Why must/should UI frameworks be single threaded? - multithreading

Closely related questions have been asked before:
Why are most UI frameworks single threaded?.
Should all event-driven frameworks be single-threaded?
But the answers to those questions still leave me unclear on some points.
The asker of the first question asked if multi-threading would help performance, and the answerers mostly said that it would not, because it is very unlikely that the GUI would be the bottleneck in a 2D application on modern hardware. But this seems to me a sneaky debating tactic. Sure, if you have carefully structured your application to do nothing other than UI calls on the UI thread you won't have a bottleneck. But that might take a lot of work and make your code more complicated, and if you had a faster core or could make UI calls from multiple threads, maybe it wouldn't be worth doing.
A commonly advocated architectural design is to have view components that don't have callbacks and don't need to lock anything except maybe their descendants. Under such an architecture, can't you let any thread invoke methods on view objects, using per-object locks, without fear of deadlock?
I am less confident about the situation with UI controls, but as long their callbacks are only invoked by the system, why should they cause any special deadlock issues? After all, if the callbacks need to do anything time consuming, they will delegate to another thread, and then we're right back in the multiple threads case.
How much of the benefit of a multi-threaded UI would you get if you could just block on the UI thread? Because various emerging abstractions over async in effect let you do that.
Almost all of the discussion I have seen assumes that concurrency will be dealt with using manual locking, but there is a broad consensus that manual locking is a bad way to manage concurrency in most contexts. How does the discussion change when we take into consideration the concurrency primitives that the experts are advising us to use more, such as software transactional memory, or eschewing shared memory in favor of message passing (possibly with synchronization, as in go)?

TL;DR
It is a simple way to force sequencing to occur in an activity that is going to ultimately be in sequence anyway (the screen draw X times per second, in order).
Discussion
Handling long-held resources which have a single identity within a system is typically done by representing them with a single thread, process, "object" or whatever else represents an atomic unit with regard to concurrency in a given language. Back in the non-emptive, negligent-kernel, non-timeshared, One True Thread days this was managed manually by polling/cycling or writing your own scheduling system. In such a system you still had a 1::1 mapping between function/object/thingy and singular resources (or you went mad before 8th grade).
This is the same approach used with handling network sockets, or any other long-lived resource. The GUI itself is but one of many such resources a typical program manages, and typically long-lived resources are places where the ordering of events matters.
For example, in a chat program you would usually not write a single thread. You would have a GUI thread, a network thread, and maybe some other thread that deals with logging resources or whatever. It is not uncommon for a typical system to be so fast that its easier to just put the logging and input into the same thread that makes GUI updates, but this is not always the case. In all cases, though, each category of resources is most easily reasoned about by granting them a single thread, and that means one thread for the network, one thread for the GUI, and however many other threads are necessary for long-lived operations or resources to be managed without blocking the others.
To make life easier its common to not share data directly among these threads as much as possible. Queues are much easier to reason about than resource locks and can guarantee sequencing. Most GUI libraries either queue events to be handled (so they can be evaluated in order) or commit data changes required by events immediately, but get a lock on the state of the GUI prior to each pass of the repaint loop. It doesn't matter what happened before, the only thing that matters when painting the screen is the state of the world right then. This is slightly different than the typical network case where all the data needs to be sent in order and forgetting about some of it is not an option.
So GUI frameworks are not multi-threaded, per se, it is the GUI loop that needs to be a single thread to sanely manage that single long-held resource. Programming examples, typically being trivial by nature, are often single-threaded with all the program logic running in the same process/thread as the GUI loop, but this is not typical in more complex programs.
To sum up
Because scheduling is hard, shared data management is even harder, and a single resource can only be accessed serially anyway, a single thread used to represent each long-held resource and each long-running procedure is a typical way to structure code. GUIs are only one resource among several that a typical program will manage. So "GUI programs" are by no means single-threaded, but GUI libraries typically are.
In trivial programs there is no realized penalty to putting other program logic in the GUI thread, but this approach falls apart when significant loads are experienced or resource management requires either a lot of blocking or polling, which is why you will often see event queue, signal-slot message abstractions or other approaches to multi-threading/processing mentioned in the dusty corners of nearly any GUI library (and here I'm including game libraries -- while game libs typically expect that you want to essentially build your own widgets around your own UI concept, the basic principles are very similar, just a bit lower-level).
[As an aside, I've been doing a lot of Qt/C++ and Wx/Erlang lately. The Qt docs do a good job of explaining approaches to multi-threading, the role of the GUI loop, and where Qt's signal/slot approach fits into the abstraction (so you don't have to think about concurrency/locking/sequencing/scheduling/etc very much). Erlang is inherently concurrent, but wx itself is typically started as a single OS process that manages a GUI update loop and Erlang posts update events to it as messages, and GUI events are sent to the Erlang side as messages -- thus permitting normal Erlang concurrent coding, but providing a single point of GUI event sequencing so that wx can do its GUI update looping thing.]

