How do you make your application multithreaded ?
Do you use asynch functions ?
or do you spawn a new thread ?
I think that asynch functions are already spawning a thread so if your job is doing just some file reading, being lazy and just spawning your job on a thread would just "waste" ressources...
So is there some kind of design when using thread or asynch functions ?
If you are talking about .Net, then don't forget the ThreadPool. The thread pool is also what asynch functions often use. Spawning to much threads can actually hurt your performance. A thread pool is designed to spawn just enough threads to do the work the fastest. So do use a thread pool instead of spwaning your own threads, unless the thread pool doesn't meet your needs.
PS: And keep an eye out on the Parallel Extensions from Microsoft
Spawning threads is only going to waste resources if you start spawning tons of them, one or two extra threads isn't going to effect the platforms proformance, infact System currently has over 70 threads for me, and msn is using 32 (I really have no idea how a messenger can use that many threads, exspecialy when its minimised and not really doing anything...)
Useualy a good time to spawn a thread is when something will take a long time, but you need to keep doing something else.
eg say a calculation will take 30 seconds. The best thing to do is spawn a new thread for the calculation, so that you can continue to update the screen, and handle any user input because users will hate it if your app freezes untill its finished doing the calculation.
On the other hand, creating threads to do something that can be done almost instantly is nearly pointless, since the overhead of creating (or even just passing work to an existing thread using a thread pool) will be higher than just doing the job in the first place.
Sometimes you can break your app into a couple of seprate parts which run in their own threads. For example in games the updates/physics etc may be one thread, while grahpics are another, sound/music is a third, and networking is another. The problem here is you really have to think about how these parts will interact or else you may have worse proformance, bugs that happen seemingly "randomly", or it may even deadlock.
I'll second Fire Lancer's answer - creating your own threads is an excellent way to process big tasks or to handle a task that would otherwise be "blocking" to the rest of synchronous app, but you have to have a clear understanding of the problem that you must solve and develope in a way that clearly defines the task of a thread, and limits the scope of what it does.
For an example I recently worked on - a Java console app runs periodically to capture data by essentially screen-scraping urls, parsing the document with DOM, extracting data and storing it in a database.
As a single threaded application, it, as you would expect, took an age, averaging around 1 url a second for a 50kb page. Not too bad, but when you scale out to needing to processes thousands of urls in a batch, it's no good.
Profiling the app showed that most of the time the active thread was idle - it was waiting for I/O operations - opening of a socket to the remote URL, opening a connection to the database etc. It's this sort of situation that can easily be improved with multithreading. Rewriting to be multi-threaded and with just 5 threads instead of one, even on a single core cpu, gave an increase in throughput of over 20 times.
In this example, each "worker" thread was explicitly limited to what it did - open the remote a remote url, parse the data, store it in the db. All the "high level" processing - generating the list of urls to parse, working out which next, handling errors, all remained with the control of the main thread.
The use of threads makes you think more about the way your application needs threading and can in the long run make it easier to improve / control your performance.
Async methods are faster to use but they are a bit magic - a lot of things happen to make them possible - so it's probable that at some point you will need something that they can't give you. Then you can try and roll some custom threading code.
It all depends on your needs.
The answer is "it depends".
It depends on what you're trying to achieve. I'm going to assume that you're aiming for more performance.
The simplest solution is to find another way to improve your performance. Run a profiler. Look for hot spots. Reduce unnecessary IO.
The next solution is to break your program into multiple processes, each of which can run in their own address space. This is easiest because there is no chance of the individual processes messing each other up.
The next solution is to use threads. At this point you're opening a major can of worms, so start small, and only multi-thread the critical path of the code.
The next solution is to use asynch IO. Generally only recommended for people writing some of very heavily loaded server, and even then I would rather re-use one of the existing frameworks that abstract away the details e.g. the C++ framework ICE, or an EJB server under java.
Note that each of these solutions has multiple sub-solutions - there are different breeds of threads and different kinds of asynch IO, each with slightly different performance characteristics, but again, it's generally best to let the framework handle it for you.
Related
I am using python 2.7 .I am using multi-threading.Now if a thread dies I again
create one to compensate for it.So should I create a lot of threads before hand and store them
and use from them when one or more existing threads die or should I create one when some thread dies??
Which is more efficient in terms of time ??
When you say a thread "dies", do you mean you intentionally terminate it or it fails due to error?
If you're intentionally terminating it and you're worried about the time required to spawn a new thread, why not keep the thread persistent and simply have it do the job that the new thread would have done? This is a pretty standard approach - maintain a pool of "worker" threads and have a work queue with pending items to execute. They all run an identical loop which is to pull an item off the queue and execute it. These items can be objects with methods which contain the code to execute if it's convenient to work that way - if the tasks are all very similar then it might be easier to put the code into the thread's own function instead.
If you're talking about threads failing due to error, I wouldn't have imagined this was common enough to worry about it. If it is, you probably need to look at making your code more robust.
In either case, spawning a thread on most systems should be a lightweight activity - a lot more lightweight than spawning a whole new process, for example. As a result, I really wouldn't worry about keeping a pool of threads in reserve to use - that really sounds like early optimisation to me.
