Case Studies

Meadowrun is a general-purpose tool for running python code in the cloud, and it can be used to accomplish a variety of tasks. Here are a few fully worked examples:

• Using AWS and Hyperscan to Match Regular Expressions on 100GB of Text Uses Meadowrun's run_map to process a (relatively) large dataset.
• Running pytest in the Cloud Uses Meadowrun's run_map to run the pandas tests faster.
• Run Your Own DALL·E Mini (Craiyon) Server on EC2 and How to Run Stable Diffusion on EC2 Uses Meadowrun's support for specifying GPU instances to do inference quickly with large ML models.
• How to Deploy ML Models Using Gravity AI and Meadowrun Uses Meadowrun's support for sidecar containers to use ML models deployed as containers efficiently from batch jobs.