Because the GUI main thread code is old. Very old and therefore very much designed for low resource usage. If someone would write everything from scratch again (and even Android as the most recent GUI OS didn't) it would be working well and be better in multithreading.
For example the best two improvements that would help for MT are
Now we have MVVM (Model-View-ViewModel) pattern, this is an extra duplication of data. When the toolskits were developed even a single duplication in a MVC was highly debated. MVVM makes multithreading much easier. IMHO this was the main reason for Microsoft to invent it in the first place in .NET not the data binding.
The scene graph approach. Android, iOS, Windows UWP (based on CoreWindow not hWnd until Windows11 Project Reunion), Gtk4 is decoupling the GPU part from the model. Yes it is in fact a MVVMGM now (Model-View-ViewModel-GPUModel). So another memory intense layer. If you duplicate stuff you need less synchronisation. Combine on Android and SwiftUI on MacOS/iOS is using immutability of GUI widgets now to further improve this View->GPUModel.
Especially with the GPU Model/Scene Graph, the statement that GUIs are single threaded is not true anymore.

Two reasons, as far as I can tell:
It is much easier to reason about single-threaded code; thus the event loop model reduces the likelihood of bugs.
2D User interfaces are not CPU intensive. An old computer with a wimpy graphics card can smoothly render all the windows, frames, widgets, etc. you could possibly desire without skipping a beat.
Basically, if single-threaded code is easier and tends to have fewer bugs, favor that over multithreaded code unless you have a compelling need for parallelization or speed. Your typical GUI frameworks don't have this need.
Now, of course we've all experienced lagginess and freezes from GUI applications before. I'd argue that the vast majority of the time, this is the fault of the developer: putting long-running synchronous code for an event that should have been handled asynchronously (which is a mechanism all the major UI frameworks have).

Related

Multi threading analysis techniques

Does anyone know of any analysis techniques that can be used to design/debug thread locking and unlocking sequences? Essentially a technique (like a truth table) I can use to prove that my sequence of locks won't deadlock.
This is not the sort of problem that programming by trial and error works well in.
My particular problem is a read write lock - but I ask this in the general sense. I believe it would be a useful technique to learn if one exists.
I have tried a causal graph in which I have boxes and arrows that I can use to follow the flow of control and that has solved 80% of my problem. But I am still getting occasional deadlocks under stress testing when one thread sneaks though the "gap between instructions" if that makes any sense.
To summarize; what I need is some way of representing the problem so that I can formally analyze the overlap of mutex locks.
Bad news I'm afraid. There are no techniques that I know of that can "prove" that a system that uses locks to control access to shared memory. By "prove" I mean that you cannot demonstrate analytically that a program won't deadlock, livelock, etc.
The problem is that threads run asynchronously. As soon as you start having a sensible number of threads and shared resources, the number of possible sequences of events (e.g. locking/unlocking shared resources) is astronomically high and you cannot model / analyse each and every one of them.
For this reason Communicating Sequential Processes was developed by Tony Hoare, way back in 1978. It is a development of the Actor model which itself goes a long way to resolving the problem.
Actor and CSP
Briefly, in the Actor model data is not communicated via shared memory with a lock. Instead a copy is sent down a communications channel of some sort (e.g. a socket, or pipe) between two threads. This means that you're never locking memory. In effect all memory is private to threads, with copies of it being sent as and when required to other threads. It's a very 'object orientated' thing; private data (thread-owned memory), public interface (messages emitted and received on communications channels). It's also very scalable - pipes can become sockets, threads can become processes on other computers.
The CSP model is just like that, except that the communications channel won't accept a message unless the receiving end is ready to read it.
This addition is crucial - it means that a system design can be analysed algebraically. Indeed Tony Hoare formulated a process calculi for CSP. The Wikipedia page on CSP cites use of this to prove an eCommerce system's design.
So if one is developing a strict CSP system, it is possible to prove analytically that it cannot deadlock, etc.
Real World Experience
I've done many a CSP (or CSP-ish) system, and it's always been good. Instead of doing the maths I've used intuition to help me avoid problems. In effect CSP ensures that if I've gone and built a system that can deadlock, it will deadlock every time. So at least I find it in development, not 2 years later when some network link gets a bit busier than normal.
Real World Options
For Actor model programming there's a lot of options. ZeroMQ, nanomsg, Microsoft's .NET Data Flow library.
They're all pretty good, and with care you can make a system that'll be pretty good. I like ZeroMQ and nanomsg a lot - they make it trivial to split a bunch of threads up into separate processes on separate computers and you've not changed the architecture at all. If absolute performance isn't essential coupling these two up with, for example, Google Protocol Buffers makes for a really tidy system with huge options for incorporating different OSes, languages and systems into your design.
I suspect that MS's DataFlow library for .NET moves owner of references to the data around instead of copying it. That ought to make it pretty performant (though I've not actually tried it to see).
CSP is a bit harder to come by. You can nearly make ZeroMQ and DataFlow into CSP by setting message buffer lengths. Unfortunately you cannot set the buffer length to zero (which is what would make it CSP). MS's documentation even talks about the benefits to system robustness achieved by setting the queue length to 1.
You can synthesize CSP on top of Actor by having flows of synchronisation messages across the links. This is annoying to have to implement.
I've quite often spun up my own comms framework to get a CSP environment.
There's libraries for Java I think, don't know how actively developed they are.
However as you have existing code written around locked shared memory it'll be a tough job to adapt your code. So....
Kernel Shark
If you're on Linux and your kernel has FTRACE compiled in you can use Kernel Shark to see what has happened in your system. Similarly with DTRACE on Solaris, WindView on VxWorks, TATL on MCOS.
What you do is run your system until it stops, and then very quickly preserve the FTRACE log (it gets overwritten in a circular buffer by the OS). You can then see graphically what has happened (turn on Kernel Shark's process view), which may give clues as to what did what and when.
This helps you diagnose your application's deadlock, which may lead you towards getting things right, but ultimately you can never prove that it is correct this way. That doesn't stop you having a Eureka moment where you now know in your bones that you've got it right.
I know of no equivalent of FTRACE / Kernel shark for Windows.
For a broad range of multithreading tasks, we can draw a graph which reflects the order of locking of resources. If that graph has cycles, this means that deadlock is well possible. If there is no cycles, deadlock never occur.
For example, consider the Dining Philosophers task. If each philosopher takes left fork first, and then the right fork, then the graph of order of locking is a ring connecting all the forks. Deadlock is very possible in this situation. However, if one of philosophers changes his order, the ring become a line and deadlock would never occur. If all philosophers change their order and all would take right fork first, the graph again shapes a ring and deadlock is real.

