2 min read

An open-source libre GPU project is under the works by Luke Kenneth Casson Leighton. He is the hardware engineer who developed the EOMA68, an earth-friendly computer.

The project already has access to $250k USD in funding. The basic idea for this “libre GPU” is to use a RISC-V processor.

The GPU will be mostly software-based. It will leverage the LLVM compiler infrastructure and utilize a software-based Vulkan renderer to emit code and run on the RISC-V processor. The Vulkan implementation will be used for writing in the Rust programming language.

The project’s current road-map has details only on the software side of figuring out the RISC-V LLVM back-end state. Work is being done on writing a user-space graphics driver, implementing the necessary bits for the proposed RISC-V extensions like “Simple-V”. While doing this, they will start figuring out the hardware design and the rest of the project. The road-map is quite simplified for the arduous task at hand.

The website notes: “Once you’ve been through the “Extension Proposal Process” with Simple-V, it need never be done again, not for one single parallel / vector / SIMD instruction, ever again.

This process will include creating a fixed-function 3D “FP to ARGB” custom instruction, a custom extension with special 3D pipelines. With Simple-V, there is no need to worry about about how those operations would be parallelised. This is not a new concept, it’s borrowed directly from videocore-iv. videocore-iv calls it “virtual parallelism”.

It’s an enormous effort on both the software and hardware ends to come up with a RISC-V, Rust, LLVM, and Vulkan open-source combined project. It is difficult even with the funding considering it is a software based GPU. It is worth noting that the EOMA68 project was started by Luke in 2016 and raised over $227k USD from crowdfunding participants and hasn’t shipped yet.

To know more about this project, visit the libre risc-v website.

Read next

NVIDIA leads the AI hardware race. But which of its GPUs should you use for deep learning?

AMD ROCm GPUs now support TensorFlow v1.8, a major milestone for AMD’s deep learning plans

PyTorch-based HyperLearn Statsmodels aims to implement a faster and leaner GPU Sklearn


Subscribe to the weekly Packt Hub newsletter. We'll send you the results of our AI Now Survey, featuring data and insights from across the tech landscape.

* indicates required