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I'm reading up on concurrency. I've got a bit over my head with terms that have confusingly similar definitions. Namely:
Processes
Threads
"Green threads"
Protothreads
Fibers
Coroutines
"Goroutines" in the Go language
My impression is that the distinctions rest on (1) whether truly parallel or multiplexed; (2) whether managed at the CPU, at the OS, or in the program; and (3..5) a few other things I can't identify.
Is there a succinct and unambiguous guide to the differences between these approaches to parallelism?
OK, I'm going to do my best. There are caveats everywhere, but I'm going to do my best to give my understanding of these terms and references to something that approximates the definition I've given.
Process: OS-managed (possibly) truly concurrent, at least in the presence of suitable hardware support. Exist within their own address space.
Thread: OS-managed, within the same address space as the parent and all its other threads. Possibly truly concurrent, and multi-tasking is pre-emptive.
Green Thread: These are user-space projections of the same concept as threads, but are not OS-managed. Probably not truly concurrent, except in the sense that there may be multiple worker threads or processes giving them CPU time concurrently, so probably best to consider this as interleaved or multiplexed.
Protothreads: I couldn't really tease a definition out of these. I think they are interleaved and program-managed, but don't take my word for it. My sense was that they are essentially an application-specific implementation of the same kind of "green threads" model, with appropriate modification for the application domain.
Fibers: OS-managed. Exactly threads, except co-operatively multitasking, and hence not truly concurrent.
Coroutines: Exactly fibers, except not OS-managed.
Goroutines: They claim to be unlike anything else, but they seem to be exactly green threads, as in, process-managed in a single address space and multiplexed onto system threads. Perhaps somebody with more knowledge of Go can cut through the marketing material.
It's also worth noting that there are other understandings in concurrency theory of the term "process", in the process calculus sense. This definition is orthogonal to those above, but I just thought it worth mentioning so that no confusion arises should you see process used in that sense somewhere.
Also, be aware of the difference between parallel and concurrent. It's possible you were using the former in your question where I think you meant the latter.
I mostly agree with Gian's answer, but I have different interpretations of a few concurrency primitives. Note that these terms are often used inconsistently by different authors. These are my favorite definitions (hopefully not too far from the modern consensus).
Process:
OS-managed
Each has its own virtual address space
Can be interrupted (preempted) by the system to allow another process to run
Can run in parallel with other processes on different processors
The memory overhead of processes is high (includes virtual memory tables, open file handles, etc)
The time overhead for creating and context switching between processes is relatively high
Threads:
OS-managed
Each is "contained" within some particular process
All threads in the same process share the same virtual address space
Can be interrupted by the system to allow another thread to run
Can run in parallel with other threads on different processors
The memory and time overheads associated with threads are smaller than processes, but still non-trivial
(For example, typically context switching involves entering the kernel and invoking the system scheduler.)
Cooperative Threads:
May or may not be OS-managed
Each is "contained" within some particular process
In some implementations, each is "contained" within some particular OS thread
Cannot be interrupted by the system to allow a cooperative peer to run
(The containing process/thread can still be interrupted, of course)
Must invoke a special yield primitive to allow peer cooperative threads to run
Generally cannot be run in parallel with cooperative peers
(Though some people think it's possible: http://ocm.dreamhosters.com/.)
