Folly VS tokio

https://github.com/facebook/folly/commit/b1391e1c57be71c1e2a...

https://github.com/facebook/folly/pull/2153

To set a HP on Linux, Folly just does a relaxed load of the src pointer, release store of the HP, compiler-only barrier, and acquire load. (This prevents the compiler from reordering the 2nd load before the store, right? But to my understanding does not prevent a hypothetical CPU reordering of the 2nd load before the store, which seems potentially problematic!)

Then on the GC/reclaim side of things, after protected object pointers are stored, it does a more expensive barrier[0] before acquire-loading the HPs.

I'll admit, I am not confident I understand why this works. I mean, even on x86, loads can be reordered before earlier program-order stores. So it seems like the 2nd check on the protection side could be ineffective. (The non-Linux portable version just uses an atomic_thread_fence SeqCst on both sides, which seems more obviously correct.) And if they don't need the 2nd load on Linux, I'm unclear on why they do it.

[0]: https://github.com/facebook/folly/blob/main/folly/synchroniz...

(This uses either mprotect to force a TLB flush in process-relevant CPUs, or the newer Linux membarrier syscall if available.)

folly provides functions to resize std::string & std::vector without initialization [0].

[0] https://github.com/facebook/folly/blob/3c8829785e3ce86cb821c...

My implementation was quite similar to Boost's spsc_queue and Facebook's folly/ProducerConsumerQueue.h.

> How is that relevant?

Roaring bitmaps and similar data structures get their speed from decoding together consecutive groups of elements, so if you do sequential decoding or decode a large fraction of the list you get excellent performance.

EF instead excels at random skipping, so if you visit a small fraction of the list you generally get better performance. This is why it works so well for inverted indexes, as generally the queries are very selective (otherwise why do you need an index?) and if you have good intersection algorithms you can skip a large fraction of documents.

I didn't follow the rest of your comment, select is what EF is good at, every other data structure needs a lot more scanning once you land on the right chunk. With BMI2 you can also use the PDEP instruction to accelerate the final select on a 64-bit block: https://github.com/facebook/folly/blob/main/folly/experiment...

C++ with folly's SCOPE_EXIT {} construct:

https://github.com/facebook/folly/blob/main/folly/ScopeGuard...

Seems like github issues taking a long time to get any response: https://github.com/facebook/folly

Can't speak for abseil and tbb, but in folly there are a few solutions for the common problem of sharing state between a writer that updates it very infrequently and concurrent readers that read it very frequently (typical use case is configs).

The most performant solutions are RCU (https://github.com/facebook/folly/blob/main/folly/synchroniz...) and hazard pointers (https://github.com/facebook/folly/blob/main/folly/synchroniz...), but they're not quite as easy to use as a shared_ptr [1].

Then there is simil-shared_ptr implemented with thread-local counters (https://github.com/facebook/folly/blob/main/folly/experiment...).

If you absolutely need a std::shared_ptr (which can be the case if you're working with pre-existing interfaces) there is CoreCachedSharedPtr (https://github.com/facebook/folly/blob/main/folly/concurrenc...), which uses an aliasing trick to transparently maintain per-core reference counts, and scales linearly, but it works only when acquiring the shared_ptr, any subsequent copies of that would still cause contention if passed around in threads.

[1] Google has a proposal to make a smart pointer based on RCU/hazptr, but I'm not a fan of it because generally RCU/hazptr guards need to be released in the same thread that acquired them, and hiding them in a freely movable object looks like a recipe for disaster to me, especially if paired with coroutines https://www.open-std.org/jtc1/sc22/wg21/docs/papers/2020/p05...

Not sure if it's still the case but about 6 years ago Facebook's folly C++ library was something I'd point to for my junior engineers to get a sense of "good" C++ https://github.com/facebook/folly

Being able to control nondeterminism is particularly useful for testing and debugging. This allows creating reproducible test environments, as well as discrete-event simulation for faster-than-real-time simulation of time delays. For example, Cardano uses a simulation environment for the IO monad that closely follows core Haskell packages; Sui has a simulator based on madsim that provides an API-compatible replacement for the Tokio runtime and intercepts various POSIX API calls in order to enforce determinism. Both allow running the same code in production as in the simulator for testing.

tokio / hyper / toml / serde / serde_json / json5 / console

tokio - An asynchronous runtime for Rust

3. Tokio

The AWS SDK makes use of the async capabilities in the Tokio library. So when you see async in front of a fn that function is capable of executing asynchronously.

Petar is also looking at implementing concurrency the way it is in Go to have a fully functional virtual machine as it is in the spec. This would likely attract more external contributors to developing the VM. One advantage of Rust is that, with the concurrency model, there is already an extensive library called Tokio which he can use. Petar stresses that this isn’t easy, but he believes it’s achievable, at least as a research topic around determinism and concurrency.

Another thing to point out is that async is a thing in Rust. I'm not going to begin to dive into this paradigm in this article, but know it's handled by the awesome Tokio framework.

So I started by using Tokio, a popular async runtime. The docs and samples helped me get a simple outbound TCP connection working. The Rust async book also had a lot of good explanations, both practical and digging into the details of what a runtime does.

Regarding the quote:

> The Original Sin of Rust async programming is making it multi-threaded by default. If premature optimization is the root of all evil, this is the mother of all premature optimizations, and it curses all your code with the unholy Send + 'static, or worse yet Send + Sync + 'static, which just kills all the joy of actually writing Rust.

Agree about the melodramatic tone. I also don't think removing the Send + Sync really makes that big a difference. It's the 'static that bothers me the most. I want scoped concurrency. Something like <https://github.com/tokio-rs/tokio/issues/2596>.

Another thing I really hate about Rust async right now is the poor instrumentation. I'm having a production problem at work right now in which some tasks just get stuck. I wish I could do the equivalent of `gdb; thread apply all bt`. Looking forward to <https://github.com/tokio-rs/tokio/issues/5638> landing at least. It exists right now but is experimental and in my experience sometimes panics. I'm actually writing a PR today to at least use the experimental version on SIGTERM to see what's going on, on the theory that if it crashes oh well, we're shutting down anyway.

Neither of these complaints would be addressed by taking away work stealing. In fact, I could keep doing down my list, and taking away work stealing wouldn't really help with much of anything.

The PHP <-> Rust bindings are provided by https://github.com/Nicelocal/ext-php-rs/ (our fork of https://github.com/davidcole1340/ext-php-rs with a bunch of UX improvements :).

php-tokio's integrates the https://revolt.run event loop with the https://tokio.rs event loop; async functionality is provided by the two event loops, in combination with PHP fibers through revolt's suspension API (I could've directly used the PHP Fiber API to provide coroutine suspension, but it was a tad easier with revolt's suspension API (https://revolt.run/fibers), since it also handles the base case of suspension in the main fiber).