Tutorial :Thread vs async execution. What's different?



Question:

I believed any kind of asynchronous execution makes a thread in invisible area. But if so,

  • Async codes does not offer any performance gain than threaded codes.

But I can't understand why so many developers are making many features async form. Could you explain about difference and cost of them?


Solution:1

The purpose of an asynchronous execution is to prevent the code calling the asynchronous method (the foreground code) from being blocked. This allows your foreground code to go on doing useful work while the asynchronous thread is performing your requested work in the background. Without asynchronous execution, the foreground code must wait until the background task is completed before it can continue executing.

The cost of an asynchronous execution is the same as that of any other task running on a thread.

Typically, an async result object is registered with the foreground code. The async result object can either raise an event when the background task is completed, or the foreground code can periodically check the async result object to see if its completion flag has been set.


Solution:2

Concurrency does not necessarily require threads.

In Linux, for example, you can perform non-blocking syscalls. Using this type of calls, you can for instance start a number of network reads. Your code can keep track of the reads manually (using handles in a list or similar) and periodically ask the OS if new data is available on any of the connections. Internally, the OS also keeps a list of ongoing reads. Using this technique, you can thus achieve concurrency without any (extra) threads, neither in your program nor in the OS.

If you use threads and blocking IO, you would typically start one thread per read. In this scenario, the OS will instead have a list of ongoing threads, which it parks when the tread tries to read data when there is none available. Threads are resumed as data becomes available.

Having the OS switch between threads might involve slightly more overhead in the form of context switching - switching program counter and register content. But the real deal breaker is usually stack allocation per thread. This size is a couple of megabytes by default on Linux. If you have a lot of concurrency in your program, this might push you in the direction of using non-blocking calls to handle more concurrency per thread.

So it is possible to do async programming without threads. If you want to do async programming using only blocking OS-calls you need to dedicate a thread to do the blocking while you continue. But if you use non-blocking calls you can do a lot of concurrent things with just a single thread. Have a look at Node.js, which have great support for many concurrent connections while being single-threaded for most operations.

Also check out Golang, which achieve a similar effect using a sort of green threads called goroutines. Multiple goroutines run concurrently on the same OS thread and they are restrictive in stack memory, pushing the limit much further.


Solution:3

  • Async codes does not offer any performance gain than threaded codes.

Asynchornous execution is one of the traits of multi-threaded execution, which is becoming more relevant as processors are packing in more cores.

For servers, multi-core only mildly relevant, as they are already written with concurrency in mind and will scale natrually, but multi-core is particularly relevant for desktop apps, which traditionally do only a few things concurrently - often just one foreground task with a background thread. Now, they have to be coded to do many things concurrently if they are to take advantage of the power of the multi-core cpu.

As to the performance - on single-core - the asynchornous tasks slow down the system as much as they would if run sequentially (this a simplication, but true for the most part.) So, running task A, which takes 10s and task B which takes 5s on a single core, the total time needed will be 15s, if B is run asynchronously or not. The reason is, is that as B runs, it takes away cpu resources from A - A and B compete for the same cpu.

With a multi-core machine, additional tasks run on otherwise unused cores, and so the situation is different - the additional tasks don't really consume any time - or more correctly, they don't take away time from the core running task A. So, runing tasks A and B asynchronously on multi-core will conume just 10s - not 15s as with single core. B's execution runs at the same time as A, and on a separate core, so A's execution time is unaffected.

As the number of tasks and cores increase, then the potential improvements in performance also increase. In parallel computing, exploiting parallelism to produce an improvement in performance is known as speedup.

we are already seeing 64-core cpus, and it's esimated that we will have 1024 cores commonplace in a few years. That's a potential speedup of 1024 times, compared to the single-threaded synchronous case. So, to answer your question, there clearly is a performance gain to be had by using asynchronous execution.


Solution:4

I believed any kind of asynchronous execution makes a thread in invisible area.

This is your problem - this actually isn't true.

The thing is, your whole computer is actually massively asynchronous - requests to RAM, communication via a network card, accessing a HDD... those are all inherently asynchronous operations.

Modern OSes are actually built around asynchronous I/O. Even when you do a synchronous file request, for example (e.g. File.ReadAllText), the OS sends an asynchronous request. However, instead of giving control back to your code, it blocks while it waits for the response to the asynchronous request. And this is where proper asynchronous code comes in - instead of waiting for the response, you give the request a callback - a function to execute when the response comes back.

For the duration of the asynchronous request, there is no thread. The whole thing happens on a completely different level - say, the request is sent to the firmware on your NIC, and given a DMA address to fill the response. When the NIC finishes your request, it fills the memory, and signals an interrupt to the processor. The OS kernel handles the interrupt by signalling the owner application (usually an IOCP "channel") the request is done. This is still all done with no thread whatsoever - only for a short time right at the end, a thread is borrowed (in .NET this is from the IOCP thread pool) to execute the callback.

So, imagine a simple scenario. You need to send 100 simultaneous requests to a database engine. With multi-threading, you would spin up a new thread for each of those requests. That means a hundred threads, a hundread thread stacks, the cost of starting a new thread itself (starting a new thread is cheap - starting a hundred at the same time, not so much), quite a bit of resources. And those threads would just... block. Do nothing. When the response comes, the threads are awakened, one after another, and eventually disposed.

On the other hand, with asynchronous I/O, you can simply post all the requests from a single thread - and register a callback when each of those is finished. A hundred simultaneous requests will cost you just your original thread (which is free for other work as soon as the requests are posted), and a short time with threads from the thread pool when the requests are finished - in "worst" case scenario, about as many threads as you have CPU cores. Provided you don't use blocking code in the callback, of course :)

This doesn't necessarily mean that asynchronous code is automatically more efficient. If you only need a single request, and you can't do anything until you get a response, there's little point in making the request asynchronous. But most of the time, that's not your actual scenario - for example, you need to maintain a GUI in the meantime, or you need to make simultaneous requests, or your whole code is callback-based, rather than being written synchronously (a typical .NET Windows Forms application is mostly event-based).

The real benefit from asynchronous code comes from exactly that - simplified non-blocking UI code (no more "(Not Responding)" warnings from the window manager), and massively improved parallelism. If you have a web server that handles a thousand requests simultaneously, you don't want to waste 1 GiB of address space just for the completely unnecessary thread stacks (especially on a 32-bit system) - you only use threads when you have something to do.

So, in the end, asynchronous code makes UI and server code much simpler. In some cases, mostly with servers, it can also make it much more efficient. The efficiency improvements come precisely from the fact that there is no thread during the execution of the asynchronous request.

Your comment only applies to one specific kind of asynchronous code - multi-threaded parallelism. In that case, you really are wasting a thread while executing a request. However, that's not what people mean when saying "my library offers an asynchronous API" - after all, that's a 100% worthless API; you could have just called await Task.Run(TheirAPIMethod) and gotten the exact same thing.


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