All articles tagged with #zluda
ZLUDA has released version 6-preview.48, now supporting CUDA 13.1, enabling unmodified CUDA applications to run on non-NVIDIA GPUs, with a focus on AI workloads and broader hardware compatibility.
ZLUDA, a project funded by AMD, enables unmodified CUDA code to run on AMD Radeon GPUs, allowing native CUDA applications to run on AMD hardware with near-native performance. Despite AMD discontinuing its support for the project, ZLUDA has been released as open-source software. While ZLUDA cannot run Nvidia Optix code, it has shown improved performance over AMD's Radeon HIP code in various applications. The developer plans to continue working on ZLUDA, focusing on personal interests without financial backing from AMD.
AMD's ROCm now indirectly supports NVIDIA CUDA libraries through the open-source ZLUDA project, allowing AMD GPU owners to run CUDA apps within ROCm without code adaptation. ZLUDA, originally designed for NVIDIA CUDA support on Intel GPUs, has been successfully tested with AMD's Radeon GPUs on ROCm, enabling performance on par with NVIDIA for rendering tasks. While native CUDA support on Radeon GPUs remains unavailable, the potential of ZLUDA in bridging ROCm and CUDA stacks for AI applications is promising, with the developer exploring NVIDIA's upscaling capabilities on RDNA GPUs.
AMD quietly funded a project to create a drop-in replacement for CUDA on AMD GPUs, allowing many CUDA applications to run on the ROCm stack without modification. The project, based on the ZLUDA implementation, was developed by Andrzej Janik and is now open-source, dual-licensed under Apache 2.0 or MIT. While it's a promising solution, it's not without limitations, such as incomplete NVIDIA OptiX support. The implementation, leveraging the Rust programming language, has been tested successfully, and the exposed device name for Radeon GPUs via CUDA will be updated as part of the open-sourcing.