Get Started with Intel® Extension for PyTorch* on GPU

If you’re looking to accelerate your PyTorch* workflows on GPU, the Intel® Extension for PyTorch* can help you achieve significant performance improvements. In this article, we’ll walk you through the steps to get started with this extension and take advantage of its capabilities.

Step 1: Install PyTorch*

Before you can use the Intel® Extension for PyTorch*, you’ll need to have PyTorch* installed on your system. You can find installation instructions on the PyTorch* website.

Step 2: Install the Intel® Extension for PyTorch*

Once you have PyTorch* installed, you can install the Intel® Extension for PyTorch* using the following command:

pip install torch-ipt

Step 3: Use the Extension with GPU

Now that you have the extension installed, you can start using it with GPU. Simply import the extension in your Python code and specify the device as “gpu” when creating tensors or performing operations:


import torch
import torch_ipt

# Perform operations on GPU
y = x * 2


Step 4: Measure Performance

After using the extension with GPU, you can measure the performance improvements compared to using PyTorch* without the extension. You can use tools like Intel® VTune™ Profiler to analyze the performance and make further optimizations.

Conclusion

By following these steps, you can quickly get started with the Intel® Extension for PyTorch* on GPU and unlock its performance benefits for your PyTorch* workflows. Experiment with different models and workloads to see the full potential of this extension.

For more information and detailed documentation, be sure to visit the Intel® Software website.