5x+ Faster Deep Learning at Scale
Train and Control Multiple Models Simultaneously
For Any Data or Model Size
Why RapidFire
Agile Experiments. Rapid Results.
Hyperparallelized
Train many model configurations at once
Real-Time Control
Kill what doesn’t work, clone what does
Optimized Environment
Maximize GPU utilization, faster time to accuracy
Scale Out of the Box
Across any model and data sizes
Simple Setup
No MLOps friction, use API from a notebook
Our Technology
What RapidFire Does
Multi-Dimensional Parallelism
RapidFire AI features a patent-pending innovative hybrid-parallel distributed execution engine that we call interdimensional parallelism to scale workloads automatically on a cluster, improve GPU utilization, and reduce runtimes.
Agile DL Development Environment
Gain full visibility and control over the DL process and dramatically reduce time to accuracy.
- Compare running models
- Remove underperforming ones
- Clone, modify, and add new configurations on the fly
Integrates Into Your Stack
Seamlessly integrate with your existing tools and cloud, minimizing disruption and maximizing efficiency.
- Full support for your existing tools (Jupyter, TensorFlow, Hugging Face, Pytorch, etc.)
- Complete visibility and control over deep learning experimentation
- Runs on Kubernetes and drops into your cloud ecosystem seamlessly