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After reading how the thread pool and tasks work in this article I came up with this question -
If I have a complex program in which some modules use tasks and some use thread pool, is it possible that there will be some scheduling problems due to the different uses?
Task are often implemented using the thread pool (one can of course also have tasks using other types of schedulers that give different behavior, but this is the default). In terms of the actual code being executed (assuming your tasks are representing delegates being run) there really isn't much difference.
Tasks are simply creating a wrapper around that thread pool call to provide additional functionality when it comes to gather information about, and processing the results of, that asynchronous operation. If you want to leverage that additional functionality then use tasks. If you have no need to use it in some particular context, there's nothing wrong with using the thread pool directly.
Mix the two, so long as you don't have trouble getting what you want out of the results of those operations, is not a problem at all.
No. And there actually isn't much in the way of memory or performance inefficiencies when mixing approaches; by default tasks use the same thread pool that thread pool threads use.
The only significant disadvantage of mixing both is lack of consistency in your codebase. If you were to pick one, I would use TPL since it is has a rich API for handling many aspects of multi-threading and takes advantage of async/await language features.
Since your usage is divided down module lines, you don't have much to worry about.
No, there wouldn't be problems - you just would be inefficient in doing both. use what is really needed and stick with the pattern. Remember to be sure that you make your app MT Safe also especially if you are accessing the same resources/variables etc... from different threads, regardless of which threading algorithm you use.
There shouldn't be any scheduling problems as such, but of course it's better to use Tasks and let the Framework decide what to do with the scheduled work. In the current version of the framework (4.5) the work will be queued through the ThreadPool unless the LongRunning option is used, but this behaviour may change in future of course.
Verdict: Mixing Tasks and ThreadPool isn't a problem, but for new applications it's recommended to use Tasks instead of queueing work items directly on the ThreadPool (one reason for that is ThreadPool isn't available in Windows 8 Runtime (Modern UI apps).
i´m currently dealing with a problem where i have to dispatch hell a lot of functions to another thread to prevent the current function from blocking.
now i wonder what the fastest way is to perform this task.
currently i´m stuck with
ThreadPool.UnsafeQueueUserWorkItem
as its slightly faster than the regular QueueUserWorkItem. however, i´m afraid that the threadpool may block this here. is there a faster way of dispatching a method call to another thread?
i just wonder what the best practice is for such a task? unsafe code would be no problem as it i´s in a scenario where already a lot of interop is used.
thanks
j.
CLR(4) team recommends:
Task is now the preferred way to queue work to the thread pool.
Read CLR 4.0 ThreadPool Improvements: Part 1 and New and Improved CLR 4 Thread Pool Engine for detail information. In short, reasons are: local queues, threads reusing, work stealing. Basiclly for load balancing goal.
Extras:
I don't understand why it's not the answer (downvoted).
You wrote
i have to dispatch hell a lot of functions to another thread to
prevent the current function from blocking"
I reply:
Some TPL (exists for net35) 'blocks' (concurrent collections, spinning primitives etc) are designed specifically for highly concurrent access, with the focus on minimizing or eliminating blocking for efficient management of work. You can use those blocks as well (for ex. - BlockingCollection for your problem). TPL designed for creating and handling hundreds (or even thousands) of cpu/io-bound operations (tasks) with minimal overhead (or millions with the help of PLinq).
You asked:
i just wonder what the best practice is for such a task?
I've already answered: best practice - TPL (reasoned, not just my recommendation)
Inserting multiple or bigger items at once should reduce the overhead.
Edited after reading one of your comments:
I have experienced similar things. My usual remedy is not to dispatch every asynchronous request immediately but rather mimic what Nagle's Algorithm does for TCP.
Here, upon receiving a Request() you would dispatch it immediately only if no asynchronous work is pending. If asynchronous work is pending you would dispatch only if a certain number of milliseconds since the earliest non-dispatched Request has elapsed or a certain number of outstanding Request()s has accumulated.
This is an effective pattern to cut down overhead when getting frequent Request()s over which you have no control. Hope that helps.
Maybe you could throw all your dispatch requests into a List<> and wake up another background thread to make the calls to QueueUserWorkItem.
Am I understanding the problem correctly?
I've read that threads are very problematic. What alternatives are available? Something that handles blocking and stuff automatically?
A lot of people recommend the background worker, but I've no idea why.
Anyone care to explain "easy" alternatives? The user will be able to select the number of threads to use (depending on their speed needs and computer power).
Any ideas?
To summarize the problems with threads:
if threads share memory, you can get
race conditions
if you avoid races by liberally using locks, you
can get deadlocks (see the dining philosophers problem)
An example of a race: suppose two threads share access to some memory where a number is stored. Thread 1 reads from the memory address and stores it in a CPU register. Thread 2 does the same. Now thread 1 increments the number and writes it back to memory. Thread 2 then does the same. End result: the number was only incremented by 1, while both threads tried to increment it. The outcome of such interactions depend on timing. Worse, your code may seem to work bug-free but once in a blue moon the timing is wrong and bad things happen.
