# 1. PIN the NVIDIA repository to prioritize it over default OS packages wget https://nvidia.com sudo mv cuda-ubuntu2204.pin /etc/apt/preferences.d/cuda-repository-pin-600 # 2. Fetch the repository keys and add the repository sudo apt-key adv --fetch-keys https://nvidia.com sudo add-apt-repository "deb https://nvidia.com /" # 3. Update package lists and install CUDA 12.6 sudo apt-get update sudo apt-get -y install cuda-toolkit-12-6 Use code with caution. Environment Configuration
If your application handles matrix mathematics or deep learning layers, ensure your data structures are aligned to leverage Tensor Cores. CUDA 12.6 includes built-in optimizations for formats, which drastically reduce memory bandwidth pressure and double the compute throughput compared to FP16 execution on Hopper and Blackwell architectures. 3. Minimize Global Memory Bottlenecks
While CUDA 12.6 is a strong choice, it's not the only option.
