation.
The IO on the 2 core server VM is probably quite a bit slower than your 8 core server, which, in turn, throttles the behavior there. This may be why the apparent CPU usage is the same, though I would suspect that the full server likely finishes the task sooner overall.

Launching multiple tasks from a WCF service

I need to optimize a WCF service... it's quite a complex thing. My problem this time has to do with tasks (Task Parallel Library, .NET 4.0). What happens is that I launch several tasks when the service is invoked (using Task.Factory.StartNew) and then wait for them to finish:
Task.WaitAll(task1, task2, task3, task4, task5, task6);
Ok... what I see, and don't like, is that on the first call (sometimes the first 2-3 calls, if made quickly one after another), the final task starts much later than the others (I am looking at a case where it started 0.5 seconds after the others). I tried calling
ThreadPool.SetMinThreads(12*Environment.ProcessorCount, 20);
at the beginning of my service, but it doesn't seem to help.
The tasks are all database-related: I'm reading from multiple databases and it has to take as little time as possible.
Any idea why the last task is taking so long? Is there something I can do about it?
Alternatively, should I use the thread pool directly? As it happens, in one case I'm looking at, one task had already ended before the last one started - I would had saved 0.2 seconds if I had reused that thread instead of waiting for a new one to be created. However, I can not be sure that that task will always end so quickly, so I can't put both requests in the same task.
[Edit] The OS is Windows Server 2003, so there should be no connection limit. Also, it is hosted in IIS - I don't know if I should create regular threads or using the thread pool - which is the preferred version?
[Edit] I've also tried using Task.Factory.StartNew(action, TaskCreationOptions.LongRunning); - it doesn't help, the last task still starts much later (around half a second later) than the rest.
[Edit] MSDN1 says:
The thread pool has a built-in delay
(half a second in the .NET Framework
version 2.0) before starting new idle
threads. If your application
periodically starts many tasks in a
short time, a small increase in the
number of idle threads can produce a
significant increase in throughput.
Setting the number of idle threads too
high consumes system resources
needlessly.
However, as I said, I'm already calling SetMinThreads and it doesn't help.

I have had problems myself with delays in thread startup when using the (.Net 4.0) Task-object. So for time-critical stuff I now use dedicated threads (... again, as that is what I was doing before .Net 4.0.)
The purpose of a thread pool is to avoid the operative system cost of starting and stopping threads. The threads are simply being reused. This is a common model found in for example internet servers. The advantage is that they can respond quicker.
I've written many applications where I implement my own threadpool by having dedicated threads picking up tasks from a task queue. Note however that this most often required locking that can cause delays/bottlenecks. This depends on your design; are the tasks small then there would be a lot of locking and it might be faster to trade some CPU in for less locking: http://www.boyet.com/Articles/LockfreeStack.html
SmartThreadPool is a replacement/extension of the .Net thread pool. As you can see in this link it has a nice GUI to do some testing: http://www.codeproject.com/KB/threads/smartthreadpool.aspx
In the end it depends on what you need, but for high performance I recommend implementing your own thread pool. If you experience a lot of thread idling then it could be beneficial to increase the number of threads (beyond the recommended cpucount*2). This is actually how HyperThreading works inside the CPU - using "idle" time while doing operations to do other operations.
Note that .Net has a built-in limit of 25 threads per process (ie. for all WCF-calls you receive simultaneously). This limit is independent and overrides the ThreadPool setting. It can be increased, but it requires some magic: http://www.csharpfriends.com/Articles/getArticle.aspx?articleID=201