Even if spawning threads were slow, consider what you would be doing by spawning threads in advance - you would be taking up more memory (some memory in the OS to keep track of a the thread, some in Python for the objects that it uses to track the thread), although not a great deal; you'd also be spending more time at the start of your program creating all these threads. So, you might save a little time while you were running, but instead your program takes significantly longer to start. That doesn't sound like a sensible trade-off to me unless the speed and latency of your code is absolutely critical while it's running, and if speed is that critical then I'm not sure a pure Python solution is the right approach anyway. Something like C/C++ is going to give you better control of scheduling, at the expense of much more complexity.
In summary: seriously, don't worry about it, just spawn threads as you need them. Trust me, there will be much bigger speed problems elsewhere in your code which are much more deserving of your time.
I stumbled over node.js sometime ago and like it a lot. But soon I found out that it lacked badly the ability to perform CPU-intensive tasks. So, I started googling and got these answers to solve the problem: Fibers, Webworkers and Threads (thread-a-gogo). Now which one to use is a confusion and one of them definitely needs to be used - afterall what's the purpose of having a server which is just good at IO and nothing else? Suggestions needed!
UPDATE:
I was thinking of a way off-late; just needing suggestions over it. Now, what I thought of was this: Let's have some threads (using thread_a_gogo or maybe webworkers). Now, when we need more of them, we can create more. But there will be some limit over the creation process. (not implied by the system but probably because of overhead). Now, when we exceed the limit, we can fork a new node, and start creating threads over it. This way, it can go on till we reach some limit (after all, processes too have a big overhead). When this limit is reached, we start queuing tasks. Whenever a thread becomes free, it will be assigned a new task. This way, it can go on smoothly.
So, that was what I thought of. Is this idea good? I am a bit new to all this process and threads stuff, so don't have any expertise in it. Please share your opinions.
Thanks. :)
Node has a completely different paradigm and once it is correctly captured, it is easier to see this different way of solving problems. You never need multiple threads in a Node application(1) because you have a different way of doing the same thing. You create multiple processes; but it is very very different than, for example how Apache Web Server's Prefork mpm does.
For now, let's think that we have just one CPU core and we will develop an application (in Node's way) to do some work. Our job is to process a big file running over its contents byte-by-byte. The best way for our software is to start the work from the beginning of the file, follow it byte-by-byte to the end.
-- Hey, Hasan, I suppose you are either a newbie or very old school from my Grandfather's time!!! Why don't you create some threads and make it much faster?
-- Oh, we have only one CPU core.
-- So what? Create some threads man, make it faster!
-- It does not work like that. If I create threads I will be making it slower. Because I will be adding a lot of overhead to the system for switching between threads, trying to give them a just amount of time, and inside my process, trying to communicate between these threads. In addition to all these facts, I will also have to think about how I will divide a single job into multiple pieces that can be done in parallel.
-- Okay okay, I see you are poor. Let's use my computer, it has 32 cores!
-- Wow, you are awesome my dear friend, thank you very much. I appreciate it!
Then we turn back to work. Now we have 32 cpu cores thanks to our rich friend. Rules we have to abide have just changed. Now we want to utilize all this wealth we are given.
To use multiple cores, we need to find a way to divide our work into pieces that we can handle in parallel. If it was not Node, we would use threads for this; 32 threads, one for each cpu core. However, since we have Node, we will create 32 Node processes.
Threads can be a good alternative to Node processes, maybe even a better way; but only in a specific kind of job where the work is already defined and we have complete control over how to handle it. Other than this, for every other kind of problem where the job comes from outside in a way we do not have control over and we want to answer as quickly as possible, Node's way is unarguably superior.
-- Hey, Hasan, are you still working single-threaded? What is wrong with you, man? I have just provided you what you wanted. You have no excuses anymore. Create threads, make it run faster.
-- I have divided the work into pieces and every process will work on one of these pieces in parallel.
-- Why don't you create threads?
-- Sorry, I don't think it is usable. You can take your computer if you want?
-- No okay, I am cool, I just don't understand why you don't use threads?
-- Thank you for the computer. :) I already divided the work into pieces and I create processes to work on these pieces in parallel. All the CPU cores will be fully utilized. I could do this with threads instead of processes; but Node has this way and my boss Parth Thakkar wants me to use Node.
-- Okay, let me know if you need another computer. :p
If I create 33 processes, instead of 32, the operating system's scheduler will be pausing a thread, start the other one, pause it after some cycles, start the other one again... This is unnecessary overhead. I do not want it. In fact, on a system with 32 cores, I wouldn't even want to create exactly 32 processes, 31 can be nicer. Because it is not just my application that will work on this system. Leaving a little room for other things can be good, especially if we have 32 rooms.
I believe we are on the same page now about fully utilizing processors for CPU-intensive tasks.
-- Hmm, Hasan, I am sorry for mocking you a little. I believe I understand you better now. But there is still something I need an explanation for: What is all the buzz about running hundreds of threads? I read everywhere that threads are much faster to create and dumb than forking processes? You fork processes instead of threads and you think it is the highest you would get with Node. Then is Node not appropriate for this kind of work?
