I'm designing an application for an asphalt batch mix plant, using a thread to run the mixing process, several timers to read system states and perform control actions.
If "Hyper-Threading" features is disabled, the application will run smoothly, everything is OK; or it will bring up a dialog grumbling that memory access is invalid and abort immediately after click "OK".
Don't know why? Maybe something wrong with IDE version, since Delphi 5 was released at 10th August 1999; maybe the thread unit in Delphi 5.0 cannot deal with new CPU technology?
Maybe memory management has some bugs, maybe the thread mode is not suitable for new era?
I want to upgrade the IDE, but since there are many many years pasted, I have no idea which would be the best choice,
Delphi 7? Delphi 2007(which support OmniThreadLibrary)? RAD Studio XE6/7? Hope someone will help.
The most plausible explanation is that your program has a bug related to threading. You happen to get away with the flaw in your code when hyperthreading is disabled, but enabling it is sufficient to make the error in your code manifest.
Threading bugs are just like this. They will manifest if threads execute specific code in a particular order, with respect to the other threads. And the relative ordering is unpredictable. Which is part and parcel of parallel computation. Code that is broken can appear to be correct when running under one environment, but then fail under another. Whilst it is tempting to blame the tools, always check in the mirror first.
Changing development environment is not the solution. What you need to do is to find and then fix the error in your code. Getting a good stack trace will help, and I can recommend a tool like madExcept for that.
I have a django application which relies heavily on threading and I'm noticing no performance increment no matter how much processes or threads I add to the WSGIDaemonProcess.
I can't find a YES/NO answer out there and I'm wondering. Could it be that mod_wsgi is using the same interpreter for each request so I'm running in a bottleneck due to a GIL limitation?
If so, would you recommend something else that would help me workaround this limitation?
For a typical configuration, yes, all requests would be handle in same sub interpreter.
If in different sub interpreters of same process, you are still affected by the GIL.
Post your actual mod_wsgi configuration to confirm you have set things up right.
Consider trying New Relic to find out where real bottlenecks are.
Watch my PyCon US 2012 talk on finding bottlenecks
Short answer:
No.
Long answer:
This ability to make good use of more than processor, even when using multithreading, is further enchanced by the fact that Apache uses multiple processes for handling requests and not just a single process. Thus, even when there is some contention for the GIL within a specific process, it doesn't stop other processes from being able to run as the GIL is only local to a process and does not extend across processes.
Citation: https://code.google.com/p/modwsgi/wiki/ProcessesAndThreading
You haven't given enough information for anybody to recommend how to improve performance, but if you've actually written a thread-heavy program in Python, that's your first mistake.
Instead of running your program on CPython, maybe you should try Jython or IronPython instead. But then it wouldn't work with mod_wsgi, so we really need more details to understand what you're trying to do...
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.
Now here's something interesting. When I have more than one thread in Tcl invoking package require Expect, I get a seg fault.
e.g.
package require Threads
package require Expect
set t [thread::create]
thread::send {package require Expect}
puts "blarg! Damned thing crashes before I get here"
This is not a good time. Any thoughts?
Expect and Threads don't go together too well. Its the complexity you get from fork() + threads that can bite a lot there and lead to deadlocks and all kinds of uglyness. Usually not a good idea to combine the two.
If you really need Expect and the added concurrency a multi process approach with on multi threaded driver program and one single threaded expect process might work better. If you used tcllibs comm package the api's for sending commands are not that much different either (you mostly miss the tsv and tpool stuff if you used comm).
But it shouldn't segfault for sure. Which Expect/Threads/Tcl core combination did you use (e.g. ActiveStates ActiveTcl bundle or some self compiled stuff on an unusual platform?)
It's all from the latest debian packages, Ubuntu 9.0.4, 64 bit.
One alternative is to organize the code such that one thread is dedicated to handling all expect calls...which isn't the most elegant, generic solution but it might have to do.
The C code of the expect library (loaded with package require Expect) is not thread-safe (it probably uses global variables or else). I tried a lot to work around this limitation because I wanted to have a load balancing algorithm based on the Thread library which would pilot some expect code launching builds on a pool of slave machines. Unless you are very good at C and want to enhance expect, I would rather suggest to launch expect interpreters (in their own OS process) each time you need to use it from your Thread-enabled program. But of course I don't know your problem to solve, and this would only work if the "expect works" are unrelated.. Good luck anyway..