Folly VS minisketch

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

Anyone interested in IBLT with low failure probablity should also be aware of pinsketch and, particularly, our implementation of it: minisketch ( https://github.com/sipa/minisketch/ ).

Our implementation communicates a difference of N b-bit entries with exactly N*b bits with 100% success. The cost for this communications efficiency and reliability is that the decoder takes CPU time quadratic in N, instead of IBLT's linear decoder. However, when N is usually small, if the implementation is fast this can be fine -- especially since you wouldn't normally want to use set recon unless you were communications limited.

Pinsketches and iblt can also be combined-- one can use pinsketches as the cells of an iblt and one can also use a small pinsketch to improve the failure rate of an iblt (since when a correctly sized IBLT fails, it's usually just due to a single undecodable cycle).

Since the protocol appears to use adhoc synchronization, the authors might be interested in https://github.com/sipa/minisketch/ which is a library that implements a data structure (pinsketch) that allows two parties to synchronize their sets of m b-bit elements which differ by c entries using only b*c bits. A naive protocol would use m*b bits instead, which is potentially much larger.

I'd guess that under normal usage the message densities probably don't justify such efficient means-- we developed this library for use in bitcoin targeting rates on the order of a dozen new messages per second and where every participant has many peers with potentially differing sets--, but it's still probably worth being aware of. The pinsketch is always equal or more efficient than a naive approach, but may not be worth the complexity.

The somewhat better known IBLT data structure has constant overheads that make it less efficient than even naive synchronization until the set differences are fairly large (particular when the element hashes are small); so some applications that evaluated and eschewed IBLT might find pinsketch applicable.

I love the set reconciliation structures like the IBLT (Iterative Bloom Lookup Table) and BCH set digests like minisketch.

https://github.com/sipa/minisketch

Lets say you have a set of a billion items. Someone else has mostly the same set but they differ by 10 items. These let you exchange messages that would fit in one UDP packet to reconcile the sets.

Sipa is working on a better version of that for a while. The technical term is a "set reconciliation protocol", but Bitcoin Core been doing a more basic version of this for a while. Note that the "BCH" there isn't the same as Bcash

I'd also have to say that Zig is a pretty neat library for this. In order to implement PBS I needed the MiniSketch-library (written in C/C++) and I'll have to say that integrating with it has been a breeze. Some fiddling in build.zig so that I can avoid Makefile, and after that everything has worked amazingly.

Networks that need to constrain themselves to limited typologies to avoid traffic magnification do so at the expense of robustness, especially against active attackers that grind their identifiers to gain privileged positions.

Maybe this is a space where efficient reconciliation ( https://github.com/sipa/minisketch/ ) could help-- certainly if the goal were to flood messages to participants reconciliation can give almost optimal communication without compromising robustness.