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ZLUDA: Run CUDA Applications on Non-NVIDIA GPUs with Near-Native Performance
ZLUDA is an innovative open-source project providing a drop-in replacement for CUDA, enabling users to run CUDA applications on non-NVIDIA GPUs. Written in Rust, it aims to deliver near-native performance, significantly expanding hardware compatibility for CUDA-dependent software. This project offers a powerful solution for greater flexibility in GPU computing environments.
CuPy: NumPy & SciPy for GPU-Accelerated Computing in Python
CuPy is a powerful Python array library that provides NumPy and SciPy-compatible interfaces for GPU-accelerated computing. It enables users to seamlessly run existing numerical code on NVIDIA CUDA or AMD ROCm platforms with minimal changes. This tool also offers direct access to low-level CUDA features for advanced performance tuning and high-performance scientific computing.