I'm rewriting existing real-time kernel TNKernel; I have used it for a couple of years, but I don't like many of its design decisions (as well as implementation details), so I decided to fork it and have fun implementing what I want. Anyone who is interested might read additional information at the project page on bitbucket.
TNKernel has one strange, in my opinion, feature: it has service tn_task_sleep(int timeout) which puts current task to sleep, and it has tn_task_wakeup(struct TN_Task *task) which wakes currently sleeping task up.
The strangeness is that it is legal to call tn_task_wakeup() on non-sleeping task; in this case, special flag like wakeup_request will be set, and on the next call to tn_task_sleep() this flag will be cleared, and task won't sleep.
All of this seems to me as a completely dirty hack, it probably might be used as a workaround to avoid race condition problems, or as a hacky replacement for semaphore.
It just encourages programmer to go with hacky approach, instead of creating straightforward semaphore and provide proper synchronization. So, I'm willing to remove this service from my project. Is this good idea to get rid of it, or have I missed something important? Why do we ever need that?
Since no one said that I'm wrong, I assumed that I'm right and removed these strange "features" from my kernel.
I'm using lua as the scripting language for handling events in my application, and I don't want to restrict users to writing short handlers - e.g. someone might want to have one handler run an infinite loop, and another handler would interrupt the first one. Obviously, lua doesn't directly support such behavior, so I'm looking for workarounds.
First of all, I'd like to avoid modifying the engine. Is it possible to set up a debug hook that would yield once the state has reached its quota? Judging by the documentation, it shouldn't be hard at all, but I don't know if there are any caveats to this.
And second, can I use lua_close to terminate a thread as I would in actual multithreading?
I've done something similar in the past. Its completely possible to multi-thread on separate Lua states. Be sure to take a look at luaL_lock() and luaL_unlock() (plus associated setup/cleanup), as you will no doubt need this setup (a simple mutex should do the trick).
After that, it should be a fairly simple matter of creating a lock/wait/interrupt API for your handlers.
I know the title sounds like a dupe of a dozen other questions, and it may well be. However, I've read those dozen questions, and Googled around for awhile, and found nothing that answers these questions to my satisfaction.
This might be because nobody has answered it properly, in which case you should vote me up.
This might be because I'm dumb and didn't understand the other answers (much more likely), in which case you should vote me down.
Context:
I know that IO operations in Node.js are detected and made to run asynchronously by default. My question is about non-IO operations that still might block/run for a long time.
Say I have a function blockingfunction with a for loop that does addition or whatnot (pure CPU cycles, no IO), and a lot of it. It takes a minute or more to run.
Say I want this function to run whenever someone makes a certain request to my server.
Question:
Obviously, if I explicitly invoke this loop at the outer level in my code, everything will block until it completes.
Most suggestions I've read suggest pushing it off into the future by starting all of my other handlers/servers etc. first, and deferring invocation of the function via process.nextTick or setTimeout(blockingfunction, 0).
But won't blockingfunction1 then just block on the next spin around the execution loop? I may be wrong, but it seems like doing that would start all of my other stuff without blocking the app, but then the first time someone made the request that results in blockingfunction being called, everything would block for as long as it took to complete.
Does putting blockingfunction inside a setTimeout or process.nextTick call somehow make it coexist with future operations without blocking them?
If not, is there a way to make blockingfunction do that without rewriting it?
How do others handle this problem? A lot of the answers I've seen are to the tune of "just trust your CPU-intensive things to be fast, they will be", but this doesn't satisfy.
Absent threading (where I can be guaranteed that the execution of blockingfunction will be interleaved with the execution of whatever else is going on), should I re-write CPU-intensive/time consuming loops to use process.nextTick to perform a fixed, guaranteed-fast number of iterations per tick?
Yes, you are correct. If you defer your function until the next tick, it will just block in that tick rather than the current one.
Unfortunately, there is no magic here that solves this for you. While it is possible to fire up that function in another process, it might not be worth the hassle, depending on what you're doing.
I recommend re-writing your function in such a way that work happens for a bit, and then continues on the next tick. Node ticks are very efficient... you could call them every iteration of a decent sized loop if needed, without a whole ton of overhead. Of course, you would have to profile it in your code to see what the impact is.
Yes, a blocking function will keep blocking even if you run it process.nextTick.