-- No worries, I am cool, too. Everybody says these things so I think I am used to hearing them.
-- So? Node is not good for this?
-- Node is perfectly good for this even though threads can be good too. As for thread/process creation overhead; on things that you repeat a lot, every millisecond counts. However, I create only 32 processes and it will take a tiny amount of time. It will happen only once. It will not make any difference.
-- When do I want to create thousands of threads, then?
-- You never want to create thousands of threads. However, on a system that is doing work that comes from outside, like a web server processing HTTP requests; if you are using a thread for each request, you will be creating a lot of threads, many of them.
-- Node is different, though? Right?
-- Yes, exactly. This is where Node really shines. Like a thread is much lighter than a process, a function call is much lighter than a thread. Node calls functions, instead of creating threads. In the example of a web server, every incoming request causes a function call.
-- Hmm, interesting; but you can only run one function at the same time if you are not using multiple threads. How can this work when a lot of requests arrive at the web server at the same time?
-- You are perfectly right about how functions run, one at a time, never two in parallel. I mean in a single process, only one scope of code is running at a time. The OS Scheduler does not come and pause this function and switch to another one, unless it pauses the process to give time to another process, not another thread in our process. (2)
-- Then how can a process handle 2 requests at a time?
-- A process can handle tens of thousands of requests at a time as long as our system has enough resources (RAM, Network, etc.). How those functions run is THE KEY DIFFERENCE.
-- Hmm, should I be excited now?
-- Maybe :) Node runs a loop over a queue. In this queue are our jobs, i.e, the calls we started to process incoming requests. The most important point here is the way we design our functions to run. Instead of starting to process a request and making the caller wait until we finish the job, we quickly end our function after doing an acceptable amount of work. When we come to a point where we need to wait for another component to do some work and return us a value, instead of waiting for that, we simply finish our function adding the rest of work to the queue.
-- It sounds too complex?
-- No no, I might sound complex; but the system itself is very simple and it makes perfect sense.
Now I want to stop citing the dialogue between these two developers and finish my answer after a last quick example of how these functions work.
In this way, we are doing what OS Scheduler would normally do. We pause our work at some point and let other function calls (like other threads in a multi-threaded environment) run until we get our turn again. This is much better than leaving the work to OS Scheduler which tries to give just time to every thread on system. We know what we are doing much better than OS Scheduler does and we are expected to stop when we should stop.
Below is a simple example where we open a file and read it to do some work on the data.
Synchronous Way:
Open File
Repeat This:
Read Some
Do the work
Asynchronous Way:
Open File and Do this when it is ready: // Our function returns
Repeat this:
Read Some and when it is ready: // Returns again
Do some work
As you see, our function asks the system to open a file and does not wait for it to be opened. It finishes itself by providing next steps after file is ready. When we return, Node runs other function calls on the queue. After running over all the functions, the event loop moves to next turn...
In summary, Node has a completely different paradigm than multi-threaded development; but this does not mean that it lacks things. For a synchronous job (where we can decide the order and way of processing), it works as well as multi-threaded parallelism. For a job that comes from outside like requests to a server, it simply is superior.
(1) Unless you are building libraries in other languages like C/C++ in which case you still do not create threads for dividing jobs. For this kind of work you have two threads one of which will continue communication with Node while the other does the real work.
(2) In fact, every Node process has multiple threads for the same reasons I mentioned in the first footnote. However this is no way like 1000 threads doing similar works. Those extra threads are for things like to accept IO events and to handle inter-process messaging.
UPDATE (As reply to a good question in comments)
#Mark, thank you for the constructive criticism. In Node's paradigm, you should never have functions that takes too long to process unless all other calls in the queue are designed to be run one after another. In case of computationally expensive tasks, if we look at the picture in complete, we see that this is not a question of "Should we use threads or processes?" but a question of "How can we divide these tasks in a well balanced manner into sub-tasks that we can run them in parallel employing multiple CPU cores on the system?" Let's say we will process 400 video files on a system with 8 cores. If we want to process one file at a time, then we need a system that will process different parts of the same file in which case, maybe, a multi-threaded single-process system will be easier to build and even more efficient. We can still use Node for this by running multiple processes and passing messages between them when state-sharing/communication is necessary. As I said before, a multi-process approach with Node is as well as a multi-threaded approach in this kind of tasks; but not more than that. Again, as I told before, the situation that Node shines is when we have these tasks coming as input to system from multiple sources since keeping many connections concurrently is much lighter in Node compared to a thread-per-connection or process-per-connection system.
As for setTimeout(...,0) calls; sometimes giving a break during a time consuming task to allow calls in the queue have their share of processing can be required. Dividing tasks in different ways can save you from these; but still, this is not really a hack, it is just the way event queues work. Also, using process.nextTick for this aim is much better since when you use setTimeout, calculation and checks of the time passed will be necessary while process.nextTick is simply what we really want: "Hey task, go back to end of the queue, you have used your share!"