Why is it wrong to access GUI elements from another thread? [duplicate]

This question already has answers here:
Why are most UI frameworks single threaded?
(6 answers)
Closed 7 years ago.
In every GUI library I've used (Swing, Android, Windows Forms, WPF) there's this golden rule saying that one cannot access or modify GUI elements from another thread (other than the GUI thread). I suppose this rule applies to any GUI library. Breaking this rule will most likely cause application to crash. However, I've been wondering recently, why is it so? I couldn't find any profound explanation. So what is the low-level explanation of this rule?
No piece of software is thread-safe unless it is explicitly designed and build to be so.
A GUI is a complex and stateful beast, making it thread-safe would be 'prohibitively expensive'.
There is a very simple reason for this. Usually UI functions are not thread-safe (as making them thread-safe would pessimize performance).
Of those you listed, some may be wrappers around existing mechanisms, so you have to answer the question indirectly via the underlying GUI framework. In case of multi-platform GUI frameworks like e.g. Qt, you will also have the lowest-common denominator that determines what is possible and what isn't.
Now, why is access to the GUI not thread-safe? In the cases where I'm most familiar with (win32 and X11), accesses are often performed indirectly by sending requests and sometimes waiting for the according answer. This usually works in an atomic way, even across process boundaries, so that is not directly cause of the problem. However, if you do so from multiple threads, the worst that can happen is that data is modified in an uncoordinated way. For example, if you read, modify and write the same widget from two threads, these operations might be interleaved, so that only one thread's modifications will actually be applied.
There are other reasons for not supporting cross-thread access:
In win32, the queue with the messages is thread-local, which means that only the thread that created a window will actually find and be able to handle messages for that window. I guess this a legacy from times where processes were single-threaded and the message queue was simply a global. Making it thread-local is the same approach as the one used for making errno thread-safe.
Another reason is that support objects are created inside a process that represent some GUI element. For example, the MFC (on top of win32) use a map from the OS' widget handle to a C++ object representing that object. That map is stored in thread-local storage (which follows the thread-local message queue) and the access to the C++ objects is not guarded by a mutex. Accessing these objects from different threads is bad, not because they represent GUI objects but because they are not synchronized, simple as that.
If you think about modifying the structure of a widget tree (like e.g. the DOM tree in a browser), you either have very detailed knowledge of what other parts of the application are doing or you need to lock access to the whole tree before every operation just to be safe. Needless to say, this effectively prevents any parallel operations, so you can also take the next step and require all operations to come from one thread and thus save the whole multithreading overhead.
That said, I believe that Qt and C# (and probably others) actually do support some cross-thread operations. They will work some (more or less obscure) magic that forwards the calls to the GUI thread and forwards the results back to the calling thread again. In other words, they try to make the necessary inter-thread communication more convenient for the programmer, while retaining the efficiency and simplicity of the single-threaded GUI. This is not restricted to GUI handling though but rather a general approach, only that it is especially important for the GUI.
As far as I know, that is simply not true: Every object in Java might be accesed concurrently, as far as thread-safe techniques are correctly applied. The fact is that Java Swing objects are mostly not prepared for multithreading, so you'll have to perform external synchronization.
There are several instances in which you need several threads to interoperate in a GUI: Games, visual effects, user events...
More information about the GUI and multithreading:
https://docs.oracle.com/javase/tutorial/uiswing/concurrency/dispatch.html

What are some of the core principles needed to master multi-threading using Delphi?

