I have been reading a bit about async/await vs ThreadPool vs Threads, and I have to admit, I'm not fully clear on the details. There is one specific question that I think I have the answer to, but I can't say for sure.
I am also aware of the many many questions on SO and elsewhere, where these questiosn are being discussed and explained. I have read a fair few here on SO, but I haven't found a clear answer, or at least as clear as I'd like.
What I gathered:
Using async/await in an I/O operation, will make that thread available to use for other things, while the I/O operation continues elsewhere
For a server application, this means higher throughput etc
However, a collegue said something like this:
that using a ThreadPool to execute the same I/O operation would behave almost the same as async/await
that when the ThreadPool thread "hands over" the I/O operation to the OS, it might wait for the answer, but that it won't matter much, since there is no work done on the CPU (the thread is waiting), and thus, the ThreadPool/OS/framework can use or spawn another thread to do some other work.
Since the threadpool has a limit of some 32000+ threads, it wouldn't matter much, since it could just use more threads. The cost for a thread is very small, just a few bytes of memory
So, what I am asking is:
Does the Thread from a ThreadPool block in I/O operations?
Does it matter if it does, since the OS/framework/Threadpool can just use another thread from the pool if needed for some other work?
Bottom line: I/O operations with async/await or ThreadPool; does it matter for efficiency and throughput?
Please note that I am not discussing the client-side of things, just from a server perspective.
And sorry in advance if I missed an exact answer to this, I have looked =)
The real issue is not "thread pool vs. async/await", it's synchronous I/O vs. asynchronous I/O. [1]
On Windows, threads are relatively expensive objects -- a thread has a lot of OS bookkeeping associated with it, not to mention 1 MB of preallocated stack space. This puts a fairly low cap on how many threads the system will even support, and even when you don't hit that cap, context switching between all those threads is not cheap either. That "32,000 threads" limit is a strictly theoretical one, and highly optimistic about how many threads you can have and still be responsive! [2]
Enter asynchronous I/O, which is optimized to use only as many threads as necessary (usually some conservative multiple of the number of physical processor cores in the system), ideally never even creating new threads beyond the initial batch. These threads are dedicated to handling completed I/O operations by removing them from a queue (known as a completion port). While an asynchronous operation is in progress, no thread is dedicated to it at all, not even as an item on a wait list (Stephen Cleary has a nice blog post about it that explains this in more detail). Not much imagination is needed to think about what's more efficient:
A few thousand individual threads that each wait on a particular operation, which have to be woken up and switched to (and between) depending on what operation(s) completed; or
A few dozen threads (if that), each of which can handle any completed operation, so that only as many ever need to run as necessary to be responsive.
As it turns out, the latter scales much better than the former; the "thread per request" model which is common in naive server code quickly shows its limits, even when you use a thread pool to reduce the creation of new threads. Note that this was an issue long before async/await was ever a thing, and so is the solution Windows went with; async/await is just a new way of writing code to use the existing mechanisms.
Are you likely to notice a difference with only a few requests in flight at a time? No. But since async/await essentially allows you to write code that looks synchronous but has the scalability of asynchronous I/O "for free", why would you not choose to use that in favor of synchronous I/O queued to the thread pool?
[1] Turns out Stephen Cleary already wrote most of what's in this answer a few years ago. I recommend you read that as well.
[2] Here's an older post by Mark Russinovich where he actually tries to squeeze as many threads out of the system as possible -- just for fun and profit. He "only" gets to 55K on a 64-bit machine before all resources are gone, and that's with adjusting the default stack size, and without doing any actually useful work. On a modern system you could probably get more, but the real question should not be "how many threads can I have" -- if it is, you're Doing it Wrong.
Related
When working with tasks, a rule of thumb appears to be that the thread pool - typically used by e.g. invoking Task.Run(), or Parallel.Invoke() - should be used for relatively short operations. When working with long running operations, we are supposed to use the TaskCreationOptions.LongRunning flag in order to - as far as I understand it - avoid clogging the thread pool queue, i.e. to push work to a newly-created thread.
But what exactly is a long running operation? How long is long, in terms of time? Are there other factors besides the expected task duration to be considered when deciding whether or not to use the LongRunning, like the anticipated CPU architecture (frequency, the number of cores, ...) or the number of tasks that will be attempted to be run at once from the programmer's perspective?