(Update 2016: Web workers are going into io.js - a Node.js fork Node.js v7 - see below.)
(Update 2017: Web workers are not going into Node.js v7 or v8 - see below.)
(Update 2018: Web workers are going into Node.js Node v10.5.0 - see below.)
Some clarification
Having read the answers above I would like to point out that there is nothing in web workers that is against the philosophy of JavaScript in general and Node in particular regarding concurrency. (If there was, it wouldn't be even discussed by the WHATWG, much less implemented in the browsers).
You can think of a web worker as a lightweight microservice that is accessed asynchronously. No state is shared. No locking problems exist. There is no blocking. There is no synchronization needed. Just like when you use a RESTful service from your Node program you don't worry that it is now "multithreaded" because the RESTful service is not in the same thread as your own event loop. It's just a separate service that you access asynchronously and that is what matters.
The same is with web workers. It's just an API to communicate with code that runs in a completely separate context and whether it is in different thread, different process, different cgroup, zone, container or different machine is completely irrelevant, because of a strictly asynchronous, non-blocking API, with all data passed by value.
As a matter of fact web workers are conceptually a perfect fit for Node which - as many people are not aware of - incidentally uses threads quite heavily, and in fact "everything runs in parallel except your code" - see:
Understanding the node.js event loop by Mikito Takada
Understanding node.js by Felix Geisendörfer
Understanding the Node.js Event Loop by Trevor Norris
Node.js itself is blocking, only its I/O is non-blocking by Jeremy Epstein
But the web workers don't even need to be implemented using threads. You could use processes, green threads, or even RESTful services in the cloud - as long as the web worker API is used. The whole beauty of the message passing API with call by value semantics is that the underlying implementation is pretty much irrelevant, as the details of the concurrency model will not get exposed.
A single-threaded event loop is perfect for I/O-bound operations. It doesn't work that well for CPU-bound operations, especially long running ones. For that we need to spawn more processes or use threads. Managing child processes and the inter-process communication in a portable way can be quite difficult and it is often seen as an overkill for simple tasks, while using threads means dealing with locks and synchronization issues that are very difficult to do right.
What is often recommended is to divide long-running CPU-bound operations into smaller tasks (something like the example in the "Original answer" section of my answer to Speed up setInterval) but it is not always practical and it doesn't use more than one CPU core.
I'm writing it to clarify the comments that were basically saying that web workers were created for browsers, not servers (forgetting that it can be said about pretty much everything in JavaScript).
Node modules
There are few modules that are supposed to add Web Workers to Node:
https://github.com/pgriess/node-webworker
https://github.com/audreyt/node-webworker-threads
I haven't used any of them but I have two quick observations that may be relevant: as of March 2015, node-webworker was last updated 4 years ago and node-webworker-threads was last updated a month ago. Also I see in the example of node-webworker-threads usage that you can use a function instead of a file name as an argument to the Worker constructor which seems that may cause subtle problems if it is implemented using threads that share memory (unless the functions is used only for its .toString() method and is otherwise compiled in a different environment, in which case it may be fine - I have to look more deeply into it, just sharing my observations here).
If there is any other relevant project that implements web workers API in Node, please leave a comment.
Update 1
I didn't know it yet at the time of writing but incidentally one day before I wrote this answer Web Workers were added to io.js.
(io.js is a fork of Node.js - see: Why io.js decided to fork Node.js, an InfoWorld interview with Mikeal Rogers, for more info.)
Not only does it prove the point that there is nothing in web workers that is against the philosophy of JavaScript in general and Node in particular regarding concurrency, but it may result in web workers being a first class citizen in server-side JavaScript like io.js (and possibly Node.js in the future) just as it already is in client-side JavaScript in all modern browsers.
Update 2
In Update 1 and my tweet I was referring to io.js pull request #1159
which now redirects to
Node PR #1159
that was closed on Jul 8 and replaced with Node PR #2133 - which is still open.
There is some discussion taking place under those pull requests that may provide some more up to date info on the status of Web workers in io.js/Node.js.
Update 3
Latest info - thanks to NiCk Newman for posting it in
the comments: There is the workers: initial implementation commit by Petka Antonov from Sep 6, 2015
that can be downloaded and tried out in
this tree. See comments by NiCk Newman for details.
Update 4
As of May 2016 the last comments on the still open PR #2133 - workers: initial implementation were 3 months old. On May 30 Matheus Moreira asked me to post an update to this answer in the comments below and he asked for the current status of this feature in the PR comments.
The first answers in the PR discussion were skeptical but later
Ben Noordhuis wrote that "Getting this merged in one shape or another is on my todo list for v7".
All other comments seemed to second that and as of July 2016 it seems that Web Workers should be available in the next version of Node, version 7.0 that is planned to be released on October 2016 (not necessarily in the form of this exact PR).
Thanks to Matheus Moreira for pointing it out in the comments and reviving the discussion on GitHub.
Update 5
As of July 2016 there are few modules on npm that were not available before - for a complete list of relevant modules, search npm for workers, web workers, etc. If anything in particular does or doesn't work for you, please post a comment.
