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/.
Related
I've been reading this article on MSDN about C# Concurrent Collections. It talks about the optimum threading to use for particular scenarios to get the most benefit out of the collections e.g:
ConcurrentQueue performs best when one dedicated thread is queuing and one dedicated thread is de-queuing. If you do not enforce this rule, then Queue might even perform slightly faster than ConcurrentQueue on computers that have multiple cores.
Is this advice still valid when one is using Tasks instead of raw Threads? From my (limited) understanding of C# Tasks, there is no guarantee that a particular Task will always run on the same thread between context switches, or does maintaining the stack frame mean that the same rules apply in terms of best usage?
Thanks.
One task always runs on the same thread. TPL is a user-mode library. User mode has no (practical) way of migrating executing code from thread to thread. Also there would be no point to doing that.
This advice applies exactly to tasks as it does to threads.
What that piece of advice means to say is that at the same time there should be one producer and one consumer only. You can have 100 threads enqueuing from time to time as long as they do not contend.
(I'm not questioning that advice here since that is out of scope for this question. But that is what's meant here.)
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).
When do you use threads in a application? For example, in simple CRUD operations, use of smtp, calling webservices that may take a few time if the server is facing bandwith issues, etc.
To be honest, i don't know how to determine if i need to use a thread (i know that it must be when we're excepting that a operation will take a few time to be done).
This may be a "noob" question but it'll be great if you share with me your experience in threads.
Thanks
I added C# and .NET tags to your question because you mention C# in your title. If that is not accurate, feel free to remove the tags.
There are different styles of multithreading. For example, there are asynchronous operations with callback functions. .NET 4 introduces the parallel Linq library. The style of multithreading you would use, or whether to use any at all, depends on what you are trying to accomplish.
Parallel execution, such as what parallel Linq would generally be trying to do, takes advantage of multiple processor cores executing instructions that do not need to wait for data from each other. There are many sources for such algorithms outside Linq, such as this. However, it is possible that parallel execution may be unable to you or that it does not suit your application.
More traditional multithreading takes advantage of threading within the .NET library (in this case) as provided by System.Thread. Remember that there is some overhead in starting processes on threads, so only use threads when the advantages of doing so outweigh this overhead. Generally speaking, you would only want to use this type of single-processor multithreading when the task running under the thread will have long gaps in which the processor could be doing something else. For example, I/O from hard disk (and, consequently, from a database system that uses one) is many orders of magnitude slower than memory access. Network access can also be slow, as another example. Multithreading could allow another process to be running while waiting for these slow (compared to the processor) operations to complete.
Another example when I have used traditional multithreading is to cache some values the first time a particular ASP.NET page is accessed within a session. I kick off a thread so that the user does not have to wait for the caching to complete before interacting with the page. I also regulate the behavior when the caching does not complete before the user requests another page so that, if the caching does not complete, it is not a problem. It simply makes some further requests faster that were previously too slow.
Consider also the cost that multithreading has to the maintainability of your application. Threaded applications can be harder to debug, for example.
I hope this answers your question at least somewhat.
Joseph Albahari summarized it very well here:
Maintaining a responsive user interface
Making efficient use of an otherwise blocked CPU
Parallel programming
Speculative execution
Allowing requests to be processed simultaneously
One reason to use threads is to split large, CPU-bound tasks across a number of CPUs/cores, to finish faster. Another is to let an extended task execute asynchronously, so the foreground can remain responsive while it runs.
Your examples seem to be concentrating on the second of these. While it can be a good reason, if you can use asynchronous I/O instead, that's usually preferable (e.g., almost anything using sockets can/will be better off using the socket(s) asynchronously). Asynchronous I/O is easier to cancel, and it'll usually have lower CPU overhead as well.
You can use threads when you need different execution paths. This leads(when done correctly) to more responsive and/or faster applications but also leads to more complex code and debugging.
In a simple CRUD scenario maybe is not that useful, but maybe your UI is consuming a slow web service. If you your code is tied to your UI thread you will have unresponsive UI between the service calls.
In that case, using System.Threading.Threads maybe be overkill because you don't need so much control. Using a BackgrounWorker maybe a better choice.
Threading is something difficult to master, but the benefits when used correctly are huge, performance is the most common.
Somehow you have answered your question by yourself. Using threads whenever you execute time consuming operations is right choice. Also you should it in situations when you want to make things faster. For example you want to process some amount of files - each file can be processed by different thread.
By using threads you can better utilize power of multi-core/processor machines.
Monitoring some data in background of your application.
There are dozens of such scenarios.
Realising my comment might suffice as an answer ...
I like to view multi-threading scenarios from a resource perspective. In other words, UI (graphics), networking, disk IO, CPU (cores), RAM etc. I find that helps when deciding where to use multi-threading in the general sense at least.
