Train and benchmark AI workloads with DeepSpeed on Google Cloud C4A Axion VMs

About this Learning Path

Who is this for?

This is an introductory topic for DevOps engineers, ML engineers, and software developers who want to run AI training and benchmarking workloads using PyTorch and DeepSpeed on SUSE Linux Enterprise Server (SLES) Arm64, validate CPU-based neural network execution, and benchmark AI performance on Arm processors.

What will you learn?

Upon completion of this Learning Path, you will be able to:

• Install and configure PyTorch and DeepSpeed on Arm-based Google Cloud C4A Axion VMs
• Create and execute neural network training workloads using PyTorch
• Benchmark CPU-based AI workloads on Arm64 processors
• Validate scalable AI execution and workload performance on Google Axion Arm VMs

Prerequisites

Before starting, you will need the following:

• A Google Cloud Platform (GCP) account with billing enabled
• Basic familiarity with Python and machine learning concepts