Update 6
As of January 2017 it is unlikely that web workers will get merged into Node.js.
The pull request #2133 workers: initial implementation by Petka Antonov from July 8, 2015 was finally closed by Ben Noordhuis on December 11, 2016 who commented that "multi-threading support adds too many new failure modes for not enough benefit" and "we can also accomplish that using more traditional means like shared memory and more efficient serialization."
For more information see the comments to the PR 2133 on GitHub.
Thanks again to Matheus Moreira for pointing it out in the comments.
Update 6
I'm happy to announce that few days ago, in June 2018 web workers appeared in Node v10.5.0 as an experimental feature activated with the --experimental-worker flag.
For more info, see:
Node v10.5.0 release blog post
Pull Request #20876 - worker: initial implementation by Anna Henningsen
My original tweet of happiness when I learned that this got into v10.5.0:
🎉🎉🎉 Finally! I can make the 7th update to my 3 year old Stack Overflow answer where I argue that threading a la web workers is not against Node philosophy, only this time saying that we finally got it! 😜👍
I come from the old school of thought where we used multi-threading to make software fast. For past 3 years i have been using Node.js and a big supporter of it. As hasanyasin explained in detail how node works and the concept of asyncrous functionality. But let me add few things here.
Back in the old days with single cores and lower clock speeds we tried various ways to make software work fast and parallel. in DOS days we use to run one program at a time. Than in windows we started running multiple applications (processes) together. Concepts like preemptive and non-preemptive (or cooperative) where tested. we know now that preemptive was the answer for better multi-processing task on single core computers. Along came the concepts of processes/tasks and context switching. Than the concept of thread to further reduce the burden of process context switching. Thread where coined as light weight alternative to spawning new processes.
So like it or not signal thread or not multi-core or single core your processes will be preempted and time sliced by the OS.
Nodejs is a single process and provides async mechanism. Here jobs are dispatched to under lying OS to perform tasks while we waiting in an event loop for the task to finish. Once we get a green signal from OS we perform what ever we need to do. Now in a way this is cooperative/non-preemptive multi-tasking, so we should never block the event loop for a very long period of time other wise we will degrade our application very fast.
So if there is ever a task that is blocking in nature or is very time consuming we will have to branch it out to the preemptive world of OS and threads.
there are good examples of this is in the libuv documentation. Also if you read the documentation further you find that FileI/O is handled in threads in node.js.
So Firstly its all in the design of our software. Secondly Context switching is always happening no matter what they tell you. Thread are there and still there for a reason, the reason is they are faster to switch in between then processes.
Under hood in node.js its all c++ and threads. And node provides c++ way to extend its functionality and to further speed out by using threads where they are a must i.e., blocking tasks such as reading from a source writing to a source, large data analysis so on so forth.
I know hasanyasin answer is the accepted one but for me threads will exist no matter what you say or how you hide them behind scripts, secondly no one just breaks things in to threads just for speed it is mostly done for blocking tasks. And threads are in the back bone of Node.js so before completely bashing multi-threading is in correct. Also threads are different from processes and the limitation of having node processes per core don't exactly apply to number of threads, threads are like sub tasks to a process. in fact threads won;t show up in your windows task manager or linux top command. once again they are more little weight then processes
I'm not sure if webworkers are relevant in this case, they are client-side tech (run in the browser), while node.js runs on the server. Fibers, as far as I understand, are also blocking, i.e. they are voluntary multitasking, so you could use them, but should manage context switches yourself via yield. Threads might be actually what you need, but I don't know how mature they are in node.js.
worker_threads has been implemented and shipped behind a flag in node#10.5.0. It's still an initial implementation and more efforts are needed to make it more efficient in future releases. Worth giving it a try in latest node.
In many Node developers' opinions one of the best parts of Node is actually its single-threaded nature. Threads introduce a whole slew of difficulties with shared resources that Node completely avoids by doing nothing but non-blocking IO.
That's not to say that Node is limited to a single thread. It's just that the method for getting threaded concurrency is different from what you're looking for. The standard way to deal with threads is with the cluster module that comes standard with Node itself. It's a simpler approach to threads than manually dealing with them in your code.
For dealing with asynchronous programming in your code (as in, avoiding nested callback pyramids), the [Future] component in the Fibers library is a decent choice. I would also suggest you check out Asyncblock which is based on Fibers. Fibers are nice because they allow you to hide callback by duplicating the stack and then jumping between stacks on a single-thread as they're needed. Saves you the hassle of real threads while giving you the benefits. The downside is that stack traces can get a bit weird when using Fibers, but they aren't too bad.
If you don't need to worry about async stuff and are more just interested in doing a lot of processing without blocking, a simple call to process.nextTick(callback) every once in a while is all you need.
Maybe some more information on what tasks you are performing would help. Why would you need to (as you mentioned in your comment to genericdave's answer) need to create many thousands of them? The usual way of doing this sort of thing in Node is to start up a worker process (using fork or some other method) which always runs and can be communicated to using messages. In other words, don't start up a new worker each time you need to perform whatever task it is you're doing, but simply send a message to the already running worker and get a response when it's done. Honestly, I can't see that starting up many thousands of actual threads would be very efficient either, you are still limited by you CPUs.
