ZLUDA VS murex

It now supports AMD GPUs since 3 weeks ago, check the latest commit at the repo:

https://github.com/vosen/ZLUDA

The article also mentions exactly this fact.

Looks like nvidia is trying to keep the lynchpin of their entire business model from crumbling underneath them. ZLUDA lets you run unmodified CUDA applications with near-native performance on AMD GPUs.

https://github.com/vosen/ZLUDA

With Triton looking to eclipse CUDA entirely, im not sure this prohibition does anything more than placate casual shareholders.

>Dark API functions are reverse-engineered and implemented by ZLUDA on a case-by-case basis once we observe an application making use of it.

https://github.com/vosen/ZLUDA/blob/master/ARCHITECTURE.md

> I know AMD have their competition, but their GPU software division keeps tripping over itself.

They are actively stepping on every rake there is. Eg they just stopped supporting the drop-in-cuda project everyone is waiting for, due to there being "no business-case for CUDA on AMD GPUs" [0].

[0] https://github.com/vosen/ZLUDA?tab=readme-ov-file#faq

https://github.com/vosen/ZLUDA

They still funded it and it was created.

From the same repo, I found this excellent, well-written architecture document: https://github.com/vosen/ZLUDA/blob/master/ARCHITECTURE.md

I love the direct, "no bullshit" style of writing.

Some gems:

> Anyone familiar with C++ will instantly understand that compiling it is a complicated affair.

> Additionally CUDA allows, to a large degree, mixing CPU code and GPU code. What does all this complexity mean for ZLUDA? Absolutely nothing

> Since an application can dynamically link to either Driver API or Runtime API, it would seem that ZLUDA needs to provide both. In reality very few applications dynamically link to Runtime API. For the vast majority of applications it's sufficient to provide Driver API for dynamic (runtime) linking.

CUDA is huge and nvidia spent a ton in a lot of "dead end" use cases optimizing it. There have been experiments with CUDA translation layers with decent performance[1]. There are two things that most projects hit:

1. The CUDA API is huge; I'm sure Intel/AMD will focus on what they need to implement pytorch and ignore every other use case ensuring that CUDA always has the leg up in any new frontier

2. Nvidia actually cares about developer experience. The most prominent example is Geohotz with tinygrad - where AMD examples didn't even work or had glaring compiler bugs. You will find nvidia engineer in github issues for CUDA projects. Intel/AMD hasn't made that level of investment and thats important because GPUs tend to be more fickle than CPUs.

[1] https://github.com/vosen/ZLUDA

> I don't think you understand just how insanely difficult it is to break into that market.

You're right, I have no clue nor have I ever tried myself.

> Even with apple money or something like that, it's a losing prospect because in the time it'll take you to get up and off the ground (which is FOREVER) your competition will crush you.

This I find hard to believe, do you have a source or reference for that claim? Companies with that amount of cash are hardly going to be crushed by competition be it direct or indirect. Anyway, I'm talking more about the Intels and AMDs of this world.

We have very lacklustre efforts from players I won't name with their Zluda library (https://github.com/vosen/ZLUDA) which I got REALLY excited about, until I read the README.txt. Four contributors, last commit early 2021.

Why, oh why, is it this bad?

This is how murex works too https://github.com/lmorg/murex/blob/master/config/defaults/p...

I agree. I’ve written about this before but this is what murex (1) does. It reimplements some of coreutils where there are benefits in doing so (eg sed, grep etc -like parsing of lists that are in formats other than flat lines of text. Such as JSON arrays)

Mutex does this by having these utilities named slightly different to their POSIX counterparts. So you can use all of the existing CLI tools completely but additionally have a bunch of new stuff too.

Far too many alt shells these days try to replace coreutils and that just creates friction in my opinion.

1. https://murex.rocks

This is exactly what Murex shell does. It has lots of builtin tools for querying structured data (of varying formats) but also supports POSIX pipes for using existing tools like `jq` et al seamlessly too.

https://murex.rocks

Stable is a problem because a lot of these shells don’t offer any guarantees for breaking changes.

My own shell, https://github.com/lmorg/murex is committed to backwards compatibility but even here, there are occasional changes made that might break backwards compatibility. Though I do push back on such changes as much as possible, to the extent that most of my scripts from 5 years ago still run unmodified.

This is similar to how my shell works. It still just passes bytes around but additionally passes information about how those bytes could be interpreted. A schema if you will. So it works as cleanly with POSIX / GNU / et al tools as it does with fancy JSON, YAML, CSV and other document formats.

It basically sits somewhere between Powershell and Bash: typed pipelines like Powershell but without sacrificing familiarity with all the CLI commands you already use day in and day out.

https://github.com/lmorg/murex

As an aside, I’m about to drop a massive update in the next few days that will make the shell even more intuitive to use.