CPU vs. GPU?
The assumption for running machine learning models is that if you have a complex model with several parameters to evaluate and you have a short amount of time to get answers (measured in milliseconds), you will need the power of a GPU.
The problem is GPUs are expensive, have been hard to source (recently), and in some deployment scenarios, especially at the edge, are just not an option.
However, we’ve been able to surprise our clients by taking their most demanding NLP or even computer vision models, operationalizing them on standard CPUs, and generating faster inferences on less servers. That’s because we purpose built our runtime engine from the ground up in Rust specifically for machine learning.
Reach out to us if you’re ready to ditch GPUs to run even your boldest models.