Now, after saying all of that, I have been doing a lot of work with Hook.io lately which seems to work very well for this sort of off-loading tasks into other processes, maybe it can accomplish what you need.
As multi-processor and multi-core computers become more and more ubiquitous, is simply firing off a new thread a (relatively) simple and painless way of simplifying code? For instance, in a current personal project, I have a network server listening on a port. Since this is just a personal project, it's just a desktop app, with a GUI integrated into it for configuration. So, the app reads something like this:
Main()
Read configuration
Start listener thread
Run GUI
Listener Thread
While the app is running
Wait for a new connection
Run a client thread for the new connection
Client Thread
Write synchronously
Read synchronously
ad inifinitum, or till they disconnect
This approach means that while I have to worry about alot of locking, with the potential issues that involves, I avoid alot of spaghetti code from assynchronous calls, etc.
A slightly more insidious version of this came up today when I was working on the startup code. The startup was quick, but it was using lazy loading for alot of the configuration, which meant that while startup was quick, actually connecting to and using the service was difficult because of the lag while it loaded different sections (this was actually measurable in real time, up to 3-10 seconds sometimes). So I moved to a different strategy, on startup, loop through everything and force the lazy loading to kick in... but this made it start prohibitively slow; get up, go get a coffee slow. Final solution: throw the loop into a seperate thread with feedback in the system tray while it's still loading.
Is this "Meh, throw it in another thread, it'll be fine" attitude ok? At what point do you start getting diminishing returns and/or even reduced performance?
Multithreading does a lot of things, but I don't think "simplification" is ever one of them.
It's a great way to introduce bugs into code.
Using multiple threads properly is not easy. It should not be attempted by new developers.
In my opinion, multi-threaded programming is pretty high up on the difficulty (and complexity) scale, along with memory management. To me, the "Meh, throw it in another thread, it'll be fine" attitude is a bit too casual. Think long and hard you must, before forking threads you do.
No.
Plainly and simply, multithreading increases complexity and is a nearly trivial way to add bugs to code. There are concurrency issues such as synchronization, deadlock, race conditions, and priority inversion to name a few.
Secondly, the performance gains are not automatic. Recently, there was an excellent article in MSDN Magazine along these lines. The salient details are that a certain operation was taking 46 seconds per ten iterations coded as a single-threaded operation. The author parallelized the operation naively (one thread per four cores) and the operation dropped to 30 seconds per ten iterations. Sounds great until you take into consideration that the operation now eats 300% more processing power but only experienced a 34% gain in efficiency. It's not worth consuming all available processing power for a gain like that.
This gives you the extra job of debugging race conditions, and handling locks and sycronisation issues.
I would not use this unless there was a real need.
Read up on Amdahl's law, best summarized by "The speedup of a program using multiple processors in parallel computing is limited by the time needed for the sequential fraction of the program."
As it turns out, if only a small part of your app can run in parallel you won't get much gains, but potentially many hard-to-debug bugs.
I don't mean to be flip but what's in that configuration file that it takes so long to load? That's the origin of your problem, right?
Before spawning another thread to handle it, perhaps it can be parred down? Reduced, perhaps put in another data format that would be quicker, etc?
How often does it change? Is it something you can parse once at the beginning of the day and put the variables in shared memory so subsequent runs of your main program can just attach and get the needed values from there?
While I agree with everyone else here in saying that multithreading does not simplify code, it can be used to greatly simplify the user experience of your application.
Consider an application that has a lot of interactive widgets (I am currently developing one where this helps) - in the workflow of my application, a user can "build" the current project they are working on. This requires disabling the interactive widgets my application presents to the user and presenting a dialog with a indeterminate progress bar and a friendly "please wait" message.
The "build" occurs on a background thread; if it were to happen on the UI thread it would make the user experience less enjoyable - after all, it's no fun not being able to tell whether or not you are able to click on a widget in an application while a background task is running (cough, Visual Studio). Not to say that VS doesn't use background threads, I'm just saying their user experience could use some improvement. But I digress.
The one thing I take issue with in the title of your post is that you think of firing off threads when you need to perform tasks - I generally prefer to reuse threads - in .NET, I generally favor using the system thread pool over creating a new thread each time I want to do something, for the sake of performance.
I'm going to provide some balance against the unanimous "no".
DISCLAIMER: Yes, threads are complicated and can cause a whole bunch of problems. Everyone else has pointed this out.
From experience, a sequence of blocking reads/writes to a socket (which requires a separate thead) is much simpler than non-blocking ones. With blocking calls, you can tell the state of the connection just by looking at where you are in the function. With non-blocking calls, you need a bunch of variables to record the state of the connection, and check and modify them every time you interact with the connection. With blocking calls, you can just say "read the next X bytes" or "read until you find X" and it will actually do it (or fail). With non-blocking calls, you have to deal with fragmented data which usually requires keeping temporary buffers and filling them as necessary. You also end up checking if you've received enough data every time you receive little more. Plus you have to keep a list of open connections and handle unexpected closes for all of them.