The reasoning behind this is simply that I can take advantage of one resource on a specific thread (eg. Disk IO) while at the same time using another thread to accomplish something else using a different resource.
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.
I have some embarrassingly-parallelizable work in a .NET 3.5 console app and I want to take advantage of hyperthreading and multi-core processors. How do I pick the best number of worker threads to utilize either of these the best on an arbitrary system? For example, if it's a dual core I will want 2 threads; quad core I will want 4 threads. What I'm ultimately after is determining the processor characteristics so I can know how many threads to create.
I'm not asking how to split up the work nor how to do threading, I'm asking how do I determine the "optimal" number of the threads on an arbitrary machine this console app will run on.
I'd suggest that you don't try to determine it yourself. Use the ThreadPool and let .NET manage the threads for you.
You can use Environment.ProcessorCount if that's the only thing you're after. But usually using a ThreadPool is indeed the better option.
The .NET thread pool also has provisions for sometimes allocating more threads than you have cores to maximise throughput in certain scenarios where many threads are waiting for I/O to finish.
The correct number is obviously 42.
Now on the serious note. Just use the thread pool, always.
1) If you have a lengthy processing task (ie. CPU intensive) that can be partitioned into multiple work piece meals then you should partition your task and then submit all individual work items to the ThreadPool. The thread pool will pick up work items and start churning on them in a dynamic fashion as it has self monitoring capabilities that include starting new threads as needed and can be configured at deployment by administrators according to the deployment site requirements, as opposed to pre-compute the numbers at development time. While is true that the proper partitioning size of your processing task can take into account the number of CPUs available, the right answer depends so much on the nature of the task and the data that is not even worth talking about at this stage (and besides the primary concerns should be your NUMA nodes, memory locality and interlocked cache contention, and only after that the number of cores).
2) If you're doing I/O (including DB calls) then you should use Asynchronous I/O and complete the calls in ThreadPool called completion routines.
These two are the the only valid reasons why you should have multiple threads, and they're both best handled by using the ThreadPool. Anything else, including starting a thread per 'request' or 'connection' are in fact anti patterns on the Win32 API world (fork is a valid pattern in *nix, but definitely not on Windows).
For a more specialized and way, way more detailed discussion of the topic I can only recommend the Rick Vicik papers on the subject:
designing-applications-for-high-performance-part-1.aspx
designing-applications-for-high-performance-part-ii.aspx
designing-applications-for-high-performance-part-iii.aspx
The optimal number would just be the processor count. Optimally you would always have one thread running on a CPU (logical or physical) to minimise context switches and the overhead that has with it.
Whether that is the right number depends (very much as everyone has said) on what you are doing. The threadpool (if I understand it correctly) pretty much tries to use as few threads as possible but spins up another one each time a thread blocks.
The blocking is never optimal but if you are doing any form of blocking then the answer would change dramatically.
The simplest and easiest way to get good (not necessarily optimal) behaviour is to use the threadpool. In my opinion its really hard to do any better than the threadpool so thats simply the best place to start and only ever think about something else if you can demonstrate why that is not good enough.
A good rule of the thumb, given that you're completely CPU-bound, is processorCount+1.
That's +1 because you will always get some tasks started/stopped/interrupted and n tasks will almost never completely fill up n processors.
The only way is a combination of data and code analysis based on performance data.
Different CPU families and speeds vs. memory speed vs other activities on the system are all going to make the tuning different.
Potentially some self-tuning is possible, but this will mean having some form of live performance tuning and self adjustment.
Or even better than the ThreadPool, use .NET 4.0 Task instances from the TPL. The Task Parallel Library is built on a foundation in the .NET 4.0 framework that will actually determine the optimal number of threads to perform the tasks as efficiently as possible for you.
I read something on this recently (see the accepted answer to this question for example).
The simple answer is that you let the operating system decide. It can do a far better job of deciding what's optimal than you can.
There are a number of questions on a similar theme - search for "optimal number threads" (without the quotes) gives you a couple of pages of results.
I would say it also depends on what you are doing, if your making a server application then using all you can out of the CPU`s via either Environment.ProcessorCount or a thread pool is a good idea.
But if this is running on a desktop or a machine that not dedicated to this task, you might want to leave some CPU idle so the machine "functions" for the user.
It can be argued that the real way to pick the best number of threads is for the application to profile itself and adaptively change its threading behavior based on what gives the best performance.
I wrote a simple number crunching app that used multiple threads, and found that on my Quad-core system, it completed the most work in a fixed period using 6 threads.
I think the only real way to determine is through trialling or profiling.
In addition to processor count, you may want to take into account the process's processor affinity by counting bits in the affinity mask returned by the GetProcessAffinityMask function.
If there is no excessive i/o processing or system calls when the threads are running, then the number of thread (except the main thread) is in general equal to the number of processors/cores in your system, otherwise you can try to increase the number of threads by testing.