Some options:
If it truly takes a while, then perhaps it should be spun out to a queue where you can have a dedicated worker process handle it.
1a. Node.js has a child-process flavor specifically for forking other node.js files with a built in communication channel. So e.g. you can create one (or several) thread that handles these requests in order, then responds and hits the callback. See: http://nodejs.org/api/child_process.html#child_process_child_process_fork_modulepath_args_options
You can break up the blockingFunction into chunks that run in a loop. Have it call every X iterations with process.nextTick to make way for other events to be handled.
I've been learning some lua for game development. I heard about coroutines in other languages but really came up on them in lua. I just don't really understand how useful they are, I heard a lot of talk how it can be a way to do multi-threaded things but aren't they run in order? So what benefit would there be from normal functions that also run in order? I'm just not getting how different they are from functions except that they can pause and let another run for a second. Seems like the use case scenarios wouldn't be that huge to me.
Anyone care to shed some light as to why someone would benefit from them?
Especially insight from a game programming perspective would be nice^^
OK, think in terms of game development.
Let's say you're doing a cutscene or perhaps a tutorial. Either way, what you have are an ordered sequence of commands sent to some number of entities. An entity moves to a location, talks to a guy, then walks elsewhere. And so forth. Some commands cannot start until others have finished.
Now look back at how your game works. Every frame, it must process AI, collision tests, animation, rendering, and sound, among possibly other things. You can only think every frame. So how do you put this kind of code in, where you have to wait for some action to complete before doing the next one?
If you built a system in C++, what you would have is something that ran before the AI. It would have a sequence of commands to process. Some of those commands would be instantaneous, like "tell entity X to go here" or "spawn entity Y here." Others would have to wait, such as "tell entity Z to go here and don't process anymore commands until it has gone here." The command processor would have to be called every frame, and it would have to understand complex conditions like "entity is at location" and so forth.
In Lua, it would look like this:
local entityX = game:GetEntity("entityX");
entityX:GoToLocation(locX);
local entityY = game:SpawnEntity("entityY", locY);
local entityZ = game:GetEntity("entityZ");
entityZ:GoToLocation(locZ);
do
coroutine.yield();
until (entityZ:isAtLocation(locZ));
return;
On the C++ size, you would resume this script once per frame until it is done. Once it returns, you know that the cutscene is over, so you can return control to the user.
Look at how simple that Lua logic is. It does exactly what it says it does. It's clear, obvious, and therefore very difficult to get wrong.
The power of coroutines is in being able to partially accomplish some task, wait for a condition to become true, then move on to the next task.
Coroutines in a game:
Easy to use, Easy to screw up when used in many places.
Just be careful and not use it in many places.
Don't make your Entire AI code dependent on Coroutines.
Coroutines are good for making a quick fix when a state is introduced which did not exist before.
This is exactly what java does. Sleep() and Wait()
Both functions are the best ways to make it impossible to debug your game.
If I were you I would completely avoid any code which has to use a Wait() function like a Coroutine does.
OpenGL API is something you should take note of. It never uses a wait() function but instead uses a clean state machine which knows exactly what state what object is at.
If you use coroutines you end with up so many stateless pieces of code that it most surely will be overwhelming to debug.
Coroutines are good when you are making an application like Text Editor ..bank application .. server ..database etc (not a game).
Bad when you are making a game where anything can happen at any point of time, you need to have states.
So, in my view coroutines are a bad way of programming and a excuse to write small stateless code.
But that's just me.
It's more like a religion. Some people believe in coroutines, some don't. The usecase, the implementation and the environment all together will result into a benefit or not.
Don't trust benchmarks which try to proof that coroutines on a multicore cpu are faster than a loop in a single thread: it would be a shame if it were slower!
If this runs later on some hardware where all cores are always under load, it will turn out to be slower - ups...
So there is no benefit per se.
Sometimes it's convenient to use. But if you end up with tons of coroutines yielding and states that went out of scope you'll curse coroutines. But at least it isn't the coroutines framework, it's still you.
We use them on a project I am working on. The main benefit for us is that sometimes with asynchronous code, there are points where it is important that certain parts are run in order because of some dependencies. If you use coroutines, you can force one process to wait for another process to complete. They aren't the only way to do this, but they can be a lot simpler than some other methods.
