🛠️ Fixing GPU Invisibility – CUDA 12.6 Upgrade Guide
If your system isn't using the GPU for TensorFlow workloads even though the hardware is installed and drivers are up to date, you're likely hitting a compatibility wall between your current CUDA version and TensorFlow.
This situation led to zero GPU memory usage, nvidia-smi errors, and full CPU fallback during training.
The attached .md file walks you through upgrading from CUDA 11.8 to 12.6, setting up the environment, and confirming TensorFlow is actually using the GPU. This resolved the issue on our end and restored full GPU acceleration.
Use this as a step-by-step fix if you're running into similar GPU detection problems.
This situation led to zero GPU memory usage, nvidia-smi errors, and full CPU fallback during training.
The attached .md file walks you through upgrading from CUDA 11.8 to 12.6, setting up the environment, and confirming TensorFlow is actually using the GPU. This resolved the issue on our end and restored full GPU acceleration.
Use this as a step-by-step fix if you're running into similar GPU detection problems.
