rust
leaf
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rust | leaf | |
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2,681 | 2 | |
92,831 | 5,552 | |
2.6% | 0.1% | |
10.0 | 0.0 | |
3 days ago | about 1 month ago | |
Rust | Rust | |
GNU General Public License v3.0 or later | Apache License 2.0 |
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.
rust
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I hate Rust (programming language)
> instead of choosing a certain numbered version of the random library (if I remember correctly) I let cargo download the latest version which had a completely different API.
Yeah, they didn't follow the instructions and got burned. I still think that multiple things went wrong simultaneously for that experience. I wonder if more prevalent uses of `#[doc(alias = "name")]` being leveraged by https://github.com/rust-lang/rust/pull/120730 (which now that I check only accounts for methods and not functions, I should get on that!) so that when changing APIs around people at least get a slightly better experience.
- Rust Weird Exprs
- Critical safety flaw found in Rust on Windows (CVE-2024-24576)
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Unformat Rust code into perfect rectangles
Almost fixed the compiler: https://github.com/rust-lang/rust/pull/123325
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Implement React v18 from Scratch Using WASM and Rust - [1] Build the Project
Rust: A secure, efficient, and modern programming language (omitting ten thousand words). You can simply follow the installation instructions provided on the official website.
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Show HN: Fancy-ANSI – Small JavaScript library for converting ANSI to HTML
Recently did something similar in Rust but for generating SVGs. We've adopted it for snapshot testing of cargo and rustc's output. Don't have a good PR handy for showing Github's rendering of changes in the SVG (text, side-by-side, swiping) but https://github.com/rust-lang/rust/pull/121877/files has newly added SVGs.
To see what is supported, see the screenshot in the docs: https://docs.rs/anstyle-svg/latest/anstyle_svg/
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Upgrading Hundreds of Kubernetes Clusters
We strongly believe in Rust as a powerful language for building production-grade software, especially for systems like ours that run alongside Kubernetes.
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What Are Const Generics and How Are They Used in Rust?
The above Assert<{N % 2 == 1}> requires #![feature(generic_const_exprs)] and the nightly toolchain. See https://github.com/rust-lang/rust/issues/76560 for more info.
- Enable frame pointers for the Rust standard library
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Learning Rust: Structuring Data with Structs
Another week, another dive into Rust. This time, we're delving into structs. Structs bear resemblance to interfaces in TypeScript, enabling the grouping of intricate data sets within an object, much like TypeScript/JavaScript. Rust also accommodates functions within these structs, offering a semblance of classes, albeit with distinctions. Let's delve into this topic.
leaf
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[D] Why does AMD do so much less work in AI than NVIDIA?
I used a lot of the dependencies behind the leaf framework which was abandoned by its authors a while back due to funding issues, as I implemented it in Rust and most bindings were maintained while the leaf framework itself wasn't anymore.
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AMD Demonstrates Stacked 3D V-Cache Technology: 192 MB at 2 TB/SEC
I tried to create a ML framework[0] that would work on both CUDA and OpenCL (and natively on the CPU) around 2015/2016, which included creating FFI wrappers for both CUDA and OpenCL. This is where my experience on the subject (and my contempt for NVIDIA) comes from.
Me memory isn't perfect, but IIRC the situation was roughly the following: We were quite short on resources (both devtime and money), which meant that we had to choose our scope wisely. Optimally we would have implemented both CUDA and OpenCL 2.0, but we had to settle for OpenCL 1.2 (which offered reduced performance, but was "good enough" for inference). IIRC OpenCL 2.0 was very very similar in what capabilities it assumed and offered to the CUDA version at the time, and cards like the GTX Titan X had "compute capabilities" that supported features like shared virtual memory between CPU and GPU in CUDA at the time. In fact the advances around memory management (and async copying) that were present in CUDA and not in OpenCL 1.x were the main source for the performance differences between the two.
From everything that I can tell at that point in time, if NVIDIA would have wanted to support OpenCL 2.0 they could have done so based on technical requirements. What the reason for not doing so is, is just pure speculation (lack of internal resources due to focusing on devtools?), but to me it always looked like they were using the edge they got via their proprietary libraries like cuDNN to get a foot into the field of ML and then purposefully neglected OpenCL to prevent any competitors from catching up. Classic Embrace, Extend, Extinguish.
[0]: https://github.com/autumnai/leaf
What are some alternatives?
carbon-lang - Carbon Language's main repository: documents, design, implementation, and related tools. (NOTE: Carbon Language is experimental; see README)
rusty-machine - Machine Learning library for Rust
zig - General-purpose programming language and toolchain for maintaining robust, optimal, and reusable software.
rust - Rust language bindings for TensorFlow
Nim - Nim is a statically typed compiled systems programming language. It combines successful concepts from mature languages like Python, Ada and Modula. Its design focuses on efficiency, expressiveness, and elegance (in that order of priority).
rustlearn - Machine learning crate for Rust
Odin - Odin Programming Language
CNTK - Wrapper around Microsoft CNTK library
Elixir - Elixir is a dynamic, functional language for building scalable and maintainable applications
opencl3 - A Rust implementation of the Khronos OpenCL 3.0 API.
Rustup - The Rust toolchain installer
qdrant - Qdrant - High-performance, massive-scale Vector Database for the next generation of AI. Also available in the cloud https://cloud.qdrant.io/