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fiberize's Introduction

Fiberize

The PoC for a library to help us create cooperative programs using JavaScript.

Screencast

Demo

For a intuitive feeling, clone this repo and run it:

$ npm i

then:

$ npm test

And there is also a browser version, run this:

$ npm run build && open ./demo.html

Prior Art

React Fiber introduced an approach that can make the diffing process interruptible. The idea behind it is to use a looping-based algorithm to replace the old stack-based algorithm. A loop is much easier to jump out because the callstack is not deep (and there is literally no setjmp/longjmp in JavaScript). And to make the works resumable, we need a new data structure to record which stage we were processing, that is what Fiber does.

Fiber is pretty like a linked-tree, and is just a plain-old-JavaScript-object. It has child, sibling and return pointers to keep track each of its relationships.

A Glance of the Fiberize

const { run, executeWhileIdle } = require('fiberize');

function* fib(n) {
  if (n <= 2) {
    return 1;
  }

  return (yield fib(n - 1)) + (yield fib(n - 2));
}

function* main() {
  for (let i = 1; i < 40; i++) {
    const res = yield fib(i);
    console.log(res);
  }
}

run(main());
executeWhileIdle();

console.log('Back to main.');
setInterval(function () {
  console.log('Main loop is still alive!!');
}, 1000);

When you run this, you should see the program keeps printing the fibonacci results, while the main loop is still ready to response (the timer is working).

Behind the Scene

If you take a look at the executeWhileIdle function:

export function executeWhileIdle() {
  if (!executeUntilDeadline(Date.now() + 10)) {
    setTimeout(executeWhileIdle, 0);
  }
}

You'll find that we limit the work that can only be executing before a deadline (in this case, 10ms).

To make a long-term work interruptible, we must divide it in to small pieces. That is exactly what yield does. yields in your code will suspend the underlying generator (aka. stackless coroutine, and that will save all the contexts for resuming the work) and return to our scheduler code.

The scheduler simply checks whether there is enough time to continue the work. If the time is up, executeUntilDeadline function will return with false, indicating that the work isn't done but there is no enough time to continue. Then, we will call setTimeout to request another opportunity to continue our works. After setTimeout is called, JavaScript event-loop is allowed to process its events and tasks such as I/O, timers, rendering, etc.

So, your long-term work and other code can be executing cooperatively, no more blocking.

Tasks Dispatching

As you can see, the fib function in the demo above yield with another generator by calling fib itself. Regardless of the recursion, let's talk about what is happening when you do this.

What you yield is called a syscall, yeah, that's a metaphor: an instruction to the scheduler. And yielding an generator is just a syntactic sugar of run syscall.

A run syscall will put the current work into wait state (wait for the return value of the new work) and spawn a new work, when the new work is done, scheduler resumes the previously suspended work and send it the return value.

Browser-Side Execution

Modern browsers provide an API called requestIdleCallback, which will give us a more precise deadline for each execution period. Combining the usage of requestAnimationFrame, we may be able to achieve task priorities.

Further Research

Now the library only has a foundation and is obviously incomplete. To make it full-fledged, there is a to-do list:

  • Improved scheduling algorithm.

The current algorithm is just simple "FCFS" (First-Come, First-Served). But most of operating systems may use "RR" (Round Robin) or priority scheduling. To make it, I may need to refactor the scheduler and design the work structure detailly.

  • More concurrent primitive.

run syscall just make the caller work suspend, but there may be some scenarios that we need perform some works concurrently.

And there are some hypothetical syscalls we can implement:

  • spawn

    • Behavior: similar to run, but will not suspend the caller.
    • Parameters: a generator.
    • Returns: an opaque handle to the spawned work.
  • join

    • Behavior: put the caller into wait state until the given work is finished.
    • Parameters: a handle to work.
    • Returns: (TBD)
  • park

    • Behavior: put the caller or a given work into wait state.
    • Parameters: a handle to work or null (represents self).
    • Returns: none
  • unpark

    • Behavior: wake up the given work.
    • Parameters: a handle to work.
    • Returns: none

With those syscalls, we will have enough primitives to create higher level abstracts, like "Semaphore".

  • Interactions between works and external environment.

In a work function, we can call external functions to interact with external environment. But that is not quite safe, and there are no ways to get to know the result of a work without doing that.

And we also need a way to get the self-information of a work. That's kinda like a set of syscalls without yield that directly return something about the current work.

  • Work cancellation.

Cancel a single work is easy, but currently it's hard to cancel all the works it ran or spawned. A structure is needed to record the child works and resources related to a certain work.

  • Parallel execution.

This feature is hard to implement in JavaScript and yet I don't have any idea of that. Comparing to Golang, we now have the Processor (P) and Goroutines (G) alternatives, but no OSThread (M) alternatives. Because JavaScript literally doesn't support multi-thread. Web Workers may not work due to the context isolation. So Fiberize is so far completely user-land green thread implementation.

Contribution

This library is not targeted to production-use and will be slowly developed. If you are interested with it and want to standardize it, feel free to leave an issue and let me know.

License

The Unlicense

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