Some Software Best Practices

To help you get started with available computing resources and Software Engineering best practices, we’ve collected some resources.

First and foremost, AI can be compute-intensive! We highly recommend using the University’s High Performance Computing (HPC) cluster when you need computing power. You can find some getting-started instructions:

• HPC Documentation
• HPC Access Application Form
• Usage allocations

The Bioinformatics department have created a comprehensive introduction to using the HPC.

Managing experimentation can become cumbersome as you start to use different models and datasets. Weights & Biases or MLflow are platforms that allow you to track ML experiments. As you move to using AI in your own domains, these platforms can make your life easier:

• https://mlflow.org
• https://wandb.ai/site

Version control is a key part of the workflow for anyone writing software, to manage and track the code changes that you’re making. GitHub is a widely used version control tool, and their documentation can help you get started:

• GitHub Documentation