slice_deque VS Folly

> It's not an attack on the wording, but the correctness of your first bullet point. `unsafe` is appropriate for the initialization of a ring buffer in Rust. That's true for using `mmap` or anything in "pure" Rust using the allocator API to get the most idiomatic representation (which can't be done in safe or stable Rust). It's not one line. It's also not platform dependent, the code is the same on MacOS, Linux, and Windows the last I tried it.

We're not talking about the same thing then.

I'm talking about this code here: <https://github.com/gnzlbg/slice_deque/tree/master/src/mirror...> It is absolutely platform specific.

Yes, most ring buffer implementations feature a little bit of `unsafe` code. No, it doesn't make sense to say "I have a tiny amount of `unsafe` already, so adding more has no cost."

> But if your bottleneck is determined by the frequency at which channels get created or how many exist then I would call architecture into the question. ... This last month I've written a lock-free ring buffer to solve a problem and there's exactly one in an application that spawns millions of concurrent tasks.

Okay, but a lot of applications or libraries are written to support many connections, and you don't necessarily know when writing the code (or even when your server receives them) if those connections will be just cycled very quickly or will be high-throughput long-lived affairs. Each of those probably has a send buffer and a receive buffer. So while it might make sense for your application to have a single ring buffer for its life, applications which churn through them heavily are completely valid.

There is a single contiguous memory allocation, which mirrors itself.

One thread produces elements and pushes them at the tail (e.g. I/O bytes, in batch), and one thread consumes as many elements as possible in batch from the other end (e.g. all bytes available, in batch).

The mirror is required to allow processing all elements in the deque as if they were adjacent in memory.

This is the library i am using, the array contains an explanation : https://github.com/gnzlbg/slice_deque

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