I am kind of new to programming in general (about 8 months with on and off in Delphi and a little Python here and there) and I am in the process of buying some books.
I am interested in learning about concurrent programming and building multi-threaded apps using Delphi. Whenever I do a search for "multithreading Delphi" or "Delphi multithreading tutorial" I seem to get conflicting results as some of the stuff is about using certain libraries (Omnithread library) and other stuff seems to be more geared towards programmers with more experience.
I have studied quite a few books on Delphi and for the most part they seem to kind of skim the surface and not really go into depth on the subject. I have a friend who is a programmer (he uses c++) who recommends I learn what is actually going on with the underlying system when using threads as opposed to jumping into how to actually implement them in my programs first.
On Amazon.com there are quite a few books on concurrent programming but none of them seem to be made with Delphi in mind.
Basically I need to know what are the main things I should be focused on learning before jumping into using threads, if I can/should attempt to learn them using books that are not specifically aimed at Delphi developers (don't want to confuse myself reading books with a bunch of code examples in other languages right now) and if there are any reliable resources/books on the subject that anyone here could recommend.
Short answer
Go to OmnyThreadLibrary install it and read everything on the site.
Longer answer
You asked for some info so here goes:
Here's some stuff to read:
http://delphi.about.com/od/kbthread/Threading_in_Delphi.htm
I personally like: Multithreading - The Delphi Way.
(It's old, but the basics still apply)
Basic principles:
Your basic VCL application is single threaded.
The VCL was not build with multi-threading in mind, rather thread-support is bolted on so that most VCL components are not thread-safe.
The way in which this is done is by making the CPU wait, so if you want a fast application be careful when and how to communicate with the VCL.
Communicating with the VCL
Your basic thread is a decendent of TThread with its own members.
These are per thread variables. As long as you use these you don't have any problems.
My favorite way of communicating with the main window is by using custom windows Messages and postmessage to communicate asynchronically.
If you want to communicate synchronically you will need to use a critical section or a synchonize method.
See this article for example: http://edn.embarcadero.com/article/22411
Communicating between threads
This is where things get tricky, because you can run into all sorts of hard to debug synchonization issues.
My advice: use OmnithreadLibrary, also see this question: Cross thread communication in Delphi
Some people will tell you that reading and writing integers is atomic on x86, but this is not 100% true, so don't use those in a naive way, because you'll most likely get subtle issues wrong and end up with hard to debug code.
Starting and stopping threads
In old Delphi versions Thread.suspend and Thread.resume were used, however these are no longer recommended and should be avoided (in the context of thread synchronization).
See this question: With what delphi Code should I replace my calls to deprecated TThread method Suspend?
Also have a look at this question although the answers are more vague: TThread.resume is deprecated in Delphi-2010 what should be used in place?
You can use suspend and resume to pause and restart threads, just don't use them for thread synchronization.
Performance issues
Putting wait_for... , synchonize etc code in your thread effectively stops your thread until the action it's waiting for has occured.
In my opinion this defeats a big purpose of threads: speed
So if you want to be fast you'll have to get creative.
A long time ago I wrote an application called Life32.
Its a display program for conways game of life. That can generate patterns very fast (millions of generations per second on small patterns).
It used a separate thread for calculation and a separate thread for display.
Displaying is a very slow operation that does not need to be done every generation.
The generation thread included display code that removes stuff from the display (when in view) and the display thread simply sets a boolean that tells the generation thread to also display the added stuff.
The generation code writes directly to the video memory using DirectX, no VCL or Windows calls required and no synchronization of any kind.
If you move the main window the application will keep on displaying on the old location until you pause the generation, thereby stopping the generation thread, at which point it's safe to update the thread variables.
If the threads are not 100% synchronized the display happens a generation too late, no big deal.
It also features a custom memory manager that avoids the thread-safe slowness that's in the standard memory manager.
By avoiding any and all forms of thread synchronization I was able to eliminate the overhead from 90%+ (on smallish patterns) to 0.
You really shouldn't get me started on this, but anyway, my suggestions:
Try hard to not use the following:
TThread.Synchronize
TThread.WaitFor
TThread.OnTerminate
TThread.Suspend
TThread.Resume, (except at the end of constructors in some Delphi versions)
TApplication.ProcessMessages
Use the PostMessage API to communicate to the main thread - post objects in lParam, say.
Use a producer-consumer queue to communicate to secondary threads, (not a Windows message queue - only one thread can wait on a WMQ, making thread pooling impossible).
Do not write directly from one thread to fields in another - use message-passing.
Try very hard indeed to create threads at application startup and to not explicitly terminate them at all.
Do use object pools instead of continually creating and freeing objects for inter-thread communication.
The result will be an app that performs well, does not leak, does not deadlock and shuts down immediately when you close the main form.
What Delphi should have had built-in:
TWinControl.PostObject(anObject:TObject) and TWinControl.OnObjectRx(anObject:TObject) - methods to post objects from a secondary thread and fire a main-thread event with them. A trivial PostMessage wrap to replace the poor performing, deadlock-generating, continually-rewritten TThread.Synchronize.
A simple, unbounded producer-consumer class that actually works for multiple producers/consumers. This is, like, 20 lines of TObjectQueue descendant but Borland/Embarcadero could not manage it. If you have object pools, there is no need for complex bounded queues.
A simple thread-safe, blocking, object pool class - again, really simple with Delphi since it has class variables and virtual constructors, eg. creating a lot of buffer objects:
myPool:=TobjectPool.create(1024,TmyBuffer);
I thought it might be useful to actually try to compile a list of things that one should know about multithreading.
Synchronization primitives: mutexes, semaphores, monitors
Delphi implementations of synchronization primitives: TCriticalSection, TMREWSync, TEvent
Atomic operations: some knowledge about what operations are atomic and what not (discussed in this question)
Windows API multithreading capabilities: InterlockedIncrement, InterlockedExchange, ...
OmniThreadLibrary
Of course this is far from complete. I made this community wiki so that everyone can edit.
Appending to all the other answers I strongly suggest reading a book like:
"Modern Operating Systems" or any other one going into multithreading details.
This seems to be an overkill but it would make you a better programmer and
you defenitely get a very good insight
into threading/processes in an abstract way - so you learn why and how to
use critical section or semaphores on examples (like the
dining philosophers problem or the sleeping barber problem)

