RustTokioBenchmark VS burn

Compare RustTokioBenchmark vs burn and see what are their differences.

RustTokioBenchmark

Simple benchmark comparing tokio mpsc with standard rust one (by eras)

burn

Burn is a new comprehensive dynamic Deep Learning Framework built using Rust with extreme flexibility, compute efficiency and portability as its primary goals. (by tracel-ai)
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RustTokioBenchmark burn
1 9
0 7,526
- 6.0%
2.7 9.8
about 2 months ago 4 days ago
Rust Rust
MIT License Apache License 2.0
The number of mentions indicates the total number of mentions that we've tracked plus the number of user suggested alternatives.
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RustTokioBenchmark

Posts with mentions or reviews of RustTokioBenchmark. We have used some of these posts to build our list of alternatives and similar projects. The last one was on 2024-04-26.
  • 3 years of fulltime Rust game development, and why we're leaving Rust behind
    21 projects | news.ycombinator.com | 26 Apr 2024
    > If you ever pull up a debugger and step through an async Rust/tokio codebase, you'll get a good sense for what the overhead here we're talking about is.

    So I didn't quite do that, but the overhead was interesting to me anyway, and as I was unable to find existing benchmarks (surely they exist?), I instructed computer to create one for me: https://github.com/eras/RustTokioBenchmark

    On this wee laptop the numbers are 532 vs 6381 cpu cycles when sending a message (one way) from one async thread to another (tokio) or one kernel thread to another (std::mpsc), when limited to one CPU. (It's limited to one CPU as rdtscp numbers are not comparable between different CPUs; I suppose pinning both threads to their own CPUs and actually measuring end-to-end delay would solve that, but this is what I have now.)

    So this was eye-opening to me, as I expected tokio to be even faster! But still, it's 10x as fast as the thread-based method.. Straight up callback would still be a lot faster, of course, but it will affect the way you structure your code.

    Improvements to methodology accepted via pull requests :).

burn

Posts with mentions or reviews of burn. We have used some of these posts to build our list of alternatives and similar projects. The last one was on 2024-04-26.

What are some alternatives?

When comparing RustTokioBenchmark and burn you can also consider the following projects:

dfdx - Deep learning in Rust, with shape checked tensors and neural networks

candle - Minimalist ML framework for Rust

wonnx - A WebGPU-accelerated ONNX inference run-time written 100% in Rust, ready for native and the web

tch-rs - Rust bindings for the C++ api of PyTorch.

rust-mlops-template - A work in progress to build out solutions in Rust for MLOPs

llama2.rs - A fast llama2 decoder in pure Rust.

albumin - Simple Hierarchical Album Generator

Enzyme - High-performance automatic differentiation of LLVM and MLIR.

corgi - A neural network, and tensor dynamic automatic differentiation implementation for Rust.

rust-ndarray - ndarray: an N-dimensional array with array views, multidimensional slicing, and efficient operations

are-we-learning-yet - How ready is Rust for Machine Learning?

cob-webber - Shelob of Cirith Ungol

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