For example, suppose I have 500 tasks to process in a dedicated application, each taking 10-20 seconds to complete. Should I just start all 500 tasks using Task.Run (e.g. in a loop) and then await them all, perhaps as LongRunning, while leaving the default max level of concurrency? Then again, if I set LongRunning in such case, wouldn't this create 500 new threads and actually cause a lot of overhead and higher memory usage (due to extra threads being allocated) as compared to omitting LongRunning? This is assuming that no new tasks will be scheduled for execution while these 500 are being awaited.
I would guess that the decision to set LongRunning depends on the number of requests made to the thread pool in a given time interval, and that LongRunning should only be used for tasks that are expected to take significantly longer that the majority of the thread pool-placed tasks - by definition, at most a small percentage of all tasks. In other words, this appears to be a queuing and thread pool utilization optimization problem that should likely be solved case-by-case through testing, if at all. Am I correct?
It kind of doesn't matter. The problem isn't really about time, it's about what your code is doing. If you're doing asynchronous I/O, you're only using the thread for the short amount of time between individual requests. If you're doing CPU work... well, you're using the CPU. There's no "thread-pool starvation", because the CPUs are fully utilized.
The real problem is when you're doing blocking work that doesn't use the CPU. In case like that, thread-pool starvation leads to CPU-underutilization - you said "I need the CPU for my work" and then you don't actually use it.
If you're not using blocking APIs, there's no point in using Task.Run with LongRunning. If you have to run some legacy blocking code asynchronously, using LongRunning may be a good idea. Total work time isn't as important as "how often you are doing this". If you spin up one thread based on a user clicking on a GUI, the cost is tiny compared to all the latencies already included in the act of clicking a button in the first place, and you can use LongRunning just fine to avoid the thread-pool. If you're running a loop that spawns lots of blocking tasks... stop doing that. It's a bad idea :D
For example, imagine there is no asynchronous API alternative File.Exists. So if you see that this is giving you trouble (e.g. over a faulty network connection), you'd fire it up using Task.Run - and since you're not doing CPU work, you'd use LongRunning.
In contrast, if you need to do some image manipulation that's basically 100% CPU work, it doesn't matter how long the operation takes - it's not a LongRunning thing.
And finally, the most common scenario for using LongRunning is when your "work" is actually the old-school "loop and periodically check if something should be done, do it and then loop again". Long running, but 99% of the time just blocking on some wait handle or something like that. Again, this is only useful when dealing with code that isn't CPU-bound, but that doesn't have proper asynchronous APIs. You might find something like this if you ever need to write your own SynchronizationContext, for example.
Now, how do we apply this to your example? Well, we can't, not without more information. If your code is CPU-bound, Parallel.For and friends are what you want - those ensure you only use enough threads to sature the CPUs, and it's fine to use the thread-pool for that. If it's not CPU bound... you don't really have any option besides using LongRunning if you want to run the tasks in parallel. Ideally, such work would consist of asynchronous calls you can safely invoke and await Task.WhenAll(...) from your own thread.
When working with tasks, a rule of thumb appears to be that the thread pool - typically used by e.g. invoking Task.Run(), or Parallel.Invoke() - should be used for relatively short operations. When working with long running operations, we are supposed to set the TaskCreationOptions.LongRunning to true in order to - as far as I understand it - avoid clogging the thread pool queue, i.e. to push work to a newly-created thread.
The vast majority of the time, you don't need to use LongRunning at all, because the thread pool will adjust to "losing" a thread to a long-running operation after 2 seconds.
The main problem with LongRunning is that it forces you to use the very dangerous StartNew API.
In other words, this appears to be a queuing and thread pool utilization optimization problem that should likely be solved case-by-case through testing, if at all. Am I correct?
Yes. You should never set LongRunning when first writing code. If you are seeing delays due to the thread pool injection rate, then you can carefully add LongRunning.
You should not use TaskCreationOptions.LongRunning in your case. I would use Parallel.For.
The LongRunning option is not to be used if you're going to create a lot of tasks, just like in your case. It is to be used for creating couple of tasks that will be running for a Long Time.
By the way, i never used this option in any similar scenario.
As you point out, TaskCreationOptions.LongRunning's purpose is
to allow the ThreadPool to continue to process work items even though one task is running for an extended period of time
As for when to use it:
It's not a specific length per se...You'd typically only use LongRunning if you found through performance testing that not using it was causing long delays in the processing of other work.