Why might threads be considered "evil"?

I was reading the SQLite FAQ, and came upon this passage:
Threads are evil. Avoid them.
I don't quite understand the statement "Thread are evil". If that is true, then what is the alternative?
My superficial understanding of threads is:
Threads make concurrence happen. Otherwise, the CPU horsepower will be wasted, waiting for (e.g.) slow I/O.
But the bad thing is that you must synchronize your logic to avoid contention and you have to protect shared resources.
Note: As I am not familiar with threads on Windows, I hope the discussion will be limited to Linux/Unix threads.
When people say that "threads are evil", the usually do so in the context of saying "processes are good". Threads implicitly share all application state and handles (and thread locals are opt-in). This means that there are plenty of opportunities to forget to synchronize (or not even understand that you need to synchronize!) while accessing that shared data.
Processes have separate memory space, and any communication between them is explicit. Furthermore, primitives used for interprocess communication are often such that you don't need to synchronize at all (e.g. pipes). And you can still share state directly if you need to, using shared memory, but that is also explicit in every given instance. So there are fewer opportunities to make mistakes, and the intent of the code is more explicit.
Simple answer the way I understand it...
Most threading models use "shared state concurrency," which means that two execution processes can share the same memory at the same time. If one thread doesn't know what the other is doing, it can modify the data in a way that the other thread doesn't expect. This causes bugs.
Threads are "evil" because you need to wrap your mind around n threads all working on the same memory at the same time, and all of the fun things that go with it (deadlocks, racing conditions, etc).
You might read up about the Clojure (immutable data structures) and Erlang (message passsing) concurrency models for alternative ideas on how to achieve similar ends.
What makes threads "evil" is that once you introduce more than one stream of execution into your program, you can no longer count on your program to behave in a deterministic manner.
That is to say: Given the same set of inputs, a single-threaded program will (in most cases) always do the same thing.
A multi-threaded program, given the same set of inputs, may well do something different every time it is run, unless it is very carefully controlled. That is because the order in which the different threads run different bits of code is determined by the OS's thread scheduler combined with a system timer, and this introduces a good deal of "randomness" into what the program does when it runs.
The upshot is: debugging a multi-threaded program can be much harder than debugging a single-threaded program, because if you don't know what you are doing it can be very easy to end up with a race condition or deadlock bug that only appears (seemingly) at random once or twice a month. The program will look fine to your QA department (since they don't have a month to run it) but once it's out in the field, you'll be hearing from customers that the program crashed, and nobody can reproduce the crash.... bleah.
To sum up, threads aren't really "evil", but they are strong juju and should not be used unless (a) you really need them and (b) you know what you are getting yourself into. If you do use them, use them as sparingly as possible, and try to make their behavior as stupid-simple as you possibly can. Especially with multithreading, if anything can go wrong, it (sooner or later) will.
I would interpret it another way. It's not that threads are evil, it's that side-effects are evil in a multithreaded context (which is a lot less catchy to say).
A side effect in this context is something that affects state shared by more than one thread, be it global or just shared. I recently wrote a review of Spring Batch and one of the code snippets used is:
private static Map<Long, JobExecution> executionsById = TransactionAwareProxyFactory.createTransactionalMap();
private static long currentId = 0;
public void saveJobExecution(JobExecution jobExecution) {
Assert.isTrue(jobExecution.getId() == null);
Long newId = currentId++;
jobExecution.setId(newId);
jobExecution.incrementVersion();
executionsById.put(newId, copy(jobExecution));
}
Now there are at least three serious threading issues in less than 10 lines of code here. An example of a side effect in this context would be updating the currentId static variable.
Functional programming (Haskell, Scheme, Ocaml, Lisp, others) tend to espouse "pure" functions. A pure function is one with no side effects. Many imperative languages (eg Java, C#) also encourage the use of immutable objects (an immutable object is one whose state cannot change once created).
The reason for (or at least the effect of) both of these things is largely the same: they make multithreaded code much easier. A pure function by definition is threadsafe. An immutable object by definition is threadsafe.
The advantage processes have is that there is less shared state (generally). In traditional UNIX C programming, doing a fork() to create a new process would result in shared process state and this was used as a means of IPC (inter-process communication) but generally that state is replaced (with exec()) with something else.
But threads are much cheaper to create and destroy and they take less system resources (in fact, the operating itself may have no concept of threads yet you can still create multithreaded programs). These are called green threads.
The paper you linked to seems to explain itself very well. Did you read it?
Keep in mind that a thread can refer to the programming-language construct (as in most procedural or OOP languages, you create a thread manually, and tell it to executed a function), or they can refer to the hardware construct (Each CPU core executes one thread at a time).
The hardware-level thread is obviously unavoidable, it's just how the CPU works. But the CPU doesn't care how the concurrency is expressed in your source code. It doesn't have to be by a "beginthread" function call, for example. The OS and the CPU just have to be told which instruction threads should be executed.
His point is that if we used better languages than C or Java with a programming model designed for concurrency, we could get concurrency basically for free. If we'd used a message-passing language, or a functional one with no side-effects, the compiler would be able to parallelize our code for us. And it would work.
