librapid VS ROCm

In addition to all of these changes, I used LibRapid and Surge to write a simple Flappy Bird genetic AI as a proof of concept. The code runs well on all platforms and can simulate over 20,000 birds without too much trouble. If you want to check it out, here's the GitHub page: https://github.com/Pencilcaseman/FlappyBirdAI

LibRapid: https://github.com/LibRapid/librapid Documentation: https://librapid.readthedocs.io/en/latest/

tl;dr

I'm developing an incredibly fast library for arrays and mathematics, and I've implemented a few new features and made some improvements. I'd love for you to check it out!

Links:

GitHub: https://github.com/LibRapid/librapid/

Documentation: https://librapid.readthedocs.io/en/latest/

Discord: https://discord.com/invite/cGxTFTgCAC

Hey everyone!

I am the lead developer of LibRapid (https://github.com/LibRapid/librapid/), a high-performance C++ library for array manipulation and mathematics. I've been working hard to bring you some significant updates and improvements to the library, and I'm excited to share them with you! These changes will make it even easier for you to use LibRapid in your projects and enable you to do even more with it.

Here's a rundown of the most notable changes:

CUDA improvements: We've fixed several bugs and made performance enhancements for the CUDA implementation.

Expanded support for BLAS libraries: LibRapid now has greater support for BLAS libraries, including Intel's MKL.

Test suite and documentation updates: We've updated our test suite and overhauled the documentation for clarity and ease of use.

Matrix Transposition: The library now supports matrix transposition with highly optimised, architecture-specific SIMD implementations and generic implementations for non-trivial types.

New math utility functions: We've added various new utility functions for complex numbers, multi-precision arithmetic, and more.

Matrix transposition and SIMD: LibRapid now supports matrix transposition and SIMD matrix transpose for SSE and AVX2, improving performance and memory alignment.

Random number generation: We've started implementing a new random number generation library.

Fast Fourier Transforms: LibRapid now supports fast Fourier transforms on 1D arrays, with more features coming soon! (We're using FFTW, so you can be sure you are getting the best possible performance)

Array BLAS operations: We're implementing BLAS functions that operate on our high-level array type, allowing you to access the high-performace, specialised routines without the tedious interface. (Many operations already use BLAS functions internally)

You can find more detailed information about the library and example code and usage guides in the documentation (https://librapid.readthedocs.io/en/latest/).

We're always looking for feedback and contributions, so if you're interested in using LibRapid or helping out, please feel free to create a pull request or contact us via our Discord Server (https://discord.com/invite/cGxTFTgCAC). I'm putting in a lot of effort to enhance LibRapid and would greatly appreciate any sponsorships to support my work. If you or your organisation is interested in sponsoring LibRapid, please feel free to reach out to me to discuss your ideas.

We hope you enjoy the latest updates to LibRapid, and look forward to seeing what you build with it!

I am the lead developer of LibRapid, a high-performance C++ library for array manipulation and mathematics. I've been working hard to bring you some significant updates and improvements to the library, and I'm excited to share them with you! These changes will make it even easier for you to use LibRapid in your projects and enable you to do even more with it.

LibRapid is a high-performance C++ library focusing primarily on linear algebra operations, though also supporting a wide range of classes, functions and utilities such as vectors, complex numbers and more.

LibRapid GitHub Repository

Probably LibRapid, which is my high-performance array library for C++. Nothing huge but I'm quite proud of the features it currently implements (given time restrictions and rewrites) and it is, in many cases, faster than things like Eigen and XTensor :)

Yep, did exactly that. IMO he threw a fit, even though AMD was working with him squashing bugs. https://github.com/RadeonOpenCompute/ROCm/issues/2198#issuec...

Ok, I wonder what's wrong. maybe it's this? https://stackoverflow.com/questions/4959621/error-1001-in-cl...

Nope. Anything about this on the arch wiki? Nope

This bug report[2] from 2021? Maybe I need to update my groups.

[2]: https://github.com/RadeonOpenCompute/ROCm/issues/1411

    $ ls -la /dev/kfd

HMM is, I believe, a Linux feature.

AMD added HMM support in ROCm 5.0 according to this: https://github.com/RadeonOpenCompute/ROCm/blob/develop/CHANG...

Woot AMD now supports APU? I sold my notebook as i hit a wall when trying rocm [1] Is there a list oft Wirkung apu's ?

[1] https://github.com/RadeonOpenCompute/ROCm/issues/1587

Last I heard he's abandoned working with AMD products.

https://github.com/RadeonOpenCompute/ROCm/issues/2198#issuec...

They're talking about the meltdown he had on stream [1] (in front of the mentioned pirate flag), that ended with him saying he'd stop using AMD hardware [2]. He recanted this two weeks after talking with AMD [3].

Maybe he'll succeed, but this definitely doesn't scream stability to me. I'd be wary of investing money into his ventures (but then I'm not a VC, so what do I know).

[1] https://www.youtube.com/watch?v=Mr0rWJhv9jU

[2] https://github.com/RadeonOpenCompute/ROCm/issues/2198#issuec...

[3] https://twitter.com/realGeorgeHotz/status/166980346408248934...

As for rocm support on consumer devices, AMD wont even clarify what devices are supported. https://github.com/RadeonOpenCompute/ROCm/pull/1738

He flamed out, then is back after Lisa Su called him (lmao)

https://geohot.github.io/blog/jekyll/update/2023/05/24/the-t...

https://www.youtube.com/watch?v=Mr0rWJhv9jU

https://github.com/RadeonOpenCompute/ROCm/issues/2198#issuec...

https://geohot.github.io/blog/jekyll/update/2023/06/07/a-div...

On a personal level that youtube doesn't make him come off looking that good... like people are trying to get patches to him and generally soothe him/damage control and he's just being a bit of a manchild. And it sounds like that's the general course of events around a lot of his "efforts".

On the other hand he's not wrong either, having this private build inside AMD and not even validating official, supported configurations for the officially supported non-private builds they show to the world isn't a good look, and that's just the very start of the problems around ROCm. AMD's OpenCL runtime was never stable or good either and every experience I've heard with it was "we spent so much time fighting AMD-specific runtime bugs and specs jank that what we ended up with was essentially vendor-proprietary anyway".

On the other other hand, it sounds like AMD know this is a mess and has some big stability/maturity improvements in the pipeline. It seems clear from some of the smoke coming out of the building that they're cooking on more general ROCm support for RDNA cards, and generally working to patch the maturity and stability issues he's talking about. I hate the "wait for drivers/new software release bro it's gonna fix everything" that surrounds AMD products but in this case I'm at least hopeful they seem to understand the problem, even if it's completely absurdly late.

Some of what he was viewing as "the process happening in secret" was likely people doing rush patches on the latest build to accommodate him, and he comes off as berating them over it. Again, like, that stream just comes off as "mercurial manchild" not coding genius. And everyone knew the driver situation is bad, that's why there's notionally alpha for him to realize here in the first place. He's bumping into moneymakers, and getting mad about it.

I tried to train another model using InceptionResNetV2 and the same issues happens. Also, this happens even using the model.predict() method if using the GPU. Probably this is an issue related to the AMD Radeon RX 6700 XT or some mine misconfiguration. System Inormation: ArchLinux 6.1.32-1-lts - AMD Radeon RX 6700 XT - gfx1031 Opened issues: - https://github.com/RadeonOpenCompute/ROCm/issues/2250 - https://github.com/ROCmSoftwarePlatform/tensorflow-upstream/issues/2125