Source
I am currently converting a database stored procedure call to be asynchronous, leveraging async/await. Similar to the method described here.
Based on this answer, I'd like to verify that asynchronous call is actually using I/O completion ports. If it's ultimately waiting on another thread from the ThreadPool, then it is effectively defeating the purpose of converting the call.
What is the best way to verify that an I/O completion port is being used and it's not simply blocking on another thread?
Invoke WAITFOR DELAY '1:00:00' 1000 times in parallel. If far less than 1000 threads are being used, you are getting threadless IO. You should see a few dozens (which includes lots of utility threads started by runtimes and frameworks).
You can also break with the debugger and make sure that no thread is currently waiting for IO. You can tell from the stack trace. This works with any existing application.
I would create some perfmon counters and update them in the thread pool threads. Then you can watch the app being used, and see how many threads are in-use at any given time, which in turn might help you tune the number. You could also log the time each thread took, and count that too so you can see the average wait time, this would help you determine if they were getting blocked, though I think the number of threads would show that too - in that you'd see several complete at once if they were waiting on each other. Depends on the work you're doing.
I did this years ago for a web app, it was very informative to performance tuning the app.
I'm currently trying to figure what is the best way to minimize the amount of threads I use in a TCP master server, in order to maximize performance.
As I've been reading a lot recently with the new async features of C# 5.0, asynchronous does not necessarily mean multithreaded. It could mean separated in smaller chunks of finite state objects, then processed alongside other operations, by alternating. However, I don't see how this could be done in networking, since I'm basically "waiting" for input (from the client).
Therefore, I wouldn't use ReceiveAsync() for all my sockets, it would just be creating and ending threads continuously (assuming it does create threads).
Consequently, my question is more or less: what architecture can a master server take without having one "thread" per connection?
Side question for bonus coolness points: Why is having multiple threads bad, considering that having an amount of threads that is over your amount of processing cores simply makes the machine "fake" multithreading, just like any other asynchronous method would?
No, you would not necessarily be creating threads. There are two possible ways you can do async without setting up and tearing down threads all the time:
You can have a "small" number of long-lived threads, and have them sleep when there's no work to do (this means that the OS will never schedule them for execution, so the resource drain is minimal). Then, when work arrives (i.e. Async method called), wake one of them up and tell it what needs to be done. Pleased to meet you, managed thread pool.
In Windows, the most efficient mechanism for async is I/O completion ports which synchronizes access to I/O operations and allows a small number of threads to manage massive workloads.
Regarding multiple threads:
Having multiple threads is not bad for performance, if
the number of threads is not excessive
the threads do not oversaturate the CPU
If the number of threads is excessive then obviously we are taxing the OS with having to keep track of and schedule all these threads, which uses up global resources and slows it down.
If the threads are CPU-bound, then the OS will need to perform much more frequent context switches in order to maintain fairness, and context switches kill performance. In fact, with user-mode threads (which all highly scalable systems use -- think RDBMS) we make our lives harder just so we can avoid context switches.
Update:
I just found this question, which lends support to the position that you can't say how many threads are too much beforehand -- there are just too many unknown variables.
Seems like the *Async methods use IOCP (by looking at the code with Reflector).
Jon's answer is great. As for the 'side question'... See http://en.wikipedia.org/wiki/Amdahl%27s_law. Amdel's law says that serial code quickly diminishes the gains to be had from parallel code. We also know that thread coordination (scheduling, context switching, etc) is serial - so at some point more threads means there are so many serial steps that parallelization benefits are lost and you have a net negative performance. This is tricky stuff. That's why there is so much effort going into letting .NET manage threads while we define 'tasks' for the framework to decide what thread to run on. The framework can switch between tasks much more efficiently than the OS can switch between threads because the OS has a lot of extra things it needs to worry about when doing so.
Asynchronous work can be done without one-thread-per-connection or a thread pool with OS support for select or poll (and Windows supports this and it is exposed via Socket.Select). I am not sure of the performance on windows, but this is a very common idiom elsewhere.
One thread is the "pump" that manages the IO connections and monitors changes to the streams and then dispatches messages to/from other threads (conceivably 0 ... n depending upon model). Approaches with 0 or 1 additional threads may fall into the "Event Machine" category like twisted (Python) or POE (Perl). With >1 threads the callers form an "implicit thread pool" (themselves) and basically just offload the blocking IO.