Threads aren't any more "evil" than hammers or screwdrivers or any other tools; they just require skill to utilize. The solution isn't to avoid them; it's to educate yourself and up your skill set.
Creating a lot of threads without constraint is indeed evil.. using a pooling mechanisme (threadpool) will mitigate this problem.
Another way threads are 'evil' is that most framework code is not designed to deal with multiple threads, so you have to manage your own locking mechanisme for those datastructures.
Threads are good, but you have to think about how and when you use them and remember to measure if there really is a performance benefit.
A thread is a bit like a light weight process. Think of it as an independent path of execution within an application. The thread runs in the same memory space as the application and therefore has access to all the same resources, global objects and global variables.
The good thing about them: you can parallelise a program to improve performance. Some examples, 1) In an image editing program a thread may run the filter processing independently of the GUI. 2) Some algorithms lend themselves to multiple threads.
Whats bad about them? if a program is poorly designed they can lead to deadlock issues where both threads are waiting on each other to access the same resource. And secondly, program design can me more complex because of this. Also, some class libraries don't support threading. e.g. the c library function "strtok" is not "thread safe". In other words, if two threads were to use it at the same time they would clobber each others results. Fortunately, there are often thread safe alternatives... e.g. boost library.
Threads are not evil, they can be very useful indeed.
Under Linux/Unix, threading hasn't been well supported in the past although I believe Linux now has Posix thread support and other unices support threading now via libraries or natively. i.e. pthreads.
The most common alternative to threading under Linux/Unix platforms is fork. Fork is simply a copy of a program including it's open file handles and global variables. fork() returns 0 to the child process and the process id to the parent. It's an older way of doing things under Linux/Unix but still well used. Threads use less memory than fork and are quicker to start up. Also, inter process communications is more work than simple threads.
In a simple sense you can think of a thread as another instruction pointer in the current process. In other words it points the IP of another processor to some code in the same executable. So instead of having one instruction pointer moving through the code there are two or more IP's executing instructions from the same executable and address space simultaneously.
Remember the executable has it's own address space with data / stack etc... So now that two or more instructions are being executed simultaneously you can imagine what happens when more than one of the instructions wants to read/write to the same memory address at the same time.
The catch is that threads are operating within the process address space and are not afforded protection mechanisms from the processor that full blown processes are. (Forking a process on UNIX is standard practice and simply creates another process.)
Out of control threads can consume CPU cycles, chew up RAM, cause execeptions etc.. etc.. and the only way to stop them is to tell the OS process scheduler to forcibly terminate the thread by nullifying it's instruction pointer (i.e. stop executing). If you forcibly tell a CPU to stop executing a sequence of instructions what happens to the resources that have been allocated or are being operated on by those instructions? Are they left in a stable state? Are they properly freed? etc...
So, yes, threads require more thought and responsibility than executing a process because of the shared resources.
For any application that requires stable and secure execution for long periods of time without failure or maintenance, threads are always a tempting mistake. They invariably turn out to be more trouble than they are worth. They produce rapid results and prototypes that seem to be performing correctly but after a couple weeks or months running you discover that they have critical flaws.
As mentioned by another poster, once you use even a single thread in your program you have now opened a non-deterministic path of code execution that can produce an almost infinite number of conflicts in timing, memory sharing and race conditions. Most expressions of confidence in solving these problems are expressed by people who have learned the principles of multithreaded programming but have yet to experience the difficulties in solving them.
Threads are evil. Good programmers avoid them wherever humanly possible. The alternative of forking was offered here and it is often a good strategy for many applications. The notion of breaking your code down into separate execution processes which run with some form of loose coupling often turns out to be an excellent strategy on platforms that support it. Threads running together in a single program is not a solution. It is usually the creation of a fatal architectural flaw in your design that can only be truly remedied by rewriting the entire program.
The recent drift towards event oriented concurrency is an excellent development innovation. These kinds of programs usually prove to have great endurance after they are deployed.
I've never met a young engineer who didn't think threads were great. I've never met an older engineer who didn't shun them like the plague.
Being an older engineer, I heartily agree with the answer by Texas Arcane.
Threads are very evil because they cause bugs that are extremely difficult to solve. I have literally spent months solving sporadic race-conditions. One example caused trams to suddenly stop about once a month in the middle of the road and block traffic until towed away. Luckily I didn't create the bug, but I did get to spend 4 months full-time to solve it...
It's a tad late to add to this thread, but I would like to mention a very interesting alternative to threads: asynchronous programming with co-routines and event loops. This is being supported by more and more languages, and does not have the problem of race conditions like multi-threading has.
It can replace multi-threading in cases where it is used to wait on events from multiple sources, but not where calculations need to be performed in parallel on multiple CPU cores.