To avoid these problems, the answer is simple: avoid sharing writable memory. Instead, use message passing to communicate between threads. An extreme example is to put the threads in separate processes and communicate via TCP/IP connections or named pipes.
Another approach is to share only read-only data structures, which is why functional programming languages can work so well with multiple threads.
This is a bit higher-level answer, but it may be useful if you want to consider other alternatives to threads. Anyway, most of the answers discussed solutions based on threads (or thread pools) or maybe tasks from .NET 4.0, but there is one more alternative, which is called message-passing. This has been successfuly used in Erlang (a functional language used by Ericsson). Since functional programming is becoming more mainstream in these days (e.g. F#), I thought I could mention it. In genral:
Threads (or thread pools) can usually used when you have some relatively long-running computation. When it needs to share state with other threads, it gets tricky (you have to correctly use locks or other synchronization primitives).
Tasks (available in TPL in .NET 4.0) are very lightweight - you can split your program into thousands of tasks and then let the runtime run them (it will use optimal number of threads). If you can write your algorithm using tasks instead of threads, it sounds like a good idea - you can avoid some synchronization when you run computation using smaller steps.
Declarative approaches (PLINQ in .NET 4.0 is a great option) if you have some higher-level data processing operation that can be encoded using LINQ primitives, then you can use this technique. The runtime will automatically parallelize your code, because LINQ doesn't specify how exactly should it evaluate the results (you just say what results you want to get).
Message-passing allows you two write program as concurrently running processes that perform some (relatively simple) tasks and communicate by sending messages to each other. This is great, because you can share some state (send messages) without the usual synchronization issues (you just send a message, then do other thing or wait for messages). Here is a good introduction to message-passing in F# from Robert Pickering.
Note that the last three techniques are quite related to functional programming - in functional programming, you desing programs differently - as computations that return result (which makes it easier to use Tasks). You also often write declarative and higher-level code (which makes it easier to use Declarative approaches).
When it comes to actual implementation, F# has a wonderful message-passing library right in the core libraries. In C#, you can use Concurrency & Coordination Runtime, which feels a bit "hacky", but is probably quite powerful too (but may look too complicated).
Won't the parallel programming options in .Net 4 be an "easy" way to use threads? I'm not sure what I'd suggest for .Net 3.5 and earlier...
This MSDN link to the Parallel Computing Developer Center has links to lots of info on Parellel Programming including links to videos, etc.
I can recommend this project. Smart Thread Pool
Project Description
Smart Thread Pool is a thread pool written in C#. It is far more advanced than the .NET built-in thread pool.
Here is a list of the thread pool features:
The number of threads dynamically changes according to the workload on the threads in the pool.
Work items can return a value.
A work item can be cancelled.
The caller thread's context is used when the work item is executed (limited).
Usage of minimum number of Win32 event handles, so the handle count of the application won't explode.
The caller can wait for multiple or all the work items to complete.
Work item can have a PostExecute callback, which is called as soon the work item is completed.
The state object, that accompanies the work item, can be disposed automatically.
Work item exceptions are sent back to the caller.
Work items have priority.
Work items group.
The caller can suspend the start of a thread pool and work items group.
Threads have priority.
Can run COM objects that have single threaded apartment.
Support Action and Func delegates.
Support for WindowsCE (limited)
The MaxThreads and MinThreads can be changed at run time.
Cancel behavior is imporved.
"Problematic" is not the word I would use to describe working with threads. "Tedious" is a more appropriate description.
If you are new to threaded programming, I would suggest reading this thread as a starting point. It is by no means exhaustive but has some good introductory information. From there, I would continue to scour this website and other programming sites for information related to specific threading questions you may have.
As for specific threading options in C#, here's some suggestions on when to use each one.
Use BackgroundWorker if you have a single task that runs in the background and needs to interact with the UI. The task of marshalling data and method calls to the UI thread are handled automatically through its event-based model. Avoid BackgroundWorker if (1) your assembly does not already reference the System.Windows.Form assembly, (2) you need the thread to be a foreground thread, or (3) you need to manipulate the thread priority.
Use a ThreadPool thread when efficiency is desired. The ThreadPool helps avoid the overhead associated with creating, starting, and stopping threads. Avoid using the ThreadPool if (1) the task runs for the lifetime of your application, (2) you need the thread to be a foreground thread, (3) you need to manipulate the thread priority, or (4) you need the thread to have a fixed identity (aborting, suspending, discovering).
Use the Thread class for long-running tasks and when you require features offered by a formal threading model, e.g., choosing between foreground and background threads, tweaking the thread priority, fine-grained control over thread execution, etc.
