How to maximize GPU utilization by finding the right batch size

Introduction

Oftentimes, one of the most asked questions by new data scientists and ML engineers is whether their deep learning training processes are running optimally. In this guide, we will learn how to diagnose and fix deep learning performance issues regardless of whether we are working on one or numerous machines. This is to help us understand how to make practical and effective use of the wide variety of available cloud GPUs.

We will start by understanding what GPU utilization is, and we’ll finish by discussing the optimal batch size for maximum GPU utilization.

Note: This guide assumes we have a basic understanding of the Linux operating system and the Python programming language. The latest Linux distros come with Ubuntu pre-installed, so we can go ahead and install pip and conda, as we will use them here.