Using Specialized Libraries
Nobody needs to do all things by themselves. Neither does PyTorch! We already know PyTorch is one of the most powerful frameworks for building deep learning models. However, as many other tasks are involved in the model-building process, PyTorch relies on specialized libraries and tools to get the job done.
In this chapter, we will learn how to install, use, and configure libraries to optimize CPU-based training and multithreading.
More important than learning the technical nuances presented in this chapter is catching the message it brings: we can improve performance by using and configuring third-party libraries specialized in tasks that PyTorch relies on. In this sense, we can search for many other options than the ones described in this book.
Here is what you will learn as part of this chapter:
- Understanding the concept of multithreading with OpenMP
- Learning how to use and configure OpenMP
- Understanding IPEX – an API for...
