Why do I get RuntimeError CUDA out of memory when training a large model on GPU

Question

I am facing a run time error related to CUDA. Can you tell me why I get RuntimeError: CUDA out of memory when training a large model on GPU?

Answer 1

The RuntimeError: CUDA out of memory occurs when your GPU doesn't have enough memory to store the model, inputs, and intermediate computations. Here's how to resolve it:

• Reduce Batch Size
  • Lower the batch size to reduce memory usage.
• Enable Gradient Accumulation
  • Simulate a larger batch size by splitting it across iterations.
• Use Mixed Precision Training
  • Leverage torch.cuda.amp to minimize memory usage.
• Free Unused Tensors
  • Use torch.cuda.empty_cache() to clear unused memory.
• Model Checkpoints
  • Save GPU memory by not retaining intermediate states.
• Use Smaller Model or Layers
  • Replace heavy layers with lightweight alternatives, e.g., MobileNet instead of ResNet.

Here is the code snippet you can refer to, explaining the following steps:

Hence, these techniques can be applied to manage GPU memory efficiently.