orion VS libjpeg-turbo

GitHub: https://github.com/orion-rs/orion Crates.io: https://crates.io/crates/orion

I'm the author and maintainer of a pure-Rust crypto library called Orion. I've been at it for a couple of years now, working on it in my spare time as well. There are a few people involved already, but we're still missing someone that is involved enough to be a "co-maintainer". There are some larger features that have been planned, but I lack the time currently to start too many new things. Of course, you can contribute in any amount you want.

Custom (the ones I have in the implementation I wrote)

With that said, i think multiple people are working on crypto libraries that take footguns out of it - which is what i think we definitely need. https://github.com/brycx/orion seems like a solid attempt at making crypto fool-proof , so i do have hope.

You're more than welcome to swing by at Orion (a pure-Rust crypto lib). You can also check the new Matrix room for a small chat.

> all decoders will render the same pixels

Not true. Even just within libjpeg, there are three different IDCT implementations (jidctflt.c, jidctfst.c, jidctint.c) and they produce different pixels (it's a classic speed vs quality trade-off). It's spec-compliant to choose any of those.

A few years ago, in libjpeg-turbo, they changed the smoothing kernel used for decoding (incomplete) progressive JPEGs, from a 3x3 window to 5x5. This meant the decoder produced different pixels, but again, that's still valid:

https://github.com/libjpeg-turbo/libjpeg-turbo/commit/6d91e9...

Last vestiges of this fact AFAIK were libjpeg, which had a macro NEED_SHORT_EXTERNAL_NAMES that shortens all public identifiers to have unique 6-letter-long prefixes. Libjpeg-turbo nowadays has removed them though [1].

[1] https://github.com/libjpeg-turbo/libjpeg-turbo/commit/52ded8...

While I think the move to safer code through Rust and other alternatives is a nice breath of fresh air, I doubt you can get these kinds of optimization without using unsafe code in Rust. These optimized implementations often require some kind of safety-bypassing memory modifications to work as efficiently ad they do.

There's a reason https://github.com/libjpeg-turbo/libjpeg-turbo/tree/main/sim... is filled with assembly files with conditional loading.

Sure. You'll see it very often in codec implementations. From rav1e, a fast AV1 encoder mostly written in Rust: https://github.com/xiph/rav1e/tree/master/src/x86

Large portions of the algorithm have been translated into assembly for ARM and x86. Shaving even a couple percent off something like motion compensation search will add up to meaningful gains.

Or the current reference implementation of JPEG: https://github.com/libjpeg-turbo/libjpeg-turbo/tree/main/sim...

zune-jpeg is 1.5x to 2x faster than jpeg-decoder and is on par with libjpeg-turbo.

This is interesting from the standpoint of how new JVM features can be used to improve performance (what I presume the article's main purpose to have been), but the image processing improvement itself isn't head-turning. Also, we've found that libjpeg-turbo (https://libjpeg-turbo.org/) is ~5x (IIRC, can re-run my JMH benchmark if anyone wants me to) as fast for decoding JPEGs as ImageIO, so we wouldn't even benefit from this change in 21 much.

libjpeg-turbo: https://github.com/libjpeg-turbo/libjpeg-turbo/blob/main/simd/x86_64/jsimdcpu.asm

libjpeg-turbo

For all but the simplest formats (basically BMP), the difficulty of implementing encoding/decoding from scratch is significant - well beyond a beginner's ability, and challenging/time-consuming even for senior developers. So, libraries are used in practice - e.g. libpng and libjpeg-turbo.