Roblox Guest Blog: Fast and Efficient Online Model Serving
Younes Abouelnagah, a Principal ML Engineer at Roblox, shares how his team scaled their online NLP ML model inference on CPU machines and reduced latency using Ray, a distributed computing framework for Python. The blog post details the process of scaling up and out, reducing latency and CPU usage while maintaining civility on the platform by running user-generated content through multiple models. It highlights key learnings in using Ray Core to scale the serving of ML models with very low latency requirements, including setting up a dedicated Ray cluster for improved performance and efficiency.
Company
Anyscale
Date published
Sept. 19, 2024
Author(s)
Younes Abouelnagah
Word count
2925
Language
English
Hacker News points
None found.