Mar 05, 2024 23:00:00

NVIDIA bans CUDA from running on other hardware

It turns out that the software license agreement (EULA) for

CUDA , which NVIDIA provides as a computing platform for GPUs, prohibits its execution on hardware platforms other than NVIDIA through the translation layer. I did. This clause was originally included in the online version of the EULA published on NVIDIA's website, but it is now also included in the installed CUDA documentation.

License Agreement for NVIDIA Software Development Kits — EULA
https://docs.nvidia.com/cuda/eula/index.html

Nvidia bans using translation layers for CUDA software — previously the prohibition was only listed in the online EULA, now included in installed files [Updated] | Tom's Hardware

https://www.tomshardware.com/pc-components/gpus/nvidia-bans-using-translation-layers-for-cuda-software-to-run-on-other-chips-new-restriction-apparently-targets- zluda-and-some-chinese-gpu-makers

A lone developer just open sourced a tool that could bring an end to Nvidia's AI hegemony — AMD financed it for months but abruptly ended its support. Nobody knows why | TechRadar : r/StableDiffusion
https://www.reddit.com/r/StableDiffusion/comments/1ayfb66/comment/krx40h7/

The clause in question is subsection 8 of Article 1, Section 2, 'Restrictions' of the EULA.

The original text is as follows.

You may not reverse engineer, decompile or disassemble any portion of the output generated using SDK elements for the purpose of translating such output artifacts to target a non-NVIDIA platform.

'You may not reverse engineer, decompile, or disassemble any portion of the output produced using the SDK elements for the purpose of converting them into output artifacts that target a platform other than NVIDIA.' ”.

According to the news site Tom's Hardware, this wording is not included in the documentation for CUDA versions 11.4 and 11.5, and appears to have been included from version 11.6.

CUDA is a computing platform released by NVIDIA for its own GPUs, and achieves high efficiency when combined with NVIDIA hardware. However, some users run CUDA on platforms that compete with NVIDIA.

According to Tom's Hardware, there are two ways to use CUDA on other platforms: ``recompiling the code'' and ``using a translation layer.'' Using a translation layer like `` ZLUDA '' is particularly easy. That's it.

Multiple GPU manufacturers in China have admitted to running CUDA.

For example, Denglin Technology is developing a processor that features a 'computer architecture that is compatible with programming models such as CUDA and OpenCL .' Since reverse engineering NVIDIA's GPU is difficult, Tom's Hardware speculates that it is dealing with some kind of translation layer.

It is also known that Moore Threads handles a translation tool called ``MUSIFY'' designed to run CUDA code on GPU. In addition, it is not known whether MUSIFY belongs to the translation layer.

Tom's Hardware notes that it is unclear whether NVIDIA's ban on the use of CUDA on other platforms is a response to the movements of these Chinese manufacturers or a proactive response to future development.

However, Tom's Hardware predicts that the use of translation layers will be the driving force behind NVIDIA's move to ban it, as it appears to threaten NVIDIA's hegemony in the high-speed computing field, especially in AI applications.