NVIDIA CUDA Can Now Directly Run On AMD GPUs Using The “SCALE” Toolkit

British startup Spectral Compute has unveiled “SCALE,” a GPGPU toolchain that allows NVIDIA’s CUDA to function seamlessly on AMD’s GPUs.

NVIDIA’s CUDA Can Now Directly Function With Non-NVIDIA GPUs Such As AMD’s Without The Need For Code Porting, Courtesy of SCALE

Well, it looks like the industry has been able to break NVIDIA’s software stack dominance, so they are now looking for ways to remove the “exclusivity” status through various means. We previously saw the emergence of ZLUDA, an open-source porting project that allowed CUDA libraries to work with AMD’s ROCm, ultimately supporting Team Red’s GPUs. A new competitor has emerged on the scene, the SCALE, which allows AMD’s consumers to leverage the capabilities of NVIDIA’s CUDA to create a high-end “hybrid” model.

We believe that it should be possible to write code once, and build/run it on any hardware platform. This has been a reality for CPU code for many years, so why not GPUs? We set out to directly solve this problem by bridging the compatibility gap between the popular CUDA programming language and other hardware vendors.

One codebase, multiple vendors.

– Spectral Compute’s CEO, Michael Sondergaard

Spectral Compute’s CEO, Michael Sondergaard, believes that GPUs should have an open-source environment, similar to modern-day CPUs, and that interconnectivity should exist among various platforms. He believes that SCALE acts as a bridge for the compatibility gap between CUDA and other hardware vendors, ultimately removing the limits that exist in the markets. According to Michael, SCALE is a GPGPU toolkit, similar to NVIDIA’s CUDA toolkit, which uses binaries for non-NVIDIA GPUs while compiling CUDA code, ultimately removing the need for a translation layer.

SCALE has been in development for seven years, according to Spectral Compute, and it doesn’t rely on NVIDIA’s code but builds its CUDA-compatible toolchain, which makes SCALE highly adaptable amongst multiple platforms, such as AMD’s RDNA GPUs. The resource avoids code porting and allows developers to work with a single version of their codebase since SCALE eliminates the need to work with other languages, as it’s source-compatible with CUDA.

Well, with the implementation of SCALE, it’s apparent that the status of NVIDIA’s CUDA will change from being exclusive to relatively widely available. However, it’s important to note that SCALE itself isn’t open-source; users can access it through a free software license. Spectral Compute says that they have tested the software in multiple applications, such as Blender, Llama-cpp, XGboost, FAISS, GOMC, STDGPU, Hashcat, and NVIDIA Thrust, employing AMD’s RDNA 3 and RDNA 2 architectures.

NVIDIA has shown some resentment against certain resources that allow CUDA to run on external components, given that Team Green previously listed a warning in their EULA against platforms like SCALE. CUDA has played a huge role in NVIDIA’s dominance over the AI markets, and the firm won’t let the software lose its exclusivity status easily.