I'm just not getting how different they are from functions except that
they can pause and let another run for a second.
That's a pretty important property. I worked on a game engine which used them for timing. For example, we had an engine that ran at 10 ticks a second, and you could WaitTicks(x) to wait x number of ticks, and in the user layer, you could run WaitFrames(x) to wait x frames.
Even professional native concurrency libraries use the same kind of yielding behaviour.
Lots of good examples for game developers. I'll give another in the application extension space. Consider the scenario where the application has an engine that can run a users routines in Lua while doing the core functionality in C. If the user needs to wait for the engine to get to a specific state (e.g. waiting for data to be received), you either have to:
multi-thread the C program to run Lua in a separate thread and add in locking and synchronization methods,
abend the Lua routine and retry from the beginning with a state passed to the function to skip anything, least you rerun some code that should only be run once, or
yield the Lua routine and resume it once the state has been reached in C
The third option is the easiest for me to implement, avoiding the need to handle multi-threading on multiple platforms. It also allows the user's code to run unmodified, appearing as if the function they called took a long time.
I've read a lot recently about how writing multi-threaded apps is a huge pain in the neck, and have learned enough about the topic to understand, at least at some level, why it is so.
I've read that using functional programming techniques can help alleviate some of this pain, but I've never seen a simple example of functional code that is concurrent. So, what are some alternatives to using threads? At least, what are some ways to abstract them away so you needn't think about things like locking and whether a particular library's objects are thread-safe.
I know Google's MapReduce is supposed to help with the problem, but I haven't seen a succinct explanation of it.
Although I'm giving a specific example below, I'm more curious of general techniques than solving this specific problem (using the example to help illustrate other techniques would be helpful though).
I came to the question when I wrote a simple web crawler as a learning exercise. It works pretty well, but it is slow. Most of the bottleneck comes from downloading pages. It is currently single threaded, and thus only downloads a single page at a time. Thus, if the pages can be downloaded concurrently, it would speed things up dramatically, even if the crawler ran on a single processor machine. I looked into using threads to solve the issue, but they scare me. Any suggestions on how to add concurrency to this type of problem without unleashing a terrible threading nightmare?
The reason functional programming helps with concurrency is not because it avoids using threads.
Instead, functional programming preaches immutability, and the absence of side effects.
This means that an operation could be scaled out to N amount of threads or processes, without having to worry about messing with shared state.
Actually, threads are pretty easy to handle until you need to synchronize them. Usually, you use threadpool to add task and wait till they are finished.
It is when threads need to communicate and access shared data structures that multi threading becomes really complicated. As soon as you have two locks, you can get deadlocks, and this is where multithreading gets really hard. Sometimes, your locking code could be wrong by just a few instructions. In that case, you could only see bugs in production, on multi-core machines (if you developed on single core, happened to me) or they could be triggered by some other hardware or software. Unit testing doesn't help much here, testing finds bugs, but you can never be as sure as in "normal" apps.
I'll add an example of how functional code can be used to safely make code concurrent.
Here is some code you might want to do in parallel, so you don't have wait for one file to finish to start downloading the next:
void DownloadHTMLFiles(List<string> urls)
{
foreach(string url in urls)
{
DownlaodOneFile(url); //download html and save it to a file with a name based on the url - perhaps used for caching.
}
}
If you have a number of files the user might spend a minute or more waiting for them all. We can re-write this code functionally like this, and it basically does the exact same thing:
urls.ForEach(DownloadOneFile);
Note that this still runs sequentially. However, not only is it shorter, we've gained an important advantage here. Since each call to the DownloadOneFile function is completely isolated from the others (for our purposes, available bandwidth isn't an issue) you could very easily swap out the ForEach function for another very similar function: one that kicks off each call to DownlaodOneFile on a separate thread from a threadpool.
It turns out .Net has just such a function availabe using Parallel Extensions. So, by using functional programming you can change one line of code and suddenly have something run in parallel that used to run sequentially. That's pretty powerful.
There are a couple of brief mentions of asynchronous models but no one has really explained it so I thought I'd chime in. The most common method I've seen used as an alternative for multi-threading is asynchronous architectures. All that really means is that instead of executing code sequentially in a single thread, you use a polling method to initiate some functions and then come back and check periodically until there's data available.