Any time you introduce multiple threads, each running at once, you open up the potential for race conditions. To avoid these, you tend to need to add synchronization, which adds complexity, as well as the potential for deadlocks.
Many tools make this easier. .NET has quite a few classes specifically meant to ease the pain of dealing with multiple threads, including the BackgroundWorker class, which makes running background work and interacting with a user interface much simpler.
.NET 4 is going to do a lot to ease this even more. The Task Parallel Library and PLINQ dramatically ease working with multiple threads.
As for your last comment:
The user will be able to select the number of threads to use (depending on their speed needs and computer power).
Most of the routines in .NET are built upon the ThreadPool. In .NET 4, when using the TPL, the work load will actually scale at runtime, for you, eliminating the burden of having to specify the number of threads to use. However, there are ways to do this now.
Currently, you can use ThreadPool.SetMaxThreads to help limit the number of threads generated. In TPL, you can specify ParallelOptions.MaxDegreesOfParallelism, and pass an instance of the ParallelOptions into your routine to control this. The default behavior scales up with more threads as you add more processing cores, which is usually the best behavior in any case.
Threads are not problematic if you understand what causes problems with them.
For ex. if you avoid statics, you know which API's to use (e.g. use synchronized streams), you will avoid many of the issues that come up for their bad utilization.
If threading is a problem (this can happen if you have unsafe/unmanaged 3rd party dll's that cannot support multithreading. In this can an option is to create a meachism to queue the operations. ie store the parameters of the action to a database and just run through them one at a time. This can be done in a windows service. Obviously this will take longer but in some cases is the only option.
Threads are indispensable tools for solving many problems, and it behooves the maturing developer to know how to effectively use them. But like many tools, they can cause some very difficult-to-find bugs.
Don't shy away from some so useful just because it can cause problems, instead study and practice until you become the go-to guy for multi-threaded apps.
A great place to start is Joe Albahari's article: http://www.albahari.com/threading/.
I am working on a problem where I need to perform a lot of embarrassingly parallelizable tasks. The task is created by reading data from the database but a collection of all tasks would exceed the amount of memory on the machine so tasks have to be created, processed and disposed. I am wondering what would be a good approach to solve this problem? I am thinking the following two approaches:
Implement a synchronized task queue. Implement a producer (task creater) that read data from database and put task in the queue (limit the number of tasks currently in the queue to a constant value to make sure that the amount of memory is not exceeded). Have multiple consumer processes (task processor) that read task from the queue, process task, store the result and dispose the task. What would be a good number of consumer processes in this approach?
Use .NET Parallel extension (PLINQ or parallel for), but I understand that a collection of tasks have to be created (Can we add tasks to the collection while processing in the parallel for?). So we will create a batch of tasks -- say N tasks at a time and do process these batch of tasks and read another N tasks.
What are your thoughts on these two approaches?
Use a ThreadPool with a bounded queue to avoid overwhelming the system.
If each of your worker tasks is CPU bound then configure your system initially so that the number of threads in your system is equal to the number of hardware threads that your box can run.
If your tasks aren't CPU bound then you'll have to experiment with the pool size to get an optimal solution for your particular situation
You may have to experiment with either approach to get to the optimal configuration.
Basically, test, adjust, test, repeat until you're happy.
I've not had the opportunity to actually use PLINQ, however I do know that PLINQ (like vanilla LINQ) is based on IEnumerable. As such, I think this might be a case where it would make sense to implement the task producer via C# iterator blocks (i.e. the yield keyword).
Assuming you are not doing any operations where the entire set of tasks must be known in advance (e.g. ordering), I would expect that PLINQ would only consume as many tasks as it could process at once. Also, this article references some strategies for controlling just how PLINQ goes about consuming input (the section titled "Processing Query Output").
EDIT: Comparing PLINQ to a ThreadPool.
According to this MSDN article, efficiently allocating work to a thread pool is not at all trivial, and even when you do it "right", using the TPL generally exhibits better performance.
Use the ThreadPool.
Then you can queue up everything and items will be run as threads become available to the pool without overwhelming the system. The only trick is determining the optimum number of threads to run at a time.
Sounds like a job for Microsoft HPC Server 2008. Given that it's the number of tasks that's overwhelming, you need some kind of parallel process manager. That's what HPC server is all about.
http://www.microsoft.com/hpc/en/us/default.aspx
In order to give a good answer we need a few questions answered.
Is each individual task parallelizable? Or each task is the product of a parallelizable main task?
Also, is it the number of tasks that would cause the system to run out of memory, or is it the quantity of data each task holds and processes that would cause the system to run out of memory?
Sounds like Windows Workflow Foundation (WF) might be a good thing to use to do this. It might also give you some extra benefits such as pause/resume on your tasks.
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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.