When is multi-threading not a good idea? [closed]

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I was recently working on an application that sent and received messages over Ethernet and Serial. I was then tasked to add the monitoring of DIO discretes. I throught,
"No reason to interrupt the main
thread which is involved in message
processing, I'll just create
another thread that monitors DIO."
This decision, however, proved to be poor. Sometimes the main thread would be interrupted between a Send and a Receive serial message. This interruption would disrupt the timing and alas, messages would be lost (forever).
I found another way to monitor the DIO without using another thread and Ethernet and Serial communication were restored to their correct functionality.
The whole fiasco, however, got me thinking. Are their any general guidelines about when not to use multiple-threads and/or does anyone have anymore examples of situations when using multiple-threads is not a good idea?
**EDIT:Based on your comments and after scowering the internet for information, I have composed a blog post entitled When is multi-threading not a good idea?
On a single processor machine and a desktop application, you use multi threads so you don't freeze the app but for nothing else really.
On a single processor server and a web based app, no need for multi threading because the web server handles most of it.
On a multi-processor machine and desktop app, you are suggested to use multi threads and parallel programming. Make as many threads as there are processors.
On a multi-processor server and a web based app, no need again for multi threads because the web server handles it.
In total, if you use multiple threads for other than un-freezing desktop apps and any other generic answer, you will make the app slower if you have a single core machine due to the threads interrupting each other.
Why? Because of the hardware switches. It takes time for the hardware to switch between threads in total. On a multi-core box, go ahead and use 1 thread for each core and you will greatly see a ramp up.
To paraphrase an old quote: A programmer had a problem. He thought, "I know, I'll use threads." Now the programmer has two problems. (Often attributed to JWZ, but it seems to predate his use of it talking about regexes.)
A good rule of thumb is "Don't use threads, unless there's a very compelling reason to use threads." Multiple threads are asking for trouble. Try to find a good way to solve the problem without using multiple threads, and only fall back to using threads if avoiding it is as much trouble as the extra effort to use threads. Also, consider switching to multiple threads if you're running on a multi-core/multi-CPU machine, and performance testing of the single threaded version shows that you need the performance of the extra cores.
Multi-threading is a bad idea if:
Several threads access and update the same resource (set a variable, write to a file), and you don't understand thread safety.
Several threads interact with each other and you don't understand mutexes and similar thread-management tools.
Your program uses static variables (threads typically share them by default).
You haven't debugged concurrency issues.
Actually, multi threading is not scalable and is hard to debug, so it should not be used in any case if you can avoid it. There is few cases where it is mandatory : when performance on a multi CPU matters, or when you deal whith a server that have a lot of clients taking a long time to answer.
In any other cases, you can use alternatives such as queue + cron jobs or else.
You might want to take a look at the Dan Kegel's "The C10K problem" web page about handling multiple data sources/sinks.
Basically it is best to use minimal threads, which in sockets can be done in most OS's w/ some event system (or asynchronously in Windows using IOCP).
When you run into the case where the OS and/or libraries do not offer a way to perform communication in a non-blocking manner, it is best to use a thread-pool to handle them while reporting back to the same event loop.
Example diagram of layout:
Per CPU [*] EVENTLOOP ------ Handles nonblocking I/O using OS/library utilities
| \___ Threadpool for various blocking events
Threadpool for handling the I/O messages that would take long
Multithreading is bad except in the single case where it is good. This case is
The work is CPU Bound, or parts of it is CPU Bound
The work is parallelisable.
If either or both of these conditions are missing, multithreading is not going to be a winning strategy.
If the work is not CPU bound, then you are waiting not on threads to finish work, but rather for some external event, such as network activity, for the process to complete its work. Using threads, there is the additional cost of context switches between threads, The cost of synchronization (mutexes, etc), and the irregularity of thread preemption. The alternative in most common use is asynchronous IO, in which a single thread listens to several io ports, and acts on whichever happens to be ready now, one at a time. If by some chance these slow channels all happen to become ready at the same time, It might seem like you will experience a slow-down, but in practice this is rarely true. The cost of handling each port individually is often comparable or better than the cost of synchronizing state on multiple threads as each channel is emptied.
