OSStreams VS hyperia

Compare OSStreams vs hyperia and see what are their differences.

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OSStreams hyperia
1 1
11 44
- -
0.0 3.2
about 3 years ago almost 3 years ago
C++ Zig
Apache License 2.0 MIT License
The number of mentions indicates the total number of mentions that we've tracked plus the number of user suggested alternatives.
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.

OSStreams

Posts with mentions or reviews of OSStreams. We have used some of these posts to build our list of alternatives and similar projects. The last one was on 2021-09-13.

hyperia

Posts with mentions or reviews of hyperia. We have used some of these posts to build our list of alternatives and similar projects. The last one was on 2021-09-13.
  • Lock-free, allocation-free, efficient thread pool
    6 projects | news.ycombinator.com | 13 Sep 2021
    This actually can be at the level of a missed optimization. A run queue with a lock-shared queue amongs all the threads scales even worse than the tokio version. Sharding the run queues and changing the notification algorithm, even while keeping locks on the sharded queues improves throughput drastically.

    Tokio is an async runtime, but I don't see why being an async runtime should make it worse from a throughput perspective for a thread pool. I actually started on a Rust version [0] to test out this theory of whether async-rust was the culprit, but realized that I was being nerd-sniped [1] at this point and I should continue my Zig work instead. If you're still interested, I'm open to receiving PRs and questions on that if you want to see that in action.

    It's still correct to benchmark and compare tokio here given the scheduler I was designing was mean to be used with async tasks: a bunch of concurrent and small-executing work units. I mention this in the second paragraph of "Why Build Your Own?".

    The thread pool in the post is meant to be used to distribute I/O bound work. A friend of mine hooked up cross-platform I/O abstractions to the thread pool [2], benchmarked it against tokio to be have greater throughput and slightly worse tail latency under a local load [3]. The thread pool serves it's purpose and the quicksort benchmark is to show how schedulers behave under relatively concurrent work-loads. I could've used a benchmark with smaller tasks than the cpu-bound partition()/insertion_sort() but this worked as a common example.

    I've already mentioned why rayon isn't a good comparison: 1. It doesn't support async root concurrency. 2. scoped() waits for tasks to complete by either blocking the OS thread or using similar inline-scheduler-loop optimizations. This risks stack overflow and isn't available as a use case in other async runtimes due to primarily being a fork-join optimization.

    [0]: https://github.com/kprotty/zap/blob/blog-rust/src/thread_poo...

    [1]: https://xkcd.com/356/

    [2]: https://github.com/lithdew/hyperia

    [3]: https://gist.github.com/kprotty/5a41e9612657de00788478a7dde4...

What are some alternatives?

When comparing OSStreams and hyperia you can also consider the following projects:

spl-token-ui - Interface for creating and managing SPL Tokens

zap - An asynchronous runtime with a focus on performance and resource efficiency.

forem - For empowering community 🌱

tokio - A runtime for writing reliable asynchronous applications with Rust. Provides I/O, networking, scheduling, timers, ...

ni-media - NI Media is a C++ library for reading and writing audio streams.

Memgraph - Open-source graph database, built for real-time streaming data, compatible with Neo4j.