About Paperspace Jobs
The Paperspace Job Runner is designed for users who want to execute code (such as training a deep neural network) on a cluster of GPUs easily and without thinking about the underlying infrastructure.
Jobs were created as part of a larger workflow for artificial intelligence. Some users will generate the data used as the basis of their Job using a virtual machine or a Notebook. Jobs have access to Gradient Storage.
A Job consists of:
- a collection of files (code, resources, etc)
- a docker container (with code dependencies and packages pre-installed)
- a command to execute (i.e. python main.py or nvidia-smi)
Running a Job in Gradient
There are several ways to run a Job in Gradient. You can use our Job Builder, which is a GUI for submitting Jobs, run a Job using the Paperspace CLI, or you can clone a Public Job that was shared with you.
Jobs can be chosen to run on a variety of hardware. Pricing and details for all available options can be found here.