You can run Nvidia CUDA applications natively on Radeon GPUs thanks to ZLUDA, the open-source project that AMD once funded

pcgamer.com:

You don't need to be a professional content creator or an expert in data analysis to know that when it comes to GPUs for these roles, one manufacturer dominates the market: Nvidia. That's almost entirely down to CUDA, a programming platform that's been around for years. AMD has its own system called ROCm but it's nowhere near as popular. Well, thanks to the tireless efforts and work of one person, you can now enjoy all the benefits of CUDA applications on a Radeon graphics card, without changing a single line of code.

The work in question is called ZLUDA and the person is Andrzej Janik. As explained by Phoronix, he first created the system while working at Intel and it was used to permit Intel GPUs to run CUDA applications. After leaving that company, he was then contracted by AMD to do the same thing with its ROCm platform but the chip giant ultimately shelved the whole project after a few years.

However, there was a nice ending to it all, as Janik was contractually permitted to continue the work as an open-source project. And that's where it's all at right now (you can grab it off Github) and Phoronix tested the latest version of ZLUDA on a ROCm platform, using the classic CUDA-based benchmark Blender (as shown at the top of this story).

And it works really well. For example, in the Classroom benchmark for Blender, it took 20.89 seconds for a Radeon RX 7900 XTX to render the scene using the standard Radeon HIP software platform, where using ZLUDA (with Blender running in CUDA mode), the render time dropped a little down to 18.44 seconds.

While a 12% reduction in processing time doesn't sound a lot, the fact that this was achieved simply by using a software layer to convert everything is really impressive. No part of Blender's code needed to be altered to make this happen and ZLUDA has the potential to open up the compute and content creation market more for AMD's GPUs.

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