Many tasks may be compute bound, but still not practical to use a multithreaded approach because the process must synchronise on the entire state. Such a program cannot benefit from multithreading because no work can be performed concurrently. Fortunately, most programs that require enormous amounts of CPU can be parallelized to some level.
Multi-threading is not a good idea if you need to guarantee precise physical timing (like in your example). Other cons include intensive data exchange between threads. I would say multi-threading is good for really parallel tasks if you don't care much about their relative speed/priority/timing.
A recent application I wrote that had to use multithreading (although not unbounded number of threads) was one where I had to communicate in several directions over two protocols, plus monitoring a third resource for changes. Both protocol libraries required a thread to run the respective event loop in, and when those were accounted for, it was easy to create a third loop for the resource monitoring. In addition to the event loop requirements, the messages going through the wires had strict timing requirements, and one loop couldn't be risked blocking the other, something that was further alleviated by using a multicore CPU (SPARC).
There were further discussions on whether each message processing should be considered a job that was given to a thread from a thread pool, but in the end that was an extension that wasn't worth the work.
All-in-all, threads should if possible only be considered when you can partition the work into well defined jobs (or series of jobs) such that the semantics are relatively easy to document and implement, and you can put an upper bound on the number of threads you use and that need to interact. Systems where this is best applied are almost message passing systems.
In priciple everytime there is no overhead for the caller to wait in a queue.
A couple more possible reasons to use threads:
Your platform lacks asynchronous I/O operations, e.g. Windows ME (No completion ports or overlapped I/O, a pain when porting XP applications that use them.) Java 1.3 and earlier.
A third-party library function that can hang, e.g. if a remote server is down, and the library provides no way to cancel the operation and you can't modify it.
Keeping a GUI responsive during intensive processing doesn't always require additional threads. A single callback function is usually sufficient.
If none of the above apply and I still want parallelism for some reason, I prefer to launch an independent process if possible.
I would say multi-threading is generally used to:
Allow data processing in the background while a GUI remains responsive
Split very big data analysis onto multiple processing units so that you can get your results quicker.
When you're receiving data from some hardware and need something to continuously add it to a buffer while some other element decides what to do with it (write to disk, display on a GUI etc.).
So if you're not solving one of those issues, it's unlikely that adding threads will make your life easier. In fact it'll almost certainly make it harder because as others have mentioned; debugging mutithreaded applications is considerably more work than a single threaded solution.
Security might be a reason to avoid using multiple threads (over multiple processes). See Google chrome for an example of multi-process safety features.
Multi-threading is scalable, and will allow your UI to maintain its responsivness while doing very complicated things in the background. I don't understand where other responses are acquiring their information on multi-threading.
When you shouldn't multi-thread is a mis-leading question to your problem. Your problem is this: Why did multi-threading my application cause serial / ethernet communications to fail?
The answer to that question will depend on the implementation, which should be discussed in another question. I know for a fact that you can have both ethernet and serial communications happening in a multi-threaded application at the same time as numerous other tasks without causing any data loss.
The one reason to not use multi-threading is:
There is one task, and no user interface with which the task will interfere.
The reasons to use mutli-threading are:
Provides superior responsiveness to the user
Performs multiple tasks at the same time to decrease overall execution time
Uses more of the current multi-core CPUs, and multi-multi-cores of the future.
There are three basic methods of multi-threaded programming that make thread safety implemented with ease - you only need to use one for success:
Thread Safe Data types passed between threads.
Thread Safe Methods in the threaded object to modify data passed between.
PostMessage capabilities to communicate between threads.
Are the processes parallel? Is performance a real concern? Are there multiple 'threads' of execution like on a web server? I don't think there is a finite answer.
A common source of threading issues is the usual approaches employed to synchronize data. Having threads share state and then implement locking at all the appropriate places is a major source of complexity for both design and debugging. Getting the locking right to balance stability, performance, and scalability is always a hard problem to solve. Even the most experienced experts get it wrong frequently. Alternative techniques to deal with threading can alleviate much of this complexity. The Clojure programming language implements several interesting techniques for dealing with concurrency.

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