tinygrad VS cerbos

Not sure if I completely understand what "Ryzen AI" does, but Tinygrad for example has some limited support for RDNA3[0]. It isn't quite there yet in matters of performance though, as you can read in the comments of that file.

There's also a small tutorial by AMD on how to use the WMMA intrinsic[1] using AMD's hipcc[2] compiler. Documentation is sparse kinda sparse, but the instruction set is not huge. The RDNA3 ISA guide[3] might also be helpful (and only a fraction of the pages are relevant.)

0. https://github.com/tinygrad/tinygrad/blob/master/extra/gemm/...

1. https://gpuopen.com/learn/wmma_on_rdna3/

2. https://github.com/ROCm/HIPCC

3. https://www.amd.com/content/dam/amd/en/documents/radeon-tech...

This post describes how I added automatic differentiation to Tensorken. Tensorken is my attempt to build a fully featured yet easy-to-understand and hackable implementation of a deep learning library in Rust. It takes inspiration from the likes of PyTorch, Tinygrad, and JAX.

what do you think about tinygrad? I think its a good example of growing and well written, (partially) well documented library with many close to reference implementations

The idea of model architecture making fast hardware design easier is what makes https://github.com/tinygrad/tinygrad so interesting.

🌟 Support on GitHub Website: https://tinygrad.org/

Before we begin, make sure you have TinyGrad and the required dependencies installed. You can find the installation instructions here.

Try to get something like tinygrad[1] running locally, that way you can tweak things a bit run it again and see how it performs. While doing this you'll pick up most of the concepts and get a feeling of how things work. Also, take a look at projects like llama.cpp[2], you don't have to fully understand what's going on here, tho.

You may need some intermediate knowledge of linear algebra and this thing called "data science" nowadays, which is pretty much knowing how to mangle data and visualize it.

Try creating a small model on your own, it doesn't have to be super fancy just make sure it does something you want it to do. And then ... you'll probably could go on your own then.

1: https://github.com/tinygrad/tinygrad

2: https://github.com/ggerganov/llama.cpp

Here, Cerbos comes into the picture.

In this tutorial you will learn how to use Cerbos to add fine-grained access control to any Nuxt web application, simplifying authorization as a result.

In my work with Cerbos, I apply the lessons learned from Da Vinci to tackle authorization challenges. Our approach is to create solutions where functionality seamlessly integrates with developer experience. Constantly iterating and viewing the tools through the users' lens, helps ensure that our access control solutions are robust and dev-friendly.

You may already know of our open source solution - Cerbos Policy Decision Point (PDP); a devtool which helps developers enforce access control over different parts of their software. If you need to learn more about Cerbos in general, we strongly recommend checking out the website and the docs.

GitHub: https://github.com/cerbos/cerbos URL: https://cerbos.dev

Cerbos Hub is a managed service offering for the open source authorization product, Cerbos.

Hello fellow devs! I'm with Cerbos (https://cerbos.dev/), a tool designed to manage who can do what in your software applications.