There are also approaches like Actors, Continuations or Fibres exposed in the underlying models of some languages which alter how the basic problem is approached -- don't wait, react.
Happy coding.
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I have been trying to learn multi-threaded programming in C# and I am confused about when it is best to use a thread pool vs. create my own threads. One book recommends using a thread pool for small tasks only (whatever that means), but I can't seem to find any real guidelines.
What are some pros and cons of thread pools vs creating my own threads? And what are some example use cases for each?
I would suggest you use a thread pool in C# for the same reasons as any other language.
When you want to limit the number of threads running or don't want the overhead of creating and destroying them, use a thread pool.
By small tasks, the book you read means tasks with a short lifetime. If it takes ten seconds to create a thread which only runs for one second, that's one place where you should be using pools (ignore my actual figures, it's the ratio that counts).
Otherwise you spend the bulk of your time creating and destroying threads rather than simply doing the work they're intended to do.
If you have lots of logical tasks that require constant processing and you want that to be done in parallel use the pool+scheduler.
If you need to make your IO related tasks concurrently such as downloading stuff from remote servers or disk access, but need to do this say once every few minutes, then make your own threads and kill them once you're finished.
Edit: About some considerations, I use thread pools for database access, physics/simulation, AI(games), and for scripted tasks ran on virtual machines that process lots of user defined tasks.
Normally a pool consists of 2 threads per processor (so likely 4 nowadays), however you can set up the amount of threads you want, if you know how many you need.
Edit: The reason to make your own threads is because of context changes, (thats when threads need to swap in and out of the process, along with their memory). Having useless context changes, say when you aren't using your threads, just leaving them sit around as one might say, can easily half the performance of your program (say you have 3 sleeping threads and 2 active threads). Thus if those downloading threads are just waiting they're eating up tons of CPU and cooling down the cache for your real application
Here's a nice summary of the thread pool in .Net: http://blogs.msdn.com/pedram/archive/2007/08/05/dedicated-thread-or-a-threadpool-thread.aspx
The post also has some points on when you should not use the thread pool and start your own thread instead.
I highly recommend reading the this free e-book:
Threading in C# by Joseph Albahari
At least read the "Getting Started" section. The e-book provides a great introduction and includes a wealth of advanced threading information as well.
Knowing whether or not to use the thread pool is just the beginning. Next you will need to determine which method of entering the thread pool best suits your needs:
Task Parallel Library (.NET Framework
4.0)
ThreadPool.QueueUserWorkItem
Asynchronous Delegates
BackgroundWorker
This e-book explains these all and advises when to use them vs. create your own thread.
The thread pool is designed to reduce context switching among your threads. Consider a process that has several components running. Each of those components could be creating worker threads. The more threads in your process, the more time is wasted on context switching.
Now, if each of those components were queuing items to the thread pool, you would have a lot less context switching overhead.
The thread pool is designed to maximize the work being done across your CPUs (or CPU cores). That is why, by default, the thread pool spins up multiple threads per processor.
There are some situations where you would not want to use the thread pool. If you are waiting on I/O, or waiting on an event, etc then you tie up that thread pool thread and it can't be used by anyone else. Same idea applies to long running tasks, though what constitutes a long running task is subjective.
Pax Diablo makes a good point as well. Spinning up threads is not free. It takes time and they consume additional memory for their stack space. The thread pool will re-use threads to amortize this cost.
Note: you asked about using a thread pool thread to download data or perform disk I/O. You should not use a thread pool thread for this (for the reasons I outlined above). Instead use asynchronous I/O (aka the BeginXX and EndXX methods). For a FileStream that would be BeginRead and EndRead. For an HttpWebRequest that would be BeginGetResponse and EndGetResponse. They are more complicated to use, but they are the proper way to perform multi-threaded I/O.
Beware of the .NET thread pool for operations that may block for any significant, variable or unknown part of their processing, as it is prone to thread starvation. Consider using the .NET parallel extensions, which provide a good number of logical abstractions over threaded operations. They also include a new scheduler, which should be an improvement on ThreadPool. See here
One reason to use the thread pool for small tasks only is that there are a limited number of thread pool threads. If one is used for a long time then it stops that thread from being used by other code. If this happens many times then the thread pool can become used up.
Using up the thread pool can have subtle effects - some .NET timers use thread pool threads and will not fire, for example.