Following from my prior question (yep, should have been a Q against original message - apologies):
Why do you feel that creating 12 threads for each processor core in your machine will in some way speed-up your server's ability to create worker threads? All you're doing is slowing your server down!
As per MSDN do
As per the MSDN docs: "You can use the SetMinThreads method to increase the minimum number of threads. However, unnecessarily increasing these values can cause performance problems. If too many tasks start at the same time, all of them might appear to be slow. In most cases, the thread pool will perform better with its own algorith for allocating threads. Reducing the minimum to less than the number of processors can also hurt performance.".
Issues like this are usually caused by bumping into limits or contention on a shared resource.
In your case, I am guessing that your last task(s) is/are blocking while they wait for a connection to the DB server to come available or for the DB to respond. Remember - if your invocation kicks off 5-6 other tasks then your machine is going to have to create and open numerous DB connections and is going to kick the DB with, potentially, a lot of work. If your WCF server and/or your DB server are cold, then your first few invocations are going to be slower until the machine's caches etc., are populated.
Have you tried adding a little tracing/logging using the stopwatch to time how long it takes for your tasks to connect to the DB server and then execute their operations?
You may find that reducing the number of concurrent tasks you kick off actually speeds things up. Try spawning 3 tasks at a time, waiting for them to complete and then spawn the next 3.

When you call Task.Factory.StartNew, it uses a TaskScheduler to map those tasks into actual work items.
In your case, it sounds like one of your Tasks is delaying occasionally while the OS spins up a new Thread for the work item. You could, potentially, build a custom TaskScheduler which already contained six threads in a wait state, and explicitly used them for these six tasks. This would allow you to have complete control over how those initial tasks were created and started.
That being said, I suspect there is something else at play here... You mentioned that using TaskCreationOptions.LongRunning demonstrates the same behavior. This suggests that there is some other factor at play causing this half second delay. The reason I suspect this is due to the nature of TaskCreationOptions.LongRunning - when using the default TaskScheduler (LongRunning is a hint used by the TaskScheduler class), starting a task with TaskCreationOptions.LongRunning actually creates an entirely new (non-ThreadPool) thread for that Task. If creating 6 tasks, all with TaskCreationOptions.LongRunning, demonstrates the same behavior, you've pretty much guaranteed that the problem is NOT the default TaskScheduler, since this is going to always spin up 6 threads manually.
I'd recommend running your code through a performance profiler, and potentially the Concurrency Visualizer in VS 2010. This should help you determine exactly what is causing the half second delay.

What is the OS? If you are not running the server versions of windows, there is a connection limit. Your many threads are probably being serialized because of the connection limit.
Also, I have not used the task parallel library yet, but my limited experience is that new threads are cheap to make in the context of networking.

These articles might explain the problem you're having:
http://blogs.msdn.com/b/wenlong/archive/2010/02/11/why-are-wcf-responses-slow-and-setminthreads-does-not-work.aspx
http://blogs.msdn.com/b/wenlong/archive/2010/02/11/why-does-wcf-become-slow-after-being-idle-for-15-seconds.aspx
seeing as you're using .Net 4, the first article probably doesn't apply, but as the second article points out the ThreadPool terminates idle threads after 15 seconds which might explain the problem you're having and offers a simple (though a little hacky) solution to get around it.
Whether or not you should be using the ThreadPool directly wouldn't make any difference as I suspect the task library is using it for you underneath anyway.
One third-party library we have been using for a while might help you here - Smart Thread Pool. You still get the same benefits of using the task libraries, in that you can have the return values from the threads and get any exception information from them too.
Also, you can instantiate threadpools so that when you have multiple places each needing a threadpool (so that a low priority process doesn't start eating into the quota of some high priority process) and oh yeah you can set the priority of the threads in the pool too which you can't do with the standard ThreadPool where all the threads are background threads.
You can find plenty of info on the codeplex page, I've also got a post which highlights some of the key differences:
http://theburningmonk.com/2010/03/threading-introducing-smartthreadpool/
Just on a side note, for tasks like the one you've mentioned, which might take some time to return, you probably shouldn't be using the threadpool anyway. It's recommended that we should avoid using the threadpool for any blocking tasks like that because it hogs up the threadpool which is used by all sorts of things by the framework classes, like handling timer events, etc. etc. (not to mention handling incoming WCF requests!). I feel like I'm spamming here but here's some of the info I've gathered around the use of the threadpool and some useful links at the bottom:
http://theburningmonk.com/2010/03/threading-using-the-threadpool-vs-creating-your-own-threads/
well, hope this helps!