There are lots of variations on the cooperative thread theme that go by different names:
Fibers
Green threads
Protothreads
User-level threads (user-level threads can be interruptable/preemptive, but that's a relatively unusual combination)
Some implementations of cooperative threads use techniques like split/segmented stacks or even individually heap-allocating every call frame to reduce the memory overhead associated with pre-allocating a large chunk of memory for the stack
Depending on the implementation, calling a blocking syscall (like reading from the network or sleeping) will either cause a whole group of cooperative threads to block or implicitly cause the calling thread to yield
Coroutines:
Some people use "coroutine" and "cooperative thread" more or less synonymously
I do not prefer this usage
Some coroutine implementations are actually "shallow" cooperative threads; yield can only be invoked by the "coroutine entry procedure"
The shallow (or semi-coroutine) version is easier to implement than threads, because each coroutine does not need a complete stack (just one frame for the entry procedure)
Often coroutine frameworks have yield primitives that require the invoker to explicitly state which coroutine control should transfer to
Generators:
Restricted (shallow) coroutines
yield can only return control back to whichever code invoked the generator
Goroutines:
An odd hybrid of cooperative and OS threads
Cannot be interrupted (like cooperative threads)
Can run in parallel on a language runtime-managed pool of OS threads
Event handlers:
Procedures/methods that are invoked by an event dispatcher in response to some action happening
Very popular for user interface programming
Require little to no language/system support; can be implemented in a library
At most one event handler can be running at a time; the dispatcher must wait for a handler to finish (return) before starting the next
Makes synchronization relatively simple; different handler executions never overlap in time
Implementing complex tasks with event handlers tends to lead to "inverted control flow"/"stack ripping"
Tasks:
Units of work that are doled out by a manager to a pool of workers
The workers can be threads, processes or machines
Of course the kind of worker a task library uses has a significant impact on how one implements the tasks
In this list of inconsistently and confusingly used terminology, "task" takes the crown. Particularly in the embedded systems community, "task" is sometimes used to mean "process", "thread" or "event handler" (usually called an "interrupt service routine"). It is also sometimes used generically/informally to refer to any kind of unit of computation.
One pet peeve that I can't stop myself from airing: I dislike the use of the phrase "true concurrency" for "processor parallelism". It's quite common, but I think it leads to much confusion.
For most applications, I think task-based frameworks are best for parallelization. Most of the popular ones (Intel's TBB, Apple's GCD, Microsoft's TPL & PPL) use threads as workers. I wish there were some good alternatives that used processes, but I'm not aware of any.
If you're interested in concurrency (as opposed to processor parallelism), event handlers are the safest way to go. Cooperative threads are an interesting alternative, but a bit of a wild west. Please do not use threads for concurrency if you care about the reliability and robustness of your software.
Protothreads are just a switch case implementation that acts like a state machine but makes implementation of the software a whole lot simpler. It is based around idea of saving a and int value before a case label and returning and then getting back to the point after the case by reading back that variable and using switch to figure out where to continue. So protothread are a sequential implementation of a state machine.
Protothreads are great when implementing sequential state machines. Protothreads are not really threads at all, but rather a syntax abstraction that makes it much easier to write a switch/case state machine that has to switch states sequentially (from one to the next etc..).
I have used protothreads to implement asynchronous io: http://martinschroder.se/asynchronous-io-using-protothreads/
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.
Separating different parts of a program into different processes seems (to me) to make a more elegant program than just threading everything. In what scenario would it make sense to make things run on a thread vs. separating the program into different processes? When should I use a thread?
Edit
Anything on how (or if) they act differently with single-core and multi-core would also be helpful.
You'd prefer multiple threads over multiple processes for two reasons:
Inter-thread communication (sharing data etc.) is significantly simpler to program than inter-process communication.
Context switches between threads are faster than between processes. That is, it's quicker for the OS to stop one thread and start running another than do the same with two processes.
Example:
Applications with GUIs typically use one thread for the GUI and others for background computation. The spellchecker in MS Office, for example, is a separate thread from the one running the Office user interface. In such applications, using multiple processes instead would result in slower performance and code that's tough to write and maintain.
Well apart from advantages of using thread over process, like:
Advantages:
Much quicker to create a thread than
a process.
Much quicker to switch
between threads than to switch
between processes.
Threads share data
easily
Consider few disadvantages too:
No security between threads.
One thread can stomp on another thread's
data.
If one thread blocks, all
threads in task block.
As to the important part of your question "When should I use a thread?"
Well you should consider few facts that a threads should not alter the semantics of a program. They simply change the timing of operations. As a result, they are almost always used as an elegant solution to performance related problems. Here are some examples of situations where you might use threads:
Doing lengthy processing: When a windows application is calculating it cannot process any more messages. As a result, the display cannot be updated.
Doing background processing: Some
tasks may not be time critical, but
need to execute continuously.
Doing I/O work: I/O to disk or to
network can have unpredictable
delays. Threads allow you to ensure
that I/O latency does not delay
unrelated parts of your application.
I assume you already know you need a thread or a process, so I'd say the main reason to pick one over the other would be data sharing.
Use of a process means you also need Inter Process Communication (IPC) to get data in and out of the process. This is a good thing if the process is to be isolated though.
You sure don't sound like a newbie. It's an excellent observation that processes are, in many ways, more elegant. Threads are basically an optimization to avoid too many transitions or too much communication between memory spaces.