If you have a background task that will live for a long time, like for the entire lifetime of your application, then creating your own thread is a reasonable thing. If you have short jobs that need to be done in a thread, then use thread pooling.
In an application where you are creating many threads, the overhead of creating the threads becomes substantial. Using the thread pool creates the threads once and reuses them, thus avoiding the thread creation overhead.
In an application that I worked on, changing from creating threads to using the thread pool for the short lived threads really helpped the through put of the application.
For the highest performance with concurrently executing units, write your own thread pool, where a pool of Thread objects are created at start up and go to blocking (formerly suspended), waiting on a context to run (an object with a standard interface implemented by your code).
So many articles about Tasks vs. Threads vs. the .NET ThreadPool fail to really give you what you need to make a decision for performance. But when you compare them, Threads win out and especially a pool of Threads. They are distributed the best across CPUs and they start up faster.
What should be discussed is the fact that the main execution unit of Windows (including Windows 10) is a thread, and OS context switching overhead is usually negligible. Simply put, I have not been able to find convincing evidence of many of these articles, whether the article claims higher performance by saving context switching or better CPU usage.
Now for a bit of realism:
Most of us won’t need our application to be deterministic, and most of us do not have a hard-knocks background with threads, which for instance often comes with developing an operating system. What I wrote above is not for a beginner.
So what may be most important is to discuss is what is easy to program.
If you create your own thread pool, you’ll have a bit of writing to do as you’ll need to be concerned with tracking execution status, how to simulate suspend and resume, and how to cancel execution – including in an application-wide shut down. You might also have to be concerned with whether you want to dynamically grow your pool and also what capacity limitation your pool will have. I can write such a framework in an hour but that is because I’ve done it so many times.
Perhaps the easiest way to write an execution unit is to use a Task. The beauty of a Task is that you can create one and kick it off in-line in your code (though caution may be warranted). You can pass a cancellation token to handle when you want to cancel the Task. Also, it uses the promise approach to chaining events, and you can have it return a specific type of value. Moreover, with async and await, more options exist and your code will be more portable.
In essence, it is important to understand the pros and cons with Tasks vs. Threads vs. the .NET ThreadPool. If I need high performance, I am going to use threads, and I prefer using my own pool.
An easy way to compare is start up 512 Threads, 512 Tasks, and 512 ThreadPool threads. You’ll find a delay in the beginning with Threads (hence, why write a thread pool), but all 512 Threads will be running in a few seconds while Tasks and .NET ThreadPool threads take up to a few minutes to all start.
Below are the results of such a test (i5 quad core with 16 GB of RAM), giving each 30 seconds to run. The code executed performs simple file I/O on an SSD drive.
Test Results
Thread pools are great when you have more tasks to process than available threads.
You can add all the tasks to a thread pool and specify the maximum number of threads that can run at a certain time.
Check out this page on MSDN:
http://msdn.microsoft.com/en-us/library/3dasc8as(VS.80).aspx
Always use a thread pool if you can, work at the highest level of abstraction possible. Thread pools hide creating and destroying threads for you, this is usually a good thing!
Most of the time you can use the pool as you avoid the expensive process of creating the thread.
However in some scenarios you may want to create a thread. For example if you are not the only one using the thread pool and the thread you create is long-lived (to avoid consuming shared resources) or for example if you want to control the stacksize of the thread.
Don't forget to investigate the Background worker.
I find for a lot of situations, it gives me just what i want without the heavy lifting.
Cheers.
I usually use the Threadpool whenever I need to just do something on another thread and don't really care when it runs or ends. Something like logging or maybe even background downloading a file (though there are better ways to do that async-style). I use my own thread when I need more control. Also what I've found is using a Threadsafe queue (hack your own) to store "command objects" is nice when I have multiple commands that I need to work on in >1 thread. So you'd may split up an Xml file and put each element in a queue and then have multiple threads working on doing some processing on these elements. I wrote such a queue way back in uni (VB.net!) that I've converted to C#. I've included it below for no particular reason (this code might contain some errors).
