Accelerate Model Training With Pytorch 2x Build More Accurate Models By Boosting The Model Training Process 1st Edition Maicon Melo Alves by Maicon Melo Alves instant download after payment.

Key Features

Reduce the model-building time by applying optimization techniques and approaches

Harness the computing power of multiple devices and machines to boost the training process

Focus on model quality by quickly evaluating different model configurations

Purchase of the print or Kindle book includes a free PDF eBook

Book Description

Penned by an expert in High-Performance Computing (HPC) with over 25 years of experience, this book is your guide to enhancing the performance of model training using PyTorch, one of the most widely adopted machine learning frameworks.

You’ll start by understanding how model complexity impacts training time before discovering distinct levels of performance tuning to expedite the training process. 

You’ll also learn how to use a new PyTorch feature to compile the model and train it faster, alongside learning how to benefit from specialized libraries to optimize the training process on the CPU. 

As you progress, you’ll gain insights into building an efficient data pipeline to keep accelerators occupied during the entire training execution and explore strategies for reducing model complexity and adopting mixed precision to minimize computing time and memory consumption. 

The book will get you acquainted with distributed training and show you how to use PyTorch to harness the computing power of multicore systems and multi-GPU environments available on single or multiple machines.