Superficially using threads may also seem like it makes your program easier to read and write, because you can share variables and memory between the threads freely. In practice, doing that requires very careful attention to avoid race conditions or deadlocks.
There are operating-system kernels (most notably L4) that try very hard to improve the efficiency of inter-process communication. For such systems one could probably make a convincing argument that threads are pointless.
I would like to answer this in a different way. "It depends on your application's working scenario and performance SLA" would be my answer.
For instance threads may be sharing the same address space and communication between threads may be faster and easier but it is also possible that under certain conditions threads deadlock and then what do you think would happen to your process.
Even if you are a programming whiz and have used all the fancy thread synchronization mechanisms to prevent deadlocks it certainly is not rocket science to see that unless a deterministic model is followed which may be the case with hard real time systems running on Real Time OSes where you have a certain degree of control over thread priorities and can expect the OS to respect these priorities it may not be the case with General Purpose OSes like Windows.
From a Design perspective too you might want to isolate your functionality into independent self contained modules where they may not really need to share the same address space or memory or even talk to each other. This is a case where processes will make sense.
Take the case of Google Chrome where multiple processes are spawned as opposed to most browsers which use a multi-threaded model.
Each tab in Chrome can be talking to a different server and rendering a different website. Imagine what would happen if one website stopped responding and if you had a thread stalled due to this, the entire browser would either slow down or come to a stop.
So Google decided to spawn multiple processes and that is why even if one tab freezes you can still continue using other tabs of your Chrome browser.
Read more about it here
and also look here
I agree to most of the answers above. But speaking from design perspective i would rather go for a thread when i want set of logically co-related operations to be carried out parallel. For example if you run a word processor there will be one thread running in foreground as an editor and other thread running in background auto saving the document at regular intervals so no one would design a process to do that auto saving task separately.
In addition to the other answers, maintaining and deploying a single process is a lot simpler than having a few executables.
One would use multiple processes/executables to provide a well-defined interface/decoupling so that one part or the other can be reused or reimplemented more easily than keeping all the functionality in one process.
Came across this post. Interesting discussion. but I felt one point is missing or indirectly pointed.
Creating a new process is costly because of all of the
data structures that must be allocated and initialized. The process is subdivided into different threads of control to achieve multithreading inside the process.
Using a thread or a process to achieve the target is based on your program usage requirements and resource utilization.
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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.
On a small embedded system project we have some code which we would like to run in a thread so we are electing to build in top of an embedded RTOS (eCos).
Previously, we have used a cyclic executive in main() that drove tasks each implemented as a state machine. For some tasks we encountered problems where the task would need to be broken up into many fine grained states thus making the code extra complex.
When switching to an RTOS we found the memory usage for each thread's stack adds up quickly if we give each separate task it's own thread. (we only have 64k and need the memory for our communications buffers)
We are considering using a tread for our communications task and an other thread for a cyclic executive. The cyclic executive will drive the other logical tasks.
Does it make sense to mix an RTOS and cyclic executive like this?
This is a perfectly valid design.
In one of our product, we used a similar design, where the asynchronous I/O channels (TCP/IP, 2 serial streams) were in their own tasks and we had a "main" task which would be responsible for multiple areas of functionality.
Think of tasks as simply a partitioning mechanism that allows you to simplify your design.
Yes, having a cyclic executive in one OS thread running multiple 'tasks' can make sense. In fact unless two tasks conflict with scheduling needs (one needs to block, one is higher priority than the other and the low-priority one takes a long time to execute, etc.), I'd recommend putting them in the same thread.
This is especially true in the case where you are using a light-weight RTOS with no memory protection: separate threads aren't any safer than one thread (no MMU protection of address spaces), in fact they are potentially more dangerous because of the greater need for concurrency protection. Even if your IPC scheme is robust and not susceptible to misuse by programmers, it's overhead is usually non-zero, so avoiding the need for it can result in performance gains.
If you look at FreeRTOS, they actually run another scheduler in a task, sort of :)
And to echo others, nothing sounds wrong in the design. No reason (some of) your tasks can't be state machines if there's a clear way to express something that way.
It is a valid design, but I think I missed the reason for having the OS at all.
What facilities of the OS are you planning to use?
From the information available it seems that you will end up moving the complexity of the tasks to your new main loop.