It doesn't get much simpler than this:
void WorkerThreadMain(Connection connection) {
Request request = ReadRequest(connection);
if(!request) return;
Reply reply = ProcessRequest(request);
if(!connection.isOpen) return;
SendReply(reply, connection);
connection.close();
}
I'd like to note that this "listener spawns off a worker thread per connection" pattern is how web servers are designed, and I assume it's how a lot of request/response soft of server applications are designed.
So in conclusion, I have experienced the asynchronous socket spaghetti code you mentioned, and spawning off worker threads for every connection ended up being a good solution. Having said all this, throwing threads at a problem should usually be your last resort.
I think your have no choice but to deal with threads especially with networking and concurrent connections. Do threads make code simpler? I don't think so. But without them how would you program a server that can handle more than 1 client at the same time?
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.
What are some concrete examples of applications that need to be multi-threaded, or don't need to be, but are much better that way?
Answers would be best if in the form of one application per post that way the most applicable will float to the top.
There is no hard and fast answer, but most of the time you will not see any advantage for systems where the workflow/calculation is sequential. If however the problem can be broken down into tasks that can be run in parallel (or the problem itself is massively parallel [as some mathematics or analytical problems are]), you can see large improvements.
If your target hardware is single processor/core, you're unlikely to see any improvement with multi-threaded solutions (as there is only one thread at a time run anyway!)
Writing multi-threaded code is often harder as you may have to invest time in creating thread management logic.
Some examples
Image processing can often be done in parallel (e.g. split the image into 4 and do the work in 1/4 of the time) but it depends upon the algorithm being run to see if that makes sense.
Rendering of animation (from 3DMax,etc.) is massively parallel as each frame can be rendered independently to others -- meaning that 10's or 100's of computers can be chained together to help out.
GUI programming often helps to have at least two threads when doing something slow, e.g. processing large number of files - this allows the interface to remain responsive whilst the worker does the hard work (in C# the BackgroundWorker is an example of this)
GUI's are an interesting area as the "responsiveness" of the interface can be maintained without multi-threading if the worker algorithm keeps the main GUI "alive" by giving it time, in Windows API terms (before .NET, etc) this could be achieved by a primitive loop and no need for threading:
MSG msg;
while(GetMessage(&msg, hwnd, 0, 0))
{
TranslateMessage(&msg);
DispatchMessage(&msg);
// do some stuff here and then release, the loop will come back
// almost immediately (unless the user has quit)
}
Servers are typically multi-threaded (web servers, radius servers, email servers, any server): you usually want to be able to handle multiple requests simultaneously. If you do not want to wait for a request to end before you start to handle a new request, then you mainly have two options:
Run a process with multiple threads
Run multiple processes
Launching a process is usually more resource-intensive than lauching a thread (or picking one in a thread-pool), so servers are usually multi-threaded. Moreover, threads can communicate directly since they share the same memory space.
The problem with multiple threads is that they are usually harder to code right than multiple processes.
There are really three classes of reasons that multithreading would be applied:
Execution Concurrency to improve compute performance: If you have a problem that can be broken down into pieces and you also have more than one execution unit (processor core) available then dispatching the pieces into separate threads is the path to being able to simultaneously use two or more cores at once.
Concurrency of CPU and IO Operations: This is similar in thinking to the first one but in this case the objective is to keep the CPU busy AND also IO operations (ie: disk I/O) moving in parallel rather than alternating between them.
Program Design and Responsiveness: Many types of programs can take advantage of threading as a program design benefit to make the program more responsive to the user. For example the program can be interacting via the GUI and also doing something in the background.
Concrete Examples:
Microsoft Word: Edit document while the background grammar and spell checker works to add all the green and red squiggle underlines.
Microsoft Excel: Automatic background recalculations after cell edits
Web Browser: Dispatch multiple threads to load each of the several HTML references in parallel during a single page load. Speeds page loads and maximizes TCP/IP data throughput.
These days, the answer should be Any application that can be.
The speed of execution for a single thread pretty much peaked years ago - processors have been getting faster by adding cores, not by increasing clock speeds. There have been some architectural improvements that make better use of the available clock cycles, but really, the future is taking advantage of threading.
There is a ton of research going on into finding ways of parallelizing activities that we traditionally wouldn't think of parallelizing. Even something as simple as finding a substring within a string can be parallelized.
Basically there are two reasons to multi-thread:
To be able to do processing tasks in parallel. This only applies if you have multiple cores/processors, otherwise on a single core/processor computer you will slow the task down compared to the version without threads.
I/O whether that be networked I/O or file I/O. Normally if you call a blocking I/O call, the process has to wait for the call to complete. Since the processor/memory are several orders of magnitude quicker than a disk drive (and a network is even slower) it means the processor will be waiting a long time. The computer will be working on other things but your application will not be making any progress. However if you have multiple threads, the computer will schedule your application and the other threads can execute. One common use is a GUI application. Then while the application is doing I/O the GUI thread can keep refreshing the screen without looking like the app is frozen or not responding. Even on a single processor putting I/O in a different thread will tend to speed up the application.
