Compute resource options for Deep Learning experiments
When you run a Deep Learning experiment in a project, you choose the type, size, and power of the hardware configuration for your experiment.
Default hardware configurations
Choose from a default hardware configuration for your Deep Learning experiment.
Capacity type | Capacity units per hour |
---|---|
1 (one) NVIDIA K80 GPU | 2 |
1 (one) NVIDIA V100 GPU | 8 |
The runtimes for Deep Learning stop automatically when processing is complete.
Compute usage in projects
Deep Learning experiments consume compute resources as CUH from the Watson Machine Learning service.
You can monitor the total monthly amount of CUH consumption for the Watson Machine Learning service on the Environments page.
Learn more
- AutoAI
- Watson Machine Learning service
- Compute resource options for assets and deployments in spaces
- Monitoring account resource usage
Parent topic: Choosing compute resources for tools