rotate VS rust

quadsort/fluxsort/crumsort author here.

For me there's a strong visual component, perhaps most obvious for my work on array rotation algorithms.

https://github.com/scandum/rotate

There's also the ability to notice strange/curious/discordant things, and either connect the dots through trying semi-random things, as well as sudden insights which seem to be partially subconscious.

One of my (many) theories is that I have the ability to use long-term memory in a quasi-similar manner to short-term memory for problem solving. My IQ is in the 120-130 range, I suffer from hypervigilance, so it's generally on the lower end due to lack of sleep.

I'd say there's a strong creative aspect. If I could redo life I might try my hand at music.

This is essentially just a rotation of a subrange of your original array. A variety of different algorithms for this operation can be found here.

Memory bandwidth is 1000x lower than CPU bandwidth, so as a rule of thumb any algorithm whose work scales linearly in the amount of data being processed will be memory bandwidth bound, and also any algorithm which can't be structured to do a lot of work on one memory region at once before moving onto the next one.

Examples (for large enough inputs that it's relevant) include shuffling, sorting, kmeans clustering, branch and bound sudoku solving, vector addition, dot products, and so on.

Moreover, writing a particular piece of code is often easier if you ignore memory bandwidth as a constraint. The classic example is matrix multiplication -- it can be structured such that even disk bandwidth isn't relevant compared to CPU bandwidth, but doing so is a little fiddly compared to the naive n^2 dot products approach, so writing it yourself usually results in a memory bandwidth bound solution for large matrices.

Similarly, writing two passes over your data rather than doing a mega-loop, the choice to use classic kmeans rather than one of its approximations (when it would be appropriate to do so), or not enforcing sortedness at some reasonable boundary and having to do additional passes over your data. It's easy to write code that hoovers up way more bandwidth than it needs to, and often faster algorithms that come out don't do anything different than access the right data at the right time to reduce that pressure, like a trinity rotation [0].

Caveat: Benchmark everything, especially as you're building intuition. Trying to fix what you think is a memory bandwidth issue can result in pipeline stalls and all sorts of fun things, especially when your server has more faster caches than your dev machine, when data in prod doesn't match your micro benchmark, ....

[0] https://github.com/scandum/rotate

If you haven't dipped your touch-typing fingers into Rust yet, you really owe it to yourself. Rust is a modern programming language with features that make it suitable not only for systems programming -- its original purpose, but just about any other environment, too; there are frameworks that let your build web services, web applications including user interfaces, software for embedded devices, machine learning solutions, and of course, command-line tools. Since a custom GitHub Action is essentially a command-line tool that interacts with the system through files and environment variables, Rust is perfectly suited for that as well.

Here's an example of someone citing a disagreement between CRT and shell32:

https://github.com/rust-lang/rust/issues/44650

This in addition to the Rust CVE mentioned elsewhere in the thread which was rooted in this issue:

https://blog.rust-lang.org/2024/04/09/cve-2024-24576.html

Here are some quick programs to test contrasting approaches. I don't have examples of inputs where they parse differently on hand right now, but I know they exist. This was also a problem that was frequently discussed internally when I worked at MSFT.

    #include 

> 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.

Almost fixed the compiler: https://github.com/rust-lang/rust/pull/123325

Rust: A secure, efficient, and modern programming language (omitting ten thousand words). You can simply follow the installation instructions provided on the official website.

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/

We strongly believe in Rust as a powerful language for building production-grade software, especially for systems like ours that run alongside Kubernetes.

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.