The single threaded alternative to 2 is to use asynchronous calls where they return immediately and you keep controlling your program. Then you have to see when the I/O completes and manage using it. It is often simpler just to use a thread to do the I/O using the synchronous calls as they tend to be easier.
The reason to use threads instead of separate processes is because threads should be able to share data easier than multiple processes. And sometimes switching between threads is less expensive than switching between processes.
As another note, for #1 Python threads won't work because in Python only one python instruction can be executed at a time (known as the GIL or Global Interpreter Lock). I use that as an example but you need to check around your language. In python if you want to do parallel calculations, you need to do separate processes.
Many GUI frameworks are multi-threaded. This allows you to have a more responsive interface. For example, you can click on a "Cancel" button at any time while a long calculation is running.
Note that there are other solutions for this (for example the program can pause the calculation every half-a-second to check whether you clicked on the Cancel button or not), but they do not offer the same level of responsiveness (the GUI might seem to freeze for a few seconds while a file is being read or a calculation being done).
All the answers so far are focusing on the fact that multi-threading or multi-processing are necessary to make the best use of modern hardware.
There is however also the fact that multithreading can make life much easier for the programmer. At work I program software to control manufacturing and testing equipment, where a single machine often consists of several positions that work in parallel. Using multiple threads for that kind of software is a natural fit, as the parallel threads model the physical reality quite well. The threads do mostly not need to exchange any data, so the need to synchronize threads is rare, and many of the reasons for multithreading being difficult do therefore not apply.
Edit:
This is not really about a performance improvement, as the (maybe 5, maybe 10) threads are all mostly sleeping. It is however a huge improvement for the program structure when the various parallel processes can be coded as sequences of actions that do not know of each other. I have very bad memories from the times of 16 bit Windows, when I would create a state machine for each machine position, make sure that nothing would take longer than a few milliseconds, and constantly pass the control to the next state machine. When there were hardware events that needed to be serviced on time, and also computations that took a while (like FFT), then things would get ugly real fast.
Not directly answering your question, I believe in the very near future, almost every application will need to be multithreaded. The CPU performance is not growing that fast these days, which is compensated for by the increasing number of cores. Thus, if we will want our applications to stay on the top performance-wise, we'll need to find ways to utilize all your computer's CPUs and keep them busy, which is quite a hard job.
This can be done via telling your programs what to do instead of telling them exactly how. Now, this is a topic I personally find very interesting recently. Some functional languages, like F#, are able to parallelize many tasks quite easily. Well, not THAT easily, but still without the necessary infrastructure needed in more procedural-style environments.
Please take this as additional information to think about, not an attempt to answer your question.
The kind of applications that need to be threaded are the ones where you want to do more than one thing at once. Other than that no application needs to be multi-threaded.
Applications with a large workload which can be easily made parallel. The difficulty of taking your application and doing that should not be underestimated. It is easy when your data you're manipulating is not dependent upon other data but v. hard to schedule the cross thread work when there is a dependency.
Some examples I've done which are good multithreaded candidates..
running scenarios (eg stock derivative pricing, statistics)
bulk updating data files (eg adding a value / entry to 10,000 records)
other mathematical processes
E.g., you want your programs to be multithreaded when you want to utilize multiple cores and/or CPUs, even when the programs don't necessarily do many things at the same time.
EDIT: using multiple processes is the same thing. Which technique to use depends on the platform and how you are going to do communications within your program, etc.
Although frivolous, games, in general are becomming more and more threaded every year. At work our game uses around 10 threads doing physics, AI, animation, redering, network and IO.
Just want to add that caution must be taken with treads if your sharing any resources as this can lead to some very strange behavior, and your code not working correctly or even the threads locking each other out.
mutex will help you there as you can use mutex locks for protected code regions, a example of protected code regions would be reading or writing to shared memory between threads.
just my 2 cents worth.
The main purpose of multithreading is to separate time domains. So the uses are everywhere where you want several things to happen in their own distinctly separate time domains.
HERE IS A PERFECT USE CASE
If you like affiliate marketing multi-threading is essential. Kick the entire process off via a multi-threaded application.
Download merchant files via FTP, unzipping the files, enumerating through each file performing cleanup like EOL terminators from Unix to PC CRLF then slam each into SQL Server via Bulk Inserts then when all threads are complete create the full text search indexes for a environmental instance to be live tomorrow and your done. All automated to kick off at say 11:00 pm.
BOOM! Fast as lightening. Heck you have so much time left you can even download merchant images locally for the products you download, save the images as webp and set the product urls to use local images.
Yep I did it. Wrote it in C#. Works like a charm. Purchase a AMD Ryzen Threadripper 64-core with 256gb memory and fast drives like nvme, get lunch come back and see it all done or just stay around and watch all cores peg to 95%+, listen to the pc's fans kick, warm up the room and the look outside as the neighbors lights flicker from the power drain as you get shit done.
Future would be to push processing to GPU's as well.
Ok well I am pushing it a little bit with the neighbors lights flickering but all else was absolutely true. :)