Accelerate Model Training with PyTorch 2.X

2

Training Models Faster

In the last chapter, we learned the factors that contribute to increasing the computational burden of the training process. Those factors have a direct influence on the complexity of the training phase and, hence, on the execution time.

Now, it is time to learn how to accelerate this process. In general, we can improve performance by changing something in the software stack or increasing the number of computing resources.

In this chapter, we will start to understand both of these options. Next, we will learn what can be modified in the application and environment layers.

Here is what you will learn as part of this chapter:

• Understanding the approaches to accelerate the training process
• Knowing the layers of the software ...