using System.Collections.Generic;
using System.Threading;
namespace ThreadSafeQueue {
public class ThreadSafeQueue<T> {
private Queue<T> _queue;
public ThreadSafeQueue() {
_queue = new Queue<T>();
}
public void EnqueueSafe(T item) {
lock ( this ) {
_queue.Enqueue(item);
if ( _queue.Count >= 1 )
Monitor.Pulse(this);
}
}
public T DequeueSafe() {
lock ( this ) {
while ( _queue.Count <= 0 )
Monitor.Wait(this);
return this.DeEnqueueUnblock();
}
}
private T DeEnqueueUnblock() {
return _queue.Dequeue();
}
}
}
I wanted a thread pool to distribute work across cores with as little latency as possible, and that didn't have to play well with other applications. I found that the .NET thread pool performance wasn't as good as it could be. I knew I wanted one thread per core, so I wrote my own thread pool substitute class. The code is provided as an answer to another StackOverflow question over here.
As to the original question, the thread pool is useful for breaking repetitive computations up into parts that can be executed in parallel (assuming they can be executed in parallel without changing the outcome). Manual thread management is useful for tasks like UI and IO.
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When should I not use the ThreadPool in .Net?
It looks like the best option is to use a ThreadPool, in which case, why is it not the only option?
What are your experiences around this?
#Eric, I'm going to have to agree with Dean. Threads are expensive. You can't assume that your program is the only one running. When everyone is greedy with resources, the problem multiplies.
I prefer to create my threads manually and control them myself. It keeps the code very easy to understand.
That's fine when it's appropriate. If you need a bunch of worker threads, though, all you've done is make your code more complicated. Now you have to write code to manage them. If you just used a thread pool, you'd get all the thread management for free. And the thread pool provided by the language is very likely to be more robust, more efficient, and less buggy than whatever you roll for yourself.
Thread t = new Thread(new ThreadStart(DoSomething));
t.Start();
t.Join();
I hope that you would normally have some additional code in between Start() and Join(). Otherwise, the extra thread is useless, and you're wasting resources for no reason.
People are way too afraid of the resources used by threads. I've never seen creating and starting a thread to take more than a millisecond. There is no hard limit on the number of threads you can create. RAM usage is minimal. Once you have a few hundred threads, CPU becomes an issue because of context switches, so at that point you might want to get fancy with your design.
A millisecond is a long time on modern hardware. That's 3 million cycles on a 3GHz machine. And again, you aren't the only one creating threads. Your threads compete for the CPU along with every other program's threads. If you use not-quite-too-many threads, and so does another program, then together you've used too many threads.
Seriously, don't make life more complex than it needs to be. Don't use the thread pool unless you need something very specific that it offers.
Indeed. Don't make life more complex. If your program needs multiple worker threads, don't reinvent the wheel. Use the thread pool. That's why it's there. Would you roll your own string class?
The only reason why I wouldn't use the ThreadPool for cheap multithreading is if I need to…
interract with the method running (e.g., to kill it)
run code on a STA thread (this happened to me)
keep the thread alive after my application has died (ThreadPool threads are background threads)
in case I need to change the priority of the Thread. We can not change priority of threads in ThreadPool which is by default Normal.
P.S.: The MSDN article "The Managed Thread Pool" contains a section titled, "When Not to Use Thread Pool Threads", with a very similar but slightly more complete list of possible reasons for not using the thread pool.
There are lots of reasons why you would need to skip the ThreadPool, but if you don't know them then the ThreadPool should be good enough for you.
Alternatively, look at the new Parallel Extensions Framework, which has some neat stuff in there that may suit your needs without having to use the ThreadPool.
To quarrelsome's answer, I would add that it's best not to use a ThreadPool thread if you need to guarantee that your thread will begin work immediately. The maximum number of running thread-pooled threads is limited per appdomain, so your piece of work may have to wait if they're all busy. It's called "queue user work item", after all.
Two caveats, of course:
You can change the maximum number of thread-pooled threads in code, at runtime, so there's nothing to stop you checking the current vs maximum number and upping the maximum if required.
Spinning up a new thread comes with its own time penalty - whether it's worthwhile for you to take the hit depends on your circumstances.
Thread pools make sense whenever you have the concept of worker threads. Any time you can easily partition processing into smaller jobs, each of which can be processed independently, worker threads (and therefore a thread pool) make sense.
Thread pools do not make sense when you need thread which perform entirely dissimilar and unrelated actions, which cannot be considered "jobs"; e.g., One thread for GUI event handling, another for backend processing. Thread pools also don't make sense when processing forms a pipeline.