This really only works in models like your aforementioned crawler, where the real bottleneck is I/O rather than CPU. In broad strokes, the asynchronous approach would initiate the downloads on several sockets, and a polling loop periodically checks to see if they're finished downloading and when that's done, we can move on to the next step. This allows you to run several downloads that are waiting on the network, by context switching within the same thread, as it were.
The multi-threaded model would work much the same, except using a separate thread rather than a polling loop checking multiple sockets in the same thread. In an I/O bound application, asynchronous polling works almost as well as threading for many use cases, since the real problem is simply waiting for the I/O to complete and not so much the waiting for the CPU to process the data.
Another real world example is for a system that needed to execute a number of other executables and wait for results. This can be done in threads, but it's also considerably simpler and almost as effective to simply fire off several external applications as Process objects, then check back periodically until they're all finished executing. This puts the CPU-intensive parts (the running code in the external executables) in their own processes, but the data processing is all handled asynchronously.
The Python ftp server lib I work on, pyftpdlib uses the Python asyncore library to handle serving FTP clients with only a single thread, and asynchronous socket communication for file transfers and command/response.
See for further reading the Python Twisted library's page on Asynchronous Programming - while somewhat specific to using Twisted, it also introduces async programming from a beginner perspective.
Concurrency is quite a complicated subject in computer science, which demands good understanding of hardware architecture as well as operating system behavior.
Multi-threading has many implementations based on your hardware and your hosting OS, and as tough as it is already, the pitfalls are numerous. It should be noted that in order to achieve "true" concurrency, threads are the only way to go. Basically, threads are the only way for you as a programmer to share resources between different parts of your software while allowing them to run in parallel. By parallel you should consider that a standard CPU (dual/multi-cores aside) can only do one thing at a time. Concepts like context switching now come into play, and they have their own set of rules and limitations.
I think you should seek more generic background on the subject, like you are saying, before you go about implementing concurrency in your program.
I guess the best place to start is the wikipedia article on concurrency, and go on from there.
What typically makes multi-threaded programming such a nightmare is when threads share resources and/or need to communicate with each other. In the case of downloading web pages, your threads would be working independently, so you may not have much trouble.
One thing you may want to consider is spawning multiple processes rather than multiple threads. In the case you mention--downloading web pages concurrently--you could split the workload up into multiple chunks and hand each chunk off to a separate instance of a tool (like cURL) to do the work.
If your goal is to achieve concurrency it will be hard to get away from using multiple threads or processes. The trick is not to avoid it but rather to manage it in a way that is reliable and non-error prone. Deadlocks and race conditions in particular are two aspects of concurrent programming that are easy to get wrong. One general approach to manage this is to use a producer/consumer queue... threads write work items to the queue and workers pull items from it. You must make sure you properly synchronize access to the queue and you're set.
Also, depending on your problem, you may also be able to create a domain specific language which does away with concurrency issues, at least from the perspective of the person using your language... of course the engine which processes the language still needs to handle concurrency, but if this will be leveraged across many users it could be of value.
There are some good libraries out there.
java.util.concurrent.ExecutorCompletionService will take a collection of Futures (i.e. tasks which return values), process them in background threads, then bung them in a Queue for you to process further as they complete. Of course, this is Java 5 and later, so isn't available everywhere.
In other words, all your code is single threaded - but where you can identify stuff safe to run in parallel, you can farm it off to a suitable library.
Point is, if you can make the tasks independent, then thread safety isn't impossible to achieve with a little thought - though it is strongly recommended you leave the complicated bit (like implementing the ExecutorCompletionService) to an expert...
One simple way to avoid threading in your simple scenario, Is to download from different processes. The main process will invoke other processes with parameters that will download the files to local directory, And then the main process can do the real job.
I don't think that there are any simple solution to those problems. Its not a threading problem. Its the concurrency that brake the human mind.
You might watch the MSDN video on the F# language: PDC 2008: An introduction to F#
This includes the two things you are looking for. (Functional + Asynchronous)
For python, this looks like an interesting approach: http://members.verizon.net/olsongt/stackless/why_stackless.html#introduction
Use Twisted. "Twisted is an event-driven networking engine written in Python" http://twistedmatrix.com/trac/. With it, I could make 100 asynchronous http requests at a time without using threads.