Basically, if you have threads which start, process a job, and quit, a thread pool is probably the way to go. Otherwise, the thread pool isn't really going to help.
I'm not speaking as someone with only
theoretical knowledge here. I write
and maintain high volume applications
that make heavy use of multithreading,
and I generally don't find the thread
pool to be the correct answer.
Ah, argument from authority - but always be on the look out for people who might be on the Windows kernel team.
Neither of us were arguing with the fact that if you have some specific requirements then the .NET ThreadPool might not be the right thing. What we're objecting to is the trivialisation of the costs to the machine of creating a thread.
The significant expense of creating a thread at the raison d'etre for the ThreadPool in the first place. I don't want my machines to be filled with code written by people who have been misinformed about the expense of creating a thread, and don't, for example, know that it causes a method to be called in every single DLL which is attached to the process (some of which will be created by 3rd parties), and which may well hot-up a load of code which need not be in RAM at all and almost certainly didn't need to be in L1.
The shape of the memory hierarchy in a modern machine means that 'distracting' a CPU is about the worst thing you can possibly do, and everybody who cares about their craft should work hard to avoid it.
When you're going to perform an operation that is going to take a long time, or perhaps a continuous background thread.
I guess you could always push the amount of threads available in the pool up but there would be little point in incurring the management costs of a thread that is never going to be given back to the pool.
Threadpool threads are appropriate for tasks that meet both of the following criteria:
The task will not have to spend any significant time waiting for something to happen
Anything that's waiting for the task to finish will likely be waiting for many tasks to finish, so its scheduling priority isn't apt to affect things much.
Using a threadpool thread instead of creating a new one will save a significant but bounded amount of time. If that time is significant compared with the time it will take to perform a task, a threadpool task is likely appropriate. The longer the time required to perform a task, however, the smaller the benefit of using the threadpool and the greater the likelihood of the task impeding threadpool efficiency.
MSDN has a list some reasons here:
http://msdn.microsoft.com/en-us/library/0ka9477y.aspx
There are several scenarios in which it is appropriate to create and
manage your own threads instead of using thread pool threads:
You require a foreground thread.
You require a thread to have a particular priority.
You have tasks that cause the thread to block for long periods of time. The thread pool has a maximum number of threads, so a large
number of blocked thread pool threads might prevent tasks from
starting.
You need to place threads into a single-threaded apartment. All ThreadPool threads are in the multithreaded apartment.
You need to have a stable identity associated with the thread, or to dedicate a thread to a task.
#Eric
#Derek, I don't exactly agree with the scenario you use as an example. If you don't know exactly what's running on your machine and exactly how many total threads, handles, CPU time, RAM, etc, that your app will use under a certain amount of load, you are in trouble.
Are you the only target customer for the programs you write? If not, you can't be certain about most of that. You generally have no idea when you write a program whether it will execute effectively solo, or if it will run on a webserver being hammered by a DDOS attack. You can't know how much CPU time you are going to have.
Assuming your program's behavior changes based on input, it's rare to even know exactly how much memory or CPU time your program will consume. Sure, you should have a pretty good idea about how your program is going to behave, but most programs are never analyzed to determine exactly how much memory, how many handles, etc. will be used, because a full analysis is expensive. If you aren't writing real-time software, the payoff isn't worth the effort.
In general, claiming to know exactly how your program will behave is far-fetched, and claiming to know everything about the machine approaches ludicrous.
And to be honest, if you don't know exactly what method you should use: manual threads, thread pool, delegates, and how to implement it to do just what your application needs, you are in trouble.
I don't fully disagree, but I don't really see how that's relevant. This site is here specifically because programmers don't always have all the answers.
If your application is complex enough to require throttling the number of threads that you use, aren't you almost always going to want more control than what the framework gives you?
No. If I need a thread pool, I will use the one that's provided, unless and until I find that it is not sufficient. I will not simply assume that the provided thread pool is insufficient for my needs without confirming that to be the case.
I'm not speaking as someone with only theoretical knowledge here. I write and maintain high volume applications that make heavy use of multithreading, and I generally don't find the thread pool to be the correct answer.
Most of my professional experience has been with multithreading and multiprocessing programs. I have often needed to roll my own solution as well. That doesn't mean that the thread pool isn't useful, or appropriate in many cases. The thread pool is built to handle worker threads. In cases where multiple worker threads are appropriate, the provided thread pool should should generally be the first approach.