Your specific example is seldom solved with multi-threading. As many have said, this class of problems is IO-bound, meaning the processor has very little work to do, and spends most of it's time waiting for some data to arrive over the wire and to process that, and similarly it has to wait for disk buffers to flush so that it can put more of the recently downloaded data on disk.
The method to performance is through the select() facility, or an equivalent system call. The basic process is to open a number of sockets (for the web crawler downloads) and file handles (for storing them to disk). Next you set all of the different sockets and fh to non-blocking mode, meaning that instead of making your program wait until data is available to read after issuing a request, it returns right away with a special code (usually EAGAIN) to indicate that no data is ready. If you looped through all of the sockets in this way you would be polling, which works well, but is still a waste of cpu resources because your reads and writes will almost always return with EAGAIN.
To get around this, all of the sockets and fp's will be collected into a 'fd_set', which is passed to the select system call, then your program will block, waiting on ANY of the sockets, and will awaken your program when there's some data on any of the streams to process.
The other common case, compute bound work, is without a doubt best addressed with some sort of true parallelism (as apposed to the asynchronous concurrency presented above) to access the resources of multiple cpu's. In the case that your cpu bound task is running on a single threaded archetecture, definately avoid any concurrency, as the overhead will actually slow your task down.
Threads are not to be avoided nor are they "difficult". Functional programming is not necessarily the answer either. The .NET framework makes threading fairly simple. With a little thought you can make reasonable multithreaded programs.
Here's a sample of your webcrawler (in VB.NET)
Imports System.Threading
Imports System.Net
Module modCrawler
Class URLtoDest
Public strURL As String
Public strDest As String
Public Sub New(ByVal _strURL As String, ByVal _strDest As String)
strURL = _strURL
strDest = _strDest
End Sub
End Class
Class URLDownloader
Public id As Integer
Public url As URLtoDest
Public Sub New(ByVal _url As URLtoDest)
url = _url
End Sub
Public Sub Download()
Using wc As New WebClient()
wc.DownloadFile(url.strURL, url.strDest)
Console.WriteLine("Thread Finished - " & id)
End Using
End Sub
End Class
Public Sub Download(ByVal ud As URLtoDest)
Dim dldr As New URLDownloader(ud)
Dim thrd As New Thread(AddressOf dldr.Download)
dldr.id = thrd.ManagedThreadId
thrd.SetApartmentState(ApartmentState.STA)
thrd.IsBackground = False
Console.WriteLine("Starting Thread - " & thrd.ManagedThreadId)
thrd.Start()
End Sub
Sub Main()
Dim lstUD As New List(Of URLtoDest)
lstUD.Add(New URLtoDest("http://stackoverflow.com/questions/382478/how-can-threads-be-avoided", "c:\file0.txt"))
lstUD.Add(New URLtoDest("http://stackoverflow.com/questions/382478/how-can-threads-be-avoided", "c:\file1.txt"))
lstUD.Add(New URLtoDest("http://stackoverflow.com/questions/382478/how-can-threads-be-avoided", "c:\file2.txt"))
lstUD.Add(New URLtoDest("http://stackoverflow.com/questions/382478/how-can-threads-be-avoided", "c:\file3.txt"))
lstUD.Add(New URLtoDest("http://stackoverflow.com/questions/382478/how-can-threads-be-avoided", "c:\file4.txt"))
lstUD.Add(New URLtoDest("http://stackoverflow.com/questions/382478/how-can-threads-be-avoided", "c:\file5.txt"))
lstUD.Add(New URLtoDest("http://stackoverflow.com/questions/382478/how-can-threads-be-avoided", "c:\file6.txt"))
lstUD.Add(New URLtoDest("http://stackoverflow.com/questions/382478/how-can-threads-be-avoided", "c:\file7.txt"))
lstUD.Add(New URLtoDest("http://stackoverflow.com/questions/382478/how-can-threads-be-avoided", "c:\file8.txt"))
lstUD.Add(New URLtoDest("http://stackoverflow.com/questions/382478/how-can-threads-be-avoided", "c:\file9.txt"))
For Each ud As URLtoDest In lstUD
Download(ud)
Next
' you will see this message in the middle of the text
' pressing a key before all files are done downloading aborts the threads that aren't finished
Console.WriteLine("Press any key to exit...")
Console.ReadKey()
End Sub
End Module